http://2013.igem.org/wiki/index.php?title=Special:Contributions/Marguerite&feed=atom&limit=50&target=Marguerite&year=&month=2013.igem.org - User contributions [en]2024-03-28T20:02:32ZFrom 2013.igem.orgMediaWiki 1.16.5http://2013.igem.org/Team:Paris_BettencourtTeam:Paris Bettencourt2013-11-06T14:06:29Z<p>Marguerite: </p>
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Overview" title="Project Overview"><br />
<div class="subpanel1"><br />
<div style="position:relative;bottom:0px"><br />
<div class="cont"><p style="font-size:32px;line-height:34px;">FIGHT TUBERCULOSIS WITH MODERN WEAPONS </p></div><br />
<div class="cont"><br />
<p style="font-size:26px;"><br />
Tuberculosis (TB) is an infectious disease caused by <i>Mycobacterium tuberculosis</i> (Mtb) that affects nearly two billion people around the world. On this website we present four new ways to use the power of synthetic biology in the fight against TB: from gene detection, to drug targeting, to infiltrating macrophages, to sabotaging the synthesis of proteins. Hover over these panels to see the project overview.<br />
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<p style="font-size:26px;">A biosensor that detects the presence of sequence specific antibiotic resistance genes.</p><br />
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<p style="font-size:26px;">A safe and specific high-throughput drug screening method that targets essential mycobacterial metabolic proteins.</p><br />
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<p style="font-size:26px;">A phage system with low fitness cost producing sRNA, which inhibits the synthesis of antibiotic resistance proteins.</p><br />
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<p style="font-size:26px;">Infiltrate macrophages with an <i>E.coli</i> producing TDMH, an enzyme that will lyse the Mycobacteria cell wall.</p><br />
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Detect<br />
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Target<br />
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Infiltrate<br />
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Sabotage<br />
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TB Facts<br />
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TB in France<br />
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TB Gallery<br />
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Gender Study<br />
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Technology Transfer<br />
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Collaboration<br />
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SensiGEM<br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/File:PB_frontpagebanner7.pngFile:PB frontpagebanner7.png2013-11-06T14:06:20Z<p>Marguerite: </p>
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<div></div>Margueritehttp://2013.igem.org/Team:Paris_BettencourtTeam:Paris Bettencourt2013-11-06T14:04:05Z<p>Marguerite: </p>
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Overview" title="Project Overview"><br />
<div class="subpanel1"><br />
<div style="position:relative;bottom:0px"><br />
<div class="cont"><p style="font-size:32px;line-height:34px;">FIGHT TUBERCULOSIS WITH MODERN WEAPONS </p></div><br />
<div class="cont"><br />
<p style="font-size:26px;"><br />
Tuberculosis (TB) is an infectious disease caused by <i>Mycobacterium tuberculosis</i> (Mtb) that affects nearly two billion people around the world. On this website we present four new ways to use the power of synthetic biology in the fight against TB: from gene detection, to drug targeting, to infiltrating macrophages, to sabotaging the synthesis of proteins. Hover over these panels to see the project overview.<br />
</p><br />
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<div id="psdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">A biosensor that detects the presence of sequence specific antibiotic resistance genes.</p><br />
</div><br />
</div><br />
<div id="dsdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">A safe and specific high-throughput drug screening method that targets essential mycobacterial metabolic proteins.</p><br />
</div> <br />
</div><br />
<div id="thdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">A phage system with low fitness cost producing sRNA, which inhibits the synthesis of antibiotic resistance proteins.</p><br />
</div><br />
</div><br />
<div id="tcdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">Infiltrate macrophages with an <i>E.coli</i> producing TDMH, an enzyme that will lyse the Mycobacteria cell wall.</p><br />
</div><br />
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Detect<br />
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<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Target<br />
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</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Infiltrate" title="Infiltrate"><br />
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<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/2/21/PB_InfiltrateNarrow.jpg" width="125px" height="500px"/><br />
<div class="titlebox"><br />
<center><img src="https://static.igem.org/mediawiki/2013/6/6c/PB_infiltrate.gif" style="height:60px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Infiltrate<br />
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</div><br />
</a><br />
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<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/4/42/PB_SabotageNarrow.jpg" width="125px" height="500px"/><br />
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<center><img src="https://static.igem.org/mediawiki/2013/8/81/PB_sabotageicone.gif" style="height:60px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Sabotage<br />
</div><br />
</div><br />
</a><br />
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<img width="70px" style="margin-left:80px;margin-right:15px;position:relative;bottom:1px" src="https://static.igem.org/mediawiki/2013/d/d5/PB_handresults.gif"/>Jump to Results<br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/TB_Facts" title="TB Facts"><br />
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<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/f/f9/PB_TBfacts2.png" width="354px" height="156px"/><br />
<div style="position:relative;bottom:148px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/6/69/PB_logoTBfacts.png" style="height:50px;margin-top:10px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
TB Facts<br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/TB_France" title="TB in France"><br />
<div class="subpanel5"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/3/39/PB_TBinFrance.png" width="354px" height="156px"/> <br />
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<center><img src="https://static.igem.org/mediawiki/2013/c/cf/PB_logofrance.png" style="height:50px;margin-top:10px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
TB in France<br />
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<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/2/2f/PB_TBgallery%281%29.png" width="354px" height="156px"/> <br />
<div style="position:relative;bottom:158px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/d/de/PB_logoTBgallery.png" style="height:60px;margin-top:10px;margin-bottom:10px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
TB Gallery<br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Study" title="Gender Study"><br />
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<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/8/8c/Gender.png" width="354px" height="283px"/><br />
<div style="position:relative;bottom:258px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/d/da/PB_logogender.png" style="height:60px;margin-top:10px;margin-bottom:10px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Gender Study<br />
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<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/3/3c/TB_knowledge.png" width="354px" height="283px"/><br />
<div style="position:relative;bottom:258px"> <br />
<center><img src="https://static.igem.org/mediawiki/2013/6/6d/PB_logotransferttechno.png" style="height:60px;margin-top:10px;margin-bottom:10px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Technology Transfer<br />
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</div><br />
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<div style="margin-right:0;width:356px"><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Collaboration" title="Collaboration"><br />
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<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/e/e4/TB_collboration2.png" width="354px" height="283px"/><br />
<div style="position:relative;bottom:258px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/7/75/PB_lofocollaboration.png" style="height:50px;margin-top:15px;margin-bottom:15px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Collaboration<br />
</div><br />
</div><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/SensiGEM" title="SensiGEM"><br />
<div class="subpanel6" style="margin-bottom:0"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/d/d5/TB_senigem.png" width="354px" height="283px"/><br />
<div style="position:relative;bottom:258px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/3/3c/PB_logosenigem.png" style="height:60px;margin-top:10px;margin-bottom:10px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
SensiGEM<br />
</div><br />
</div><br />
</a><br />
</div><br />
</div><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Notes" title="Notebook"><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/File:PB_frontpagebanner6.pngFile:PB frontpagebanner6.png2013-11-06T14:03:52Z<p>Marguerite: </p>
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<div></div>Margueritehttp://2013.igem.org/Team:Paris_BettencourtTeam:Paris Bettencourt2013-11-06T14:02:19Z<p>Marguerite: </p>
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<div class="cont"><p style="font-size:32px;line-height:34px;">FIGHT TUBERCULOSIS WITH MODERN WEAPONS </p></div><br />
<div class="cont"><br />
<p style="font-size:26px;"><br />
Tuberculosis (TB) is an infectious disease caused by <i>Mycobacterium tuberculosis</i> (Mtb) that affects nearly two billion people around the world. On this website we present four new ways to use the power of synthetic biology in the fight against TB: from gene detection, to drug targeting, to infiltrating macrophages, to sabotaging the synthesis of proteins. Hover over these panels to see the project overview.<br />
</p><br />
</div><br />
<div id="psdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">A biosensor that detects the presence of sequence specific antibiotic resistance genes.</p><br />
</div><br />
</div><br />
<div id="dsdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">A safe and specific high-throughput drug screening method that targets essential mycobacterial metabolic proteins.</p><br />
</div> <br />
</div><br />
<div id="thdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">A phage system with low fitness cost producing sRNA, which inhibits the synthesis of antibiotic resistance proteins.</p><br />
</div><br />
</div><br />
<div id="tcdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">Infiltrate macrophages with an <i>E.coli</i> producing TDMH, an enzyme that will lyse the Mycobacteria cell wall.</p><br />
</div><br />
</div><br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Detect" title="Detect"><br />
<div id="pspanel" class="subpanel2" onmouseover="chgtrans(this)"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/a/a8/PB_DetectNarrow.jpg" width="125px" height="500px"/><br />
<div class="titlebox"><br />
<center><img src="https://static.igem.org/mediawiki/2013/0/0b/PB_detecticon.gif" style="height:60px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Detect<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Target" title="Target"><br />
<div id="dspanel" class="subpanel2"><br />
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<center><img src="https://static.igem.org/mediawiki/2013/1/11/PB_TargetIcon.gif" style="height:60px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Target<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Infiltrate" title="Infiltrate"><br />
<div id="tcpanel" class="subpanel2"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/2/21/PB_InfiltrateNarrow.jpg" width="125px" height="500px"/><br />
<div class="titlebox"><br />
<center><img src="https://static.igem.org/mediawiki/2013/6/6c/PB_infiltrate.gif" style="height:60px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Infiltrate<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Sabotage" title="Sabotage"><br />
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<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/4/42/PB_SabotageNarrow.jpg" width="125px" height="500px"/><br />
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<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Sabotage<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Results" title="Results"><br />
<div class="subpanel3" ><br />
<img width="70px" style="margin-left:80px;margin-right:15px;position:relative;bottom:1px" src="https://static.igem.org/mediawiki/2013/d/d5/PB_handresults.gif"/>Jump to Results<br />
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</a><br />
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<div style="clear: both;"></div><br />
<div class="panel" style="background:white;"><br />
<div class="subpanel4"><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/TB_Facts" title="TB Facts"><br />
<div class="subpanel5"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/f/f9/PB_TBfacts2.png" width="354px" height="156px"/><br />
<div style="position:relative;bottom:148px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/6/69/PB_logoTBfacts.png" style="height:50px;margin-top:10px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
TB Facts<br />
</div><br />
</div><br />
</a> <br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/TB_France" title="TB in France"><br />
<div class="subpanel5"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/3/39/PB_TBinFrance.png" width="354px" height="156px"/> <br />
<div style="position:relative;bottom:158px"> <br />
<center><img src="https://static.igem.org/mediawiki/2013/c/cf/PB_logofrance.png" style="height:50px;margin-top:10px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
TB in France<br />
</div> <br />
</div><br />
</a><br />
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<div class="subpanel5" style="margin-bottom:0;height:158px;"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/2/2f/PB_TBgallery%281%29.png" width="354px" height="156px"/> <br />
<div style="position:relative;bottom:158px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/d/de/PB_logoTBgallery.png" style="height:60px;margin-top:10px;margin-bottom:10px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
TB Gallery<br />
</div><br />
</div><br />
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<div class="subpanel4"><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Study" title="Gender Study"><br />
<div class="subpanel7"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/8/8c/Gender.png" width="354px" height="283px"/><br />
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<center><img src="https://static.igem.org/mediawiki/2013/d/da/PB_logogender.png" style="height:60px;margin-top:10px;margin-bottom:10px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Gender Study<br />
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<div class="subpanel9" style="font-size:26px;"><br />
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<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Technology Transfer<br />
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<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Collaboration<br />
</div><br />
</div><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/SensiGEM" title="SensiGEM"><br />
<div class="subpanel6" style="margin-bottom:0"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/d/d5/TB_senigem.png" width="354px" height="283px"/><br />
<div style="position:relative;bottom:258px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/3/3c/PB_logosenigem.png" style="height:60px;margin-top:10px;margin-bottom:10px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
SensiGEM<br />
</div><br />
</div><br />
</a><br />
</div><br />
</div><br />
</div><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/File:PB_frontpagebanner5.pngFile:PB frontpagebanner5.png2013-11-06T14:02:05Z<p>Marguerite: </p>
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<div></div>Margueritehttp://2013.igem.org/Team:Paris_BettencourtTeam:Paris Bettencourt2013-11-06T13:50:12Z<p>Marguerite: </p>
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<div style="position:relative;bottom:0px"><br />
<div class="cont"><p style="font-size:32px;line-height:34px;">FIGHT TUBERCULOSIS WITH MODERN WEAPONS </p></div><br />
<div class="cont"><br />
<p style="font-size:26px;"><br />
Tuberculosis (TB) is an infectious disease caused by <i>Mycobacterium tuberculosis</i> (Mtb) that affects nearly two billion people around the world. On this website we present four new ways to use the power of synthetic biology in the fight against TB: from gene detection, to drug targeting, to infiltrating macrophages, to sabotaging the synthesis of proteins. Hover over these panels to see the project overview.<br />
</p><br />
</div><br />
<div id="psdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">A biosensor that detects the presence of sequence specific antibiotic resistance genes.</p><br />
</div><br />
</div><br />
<div id="dsdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">A safe and specific high-throughput drug screening method that targets essential mycobacterial metabolic proteins.</p><br />
</div> <br />
</div><br />
<div id="thdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">A phage system with low fitness cost producing sRNA, which inhibits the synthesis of antibiotic resistance proteins.</p><br />
</div><br />
</div><br />
<div id="tcdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">Infiltrate macrophages with an <i>E.coli</i> producing TDMH, an enzyme that will lyse the Mycobacteria cell wall.</p><br />
</div><br />
</div><br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Detect" title="Detect"><br />
<div id="pspanel" class="subpanel2" onmouseover="chgtrans(this)"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/a/a8/PB_DetectNarrow.jpg" width="125px" height="500px"/><br />
<div class="titlebox"><br />
<center><img src="https://static.igem.org/mediawiki/2013/0/0b/PB_detecticon.gif" style="height:60px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Detect<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Target" title="Target"><br />
<div id="dspanel" class="subpanel2"><br />
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<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Target<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Infiltrate" title="Infiltrate"><br />
<div id="tcpanel" class="subpanel2"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/2/21/PB_InfiltrateNarrow.jpg" width="125px" height="500px"/><br />
<div class="titlebox"><br />
<center><img src="https://static.igem.org/mediawiki/2013/6/6c/PB_infiltrate.gif" style="height:60px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Infiltrate<br />
</div><br />
</div><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Sabotage" title="Sabotage"><br />
<div id="thpanel" class="subpanel2"> <br />
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<div class="titlebox"><br />
<center><img src="https://static.igem.org/mediawiki/2013/8/81/PB_sabotageicone.gif" style="height:60px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Sabotage<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Results" title="Results"><br />
<div class="subpanel3" ><br />
<img width="70px" style="margin-left:80px;margin-right:15px;position:relative;bottom:1px" src="https://static.igem.org/mediawiki/2013/d/d5/PB_handresults.gif"/>Jump to Results<br />
</div><br />
</a><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="panel" style="background:white;"><br />
<div class="subpanel4"><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/TB_Facts" title="TB Facts"><br />
<div class="subpanel5"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/f/f9/PB_TBfacts2.png" width="354px" height="156px"/><br />
<div style="position:relative;bottom:148px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/6/69/PB_logoTBfacts.png" style="height:50px;margin-top:10px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
TB Facts<br />
</div><br />
</div><br />
</a> <br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/TB_France" title="TB in France"><br />
<div class="subpanel5"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/3/39/PB_TBinFrance.png" width="354px" height="156px"/> <br />
<div style="position:relative;bottom:158px"> <br />
<center><img src="https://static.igem.org/mediawiki/2013/c/cf/PB_logofrance.png" style="height:50px;margin-top:10px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
TB in France<br />
</div> <br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/TB_Gallery" title="TB Gallery"><br />
<div class="subpanel5" style="margin-bottom:0;height:158px;"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/2/2f/PB_TBgallery%281%29.png" width="354px" height="156px"/> <br />
<div style="position:relative;bottom:158px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/d/de/PB_logoTBgallery.png" style="height:60px;margin-top:10px;margin-bottom:10px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
TB Gallery<br />
</div><br />
</div><br />
</a><br />
</div><br />
<div class="subpanel4"><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Study" title="Gender Study"><br />
<div class="subpanel7"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/8/8c/Gender.png" width="354px" height="283px"/><br />
<div style="position:relative;bottom:258px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/d/da/PB_logogender.png" style="height:60px;margin-top:10px;margin-bottom:10px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Gender Study<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Technology_Transfer" title="Technology Transfer"><br />
<div class="subpanel9" style="font-size:26px;"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/3/3c/TB_knowledge.png" width="354px" height="283px"/><br />
<div style="position:relative;bottom:258px"> <br />
<center><img src="https://static.igem.org/mediawiki/2013/6/6d/PB_logotransferttechno.png" style="height:60px;margin-top:10px;margin-bottom:10px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Technology Transfer<br />
</div><br />
</div><br />
</a><br />
</div><br />
<div class="subpanel4" style="margin-right:0px"><br />
<div style="margin-right:0;width:356px"><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Collaboration" title="Collaboration"><br />
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<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/e/e4/TB_collboration2.png" width="354px" height="283px"/><br />
<div style="position:relative;bottom:258px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/7/75/PB_lofocollaboration.png" style="height:50px;margin-top:15px;margin-bottom:15px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Collaboration<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/SensiGEM" title="SensiGEM"><br />
<div class="subpanel6" style="margin-bottom:0"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/d/d5/TB_senigem.png" width="354px" height="283px"/><br />
<div style="position:relative;bottom:258px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/3/3c/PB_logosenigem.png" style="height:60px;margin-top:10px;margin-bottom:10px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
SensiGEM<br />
</div><br />
</div><br />
</a><br />
</div><br />
</div><br />
</div><br />
<div style="clear: both;"></div><br />
<div><br />
<div class="subpanel8"><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Team" title="Team"><br />
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</a><br />
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<div class="subpanel8"><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Notes" title="Notebook"><br />
<center><img src="https://static.igem.org/mediawiki/2013/2/27/PB_Notebooklogo.png" height="64px"/></center> <br />
</a><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Parts" title="Submitted Parts"><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Medal_Fulfillment" title="Medal Fulfillment"><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/File:PB_frontpagebanner4.pngFile:PB frontpagebanner4.png2013-11-06T13:49:58Z<p>Marguerite: </p>
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<div></div>Margueritehttp://2013.igem.org/Team:Paris_BettencourtTeam:Paris Bettencourt2013-11-06T13:24:41Z<p>Marguerite: </p>
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Overview" title="Project Overview"><br />
<div class="subpanel1"><br />
<div style="position:relative;bottom:0px"><br />
<div class="cont"><p style="font-size:32px;line-height:34px;">FIGHT TUBERCULOSIS WITH MODERN WEAPONS </p></div><br />
<div class="cont"><br />
<p style="font-size:26px;"><br />
Tuberculosis (TB) is an infectious disease caused by <i>Mycobacterium tuberculosis</i> (Mtb) that affects nearly two billion people around the world. On this website we present four new ways to use the power of synthetic biology in the fight against TB: from gene detection, to drug targeting, to infiltrating macrophages, to sabotaging the synthesis of proteins. Hover over these panels to see the project overview.<br />
</p><br />
</div><br />
<div id="psdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">A biosensor that detects the presence of sequence specific antibiotic resistance genes.</p><br />
</div><br />
</div><br />
<div id="dsdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">A safe and specific high-throughput drug screening method that targets essential mycobacterial metabolic proteins.</p><br />
</div> <br />
</div><br />
<div id="thdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">A phage system with low fitness cost producing sRNA, which inhibits the synthesis of antibiotic resistance proteins.</p><br />
</div><br />
</div><br />
<div id="tcdesc" class="spdesc"><br />
<div class="cont"><br />
<p style="font-size:26px;">Infiltrate macrophages with an <i>E.coli</i> producing TDMH, an enzyme that will lyse the Mycobacteria cell wall.</p><br />
</div><br />
</div><br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Detect" title="Detect"><br />
<div id="pspanel" class="subpanel2" onmouseover="chgtrans(this)"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/a/a8/PB_DetectNarrow.jpg" width="125px" height="500px"/><br />
<div class="titlebox"><br />
<center><img src="https://static.igem.org/mediawiki/2013/0/0b/PB_detecticon.gif" style="height:60px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Detect<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Target" title="Target"><br />
<div id="dspanel" class="subpanel2"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/e/e2/PB_TargetNarrow.jpg" width="125px" height="500px"/><br />
<div class="titlebox"><br />
<center><img src="https://static.igem.org/mediawiki/2013/1/11/PB_TargetIcon.gif" style="height:60px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Target<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Infiltrate" title="Infiltrate"><br />
<div id="tcpanel" class="subpanel2"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/2/21/PB_InfiltrateNarrow.jpg" width="125px" height="500px"/><br />
<div class="titlebox"><br />
<center><img src="https://static.igem.org/mediawiki/2013/6/6c/PB_infiltrate.gif" style="height:60px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Infiltrate<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Project/Sabotage" title="Sabotage"><br />
<div id="thpanel" class="subpanel2"> <br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/4/42/PB_SabotageNarrow.jpg" width="125px" height="500px"/><br />
<div class="titlebox"><br />
<center><img src="https://static.igem.org/mediawiki/2013/8/81/PB_sabotageicone.gif" style="height:60px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Sabotage<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Results" title="Results"><br />
<div class="subpanel3" ><br />
<img width="70px" style="margin-left:80px;margin-right:15px;position:relative;bottom:1px" src="https://static.igem.org/mediawiki/2013/d/d5/PB_handresults.gif"/>Jump to Results<br />
</div><br />
</a><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="panel" style="background:white;"><br />
<div class="subpanel4"><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/TB_Facts" title="TB Facts"><br />
<div class="subpanel5"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/f/f9/PB_TBfacts2.png" width="354px" height="156px"/><br />
<div style="position:relative;bottom:148px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/6/69/PB_logoTBfacts.png" style="height:50px;margin-top:10px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
TB Facts<br />
</div><br />
</div><br />
</a> <br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/TB_France" title="TB in France"><br />
<div class="subpanel5"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/3/39/PB_TBinFrance.png" width="354px" height="156px"/> <br />
<div style="position:relative;bottom:158px"> <br />
<center><img src="https://static.igem.org/mediawiki/2013/c/cf/PB_logofrance.png" style="height:50px;margin-top:10px;margin-bottom:20px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
TB in France<br />
</div> <br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/TB_Gallery" title="TB Gallery"><br />
<div class="subpanel5" style="margin-bottom:0;height:158px;"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/2/2f/PB_TBgallery%281%29.png" width="354px" height="156px"/> <br />
<div style="position:relative;bottom:158px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/d/de/PB_logoTBgallery.png" style="height:60px;margin-top:10px;margin-bottom:10px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
TB Gallery<br />
</div><br />
</div><br />
</a><br />
</div><br />
<div class="subpanel4"><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Study" title="Gender Study"><br />
<div class="subpanel7"><br />
<img class="narrowimg" src="https://static.igem.org/mediawiki/2013/8/8c/Gender.png" width="354px" height="283px"/><br />
<div style="position:relative;bottom:258px"><br />
<center><img src="https://static.igem.org/mediawiki/2013/d/da/PB_logogender.png" style="height:60px;margin-top:10px;margin-bottom:10px;"/></center><br />
<div style="width:60%;margin-left:20%;margin-bottom:20px;"><hr></div><br />
Gender Study<br />
</div><br />
</div><br />
</a><br />
<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Technology_Transfer" title="Technology Transfer"><br />
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Technology Transfer<br />
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Collaboration<br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/SensiGEM" title="SensiGEM"><br />
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SensiGEM<br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Notes" title="Notebook"><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Medal_Fulfillment" title="Medal Fulfillment"><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/File:PB_frontpagebanner3.pngFile:PB frontpagebanner3.png2013-11-06T13:23:57Z<p>Marguerite: </p>
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<div></div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_StudyTeam:Paris Bettencourt/Human Practice/Gender Study2013-10-29T03:49:18Z<p>Marguerite: </p>
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<img src="https://static.igem.org/mediawiki/2013/c/c1/PB_genderestudybanner.png"/><br />
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<div class="overbox"><br />
<div class="bkgr"><br />
<h2>Background</h2><br />
<p>Science suffers from gender bias</p><br />
</div><br />
<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>Revealed gender bias in synthetic biology by studying sex ratios in SB conferences and labs</li><br />
<li>Built a database of all iGEM teams reporting all available online information and sex ratios of teams and advisors</li><br />
<li>Conducted a statistical analysis of this data-set and showed among other results that success in iGEM is correlated to gender mix</li><br />
<li>Made recommendations to implement an active gender policy in iGEM</li><br />
</ul><br />
<p></p><br />
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<div style="clear: both;"></div><br />
<div class="aims"><br />
<h2>Aims</h2><br />
<p>To investigate gender dynamics in iGEM and in synthetic biology research community at large in a quantitative manner</p><br />
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<div style="height:68px"> <br />
<a href="#Introduction"><br />
<div class="hlink"><br />
<h2>Skip to Introduction</h2><br />
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</a><br />
<a href="#Recommendations"><br />
<div class="hlink"><br />
<h2>Skip to Recommendations</h2><br />
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</a><br />
<a href="#Database"><br />
<div class="hlink"><br />
<h2>Skip to Database</h2><br />
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</a><br />
<a href="#Findings"> <br />
<div class="hlink" style="margin-right:0px"><br />
<h2>Skip to Main Findings</h2><br />
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<a href="#SynBio"><br />
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<h2>Skip to Gender Bias in SynBio</h2><br />
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<a href="#Success"><br />
<div class="hlink" style="width:355px"><br />
<h2>Skip to iGEM Diversity and Success</h2><br />
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<a href="#Clues"><br />
<div class="hlink" style="width:355px;margin-right:0"><br />
<h2>Skip to Clues to Improve Balance</h2><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Facts"><br />
<div class="hlink" style="width:100%;margin-right:0"><br />
<h2 style="font-size:24px;">Infographics on gender and Synthetic Biology</h2><br />
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<br />
<div id="Introduction"></div><br />
<h2>Introduction</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
For every woman killed by TB, there are two men. Our review of the literature on gender bias and tuberculosis can be found <a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Study/Gender_Bias">here</a>. If a disease can be biased, what about ourselves? iGEM? Synthetic biology? Gender bias in science may appear in different forms. Gender balance varies by discipline, by job title, by age or by region. Only 30% of researchers in Europe are women, while 92% of French university deans are men. </p> <p>Hisorically, gender bias has affected the lives of scientists and the practice of science. However, assessing gender bias today in a living community is very difficult. History, stereotypes, limits of the disciplines, and the simple lack of data can prevent us, the synthetic biologists, from thinking about our own relationship to gender.</p><br />
<br><br />
</div><br />
<div class="rightparagraph"><br />
<p><br />
Most of those issues should not apply in synthetic biology. Synthetic biology is a new field. The argument of the heritage of some habits cannot be made. It is a mix of previously existing disciplines and therefore very open and should not reflect preexisting stereotypes. To study gender bias in iGEM and in synthetic biology we decided to follow a data driven approach. Studying in a quantitative manner this subjects had two main benefits. First it prevented us to apply our own biases and stereotypes on this subject. Secondly, it lead us to construct data base that we make freely available and let anyone test his own hypothesis on this controversial subject and form his own conclusions.</p><br />
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<div style="clear: both;"></div><br />
<div id="SynBio"></div><br />
<h2> Synthetic biology field : general overview of gender equality in synthetic biology </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Gender repartition in synthetic biology can be looked at from different perspectives. For this study, two main ways were chosen: composition of labs and conferences. The main reasons for those choices were the accessibility of online data </p><br />
</div><br />
<div class="rightparagraph"><br />
<p><br />
as well as the necessity to get information not only about the general gender balance but also the sex ratio inside a defined category: PhD students, post docs, head of labs... </p><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<h2> Synthetic biology labs, a good representation of gender (in)equality in science </h2> <br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Teams of 50 synthetic biology labs were studied. The labs were chosen by their presence on the webpage http://syntheticbiology.org/Labs.html . For each lab, several numbers were reported in a table : total number of people in the team, number of women in the team, number of PhD students, post docs, head of labs, number of women PhD students, post docs, head of labs. From this, the sex ratios (number of women / total number of people) were then calculated for each of those categories. </p><br />
<p><br><center><a href="https://2013.igem.org/File:ParisB2013_Synthetic_Biology_Research_Groups.xls"><br />
<img src="https://static.igem.org/mediawiki/2013/b/b1/PB_downloadGD.png" width="530"></a></center></p> <br />
<br><p><br />
The first conclusion that can be made is that women are generally under-represented in synthetic biology labs. 33% correspond to the average presence of women in research in Europe. Indeed according to the European Commission, 32% of researchers in Europe are women <i>(She Figures, 2012)</i>. <br><br>The second finding also reflects well an already known reality in science : the glass ceiling. In 1995, the glass ceiling was defined by the U.S. Department of Labor, as a <i>"political term used to describe "the unseen, yet unbreakable barrier that keeps minorities and women from rising to the upper rungs of the corporate ladder, regardless of their qualifications or achievements" </i>.<br />
With only 17,85\% of heads of labs being women, synthetic biology is still doing slightly better than the average. According to a European study done in 2008 called <i>Mapping the maze,getting women to the top in research</i>., only 15% of women occupy top research position in Europe. However, the number of SB P.I. should be analyzed through the filter of history. In a new field, it would be expected in a world where bias would not be present anymore to have way more women at those positions.<br />
</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
</br></br></br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/4/46/PB_GS_LabsBis.png" width="353px"/><br><br />
<b>Figure 1:Sex ratio in synthetic biology labs</b>. The percentage of women by role in 50 synthetic biology labs. Error bars represent SD. The sex ratio of each lab is determined independently and then the mean of the labs was determined.<br />
</center><br />
<br />
</br></br></br><br />
<center><br />
<TABLE BORDER="1"> <br />
<CAPTION> </CAPTION> <br />
<TR> <br />
<TH>Labs </TH> <br />
<TH> Phd Students </TH> <br />
<TH> Post Docs</TH> <br />
<TH> Head of Labs </TH> <br />
</TR> <br />
<TR> <br />
<TH> 33,10 % </TH> <br />
<TD> 35,39 % </TD> <br />
<TD> 31,31 % </TD> <br />
<TD> 17,85 % </TD> <br />
</TR> <br />
</TABLE><br />
</center><br />
<br />
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<div style="clear: both;"></div><br />
<br />
<h2> Speakers at SB Conferences : effects of an active gender policy</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
SBX.0 conferences accompanied the development of synthetic biology. They provide a great way to investigate the evolution of gender ratio since the birth of synthetic biology. Moreover, the presence/absence of women as speakers is a known indicator of gender bias and specially of active gender policy. Indeed, several social mechanisms are in place lead to fewer female speakers that could be expected: self censorship, unconscious stereotypes, unconscious choice of only male speakers... However, having female speakers at conference is a key point. It allows women, to gain confidence but also to act as role model for women attending the conference. </p><br />
<p><br />
To study SB conferences, available programs online were downloaded. Data referring to the number of speakers but also to posters were recorded. The data-set could not be completed for certain years due to the impossibility of finding the data online.<br />
</p><br />
<p><br><center><a href="https://2013.igem.org/File:ParisB2013Resultats_SB.xls"><br />
<img src="https://static.igem.org/mediawiki/2013/b/b1/PB_downloadGD.png" width="530"></a></center></p><br />
<br><p><br />
The sex ratio of the speakers have followed a very interesting evolution. It has been multiplied by 3 from SB1 to SB5. This could indicate a change of policy considering speakers. Most likely, the first conferences invited speakers without taking into consideration the gender dimension. Might it be due to some complaints or the raise in awareness of the conferences organizers, the numbers went up. This example is interesting because it clearly show an interest in the subject by the involved community.<br />
</p><br />
<p><br />
Two main conclusions can be drawn on posters. First, the sex ratio of authors in posters has changed throughout the years. Secondly, this number is not as high as the sex ratio in labs. The question is why? The points described above could be underlying reasons, however it is very difficult to truly go beyond this with only those numbers. <br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<br><br><br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/6/62/PB_GS_Sex_ratio_in_SB_Conf.png" width="400px"/><br><br />
<b> Figure 2:Sex ratio in SB conferences</b>. The proportion of speakers and poster presenters at SBX.0 conferences who are women. Data was gathered on-line from available programs.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<h2> Under represented and badly represented</h2> <br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
In order to try to better understand the dynamics of gender behind the posters numbers, the rank of authors were reported for each poster. Sex ratio were calculated for each rank, keeping in mind that in biology, the first author is often a Phd student or a post doc and the last author, the P.I.<br />
</p><br />
<p><br />
As explained above, women are generally under-represented in synthetic biology labs, even less represented at conferences. When looking at the rank of author in posters, another bias appears. Indeed, women are more likely to be present as middle authors than first or last. This bias can be found in papers of different disciplines as shown on the graph realized on the eigenfactor.</p><br />
<p> <br />
The main finding considering gender in synthetic biology is that even though synthetic biology is new and interdisciplinary, it remains quite representative of existing gender bias in science. Therefore it can be concluded, that the issues that have kept women out of science and especially out of top research position are still present and will not be resolved with time. A strong and active policy appears necessary to bring more mixity and therefore diversity in this field.<br />
<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/6/6b/PB_GS_Author_place_.png" width="435px"/> <br><br />
<b>Figure: Sex ratio according to rank of authors in SB posters.</b> Authorship on Posters in SB conferences was collected and Women and Male authors are organized by their rank of authorship. Women tend to be middle authors more often then first or last authors.<br />
</center><br />
<br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/2/28/PB_GS_Eigenfactor.png" width="535px"/><br />
<b>Figure 4: Analysis of rank of authors according to gender in scientific publications.</b>Women's rank of authorship in various journals and databases. There is over-all far more men cited as authors than women, and this is consistent across publications and scientific fields. Additionally, Authorship rank is shown on the bottom with the % of women over all shown as the solid line with the dot indicating the % of women within that authorship rank. Dots above the line indicate that women are over represented compared to the mean and dots below the line indicate that women are underrepresented, with the further they are from the line the greater the imbalance.<br />
</center> <br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Database"></div><br />
<h2> iGEM as a model : a fantastic database </h2><br />
<div class="leftparagraph"><br />
<h3> Online Data</h3> <br />
<p> &nbsp;&nbsp;<br />
All the data concerning iGEM were retrieved from the website : <a href="https://igem.org">https://igem.org</a> <br />
List of teams were retrieved from the webpages <a href="https://igem.org/Team_List.cgi?year=2012">https://igem.org/Team_List.cgi?year=2012</a>.<br />
List of project themes were retrieved from <a href="https://igem.org/Team_Tracks?year=2012">https://igem.org/Team_Tracks?year=2012</a>.<br />
List of prices were retrieved <a href="https://igem.org/Results">https://igem.org/Results</a>.<br />
List of judges were retrieved from: <a href="https://igem.org/Judge_List">https://igem.org/Judge_List</a><br />
</p><br />
<h3> Sex ratio determination :</h3> <br />
<p> &nbsp;&nbsp; For each team, the official team profile was checked to count the number of student members, advisors and instructors.<br />
Then to determine the sex of particpants, wiki were used when names were not obvious, using pictures when they existed. When no pictures were available and names were not obviously referring to one sex, a google image search was done on the name (first and last name) and the sex was chosen as the most represented sex in the pictures (if 10 images of men come up and 30 of women, the participant was considered as a woman).</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
<h3> Database : </h3> <br />
<p> &nbsp;&nbsp; Information for the first year of iGEM were difficult to find because of the non existence of available wiki pages and it was therefore decided not to take into account this year.<br />
Teams who withdrew during the competition were not taken into account since it was most of the time impossible to know the number of participants due to the absence of wiki.<br />
In the end our data set is composed of 662 teams over 5 years. For each team were reported : <br />
Year ; region ; name of the team ; number of student members ; number of women student members ; number of advisors ; number of women advisors ; number of instructors ; number of women instructors ; participation to MIT championship ; medal ; regional prices ; championship prices ;tracks. </p><br />
<p><br><br />
<center><br />
<a href="https://static.igem.org/mediawiki/2013/3/35/PB_GS_IGEMdatabase.xls"><br />
<img src="https://static.igem.org/mediawiki/2013/b/b1/PB_downloadGD.png" width="530"/></a><br />
</center><br><br />
</p><br />
<h3> Attrition by Career Stage</h3><br />
<p> &nbsp;&nbsp; With the introduction of High School iGEM competition, We have quantitative data about gender balance through career progression. By observing trends between the High School Division, Undergraduate and Overgraduate Divisions, Advisors and finally Judges; we can identify potential glass ceilings and find out why women are being lost through various career stages.</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Findings"></div><br />
<h2> iGEM : a mirror of main gender problems </h2><br />
<div class="leftparagraph"><br />
<h3> Teams sex ratio, a very robust value </h3> <br />
<p> &nbsp;&nbsp;<br />
<br><br><br />
The first thing that was examined was the evolution of sex ratio of teams in iGEM across continents and throughout the years.<br />
</p><br />
<br><br />
<p><br />
The striking conclusion of this comparison is that the sex ratio is iGEM teams remains constant through the years and across continents (ANOVA's p-value for the different conditions > 0,5). This shows that women are underrepresented in iGEM teams. </p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/5/5a/GS_Year.png" width="250px"/><br />
<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Region.png" width="250px"/><br />
<b>Figure 5: Sex ratio of iGEM teams through the years and across continents.</b> The proportion of team members of each gender over time and between regions in the collegiate iGEM competition. Bars represent the 95% Confidence interval.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div class="leftparagraph"><br />
<h3> Women do not supervise as much as men </h3> <br />
<p> &nbsp;&nbsp;<br />
The second question investigated was the sex ratios for the different categories of people participating in iGEM. Indeed, iGEM is not only undergrad students. Advisors, instructors, judges also participate representing the complete professional ladder of synthetic biology. A category called Supervisors was created corresponding to instructors and advisers. Indeed, those terms are not understood and used in the same way in different continents. In some countries "advisers" means people who directly teach the teams (mostly grad students and post docs) whereas it means general mentors for others and vice versa.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Role.png" width="300px" height="250px"/> <br><br />
<b>Figure 6: Sex ratios in iGEM according to categories of people participating.</b> The gender balance of students, Supervisors and Judges in iGEM collegiate competitions. Supervisors is taken as the combination of advisors and instructors due to variations on how individual teams differentiate between them. Bars are 95% confidence intervals.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
When executing comparisons tests , team members' sex ratio is found to be different from judges' and instructors' ones (p value < 0,01). However judges and advisers are not significantly different ( p value > 0,5). This result reveals a tendency of women to supervise less than men. Indeed, from team members to instructors, the sex ratio is divided by two. What is even more interesting is to compare those numbers to sex ratios of PhD students and post docs in labs. The sex ratio of instructors is 10 points lower. </p><br />
<p> Women constitute a pool of talent that is not mobilized. They participate but do not supervise teams. They are "lost" along the way. Indeed, in a study published last year in PNAS, researchers showed that P.I. were less prone to have a woman mentoring students than man. This unconscious bias can be translated by a lack of encouragement from P.I.s but also by a self censorship which is not taken into account by other supervisors as explained in an recently published article by Eileen Pollack (E. Pollack Why Are There Still So Few Women in Science? NY TImes October 2013).<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<h3> Tracks and sex ratio in iGEM </h3> <br />
<p> &nbsp;&nbsp;<br />
The third finding goes against an often-heard stereotype "women are more interested by applied research". In order to investigate this subject, tracks were reported for each project. In iGEM tracks correspond to general theme of the project : medicine, fundationnal research…Tracks were then looked at in terms of sex ratios. There is no significant difference between tracks. (ANOVA > 0,1).</p><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/a/ac/PB_GS_Sexratiotracksbis.png" width="535px"/><br />
<b>Figure 7: Sex ratios and tracks in iGEM. </b>The proportion of gender in teams grouped by the track that the team is entered in during collegiate iGEM competitions. There is no statistical significant difference between the gender balance between tracks. <br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<h3> High School Division is more balanced</h3><br />
<p> When we looked at the High School Divison, we found that it had a higher percentage of women than the university iGEM teams. Additionally, The number of female advisors and instructors in the High School division is much higher than that of the Collegiate division and is approximately the same as the proportion of students. This indicates that there is a problem at the Collegiate level and that iGEM can be an important bridge for women to access new opportunities to lead in higher education</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/9/91/PB_HighSchool_Gender_Students.png" width="250px"/><br />
<img src="https://static.igem.org/mediawiki/2013/c/cb/PB_HS_By_Role.png" width="250px"/><br />
<b>Figure 8: Sex ratios in High School iGEM by year and role. </b>On the left, the proportion of students in the High School Competition that are women for each year. On the right, the proportion of women in each role for all years. Bars represent 95% Confidence Interval.<br />
</center><br />
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<div class="leftparagraph"><br />
<p><br />
To conclude, studying the iGEM competition gives a unique quantitative insight on existing questions in the field of gender studies. It also constitutes an amazing argument to convince scientists of the existence of a gender issue in science. As explained by Rascun et al in a recent paper published in PNAS, scientists believe that those type of bias only exist in some labs, not their own, therefore very objective studies need to be conducted to clearly show the reality of the numbers. More over , Jo Handelsman a microbiologist involved in that paper underlined in a recent interview, that people often think that there is still an issue in physics or maths but that there are no more women issues in biology, which is not true. This study supports strongly the view that this general thinking is untrue.<br />
</p><br />
</div><br />
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<div id="Success"></div><br />
<h3> In iGEM, is diversity a factor of success ? </h3><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Several studies led by consulting groups (McKinsey and Company Women Matter, 2007) have shown that mixity in a team increases performance. The big question of what leads to success in iGEM was therefore investigated using the database with a special focus on gender. In order to be able to get a general idea about iGEM team success, a point system was put in place.<br />
</p><br />
<p>Points were attributed the following way.<br><br />
For the medal: 1 point for bronze medal, 2 points for silver medal, 3 points for gold medal. For the world jamboree qualified teams: 2 points for every team taking part in 2010 and before (before regional jamborees existed) , 6 points for team qualified for world final (after 2010). For special prices (Best ...): 6 points were attributed for each regional price earned (only after 2010), 13 points for each price earned in the world final (all price worth 13 points before regional jamborees existed). For the final place in world final: 15 points for the sixth team, 20 points for the fifth team, 25 points for the fourth team, 30 points for the third team, 35 points for the second team, 40 points for the firth team.</p><br />
<p><br />
The aim was to give each team a score that is proportional to the rewards it earned, taking in account that all teams were in world jamboree prior to 2011, without having to be qualified in regional jamborees.<br />
</p><br />
<p>Best score is for the Imperial College London team in 2011 (81 points).<br />
All teams (all years) average is 7.41 points, considering teams with no points (due to withdrew).</p><br />
<p><br />
Correlations studies between this number of points and other variables show that that for all teams, the main variables explaining success in iGEM is the number of years of existence and the size of the team. It would therefore seem that mixity would not be a factor. However, when looking at correlations between variables of teams who truly succeeded (points > 20) , the variables that have a significant correlation with the number of points become the sex ratio and the number of supervisors. Therefore it could be hypothesized that beginning iGEM teams have to face major challenges but when the team existed for a few years and general organization or funding problems have been dealt with , diversity could be a factor for success. </p><br />
<p><br />
In order to check if this could be seen in the best iGEM teams that existed, the sex ratio of of prize winner teams was compared to the one of participating teams with boostrap resampling giving a p-value of 0.035 This means that the sex ratio of winning teams (45%) is significantly different from the one of participating teams (37%)<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/d/de/GS_Prize.png" width="400px" ><br><br />
<b>Figure 9: Gender balance and succes in iGEM. </b> The proportion of women in teams that have won prizes in iGEM compared to the proportion in teams over all. There is a significantly higher proportion of women in teams that win prizes <b>(p=0.034)</b>.<br />
</center><br />
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<div id="Clues"></div><br />
<h2> Clues to improve mixity </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
<br />
Women are not as represented as men in iGEM. Why should this be a problem ? Indeed, even if it might lead to success as explained above, the need to have gender equality could be questioned. However iGEM is an international competition. One of its main goals is to attract and educate young people as well as trying to have them solve real issues. Synthetic biology might be a key technology to solve the main challenges of the 21st century.</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
<p> The world will need science and if iGEM only succeeds in motivating half of the population that could be interested, this would be a major failure to achieve its mission. Therefore, the last part of the study was aimed at understanding how could iGEM improve mixity within its own ranks.<br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div class="leftparagraph"><br />
<h3> From the data </h3><br />
<p> &nbsp;&nbsp;<br />
By looking at correlation between sex ratios and other variables, the most striking result is the link between team size and sex ratio. Teams of 2 or 3 people are almost only male teams. Even when taking out those very small teams, out of the data set the correlation holds up. This is a first lead. <br><br />
The second analysis that was made regarding the data was to compare the detailed statistics of the 100 most female teams and 100 male teams. Again, it is found that the total team member is lower for male team (9,7 vs 7,8 (p-value 0,0019) we can hypothesize that having women instructors does matter to attract girls in teams. They serve as role models. Having a woman capable of studying and realizing a synthetic biology project is a direct signal to female students that it is also possible for them to do it. Having a woman adviser might also help girls better adapt in a group and reduce their fears about having to endure constant teasing or "male " ambiance.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<h3> From a survey</h3><br />
<p> &nbsp;&nbsp;<br />
Finally, a survey was conducted among iGEMers and former iGEMers to understand their motivations and activities in iGEM. The study was designed to be unbiased and to avoid stereotype threat (for example by putting the question about gender in the end among many other pieces of information). It is still available <a href="http://bit.ly/14WykuZ"> here</a>. Participants in the survey had to rank from 1 to 5 (1 being not important, and 5 very important) answers to questions regarding personnal and professional motivations for participating in iGEM as well values and on what did they spend their time. 63 people answered among whom 32% were women.</p><br />
<br><br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/c/c5/PB_GS_Survey1.png" width="500px" /><br />
<b>Figure 10: Results of survey : what did you hope to learn in iGEM? </b>A survey was distributed to iGEM teams asking participants to rank their motivation to participate in iGEM in various subjects between 1-5. The only significant difference between the motivation of men and women in iGEM were in the subjects leading a team and leading a project.<br />
</center><br />
<br><br><br />
<p><br />
It is interesting to notice that men and women answered almost exactly the same way regarding most of the questions. Women gave a little more importance for the value of fundamental research in iGEM while men graded a bit better "Changing the world". Motivations were approximately the same as well as time spent on each activity. Just a little fact was that men considered human practices a bit more important than women did but spent a little less time on it. <br />
There is only one main difference (more than one point out of five which is represented below) : the will to lead a project and lead a team. It is striking to see how much men are more motivated to lead teams than women. This is definitely to put in relation with the number of women advisers found and the impact it can then have on teams mixity. This could reflect women lack of self esteem in some parts of their work.</p><br />
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<div id="Recommendations"></div><br />
<h2> Recommendations</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Considering all the results that were presented above, here is a list of recommendations for the iGEM foundation to pursue an active policy to improve mixity in iGEM.<br />
<ul><br />
<li> Raise the number of women judges </li> <br />
<li> Promote large teams </li> <br />
<li> Write up a small paragraph to team heads to insist on the importance of motivating young women to be advisers.</li><br />
<li> Giving Bonus point when the team have women advisers </li><br />
</ul><br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>And finally, add in iGEM requirements a Gender reflection. By having teams filling out the database that was built and answering the survey and write a small paragraph about how they see mixity in their team and what it could bring, it would drastically raise the awareness of young men and women about the gender problem in science. Having an up-to-date database is also a great way to see improvements in a quantitative manner. It would allow a direct assessment of the effects of an active gender policy which would be a unique example in science. iGEM could become a leader in that fight and prepare the new generation of scientists to finally get rid of the gender inequality in science<br />
</p><br />
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</div><br />
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<br />
<h2>Litterature</h2><br />
<div class="leftparagraph"><br />
<ul><br />
<li>P. Allotey, M. Gyapong Gender in tuberculosis research INT J TUBERC LUNG DIS 2008 </li><br />
<li>M. Calid, S. Rasul, S Ullah Khan, M; Saeed Gender differences in delay to s to tuberculosis diagnosis and treatment outcome<br><br />
European Commission She figures 2012<br><br />
European Commission, Mapping the gaze : getting more women to the top in Research 2008.<br><br />
</li><br />
<li>C.B. Holmes, H. Hausler, P. Hunn : A review of sex differences in the epidemiology of tuberculosis</li><br />
<li>A. N. Martinez J. T. Rhee, P. M. Small,‡M. A. Behr Sex differences in the epidemiology of tuberculosis in San Francisco INT J TUBERC LUNG DIS 4(1):26–31 2000</li><br />
<li>Moss-Racusin et al, (2012) Science faculty’s subtle gender biases favor male students PNAS </li><br />
<br />
</ul><br />
</div><br />
<div class="rightparagraph"><br />
<ul><br />
<li>McKinsey and Company Women Matter, 2007 </li><br />
<li>Olivier Neyrolles, Lluis Quintana-Murci Sexual Inequality in Tuberculosis, Plos Medicine 2009</li><br />
<li>Nosek et al. (2009) National differences in gender–science stereotypes predict national sex differences in science and math achievement. PNAS June 30, 2009 vol. 106 no. 26 10593–10597</li><br />
<br />
<li>E. Pollack Why Are There Still So Few Women in Science? NY TImes OCtober 2013</li><br />
<li>Al S. Rhines The role of sex differences in the prevalence and transmission of tuberculosis : Tuberculosis 2013</li><br />
<li>M. W. Uplekar, S. Rangan, M. G. Weiss, J. Ogden, M. W. Borgdorff, P. Hudelson Attention to gender issues in tuberculosis control INT J TUBERC LUNG DIS 4(1):26–31 2001</li><br />
</ul><br />
</div><br />
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<h2>Attributions</h2><br />
<p>We would like to thank Flora Vincent, President of <a href="http://wax-science.fr/")>WAX Science</a> association for her precious help in analyzing the results, and Kim de Mora and Kitwa from the iGEM foundation, for helping spreading the survey. <p><br />
<p>This project was designed and accomplished by Aude Bernheim, Clovis Basier, Matt Deyell, Marguerite Benony and Sebastian Jaramillo in consultation with Edwin Wintermute and Ariel Lindner.</p><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_StudyTeam:Paris Bettencourt/Human Practice/Gender Study2013-10-29T03:46:51Z<p>Marguerite: </p>
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<h2>Background</h2><br />
<p>Science suffers from gender bias</p><br />
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<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>Revealed gender bias in synthetic biology by studying sex ratios in SB conferences and labs</li><br />
<li>Built a database of all iGEM teams reporting all available online information and sex ratios of teams and advisors</li><br />
<li>Conducted a statistical analysis of this data-set and showed among other results that success in iGEM is correlated to gender mix</li><br />
<li>Made recommendations to implement an active gender policy in iGEM</li><br />
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<h2>Aims</h2><br />
<p>To investigate gender dynamics in iGEM and in synthetic biology research community at large in a quantitative manner</p><br />
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<h2>Skip to Introduction</h2><br />
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<h2>Skip to Recommendations</h2><br />
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<h2>Skip to Database</h2><br />
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<h2>Skip to Main Findings</h2><br />
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<h2>Skip to Gender Bias in SynBio</h2><br />
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<h2>Skip to iGEM Diversity and Success</h2><br />
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<h2>Skip to Clues to Improve Balance</h2><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Facts"><br />
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<h2 style="font-size:24px;">Infographics on gender and Synthetic Biology</h2><br />
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<div id="Introduction"></div><br />
<h2>Introduction</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
For every woman killed by TB, there are two men. Our review of the literature on gender bias and tuberculosis can be found <a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Study/Gender_Bias">here</a>. If a disease can be biased, what about ourselves? iGEM? Synthetic biology? Gender bias in science may appear in different forms. Gender balance varies by discipline, by job title, by age or by region. Only 30% of researchers in Europe are women, while 92% of French university deans are men. </p> <p>Hisorically, gender bias has affected the lives of scientists and the practice of science. However, assessing gender bias today in a living community is very difficult. History, stereotypes, limits of the disciplines, and the simple lack of data can prevent us, the synthetic biologists, from thinking about our own relationship to gender.</p><br />
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<div class="rightparagraph"><br />
<p><br />
Most of those issues should not apply in synthetic biology. Synthetic biology is a new field. The argument of the heritage of some habits cannot be made. It is a mix of previously existing disciplines and therefore very open and should not reflect preexisting stereotypes. To study gender bias in iGEM and in synthetic biology we decided to follow a data driven approach. Studying in a quantitative manner this subjects had two main benefits. First it prevented us to apply our own biases and stereotypes on this subject. Secondly, it lead us to construct data base that we make freely available and let anyone test his own hypothesis on this controversial subject and form his own conclusions.</p><br />
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<div id="SynBio"></div><br />
<h2> Synthetic biology field : general overview of gender equality in synthetic biology </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Gender repartition in synthetic biology can be looked at from different perspectives. For this study, two main ways were chosen: composition of labs and conferences. The main reasons for those choices were the accessibility of online data </p><br />
</div><br />
<div class="rightparagraph"><br />
<p><br />
as well as the necessity to get information not only about the general gender balance but also the sex ratio inside a defined category: PhD students, post docs, head of labs... </p><br />
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<br />
<h2> Synthetic biology labs, a good representation of gender (in)equality in science </h2> <br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Teams of 50 synthetic biology labs were studied. The labs were chosen by their presence on the webpage http://syntheticbiology.org/Labs.html . For each lab, several numbers were reported in a table : total number of people in the team, number of women in the team, number of PhD students, post docs, head of labs, number of women PhD students, post docs, head of labs. From this, the sex ratios (number of women / total number of people) were then calculated for each of those categories. </p><br />
<p><center><a href="https://2013.igem.org/File:ParisB2013_Synthetic_Biology_Research_Groups.xls"><br />
<img src="https://static.igem.org/mediawiki/2013/b/b1/PB_downloadGD.png" width="530"></a></center></p> <br />
<p><br />
The first conclusion that can be made is that women are generally under-represented in synthetic biology labs. 33% correspond to the average presence of women in research in Europe. Indeed according to the European Commission, 32% of researchers in Europe are women <i>(She Figures, 2012)</i>. <br><br>The second finding also reflects well an already known reality in science : the glass ceiling. In 1995, the glass ceiling was defined by the U.S. Department of Labor, as a <i>"political term used to describe "the unseen, yet unbreakable barrier that keeps minorities and women from rising to the upper rungs of the corporate ladder, regardless of their qualifications or achievements" </i>.<br />
With only 17,85\% of heads of labs being women, synthetic biology is still doing slightly better than the average. According to a European study done in 2008 called <i>Mapping the maze,getting women to the top in research</i>., only 15% of women occupy top research position in Europe. However, the number of SB P.I. should be analyzed through the filter of history. In a new field, it would be expected in a world where bias would not be present anymore to have way more women at those positions.<br />
</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
</br></br></br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/4/46/PB_GS_LabsBis.png" width="353px"/><br><br />
<b>Figure 1:Sex ratio in synthetic biology labs</b>. The percentage of women by role in 50 synthetic biology labs. Error bars represent SD. The sex ratio of each lab is determined independently and then the mean of the labs was determined.<br />
</center><br />
<br />
</br></br></br><br />
<center><br />
<TABLE BORDER="1"> <br />
<CAPTION> </CAPTION> <br />
<TR> <br />
<TH>Labs </TH> <br />
<TH> Phd Students </TH> <br />
<TH> Post Docs</TH> <br />
<TH> Head of Labs </TH> <br />
</TR> <br />
<TR> <br />
<TH> 33,10 % </TH> <br />
<TD> 35,39 % </TD> <br />
<TD> 31,31 % </TD> <br />
<TD> 17,85 % </TD> <br />
</TR> <br />
</TABLE><br />
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<br />
<h2> Speakers at SB Conferences : effects of an active gender policy</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
SBX.0 conferences accompanied the development of synthetic biology. They provide a great way to investigate the evolution of gender ratio since the birth of synthetic biology. Moreover, the presence/absence of women as speakers is a known indicator of gender bias and specially of active gender policy. Indeed, several social mechanisms are in place lead to fewer female speakers that could be expected: self censorship, unconscious stereotypes, unconscious choice of only male speakers... However, having female speakers at conference is a key point. It allows women, to gain confidence but also to act as role model for women attending the conference. </p><br />
<p><br />
To study SB conferences, available programs online were downloaded. Data referring to the number of speakers but also to posters were recorded. The data-set could not be completed for certain years due to the impossibility of finding the data online.<br />
</p><br />
<p><center><a href="https://2013.igem.org/File:ParisB2013Resultats_SB.xls"><br />
<img src="https://static.igem.org/mediawiki/2013/b/b1/PB_downloadGD.png" width="530"></a></center></p><br />
<p><br />
The sex ratio of the speakers have followed a very interesting evolution. It has been multiplied by 3 from SB1 to SB5. This could indicate a change of policy considering speakers. Most likely, the first conferences invited speakers without taking into consideration the gender dimension. Might it be due to some complaints or the raise in awareness of the conferences organizers, the numbers went up. This example is interesting because it clearly show an interest in the subject by the involved community.<br />
</p><br />
<p><br />
Two main conclusions can be drawn on posters. First, the sex ratio of authors in posters has changed throughout the years. Secondly, this number is not as high as the sex ratio in labs. The question is why? The points described above could be underlying reasons, however it is very difficult to truly go beyond this with only those numbers. <br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<br><br><br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/6/62/PB_GS_Sex_ratio_in_SB_Conf.png" width="400px"/><br><br />
<b> Figure 2:Sex ratio in SB conferences</b>. The proportion of speakers and poster presenters at SBX.0 conferences who are women. Data was gathered on-line from available programs.<br />
</center><br />
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<br />
<h2> Under represented and badly represented</h2> <br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
In order to try to better understand the dynamics of gender behind the posters numbers, the rank of authors were reported for each poster. Sex ratio were calculated for each rank, keeping in mind that in biology, the first author is often a Phd student or a post doc and the last author, the P.I.<br />
</p><br />
<p><br />
As explained above, women are generally under-represented in synthetic biology labs, even less represented at conferences. When looking at the rank of author in posters, another bias appears. Indeed, women are more likely to be present as middle authors than first or last. This bias can be found in papers of different disciplines as shown on the graph realized on the eigenfactor.</p><br />
<p> <br />
The main finding considering gender in synthetic biology is that even though synthetic biology is new and interdisciplinary, it remains quite representative of existing gender bias in science. Therefore it can be concluded, that the issues that have kept women out of science and especially out of top research position are still present and will not be resolved with time. A strong and active policy appears necessary to bring more mixity and therefore diversity in this field.<br />
<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/6/6b/PB_GS_Author_place_.png" width="435px"/> <br><br />
<b>Figure: Sex ratio according to rank of authors in SB posters.</b> Authorship on Posters in SB conferences was collected and Women and Male authors are organized by their rank of authorship. Women tend to be middle authors more often then first or last authors.<br />
</center><br />
<br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/2/28/PB_GS_Eigenfactor.png" width="535px"/><br />
<b>Figure 4: Analysis of rank of authors according to gender in scientific publications.</b>Women's rank of authorship in various journals and databases. There is over-all far more men cited as authors than women, and this is consistent across publications and scientific fields. Additionally, Authorship rank is shown on the bottom with the % of women over all shown as the solid line with the dot indicating the % of women within that authorship rank. Dots above the line indicate that women are over represented compared to the mean and dots below the line indicate that women are underrepresented, with the further they are from the line the greater the imbalance.<br />
</center> <br />
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<div id="Database"></div><br />
<h2> iGEM as a model : a fantastic database </h2><br />
<div class="leftparagraph"><br />
<h3> Online Data</h3> <br />
<p> &nbsp;&nbsp;<br />
All the data concerning iGEM were retrieved from the website : <a href="https://igem.org">https://igem.org</a> <br />
List of teams were retrieved from the webpages <a href="https://igem.org/Team_List.cgi?year=2012">https://igem.org/Team_List.cgi?year=2012</a>.<br />
List of project themes were retrieved from <a href="https://igem.org/Team_Tracks?year=2012">https://igem.org/Team_Tracks?year=2012</a>.<br />
List of prices were retrieved <a href="https://igem.org/Results">https://igem.org/Results</a>.<br />
List of judges were retrieved from: <a href="https://igem.org/Judge_List">https://igem.org/Judge_List</a><br />
</p><br />
<h3> Sex ratio determination :</h3> <br />
<p> &nbsp;&nbsp; For each team, the official team profile was checked to count the number of student members, advisors and instructors.<br />
Then to determine the sex of particpants, wiki were used when names were not obvious, using pictures when they existed. When no pictures were available and names were not obviously referring to one sex, a google image search was done on the name (first and last name) and the sex was chosen as the most represented sex in the pictures (if 10 images of men come up and 30 of women, the participant was considered as a woman).</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
<h3> Database : </h3> <br />
<p> &nbsp;&nbsp; Information for the first year of iGEM were difficult to find because of the non existence of available wiki pages and it was therefore decided not to take into account this year.<br />
Teams who withdrew during the competition were not taken into account since it was most of the time impossible to know the number of participants due to the absence of wiki.<br />
In the end our data set is composed of 662 teams over 5 years. For each team were reported : <br />
Year ; region ; name of the team ; number of student members ; number of women student members ; number of advisors ; number of women advisors ; number of instructors ; number of women instructors ; participation to MIT championship ; medal ; regional prices ; championship prices ;tracks. </p><br />
<p><br><br />
<center><br />
<a href="https://static.igem.org/mediawiki/2013/3/35/PB_GS_IGEMdatabase.xls"><br />
<img src="https://static.igem.org/mediawiki/2013/b/b1/PB_downloadGD.png" width="530"/></a><br />
</center><br><br />
</p><br />
<h3> Attrition by Career Stage</h3><br />
<p> &nbsp;&nbsp; With the introduction of High School iGEM competition, We have quantitative data about gender balance through career progression. By observing trends between the High School Division, Undergraduate and Overgraduate Divisions, Advisors and finally Judges; we can identify potential glass ceilings and find out why women are being lost through various career stages.</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Findings"></div><br />
<h2> iGEM : a mirror of main gender problems </h2><br />
<div class="leftparagraph"><br />
<h3> Teams sex ratio, a very robust value </h3> <br />
<p> &nbsp;&nbsp;<br />
<br><br><br />
The first thing that was examined was the evolution of sex ratio of teams in iGEM across continents and throughout the years.<br />
</p><br />
<br><br />
<p><br />
The striking conclusion of this comparison is that the sex ratio is iGEM teams remains constant through the years and across continents (ANOVA's p-value for the different conditions > 0,5). This shows that women are underrepresented in iGEM teams. </p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/5/5a/GS_Year.png" width="250px"/><br />
<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Region.png" width="250px"/><br />
<b>Figure 5: Sex ratio of iGEM teams through the years and across continents.</b> The proportion of team members of each gender over time and between regions in the collegiate iGEM competition. Bars represent the 95% Confidence interval.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div class="leftparagraph"><br />
<h3> Women do not supervise as much as men </h3> <br />
<p> &nbsp;&nbsp;<br />
The second question investigated was the sex ratios for the different categories of people participating in iGEM. Indeed, iGEM is not only undergrad students. Advisors, instructors, judges also participate representing the complete professional ladder of synthetic biology. A category called Supervisors was created corresponding to instructors and advisers. Indeed, those terms are not understood and used in the same way in different continents. In some countries "advisers" means people who directly teach the teams (mostly grad students and post docs) whereas it means general mentors for others and vice versa.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Role.png" width="300px" height="250px"/> <br><br />
<b>Figure 6: Sex ratios in iGEM according to categories of people participating.</b> The gender balance of students, Supervisors and Judges in iGEM collegiate competitions. Supervisors is taken as the combination of advisors and instructors due to variations on how individual teams differentiate between them. Bars are 95% confidence intervals.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
When executing comparisons tests , team members' sex ratio is found to be different from judges' and instructors' ones (p value < 0,01). However judges and advisers are not significantly different ( p value > 0,5). This result reveals a tendency of women to supervise less than men. Indeed, from team members to instructors, the sex ratio is divided by two. What is even more interesting is to compare those numbers to sex ratios of PhD students and post docs in labs. The sex ratio of instructors is 10 points lower. </p><br />
<p> Women constitute a pool of talent that is not mobilized. They participate but do not supervise teams. They are "lost" along the way. Indeed, in a study published last year in PNAS, researchers showed that P.I. were less prone to have a woman mentoring students than man. This unconscious bias can be translated by a lack of encouragement from P.I.s but also by a self censorship which is not taken into account by other supervisors as explained in an recently published article by Eileen Pollack (E. Pollack Why Are There Still So Few Women in Science? NY TImes October 2013).<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<h3> Tracks and sex ratio in iGEM </h3> <br />
<p> &nbsp;&nbsp;<br />
The third finding goes against an often-heard stereotype "women are more interested by applied research". In order to investigate this subject, tracks were reported for each project. In iGEM tracks correspond to general theme of the project : medicine, fundationnal research…Tracks were then looked at in terms of sex ratios. There is no significant difference between tracks. (ANOVA > 0,1).</p><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/a/ac/PB_GS_Sexratiotracksbis.png" width="535px"/><br />
<b>Figure 7: Sex ratios and tracks in iGEM. </b>The proportion of gender in teams grouped by the track that the team is entered in during collegiate iGEM competitions. There is no statistical significant difference between the gender balance between tracks. <br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<h3> High School Division is more balanced</h3><br />
<p> When we looked at the High School Divison, we found that it had a higher percentage of women than the university iGEM teams. Additionally, The number of female advisors and instructors in the High School division is much higher than that of the Collegiate division and is approximately the same as the proportion of students. This indicates that there is a problem at the Collegiate level and that iGEM can be an important bridge for women to access new opportunities to lead in higher education</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/9/91/PB_HighSchool_Gender_Students.png" width="250px"/><br />
<img src="https://2013.igem.org/File:PB_HS_By_Role.png" width="250px"/><br />
<b>Figure 8: Sex ratios in High School iGEM by year and role. </b>On the left, the proportion of students in the High School Competition that are women for each year. On the right, the proportion of women in each role for all years. Bars represent 95% Confidence Interval.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<p><br />
To conclude, studying the iGEM competition gives a unique quantitative insight on existing questions in the field of gender studies. It also constitutes an amazing argument to convince scientists of the existence of a gender issue in science. As explained by Rascun et al in a recent paper published in PNAS, scientists believe that those type of bias only exist in some labs, not their own, therefore very objective studies need to be conducted to clearly show the reality of the numbers. More over , Jo Handelsman a microbiologist involved in that paper underlined in a recent interview, that people often think that there is still an issue in physics or maths but that there are no more women issues in biology, which is not true. This study supports strongly the view that this general thinking is untrue.<br />
</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Success"></div><br />
<h3> In iGEM, is diversity a factor of success ? </h3><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Several studies led by consulting groups (McKinsey and Company Women Matter, 2007) have shown that mixity in a team increases performance. The big question of what leads to success in iGEM was therefore investigated using the database with a special focus on gender. In order to be able to get a general idea about iGEM team success, a point system was put in place.<br />
</p><br />
<p>Points were attributed the following way.<br><br />
For the medal: 1 point for bronze medal, 2 points for silver medal, 3 points for gold medal. For the world jamboree qualified teams: 2 points for every team taking part in 2010 and before (before regional jamborees existed) , 6 points for team qualified for world final (after 2010). For special prices (Best ...): 6 points were attributed for each regional price earned (only after 2010), 13 points for each price earned in the world final (all price worth 13 points before regional jamborees existed). For the final place in world final: 15 points for the sixth team, 20 points for the fifth team, 25 points for the fourth team, 30 points for the third team, 35 points for the second team, 40 points for the firth team.</p><br />
<p><br />
The aim was to give each team a score that is proportional to the rewards it earned, taking in account that all teams were in world jamboree prior to 2011, without having to be qualified in regional jamborees.<br />
</p><br />
<p>Best score is for the Imperial College London team in 2011 (81 points).<br />
All teams (all years) average is 7.41 points, considering teams with no points (due to withdrew).</p><br />
<p><br />
Correlations studies between this number of points and other variables show that that for all teams, the main variables explaining success in iGEM is the number of years of existence and the size of the team. It would therefore seem that mixity would not be a factor. However, when looking at correlations between variables of teams who truly succeeded (points > 20) , the variables that have a significant correlation with the number of points become the sex ratio and the number of supervisors. Therefore it could be hypothesized that beginning iGEM teams have to face major challenges but when the team existed for a few years and general organization or funding problems have been dealt with , diversity could be a factor for success. </p><br />
<p><br />
In order to check if this could be seen in the best iGEM teams that existed, the sex ratio of of prize winner teams was compared to the one of participating teams with boostrap resampling giving a p-value of 0.035 This means that the sex ratio of winning teams (45%) is significantly different from the one of participating teams (37%)<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/d/de/GS_Prize.png" width="400px" ><br><br />
<b>Figure 9: Gender balance and succes in iGEM. </b> The proportion of women in teams that have won prizes in iGEM compared to the proportion in teams over all. There is a significantly higher proportion of women in teams that win prizes <b>(p=0.034)</b>.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Clues"></div><br />
<h2> Clues to improve mixity </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
<br />
Women are not as represented as men in iGEM. Why should this be a problem ? Indeed, even if it might lead to success as explained above, the need to have gender equality could be questioned. However iGEM is an international competition. One of its main goals is to attract and educate young people as well as trying to have them solve real issues. Synthetic biology might be a key technology to solve the main challenges of the 21st century.</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
<p> The world will need science and if iGEM only succeeds in motivating half of the population that could be interested, this would be a major failure to achieve its mission. Therefore, the last part of the study was aimed at understanding how could iGEM improve mixity within its own ranks.<br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div class="leftparagraph"><br />
<h3> From the data </h3><br />
<p> &nbsp;&nbsp;<br />
By looking at correlation between sex ratios and other variables, the most striking result is the link between team size and sex ratio. Teams of 2 or 3 people are almost only male teams. Even when taking out those very small teams, out of the data set the correlation holds up. This is a first lead. <br><br />
The second analysis that was made regarding the data was to compare the detailed statistics of the 100 most female teams and 100 male teams. Again, it is found that the total team member is lower for male team (9,7 vs 7,8 (p-value 0,0019) we can hypothesize that having women instructors does matter to attract girls in teams. They serve as role models. Having a woman capable of studying and realizing a synthetic biology project is a direct signal to female students that it is also possible for them to do it. Having a woman adviser might also help girls better adapt in a group and reduce their fears about having to endure constant teasing or "male " ambiance.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<h3> From a survey</h3><br />
<p> &nbsp;&nbsp;<br />
Finally, a survey was conducted among iGEMers and former iGEMers to understand their motivations and activities in iGEM. The study was designed to be unbiased and to avoid stereotype threat (for example by putting the question about gender in the end among many other pieces of information). It is still available <a href="http://bit.ly/14WykuZ"> here</a>. Participants in the survey had to rank from 1 to 5 (1 being not important, and 5 very important) answers to questions regarding personnal and professional motivations for participating in iGEM as well values and on what did they spend their time. 63 people answered among whom 32% were women.</p><br />
<br><br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/c/c5/PB_GS_Survey1.png" width="500px" /><br />
<b>Figure 10: Results of survey : what did you hope to learn in iGEM? </b>A survey was distributed to iGEM teams asking participants to rank their motivation to participate in iGEM in various subjects between 1-5. The only significant difference between the motivation of men and women in iGEM were in the subjects leading a team and leading a project.<br />
</center><br />
<br><br><br />
<p><br />
It is interesting to notice that men and women answered almost exactly the same way regarding most of the questions. Women gave a little more importance for the value of fundamental research in iGEM while men graded a bit better "Changing the world". Motivations were approximately the same as well as time spent on each activity. Just a little fact was that men considered human practices a bit more important than women did but spent a little less time on it. <br />
There is only one main difference (more than one point out of five which is represented below) : the will to lead a project and lead a team. It is striking to see how much men are more motivated to lead teams than women. This is definitely to put in relation with the number of women advisers found and the impact it can then have on teams mixity. This could reflect women lack of self esteem in some parts of their work.</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Recommendations"></div><br />
<h2> Recommendations</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Considering all the results that were presented above, here is a list of recommendations for the iGEM foundation to pursue an active policy to improve mixity in iGEM.<br />
<ul><br />
<li> Raise the number of women judges </li> <br />
<li> Promote large teams </li> <br />
<li> Write up a small paragraph to team heads to insist on the importance of motivating young women to be advisers.</li><br />
<li> Giving Bonus point when the team have women advisers </li><br />
</ul><br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>And finally, add in iGEM requirements a Gender reflection. By having teams filling out the database that was built and answering the survey and write a small paragraph about how they see mixity in their team and what it could bring, it would drastically raise the awareness of young men and women about the gender problem in science. Having an up-to-date database is also a great way to see improvements in a quantitative manner. It would allow a direct assessment of the effects of an active gender policy which would be a unique example in science. iGEM could become a leader in that fight and prepare the new generation of scientists to finally get rid of the gender inequality in science<br />
</p><br />
<br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<h2>Litterature</h2><br />
<div class="leftparagraph"><br />
<ul><br />
<li>P. Allotey, M. Gyapong Gender in tuberculosis research INT J TUBERC LUNG DIS 2008 </li><br />
<li>M. Calid, S. Rasul, S Ullah Khan, M; Saeed Gender differences in delay to s to tuberculosis diagnosis and treatment outcome<br><br />
European Commission She figures 2012<br><br />
European Commission, Mapping the gaze : getting more women to the top in Research 2008.<br><br />
</li><br />
<li>C.B. Holmes, H. Hausler, P. Hunn : A review of sex differences in the epidemiology of tuberculosis</li><br />
<li>A. N. Martinez J. T. Rhee, P. M. Small,‡M. A. Behr Sex differences in the epidemiology of tuberculosis in San Francisco INT J TUBERC LUNG DIS 4(1):26–31 2000</li><br />
<li>Moss-Racusin et al, (2012) Science faculty’s subtle gender biases favor male students PNAS </li><br />
<br />
</ul><br />
</div><br />
<div class="rightparagraph"><br />
<ul><br />
<li>McKinsey and Company Women Matter, 2007 </li><br />
<li>Olivier Neyrolles, Lluis Quintana-Murci Sexual Inequality in Tuberculosis, Plos Medicine 2009</li><br />
<li>Nosek et al. (2009) National differences in gender–science stereotypes predict national sex differences in science and math achievement. PNAS June 30, 2009 vol. 106 no. 26 10593–10597</li><br />
<br />
<li>E. Pollack Why Are There Still So Few Women in Science? NY TImes OCtober 2013</li><br />
<li>Al S. Rhines The role of sex differences in the prevalence and transmission of tuberculosis : Tuberculosis 2013</li><br />
<li>M. W. Uplekar, S. Rangan, M. G. Weiss, J. Ogden, M. W. Borgdorff, P. Hudelson Attention to gender issues in tuberculosis control INT J TUBERC LUNG DIS 4(1):26–31 2001</li><br />
</ul><br />
</div><br />
<div style="clear: both;"></div><br />
<h2>Attributions</h2><br />
<p>We would like to thank Flora Vincent, President of <a href="http://wax-science.fr/")>WAX Science</a> association for her precious help in analyzing the results, and Kim de Mora and Kitwa from the iGEM foundation, for helping spreading the survey. <p><br />
<p>This project was designed and accomplished by Aude Bernheim, Clovis Basier, Matt Deyell, Marguerite Benony and Sebastian Jaramillo in consultation with Edwin Wintermute and Ariel Lindner.</p><br />
</div><br />
</div><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Project/InfiltrateTeam:Paris Bettencourt/Project/Infiltrate2013-10-29T03:44:00Z<p>Marguerite: </p>
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<img src="https://static.igem.org/mediawiki/2013/3/3a/PB_logoParis.gif" width="122px" style="position:absolute;top:40px;right:30px;"/><br />
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<img src="https://static.igem.org/mediawiki/2013/0/00/PB_infiltratetitle.png" style="margin-bottom:15px"/><br />
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<div class="bkgr"><br />
<h2>Background</h2><br />
<p>Latent tuberculosis persists inside macrophages, where it is partially protected from both the host immune system and conventional antibiotics.</p><br />
</div><br />
<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>We expressed the enzyme Trehalose Dimycolate Hydrolase (TDMH) in <i>E. coli</i> and showed that it is highly toxic to mycobacteria in culture.</li><br />
<li>We expressed the listeriolyin O (LLO) gene in <i>E. coli</i> and showed that it is capable of entering the macrophage cytosol.</li><br />
<li>We co-infected macrophages with both mycobacteria and our engineered <i>E. coli</i> to characterize the resulting phagocytosis and killing.</li><br />
<li> We measured the effect of a range of pH (from 3 to 8,8) on <i>M. smegmatis</i> and the TDMH enzyme activity.</li><br />
</ul><br />
</div><br />
<div class="biocriks"><br />
<h2>BioBricks</h2><br />
<ol><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137008" target="_blank">BBa_K1137008 (TDMH)</a></li><br />
</ol><br />
</div><br />
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<div class="aims"><br />
<h2>Aim</h2><br />
<p>To create an <i>E. coli</i> strain capable of entering the macrophage cytosol and delivering a lytic enzyme to kill mycobacteria.</p><br />
</div><br />
<a href="#Introduction"><br />
<div class="hlink"><br />
<h2>Skip to Introduction</h2><br />
</div><br />
</a><br />
<a href="#Design"><br />
<div class="hlink"><br />
<h2>Skip to Design</h2><br />
</div><br />
</a><br />
<a href="#Killing"><br />
<div class="hlink"><br />
<h2>Skip to Killing Assay</h2><br />
</div><br />
</a><br />
<a href="#Macrophages"> <br />
<div class="hlink" style="margin-right:0px"><br />
<h2>Skip to Drug Delivery</h2><br />
</div><br />
</a><br />
<div style="clear: both;"></div><br />
</div><br />
<div id="Introduction"></div><br />
<h2>Introduction</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
<i>Mycobacterium tuberculosis</i> (Mtb), the bacterium responsible for tuberculosis (TB), spreads by aerosol and infects its host through the airways. The bacterium is phagocytosed by macrophages in the lung, yet often evades death in the lysosome. Mtb can persist for years or even decades inside macrophages by inhibiting phagosome/lysosome fusion and supressing the normal acidification of the lysosome.</p><br />
<p>An efficient treatment for persistent TB must enter infected macrophages and kill the pathogen there. In our system, <i>E. coli</i> is both the vector and the therapeutic agent agent by expressing the listeriolyin O gene LLO to enter macrophages and TDMH to kill mycobacteria. Additionally we thought about how we could deliver the E. coli to the lungs and decided that the most effective way would be through an inhaler.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<div style="width:90%;margin-left:5%;border:2px solid;"><br />
<h4>&nbsp;BOX 1: Why is it difficult to treat tuberculosis?</h4><br />
<ul style="width:90%"><br />
<li>Mtb can survive and replicate for years inside the macrophages by supressing the normal process of phagocytosis.</li><br />
<li>The cell wall of <i>M. tuberculosis</i> is thick, waxy and rich in mycolic acids. It it difficult to penetrate with a small-molecule drug.</li><br />
<li>The pathogen grows very slowly inside macrophages. Most conventional antibiotics target processes like DNA replication that are specific to growing cells.</li><br />
</ul><br />
</div><br />
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<center><a href="https://static.igem.org/mediawiki/2013/1/1d/PB_inhalorinfiltrate.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/1/1d/PB_inhalorinfiltrate.png" width="1100"/></a></center><br />
<br><br><br />
<br />
<div id="Design"></div><br />
<h2>TDMH and the mycobacterial cell wall</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;Mycobacterium species share a characteristic cell wall: thick, waxy, hydrophobic, and rich in mycolic acids. The low permeability of the envelope to hydrophilic solutes contributes to the intrinsic drug tolerance in mycobacteria.</p><br />
<p><br />
&nbsp;&nbsp;Trehalose Dimycolate Hydrolase (TDMH) is a cutinase-like serine esterase that triggers rapid lysis of the mycobacterial cell wall by degrading the mycolate layer. The enzyme was first isolated from <i>Mycobacterium smegmatis</i> and subsequently shown to hydrolyze purified TDM from various mycobacterial species. Exposure to TDMH triggers an immediate release of free mycolic acids, ultimately leading to lysis of many mycobacteria including Mtb (Yang et al. 2012).<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;We have used <i>M. smegmatis</i> as a model system because Mtb are highly pathogenic and difficult to culture in the lab. <i>M. smegmatis</i> is a close relative of Mtb, shares many of its membrane properties, and is commonly used as a stand-in for Mtb physiology in the lab.</p><br />
<p>&nbsp;&nbsp;In our system, described in the methods below, we used <i>E. coli</i> BL21 (DE3) as a chassis to express TDMH from an IPTG-inducible strong T7 promoter.</p><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div id="Killing"></div><br />
<h2>Killing mycobacteria with TDMH</h2><br />
<div class="leftparagraph"><br />
<p><br />
&nbsp;&nbsp;Figure 1 describes how we performed the setup of our experience by making a coculture of <i>M.smegmatis</i> and <i>E.coli</i>.</p><br />
<p>Figure 2(below) shows the killing of <i>M. smegmatis</i> with TDMH expressed by <i>E. coli</i>. We mixed liquid cultures of <i>E. coli</i> and <i>M. smegmatis</i> at equal cell densities as determined by plating assays. When expression of TMDH was induced with IPTG, nearly 99% of the <i>M. smegmatis</i> were killed within six hours. We saw no change in viability in cultures of <i>M. smegmatis</i> alone or when mixed with uninduced <i>E. coli</i>.</p><br />
<p><br />
&nbsp;&nbsp;We next sought to quantify the effectiveness of TDMH killing. We mixed induced<i> E. coli</i> and mycobacteria in different ratios and used plating assays to measure viability. As shown in figure 3 mycobacterial killing displayed dose dependence on the <i>E. coli</i> cell density. Small numbers of <i>E. coli</i> could kill many mycobacteria. For example, in mixed populations with 100 mycobactera for each <i>E. coli</i>, we still observed >50% mycobacterial killing after 2 hours. This indicates that, on average, each <i>E. coli</i> produced enough TDMH to kill 50 mycobacteria. We reason that this killing may be even more effective inside macrophages, where constrained volumes will increase the effective TDMH concentration.</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><a href="https://static.igem.org/mediawiki/2013/d/d9/PB_FigIva.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/d/d9/PB_FigIva.png" width="70%" style="margin-top:-50px"/></a></center><br />
<p><b>Figure 1</b> Experimental setup of the <i>M. smegmatis</i> killing assay.<div style="font-size:90%"> <i>M. smegmatis</i> and <i>E.coli</i> cells (Uninduced and induced with various concentrations of IPTG) were cultured up to OD 1,then serially diluted. Equal volumes of <i>E.coli</i> and <i>M. smegmatis</i> cultures of the same dilutions were mixed, incubated for 6 hours, and plated at 0,3 and 6 hours. </div></p><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<a href="https://static.igem.org/mediawiki/2013/a/a7/PB_Fig1_Myco_Kill_Curve.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/a/a7/PB_Fig1_Myco_Kill_Curve.png" width="100%"/></a><br />
<p><b>Figure 2</b> TDMH-expressing <i>E.coli</i> kill mycobacteria in culture.<div style="font-size:90%"> We mixed TDMH-expressing <i>E.coli</i> and WT <i>M. smegmatis</i> in LB media at an initial cell density of 107 cells/ml each. Plating assays were used to count specifically <i>M. smegmatis</i> after the indicated times. When TDMH-expression was fully induced with 1 mM IPTG, more than 98% of mycobacteria were killed after 6 hours (red line). Populations of mycobacteria alone (black line) and mycobacteria mixed with uninduced <i>E.coli</i> (blue line) were stable.</div></p><br />
</div><br />
<div class="rightparagraph"><br />
<center><a href="https://static.igem.org/mediawiki/2013/e/e0/PB_Fig2_Coli_Kill_Ratios.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/e/e0/PB_Fig2_Coli_Kill_Ratios.png" width="100%"/></a></center><br />
<p><b>Figure 3</b> Dose-dependence in killing of mycobacteria by <i>E. coli.</i><div style="font-size:90%">We mixed <i>M. smegmatis</i> at a density of 10<sup>7</sup> cells/ml with <i>E. coli</i> at densities of 10<sup>5</sup> cells/ml (blue line) 10<sup>6</sup> cells/ml (green line) or 10<sup>7</sup> cells/ml to produce the ratios above. Even low densities of <i>E. coli</i> produced significant killing. Uninduced <i>E. coli</i> produced no significant killing.</div></p><br />
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<h2></h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;We investigated further the mechanism of TDMH-mediated cell killing. The TDMH enzyme in our system does not carry a secretion tag. Therefore, lysis of the <i>E. coli</i> membrane is probably required for the protein to reach (and lyse) <i>M. smegmatis</i>. We used plating assays to investigate the effect of TDMH induction on <i>E. coli</i> viability and Bradford assays to measure released protein. The results are presented in figure 4.</p><br />
<p>Figure 4A shows that inducing TDMH-expressing <i>E. coli</i> with IPTG rapidly kills the <i>E. coli.</i> In figure 4B, we show that inducing TDMH expression increases the concentration of free protein in the media. In our model, TDMH induction leads to spontaneous lysis of TDMH-expressing <i>E. coli</i>. This could be simply due to the extremely high protein expression levels driven by the T7 promoter, or it may be partially due to the esterase activities of the TDMH enzyme. Once the TDMH is released from the <i>E. coli</i> it is free to act on mycobacterial membranes, causing lysis and the release of additional proteins.<br />
</p><br />
</br><br />
<p><b>Figure 4</b> Induction of TDMH kills <i>E. coli</i> and releases protein to the media.<div style="font-size:90%"><b>A)</b>Plating assays were used to determine <i>E. coli</i> viability in LB media after the indicated times. TDMH-induced <i>E. coli</i> rapidly lost viability (red line) Uninduced <i>E. coli</i> grew normally following a lag phase (black line).<b>B)</b>Bradford assays were used to measure free protein concentrations in mixed and induced bacterial cultures. When <i>E. coli</i> and mycobacteria are mixed and TDMH-expression is induced, free protein concentrations increase. This is consistent with a model in which TDMH induction leads to the lysis of the <i>E. coli</i> membrane. Action of TDMH on mycobacteria leads to further lysis and protein release.</div></p><br />
</div><br />
<div class="rightparagraph"><br />
</br></br></br></br></br><br />
<center><a href="https://static.igem.org/mediawiki/2013/7/74/PB_Fig3_Coli_Protein_Curve.png" target="_blank"><img width="100%" src="https://static.igem.org/mediawiki/2013/7/74/PB_Fig3_Coli_Protein_Curve.png"/></a></center> <br />
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<div id="Macrophages"></div><br />
<h2>Programmed drug delivery with LLO</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<i>Listeria monocytogenes</i> is a bacterial pathogen that replicates in the cytosol of mammalian cells. The pathogen is initially internalized in host phagosomes, then lyses them to obtain access to the cytosol. A single gene, LLO, is responsible for this activity and is sufficient to convey the phenotype to <i>E. coli</i>.<br />
</p><br />
<p>The LLO protein is activated by the low pH of the lysosme. By forming large pores in the lysosomal membrane, it allows protein delivery to the cytosol of macrophages (Higgins et al. 1999). Using <i>E. coli</i> as a protein vector means we don't need to isolate and purify the TDMH enzyme. </p><br />
<p>We hypothesized that a bacterial delivery system could be efficient and specific in targeting mycobacterial-infected macrophages. In effect, we might take advantage of the natural tendency of macrophages to phagocytose <i>E. coli</i> and their enzymatic payload.</p><br />
<p>Because LLO expression is known to be associated with Listeria pathogenicity, we took extra precautions in our cloning and experiments. These measures are detailed on our team safety page. Briefly, we worked in a Biosafety Level 2 lab under the supervision of two full-time lab managers. We researched and complied with French national and insitutional biosafety rules as they apply to this gene.</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><img src="https://static.igem.org/mediawiki/2013/b/b7/PB_Killing_assay_macrophages1.png" width="80%"/></center><br />
<p><b>Figure 5</b> Experimental design of the killing assay inside the macrophages. We infected them with <i>M. smegmatis</i> and washed after 1 hour. Then, we infected them with <i>E. coli</i> and washed after 1 hour. The end of this final infection step refers to the time 0 on our graphs. At this time we started the observation under the microscope</p><br />
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<h2><i>E. coli</i> and <i>M. smegmatis</i> coinfections</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;Figure 6 displays J774 macrophages one hour after coinfection with <i>E. coli</i> and <i>M. smegmatis</i>. As described in the methods, the <i>E. coli</i> express TDMH and LLO and fluorescent mRFP as a label. The <i>M. smegmatis</i> express GFP as a label, but are otherwise wild type.</p><br />
<p>The two movies displayed in figure 7 are time-lapse microscopy of live coinfected macrophages collected over a period of 6 hours. Fluorescence patterns revealing the localization of <i>E. coli</i> and <i>M. smegmatis</i> within the macrophages are relatively stable over this time period.</p><br />
</div><br />
<div class="rightparagraph"><br />
<p> We next applied quantitative microscopy to characterize the behavior of our system inside live macrophages. We imaged macrophage populations under several conditions and time points and scored their rates of infection with <i>E. coli</i>, <i>M. smegmatis</i> or both. In all we scored over 13,000 individual cells collected from more than 100 separate images.</p><br />
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<div class="leftparagraph"><br />
<center><a href="https://static.igem.org/mediawiki/2013/5/52/PB_Fig4_Fresh_coinfection.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/5/52/PB_Fig4_Fresh_coinfection.png" width="100%"/></a></center><br />
</br><br />
<a href="https://static.igem.org/mediawiki/2013/5/51/PB_Fig4_Fresh_coinfection_zoom1.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/5/51/PB_Fig4_Fresh_coinfection_zoom1.png" width="48%"/></a><br />
<a href="https://static.igem.org/mediawiki/2013/c/c1/PB_Fig4_Fresh_coinfection_zoom2.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/c/c1/PB_Fig4_Fresh_coinfection_zoom2.png" width="48%" style="margin-left:3%"/></a><br />
<br />
<p><b>Figure 6</b> Coinfection of J774 macrophages with mycobacteria and <i>E. coli</i> expressing TDMH and LLO<div style="font-size:90%"> <i>E. coli</i> (red) express mRFP as a marker and <i>M. smegmatis</i> (green) express GFP as a marker. Macrophages are observed to take up Mycobateria, <i>E. coli</i>, neither or both. This image was collected one hour after introducing the bacteria to the macrophage culture and following extensive washing to remove free bacteria.</div></p><br />
</div><br />
<div class="rightparagraph"><br />
<iframe frameborder="0" style="margin-bottom:20px;" width="535" height="300" src="http://www.dailymotion.com/embed/video/x15jnu6"></iframe><br />
<iframe frameborder="0" width="535" height="300" src="http://www.dailymotion.com/embed/video/x15jnv8"></iframe><br />
<p><b>Figure 7</b> Temporal dynamics of macrophages coinfected with <i>E. coli</i> and <i>M. smegmatis.</i><div style="font-size:90%"><i>E. coli</i> and <i>M. smegmatis</i>, expressing mRFP and GFP respectively, were introduced to J774 macrophages. Fluorescent and bright field images were collected every 15 minutes for 6 hours. In these movies, the <i>E. coli</i> also express TDMH and LLO. Macrophages are observed to uptake <i>E. coli</i>, <i>M. smegmatis</i>, neither or both. The fluorescence patterns appear stable for these conditions and time period.</div></p><br />
<br />
</div><br />
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<br />
<h2>pH influence </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;We wanted to study the pH influence on <i>M. smegmatis</i> growth and on TDMH enzyme activity. We know that the phagosomal pH is usually acid (around 6) but can reach 4,5. We wondered if TDMH enzyme was working at this range of pH.</p><br />
<p>We studied 7 different buffers : 3 ; 4,5 ; 5,1 ; 6,4 ; 7,35 ; 8,2 and 8,8. </p><br />
<br />
<p>Figure 8 shows the activity of TDMH enzyme at various pH levels.</p><br />
<br />
<p>Mycobacteria was unable to grow at pH 3 with or without the presence of TDMH. Therefore we are unable to make any conclusions regarding the activity of the enzyme at very low pH values.</p><br />
<br />
<p>TDMH activity was active across a large range of pH from 4.5 to 8.8, though there was a small decrease in efficiency observed at pH 8.2. This is a promising result due to the difference in pH between the phagosome and the cytosol. Additionally, the high activity of TDMH even at low pH is promising as it will be required to function at low pH inside the phagosome.<br />
</p><br />
<br />
<br />
</div><br />
<div class="rightparagraph"><br />
<br />
<center> <img src="https://static.igem.org/mediawiki/2013/e/e4/PB_TBC_PH_indepedence.png" width="60%"/></center> <p><b>Figure 8</b> pH influence on TDMH enzyme activity <div style="font-size:90%"> We add to <i>M.smegmatis</i> the proteins of an induced control, the uninduced strain of Bl21 and the induced strain producing TDMH.</div></p><br />
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<h2>Conclusions and continuing work</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;We have shown that <i>E. coli</i> can effectively kill mycobacteria in culture by expressing the TDMH enzyme, now a BioBrick. We have further shown that <i>E. coli</i> and mycobateria may co-localize within macrophages, where LLO-based systems can effectively deliver protein payloads.</p><br />
<p>In the coming weeks, we will continue to refine our cell culture techniques to precisely characterize the effectiveness of our system <i>in situ</i>, within the living macrophage.</p><br />
<p><b>Figure 9</b> The effect of TDMH-induced <i>E. coli</i> on macrophage infection rates after 3 hours.<div style="font-size:90%">We scored fluorescence microscopy images of macrophages exposed to both <i>E. coli</i> and <i>M. smegmatis</i> expressing fluorescent protein markers. The <i>E. coli</i> expressed LLO and were induced or uninduced for TDMH expression. For both treatments, we observed an increase in the infection rates of both bacteria after 3 hours. We attribute this to combination of the media with free bacteria, which macrophages continue to consume over the course of the experiment. TDMH induction slowed the increase in <i>E. coli</i> infection rates, which is likely due to the toxic effects of TDMH expression on <i>E. coli</i>, as shown in figure 4.</div></p><br />
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<div class="rightparagraph"><br />
<center><img src="https://static.igem.org/mediawiki/2013/1/15/PB_Fig6_Image_Counts.png" width="80%"/></center><br />
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<br />
<h2>Bibliography</h2><br />
<ul><br />
<li>Yang Y, Bhatti A, Ke D, Gonzalez-Juarrero M, Lenaerts A, Kremer L, Guerardel Y, Zhang P, Ojha AK (2012) : Exposure to a cutinase-like serine esterase triggers rapid lysis of multiple mycobacterial species. J Biol Chem. 2013 Jan 4;288(1):382-92.</li><br />
<li>Rajesh Jayachandran, Varadharajan Sundaramurthy, Benoit Combaluzier , Philipp Mueller, Hannelie Korf, Kris Huygen, Toru Miyazaki, Imke Albrecht, Jan Massner, Jean Pieters (2007) : Survival of Mycobacteria in Macrophages Is Mediated by Coronin 1-Dependent Activation of Calcineurin. Cell, Volume 130, Issue 1, 13 July 2007, Pages 12-14 </li><br />
</ul><br />
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<h2>Attributions</h2> <br />
<br />
<p>pET21 1519 plasmid was kindly provided by Anil Ojha of the University of Pittsburgh.</p><br />
<p> Murine cell line macrophages J774 were a gift from Nicole Guiso and Nicolas Hegerle from Pasteur institute (Unit of Molecular Prevention and Therapy of Human Diseases. </p><br />
<p> <i>Mycobacterium smegmatis</i> was a gift from Brigitte Gicquel from Pasteur institute (Unit Mycobacterial genetics). </p><br />
<p> <i>Mycobacterium smegmatis</i> expressing GFP was kindly provided by Stephane Canaan from CNRS (Laboratory of Enzymology at Interfaces and Physiology of Lipolysis). </p><br />
<p>The project itself was designed and accomplished by Camélia Bencherif and Iva Atanaskovic with consultation with Edwin Wintermute, Mathias Toulouze and Ariel Lindner.</p><br />
<p> We also discussed the project with Christopher Anderson from Berkeley University (Synthetic biology Anderson lab) about the feasibility, good points and critical points of the project. </p><br />
<p> We want to thank all these people that made Infiltrate project happen !</p><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_StudyTeam:Paris Bettencourt/Human Practice/Gender Study2013-10-29T03:42:14Z<p>Marguerite: </p>
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<h2>Background</h2><br />
<p>Science suffers from gender bias</p><br />
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<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>Revealed gender bias in synthetic biology by studying sex ratios in SB conferences and labs</li><br />
<li>Built a database of all iGEM teams reporting all available online information and sex ratios of teams and advisors</li><br />
<li>Conducted a statistical analysis of this data-set and showed among other results that success in iGEM is correlated to gender mix</li><br />
<li>Made recommendations to implement an active gender policy in iGEM</li><br />
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<div class="aims"><br />
<h2>Aims</h2><br />
<p>To investigate gender dynamics in iGEM and in synthetic biology research community at large in a quantitative manner</p><br />
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<h2>Skip to Introduction</h2><br />
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<h2>Skip to Recommendations</h2><br />
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<h2>Skip to Database</h2><br />
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<h2>Skip to Main Findings</h2><br />
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<h2>Skip to Gender Bias in SynBio</h2><br />
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<h2>Skip to iGEM Diversity and Success</h2><br />
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<h2>Skip to Clues to Improve Balance</h2><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Facts"><br />
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<h2 style="font-size:24px;">Infographics on gender and Synthetic Biology</h2><br />
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<div id="Introduction"></div><br />
<h2>Introduction</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
For every woman killed by TB, there are two men. Our review of the literature on gender bias and tuberculosis can be found <a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Study/Gender_Bias">here</a>. If a disease can be biased, what about ourselves? iGEM? Synthetic biology? Gender bias in science may appear in different forms. Gender balance varies by discipline, by job title, by age or by region. Only 30% of researchers in Europe are women, while 92% of French university deans are men. </p> <p>Hisorically, gender bias has affected the lives of scientists and the practice of science. However, assessing gender bias today in a living community is very difficult. History, stereotypes, limits of the disciplines, and the simple lack of data can prevent us, the synthetic biologists, from thinking about our own relationship to gender.</p><br />
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<div class="rightparagraph"><br />
<p><br />
Most of those issues should not apply in synthetic biology. Synthetic biology is a new field. The argument of the heritage of some habits cannot be made. It is a mix of previously existing disciplines and therefore very open and should not reflect preexisting stereotypes. To study gender bias in iGEM and in synthetic biology we decided to follow a data driven approach. Studying in a quantitative manner this subjects had two main benefits. First it prevented us to apply our own biases and stereotypes on this subject. Secondly, it lead us to construct data base that we make freely available and let anyone test his own hypothesis on this controversial subject and form his own conclusions.</p><br />
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<div id="SynBio"></div><br />
<h2> Synthetic biology field : general overview of gender equality in synthetic biology </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Gender repartition in synthetic biology can be looked at from different perspectives. For this study, two main ways were chosen: composition of labs and conferences. The main reasons for those choices were the accessibility of online data </p><br />
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<div class="rightparagraph"><br />
<p><br />
as well as the necessity to get information not only about the general gender balance but also the sex ratio inside a defined category: PhD students, post docs, head of labs... </p><br />
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<h2> Synthetic biology labs, a good representation of gender (in)equality in science </h2> <br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Teams of 50 synthetic biology labs were studied. The labs were chosen by their presence on the webpage http://syntheticbiology.org/Labs.html . For each lab, several numbers were reported in a table : total number of people in the team, number of women in the team, number of PhD students, post docs, head of labs, number of women PhD students, post docs, head of labs. From this, the sex ratios (number of women / total number of people) were then calculated for each of those categories. </p><br />
<p><center><a href="https://2013.igem.org/File:ParisB2013_Synthetic_Biology_Research_Groups.xls">Download the database here</a></center></p> <br />
<p><br />
The first conclusion that can be made is that women are generally under-represented in synthetic biology labs. 33% correspond to the average presence of women in research in Europe. Indeed according to the European Commission, 32% of researchers in Europe are women <i>(She Figures, 2012)</i>. <br><br>The second finding also reflects well an already known reality in science : the glass ceiling. In 1995, the glass ceiling was defined by the U.S. Department of Labor, as a <i>"political term used to describe "the unseen, yet unbreakable barrier that keeps minorities and women from rising to the upper rungs of the corporate ladder, regardless of their qualifications or achievements" </i>.<br />
With only 17,85\% of heads of labs being women, synthetic biology is still doing slightly better than the average. According to a European study done in 2008 called <i>Mapping the maze,getting women to the top in research</i>., only 15% of women occupy top research position in Europe. However, the number of SB P.I. should be analyzed through the filter of history. In a new field, it would be expected in a world where bias would not be present anymore to have way more women at those positions.<br />
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<center><br />
<img src="https://static.igem.org/mediawiki/2013/4/46/PB_GS_LabsBis.png" width="353px"/><br><br />
<b>Figure 1:Sex ratio in synthetic biology labs</b>. The percentage of women by role in 50 synthetic biology labs. Error bars represent SD. The sex ratio of each lab is determined independently and then the mean of the labs was determined.<br />
</center><br />
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<center><br />
<TABLE BORDER="1"> <br />
<CAPTION> </CAPTION> <br />
<TR> <br />
<TH>Labs </TH> <br />
<TH> Phd Students </TH> <br />
<TH> Post Docs</TH> <br />
<TH> Head of Labs </TH> <br />
</TR> <br />
<TR> <br />
<TH> 33,10 % </TH> <br />
<TD> 35,39 % </TD> <br />
<TD> 31,31 % </TD> <br />
<TD> 17,85 % </TD> <br />
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<h2> Speakers at SB Conferences : effects of an active gender policy</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
SBX.0 conferences accompanied the development of synthetic biology. They provide a great way to investigate the evolution of gender ratio since the birth of synthetic biology. Moreover, the presence/absence of women as speakers is a known indicator of gender bias and specially of active gender policy. Indeed, several social mechanisms are in place lead to fewer female speakers that could be expected: self censorship, unconscious stereotypes, unconscious choice of only male speakers... However, having female speakers at conference is a key point. It allows women, to gain confidence but also to act as role model for women attending the conference. </p><br />
<p><br />
To study SB conferences, available programs online were downloaded. Data referring to the number of speakers but also to posters were recorded. The data-set could not be completed for certain years due to the impossibility of finding the data online.<br />
</p><br />
<p><center><a href="https://2013.igem.org/File:ParisB2013Resultats_SB.xls">Download the database here</a></center></p><br />
<p><br />
The sex ratio of the speakers have followed a very interesting evolution. It has been multiplied by 3 from SB1 to SB5. This could indicate a change of policy considering speakers. Most likely, the first conferences invited speakers without taking into consideration the gender dimension. Might it be due to some complaints or the raise in awareness of the conferences organizers, the numbers went up. This example is interesting because it clearly show an interest in the subject by the involved community.<br />
</p><br />
<p><br />
Two main conclusions can be drawn on posters. First, the sex ratio of authors in posters has changed throughout the years. Secondly, this number is not as high as the sex ratio in labs. The question is why? The points described above could be underlying reasons, however it is very difficult to truly go beyond this with only those numbers. <br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<br><br><br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/6/62/PB_GS_Sex_ratio_in_SB_Conf.png" width="400px"/><br><br />
<b> Figure 2:Sex ratio in SB conferences</b>. The proportion of speakers and poster presenters at SBX.0 conferences who are women. Data was gathered on-line from available programs.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<h2> Under represented and badly represented</h2> <br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
In order to try to better understand the dynamics of gender behind the posters numbers, the rank of authors were reported for each poster. Sex ratio were calculated for each rank, keeping in mind that in biology, the first author is often a Phd student or a post doc and the last author, the P.I.<br />
</p><br />
<p><br />
As explained above, women are generally under-represented in synthetic biology labs, even less represented at conferences. When looking at the rank of author in posters, another bias appears. Indeed, women are more likely to be present as middle authors than first or last. This bias can be found in papers of different disciplines as shown on the graph realized on the eigenfactor.</p><br />
<p> <br />
The main finding considering gender in synthetic biology is that even though synthetic biology is new and interdisciplinary, it remains quite representative of existing gender bias in science. Therefore it can be concluded, that the issues that have kept women out of science and especially out of top research position are still present and will not be resolved with time. A strong and active policy appears necessary to bring more mixity and therefore diversity in this field.<br />
<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/6/6b/PB_GS_Author_place_.png" width="435px"/> <br><br />
<b>Figure: Sex ratio according to rank of authors in SB posters.</b> Authorship on Posters in SB conferences was collected and Women and Male authors are organized by their rank of authorship. Women tend to be middle authors more often then first or last authors.<br />
</center><br />
<br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/2/28/PB_GS_Eigenfactor.png" width="535px"/><br />
<b>Figure 4: Analysis of rank of authors according to gender in scientific publications.</b>Women's rank of authorship in various journals and databases. There is over-all far more men cited as authors than women, and this is consistent across publications and scientific fields. Additionally, Authorship rank is shown on the bottom with the % of women over all shown as the solid line with the dot indicating the % of women within that authorship rank. Dots above the line indicate that women are over represented compared to the mean and dots below the line indicate that women are underrepresented, with the further they are from the line the greater the imbalance.<br />
</center> <br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Database"></div><br />
<h2> iGEM as a model : a fantastic database </h2><br />
<div class="leftparagraph"><br />
<h3> Online Data</h3> <br />
<p> &nbsp;&nbsp;<br />
All the data concerning iGEM were retrieved from the website : <a href="https://igem.org">https://igem.org</a> <br />
List of teams were retrieved from the webpages <a href="https://igem.org/Team_List.cgi?year=2012">https://igem.org/Team_List.cgi?year=2012</a>.<br />
List of project themes were retrieved from <a href="https://igem.org/Team_Tracks?year=2012">https://igem.org/Team_Tracks?year=2012</a>.<br />
List of prices were retrieved <a href="https://igem.org/Results">https://igem.org/Results</a>.<br />
List of judges were retrieved from: <a href="https://igem.org/Judge_List">https://igem.org/Judge_List</a><br />
</p><br />
<h3> Sex ratio determination :</h3> <br />
<p> &nbsp;&nbsp; For each team, the official team profile was checked to count the number of student members, advisors and instructors.<br />
Then to determine the sex of particpants, wiki were used when names were not obvious, using pictures when they existed. When no pictures were available and names were not obviously referring to one sex, a google image search was done on the name (first and last name) and the sex was chosen as the most represented sex in the pictures (if 10 images of men come up and 30 of women, the participant was considered as a woman).</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
<h3> Database : </h3> <br />
<p> &nbsp;&nbsp; Information for the first year of iGEM were difficult to find because of the non existence of available wiki pages and it was therefore decided not to take into account this year.<br />
Teams who withdrew during the competition were not taken into account since it was most of the time impossible to know the number of participants due to the absence of wiki.<br />
In the end our data set is composed of 662 teams over 5 years. For each team were reported : <br />
Year ; region ; name of the team ; number of student members ; number of women student members ; number of advisors ; number of women advisors ; number of instructors ; number of women instructors ; participation to MIT championship ; medal ; regional prices ; championship prices ;tracks. </p><br />
<p><br><br />
<center><br />
<a href="https://static.igem.org/mediawiki/2013/3/35/PB_GS_IGEMdatabase.xls"><br />
<img src="https://static.igem.org/mediawiki/2013/b/b1/PB_downloadGD.png" width="530"/></a><br />
</center><br><br />
</p><br />
<h3> Attrition by Career Stage</h3><br />
<p> &nbsp;&nbsp; With the introduction of High School iGEM competition, We have quantitative data about gender balance through career progression. By observing trends between the High School Division, Undergraduate and Overgraduate Divisions, Advisors and finally Judges; we can identify potential glass ceilings and find out why women are being lost through various career stages.</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Findings"></div><br />
<h2> iGEM : a mirror of main gender problems </h2><br />
<div class="leftparagraph"><br />
<h3> Teams sex ratio, a very robust value </h3> <br />
<p> &nbsp;&nbsp;<br />
<br><br><br />
The first thing that was examined was the evolution of sex ratio of teams in iGEM across continents and throughout the years.<br />
</p><br />
<br><br />
<p><br />
The striking conclusion of this comparison is that the sex ratio is iGEM teams remains constant through the years and across continents (ANOVA's p-value for the different conditions > 0,5). This shows that women are underrepresented in iGEM teams. </p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/5/5a/GS_Year.png" width="250px"/><br />
<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Region.png" width="250px"/><br />
<b>Figure 5: Sex ratio of iGEM teams through the years and across continents.</b> The proportion of team members of each gender over time and between regions in the collegiate iGEM competition. Bars represent the 95% Confidence interval.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div class="leftparagraph"><br />
<h3> Women do not supervise as much as men </h3> <br />
<p> &nbsp;&nbsp;<br />
The second question investigated was the sex ratios for the different categories of people participating in iGEM. Indeed, iGEM is not only undergrad students. Advisors, instructors, judges also participate representing the complete professional ladder of synthetic biology. A category called Supervisors was created corresponding to instructors and advisers. Indeed, those terms are not understood and used in the same way in different continents. In some countries "advisers" means people who directly teach the teams (mostly grad students and post docs) whereas it means general mentors for others and vice versa.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Role.png" width="300px" height="250px"/> <br><br />
<b>Figure 6: Sex ratios in iGEM according to categories of people participating.</b> The gender balance of students, Supervisors and Judges in iGEM collegiate competitions. Supervisors is taken as the combination of advisors and instructors due to variations on how individual teams differentiate between them. Bars are 95% confidence intervals.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
When executing comparisons tests , team members' sex ratio is found to be different from judges' and instructors' ones (p value < 0,01). However judges and advisers are not significantly different ( p value > 0,5). This result reveals a tendency of women to supervise less than men. Indeed, from team members to instructors, the sex ratio is divided by two. What is even more interesting is to compare those numbers to sex ratios of PhD students and post docs in labs. The sex ratio of instructors is 10 points lower. </p><br />
<p> Women constitute a pool of talent that is not mobilized. They participate but do not supervise teams. They are "lost" along the way. Indeed, in a study published last year in PNAS, researchers showed that P.I. were less prone to have a woman mentoring students than man. This unconscious bias can be translated by a lack of encouragement from P.I.s but also by a self censorship which is not taken into account by other supervisors as explained in an recently published article by Eileen Pollack (E. Pollack Why Are There Still So Few Women in Science? NY TImes October 2013).<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<h3> Tracks and sex ratio in iGEM </h3> <br />
<p> &nbsp;&nbsp;<br />
The third finding goes against an often-heard stereotype "women are more interested by applied research". In order to investigate this subject, tracks were reported for each project. In iGEM tracks correspond to general theme of the project : medicine, fundationnal research…Tracks were then looked at in terms of sex ratios. There is no significant difference between tracks. (ANOVA > 0,1).</p><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/a/ac/PB_GS_Sexratiotracksbis.png" width="535px"/><br />
<b>Figure 7: Sex ratios and tracks in iGEM. </b>The proportion of gender in teams grouped by the track that the team is entered in during collegiate iGEM competitions. There is no statistical significant difference between the gender balance between tracks. <br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<h3> High School Division is more balanced</h3><br />
<p> When we looked at the High School Divison, we found that it had a higher percentage of women than the university iGEM teams. Additionally, The number of female advisors and instructors in the High School division is much higher than that of the Collegiate division and is approximately the same as the proportion of students. This indicates that there is a problem at the Collegiate level and that iGEM can be an important bridge for women to access new opportunities to lead in higher education</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/9/91/PB_HighSchool_Gender_Students.png" width="250px"/><br />
<img src="https://2013.igem.org/File:PB_HS_By_Role.png" width="250px"/><br />
<b>Figure 8: Sex ratios in High School iGEM by year and role. </b>On the left, the proportion of students in the High School Competition that are women for each year. On the right, the proportion of women in each role for all years. Bars represent 95% Confidence Interval.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<p><br />
To conclude, studying the iGEM competition gives a unique quantitative insight on existing questions in the field of gender studies. It also constitutes an amazing argument to convince scientists of the existence of a gender issue in science. As explained by Rascun et al in a recent paper published in PNAS, scientists believe that those type of bias only exist in some labs, not their own, therefore very objective studies need to be conducted to clearly show the reality of the numbers. More over , Jo Handelsman a microbiologist involved in that paper underlined in a recent interview, that people often think that there is still an issue in physics or maths but that there are no more women issues in biology, which is not true. This study supports strongly the view that this general thinking is untrue.<br />
</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Success"></div><br />
<h3> In iGEM, is diversity a factor of success ? </h3><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Several studies led by consulting groups (McKinsey and Company Women Matter, 2007) have shown that mixity in a team increases performance. The big question of what leads to success in iGEM was therefore investigated using the database with a special focus on gender. In order to be able to get a general idea about iGEM team success, a point system was put in place.<br />
</p><br />
<p>Points were attributed the following way.<br><br />
For the medal: 1 point for bronze medal, 2 points for silver medal, 3 points for gold medal. For the world jamboree qualified teams: 2 points for every team taking part in 2010 and before (before regional jamborees existed) , 6 points for team qualified for world final (after 2010). For special prices (Best ...): 6 points were attributed for each regional price earned (only after 2010), 13 points for each price earned in the world final (all price worth 13 points before regional jamborees existed). For the final place in world final: 15 points for the sixth team, 20 points for the fifth team, 25 points for the fourth team, 30 points for the third team, 35 points for the second team, 40 points for the firth team.</p><br />
<p><br />
The aim was to give each team a score that is proportional to the rewards it earned, taking in account that all teams were in world jamboree prior to 2011, without having to be qualified in regional jamborees.<br />
</p><br />
<p>Best score is for the Imperial College London team in 2011 (81 points).<br />
All teams (all years) average is 7.41 points, considering teams with no points (due to withdrew).</p><br />
<p><br />
Correlations studies between this number of points and other variables show that that for all teams, the main variables explaining success in iGEM is the number of years of existence and the size of the team. It would therefore seem that mixity would not be a factor. However, when looking at correlations between variables of teams who truly succeeded (points > 20) , the variables that have a significant correlation with the number of points become the sex ratio and the number of supervisors. Therefore it could be hypothesized that beginning iGEM teams have to face major challenges but when the team existed for a few years and general organization or funding problems have been dealt with , diversity could be a factor for success. </p><br />
<p><br />
In order to check if this could be seen in the best iGEM teams that existed, the sex ratio of of prize winner teams was compared to the one of participating teams with boostrap resampling giving a p-value of 0.035 This means that the sex ratio of winning teams (45%) is significantly different from the one of participating teams (37%)<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/d/de/GS_Prize.png" width="400px" ><br><br />
<b>Figure 9: Gender balance and succes in iGEM. </b> The proportion of women in teams that have won prizes in iGEM compared to the proportion in teams over all. There is a significantly higher proportion of women in teams that win prizes <b>(p=0.034)</b>.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Clues"></div><br />
<h2> Clues to improve mixity </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
<br />
Women are not as represented as men in iGEM. Why should this be a problem ? Indeed, even if it might lead to success as explained above, the need to have gender equality could be questioned. However iGEM is an international competition. One of its main goals is to attract and educate young people as well as trying to have them solve real issues. Synthetic biology might be a key technology to solve the main challenges of the 21st century.</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
<p> The world will need science and if iGEM only succeeds in motivating half of the population that could be interested, this would be a major failure to achieve its mission. Therefore, the last part of the study was aimed at understanding how could iGEM improve mixity within its own ranks.<br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div class="leftparagraph"><br />
<h3> From the data </h3><br />
<p> &nbsp;&nbsp;<br />
By looking at correlation between sex ratios and other variables, the most striking result is the link between team size and sex ratio. Teams of 2 or 3 people are almost only male teams. Even when taking out those very small teams, out of the data set the correlation holds up. This is a first lead. <br><br />
The second analysis that was made regarding the data was to compare the detailed statistics of the 100 most female teams and 100 male teams. Again, it is found that the total team member is lower for male team (9,7 vs 7,8 (p-value 0,0019) we can hypothesize that having women instructors does matter to attract girls in teams. They serve as role models. Having a woman capable of studying and realizing a synthetic biology project is a direct signal to female students that it is also possible for them to do it. Having a woman adviser might also help girls better adapt in a group and reduce their fears about having to endure constant teasing or "male " ambiance.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<h3> From a survey</h3><br />
<p> &nbsp;&nbsp;<br />
Finally, a survey was conducted among iGEMers and former iGEMers to understand their motivations and activities in iGEM. The study was designed to be unbiased and to avoid stereotype threat (for example by putting the question about gender in the end among many other pieces of information). It is still available <a href="http://bit.ly/14WykuZ"> here</a>. Participants in the survey had to rank from 1 to 5 (1 being not important, and 5 very important) answers to questions regarding personnal and professional motivations for participating in iGEM as well values and on what did they spend their time. 63 people answered among whom 32% were women.</p><br />
<br><br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/c/c5/PB_GS_Survey1.png" width="500px" /><br />
<b>Figure 10: Results of survey : what did you hope to learn in iGEM? </b>A survey was distributed to iGEM teams asking participants to rank their motivation to participate in iGEM in various subjects between 1-5. The only significant difference between the motivation of men and women in iGEM were in the subjects leading a team and leading a project.<br />
</center><br />
<br><br><br />
<p><br />
It is interesting to notice that men and women answered almost exactly the same way regarding most of the questions. Women gave a little more importance for the value of fundamental research in iGEM while men graded a bit better "Changing the world". Motivations were approximately the same as well as time spent on each activity. Just a little fact was that men considered human practices a bit more important than women did but spent a little less time on it. <br />
There is only one main difference (more than one point out of five which is represented below) : the will to lead a project and lead a team. It is striking to see how much men are more motivated to lead teams than women. This is definitely to put in relation with the number of women advisers found and the impact it can then have on teams mixity. This could reflect women lack of self esteem in some parts of their work.</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Recommendations"></div><br />
<h2> Recommendations</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Considering all the results that were presented above, here is a list of recommendations for the iGEM foundation to pursue an active policy to improve mixity in iGEM.<br />
<ul><br />
<li> Raise the number of women judges </li> <br />
<li> Promote large teams </li> <br />
<li> Write up a small paragraph to team heads to insist on the importance of motivating young women to be advisers.</li><br />
<li> Giving Bonus point when the team have women advisers </li><br />
</ul><br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>And finally, add in iGEM requirements a Gender reflection. By having teams filling out the database that was built and answering the survey and write a small paragraph about how they see mixity in their team and what it could bring, it would drastically raise the awareness of young men and women about the gender problem in science. Having an up-to-date database is also a great way to see improvements in a quantitative manner. It would allow a direct assessment of the effects of an active gender policy which would be a unique example in science. iGEM could become a leader in that fight and prepare the new generation of scientists to finally get rid of the gender inequality in science<br />
</p><br />
<br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<h2>Litterature</h2><br />
<div class="leftparagraph"><br />
<ul><br />
<li>P. Allotey, M. Gyapong Gender in tuberculosis research INT J TUBERC LUNG DIS 2008 </li><br />
<li>M. Calid, S. Rasul, S Ullah Khan, M; Saeed Gender differences in delay to s to tuberculosis diagnosis and treatment outcome<br><br />
European Commission She figures 2012<br><br />
European Commission, Mapping the gaze : getting more women to the top in Research 2008.<br><br />
</li><br />
<li>C.B. Holmes, H. Hausler, P. Hunn : A review of sex differences in the epidemiology of tuberculosis</li><br />
<li>A. N. Martinez J. T. Rhee, P. M. Small,‡M. A. Behr Sex differences in the epidemiology of tuberculosis in San Francisco INT J TUBERC LUNG DIS 4(1):26–31 2000</li><br />
<li>Moss-Racusin et al, (2012) Science faculty’s subtle gender biases favor male students PNAS </li><br />
<br />
</ul><br />
</div><br />
<div class="rightparagraph"><br />
<ul><br />
<li>McKinsey and Company Women Matter, 2007 </li><br />
<li>Olivier Neyrolles, Lluis Quintana-Murci Sexual Inequality in Tuberculosis, Plos Medicine 2009</li><br />
<li>Nosek et al. (2009) National differences in gender–science stereotypes predict national sex differences in science and math achievement. PNAS June 30, 2009 vol. 106 no. 26 10593–10597</li><br />
<br />
<li>E. Pollack Why Are There Still So Few Women in Science? NY TImes OCtober 2013</li><br />
<li>Al S. Rhines The role of sex differences in the prevalence and transmission of tuberculosis : Tuberculosis 2013</li><br />
<li>M. W. Uplekar, S. Rangan, M. G. Weiss, J. Ogden, M. W. Borgdorff, P. Hudelson Attention to gender issues in tuberculosis control INT J TUBERC LUNG DIS 4(1):26–31 2001</li><br />
</ul><br />
</div><br />
<div style="clear: both;"></div><br />
<h2>Attributions</h2><br />
<p>We would like to thank Flora Vincent, President of <a href="http://wax-science.fr/")>WAX Science</a> association for her precious help in analyzing the results, and Kim de Mora and Kitwa from the iGEM foundation, for helping spreading the survey. <p><br />
<p>This project was designed and accomplished by Aude Bernheim, Clovis Basier, Matt Deyell, Marguerite Benony and Sebastian Jaramillo in consultation with Edwin Wintermute and Ariel Lindner.</p><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_StudyTeam:Paris Bettencourt/Human Practice/Gender Study2013-10-29T03:41:26Z<p>Marguerite: </p>
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<h2>Background</h2><br />
<p>Science suffers from gender bias</p><br />
</div><br />
<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>Revealed gender bias in synthetic biology by studying sex ratios in SB conferences and labs</li><br />
<li>Built a database of all iGEM teams reporting all available online information and sex ratios of teams and advisors</li><br />
<li>Conducted a statistical analysis of this data-set and showed among other results that success in iGEM is correlated to gender mix</li><br />
<li>Made recommendations to implement an active gender policy in iGEM</li><br />
</ul><br />
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<h2>Aims</h2><br />
<p>To investigate gender dynamics in iGEM and in synthetic biology research community at large in a quantitative manner</p><br />
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<a href="#Introduction"><br />
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<h2>Skip to Introduction</h2><br />
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<h2>Skip to Recommendations</h2><br />
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<h2>Skip to Database</h2><br />
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<a href="#Findings"> <br />
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<h2>Skip to Main Findings</h2><br />
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<h2>Skip to Gender Bias in SynBio</h2><br />
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<a href="#Success"><br />
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<h2>Skip to iGEM Diversity and Success</h2><br />
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<h2>Skip to Clues to Improve Balance</h2><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Facts"><br />
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<h2 style="font-size:24px;">Infographics on gender and Synthetic Biology</h2><br />
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<div id="Introduction"></div><br />
<h2>Introduction</h2><br />
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<p> &nbsp;&nbsp;<br />
For every woman killed by TB, there are two men. Our review of the literature on gender bias and tuberculosis can be found <a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Study/Gender_Bias">here</a>. If a disease can be biased, what about ourselves? iGEM? Synthetic biology? Gender bias in science may appear in different forms. Gender balance varies by discipline, by job title, by age or by region. Only 30% of researchers in Europe are women, while 92% of French university deans are men. </p> <p>Hisorically, gender bias has affected the lives of scientists and the practice of science. However, assessing gender bias today in a living community is very difficult. History, stereotypes, limits of the disciplines, and the simple lack of data can prevent us, the synthetic biologists, from thinking about our own relationship to gender.</p><br />
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<p><br />
Most of those issues should not apply in synthetic biology. Synthetic biology is a new field. The argument of the heritage of some habits cannot be made. It is a mix of previously existing disciplines and therefore very open and should not reflect preexisting stereotypes. To study gender bias in iGEM and in synthetic biology we decided to follow a data driven approach. Studying in a quantitative manner this subjects had two main benefits. First it prevented us to apply our own biases and stereotypes on this subject. Secondly, it lead us to construct data base that we make freely available and let anyone test his own hypothesis on this controversial subject and form his own conclusions.</p><br />
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<div id="SynBio"></div><br />
<h2> Synthetic biology field : general overview of gender equality in synthetic biology </h2><br />
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<p> &nbsp;&nbsp;<br />
Gender repartition in synthetic biology can be looked at from different perspectives. For this study, two main ways were chosen: composition of labs and conferences. The main reasons for those choices were the accessibility of online data </p><br />
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<p><br />
as well as the necessity to get information not only about the general gender balance but also the sex ratio inside a defined category: PhD students, post docs, head of labs... </p><br />
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<h2> Synthetic biology labs, a good representation of gender (in)equality in science </h2> <br />
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<p> &nbsp;&nbsp;<br />
Teams of 50 synthetic biology labs were studied. The labs were chosen by their presence on the webpage http://syntheticbiology.org/Labs.html . For each lab, several numbers were reported in a table : total number of people in the team, number of women in the team, number of PhD students, post docs, head of labs, number of women PhD students, post docs, head of labs. From this, the sex ratios (number of women / total number of people) were then calculated for each of those categories. </p><br />
<p><center><a href="https://2013.igem.org/File:ParisB2013_Synthetic_Biology_Research_Groups.xls">Download the database here</a></center></p> <br />
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The first conclusion that can be made is that women are generally under-represented in synthetic biology labs. 33% correspond to the average presence of women in research in Europe. Indeed according to the European Commission, 32% of researchers in Europe are women <i>(She Figures, 2012)</i>. <br><br>The second finding also reflects well an already known reality in science : the glass ceiling. In 1995, the glass ceiling was defined by the U.S. Department of Labor, as a <i>"political term used to describe "the unseen, yet unbreakable barrier that keeps minorities and women from rising to the upper rungs of the corporate ladder, regardless of their qualifications or achievements" </i>.<br />
With only 17,85\% of heads of labs being women, synthetic biology is still doing slightly better than the average. According to a European study done in 2008 called <i>Mapping the maze,getting women to the top in research</i>., only 15% of women occupy top research position in Europe. However, the number of SB P.I. should be analyzed through the filter of history. In a new field, it would be expected in a world where bias would not be present anymore to have way more women at those positions.<br />
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<img src="https://static.igem.org/mediawiki/2013/4/46/PB_GS_LabsBis.png" width="353px"/><br><br />
<b>Figure 1:Sex ratio in synthetic biology labs</b>. The percentage of women by role in 50 synthetic biology labs. Error bars represent SD. The sex ratio of each lab is determined independently and then the mean of the labs was determined.<br />
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<center><br />
<TABLE BORDER="1"> <br />
<CAPTION> </CAPTION> <br />
<TR> <br />
<TH>Labs </TH> <br />
<TH> Phd Students </TH> <br />
<TH> Post Docs</TH> <br />
<TH> Head of Labs </TH> <br />
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<TR> <br />
<TH> 33,10 % </TH> <br />
<TD> 35,39 % </TD> <br />
<TD> 31,31 % </TD> <br />
<TD> 17,85 % </TD> <br />
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<h2> Speakers at SB Conferences : effects of an active gender policy</h2><br />
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<p> &nbsp;&nbsp;<br />
SBX.0 conferences accompanied the development of synthetic biology. They provide a great way to investigate the evolution of gender ratio since the birth of synthetic biology. Moreover, the presence/absence of women as speakers is a known indicator of gender bias and specially of active gender policy. Indeed, several social mechanisms are in place lead to fewer female speakers that could be expected: self censorship, unconscious stereotypes, unconscious choice of only male speakers... However, having female speakers at conference is a key point. It allows women, to gain confidence but also to act as role model for women attending the conference. </p><br />
<p><br />
To study SB conferences, available programs online were downloaded. Data referring to the number of speakers but also to posters were recorded. The data-set could not be completed for certain years due to the impossibility of finding the data online.<br />
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<p><center><a href="https://2013.igem.org/File:ParisB2013Resultats_SB.xls">Download the database here</a></center></p><br />
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The sex ratio of the speakers have followed a very interesting evolution. It has been multiplied by 3 from SB1 to SB5. This could indicate a change of policy considering speakers. Most likely, the first conferences invited speakers without taking into consideration the gender dimension. Might it be due to some complaints or the raise in awareness of the conferences organizers, the numbers went up. This example is interesting because it clearly show an interest in the subject by the involved community.<br />
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<p><br />
Two main conclusions can be drawn on posters. First, the sex ratio of authors in posters has changed throughout the years. Secondly, this number is not as high as the sex ratio in labs. The question is why? The points described above could be underlying reasons, however it is very difficult to truly go beyond this with only those numbers. <br />
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<img src="https://static.igem.org/mediawiki/2013/6/62/PB_GS_Sex_ratio_in_SB_Conf.png" width="400px"/><br><br />
<b> Figure 2:Sex ratio in SB conferences</b>. The proportion of speakers and poster presenters at SBX.0 conferences who are women. Data was gathered on-line from available programs.<br />
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<h2> Under represented and badly represented</h2> <br />
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<p> &nbsp;&nbsp;<br />
In order to try to better understand the dynamics of gender behind the posters numbers, the rank of authors were reported for each poster. Sex ratio were calculated for each rank, keeping in mind that in biology, the first author is often a Phd student or a post doc and the last author, the P.I.<br />
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<p><br />
As explained above, women are generally under-represented in synthetic biology labs, even less represented at conferences. When looking at the rank of author in posters, another bias appears. Indeed, women are more likely to be present as middle authors than first or last. This bias can be found in papers of different disciplines as shown on the graph realized on the eigenfactor.</p><br />
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The main finding considering gender in synthetic biology is that even though synthetic biology is new and interdisciplinary, it remains quite representative of existing gender bias in science. Therefore it can be concluded, that the issues that have kept women out of science and especially out of top research position are still present and will not be resolved with time. A strong and active policy appears necessary to bring more mixity and therefore diversity in this field.<br />
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<img src="https://static.igem.org/mediawiki/2013/6/6b/PB_GS_Author_place_.png" width="435px"/> <br><br />
<b>Figure: Sex ratio according to rank of authors in SB posters.</b> Authorship on Posters in SB conferences was collected and Women and Male authors are organized by their rank of authorship. Women tend to be middle authors more often then first or last authors.<br />
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<img src="https://static.igem.org/mediawiki/2013/2/28/PB_GS_Eigenfactor.png" width="535px"/><br />
<b>Figure 4: Analysis of rank of authors according to gender in scientific publications.</b>Women's rank of authorship in various journals and databases. There is over-all far more men cited as authors than women, and this is consistent across publications and scientific fields. Additionally, Authorship rank is shown on the bottom with the % of women over all shown as the solid line with the dot indicating the % of women within that authorship rank. Dots above the line indicate that women are over represented compared to the mean and dots below the line indicate that women are underrepresented, with the further they are from the line the greater the imbalance.<br />
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<div id="Database"></div><br />
<h2> iGEM as a model : a fantastic database </h2><br />
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<h3> Online Data</h3> <br />
<p> &nbsp;&nbsp;<br />
All the data concerning iGEM were retrieved from the website : <a href="https://igem.org">https://igem.org</a> <br />
List of teams were retrieved from the webpages <a href="https://igem.org/Team_List.cgi?year=2012">https://igem.org/Team_List.cgi?year=2012</a>.<br />
List of project themes were retrieved from <a href="https://igem.org/Team_Tracks?year=2012">https://igem.org/Team_Tracks?year=2012</a>.<br />
List of prices were retrieved <a href="https://igem.org/Results">https://igem.org/Results</a>.<br />
List of judges were retrieved from: <a href="https://igem.org/Judge_List">https://igem.org/Judge_List</a><br />
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<h3> Sex ratio determination :</h3> <br />
<p> &nbsp;&nbsp; For each team, the official team profile was checked to count the number of student members, advisors and instructors.<br />
Then to determine the sex of particpants, wiki were used when names were not obvious, using pictures when they existed. When no pictures were available and names were not obviously referring to one sex, a google image search was done on the name (first and last name) and the sex was chosen as the most represented sex in the pictures (if 10 images of men come up and 30 of women, the participant was considered as a woman).</p><br />
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<h3> Database : </h3> <br />
<p> &nbsp;&nbsp; Information for the first year of iGEM were difficult to find because of the non existence of available wiki pages and it was therefore decided not to take into account this year.<br />
Teams who withdrew during the competition were not taken into account since it was most of the time impossible to know the number of participants due to the absence of wiki.<br />
In the end our data set is composed of 662 teams over 5 years. For each team were reported : <br />
Year ; region ; name of the team ; number of student members ; number of women student members ; number of advisors ; number of women advisors ; number of instructors ; number of women instructors ; participation to MIT championship ; medal ; regional prices ; championship prices ;tracks. </p><br />
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<a href="https://static.igem.org/mediawiki/2013/3/35/PB_GS_IGEMdatabase.xls"><br />
<img src="https://static.igem.org/mediawiki/2013/b/b1/PB_downloadGD.png" width="520"/></a><br />
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<h3> Attrition by Career Stage</h3><br />
<p> &nbsp;&nbsp; With the introduction of High School iGEM competition, We have quantitative data about gender balance through career progression. By observing trends between the High School Division, Undergraduate and Overgraduate Divisions, Advisors and finally Judges; we can identify potential glass ceilings and find out why women are being lost through various career stages.</p><br />
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<div id="Findings"></div><br />
<h2> iGEM : a mirror of main gender problems </h2><br />
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<h3> Teams sex ratio, a very robust value </h3> <br />
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The first thing that was examined was the evolution of sex ratio of teams in iGEM across continents and throughout the years.<br />
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The striking conclusion of this comparison is that the sex ratio is iGEM teams remains constant through the years and across continents (ANOVA's p-value for the different conditions > 0,5). This shows that women are underrepresented in iGEM teams. </p><br />
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<img src="https://static.igem.org/mediawiki/2013/5/5a/GS_Year.png" width="250px"/><br />
<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Region.png" width="250px"/><br />
<b>Figure 5: Sex ratio of iGEM teams through the years and across continents.</b> The proportion of team members of each gender over time and between regions in the collegiate iGEM competition. Bars represent the 95% Confidence interval.<br />
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<h3> Women do not supervise as much as men </h3> <br />
<p> &nbsp;&nbsp;<br />
The second question investigated was the sex ratios for the different categories of people participating in iGEM. Indeed, iGEM is not only undergrad students. Advisors, instructors, judges also participate representing the complete professional ladder of synthetic biology. A category called Supervisors was created corresponding to instructors and advisers. Indeed, those terms are not understood and used in the same way in different continents. In some countries "advisers" means people who directly teach the teams (mostly grad students and post docs) whereas it means general mentors for others and vice versa.<br />
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<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Role.png" width="300px" height="250px"/> <br><br />
<b>Figure 6: Sex ratios in iGEM according to categories of people participating.</b> The gender balance of students, Supervisors and Judges in iGEM collegiate competitions. Supervisors is taken as the combination of advisors and instructors due to variations on how individual teams differentiate between them. Bars are 95% confidence intervals.<br />
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<p> &nbsp;&nbsp;<br />
When executing comparisons tests , team members' sex ratio is found to be different from judges' and instructors' ones (p value < 0,01). However judges and advisers are not significantly different ( p value > 0,5). This result reveals a tendency of women to supervise less than men. Indeed, from team members to instructors, the sex ratio is divided by two. What is even more interesting is to compare those numbers to sex ratios of PhD students and post docs in labs. The sex ratio of instructors is 10 points lower. </p><br />
<p> Women constitute a pool of talent that is not mobilized. They participate but do not supervise teams. They are "lost" along the way. Indeed, in a study published last year in PNAS, researchers showed that P.I. were less prone to have a woman mentoring students than man. This unconscious bias can be translated by a lack of encouragement from P.I.s but also by a self censorship which is not taken into account by other supervisors as explained in an recently published article by Eileen Pollack (E. Pollack Why Are There Still So Few Women in Science? NY TImes October 2013).<br />
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<h3> Tracks and sex ratio in iGEM </h3> <br />
<p> &nbsp;&nbsp;<br />
The third finding goes against an often-heard stereotype "women are more interested by applied research". In order to investigate this subject, tracks were reported for each project. In iGEM tracks correspond to general theme of the project : medicine, fundationnal research…Tracks were then looked at in terms of sex ratios. There is no significant difference between tracks. (ANOVA > 0,1).</p><br />
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<img src="https://static.igem.org/mediawiki/2013/a/ac/PB_GS_Sexratiotracksbis.png" width="535px"/><br />
<b>Figure 7: Sex ratios and tracks in iGEM. </b>The proportion of gender in teams grouped by the track that the team is entered in during collegiate iGEM competitions. There is no statistical significant difference between the gender balance between tracks. <br />
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<h3> High School Division is more balanced</h3><br />
<p> When we looked at the High School Divison, we found that it had a higher percentage of women than the university iGEM teams. Additionally, The number of female advisors and instructors in the High School division is much higher than that of the Collegiate division and is approximately the same as the proportion of students. This indicates that there is a problem at the Collegiate level and that iGEM can be an important bridge for women to access new opportunities to lead in higher education</p><br />
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<img src="https://static.igem.org/mediawiki/2013/9/91/PB_HighSchool_Gender_Students.png" width="250px"/><br />
<img src="https://2013.igem.org/File:PB_HS_By_Role.png" width="250px"/><br />
<b>Figure 8: Sex ratios in High School iGEM by year and role. </b>On the left, the proportion of students in the High School Competition that are women for each year. On the right, the proportion of women in each role for all years. Bars represent 95% Confidence Interval.<br />
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<p><br />
To conclude, studying the iGEM competition gives a unique quantitative insight on existing questions in the field of gender studies. It also constitutes an amazing argument to convince scientists of the existence of a gender issue in science. As explained by Rascun et al in a recent paper published in PNAS, scientists believe that those type of bias only exist in some labs, not their own, therefore very objective studies need to be conducted to clearly show the reality of the numbers. More over , Jo Handelsman a microbiologist involved in that paper underlined in a recent interview, that people often think that there is still an issue in physics or maths but that there are no more women issues in biology, which is not true. This study supports strongly the view that this general thinking is untrue.<br />
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<div id="Success"></div><br />
<h3> In iGEM, is diversity a factor of success ? </h3><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Several studies led by consulting groups (McKinsey and Company Women Matter, 2007) have shown that mixity in a team increases performance. The big question of what leads to success in iGEM was therefore investigated using the database with a special focus on gender. In order to be able to get a general idea about iGEM team success, a point system was put in place.<br />
</p><br />
<p>Points were attributed the following way.<br><br />
For the medal: 1 point for bronze medal, 2 points for silver medal, 3 points for gold medal. For the world jamboree qualified teams: 2 points for every team taking part in 2010 and before (before regional jamborees existed) , 6 points for team qualified for world final (after 2010). For special prices (Best ...): 6 points were attributed for each regional price earned (only after 2010), 13 points for each price earned in the world final (all price worth 13 points before regional jamborees existed). For the final place in world final: 15 points for the sixth team, 20 points for the fifth team, 25 points for the fourth team, 30 points for the third team, 35 points for the second team, 40 points for the firth team.</p><br />
<p><br />
The aim was to give each team a score that is proportional to the rewards it earned, taking in account that all teams were in world jamboree prior to 2011, without having to be qualified in regional jamborees.<br />
</p><br />
<p>Best score is for the Imperial College London team in 2011 (81 points).<br />
All teams (all years) average is 7.41 points, considering teams with no points (due to withdrew).</p><br />
<p><br />
Correlations studies between this number of points and other variables show that that for all teams, the main variables explaining success in iGEM is the number of years of existence and the size of the team. It would therefore seem that mixity would not be a factor. However, when looking at correlations between variables of teams who truly succeeded (points > 20) , the variables that have a significant correlation with the number of points become the sex ratio and the number of supervisors. Therefore it could be hypothesized that beginning iGEM teams have to face major challenges but when the team existed for a few years and general organization or funding problems have been dealt with , diversity could be a factor for success. </p><br />
<p><br />
In order to check if this could be seen in the best iGEM teams that existed, the sex ratio of of prize winner teams was compared to the one of participating teams with boostrap resampling giving a p-value of 0.035 This means that the sex ratio of winning teams (45%) is significantly different from the one of participating teams (37%)<br />
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<center><br />
<img src="https://static.igem.org/mediawiki/2013/d/de/GS_Prize.png" width="400px" ><br><br />
<b>Figure 9: Gender balance and succes in iGEM. </b> The proportion of women in teams that have won prizes in iGEM compared to the proportion in teams over all. There is a significantly higher proportion of women in teams that win prizes <b>(p=0.034)</b>.<br />
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<div id="Clues"></div><br />
<h2> Clues to improve mixity </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
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Women are not as represented as men in iGEM. Why should this be a problem ? Indeed, even if it might lead to success as explained above, the need to have gender equality could be questioned. However iGEM is an international competition. One of its main goals is to attract and educate young people as well as trying to have them solve real issues. Synthetic biology might be a key technology to solve the main challenges of the 21st century.</p><br />
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<div class="rightparagraph"><br />
<p> The world will need science and if iGEM only succeeds in motivating half of the population that could be interested, this would be a major failure to achieve its mission. Therefore, the last part of the study was aimed at understanding how could iGEM improve mixity within its own ranks.<br />
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<div class="leftparagraph"><br />
<h3> From the data </h3><br />
<p> &nbsp;&nbsp;<br />
By looking at correlation between sex ratios and other variables, the most striking result is the link between team size and sex ratio. Teams of 2 or 3 people are almost only male teams. Even when taking out those very small teams, out of the data set the correlation holds up. This is a first lead. <br><br />
The second analysis that was made regarding the data was to compare the detailed statistics of the 100 most female teams and 100 male teams. Again, it is found that the total team member is lower for male team (9,7 vs 7,8 (p-value 0,0019) we can hypothesize that having women instructors does matter to attract girls in teams. They serve as role models. Having a woman capable of studying and realizing a synthetic biology project is a direct signal to female students that it is also possible for them to do it. Having a woman adviser might also help girls better adapt in a group and reduce their fears about having to endure constant teasing or "male " ambiance.<br />
</p><br />
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<div class="rightparagraph"><br />
<h3> From a survey</h3><br />
<p> &nbsp;&nbsp;<br />
Finally, a survey was conducted among iGEMers and former iGEMers to understand their motivations and activities in iGEM. The study was designed to be unbiased and to avoid stereotype threat (for example by putting the question about gender in the end among many other pieces of information). It is still available <a href="http://bit.ly/14WykuZ"> here</a>. Participants in the survey had to rank from 1 to 5 (1 being not important, and 5 very important) answers to questions regarding personnal and professional motivations for participating in iGEM as well values and on what did they spend their time. 63 people answered among whom 32% were women.</p><br />
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<center><br />
<img src="https://static.igem.org/mediawiki/2013/c/c5/PB_GS_Survey1.png" width="500px" /><br />
<b>Figure 10: Results of survey : what did you hope to learn in iGEM? </b>A survey was distributed to iGEM teams asking participants to rank their motivation to participate in iGEM in various subjects between 1-5. The only significant difference between the motivation of men and women in iGEM were in the subjects leading a team and leading a project.<br />
</center><br />
<br><br><br />
<p><br />
It is interesting to notice that men and women answered almost exactly the same way regarding most of the questions. Women gave a little more importance for the value of fundamental research in iGEM while men graded a bit better "Changing the world". Motivations were approximately the same as well as time spent on each activity. Just a little fact was that men considered human practices a bit more important than women did but spent a little less time on it. <br />
There is only one main difference (more than one point out of five which is represented below) : the will to lead a project and lead a team. It is striking to see how much men are more motivated to lead teams than women. This is definitely to put in relation with the number of women advisers found and the impact it can then have on teams mixity. This could reflect women lack of self esteem in some parts of their work.</p><br />
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<div id="Recommendations"></div><br />
<h2> Recommendations</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Considering all the results that were presented above, here is a list of recommendations for the iGEM foundation to pursue an active policy to improve mixity in iGEM.<br />
<ul><br />
<li> Raise the number of women judges </li> <br />
<li> Promote large teams </li> <br />
<li> Write up a small paragraph to team heads to insist on the importance of motivating young women to be advisers.</li><br />
<li> Giving Bonus point when the team have women advisers </li><br />
</ul><br />
</p><br />
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<div class="rightparagraph"><br />
<p>And finally, add in iGEM requirements a Gender reflection. By having teams filling out the database that was built and answering the survey and write a small paragraph about how they see mixity in their team and what it could bring, it would drastically raise the awareness of young men and women about the gender problem in science. Having an up-to-date database is also a great way to see improvements in a quantitative manner. It would allow a direct assessment of the effects of an active gender policy which would be a unique example in science. iGEM could become a leader in that fight and prepare the new generation of scientists to finally get rid of the gender inequality in science<br />
</p><br />
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</div><br />
<div style="clear: both;"></div><br />
<br />
<h2>Litterature</h2><br />
<div class="leftparagraph"><br />
<ul><br />
<li>P. Allotey, M. Gyapong Gender in tuberculosis research INT J TUBERC LUNG DIS 2008 </li><br />
<li>M. Calid, S. Rasul, S Ullah Khan, M; Saeed Gender differences in delay to s to tuberculosis diagnosis and treatment outcome<br><br />
European Commission She figures 2012<br><br />
European Commission, Mapping the gaze : getting more women to the top in Research 2008.<br><br />
</li><br />
<li>C.B. Holmes, H. Hausler, P. Hunn : A review of sex differences in the epidemiology of tuberculosis</li><br />
<li>A. N. Martinez J. T. Rhee, P. M. Small,‡M. A. Behr Sex differences in the epidemiology of tuberculosis in San Francisco INT J TUBERC LUNG DIS 4(1):26–31 2000</li><br />
<li>Moss-Racusin et al, (2012) Science faculty’s subtle gender biases favor male students PNAS </li><br />
<br />
</ul><br />
</div><br />
<div class="rightparagraph"><br />
<ul><br />
<li>McKinsey and Company Women Matter, 2007 </li><br />
<li>Olivier Neyrolles, Lluis Quintana-Murci Sexual Inequality in Tuberculosis, Plos Medicine 2009</li><br />
<li>Nosek et al. (2009) National differences in gender–science stereotypes predict national sex differences in science and math achievement. PNAS June 30, 2009 vol. 106 no. 26 10593–10597</li><br />
<br />
<li>E. Pollack Why Are There Still So Few Women in Science? NY TImes OCtober 2013</li><br />
<li>Al S. Rhines The role of sex differences in the prevalence and transmission of tuberculosis : Tuberculosis 2013</li><br />
<li>M. W. Uplekar, S. Rangan, M. G. Weiss, J. Ogden, M. W. Borgdorff, P. Hudelson Attention to gender issues in tuberculosis control INT J TUBERC LUNG DIS 4(1):26–31 2001</li><br />
</ul><br />
</div><br />
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<h2>Attributions</h2><br />
<p>We would like to thank Flora Vincent, President of <a href="http://wax-science.fr/")>WAX Science</a> association for her precious help in analyzing the results, and Kim de Mora and Kitwa from the iGEM foundation, for helping spreading the survey. <p><br />
<p>This project was designed and accomplished by Aude Bernheim, Clovis Basier, Matt Deyell, Marguerite Benony and Sebastian Jaramillo in consultation with Edwin Wintermute and Ariel Lindner.</p><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_StudyTeam:Paris Bettencourt/Human Practice/Gender Study2013-10-29T03:40:08Z<p>Marguerite: </p>
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<h2>Background</h2><br />
<p>Science suffers from gender bias</p><br />
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<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>Revealed gender bias in synthetic biology by studying sex ratios in SB conferences and labs</li><br />
<li>Built a database of all iGEM teams reporting all available online information and sex ratios of teams and advisors</li><br />
<li>Conducted a statistical analysis of this data-set and showed among other results that success in iGEM is correlated to gender mix</li><br />
<li>Made recommendations to implement an active gender policy in iGEM</li><br />
</ul><br />
<p></p><br />
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<div class="aims"><br />
<h2>Aims</h2><br />
<p>To investigate gender dynamics in iGEM and in synthetic biology research community at large in a quantitative manner</p><br />
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<a href="#Introduction"><br />
<div class="hlink"><br />
<h2>Skip to Introduction</h2><br />
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</a><br />
<a href="#Recommendations"><br />
<div class="hlink"><br />
<h2>Skip to Recommendations</h2><br />
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<a href="#Database"><br />
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<h2>Skip to Database</h2><br />
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<a href="#Findings"> <br />
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<h2>Skip to Main Findings</h2><br />
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<h2>Skip to Gender Bias in SynBio</h2><br />
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<a href="#Success"><br />
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<h2>Skip to iGEM Diversity and Success</h2><br />
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<a href="#Clues"><br />
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<h2>Skip to Clues to Improve Balance</h2><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Facts"><br />
<div class="hlink" style="width:100%;margin-right:0"><br />
<h2 style="font-size:24px;">Infographics on gender and Synthetic Biology</h2><br />
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<div id="Introduction"></div><br />
<h2>Introduction</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
For every woman killed by TB, there are two men. Our review of the literature on gender bias and tuberculosis can be found <a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Study/Gender_Bias">here</a>. If a disease can be biased, what about ourselves? iGEM? Synthetic biology? Gender bias in science may appear in different forms. Gender balance varies by discipline, by job title, by age or by region. Only 30% of researchers in Europe are women, while 92% of French university deans are men. </p> <p>Hisorically, gender bias has affected the lives of scientists and the practice of science. However, assessing gender bias today in a living community is very difficult. History, stereotypes, limits of the disciplines, and the simple lack of data can prevent us, the synthetic biologists, from thinking about our own relationship to gender.</p><br />
<br><br />
</div><br />
<div class="rightparagraph"><br />
<p><br />
Most of those issues should not apply in synthetic biology. Synthetic biology is a new field. The argument of the heritage of some habits cannot be made. It is a mix of previously existing disciplines and therefore very open and should not reflect preexisting stereotypes. To study gender bias in iGEM and in synthetic biology we decided to follow a data driven approach. Studying in a quantitative manner this subjects had two main benefits. First it prevented us to apply our own biases and stereotypes on this subject. Secondly, it lead us to construct data base that we make freely available and let anyone test his own hypothesis on this controversial subject and form his own conclusions.</p><br />
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<div id="SynBio"></div><br />
<h2> Synthetic biology field : general overview of gender equality in synthetic biology </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Gender repartition in synthetic biology can be looked at from different perspectives. For this study, two main ways were chosen: composition of labs and conferences. The main reasons for those choices were the accessibility of online data </p><br />
</div><br />
<div class="rightparagraph"><br />
<p><br />
as well as the necessity to get information not only about the general gender balance but also the sex ratio inside a defined category: PhD students, post docs, head of labs... </p><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<h2> Synthetic biology labs, a good representation of gender (in)equality in science </h2> <br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Teams of 50 synthetic biology labs were studied. The labs were chosen by their presence on the webpage http://syntheticbiology.org/Labs.html . For each lab, several numbers were reported in a table : total number of people in the team, number of women in the team, number of PhD students, post docs, head of labs, number of women PhD students, post docs, head of labs. From this, the sex ratios (number of women / total number of people) were then calculated for each of those categories. </p><br />
<p><center><a href="https://2013.igem.org/File:ParisB2013_Synthetic_Biology_Research_Groups.xls">Download the database here</a></center></p> <br />
<p><br />
The first conclusion that can be made is that women are generally under-represented in synthetic biology labs. 33% correspond to the average presence of women in research in Europe. Indeed according to the European Commission, 32% of researchers in Europe are women <i>(She Figures, 2012)</i>. <br><br>The second finding also reflects well an already known reality in science : the glass ceiling. In 1995, the glass ceiling was defined by the U.S. Department of Labor, as a <i>"political term used to describe "the unseen, yet unbreakable barrier that keeps minorities and women from rising to the upper rungs of the corporate ladder, regardless of their qualifications or achievements" </i>.<br />
With only 17,85\% of heads of labs being women, synthetic biology is still doing slightly better than the average. According to a European study done in 2008 called <i>Mapping the maze,getting women to the top in research</i>., only 15% of women occupy top research position in Europe. However, the number of SB P.I. should be analyzed through the filter of history. In a new field, it would be expected in a world where bias would not be present anymore to have way more women at those positions.<br />
</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
</br></br></br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/4/46/PB_GS_LabsBis.png" width="353px"/><br><br />
<b>Figure 1:Sex ratio in synthetic biology labs</b>. The percentage of women by role in 50 synthetic biology labs. Error bars represent SD. The sex ratio of each lab is determined independently and then the mean of the labs was determined.<br />
</center><br />
<br />
</br></br></br><br />
<center><br />
<TABLE BORDER="1"> <br />
<CAPTION> </CAPTION> <br />
<TR> <br />
<TH>Labs </TH> <br />
<TH> Phd Students </TH> <br />
<TH> Post Docs</TH> <br />
<TH> Head of Labs </TH> <br />
</TR> <br />
<TR> <br />
<TH> 33,10 % </TH> <br />
<TD> 35,39 % </TD> <br />
<TD> 31,31 % </TD> <br />
<TD> 17,85 % </TD> <br />
</TR> <br />
</TABLE><br />
</center><br />
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<br />
<h2> Speakers at SB Conferences : effects of an active gender policy</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
SBX.0 conferences accompanied the development of synthetic biology. They provide a great way to investigate the evolution of gender ratio since the birth of synthetic biology. Moreover, the presence/absence of women as speakers is a known indicator of gender bias and specially of active gender policy. Indeed, several social mechanisms are in place lead to fewer female speakers that could be expected: self censorship, unconscious stereotypes, unconscious choice of only male speakers... However, having female speakers at conference is a key point. It allows women, to gain confidence but also to act as role model for women attending the conference. </p><br />
<p><br />
To study SB conferences, available programs online were downloaded. Data referring to the number of speakers but also to posters were recorded. The data-set could not be completed for certain years due to the impossibility of finding the data online.<br />
</p><br />
<p><center><a href="https://2013.igem.org/File:ParisB2013Resultats_SB.xls">Download the database here</a></center></p><br />
<p><br />
The sex ratio of the speakers have followed a very interesting evolution. It has been multiplied by 3 from SB1 to SB5. This could indicate a change of policy considering speakers. Most likely, the first conferences invited speakers without taking into consideration the gender dimension. Might it be due to some complaints or the raise in awareness of the conferences organizers, the numbers went up. This example is interesting because it clearly show an interest in the subject by the involved community.<br />
</p><br />
<p><br />
Two main conclusions can be drawn on posters. First, the sex ratio of authors in posters has changed throughout the years. Secondly, this number is not as high as the sex ratio in labs. The question is why? The points described above could be underlying reasons, however it is very difficult to truly go beyond this with only those numbers. <br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<br><br><br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/6/62/PB_GS_Sex_ratio_in_SB_Conf.png" width="400px"/><br><br />
<b> Figure 2:Sex ratio in SB conferences</b>. The proportion of speakers and poster presenters at SBX.0 conferences who are women. Data was gathered on-line from available programs.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<h2> Under represented and badly represented</h2> <br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
In order to try to better understand the dynamics of gender behind the posters numbers, the rank of authors were reported for each poster. Sex ratio were calculated for each rank, keeping in mind that in biology, the first author is often a Phd student or a post doc and the last author, the P.I.<br />
</p><br />
<p><br />
As explained above, women are generally under-represented in synthetic biology labs, even less represented at conferences. When looking at the rank of author in posters, another bias appears. Indeed, women are more likely to be present as middle authors than first or last. This bias can be found in papers of different disciplines as shown on the graph realized on the eigenfactor.</p><br />
<p> <br />
The main finding considering gender in synthetic biology is that even though synthetic biology is new and interdisciplinary, it remains quite representative of existing gender bias in science. Therefore it can be concluded, that the issues that have kept women out of science and especially out of top research position are still present and will not be resolved with time. A strong and active policy appears necessary to bring more mixity and therefore diversity in this field.<br />
<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/6/6b/PB_GS_Author_place_.png" width="435px"/> <br><br />
<b>Figure: Sex ratio according to rank of authors in SB posters.</b> Authorship on Posters in SB conferences was collected and Women and Male authors are organized by their rank of authorship. Women tend to be middle authors more often then first or last authors.<br />
</center><br />
<br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/2/28/PB_GS_Eigenfactor.png" width="535px"/><br />
<b>Figure 4: Analysis of rank of authors according to gender in scientific publications.</b>Women's rank of authorship in various journals and databases. There is over-all far more men cited as authors than women, and this is consistent across publications and scientific fields. Additionally, Authorship rank is shown on the bottom with the % of women over all shown as the solid line with the dot indicating the % of women within that authorship rank. Dots above the line indicate that women are over represented compared to the mean and dots below the line indicate that women are underrepresented, with the further they are from the line the greater the imbalance.<br />
</center> <br />
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<div id="Database"></div><br />
<h2> iGEM as a model : a fantastic database </h2><br />
<div class="leftparagraph"><br />
<h3> Online Data</h3> <br />
<p> &nbsp;&nbsp;<br />
All the data concerning iGEM were retrieved from the website : <a href="https://igem.org">https://igem.org</a> <br />
List of teams were retrieved from the webpages <a href="https://igem.org/Team_List.cgi?year=2012">https://igem.org/Team_List.cgi?year=2012</a>.<br />
List of project themes were retrieved from <a href="https://igem.org/Team_Tracks?year=2012">https://igem.org/Team_Tracks?year=2012</a>.<br />
List of prices were retrieved <a href="https://igem.org/Results">https://igem.org/Results</a>.<br />
List of judges were retrieved from: <a href="https://igem.org/Judge_List">https://igem.org/Judge_List</a><br />
</p><br />
<h3> Sex ratio determination :</h3> <br />
<p> &nbsp;&nbsp; For each team, the official team profile was checked to count the number of student members, advisors and instructors.<br />
Then to determine the sex of particpants, wiki were used when names were not obvious, using pictures when they existed. When no pictures were available and names were not obviously referring to one sex, a google image search was done on the name (first and last name) and the sex was chosen as the most represented sex in the pictures (if 10 images of men come up and 30 of women, the participant was considered as a woman).</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
<h3> Database : </h3> <br />
<p> &nbsp;&nbsp; Information for the first year of iGEM were difficult to find because of the non existence of available wiki pages and it was therefore decided not to take into account this year.<br />
Teams who withdrew during the competition were not taken into account since it was most of the time impossible to know the number of participants due to the absence of wiki.<br />
In the end our data set is composed of 662 teams over 5 years. For each team were reported : <br />
Year ; region ; name of the team ; number of student members ; number of women student members ; number of advisors ; number of women advisors ; number of instructors ; number of women instructors ; participation to MIT championship ; medal ; regional prices ; championship prices ;tracks. </p><br />
<p><br />
<center><br />
<a href="https://static.igem.org/mediawiki/2013/3/35/PB_GS_IGEMdatabase.xls"><br />
<img src="https://static.igem.org/mediawiki/2013/b/b1/PB_downloadGD.png" width="500"/></a><br />
</center><br />
</p><br />
<h3> Attrition by Career Stage</h3><br />
<p> &nbsp;&nbsp; With the introduction of High School iGEM competition, We have quantitative data about gender balance through career progression. By observing trends between the High School Division, Undergraduate and Overgraduate Divisions, Advisors and finally Judges; we can identify potential glass ceilings and find out why women are being lost through various career stages.</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Findings"></div><br />
<h2> iGEM : a mirror of main gender problems </h2><br />
<div class="leftparagraph"><br />
<h3> Teams sex ratio, a very robust value </h3> <br />
<p> &nbsp;&nbsp;<br />
<br><br><br />
The first thing that was examined was the evolution of sex ratio of teams in iGEM across continents and throughout the years.<br />
</p><br />
<br><br />
<p><br />
The striking conclusion of this comparison is that the sex ratio is iGEM teams remains constant through the years and across continents (ANOVA's p-value for the different conditions > 0,5). This shows that women are underrepresented in iGEM teams. </p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/5/5a/GS_Year.png" width="250px"/><br />
<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Region.png" width="250px"/><br />
<b>Figure 5: Sex ratio of iGEM teams through the years and across continents.</b> The proportion of team members of each gender over time and between regions in the collegiate iGEM competition. Bars represent the 95% Confidence interval.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div class="leftparagraph"><br />
<h3> Women do not supervise as much as men </h3> <br />
<p> &nbsp;&nbsp;<br />
The second question investigated was the sex ratios for the different categories of people participating in iGEM. Indeed, iGEM is not only undergrad students. Advisors, instructors, judges also participate representing the complete professional ladder of synthetic biology. A category called Supervisors was created corresponding to instructors and advisers. Indeed, those terms are not understood and used in the same way in different continents. In some countries "advisers" means people who directly teach the teams (mostly grad students and post docs) whereas it means general mentors for others and vice versa.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Role.png" width="300px" height="250px"/> <br><br />
<b>Figure 6: Sex ratios in iGEM according to categories of people participating.</b> The gender balance of students, Supervisors and Judges in iGEM collegiate competitions. Supervisors is taken as the combination of advisors and instructors due to variations on how individual teams differentiate between them. Bars are 95% confidence intervals.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
When executing comparisons tests , team members' sex ratio is found to be different from judges' and instructors' ones (p value < 0,01). However judges and advisers are not significantly different ( p value > 0,5). This result reveals a tendency of women to supervise less than men. Indeed, from team members to instructors, the sex ratio is divided by two. What is even more interesting is to compare those numbers to sex ratios of PhD students and post docs in labs. The sex ratio of instructors is 10 points lower. </p><br />
<p> Women constitute a pool of talent that is not mobilized. They participate but do not supervise teams. They are "lost" along the way. Indeed, in a study published last year in PNAS, researchers showed that P.I. were less prone to have a woman mentoring students than man. This unconscious bias can be translated by a lack of encouragement from P.I.s but also by a self censorship which is not taken into account by other supervisors as explained in an recently published article by Eileen Pollack (E. Pollack Why Are There Still So Few Women in Science? NY TImes October 2013).<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<h3> Tracks and sex ratio in iGEM </h3> <br />
<p> &nbsp;&nbsp;<br />
The third finding goes against an often-heard stereotype "women are more interested by applied research". In order to investigate this subject, tracks were reported for each project. In iGEM tracks correspond to general theme of the project : medicine, fundationnal research…Tracks were then looked at in terms of sex ratios. There is no significant difference between tracks. (ANOVA > 0,1).</p><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/a/ac/PB_GS_Sexratiotracksbis.png" width="535px"/><br />
<b>Figure 7: Sex ratios and tracks in iGEM. </b>The proportion of gender in teams grouped by the track that the team is entered in during collegiate iGEM competitions. There is no statistical significant difference between the gender balance between tracks. <br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<h3> High School Division is more balanced</h3><br />
<p> When we looked at the High School Divison, we found that it had a higher percentage of women than the university iGEM teams. Additionally, The number of female advisors and instructors in the High School division is much higher than that of the Collegiate division and is approximately the same as the proportion of students. This indicates that there is a problem at the Collegiate level and that iGEM can be an important bridge for women to access new opportunities to lead in higher education</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/9/91/PB_HighSchool_Gender_Students.png" width="250px"/><br />
<img src="https://2013.igem.org/File:PB_HS_By_Role.png" width="250px"/><br />
<b>Figure 8: Sex ratios in High School iGEM by year and role. </b>On the left, the proportion of students in the High School Competition that are women for each year. On the right, the proportion of women in each role for all years. Bars represent 95% Confidence Interval.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<p><br />
To conclude, studying the iGEM competition gives a unique quantitative insight on existing questions in the field of gender studies. It also constitutes an amazing argument to convince scientists of the existence of a gender issue in science. As explained by Rascun et al in a recent paper published in PNAS, scientists believe that those type of bias only exist in some labs, not their own, therefore very objective studies need to be conducted to clearly show the reality of the numbers. More over , Jo Handelsman a microbiologist involved in that paper underlined in a recent interview, that people often think that there is still an issue in physics or maths but that there are no more women issues in biology, which is not true. This study supports strongly the view that this general thinking is untrue.<br />
</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Success"></div><br />
<h3> In iGEM, is diversity a factor of success ? </h3><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Several studies led by consulting groups (McKinsey and Company Women Matter, 2007) have shown that mixity in a team increases performance. The big question of what leads to success in iGEM was therefore investigated using the database with a special focus on gender. In order to be able to get a general idea about iGEM team success, a point system was put in place.<br />
</p><br />
<p>Points were attributed the following way.<br><br />
For the medal: 1 point for bronze medal, 2 points for silver medal, 3 points for gold medal. For the world jamboree qualified teams: 2 points for every team taking part in 2010 and before (before regional jamborees existed) , 6 points for team qualified for world final (after 2010). For special prices (Best ...): 6 points were attributed for each regional price earned (only after 2010), 13 points for each price earned in the world final (all price worth 13 points before regional jamborees existed). For the final place in world final: 15 points for the sixth team, 20 points for the fifth team, 25 points for the fourth team, 30 points for the third team, 35 points for the second team, 40 points for the firth team.</p><br />
<p><br />
The aim was to give each team a score that is proportional to the rewards it earned, taking in account that all teams were in world jamboree prior to 2011, without having to be qualified in regional jamborees.<br />
</p><br />
<p>Best score is for the Imperial College London team in 2011 (81 points).<br />
All teams (all years) average is 7.41 points, considering teams with no points (due to withdrew).</p><br />
<p><br />
Correlations studies between this number of points and other variables show that that for all teams, the main variables explaining success in iGEM is the number of years of existence and the size of the team. It would therefore seem that mixity would not be a factor. However, when looking at correlations between variables of teams who truly succeeded (points > 20) , the variables that have a significant correlation with the number of points become the sex ratio and the number of supervisors. Therefore it could be hypothesized that beginning iGEM teams have to face major challenges but when the team existed for a few years and general organization or funding problems have been dealt with , diversity could be a factor for success. </p><br />
<p><br />
In order to check if this could be seen in the best iGEM teams that existed, the sex ratio of of prize winner teams was compared to the one of participating teams with boostrap resampling giving a p-value of 0.035 This means that the sex ratio of winning teams (45%) is significantly different from the one of participating teams (37%)<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/d/de/GS_Prize.png" width="400px" ><br><br />
<b>Figure 9: Gender balance and succes in iGEM. </b> The proportion of women in teams that have won prizes in iGEM compared to the proportion in teams over all. There is a significantly higher proportion of women in teams that win prizes <b>(p=0.034)</b>.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Clues"></div><br />
<h2> Clues to improve mixity </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
<br />
Women are not as represented as men in iGEM. Why should this be a problem ? Indeed, even if it might lead to success as explained above, the need to have gender equality could be questioned. However iGEM is an international competition. One of its main goals is to attract and educate young people as well as trying to have them solve real issues. Synthetic biology might be a key technology to solve the main challenges of the 21st century.</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
<p> The world will need science and if iGEM only succeeds in motivating half of the population that could be interested, this would be a major failure to achieve its mission. Therefore, the last part of the study was aimed at understanding how could iGEM improve mixity within its own ranks.<br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div class="leftparagraph"><br />
<h3> From the data </h3><br />
<p> &nbsp;&nbsp;<br />
By looking at correlation between sex ratios and other variables, the most striking result is the link between team size and sex ratio. Teams of 2 or 3 people are almost only male teams. Even when taking out those very small teams, out of the data set the correlation holds up. This is a first lead. <br><br />
The second analysis that was made regarding the data was to compare the detailed statistics of the 100 most female teams and 100 male teams. Again, it is found that the total team member is lower for male team (9,7 vs 7,8 (p-value 0,0019) we can hypothesize that having women instructors does matter to attract girls in teams. They serve as role models. Having a woman capable of studying and realizing a synthetic biology project is a direct signal to female students that it is also possible for them to do it. Having a woman adviser might also help girls better adapt in a group and reduce their fears about having to endure constant teasing or "male " ambiance.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<h3> From a survey</h3><br />
<p> &nbsp;&nbsp;<br />
Finally, a survey was conducted among iGEMers and former iGEMers to understand their motivations and activities in iGEM. The study was designed to be unbiased and to avoid stereotype threat (for example by putting the question about gender in the end among many other pieces of information). It is still available <a href="http://bit.ly/14WykuZ"> here</a>. Participants in the survey had to rank from 1 to 5 (1 being not important, and 5 very important) answers to questions regarding personnal and professional motivations for participating in iGEM as well values and on what did they spend their time. 63 people answered among whom 32% were women.</p><br />
<br><br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/c/c5/PB_GS_Survey1.png" width="500px" /><br />
<b>Figure 10: Results of survey : what did you hope to learn in iGEM? </b>A survey was distributed to iGEM teams asking participants to rank their motivation to participate in iGEM in various subjects between 1-5. The only significant difference between the motivation of men and women in iGEM were in the subjects leading a team and leading a project.<br />
</center><br />
<br><br><br />
<p><br />
It is interesting to notice that men and women answered almost exactly the same way regarding most of the questions. Women gave a little more importance for the value of fundamental research in iGEM while men graded a bit better "Changing the world". Motivations were approximately the same as well as time spent on each activity. Just a little fact was that men considered human practices a bit more important than women did but spent a little less time on it. <br />
There is only one main difference (more than one point out of five which is represented below) : the will to lead a project and lead a team. It is striking to see how much men are more motivated to lead teams than women. This is definitely to put in relation with the number of women advisers found and the impact it can then have on teams mixity. This could reflect women lack of self esteem in some parts of their work.</p><br />
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<div id="Recommendations"></div><br />
<h2> Recommendations</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Considering all the results that were presented above, here is a list of recommendations for the iGEM foundation to pursue an active policy to improve mixity in iGEM.<br />
<ul><br />
<li> Raise the number of women judges </li> <br />
<li> Promote large teams </li> <br />
<li> Write up a small paragraph to team heads to insist on the importance of motivating young women to be advisers.</li><br />
<li> Giving Bonus point when the team have women advisers </li><br />
</ul><br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>And finally, add in iGEM requirements a Gender reflection. By having teams filling out the database that was built and answering the survey and write a small paragraph about how they see mixity in their team and what it could bring, it would drastically raise the awareness of young men and women about the gender problem in science. Having an up-to-date database is also a great way to see improvements in a quantitative manner. It would allow a direct assessment of the effects of an active gender policy which would be a unique example in science. iGEM could become a leader in that fight and prepare the new generation of scientists to finally get rid of the gender inequality in science<br />
</p><br />
<br />
</div><br />
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<br />
<h2>Litterature</h2><br />
<div class="leftparagraph"><br />
<ul><br />
<li>P. Allotey, M. Gyapong Gender in tuberculosis research INT J TUBERC LUNG DIS 2008 </li><br />
<li>M. Calid, S. Rasul, S Ullah Khan, M; Saeed Gender differences in delay to s to tuberculosis diagnosis and treatment outcome<br><br />
European Commission She figures 2012<br><br />
European Commission, Mapping the gaze : getting more women to the top in Research 2008.<br><br />
</li><br />
<li>C.B. Holmes, H. Hausler, P. Hunn : A review of sex differences in the epidemiology of tuberculosis</li><br />
<li>A. N. Martinez J. T. Rhee, P. M. Small,‡M. A. Behr Sex differences in the epidemiology of tuberculosis in San Francisco INT J TUBERC LUNG DIS 4(1):26–31 2000</li><br />
<li>Moss-Racusin et al, (2012) Science faculty’s subtle gender biases favor male students PNAS </li><br />
<br />
</ul><br />
</div><br />
<div class="rightparagraph"><br />
<ul><br />
<li>McKinsey and Company Women Matter, 2007 </li><br />
<li>Olivier Neyrolles, Lluis Quintana-Murci Sexual Inequality in Tuberculosis, Plos Medicine 2009</li><br />
<li>Nosek et al. (2009) National differences in gender–science stereotypes predict national sex differences in science and math achievement. PNAS June 30, 2009 vol. 106 no. 26 10593–10597</li><br />
<br />
<li>E. Pollack Why Are There Still So Few Women in Science? NY TImes OCtober 2013</li><br />
<li>Al S. Rhines The role of sex differences in the prevalence and transmission of tuberculosis : Tuberculosis 2013</li><br />
<li>M. W. Uplekar, S. Rangan, M. G. Weiss, J. Ogden, M. W. Borgdorff, P. Hudelson Attention to gender issues in tuberculosis control INT J TUBERC LUNG DIS 4(1):26–31 2001</li><br />
</ul><br />
</div><br />
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<h2>Attributions</h2><br />
<p>We would like to thank Flora Vincent, President of <a href="http://wax-science.fr/")>WAX Science</a> association for her precious help in analyzing the results, and Kim de Mora and Kitwa from the iGEM foundation, for helping spreading the survey. <p><br />
<p>This project was designed and accomplished by Aude Bernheim, Clovis Basier, Matt Deyell, Marguerite Benony and Sebastian Jaramillo in consultation with Edwin Wintermute and Ariel Lindner.</p><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_StudyTeam:Paris Bettencourt/Human Practice/Gender Study2013-10-29T03:38:18Z<p>Marguerite: </p>
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<h2>Background</h2><br />
<p>Science suffers from gender bias</p><br />
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<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>Revealed gender bias in synthetic biology by studying sex ratios in SB conferences and labs</li><br />
<li>Built a database of all iGEM teams reporting all available online information and sex ratios of teams and advisors</li><br />
<li>Conducted a statistical analysis of this data-set and showed among other results that success in iGEM is correlated to gender mix</li><br />
<li>Made recommendations to implement an active gender policy in iGEM</li><br />
</ul><br />
<p></p><br />
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<div class="aims"><br />
<h2>Aims</h2><br />
<p>To investigate gender dynamics in iGEM and in synthetic biology research community at large in a quantitative manner</p><br />
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<a href="#Introduction"><br />
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<h2>Skip to Introduction</h2><br />
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<h2>Skip to Recommendations</h2><br />
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<h2>Skip to Database</h2><br />
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<a href="#Findings"> <br />
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<h2>Skip to Main Findings</h2><br />
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<h2>Skip to Gender Bias in SynBio</h2><br />
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<a href="#Success"><br />
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<h2>Skip to iGEM Diversity and Success</h2><br />
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<a href="#Clues"><br />
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<h2>Skip to Clues to Improve Balance</h2><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Facts"><br />
<div class="hlink" style="width:100%;margin-right:0"><br />
<h2 style="font-size:24px;">Infographics on gender and Synthetic Biology</h2><br />
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<div id="Introduction"></div><br />
<h2>Introduction</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
For every woman killed by TB, there are two men. Our review of the literature on gender bias and tuberculosis can be found <a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Study/Gender_Bias">here</a>. If a disease can be biased, what about ourselves? iGEM? Synthetic biology? Gender bias in science may appear in different forms. Gender balance varies by discipline, by job title, by age or by region. Only 30% of researchers in Europe are women, while 92% of French university deans are men. </p> <p>Hisorically, gender bias has affected the lives of scientists and the practice of science. However, assessing gender bias today in a living community is very difficult. History, stereotypes, limits of the disciplines, and the simple lack of data can prevent us, the synthetic biologists, from thinking about our own relationship to gender.</p><br />
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<div class="rightparagraph"><br />
<p><br />
Most of those issues should not apply in synthetic biology. Synthetic biology is a new field. The argument of the heritage of some habits cannot be made. It is a mix of previously existing disciplines and therefore very open and should not reflect preexisting stereotypes. To study gender bias in iGEM and in synthetic biology we decided to follow a data driven approach. Studying in a quantitative manner this subjects had two main benefits. First it prevented us to apply our own biases and stereotypes on this subject. Secondly, it lead us to construct data base that we make freely available and let anyone test his own hypothesis on this controversial subject and form his own conclusions.</p><br />
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<div id="SynBio"></div><br />
<h2> Synthetic biology field : general overview of gender equality in synthetic biology </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Gender repartition in synthetic biology can be looked at from different perspectives. For this study, two main ways were chosen: composition of labs and conferences. The main reasons for those choices were the accessibility of online data </p><br />
</div><br />
<div class="rightparagraph"><br />
<p><br />
as well as the necessity to get information not only about the general gender balance but also the sex ratio inside a defined category: PhD students, post docs, head of labs... </p><br />
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<div style="clear: both;"></div><br />
<br />
<h2> Synthetic biology labs, a good representation of gender (in)equality in science </h2> <br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Teams of 50 synthetic biology labs were studied. The labs were chosen by their presence on the webpage http://syntheticbiology.org/Labs.html . For each lab, several numbers were reported in a table : total number of people in the team, number of women in the team, number of PhD students, post docs, head of labs, number of women PhD students, post docs, head of labs. From this, the sex ratios (number of women / total number of people) were then calculated for each of those categories. </p><br />
<p><center><a href="https://2013.igem.org/File:ParisB2013_Synthetic_Biology_Research_Groups.xls"><br />
<img src="https://static.igem.org/mediawiki/2013/d/d9/PB_Geneious_Logo.gif" width="500"/><br />
</a></center></p> <br />
<p><br />
The first conclusion that can be made is that women are generally under-represented in synthetic biology labs. 33% correspond to the average presence of women in research in Europe. Indeed according to the European Commission, 32% of researchers in Europe are women <i>(She Figures, 2012)</i>. <br><br>The second finding also reflects well an already known reality in science : the glass ceiling. In 1995, the glass ceiling was defined by the U.S. Department of Labor, as a <i>"political term used to describe "the unseen, yet unbreakable barrier that keeps minorities and women from rising to the upper rungs of the corporate ladder, regardless of their qualifications or achievements" </i>.<br />
With only 17,85\% of heads of labs being women, synthetic biology is still doing slightly better than the average. According to a European study done in 2008 called <i>Mapping the maze,getting women to the top in research</i>., only 15% of women occupy top research position in Europe. However, the number of SB P.I. should be analyzed through the filter of history. In a new field, it would be expected in a world where bias would not be present anymore to have way more women at those positions.<br />
</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
</br></br></br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/4/46/PB_GS_LabsBis.png" width="353px"/><br><br />
<b>Figure 1:Sex ratio in synthetic biology labs</b>. The percentage of women by role in 50 synthetic biology labs. Error bars represent SD. The sex ratio of each lab is determined independently and then the mean of the labs was determined.<br />
</center><br />
<br />
</br></br></br><br />
<center><br />
<TABLE BORDER="1"> <br />
<CAPTION> </CAPTION> <br />
<TR> <br />
<TH>Labs </TH> <br />
<TH> Phd Students </TH> <br />
<TH> Post Docs</TH> <br />
<TH> Head of Labs </TH> <br />
</TR> <br />
<TR> <br />
<TH> 33,10 % </TH> <br />
<TD> 35,39 % </TD> <br />
<TD> 31,31 % </TD> <br />
<TD> 17,85 % </TD> <br />
</TR> <br />
</TABLE><br />
</center><br />
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<br />
<h2> Speakers at SB Conferences : effects of an active gender policy</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
SBX.0 conferences accompanied the development of synthetic biology. They provide a great way to investigate the evolution of gender ratio since the birth of synthetic biology. Moreover, the presence/absence of women as speakers is a known indicator of gender bias and specially of active gender policy. Indeed, several social mechanisms are in place lead to fewer female speakers that could be expected: self censorship, unconscious stereotypes, unconscious choice of only male speakers... However, having female speakers at conference is a key point. It allows women, to gain confidence but also to act as role model for women attending the conference. </p><br />
<p><br />
To study SB conferences, available programs online were downloaded. Data referring to the number of speakers but also to posters were recorded. The data-set could not be completed for certain years due to the impossibility of finding the data online.<br />
</p><br />
<p><center><a href="https://2013.igem.org/File:ParisB2013Resultats_SB.xls">Download the database here</a></center></p><br />
<p><br />
The sex ratio of the speakers have followed a very interesting evolution. It has been multiplied by 3 from SB1 to SB5. This could indicate a change of policy considering speakers. Most likely, the first conferences invited speakers without taking into consideration the gender dimension. Might it be due to some complaints or the raise in awareness of the conferences organizers, the numbers went up. This example is interesting because it clearly show an interest in the subject by the involved community.<br />
</p><br />
<p><br />
Two main conclusions can be drawn on posters. First, the sex ratio of authors in posters has changed throughout the years. Secondly, this number is not as high as the sex ratio in labs. The question is why? The points described above could be underlying reasons, however it is very difficult to truly go beyond this with only those numbers. <br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<br><br><br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/6/62/PB_GS_Sex_ratio_in_SB_Conf.png" width="400px"/><br><br />
<b> Figure 2:Sex ratio in SB conferences</b>. The proportion of speakers and poster presenters at SBX.0 conferences who are women. Data was gathered on-line from available programs.<br />
</center><br />
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<div style="clear: both;"></div><br />
<br />
<h2> Under represented and badly represented</h2> <br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
In order to try to better understand the dynamics of gender behind the posters numbers, the rank of authors were reported for each poster. Sex ratio were calculated for each rank, keeping in mind that in biology, the first author is often a Phd student or a post doc and the last author, the P.I.<br />
</p><br />
<p><br />
As explained above, women are generally under-represented in synthetic biology labs, even less represented at conferences. When looking at the rank of author in posters, another bias appears. Indeed, women are more likely to be present as middle authors than first or last. This bias can be found in papers of different disciplines as shown on the graph realized on the eigenfactor.</p><br />
<p> <br />
The main finding considering gender in synthetic biology is that even though synthetic biology is new and interdisciplinary, it remains quite representative of existing gender bias in science. Therefore it can be concluded, that the issues that have kept women out of science and especially out of top research position are still present and will not be resolved with time. A strong and active policy appears necessary to bring more mixity and therefore diversity in this field.<br />
<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/6/6b/PB_GS_Author_place_.png" width="435px"/> <br><br />
<b>Figure: Sex ratio according to rank of authors in SB posters.</b> Authorship on Posters in SB conferences was collected and Women and Male authors are organized by their rank of authorship. Women tend to be middle authors more often then first or last authors.<br />
</center><br />
<br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/2/28/PB_GS_Eigenfactor.png" width="535px"/><br />
<b>Figure 4: Analysis of rank of authors according to gender in scientific publications.</b>Women's rank of authorship in various journals and databases. There is over-all far more men cited as authors than women, and this is consistent across publications and scientific fields. Additionally, Authorship rank is shown on the bottom with the % of women over all shown as the solid line with the dot indicating the % of women within that authorship rank. Dots above the line indicate that women are over represented compared to the mean and dots below the line indicate that women are underrepresented, with the further they are from the line the greater the imbalance.<br />
</center> <br />
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<div id="Database"></div><br />
<h2> iGEM as a model : a fantastic database </h2><br />
<div class="leftparagraph"><br />
<h3> Online Data</h3> <br />
<p> &nbsp;&nbsp;<br />
All the data concerning iGEM were retrieved from the website : <a href="https://igem.org">https://igem.org</a> <br />
List of teams were retrieved from the webpages <a href="https://igem.org/Team_List.cgi?year=2012">https://igem.org/Team_List.cgi?year=2012</a>.<br />
List of project themes were retrieved from <a href="https://igem.org/Team_Tracks?year=2012">https://igem.org/Team_Tracks?year=2012</a>.<br />
List of prices were retrieved <a href="https://igem.org/Results">https://igem.org/Results</a>.<br />
List of judges were retrieved from: <a href="https://igem.org/Judge_List">https://igem.org/Judge_List</a><br />
</p><br />
<h3> Sex ratio determination :</h3> <br />
<p> &nbsp;&nbsp; For each team, the official team profile was checked to count the number of student members, advisors and instructors.<br />
Then to determine the sex of particpants, wiki were used when names were not obvious, using pictures when they existed. When no pictures were available and names were not obviously referring to one sex, a google image search was done on the name (first and last name) and the sex was chosen as the most represented sex in the pictures (if 10 images of men come up and 30 of women, the participant was considered as a woman).</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
<h3> Database : </h3> <br />
<p> &nbsp;&nbsp; Information for the first year of iGEM were difficult to find because of the non existence of available wiki pages and it was therefore decided not to take into account this year.<br />
Teams who withdrew during the competition were not taken into account since it was most of the time impossible to know the number of participants due to the absence of wiki.<br />
In the end our data set is composed of 662 teams over 5 years. For each team were reported : <br />
Year ; region ; name of the team ; number of student members ; number of women student members ; number of advisors ; number of women advisors ; number of instructors ; number of women instructors ; participation to MIT championship ; medal ; regional prices ; championship prices ;tracks. </p><br />
<p><br />
<center><br />
<a href="https://static.igem.org/mediawiki/2013/3/35/PB_GS_IGEMdatabase.xls"> Download the database here</a><br />
</center><br />
</p><br />
<h3> Attrition by Career Stage</h3><br />
<p> &nbsp;&nbsp; With the introduction of High School iGEM competition, We have quantitative data about gender balance through career progression. By observing trends between the High School Division, Undergraduate and Overgraduate Divisions, Advisors and finally Judges; we can identify potential glass ceilings and find out why women are being lost through various career stages.</p><br />
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<div id="Findings"></div><br />
<h2> iGEM : a mirror of main gender problems </h2><br />
<div class="leftparagraph"><br />
<h3> Teams sex ratio, a very robust value </h3> <br />
<p> &nbsp;&nbsp;<br />
<br><br><br />
The first thing that was examined was the evolution of sex ratio of teams in iGEM across continents and throughout the years.<br />
</p><br />
<br><br />
<p><br />
The striking conclusion of this comparison is that the sex ratio is iGEM teams remains constant through the years and across continents (ANOVA's p-value for the different conditions > 0,5). This shows that women are underrepresented in iGEM teams. </p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/5/5a/GS_Year.png" width="250px"/><br />
<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Region.png" width="250px"/><br />
<b>Figure 5: Sex ratio of iGEM teams through the years and across continents.</b> The proportion of team members of each gender over time and between regions in the collegiate iGEM competition. Bars represent the 95% Confidence interval.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div class="leftparagraph"><br />
<h3> Women do not supervise as much as men </h3> <br />
<p> &nbsp;&nbsp;<br />
The second question investigated was the sex ratios for the different categories of people participating in iGEM. Indeed, iGEM is not only undergrad students. Advisors, instructors, judges also participate representing the complete professional ladder of synthetic biology. A category called Supervisors was created corresponding to instructors and advisers. Indeed, those terms are not understood and used in the same way in different continents. In some countries "advisers" means people who directly teach the teams (mostly grad students and post docs) whereas it means general mentors for others and vice versa.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Role.png" width="300px" height="250px"/> <br><br />
<b>Figure 6: Sex ratios in iGEM according to categories of people participating.</b> The gender balance of students, Supervisors and Judges in iGEM collegiate competitions. Supervisors is taken as the combination of advisors and instructors due to variations on how individual teams differentiate between them. Bars are 95% confidence intervals.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
When executing comparisons tests , team members' sex ratio is found to be different from judges' and instructors' ones (p value < 0,01). However judges and advisers are not significantly different ( p value > 0,5). This result reveals a tendency of women to supervise less than men. Indeed, from team members to instructors, the sex ratio is divided by two. What is even more interesting is to compare those numbers to sex ratios of PhD students and post docs in labs. The sex ratio of instructors is 10 points lower. </p><br />
<p> Women constitute a pool of talent that is not mobilized. They participate but do not supervise teams. They are "lost" along the way. Indeed, in a study published last year in PNAS, researchers showed that P.I. were less prone to have a woman mentoring students than man. This unconscious bias can be translated by a lack of encouragement from P.I.s but also by a self censorship which is not taken into account by other supervisors as explained in an recently published article by Eileen Pollack (E. Pollack Why Are There Still So Few Women in Science? NY TImes October 2013).<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<h3> Tracks and sex ratio in iGEM </h3> <br />
<p> &nbsp;&nbsp;<br />
The third finding goes against an often-heard stereotype "women are more interested by applied research". In order to investigate this subject, tracks were reported for each project. In iGEM tracks correspond to general theme of the project : medicine, fundationnal research…Tracks were then looked at in terms of sex ratios. There is no significant difference between tracks. (ANOVA > 0,1).</p><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/a/ac/PB_GS_Sexratiotracksbis.png" width="535px"/><br />
<b>Figure 7: Sex ratios and tracks in iGEM. </b>The proportion of gender in teams grouped by the track that the team is entered in during collegiate iGEM competitions. There is no statistical significant difference between the gender balance between tracks. <br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<h3> High School Division is more balanced</h3><br />
<p> When we looked at the High School Divison, we found that it had a higher percentage of women than the university iGEM teams. Additionally, The number of female advisors and instructors in the High School division is much higher than that of the Collegiate division and is approximately the same as the proportion of students. This indicates that there is a problem at the Collegiate level and that iGEM can be an important bridge for women to access new opportunities to lead in higher education</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/9/91/PB_HighSchool_Gender_Students.png" width="250px"/><br />
<img src="https://2013.igem.org/File:PB_HS_By_Role.png" width="250px"/><br />
<b>Figure 8: Sex ratios in High School iGEM by year and role. </b>On the left, the proportion of students in the High School Competition that are women for each year. On the right, the proportion of women in each role for all years. Bars represent 95% Confidence Interval.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<p><br />
To conclude, studying the iGEM competition gives a unique quantitative insight on existing questions in the field of gender studies. It also constitutes an amazing argument to convince scientists of the existence of a gender issue in science. As explained by Rascun et al in a recent paper published in PNAS, scientists believe that those type of bias only exist in some labs, not their own, therefore very objective studies need to be conducted to clearly show the reality of the numbers. More over , Jo Handelsman a microbiologist involved in that paper underlined in a recent interview, that people often think that there is still an issue in physics or maths but that there are no more women issues in biology, which is not true. This study supports strongly the view that this general thinking is untrue.<br />
</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Success"></div><br />
<h3> In iGEM, is diversity a factor of success ? </h3><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Several studies led by consulting groups (McKinsey and Company Women Matter, 2007) have shown that mixity in a team increases performance. The big question of what leads to success in iGEM was therefore investigated using the database with a special focus on gender. In order to be able to get a general idea about iGEM team success, a point system was put in place.<br />
</p><br />
<p>Points were attributed the following way.<br><br />
For the medal: 1 point for bronze medal, 2 points for silver medal, 3 points for gold medal. For the world jamboree qualified teams: 2 points for every team taking part in 2010 and before (before regional jamborees existed) , 6 points for team qualified for world final (after 2010). For special prices (Best ...): 6 points were attributed for each regional price earned (only after 2010), 13 points for each price earned in the world final (all price worth 13 points before regional jamborees existed). For the final place in world final: 15 points for the sixth team, 20 points for the fifth team, 25 points for the fourth team, 30 points for the third team, 35 points for the second team, 40 points for the firth team.</p><br />
<p><br />
The aim was to give each team a score that is proportional to the rewards it earned, taking in account that all teams were in world jamboree prior to 2011, without having to be qualified in regional jamborees.<br />
</p><br />
<p>Best score is for the Imperial College London team in 2011 (81 points).<br />
All teams (all years) average is 7.41 points, considering teams with no points (due to withdrew).</p><br />
<p><br />
Correlations studies between this number of points and other variables show that that for all teams, the main variables explaining success in iGEM is the number of years of existence and the size of the team. It would therefore seem that mixity would not be a factor. However, when looking at correlations between variables of teams who truly succeeded (points > 20) , the variables that have a significant correlation with the number of points become the sex ratio and the number of supervisors. Therefore it could be hypothesized that beginning iGEM teams have to face major challenges but when the team existed for a few years and general organization or funding problems have been dealt with , diversity could be a factor for success. </p><br />
<p><br />
In order to check if this could be seen in the best iGEM teams that existed, the sex ratio of of prize winner teams was compared to the one of participating teams with boostrap resampling giving a p-value of 0.035 This means that the sex ratio of winning teams (45%) is significantly different from the one of participating teams (37%)<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/d/de/GS_Prize.png" width="400px" ><br><br />
<b>Figure 9: Gender balance and succes in iGEM. </b> The proportion of women in teams that have won prizes in iGEM compared to the proportion in teams over all. There is a significantly higher proportion of women in teams that win prizes <b>(p=0.034)</b>.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Clues"></div><br />
<h2> Clues to improve mixity </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
<br />
Women are not as represented as men in iGEM. Why should this be a problem ? Indeed, even if it might lead to success as explained above, the need to have gender equality could be questioned. However iGEM is an international competition. One of its main goals is to attract and educate young people as well as trying to have them solve real issues. Synthetic biology might be a key technology to solve the main challenges of the 21st century.</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
<p> The world will need science and if iGEM only succeeds in motivating half of the population that could be interested, this would be a major failure to achieve its mission. Therefore, the last part of the study was aimed at understanding how could iGEM improve mixity within its own ranks.<br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div class="leftparagraph"><br />
<h3> From the data </h3><br />
<p> &nbsp;&nbsp;<br />
By looking at correlation between sex ratios and other variables, the most striking result is the link between team size and sex ratio. Teams of 2 or 3 people are almost only male teams. Even when taking out those very small teams, out of the data set the correlation holds up. This is a first lead. <br><br />
The second analysis that was made regarding the data was to compare the detailed statistics of the 100 most female teams and 100 male teams. Again, it is found that the total team member is lower for male team (9,7 vs 7,8 (p-value 0,0019) we can hypothesize that having women instructors does matter to attract girls in teams. They serve as role models. Having a woman capable of studying and realizing a synthetic biology project is a direct signal to female students that it is also possible for them to do it. Having a woman adviser might also help girls better adapt in a group and reduce their fears about having to endure constant teasing or "male " ambiance.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<h3> From a survey</h3><br />
<p> &nbsp;&nbsp;<br />
Finally, a survey was conducted among iGEMers and former iGEMers to understand their motivations and activities in iGEM. The study was designed to be unbiased and to avoid stereotype threat (for example by putting the question about gender in the end among many other pieces of information). It is still available <a href="http://bit.ly/14WykuZ"> here</a>. Participants in the survey had to rank from 1 to 5 (1 being not important, and 5 very important) answers to questions regarding personnal and professional motivations for participating in iGEM as well values and on what did they spend their time. 63 people answered among whom 32% were women.</p><br />
<br><br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/c/c5/PB_GS_Survey1.png" width="500px" /><br />
<b>Figure 10: Results of survey : what did you hope to learn in iGEM? </b>A survey was distributed to iGEM teams asking participants to rank their motivation to participate in iGEM in various subjects between 1-5. The only significant difference between the motivation of men and women in iGEM were in the subjects leading a team and leading a project.<br />
</center><br />
<br><br><br />
<p><br />
It is interesting to notice that men and women answered almost exactly the same way regarding most of the questions. Women gave a little more importance for the value of fundamental research in iGEM while men graded a bit better "Changing the world". Motivations were approximately the same as well as time spent on each activity. Just a little fact was that men considered human practices a bit more important than women did but spent a little less time on it. <br />
There is only one main difference (more than one point out of five which is represented below) : the will to lead a project and lead a team. It is striking to see how much men are more motivated to lead teams than women. This is definitely to put in relation with the number of women advisers found and the impact it can then have on teams mixity. This could reflect women lack of self esteem in some parts of their work.</p><br />
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<div id="Recommendations"></div><br />
<h2> Recommendations</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Considering all the results that were presented above, here is a list of recommendations for the iGEM foundation to pursue an active policy to improve mixity in iGEM.<br />
<ul><br />
<li> Raise the number of women judges </li> <br />
<li> Promote large teams </li> <br />
<li> Write up a small paragraph to team heads to insist on the importance of motivating young women to be advisers.</li><br />
<li> Giving Bonus point when the team have women advisers </li><br />
</ul><br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>And finally, add in iGEM requirements a Gender reflection. By having teams filling out the database that was built and answering the survey and write a small paragraph about how they see mixity in their team and what it could bring, it would drastically raise the awareness of young men and women about the gender problem in science. Having an up-to-date database is also a great way to see improvements in a quantitative manner. It would allow a direct assessment of the effects of an active gender policy which would be a unique example in science. iGEM could become a leader in that fight and prepare the new generation of scientists to finally get rid of the gender inequality in science<br />
</p><br />
<br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<h2>Litterature</h2><br />
<div class="leftparagraph"><br />
<ul><br />
<li>P. Allotey, M. Gyapong Gender in tuberculosis research INT J TUBERC LUNG DIS 2008 </li><br />
<li>M. Calid, S. Rasul, S Ullah Khan, M; Saeed Gender differences in delay to s to tuberculosis diagnosis and treatment outcome<br><br />
European Commission She figures 2012<br><br />
European Commission, Mapping the gaze : getting more women to the top in Research 2008.<br><br />
</li><br />
<li>C.B. Holmes, H. Hausler, P. Hunn : A review of sex differences in the epidemiology of tuberculosis</li><br />
<li>A. N. Martinez J. T. Rhee, P. M. Small,‡M. A. Behr Sex differences in the epidemiology of tuberculosis in San Francisco INT J TUBERC LUNG DIS 4(1):26–31 2000</li><br />
<li>Moss-Racusin et al, (2012) Science faculty’s subtle gender biases favor male students PNAS </li><br />
<br />
</ul><br />
</div><br />
<div class="rightparagraph"><br />
<ul><br />
<li>McKinsey and Company Women Matter, 2007 </li><br />
<li>Olivier Neyrolles, Lluis Quintana-Murci Sexual Inequality in Tuberculosis, Plos Medicine 2009</li><br />
<li>Nosek et al. (2009) National differences in gender–science stereotypes predict national sex differences in science and math achievement. PNAS June 30, 2009 vol. 106 no. 26 10593–10597</li><br />
<br />
<li>E. Pollack Why Are There Still So Few Women in Science? NY TImes OCtober 2013</li><br />
<li>Al S. Rhines The role of sex differences in the prevalence and transmission of tuberculosis : Tuberculosis 2013</li><br />
<li>M. W. Uplekar, S. Rangan, M. G. Weiss, J. Ogden, M. W. Borgdorff, P. Hudelson Attention to gender issues in tuberculosis control INT J TUBERC LUNG DIS 4(1):26–31 2001</li><br />
</ul><br />
</div><br />
<div style="clear: both;"></div><br />
<h2>Attributions</h2><br />
<p>We would like to thank Flora Vincent, President of <a href="http://wax-science.fr/")>WAX Science</a> association for her precious help in analyzing the results, and Kim de Mora and Kitwa from the iGEM foundation, for helping spreading the survey. <p><br />
<p>This project was designed and accomplished by Aude Bernheim, Clovis Basier, Matt Deyell, Marguerite Benony and Sebastian Jaramillo in consultation with Edwin Wintermute and Ariel Lindner.</p><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_StudyTeam:Paris Bettencourt/Human Practice/Gender Study2013-10-29T03:34:31Z<p>Marguerite: </p>
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<h2>Background</h2><br />
<p>Science suffers from gender bias</p><br />
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<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>Revealed gender bias in synthetic biology by studying sex ratios in SB conferences and labs</li><br />
<li>Built a database of all iGEM teams reporting all available online information and sex ratios of teams and advisors</li><br />
<li>Conducted a statistical analysis of this data-set and showed among other results that success in iGEM is correlated to gender mix</li><br />
<li>Made recommendations to implement an active gender policy in iGEM</li><br />
</ul><br />
<p></p><br />
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<div class="aims"><br />
<h2>Aims</h2><br />
<p>To investigate gender dynamics in iGEM and in synthetic biology research community at large in a quantitative manner</p><br />
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<a href="#Introduction"><br />
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<h2>Skip to Introduction</h2><br />
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<h2>Skip to Recommendations</h2><br />
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<h2>Skip to Database</h2><br />
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<a href="#Findings"> <br />
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<h2>Skip to Main Findings</h2><br />
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<h2>Skip to Gender Bias in SynBio</h2><br />
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<a href="#Success"><br />
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<h2>Skip to iGEM Diversity and Success</h2><br />
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<a href="#Clues"><br />
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<h2>Skip to Clues to Improve Balance</h2><br />
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<a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Facts"><br />
<div class="hlink" style="width:100%;margin-right:0"><br />
<h2 style="font-size:24px;">Infographics on gender and Synthetic Biology</h2><br />
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<div id="Introduction"></div><br />
<h2>Introduction</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
For every woman killed by TB, there are two men. Our review of the literature on gender bias and tuberculosis can be found <a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Gender_Study/Gender_Bias">here</a>. If a disease can be biased, what about ourselves? iGEM? Synthetic biology? Gender bias in science may appear in different forms. Gender balance varies by discipline, by job title, by age or by region. Only 30% of researchers in Europe are women, while 92% of French university deans are men. </p> <p>Hisorically, gender bias has affected the lives of scientists and the practice of science. However, assessing gender bias today in a living community is very difficult. History, stereotypes, limits of the disciplines, and the simple lack of data can prevent us, the synthetic biologists, from thinking about our own relationship to gender.</p><br />
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</div><br />
<div class="rightparagraph"><br />
<p><br />
Most of those issues should not apply in synthetic biology. Synthetic biology is a new field. The argument of the heritage of some habits cannot be made. It is a mix of previously existing disciplines and therefore very open and should not reflect preexisting stereotypes. To study gender bias in iGEM and in synthetic biology we decided to follow a data driven approach. Studying in a quantitative manner this subjects had two main benefits. First it prevented us to apply our own biases and stereotypes on this subject. Secondly, it lead us to construct data base that we make freely available and let anyone test his own hypothesis on this controversial subject and form his own conclusions.</p><br />
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<div id="SynBio"></div><br />
<h2> Synthetic biology field : general overview of gender equality in synthetic biology </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Gender repartition in synthetic biology can be looked at from different perspectives. For this study, two main ways were chosen: composition of labs and conferences. The main reasons for those choices were the accessibility of online data </p><br />
</div><br />
<div class="rightparagraph"><br />
<p><br />
as well as the necessity to get information not only about the general gender balance but also the sex ratio inside a defined category: PhD students, post docs, head of labs... </p><br />
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<div style="clear: both;"></div><br />
<br />
<h2> Synthetic biology labs, a good representation of gender (in)equality in science </h2> <br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Teams of 50 synthetic biology labs were studied. The labs were chosen by their presence on the webpage http://syntheticbiology.org/Labs.html . For each lab, several numbers were reported in a table : total number of people in the team, number of women in the team, number of PhD students, post docs, head of labs, number of women PhD students, post docs, head of labs. From this, the sex ratios (number of women / total number of people) were then calculated for each of those categories. </p><br />
<p><center><a href="https://2013.igem.org/File:ParisB2013_Synthetic_Biology_Research_Groups.xls"><br />
<img src="https://static.igem.org/mediawiki/2013/b/b1/PB_downloadGD.png"/><br />
</a></center></p> <br />
<p><br />
The first conclusion that can be made is that women are generally under-represented in synthetic biology labs. 33% correspond to the average presence of women in research in Europe. Indeed according to the European Commission, 32% of researchers in Europe are women <i>(She Figures, 2012)</i>. <br><br>The second finding also reflects well an already known reality in science : the glass ceiling. In 1995, the glass ceiling was defined by the U.S. Department of Labor, as a <i>"political term used to describe "the unseen, yet unbreakable barrier that keeps minorities and women from rising to the upper rungs of the corporate ladder, regardless of their qualifications or achievements" </i>.<br />
With only 17,85\% of heads of labs being women, synthetic biology is still doing slightly better than the average. According to a European study done in 2008 called <i>Mapping the maze,getting women to the top in research</i>., only 15% of women occupy top research position in Europe. However, the number of SB P.I. should be analyzed through the filter of history. In a new field, it would be expected in a world where bias would not be present anymore to have way more women at those positions.<br />
</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
</br></br></br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/4/46/PB_GS_LabsBis.png" width="353px"/><br><br />
<b>Figure 1:Sex ratio in synthetic biology labs</b>. The percentage of women by role in 50 synthetic biology labs. Error bars represent SD. The sex ratio of each lab is determined independently and then the mean of the labs was determined.<br />
</center><br />
<br />
</br></br></br><br />
<center><br />
<TABLE BORDER="1"> <br />
<CAPTION> </CAPTION> <br />
<TR> <br />
<TH>Labs </TH> <br />
<TH> Phd Students </TH> <br />
<TH> Post Docs</TH> <br />
<TH> Head of Labs </TH> <br />
</TR> <br />
<TR> <br />
<TH> 33,10 % </TH> <br />
<TD> 35,39 % </TD> <br />
<TD> 31,31 % </TD> <br />
<TD> 17,85 % </TD> <br />
</TR> <br />
</TABLE><br />
</center><br />
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<br />
<h2> Speakers at SB Conferences : effects of an active gender policy</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
SBX.0 conferences accompanied the development of synthetic biology. They provide a great way to investigate the evolution of gender ratio since the birth of synthetic biology. Moreover, the presence/absence of women as speakers is a known indicator of gender bias and specially of active gender policy. Indeed, several social mechanisms are in place lead to fewer female speakers that could be expected: self censorship, unconscious stereotypes, unconscious choice of only male speakers... However, having female speakers at conference is a key point. It allows women, to gain confidence but also to act as role model for women attending the conference. </p><br />
<p><br />
To study SB conferences, available programs online were downloaded. Data referring to the number of speakers but also to posters were recorded. The data-set could not be completed for certain years due to the impossibility of finding the data online.<br />
</p><br />
<p><center><a href="https://2013.igem.org/File:ParisB2013Resultats_SB.xls">Download the database here</a></center></p><br />
<p><br />
The sex ratio of the speakers have followed a very interesting evolution. It has been multiplied by 3 from SB1 to SB5. This could indicate a change of policy considering speakers. Most likely, the first conferences invited speakers without taking into consideration the gender dimension. Might it be due to some complaints or the raise in awareness of the conferences organizers, the numbers went up. This example is interesting because it clearly show an interest in the subject by the involved community.<br />
</p><br />
<p><br />
Two main conclusions can be drawn on posters. First, the sex ratio of authors in posters has changed throughout the years. Secondly, this number is not as high as the sex ratio in labs. The question is why? The points described above could be underlying reasons, however it is very difficult to truly go beyond this with only those numbers. <br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<br><br><br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/6/62/PB_GS_Sex_ratio_in_SB_Conf.png" width="400px"/><br><br />
<b> Figure 2:Sex ratio in SB conferences</b>. The proportion of speakers and poster presenters at SBX.0 conferences who are women. Data was gathered on-line from available programs.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<h2> Under represented and badly represented</h2> <br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
In order to try to better understand the dynamics of gender behind the posters numbers, the rank of authors were reported for each poster. Sex ratio were calculated for each rank, keeping in mind that in biology, the first author is often a Phd student or a post doc and the last author, the P.I.<br />
</p><br />
<p><br />
As explained above, women are generally under-represented in synthetic biology labs, even less represented at conferences. When looking at the rank of author in posters, another bias appears. Indeed, women are more likely to be present as middle authors than first or last. This bias can be found in papers of different disciplines as shown on the graph realized on the eigenfactor.</p><br />
<p> <br />
The main finding considering gender in synthetic biology is that even though synthetic biology is new and interdisciplinary, it remains quite representative of existing gender bias in science. Therefore it can be concluded, that the issues that have kept women out of science and especially out of top research position are still present and will not be resolved with time. A strong and active policy appears necessary to bring more mixity and therefore diversity in this field.<br />
<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/6/6b/PB_GS_Author_place_.png" width="435px"/> <br><br />
<b>Figure: Sex ratio according to rank of authors in SB posters.</b> Authorship on Posters in SB conferences was collected and Women and Male authors are organized by their rank of authorship. Women tend to be middle authors more often then first or last authors.<br />
</center><br />
<br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/2/28/PB_GS_Eigenfactor.png" width="535px"/><br />
<b>Figure 4: Analysis of rank of authors according to gender in scientific publications.</b>Women's rank of authorship in various journals and databases. There is over-all far more men cited as authors than women, and this is consistent across publications and scientific fields. Additionally, Authorship rank is shown on the bottom with the % of women over all shown as the solid line with the dot indicating the % of women within that authorship rank. Dots above the line indicate that women are over represented compared to the mean and dots below the line indicate that women are underrepresented, with the further they are from the line the greater the imbalance.<br />
</center> <br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Database"></div><br />
<h2> iGEM as a model : a fantastic database </h2><br />
<div class="leftparagraph"><br />
<h3> Online Data</h3> <br />
<p> &nbsp;&nbsp;<br />
All the data concerning iGEM were retrieved from the website : <a href="https://igem.org">https://igem.org</a> <br />
List of teams were retrieved from the webpages <a href="https://igem.org/Team_List.cgi?year=2012">https://igem.org/Team_List.cgi?year=2012</a>.<br />
List of project themes were retrieved from <a href="https://igem.org/Team_Tracks?year=2012">https://igem.org/Team_Tracks?year=2012</a>.<br />
List of prices were retrieved <a href="https://igem.org/Results">https://igem.org/Results</a>.<br />
List of judges were retrieved from: <a href="https://igem.org/Judge_List">https://igem.org/Judge_List</a><br />
</p><br />
<h3> Sex ratio determination :</h3> <br />
<p> &nbsp;&nbsp; For each team, the official team profile was checked to count the number of student members, advisors and instructors.<br />
Then to determine the sex of particpants, wiki were used when names were not obvious, using pictures when they existed. When no pictures were available and names were not obviously referring to one sex, a google image search was done on the name (first and last name) and the sex was chosen as the most represented sex in the pictures (if 10 images of men come up and 30 of women, the participant was considered as a woman).</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
<h3> Database : </h3> <br />
<p> &nbsp;&nbsp; Information for the first year of iGEM were difficult to find because of the non existence of available wiki pages and it was therefore decided not to take into account this year.<br />
Teams who withdrew during the competition were not taken into account since it was most of the time impossible to know the number of participants due to the absence of wiki.<br />
In the end our data set is composed of 662 teams over 5 years. For each team were reported : <br />
Year ; region ; name of the team ; number of student members ; number of women student members ; number of advisors ; number of women advisors ; number of instructors ; number of women instructors ; participation to MIT championship ; medal ; regional prices ; championship prices ;tracks. </p><br />
<p><br />
<center><br />
<a href="https://static.igem.org/mediawiki/2013/3/35/PB_GS_IGEMdatabase.xls"> Download the database here</a><br />
</center><br />
</p><br />
<h3> Attrition by Career Stage</h3><br />
<p> &nbsp;&nbsp; With the introduction of High School iGEM competition, We have quantitative data about gender balance through career progression. By observing trends between the High School Division, Undergraduate and Overgraduate Divisions, Advisors and finally Judges; we can identify potential glass ceilings and find out why women are being lost through various career stages.</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Findings"></div><br />
<h2> iGEM : a mirror of main gender problems </h2><br />
<div class="leftparagraph"><br />
<h3> Teams sex ratio, a very robust value </h3> <br />
<p> &nbsp;&nbsp;<br />
<br><br><br />
The first thing that was examined was the evolution of sex ratio of teams in iGEM across continents and throughout the years.<br />
</p><br />
<br><br />
<p><br />
The striking conclusion of this comparison is that the sex ratio is iGEM teams remains constant through the years and across continents (ANOVA's p-value for the different conditions > 0,5). This shows that women are underrepresented in iGEM teams. </p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/5/5a/GS_Year.png" width="250px"/><br />
<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Region.png" width="250px"/><br />
<b>Figure 5: Sex ratio of iGEM teams through the years and across continents.</b> The proportion of team members of each gender over time and between regions in the collegiate iGEM competition. Bars represent the 95% Confidence interval.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div class="leftparagraph"><br />
<h3> Women do not supervise as much as men </h3> <br />
<p> &nbsp;&nbsp;<br />
The second question investigated was the sex ratios for the different categories of people participating in iGEM. Indeed, iGEM is not only undergrad students. Advisors, instructors, judges also participate representing the complete professional ladder of synthetic biology. A category called Supervisors was created corresponding to instructors and advisers. Indeed, those terms are not understood and used in the same way in different continents. In some countries "advisers" means people who directly teach the teams (mostly grad students and post docs) whereas it means general mentors for others and vice versa.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/4/41/GS_Role.png" width="300px" height="250px"/> <br><br />
<b>Figure 6: Sex ratios in iGEM according to categories of people participating.</b> The gender balance of students, Supervisors and Judges in iGEM collegiate competitions. Supervisors is taken as the combination of advisors and instructors due to variations on how individual teams differentiate between them. Bars are 95% confidence intervals.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
When executing comparisons tests , team members' sex ratio is found to be different from judges' and instructors' ones (p value < 0,01). However judges and advisers are not significantly different ( p value > 0,5). This result reveals a tendency of women to supervise less than men. Indeed, from team members to instructors, the sex ratio is divided by two. What is even more interesting is to compare those numbers to sex ratios of PhD students and post docs in labs. The sex ratio of instructors is 10 points lower. </p><br />
<p> Women constitute a pool of talent that is not mobilized. They participate but do not supervise teams. They are "lost" along the way. Indeed, in a study published last year in PNAS, researchers showed that P.I. were less prone to have a woman mentoring students than man. This unconscious bias can be translated by a lack of encouragement from P.I.s but also by a self censorship which is not taken into account by other supervisors as explained in an recently published article by Eileen Pollack (E. Pollack Why Are There Still So Few Women in Science? NY TImes October 2013).<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<h3> Tracks and sex ratio in iGEM </h3> <br />
<p> &nbsp;&nbsp;<br />
The third finding goes against an often-heard stereotype "women are more interested by applied research". In order to investigate this subject, tracks were reported for each project. In iGEM tracks correspond to general theme of the project : medicine, fundationnal research…Tracks were then looked at in terms of sex ratios. There is no significant difference between tracks. (ANOVA > 0,1).</p><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/a/ac/PB_GS_Sexratiotracksbis.png" width="535px"/><br />
<b>Figure 7: Sex ratios and tracks in iGEM. </b>The proportion of gender in teams grouped by the track that the team is entered in during collegiate iGEM competitions. There is no statistical significant difference between the gender balance between tracks. <br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<h3> High School Division is more balanced</h3><br />
<p> When we looked at the High School Divison, we found that it had a higher percentage of women than the university iGEM teams. Additionally, The number of female advisors and instructors in the High School division is much higher than that of the Collegiate division and is approximately the same as the proportion of students. This indicates that there is a problem at the Collegiate level and that iGEM can be an important bridge for women to access new opportunities to lead in higher education</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/9/91/PB_HighSchool_Gender_Students.png" width="250px"/><br />
<img src="https://2013.igem.org/File:PB_HS_By_Role.png" width="250px"/><br />
<b>Figure 8: Sex ratios in High School iGEM by year and role. </b>On the left, the proportion of students in the High School Competition that are women for each year. On the right, the proportion of women in each role for all years. Bars represent 95% Confidence Interval.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<p><br />
To conclude, studying the iGEM competition gives a unique quantitative insight on existing questions in the field of gender studies. It also constitutes an amazing argument to convince scientists of the existence of a gender issue in science. As explained by Rascun et al in a recent paper published in PNAS, scientists believe that those type of bias only exist in some labs, not their own, therefore very objective studies need to be conducted to clearly show the reality of the numbers. More over , Jo Handelsman a microbiologist involved in that paper underlined in a recent interview, that people often think that there is still an issue in physics or maths but that there are no more women issues in biology, which is not true. This study supports strongly the view that this general thinking is untrue.<br />
</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Success"></div><br />
<h3> In iGEM, is diversity a factor of success ? </h3><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Several studies led by consulting groups (McKinsey and Company Women Matter, 2007) have shown that mixity in a team increases performance. The big question of what leads to success in iGEM was therefore investigated using the database with a special focus on gender. In order to be able to get a general idea about iGEM team success, a point system was put in place.<br />
</p><br />
<p>Points were attributed the following way.<br><br />
For the medal: 1 point for bronze medal, 2 points for silver medal, 3 points for gold medal. For the world jamboree qualified teams: 2 points for every team taking part in 2010 and before (before regional jamborees existed) , 6 points for team qualified for world final (after 2010). For special prices (Best ...): 6 points were attributed for each regional price earned (only after 2010), 13 points for each price earned in the world final (all price worth 13 points before regional jamborees existed). For the final place in world final: 15 points for the sixth team, 20 points for the fifth team, 25 points for the fourth team, 30 points for the third team, 35 points for the second team, 40 points for the firth team.</p><br />
<p><br />
The aim was to give each team a score that is proportional to the rewards it earned, taking in account that all teams were in world jamboree prior to 2011, without having to be qualified in regional jamborees.<br />
</p><br />
<p>Best score is for the Imperial College London team in 2011 (81 points).<br />
All teams (all years) average is 7.41 points, considering teams with no points (due to withdrew).</p><br />
<p><br />
Correlations studies between this number of points and other variables show that that for all teams, the main variables explaining success in iGEM is the number of years of existence and the size of the team. It would therefore seem that mixity would not be a factor. However, when looking at correlations between variables of teams who truly succeeded (points > 20) , the variables that have a significant correlation with the number of points become the sex ratio and the number of supervisors. Therefore it could be hypothesized that beginning iGEM teams have to face major challenges but when the team existed for a few years and general organization or funding problems have been dealt with , diversity could be a factor for success. </p><br />
<p><br />
In order to check if this could be seen in the best iGEM teams that existed, the sex ratio of of prize winner teams was compared to the one of participating teams with boostrap resampling giving a p-value of 0.035 This means that the sex ratio of winning teams (45%) is significantly different from the one of participating teams (37%)<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/d/de/GS_Prize.png" width="400px" ><br><br />
<b>Figure 9: Gender balance and succes in iGEM. </b> The proportion of women in teams that have won prizes in iGEM compared to the proportion in teams over all. There is a significantly higher proportion of women in teams that win prizes <b>(p=0.034)</b>.<br />
</center><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Clues"></div><br />
<h2> Clues to improve mixity </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
<br />
Women are not as represented as men in iGEM. Why should this be a problem ? Indeed, even if it might lead to success as explained above, the need to have gender equality could be questioned. However iGEM is an international competition. One of its main goals is to attract and educate young people as well as trying to have them solve real issues. Synthetic biology might be a key technology to solve the main challenges of the 21st century.</p><br />
<br />
</div><br />
<div class="rightparagraph"><br />
<p> The world will need science and if iGEM only succeeds in motivating half of the population that could be interested, this would be a major failure to achieve its mission. Therefore, the last part of the study was aimed at understanding how could iGEM improve mixity within its own ranks.<br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div class="leftparagraph"><br />
<h3> From the data </h3><br />
<p> &nbsp;&nbsp;<br />
By looking at correlation between sex ratios and other variables, the most striking result is the link between team size and sex ratio. Teams of 2 or 3 people are almost only male teams. Even when taking out those very small teams, out of the data set the correlation holds up. This is a first lead. <br><br />
The second analysis that was made regarding the data was to compare the detailed statistics of the 100 most female teams and 100 male teams. Again, it is found that the total team member is lower for male team (9,7 vs 7,8 (p-value 0,0019) we can hypothesize that having women instructors does matter to attract girls in teams. They serve as role models. Having a woman capable of studying and realizing a synthetic biology project is a direct signal to female students that it is also possible for them to do it. Having a woman adviser might also help girls better adapt in a group and reduce their fears about having to endure constant teasing or "male " ambiance.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<h3> From a survey</h3><br />
<p> &nbsp;&nbsp;<br />
Finally, a survey was conducted among iGEMers and former iGEMers to understand their motivations and activities in iGEM. The study was designed to be unbiased and to avoid stereotype threat (for example by putting the question about gender in the end among many other pieces of information). It is still available <a href="http://bit.ly/14WykuZ"> here</a>. Participants in the survey had to rank from 1 to 5 (1 being not important, and 5 very important) answers to questions regarding personnal and professional motivations for participating in iGEM as well values and on what did they spend their time. 63 people answered among whom 32% were women.</p><br />
<br><br><br />
<center><br />
<img src="https://static.igem.org/mediawiki/2013/c/c5/PB_GS_Survey1.png" width="500px" /><br />
<b>Figure 10: Results of survey : what did you hope to learn in iGEM? </b>A survey was distributed to iGEM teams asking participants to rank their motivation to participate in iGEM in various subjects between 1-5. The only significant difference between the motivation of men and women in iGEM were in the subjects leading a team and leading a project.<br />
</center><br />
<br><br><br />
<p><br />
It is interesting to notice that men and women answered almost exactly the same way regarding most of the questions. Women gave a little more importance for the value of fundamental research in iGEM while men graded a bit better "Changing the world". Motivations were approximately the same as well as time spent on each activity. Just a little fact was that men considered human practices a bit more important than women did but spent a little less time on it. <br />
There is only one main difference (more than one point out of five which is represented below) : the will to lead a project and lead a team. It is striking to see how much men are more motivated to lead teams than women. This is definitely to put in relation with the number of women advisers found and the impact it can then have on teams mixity. This could reflect women lack of self esteem in some parts of their work.</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div id="Recommendations"></div><br />
<h2> Recommendations</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
Considering all the results that were presented above, here is a list of recommendations for the iGEM foundation to pursue an active policy to improve mixity in iGEM.<br />
<ul><br />
<li> Raise the number of women judges </li> <br />
<li> Promote large teams </li> <br />
<li> Write up a small paragraph to team heads to insist on the importance of motivating young women to be advisers.</li><br />
<li> Giving Bonus point when the team have women advisers </li><br />
</ul><br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>And finally, add in iGEM requirements a Gender reflection. By having teams filling out the database that was built and answering the survey and write a small paragraph about how they see mixity in their team and what it could bring, it would drastically raise the awareness of young men and women about the gender problem in science. Having an up-to-date database is also a great way to see improvements in a quantitative manner. It would allow a direct assessment of the effects of an active gender policy which would be a unique example in science. iGEM could become a leader in that fight and prepare the new generation of scientists to finally get rid of the gender inequality in science<br />
</p><br />
<br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<h2>Litterature</h2><br />
<div class="leftparagraph"><br />
<ul><br />
<li>P. Allotey, M. Gyapong Gender in tuberculosis research INT J TUBERC LUNG DIS 2008 </li><br />
<li>M. Calid, S. Rasul, S Ullah Khan, M; Saeed Gender differences in delay to s to tuberculosis diagnosis and treatment outcome<br><br />
European Commission She figures 2012<br><br />
European Commission, Mapping the gaze : getting more women to the top in Research 2008.<br><br />
</li><br />
<li>C.B. Holmes, H. Hausler, P. Hunn : A review of sex differences in the epidemiology of tuberculosis</li><br />
<li>A. N. Martinez J. T. Rhee, P. M. Small,‡M. A. Behr Sex differences in the epidemiology of tuberculosis in San Francisco INT J TUBERC LUNG DIS 4(1):26–31 2000</li><br />
<li>Moss-Racusin et al, (2012) Science faculty’s subtle gender biases favor male students PNAS </li><br />
<br />
</ul><br />
</div><br />
<div class="rightparagraph"><br />
<ul><br />
<li>McKinsey and Company Women Matter, 2007 </li><br />
<li>Olivier Neyrolles, Lluis Quintana-Murci Sexual Inequality in Tuberculosis, Plos Medicine 2009</li><br />
<li>Nosek et al. (2009) National differences in gender–science stereotypes predict national sex differences in science and math achievement. PNAS June 30, 2009 vol. 106 no. 26 10593–10597</li><br />
<br />
<li>E. Pollack Why Are There Still So Few Women in Science? NY TImes OCtober 2013</li><br />
<li>Al S. Rhines The role of sex differences in the prevalence and transmission of tuberculosis : Tuberculosis 2013</li><br />
<li>M. W. Uplekar, S. Rangan, M. G. Weiss, J. Ogden, M. W. Borgdorff, P. Hudelson Attention to gender issues in tuberculosis control INT J TUBERC LUNG DIS 4(1):26–31 2001</li><br />
</ul><br />
</div><br />
<div style="clear: both;"></div><br />
<h2>Attributions</h2><br />
<p>We would like to thank Flora Vincent, President of <a href="http://wax-science.fr/")>WAX Science</a> association for her precious help in analyzing the results, and Kim de Mora and Kitwa from the iGEM foundation, for helping spreading the survey. <p><br />
<p>This project was designed and accomplished by Aude Bernheim, Clovis Basier, Matt Deyell, Marguerite Benony and Sebastian Jaramillo in consultation with Edwin Wintermute and Ariel Lindner.</p><br />
</div><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/File:PB_downloadGD.pngFile:PB downloadGD.png2013-10-29T03:29:06Z<p>Marguerite: uploaded a new version of &quot;File:PB downloadGD.png&quot;</p>
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<div></div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/AcknowledgementsTeam:Paris Bettencourt/Acknowledgements2013-10-29T03:26:30Z<p>Marguerite: </p>
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<h2>Thanks!</p></h2><br />
<p>The participation of our team at the 2013 competition was made possible through the extremely generous support of the Bettencourt Schueller Foundation, which supports the team since its first appearance in the competition in 2007.</p><br />
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<img src="https://static.igem.org/mediawiki/2013/a/a4/LogoRVB_UParisDescartes.gif" width="100px"/><br />
</a><br />
<a class="sponsor" href="http://www.erasynbio.eu/"><br />
<img src="https://static.igem.org/mediawiki/2013/f/f3/Logo_ERASynbio.jpg" width="100px"/><br />
</a><br />
<div style="clear:both;"></div><br />
<br />
<h2>Host Laboratory</h2><br />
<div class="leftparagraph"><br />
<p>Our iGEM team is kindly hosted in the <a href="http://www.cri-paris.org">CRI (Inderdisciplinary Research Center)</a> located in the <i>Faculté de médecine Paris Descartes</i> at the center of Paris. In the heart of one of Paris' biggest hospitals, the CRI hosts interdisciplinary <a href="http://www.licence.fdv-paris.org">undergraduate (LFdV)</a>, <a href="http://www.aiv-paris.org">Master (AIV)</a>; devoted also to systems and synthetic biology!) as well as a <a href="http://www.fdv-paris.org">PhD program (FdV)</a>. This center is directed by François Taddei and Ariel Lindner. We also want especially like to thank Jake, Zoran, Stanislas, Mathias and Luis, who made themselves available at any time, and guided us through this project.</p><br />
<p><br />
For the Laboratory's facilities, we are kindly hosted by the CRI/INSERM U1001 lab, that lent us benches, microscopes and others facilities. We thank all the members of the INSERM U1001 for their kind help and that they shared not only their equipment but also their experience with us. We want to name Sebastien Fleurier and Marie-Florence Bredèche for their support. We would like to give a special thank Chantal Lotton, the lab manager, for her advices on the bench, her warm words, her organization skills, her introductions, for being there for us any time and that she ensured that we worked safely.</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><img src="https://static.igem.org/mediawiki/2011/3/3e/FaculteCochin.jpeg" height=280px/></center><br />
<p><br />
<table align="center" border=0><br />
<tr><br />
<td align="center"><img src="https://static.igem.org/mediawiki/2013/f/fc/Cri_square.gif" width="135px"/></td><br />
<td align="center"><img src="http://www.cri-paris.org/images/francois_taddei.jpg" height=135px><br/><p>François Taddei</p></td><br />
<td align="center"><img src="http://www.cri-paris.org/images/ariel-trombi.jpg" height=135px><br/><p>Ariel Lindner</p></td><br />
</tr><br />
</table><br />
</p><br />
</div><br />
<div style="clear:both;"></div><br />
<h2>Special Thanks</h2><br />
<div class="leftparagraph"><br />
<p>We want to thank Tamara Milosevic and Maria Pothier who survived the summer with us in the lab.<br />
We would also like to thank the secretary staff of the CRI, Laura Ciriani, Véronique Waquet, Elodie Kaslikowski and the rest of the staff for their help and advice in the administrative tasks and commercial relations every team has to face.<br />
We also want to thank the labs that supported us by making us their parts/strains available. Special thanks go to Monica Ortiz from the Endy Lab in Stanford, Anil Ojha of the University of Pittsburgh, Daniel A. Portnoy from UC Berkeley, Pamela Silver at the Harvard Medical School, Nicole Guiso, Nicolas Hegerle, Brigitte Gicquel, Catherine Grillot-Courvalin and Patrice Courvalin from the Institute Pasteur and Stephane Canaan UMR 7282 - CNRS. Also, thanks to Lorenzo Guglielmetti for useful discussions on the situation of TB in France and Europe. Thanks to Christopher Dye of World Health Organization (WHO) for his wise advice about tuberculosis. Last but not least, thanks to Christopher Anderson for the discussion about our project and about health and synthetic biology. <br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p> Specially, we like to thank Nicola Bertoldi. Nicola did the master with many of us, and coming from a philosophy background he has a great interest in Synthetic Biology. We wanted for him to be in the team, but due to differences in calendar it was not possible. However, during the brief time we got together resulted in the <a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Technology_Transfer">"Technology Transfer"</a> essay.</p></br> <br />
<center><img src="https://static.igem.org/mediawiki/2013/e/e9/Bretagne_2011_099-2.JPG" width="135px"></center><br />
</div><br />
<div style="clear:both;"></div><br />
</div><br />
</html><br />
{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/AcknowledgementsTeam:Paris Bettencourt/Acknowledgements2013-10-29T03:23:25Z<p>Marguerite: </p>
<hr />
<div>{{:Team:Paris_Bettencourt/Wiki}}<br />
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<div><br />
<a class="sponsor" href="http://www.fondationbs.org/"><br />
<img src="https://static.igem.org/mediawiki/2013/9/9a/PB_acknowledgmentsbanner.png"/><br />
</a><br />
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<br />
<style><br />
.sponsor {<br />
float:left;<br />
width:120px;<br />
margin:15px;<br />
text-align:center;<br />
}<br />
.sponsor img {<br />
margin: auto 0;<br />
}<br />
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}<br />
.rightparagraph {<br />
float:left;<br />
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margin:10px 15px;<br />
margin-right:0;<br />
text-align:justify;<br />
}<br />
<br />
</style><br />
<div id="page"><br />
<br />
<h2>Thanks!</p></h2><br />
<p>The participation of our team at the 2013 competition was made possible through the extremely generous support of the Bettencourt Schueller Foundation, which supports the team since its first appearance in the competition in 2007.</p><br />
<br />
<br> <center> <img src="https://static.igem.org/mediawiki/2013/a/ac/009384652.png" width="400px"/></center><br />
<br />
<h2>Our generous sponsors</p></h2><br />
<br />
<br />
<a class="sponsor" href="http://www.geneious.com/"><br />
<img src="https://static.igem.org/mediawiki/2013/d/d9/PB_Geneious_Logo.gif" width="100px"/><br />
</a><br />
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</a><br />
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<img src="https://static.igem.org/mediawiki/2013/4/45/PB_IDTLogo2010.png" width="100px"/><br />
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</a><br />
<div style="clear:both;"></div><br />
<br />
<h2>Host Laboratory</h2><br />
<div class="leftparagraph"><br />
<p>Our iGEM team is kindly hosted in the <a href="http://www.cri-paris.org">CRI (Inderdisciplinary Research Center)</a> located in the <i>Faculté de médecine Paris Descartes</i> at the center of Paris. In the heart of one of Paris' biggest hospitals, the CRI hosts interdisciplinary <a href="http://www.licence.fdv-paris.org">undergraduate (LFdV)</a>, <a href="http://www.aiv-paris.org">Master (AIV)</a>; devoted also to systems and synthetic biology!) as well as a <a href="http://www.fdv-paris.org">PhD program (FdV)</a>. This center is directed by François Taddei and Ariel Lindner. We also want especially like to thank Jake, Zoran, Stanislas, Mathias and Luis, who made themselves available at any time, and guided us through this project.</p><br />
<p><br />
For the Laboratory's facilities, we are kindly hosted by the CRI/INSERM U1001 lab, that lent us benches, microscopes and others facilities. We thank all the members of the INSERM U1001 for their kind help and that they shared not only their equipment but also their experience with us. We want to name Sebastien Fleurier and Marie-Florence Bredèche for their support. We would like to give a special thank Chantal Lotton, the lab manager, for her advices on the bench, her warm words, her organization skills, her introductions, for being there for us any time and that she ensured that we worked safely.</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><img src="https://static.igem.org/mediawiki/2011/3/3e/FaculteCochin.jpeg" height=280px/></center><br />
<p><br />
<table align="center" border=0><br />
<tr><br />
<td align="center"><img src="https://static.igem.org/mediawiki/2013/f/fc/Cri_square.gif" width="135px"/></td><br />
<td align="center"><img src="http://www.cri-paris.org/images/francois_taddei.jpg" height=135px><br/><p>François Taddei</p></td><br />
<td align="center"><img src="http://www.cri-paris.org/images/ariel-trombi.jpg" height=135px><br/><p>Ariel Lindner</p></td><br />
</tr><br />
</table><br />
</p><br />
</div><br />
<div style="clear:both;"></div><br />
<h2>Special Thanks</h2><br />
<div class="leftparagraph"><br />
<p>We want to thank Tamara Milosevic and Maria Pothier who survived the summer with us in the lab.<br />
We would also like to thank the secretary staff of the CRI, Laura Ciriani, Véronique Waquet, Elodie Kaslikowski and the rest of the staff for their help and advice in the administrative tasks and commercial relations every team has to face.<br />
We also want to thank the labs that supported us by making us their parts/strains available. Special thanks go to Monica Ortiz from the Endy Lab in Stanford, Anil Ojha of the University of Pittsburgh, Daniel A. Portnoy from UC Berkeley, Pamela Silver at the Harvard Medical School, Nicole Guiso, Nicolas Hegerle, Brigitte Gicquel, Catherine Grillot-Courvalin and Patrice Courvalin from the Institute Pasteur and Stephane Canaan UMR 7282 - CNRS. Also, thanks to Lorenzo Guglielmetti for useful discussions on the situation of TB in France and Europe. Thanks to Christopher Dye of World Health Organization (WHO) for his wise advice about tuberculosis. Last but not least, thanks to Christopher Anderson for the discussion about our project and about health and synthetic biology. <br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p> Specially, we like to thank Nicola Bertoldi. Nicola did the master with many of us, and coming from a philosophy background he has a great interest in Synthetic Biology. We wanted for him to be in the team, but due to differences in calendar it was not possible. However, during the brief time we got together resulted in the <a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Technology_Transfer">"Technology Transfer"</a> essay.</p></br> <br />
<center><img src="https://static.igem.org/mediawiki/2013/e/e9/Bretagne_2011_099-2.JPG" width="135px"></center><br />
</div><br />
<div style="clear:both;"></div><br />
</div><br />
</html><br />
{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/AcknowledgementsTeam:Paris Bettencourt/Acknowledgements2013-10-29T03:22:03Z<p>Marguerite: </p>
<hr />
<div>{{:Team:Paris_Bettencourt/Wiki}}<br />
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<html><br />
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<style><br />
.sponsor {<br />
float:left;<br />
width:120px;<br />
margin:15px;<br />
text-align:center;<br />
}<br />
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float:left;<br />
margin:10px 15px;<br />
margin-left:0;<br />
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text-align:justify;<br />
}<br />
.rightparagraph {<br />
float:left;<br />
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margin:10px 15px;<br />
margin-right:0;<br />
text-align:justify;<br />
}<br />
<br />
</style><br />
<div id="page"><br />
<br />
<h2>Thanks!</p></h2><br />
<p>The participation of our team at the 2013 competition was made possible through the extremely generous support of the Bettencourt Schueller Foundation, which supports the team since its first appearance in the competition in 2007.</p><br />
<br />
<br> <center> <img src="https://static.igem.org/mediawiki/2013/a/ac/009384652.png" width="400px"/></center><br />
<br />
<h2>Our generous sponsors</p></h2><br />
<br />
<br />
<a class="sponsor" href="http://www.geneious.com/"><br />
<img src="https://static.igem.org/mediawiki/2013/d/d9/PB_Geneious_Logo.gif" width="100px"/><br />
</a><br />
<a class="sponsor" href="http://www.thermoscientificbio.com/fermentas"><br />
<img src="https://static.igem.org/mediawiki/2013/c/c6/PB_Fermentas_logo.jpg" width="100px"/><br />
</a><br />
<a class="sponsor" href="http://eu.idtdna.com/site"><br />
<img src="https://static.igem.org/mediawiki/2013/4/45/PB_IDTLogo2010.png" width="100px"/><br />
</a><br />
<a class="sponsor" href="http://www.mathworks.fr/products/matlab/"><br />
<img src="https://static.igem.org/mediawiki/2013/0/07/PB_Icon-Matlab.png" width="100px"/><br />
</a><br />
<a class="sponsor" href="https://synbiota.ca/welcome_page/welcome"><br />
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</a><br />
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</a><br />
<div style="clear:both;"></div><br />
<br />
<h2>Host Laboratory</h2><br />
<div class="leftparagraph"><br />
<p>Our iGEM team is kindly hosted in the <a href="http://www.cri-paris.org">CRI (Inderdisciplinary Research Center)</a> located in the <i>Faculté de médecine Paris Descartes</i> at the center of Paris. In the heart of one of Paris' biggest hospitals, the CRI hosts interdisciplinary <a href="http://www.licence.fdv-paris.org">undergraduate (LFdV)</a>, <a href="http://www.aiv-paris.org">Master (AIV)</a>; devoted also to systems and synthetic biology!) as well as a <a href="http://www.fdv-paris.org">PhD program (FdV)</a>. This center is directed by François Taddei and Ariel Lindner. We also want especially like to thank Jake, Zoran, Stanislas, Mathias and Luis, who made themselves available at any time, and guided us through this project.</p><br />
<p><br />
For the Laboratory's facilities, we are kindly hosted by the CRI/INSERM U1001 lab, that lent us benches, microscopes and others facilities. We thank all the members of the INSERM U1001 for their kind help and that they shared not only their equipment but also their experience with us. We want to name Sebastien Fleurier and Marie-Florence Bredèche for their support. We would like to give a special thank Chantal Lotton, the lab manager, for her advices on the bench, her warm words, her organization skills, her introductions, for being there for us any time and that she ensured that we worked safely.</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><img src="https://static.igem.org/mediawiki/2011/3/3e/FaculteCochin.jpeg" height=280px/></center><br />
<p><br />
<table align="center" border=0><br />
<tr><br />
<td align="center"><img src="https://static.igem.org/mediawiki/2013/f/fc/Cri_square.gif" width="135px"/></td><br />
<td align="center"><img src="http://www.cri-paris.org/images/francois_taddei.jpg" height=135px><br/><p>François Taddei</p></td><br />
<td align="center"><img src="http://www.cri-paris.org/images/ariel-trombi.jpg" height=135px><br/><p>Ariel Lindner</p></td><br />
</tr><br />
</table><br />
</p><br />
</div><br />
<div style="clear:both;"></div><br />
<h2>Special Thanks</h2><br />
<div class="leftparagraph"><br />
<p>We want to thank Tamara Milosevic and Maria Pothier who survived the summer with us in the lab.<br />
We would also like to thank the secretary staff of the CRI, Laura Ciriani, Véronique Waquet, Elodie Kaslikowski and the rest of the staff for their help and advice in the administrative tasks and commercial relations every team has to face.<br />
We also want to thank the labs that supported us by making us their parts/strains available. Special thanks go to Monica Ortiz from the Endy Lab in Stanford, Anil Ojha of the University of Pittsburgh, Daniel A. Portnoy from UC Berkeley, Pamela Silver at the Harvard Medical School, Nicole Guiso, Nicolas Hegerle, Brigitte Gicquel, Catherine Grillot-Courvalin and Patrice Courvalin from the Institute Pasteur and Stephane Canaan UMR 7282 - CNRS. Also, thanks to Lorenzo Guglielmetti for useful discussions on the situation of TB in France and Europe. Thanks to Christopher Dye of World Health Organization (WHO) for his wise advice about tuberculosis. Last but not least, thanks to Christopher Anderson for the discussion about our project and about health and synthetic biology. <br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p> Specially, we like to thank Nicola Bertoldi. Nicola did the master with many of us, and coming from a philosophy background he has a great interest in Synthetic Biology. We wanted for him to be in the team, but due to differences in calendar it was not possible. However, during the brief time we got together resulted in the <a href="https://2013.igem.org/Team:Paris_Bettencourt/Human_Practice/Technology_Transfer">"Technology Transfer"</a> essay.</p></br> <br />
<center><img src="https://static.igem.org/mediawiki/2013/e/e9/Bretagne_2011_099-2.JPG" width="135px"></center><br />
</div><br />
<div style="clear:both;"></div><br />
</div><br />
</html><br />
{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/File:PB_downloadGD.pngFile:PB downloadGD.png2013-10-29T03:20:32Z<p>Marguerite: </p>
<hr />
<div></div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Project/InfiltrateTeam:Paris Bettencourt/Project/Infiltrate2013-10-29T02:27:44Z<p>Marguerite: </p>
<hr />
<div>{{:Team:Paris_Bettencourt/Wiki}}<br />
{{:Team:Paris_Bettencourt/Menu}}<br />
<html><br />
<div style="width:1100px;margin:0 auto;"><br />
<img src="https://static.igem.org/mediawiki/2013/3/3a/PB_logoParis.gif" width="122px" style="position:absolute;top:40px;right:30px;"/><br />
</div><br />
<img src="https://static.igem.org/mediawiki/2013/0/00/PB_infiltratetitle.png" style="margin-bottom:15px"/><br />
<style><br />
.bkgr, .aims {<br />
width:340px; <br />
}<br />
#page .bkgr p {<br />
}<br />
.biocriks {<br />
width:185px;<br />
}<br />
</style><br />
<div id="page"><br />
<div class="overbox"><br />
<div class="bkgr"><br />
<h2>Background</h2><br />
<p>Latent tuberculosis persists inside macrophages, where it is partially protected from both the host immune system and conventional antibiotics.</p><br />
</div><br />
<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>We expressed the enzyme Trehalose Dimycolate Hydrolase (TDMH) in <i>E. coli</i> and showed that it is highly toxic to mycobacteria in culture.</li><br />
<li>We expressed the listeriolyin O (LLO) gene in <i>E. coli</i> and showed that it is capable of entering the macrophage cytosol.</li><br />
<li>We co-infected macrophages with both mycobacteria and our engineered <i>E. coli</i> to characterize the resulting phagocytosis and killing.</li><br />
<li> We measured the effect of a range of pH (from 3 to 8,8) on <i>M. smegmatis</i> and the TDMH enzyme activity.</li><br />
</ul><br />
</div><br />
<div class="biocriks"><br />
<h2>BioBricks</h2><br />
<ol><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137008" target="_blank">BBa_K1137008 (TDMH)</a></li><br />
</ol><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="aims"><br />
<h2>Aim</h2><br />
<p>To create an <i>E. coli</i> strain capable of entering the macrophage cytosol and delivering a lytic enzyme to kill mycobacteria.</p><br />
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<a href="#Introduction"><br />
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<h2>Skip to Introduction</h2><br />
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<a href="#Design"><br />
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<h2>Skip to Design</h2><br />
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<h2>Skip to Killing Assay</h2><br />
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<h2>Skip to Drug Delivery</h2><br />
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<div id="Introduction"></div><br />
<h2>Introduction</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
<i>Mycobacterium tuberculosis</i> (Mtb), the bacterium responsible for tuberculosis (TB), spreads by aerosol and infects its host through the airways. The bacterium is phagocytosed by macrophages in the lung, yet often evades death in the lysosome. Mtb can persist for years or even decades inside macrophages by inhibiting phagosome/lysosome fusion and supressing the normal acidification of the lysosome.</p><br />
<p>An efficient treatment for persistent TB must enter infected macrophages and kill the pathogen there. In our system, <i>E. coli</i> is both the vector and the therapeutic agent agent by expressing the listeriolyin O gene LLO to enter macrophages and TDMH to kill mycobacteria.<br />
</p><br />
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<div class="rightparagraph"><br />
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<h4>&nbsp;BOX 1: Why is it difficult to treat tuberculosis?</h4><br />
<ul style="width:90%"><br />
<li>Mtb can survive and replicate for years inside the macrophages by supressing the normal process of phagocytosis.</li><br />
<li>The cell wall of <i>M. tuberculosis</i> is thick, waxy and rich in mycolic acids. It it difficult to penetrate with a small-molecule drug.</li><br />
<li>The pathogen grows very slowly inside macrophages. Most conventional antibiotics target processes like DNA replication that are specific to growing cells.</li><br />
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<div id="Design"></div><br />
<h2>TDMH and the mycobacterial cell wall</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;Mycobacterium species share a characteristic cell wall: thick, waxy, hydrophobic, and rich in mycolic acids. The low permeability of the envelope to hydrophilic solutes contributes to the intrinsic drug tolerance in mycobacteria.</p><br />
<p><br />
&nbsp;&nbsp;Trehalose Dimycolate Hydrolase (TDMH) is a cutinase-like serine esterase that triggers rapid lysis of the mycobacterial cell wall by degrading the mycolate layer. The enzyme was first isolated from <i>Mycobacterium smegmatis</i> and subsequently shown to hydrolyze purified TDM from various mycobacterial species. Exposure to TDMH triggers an immediate release of free mycolic acids, ultimately leading to lysis of many mycobacteria including Mtb (Yang et al. 2012).<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;We have used <i>M. smegmatis</i> as a model system because Mtb are highly pathogenic and difficult to culture in the lab. <i>M. smegmatis</i> is a close relative of Mtb, shares many of its membrane properties, and is commonly used as a stand-in for Mtb physiology in the lab.</p><br />
<p>&nbsp;&nbsp;In our system, described in the methods below, we used <i>E. coli</i> BL21 (DE3) as a chassis to express TDMH from an IPTG-inducible strong T7 promoter.</p><br />
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<div id="Killing"></div><br />
<h2>Killing mycobacteria with TDMH</h2><br />
<div class="leftparagraph"><br />
<p><br />
&nbsp;&nbsp;Figure 1 describes how we performed the setup of our experience by making a coculture of <i>M.smegmatis</i> and <i>E.coli</i>.</p><br />
<p>Figure 2(below) shows the killing of <i>M. smegmatis</i> with TDMH expressed by <i>E. coli</i>. We mixed liquid cultures of <i>E. coli</i> and <i>M. smegmatis</i> at equal cell densities as determined by plating assays. When expression of TMDH was induced with IPTG, nearly 99% of the <i>M. smegmatis</i> were killed within six hours. We saw no change in viability in cultures of <i>M. smegmatis</i> alone or when mixed with uninduced <i>E. coli</i>.</p><br />
<p><br />
&nbsp;&nbsp;We next sought to quantify the effectiveness of TDMH killing. We mixed induced<i> E. coli</i> and mycobacteria in different ratios and used plating assays to measure viability. As shown in figure 3 mycobacterial killing displayed dose dependence on the <i>E. coli</i> cell density. Small numbers of <i>E. coli</i> could kill many mycobacteria. For example, in mixed populations with 100 mycobactera for each <i>E. coli</i>, we still observed >50% mycobacterial killing after 2 hours. This indicates that, on average, each <i>E. coli</i> produced enough TDMH to kill 50 mycobacteria. We reason that this killing may be even more effective inside macrophages, where constrained volumes will increase the effective TDMH concentration.</p><br />
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<div class="rightparagraph"><br />
<center><a href="https://static.igem.org/mediawiki/2013/d/d9/PB_FigIva.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/d/d9/PB_FigIva.png" width="70%" style="margin-top:-50px"/></a></center><br />
<p><b>Figure 1</b> Experimental setup of the <i>M. smegmatis</i> killing assay.<div style="font-size:90%"> <i>M. smegmatis</i> and <i>E.coli</i> cells (Uninduced and induced with various concentrations of IPTG) were cultured up to OD 1,then serially diluted. Equal volumes of <i>E.coli</i> and <i>M. smegmatis</i> cultures of the same dilutions were mixed, incubated for 6 hours, and plated at 0,3 and 6 hours. </div></p><br />
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<div class="leftparagraph"><br />
<a href="https://static.igem.org/mediawiki/2013/a/a7/PB_Fig1_Myco_Kill_Curve.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/a/a7/PB_Fig1_Myco_Kill_Curve.png" width="100%"/></a><br />
<p><b>Figure 2</b> TDMH-expressing <i>E.coli</i> kill mycobacteria in culture.<div style="font-size:90%"> We mixed TDMH-expressing <i>E.coli</i> and WT <i>M. smegmatis</i> in LB media at an initial cell density of 107 cells/ml each. Plating assays were used to count specifically <i>M. smegmatis</i> after the indicated times. When TDMH-expression was fully induced with 1 mM IPTG, more than 98% of mycobacteria were killed after 6 hours (red line). Populations of mycobacteria alone (black line) and mycobacteria mixed with uninduced <i>E.coli</i> (blue line) were stable.</div></p><br />
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<div class="rightparagraph"><br />
<center><a href="https://static.igem.org/mediawiki/2013/e/e0/PB_Fig2_Coli_Kill_Ratios.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/e/e0/PB_Fig2_Coli_Kill_Ratios.png" width="100%"/></a></center><br />
<p><b>Figure 3</b> Dose-dependence in killing of mycobacteria by <i>E. coli.</i><div style="font-size:90%">We mixed <i>M. smegmatis</i> at a density of 10<sup>7</sup> cells/ml with <i>E. coli</i> at densities of 10<sup>5</sup> cells/ml (blue line) 10<sup>6</sup> cells/ml (green line) or 10<sup>7</sup> cells/ml to produce the ratios above. Even low densities of <i>E. coli</i> produced significant killing. Uninduced <i>E. coli</i> produced no significant killing.</div></p><br />
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<h2></h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;We investigated further the mechanism of TDMH-mediated cell killing. The TDMH enzyme in our system does not carry a secretion tag. Therefore, lysis of the <i>E. coli</i> membrane is probably required for the protein to reach (and lyse) <i>M. smegmatis</i>. We used plating assays to investigate the effect of TDMH induction on <i>E. coli</i> viability and Bradford assays to measure released protein. The results are presented in figure 4.</p><br />
<p>Figure 4A shows that inducing TDMH-expressing <i>E. coli</i> with IPTG rapidly kills the <i>E. coli.</i> In figure 4B, we show that inducing TDMH expression increases the concentration of free protein in the media. In our model, TDMH induction leads to spontaneous lysis of TDMH-expressing <i>E. coli</i>. This could be simply due to the extremely high protein expression levels driven by the T7 promoter, or it may be partially due to the esterase activities of the TDMH enzyme. Once the TDMH is released from the <i>E. coli</i> it is free to act on mycobacterial membranes, causing lysis and the release of additional proteins.<br />
</p><br />
</br><br />
<p><b>Figure 4</b> Induction of TDMH kills <i>E. coli</i> and releases protein to the media.<div style="font-size:90%"><b>A)</b>Plating assays were used to determine <i>E. coli</i> viability in LB media after the indicated times. TDMH-induced <i>E. coli</i> rapidly lost viability (red line) Uninduced <i>E. coli</i> grew normally following a lag phase (black line).<b>B)</b>Bradford assays were used to measure free protein concentrations in mixed and induced bacterial cultures. When <i>E. coli</i> and mycobacteria are mixed and TDMH-expression is induced, free protein concentrations increase. This is consistent with a model in which TDMH induction leads to the lysis of the <i>E. coli</i> membrane. Action of TDMH on mycobacteria leads to further lysis and protein release.</div></p><br />
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<div class="rightparagraph"><br />
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<center><a href="https://static.igem.org/mediawiki/2013/7/74/PB_Fig3_Coli_Protein_Curve.png" target="_blank"><img width="100%" src="https://static.igem.org/mediawiki/2013/7/74/PB_Fig3_Coli_Protein_Curve.png"/></a></center> <br />
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<div id="Macrophages"></div><br />
<h2>Programmed drug delivery with LLO</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<i>Listeria monocytogenes</i> is a bacterial pathogen that replicates in the cytosol of mammalian cells. The pathogen is initially internalized in host phagosomes, then lyses them to obtain access to the cytosol. A single gene, LLO, is responsible for this activity and is sufficient to convey the phenotype to <i>E. coli</i>.<br />
</p><br />
<p>The LLO protein is activated by the low pH of the lysosme. By forming large pores in the lysosomal membrane, it allows protein delivery to the cytosol of macrophages (Higgins et al. 1999). Using <i>E. coli</i> as a protein vector means we don't need to isolate and purify the TDMH enzyme. </p><br />
<p>We hypothesized that a bacterial delivery system could be efficient and specific in targeting mycobacterial-infected macrophages. In effect, we might take advantage of the natural tendency of macrophages to phagocytose <i>E. coli</i> and their enzymatic payload.</p><br />
<p>Because LLO expression is known to be associated with Listeria pathogenicity, we took extra precautions in our cloning and experiments. These measures are detailed on our team safety page. Briefly, we worked in a Biosafety Level 2 lab under the supervision of two full-time lab managers. We researched and complied with French national and insitutional biosafety rules as they apply to this gene.</p><br />
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<div class="rightparagraph"><br />
<center><img src="https://static.igem.org/mediawiki/2013/b/b7/PB_Killing_assay_macrophages1.png" width="80%"/></center><br />
<p><b>Figure 5</b> Experimental design of the killing assay inside the macrophages. We infected them with <i>M. smegmatis</i> and washed after 1 hour. Then, we infected them with <i>E. coli</i> and washed after 1 hour. The end of this final infection step refers to the time 0 on our graphs. At this time we started the observation under the microscope</p><br />
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<h2><i>E. coli</i> and <i>M. smegmatis</i> coinfections</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;Figure 6 displays J774 macrophages one hour after coinfection with <i>E. coli</i> and <i>M. smegmatis</i>. As described in the methods, the <i>E. coli</i> express TDMH and LLO and fluorescent mRFP as a label. The <i>M. smegmatis</i> express GFP as a label, but are otherwise wild type.</p><br />
<p>The two movies displayed in figure 7 are time-lapse microscopy of live coinfected macrophages collected over a period of 6 hours. Fluorescence patterns revealing the localization of <i>E. coli</i> and <i>M. smegmatis</i> within the macrophages are relatively stable over this time period.</p><br />
</div><br />
<div class="rightparagraph"><br />
<p> We next applied quantitative microscopy to characterize the behavior of our system inside live macrophages. We imaged macrophage populations under several conditions and time points and scored their rates of infection with <i>E. coli</i>, <i>M. smegmatis</i> or both. In all we scored over 13,000 individual cells collected from more than 100 separate images.</p><br />
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<div class="leftparagraph"><br />
<center><a href="https://static.igem.org/mediawiki/2013/5/52/PB_Fig4_Fresh_coinfection.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/5/52/PB_Fig4_Fresh_coinfection.png" width="100%"/></a></center><br />
</br><br />
<a href="https://static.igem.org/mediawiki/2013/5/51/PB_Fig4_Fresh_coinfection_zoom1.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/5/51/PB_Fig4_Fresh_coinfection_zoom1.png" width="48%"/></a><br />
<a href="https://static.igem.org/mediawiki/2013/c/c1/PB_Fig4_Fresh_coinfection_zoom2.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/c/c1/PB_Fig4_Fresh_coinfection_zoom2.png" width="48%" style="margin-left:3%"/></a><br />
<br />
<p><b>Figure 6</b> Coinfection of J774 macrophages with mycobacteria and <i>E. coli</i> expressing TDMH and LLO<div style="font-size:90%"> <i>E. coli</i> (red) express mRFP as a marker and <i>M. smegmatis</i> (green) express GFP as a marker. Macrophages are observed to take up Mycobateria, <i>E. coli</i>, neither or both. This image was collected one hour after introducing the bacteria to the macrophage culture and following extensive washing to remove free bacteria.</div></p><br />
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<div class="rightparagraph"><br />
<iframe frameborder="0" style="margin-bottom:20px;" width="535" height="300" src="http://www.dailymotion.com/embed/video/x15jnu6"></iframe><br />
<iframe frameborder="0" width="535" height="300" src="http://www.dailymotion.com/embed/video/x15jnv8"></iframe><br />
<p><b>Figure 7</b> Temporal dynamics of macrophages coinfected with <i>E. coli</i> and <i>M. smegmatis.</i><div style="font-size:90%"><i>E. coli</i> and <i>M. smegmatis</i>, expressing mRFP and GFP respectively, were introduced to J774 macrophages. Fluorescent and bright field images were collected every 15 minutes for 6 hours. In these movies, the <i>E. coli</i> also express TDMH and LLO. Macrophages are observed to uptake <i>E. coli</i>, <i>M. smegmatis</i>, neither or both. The fluorescence patterns appear stable for these conditions and time period.</div></p><br />
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<h2>pH influence </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;We wanted to study the pH influence on <i>M. smegmatis</i> growth and on TDMH enzyme activity. We know that the phagosomal pH is usually acid (around 6) but can reach 4,5. We wondered if TDMH enzyme was working at this range of pH.</p><br />
<p>We studied 7 different buffers : 3 ; 4,5 ; 5,1 ; 6,4 ; 7,35 ; 8,2 and 8,8. </p><br />
<p> The Figure shows that at pH 3, <i>M. smegmatis</i> is not growing. Since it is an OD, we can't say if the bacteria is alive or dead. However, the OD is not growing which suggest that the bacteria is probably killed by TDMH.</p><br />
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</div><br />
<div class="rightparagraph"><br />
<br />
<center> <img src="https://static.igem.org/mediawiki/2013/e/e4/PB_TBC_PH_indepedence.png" width="80%"/></center> <p><b>Figure 8</b> pH influence on TDMH enzyme activity <div style="font-size:90%"> We add to <i>M.smegmatis</i> the proteins of an induced control, the uninduced strain of Bl21 and the induced strain producing TDMH.</div></p><br />
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<h2>Conclusions and continuing work</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;We have shown that <i>E. coli</i> can effectively kill mycobacteria in culture by expressing the TDMH enzyme, now a BioBrick. We have further shown that <i>E. coli</i> and mycobateria may co-localize within macrophages, where LLO-based systems can effectively deliver protein payloads.</p><br />
<p>In the coming weeks, we will continue to refine our cell culture techniques to precisely characterize the effectiveness of our system <i>in situ</i>, within the living macrophage.</p><br />
<p><b>Figure 9</b> The effect of TDMH-induced <i>E. coli</i> on macrophage infection rates after 3 hours.<div style="font-size:90%">We scored fluorescence microscopy images of macrophages exposed to both <i>E. coli</i> and <i>M. smegmatis</i> expressing fluorescent protein markers. The <i>E. coli</i> expressed LLO and were induced or uninduced for TDMH expression. For both treatments, we observed an increase in the infection rates of both bacteria after 3 hours. We attribute this to combination of the media with free bacteria, which macrophages continue to consume over the course of the experiment. TDMH induction slowed the increase in <i>E. coli</i> infection rates, which is likely due to the toxic effects of TDMH expression on <i>E. coli</i>, as shown in figure 4.</div></p><br />
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<div class="rightparagraph"><br />
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<h2>Bibliography</h2><br />
<ul><br />
<li>Yang Y, Bhatti A, Ke D, Gonzalez-Juarrero M, Lenaerts A, Kremer L, Guerardel Y, Zhang P, Ojha AK (2012) : Exposure to a cutinase-like serine esterase triggers rapid lysis of multiple mycobacterial species. J Biol Chem. 2013 Jan 4;288(1):382-92.</li><br />
<li>Rajesh Jayachandran, Varadharajan Sundaramurthy, Benoit Combaluzier , Philipp Mueller, Hannelie Korf, Kris Huygen, Toru Miyazaki, Imke Albrecht, Jan Massner, Jean Pieters (2007) : Survival of Mycobacteria in Macrophages Is Mediated by Coronin 1-Dependent Activation of Calcineurin. Cell, Volume 130, Issue 1, 13 July 2007, Pages 12-14 </li><br />
</ul><br />
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<h2>Attributions</h2> <br />
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<p>pET21 1519 plasmid was kindly provided by Anil Ojha of the University of Pittsburgh.</p><br />
<p> Murine cell line macrophages J774 were a gift from Nicole Guiso and Nicolas Hegerle from Pasteur institute (Unit of Molecular Prevention and Therapy of Human Diseases. </p><br />
<p> <i>Mycobacterium smegmatis</i> was a gift from Brigitte Gicquel from Pasteur institute (Unit Mycobacterial genetics). </p><br />
<p> <i>Mycobacterium smegmatis</i> expressing GFP was kindly provided by Stephane Canaan from CNRS (Laboratory of Enzymology at Interfaces and Physiology of Lipolysis). </p><br />
<p>The project itself was designed and accomplished by Camélia Bencherif and Iva Atanaskovic with consultation with Edwin Wintermute, Mathias Toulouze and Ariel Lindner.</p><br />
<p> We also discussed the project with Christopher Anderson from Berkeley University (Synthetic biology Anderson lab) about the feasibility, good points and critical points of the project. </p><br />
<p> We want to thank all these people that made Infiltrate project happen !</p><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Project/InfiltrateTeam:Paris Bettencourt/Project/Infiltrate2013-10-29T02:26:11Z<p>Marguerite: </p>
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<h2>Background</h2><br />
<p>Latent tuberculosis persists inside macrophages, where it is partially protected from both the host immune system and conventional antibiotics.</p><br />
</div><br />
<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>We expressed the enzyme Trehalose Dimycolate Hydrolase (TDMH) in <i>E. coli</i> and showed that it is highly toxic to mycobacteria in culture.</li><br />
<li>We expressed the listeriolyin O (LLO) gene in <i>E. coli</i> and showed that it is capable of entering the macrophage cytosol.</li><br />
<li>We co-infected macrophages with both mycobacteria and our engineered <i>E. coli</i> to characterize the resulting phagocytosis and killing.</li><br />
<li> We measured the effect of a range of pH (from 3 to 8,8) on <i>M. smegmatis</i> and the TDMH enzyme activity.</li><br />
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<div class="biocriks"><br />
<h2>BioBricks</h2><br />
<ol><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137008" target="_blank">BBa_K1137008 (TDMH)</a></li><br />
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<div class="aims"><br />
<h2>Aim</h2><br />
<p>To create an <i>E. coli</i> strain capable of entering the macrophage cytosol and delivering a lytic enzyme to kill mycobacteria.</p><br />
</div><br />
<a href="#Introduction"><br />
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<h2>Skip to Introduction</h2><br />
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<a href="#Design"><br />
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<h2>Skip to Design</h2><br />
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<a href="#Killing"><br />
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<h2>Skip to Killing Assay</h2><br />
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<a href="#Macrophages"> <br />
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<h2>Skip to Drug Delivery</h2><br />
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<div id="Introduction"></div><br />
<h2>Introduction</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
<i>Mycobacterium tuberculosis</i> (Mtb), the bacterium responsible for tuberculosis (TB), spreads by aerosol and infects its host through the airways. The bacterium is phagocytosed by macrophages in the lung, yet often evades death in the lysosome. Mtb can persist for years or even decades inside macrophages by inhibiting phagosome/lysosome fusion and supressing the normal acidification of the lysosome.</p><br />
<p>An efficient treatment for persistent TB must enter infected macrophages and kill the pathogen there. In our system, <i>E. coli</i> is both the vector and the therapeutic agent agent by expressing the listeriolyin O gene LLO to enter macrophages and TDMH to kill mycobacteria.<br />
</p><br />
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<div class="rightparagraph"><br />
<div style="width:90%;margin-left:5%;border:2px solid;"><br />
<h4>&nbsp;BOX 1: Why is it difficult to treat tuberculosis?</h4><br />
<ul style="width:90%"><br />
<li>Mtb can survive and replicate for years inside the macrophages by supressing the normal process of phagocytosis.</li><br />
<li>The cell wall of <i>M. tuberculosis</i> is thick, waxy and rich in mycolic acids. It it difficult to penetrate with a small-molecule drug.</li><br />
<li>The pathogen grows very slowly inside macrophages. Most conventional antibiotics target processes like DNA replication that are specific to growing cells.</li><br />
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<div id="Design"></div><br />
<h2>TDMH and the mycobacterial cell wall</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;Mycobacterium species share a characteristic cell wall: thick, waxy, hydrophobic, and rich in mycolic acids. The low permeability of the envelope to hydrophilic solutes contributes to the intrinsic drug tolerance in mycobacteria.</p><br />
<p><br />
&nbsp;&nbsp;Trehalose Dimycolate Hydrolase (TDMH) is a cutinase-like serine esterase that triggers rapid lysis of the mycobacterial cell wall by degrading the mycolate layer. The enzyme was first isolated from <i>Mycobacterium smegmatis</i> and subsequently shown to hydrolyze purified TDM from various mycobacterial species. Exposure to TDMH triggers an immediate release of free mycolic acids, ultimately leading to lysis of many mycobacteria including Mtb (Yang et al. 2012).<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;We have used <i>M. smegmatis</i> as a model system because Mtb are highly pathogenic and difficult to culture in the lab. <i>M. smegmatis</i> is a close relative of Mtb, shares many of its membrane properties, and is commonly used as a stand-in for Mtb physiology in the lab.</p><br />
<p>&nbsp;&nbsp;In our system, described in the methods below, we used <i>E. coli</i> BL21 (DE3) as a chassis to express TDMH from an IPTG-inducible strong T7 promoter.</p><br />
</div><br />
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<br />
<div id="Killing"></div><br />
<h2>Killing mycobacteria with TDMH</h2><br />
<div class="leftparagraph"><br />
<p><br />
&nbsp;&nbsp;Figure 1 describes how we performed the setup of our experience by making a coculture of <i>M.smegmatis</i> and <i>E.coli</i>.</p><br />
<p>Figure 2(below) shows the killing of <i>M. smegmatis</i> with TDMH expressed by <i>E. coli</i>. We mixed liquid cultures of <i>E. coli</i> and <i>M. smegmatis</i> at equal cell densities as determined by plating assays. When expression of TMDH was induced with IPTG, nearly 99% of the <i>M. smegmatis</i> were killed within six hours. We saw no change in viability in cultures of <i>M. smegmatis</i> alone or when mixed with uninduced <i>E. coli</i>.</p><br />
<p><br />
&nbsp;&nbsp;We next sought to quantify the effectiveness of TDMH killing. We mixed induced<i> E. coli</i> and mycobacteria in different ratios and used plating assays to measure viability. As shown in figure 3 mycobacterial killing displayed dose dependence on the <i>E. coli</i> cell density. Small numbers of <i>E. coli</i> could kill many mycobacteria. For example, in mixed populations with 100 mycobactera for each <i>E. coli</i>, we still observed >50% mycobacterial killing after 2 hours. This indicates that, on average, each <i>E. coli</i> produced enough TDMH to kill 50 mycobacteria. We reason that this killing may be even more effective inside macrophages, where constrained volumes will increase the effective TDMH concentration.</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><a href="https://static.igem.org/mediawiki/2013/d/d9/PB_FigIva.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/d/d9/PB_FigIva.png" width="70%" style="margin-top:-50px"/></a></center><br />
<p><b>Figure 1</b> Experimental setup of the <i>M. smegmatis</i> killing assay.<div style="font-size:90%"> <i>M. smegmatis</i> and <i>E.coli</i> cells (Uninduced and induced with various concentrations of IPTG) were cultured up to OD 1,then serially diluted. Equal volumes of <i>E.coli</i> and <i>M. smegmatis</i> cultures of the same dilutions were mixed, incubated for 6 hours, and plated at 0,3 and 6 hours. </div></p><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<a href="https://static.igem.org/mediawiki/2013/a/a7/PB_Fig1_Myco_Kill_Curve.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/a/a7/PB_Fig1_Myco_Kill_Curve.png" width="100%"/></a><br />
<p><b>Figure 2</b> TDMH-expressing <i>E.coli</i> kill mycobacteria in culture.<div style="font-size:90%"> We mixed TDMH-expressing <i>E.coli</i> and WT <i>M. smegmatis</i> in LB media at an initial cell density of 107 cells/ml each. Plating assays were used to count specifically <i>M. smegmatis</i> after the indicated times. When TDMH-expression was fully induced with 1 mM IPTG, more than 98% of mycobacteria were killed after 6 hours (red line). Populations of mycobacteria alone (black line) and mycobacteria mixed with uninduced <i>E.coli</i> (blue line) were stable.</div></p><br />
</div><br />
<div class="rightparagraph"><br />
<center><a href="https://static.igem.org/mediawiki/2013/e/e0/PB_Fig2_Coli_Kill_Ratios.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/e/e0/PB_Fig2_Coli_Kill_Ratios.png" width="100%"/></a></center><br />
<p><b>Figure 3</b> Dose-dependence in killing of mycobacteria by <i>E. coli.</i><div style="font-size:90%">We mixed <i>M. smegmatis</i> at a density of 10<sup>7</sup> cells/ml with <i>E. coli</i> at densities of 10<sup>5</sup> cells/ml (blue line) 10<sup>6</sup> cells/ml (green line) or 10<sup>7</sup> cells/ml to produce the ratios above. Even low densities of <i>E. coli</i> produced significant killing. Uninduced <i>E. coli</i> produced no significant killing.</div></p><br />
</div><br />
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<br />
<h2></h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;We investigated further the mechanism of TDMH-mediated cell killing. The TDMH enzyme in our system does not carry a secretion tag. Therefore, lysis of the <i>E. coli</i> membrane is probably required for the protein to reach (and lyse) <i>M. smegmatis</i>. We used plating assays to investigate the effect of TDMH induction on <i>E. coli</i> viability and Bradford assays to measure released protein. The results are presented in figure 4.</p><br />
<p>Figure 4A shows that inducing TDMH-expressing <i>E. coli</i> with IPTG rapidly kills the <i>E. coli.</i> In figure 4B, we show that inducing TDMH expression increases the concentration of free protein in the media. In our model, TDMH induction leads to spontaneous lysis of TDMH-expressing <i>E. coli</i>. This could be simply due to the extremely high protein expression levels driven by the T7 promoter, or it may be partially due to the esterase activities of the TDMH enzyme. Once the TDMH is released from the <i>E. coli</i> it is free to act on mycobacterial membranes, causing lysis and the release of additional proteins.<br />
</p><br />
</br><br />
<p><b>Figure 4</b> Induction of TDMH kills <i>E. coli</i> and releases protein to the media.<div style="font-size:90%"><b>A)</b>Plating assays were used to determine <i>E. coli</i> viability in LB media after the indicated times. TDMH-induced <i>E. coli</i> rapidly lost viability (red line) Uninduced <i>E. coli</i> grew normally following a lag phase (black line).<b>B)</b>Bradford assays were used to measure free protein concentrations in mixed and induced bacterial cultures. When <i>E. coli</i> and mycobacteria are mixed and TDMH-expression is induced, free protein concentrations increase. This is consistent with a model in which TDMH induction leads to the lysis of the <i>E. coli</i> membrane. Action of TDMH on mycobacteria leads to further lysis and protein release.</div></p><br />
</div><br />
<div class="rightparagraph"><br />
</br></br></br></br></br><br />
<center><a href="https://static.igem.org/mediawiki/2013/7/74/PB_Fig3_Coli_Protein_Curve.png" target="_blank"><img width="100%" src="https://static.igem.org/mediawiki/2013/7/74/PB_Fig3_Coli_Protein_Curve.png"/></a></center> <br />
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<br />
<div id="Macrophages"></div><br />
<h2>Programmed drug delivery with LLO</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<i>Listeria monocytogenes</i> is a bacterial pathogen that replicates in the cytosol of mammalian cells. The pathogen is initially internalized in host phagosomes, then lyses them to obtain access to the cytosol. A single gene, LLO, is responsible for this activity and is sufficient to convey the phenotype to <i>E. coli</i>.<br />
</p><br />
<p>The LLO protein is activated by the low pH of the lysosme. By forming large pores in the lysosomal membrane, it allows protein delivery to the cytosol of macrophages (Higgins et al. 1999). Using <i>E. coli</i> as a protein vector means we don't need to isolate and purify the TDMH enzyme. </p><br />
<p>We hypothesized that a bacterial delivery system could be efficient and specific in targeting mycobacterial-infected macrophages. In effect, we might take advantage of the natural tendency of macrophages to phagocytose <i>E. coli</i> and their enzymatic payload.</p><br />
<p>Because LLO expression is known to be associated with Listeria pathogenicity, we took extra precautions in our cloning and experiments. These measures are detailed on our team safety page. Briefly, we worked in a Biosafety Level 2 lab under the supervision of two full-time lab managers. We researched and complied with French national and insitutional biosafety rules as they apply to this gene.</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><img src="https://static.igem.org/mediawiki/2013/b/b7/PB_Killing_assay_macrophages1.png" width="80%"/></center><br />
<p><b>Figure 5</b> Experimental design of the killing assay inside the macrophages. We infected them with <i>M. smegmatis</i> and washed after 1 hour. Then, we infected them with <i>E. coli</i> and washed after 1 hour. The end of this final infection step refers to the time 0 on our graphs. At this time we started the observation under the microscope</p><br />
</div><br />
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<br />
<h2><i>E. coli</i> and <i>M. smegmatis</i> coinfections</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;Figure 6 displays J774 macrophages one hour after coinfection with <i>E. coli</i> and <i>M. smegmatis</i>. As described in the methods, the <i>E. coli</i> express TDMH and LLO and fluorescent mRFP as a label. The <i>M. smegmatis</i> express GFP as a label, but are otherwise wild type.</p><br />
<p>The two movies displayed in figure 7 are time-lapse microscopy of live coinfected macrophages collected over a period of 6 hours. Fluorescence patterns revealing the localization of <i>E. coli</i> and <i>M. smegmatis</i> within the macrophages are relatively stable over this time period.</p><br />
</div><br />
<div class="rightparagraph"><br />
<p> We next applied quantitative microscopy to characterize the behavior of our system inside live macrophages. We imaged macrophage populations under several conditions and time points and scored their rates of infection with <i>E. coli</i>, <i>M. smegmatis</i> or both. In all we scored over 13,000 individual cells collected from more than 100 separate images.</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<center><a href="https://static.igem.org/mediawiki/2013/5/52/PB_Fig4_Fresh_coinfection.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/5/52/PB_Fig4_Fresh_coinfection.png" width="100%"/></a></center><br />
</br><br />
<a href="https://static.igem.org/mediawiki/2013/5/51/PB_Fig4_Fresh_coinfection_zoom1.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/5/51/PB_Fig4_Fresh_coinfection_zoom1.png" width="48%"/></a><br />
<a href="https://static.igem.org/mediawiki/2013/c/c1/PB_Fig4_Fresh_coinfection_zoom2.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/c/c1/PB_Fig4_Fresh_coinfection_zoom2.png" width="48%" style="margin-left:3%"/></a><br />
<br />
<p><b>Figure 6</b> Coinfection of J774 macrophages with mycobacteria and <i>E. coli</i> expressing TDMH and LLO<div style="font-size:90%"> <i>E. coli</i> (red) express mRFP as a marker and <i>M. smegmatis</i> (green) express GFP as a marker. Macrophages are observed to take up Mycobateria, <i>E. coli</i>, neither or both. This image was collected one hour after introducing the bacteria to the macrophage culture and following extensive washing to remove free bacteria.</div></p><br />
</div><br />
<div class="rightparagraph"><br />
<iframe frameborder="0" style="margin-bottom:20px;" width="535" height="300" src="http://www.dailymotion.com/embed/video/x15jnu6"></iframe><br />
<iframe frameborder="0" width="535" height="300" src="http://www.dailymotion.com/embed/video/x15jnv8"></iframe><br />
<p><b>Figure 7</b> Temporal dynamics of macrophages coinfected with <i>E. coli</i> and <i>M. smegmatis.</i><div style="font-size:90%"><i>E. coli</i> and <i>M. smegmatis</i>, expressing mRFP and GFP respectively, were introduced to J774 macrophages. Fluorescent and bright field images were collected every 15 minutes for 6 hours. In these movies, the <i>E. coli</i> also express TDMH and LLO. Macrophages are observed to uptake <i>E. coli</i>, <i>M. smegmatis</i>, neither or both. The fluorescence patterns appear stable for these conditions and time period.</div></p><br />
<br />
</div><br />
<br />
<br />
<h2>pH influence </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;We wanted to study the pH influence on <i>M. smegmatis</i> growth and on TDMH enzyme activity. We know that the phagosomal pH is usually acid (around 6) but can reach 4,5. We wondered if TDMH enzyme was working at this range of pH.</p><br />
<p>We studied 7 different buffers : 3 ; 4,5 ; 5,1 ; 6,4 ; 7,35 ; 8,2 and 8,8. </p><br />
<p> The Figure shows that at pH 3, <i>M. smegmatis</i> is not growing. Since it is an OD, we can't say if the bacteria is alive or dead. However, the OD is not growing which suggest that the bacteria is probably killed by TDMH.</p><br />
<br />
<br />
</div><br />
<div class="rightparagraph"><br />
<br />
<center> <img src="https://static.igem.org/mediawiki/2013/e/e4/PB_TBC_PH_indepedence.png" width="80%"/></center> <p><b>Figure 8</b> pH influence on TDMH enzyme activity <div style="font-size:90%"> We add to <i>M.smegmatis</i> the proteins of an induced control, the uninduced strain of Bl21 and the induced strain producing TDMH.</div></p><br />
</div><br />
<br />
<br />
<div style="clear: both;"></div><br />
<br />
<h2>Conclusions and continuing work</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;We have shown that <i>E. coli</i> can effectively kill mycobacteria in culture by expressing the TDMH enzyme, now a BioBrick. We have further shown that <i>E. coli</i> and mycobateria may co-localize within macrophages, where LLO-based systems can effectively deliver protein payloads.</p><br />
<p>In the coming weeks, we will continue to refine our cell culture techniques to precisely characterize the effectiveness of our system <i>in situ</i>, within the living macrophage.</p><br />
<p><b>Figure 9</b> The effect of TDMH-induced <i>E. coli</i> on macrophage infection rates after 3 hours.<div style="font-size:90%">We scored fluorescence microscopy images of macrophages exposed to both <i>E. coli</i> and <i>M. smegmatis</i> expressing fluorescent protein markers. The <i>E. coli</i> expressed LLO and were induced or uninduced for TDMH expression. For both treatments, we observed an increase in the infection rates of both bacteria after 3 hours. We attribute this to combination of the media with free bacteria, which macrophages continue to consume over the course of the experiment. TDMH induction slowed the increase in <i>E. coli</i> infection rates, which is likely due to the toxic effects of TDMH expression on <i>E. coli</i>, as shown in figure 4.</div></p><br />
</div><br />
<div class="rightparagraph"><br />
<center><img src="https://static.igem.org/mediawiki/2013/1/15/PB_Fig6_Image_Counts.png" width="80%"/></center><br />
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<br />
<h2>Bibliography</h2><br />
<ul><br />
<li>Yang Y, Bhatti A, Ke D, Gonzalez-Juarrero M, Lenaerts A, Kremer L, Guerardel Y, Zhang P, Ojha AK (2012) : Exposure to a cutinase-like serine esterase triggers rapid lysis of multiple mycobacterial species. J Biol Chem. 2013 Jan 4;288(1):382-92.</li><br />
<li>Rajesh Jayachandran, Varadharajan Sundaramurthy, Benoit Combaluzier , Philipp Mueller, Hannelie Korf, Kris Huygen, Toru Miyazaki, Imke Albrecht, Jan Massner, Jean Pieters (2007) : Survival of Mycobacteria in Macrophages Is Mediated by Coronin 1-Dependent Activation of Calcineurin. Cell, Volume 130, Issue 1, 13 July 2007, Pages 12-14 </li><br />
</ul><br />
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<br />
<h2>Attributions</h2> <br />
<br />
<p>pET21 1519 plasmid was kindly provided by Anil Ojha of the University of Pittsburgh.</p><br />
<p> Murine cell line macrophages J774 were a gift from Nicole Guiso and Nicolas Hegerle from Pasteur institute (Unit of Molecular Prevention and Therapy of Human Diseases. </p><br />
<p> <i>Mycobacterium smegmatis</i> was a gift from Brigitte Gicquel from Pasteur institute (Unit Mycobacterial genetics). </p><br />
<p> <i>Mycobacterium smegmatis</i> expressing GFP was kindly provided by Stephane Canaan from CNRS (Laboratory of Enzymology at Interfaces and Physiology of Lipolysis). </p><br />
<p>The project itself was designed and accomplished by Camélia Bencherif and Iva Atanaskovic with consultation with Edwin Wintermute, Mathias Toulouze and Ariel Lindner.</p><br />
<p> We also discussed the project with Christopher Anderson from Berkeley University (Synthetic biology Anderson lab) about the feasibility, good points and critical points of the project. </p><br />
<p> We want to thank all these people that made Infiltrate project happen !</p><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/File:PB_inhalorinfiltrate.pngFile:PB inhalorinfiltrate.png2013-10-29T02:25:42Z<p>Marguerite: uploaded a new version of &quot;File:PB inhalorinfiltrate.png&quot;</p>
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<div></div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Project/InfiltrateTeam:Paris Bettencourt/Project/Infiltrate2013-10-29T02:23:05Z<p>Marguerite: </p>
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<h2>Background</h2><br />
<p>Latent tuberculosis persists inside macrophages, where it is partially protected from both the host immune system and conventional antibiotics.</p><br />
</div><br />
<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>We expressed the enzyme Trehalose Dimycolate Hydrolase (TDMH) in <i>E. coli</i> and showed that it is highly toxic to mycobacteria in culture.</li><br />
<li>We expressed the listeriolyin O (LLO) gene in <i>E. coli</i> and showed that it is capable of entering the macrophage cytosol.</li><br />
<li>We co-infected macrophages with both mycobacteria and our engineered <i>E. coli</i> to characterize the resulting phagocytosis and killing.</li><br />
<li> We measured the effect of a range of pH (from 3 to 8,8) on <i>M. smegmatis</i> and the TDMH enzyme activity.</li><br />
</ul><br />
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<div class="biocriks"><br />
<h2>BioBricks</h2><br />
<ol><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137008" target="_blank">BBa_K1137008 (TDMH)</a></li><br />
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<div class="aims"><br />
<h2>Aim</h2><br />
<p>To create an <i>E. coli</i> strain capable of entering the macrophage cytosol and delivering a lytic enzyme to kill mycobacteria.</p><br />
</div><br />
<a href="#Introduction"><br />
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<h2>Skip to Introduction</h2><br />
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<a href="#Design"><br />
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<h2>Skip to Design</h2><br />
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<a href="#Killing"><br />
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<h2>Skip to Killing Assay</h2><br />
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<a href="#Macrophages"> <br />
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<h2>Skip to Drug Delivery</h2><br />
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<div id="Introduction"></div><br />
<h2>Introduction</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
<i>Mycobacterium tuberculosis</i> (Mtb), the bacterium responsible for tuberculosis (TB), spreads by aerosol and infects its host through the airways. The bacterium is phagocytosed by macrophages in the lung, yet often evades death in the lysosome. Mtb can persist for years or even decades inside macrophages by inhibiting phagosome/lysosome fusion and supressing the normal acidification of the lysosome.</p><br />
<p>An efficient treatment for persistent TB must enter infected macrophages and kill the pathogen there. In our system, <i>E. coli</i> is both the vector and the therapeutic agent agent by expressing the listeriolyin O gene LLO to enter macrophages and TDMH to kill mycobacteria.<br />
</p><br />
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<div class="rightparagraph"><br />
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<h4>&nbsp;BOX 1: Why is it difficult to treat tuberculosis?</h4><br />
<ul style="width:90%"><br />
<li>Mtb can survive and replicate for years inside the macrophages by supressing the normal process of phagocytosis.</li><br />
<li>The cell wall of <i>M. tuberculosis</i> is thick, waxy and rich in mycolic acids. It it difficult to penetrate with a small-molecule drug.</li><br />
<li>The pathogen grows very slowly inside macrophages. Most conventional antibiotics target processes like DNA replication that are specific to growing cells.</li><br />
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<div id="Design"></div><br />
<h2>TDMH and the mycobacterial cell wall</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;Mycobacterium species share a characteristic cell wall: thick, waxy, hydrophobic, and rich in mycolic acids. The low permeability of the envelope to hydrophilic solutes contributes to the intrinsic drug tolerance in mycobacteria.</p><br />
<p><br />
&nbsp;&nbsp;Trehalose Dimycolate Hydrolase (TDMH) is a cutinase-like serine esterase that triggers rapid lysis of the mycobacterial cell wall by degrading the mycolate layer. The enzyme was first isolated from <i>Mycobacterium smegmatis</i> and subsequently shown to hydrolyze purified TDM from various mycobacterial species. Exposure to TDMH triggers an immediate release of free mycolic acids, ultimately leading to lysis of many mycobacteria including Mtb (Yang et al. 2012).<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;We have used <i>M. smegmatis</i> as a model system because Mtb are highly pathogenic and difficult to culture in the lab. <i>M. smegmatis</i> is a close relative of Mtb, shares many of its membrane properties, and is commonly used as a stand-in for Mtb physiology in the lab.</p><br />
<p>&nbsp;&nbsp;In our system, described in the methods below, we used <i>E. coli</i> BL21 (DE3) as a chassis to express TDMH from an IPTG-inducible strong T7 promoter.</p><br />
</div><br />
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<br />
<div id="Killing"></div><br />
<h2>Killing mycobacteria with TDMH</h2><br />
<div class="leftparagraph"><br />
<p><br />
&nbsp;&nbsp;Figure 1 describes how we performed the setup of our experience by making a coculture of <i>M.smegmatis</i> and <i>E.coli</i>.</p><br />
<p>Figure 2(below) shows the killing of <i>M. smegmatis</i> with TDMH expressed by <i>E. coli</i>. We mixed liquid cultures of <i>E. coli</i> and <i>M. smegmatis</i> at equal cell densities as determined by plating assays. When expression of TMDH was induced with IPTG, nearly 99% of the <i>M. smegmatis</i> were killed within six hours. We saw no change in viability in cultures of <i>M. smegmatis</i> alone or when mixed with uninduced <i>E. coli</i>.</p><br />
<p><br />
&nbsp;&nbsp;We next sought to quantify the effectiveness of TDMH killing. We mixed induced<i> E. coli</i> and mycobacteria in different ratios and used plating assays to measure viability. As shown in figure 3 mycobacterial killing displayed dose dependence on the <i>E. coli</i> cell density. Small numbers of <i>E. coli</i> could kill many mycobacteria. For example, in mixed populations with 100 mycobactera for each <i>E. coli</i>, we still observed >50% mycobacterial killing after 2 hours. This indicates that, on average, each <i>E. coli</i> produced enough TDMH to kill 50 mycobacteria. We reason that this killing may be even more effective inside macrophages, where constrained volumes will increase the effective TDMH concentration.</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><a href="https://static.igem.org/mediawiki/2013/d/d9/PB_FigIva.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/d/d9/PB_FigIva.png" width="70%" style="margin-top:-50px"/></a></center><br />
<p><b>Figure 1</b> Experimental setup of the <i>M. smegmatis</i> killing assay.<div style="font-size:90%"> <i>M. smegmatis</i> and <i>E.coli</i> cells (Uninduced and induced with various concentrations of IPTG) were cultured up to OD 1,then serially diluted. Equal volumes of <i>E.coli</i> and <i>M. smegmatis</i> cultures of the same dilutions were mixed, incubated for 6 hours, and plated at 0,3 and 6 hours. </div></p><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<a href="https://static.igem.org/mediawiki/2013/a/a7/PB_Fig1_Myco_Kill_Curve.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/a/a7/PB_Fig1_Myco_Kill_Curve.png" width="100%"/></a><br />
<p><b>Figure 2</b> TDMH-expressing <i>E.coli</i> kill mycobacteria in culture.<div style="font-size:90%"> We mixed TDMH-expressing <i>E.coli</i> and WT <i>M. smegmatis</i> in LB media at an initial cell density of 107 cells/ml each. Plating assays were used to count specifically <i>M. smegmatis</i> after the indicated times. When TDMH-expression was fully induced with 1 mM IPTG, more than 98% of mycobacteria were killed after 6 hours (red line). Populations of mycobacteria alone (black line) and mycobacteria mixed with uninduced <i>E.coli</i> (blue line) were stable.</div></p><br />
</div><br />
<div class="rightparagraph"><br />
<center><a href="https://static.igem.org/mediawiki/2013/e/e0/PB_Fig2_Coli_Kill_Ratios.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/e/e0/PB_Fig2_Coli_Kill_Ratios.png" width="100%"/></a></center><br />
<p><b>Figure 3</b> Dose-dependence in killing of mycobacteria by <i>E. coli.</i><div style="font-size:90%">We mixed <i>M. smegmatis</i> at a density of 10<sup>7</sup> cells/ml with <i>E. coli</i> at densities of 10<sup>5</sup> cells/ml (blue line) 10<sup>6</sup> cells/ml (green line) or 10<sup>7</sup> cells/ml to produce the ratios above. Even low densities of <i>E. coli</i> produced significant killing. Uninduced <i>E. coli</i> produced no significant killing.</div></p><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<h2></h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;We investigated further the mechanism of TDMH-mediated cell killing. The TDMH enzyme in our system does not carry a secretion tag. Therefore, lysis of the <i>E. coli</i> membrane is probably required for the protein to reach (and lyse) <i>M. smegmatis</i>. We used plating assays to investigate the effect of TDMH induction on <i>E. coli</i> viability and Bradford assays to measure released protein. The results are presented in figure 4.</p><br />
<p>Figure 4A shows that inducing TDMH-expressing <i>E. coli</i> with IPTG rapidly kills the <i>E. coli.</i> In figure 4B, we show that inducing TDMH expression increases the concentration of free protein in the media. In our model, TDMH induction leads to spontaneous lysis of TDMH-expressing <i>E. coli</i>. This could be simply due to the extremely high protein expression levels driven by the T7 promoter, or it may be partially due to the esterase activities of the TDMH enzyme. Once the TDMH is released from the <i>E. coli</i> it is free to act on mycobacterial membranes, causing lysis and the release of additional proteins.<br />
</p><br />
</br><br />
<p><b>Figure 4</b> Induction of TDMH kills <i>E. coli</i> and releases protein to the media.<div style="font-size:90%"><b>A)</b>Plating assays were used to determine <i>E. coli</i> viability in LB media after the indicated times. TDMH-induced <i>E. coli</i> rapidly lost viability (red line) Uninduced <i>E. coli</i> grew normally following a lag phase (black line).<b>B)</b>Bradford assays were used to measure free protein concentrations in mixed and induced bacterial cultures. When <i>E. coli</i> and mycobacteria are mixed and TDMH-expression is induced, free protein concentrations increase. This is consistent with a model in which TDMH induction leads to the lysis of the <i>E. coli</i> membrane. Action of TDMH on mycobacteria leads to further lysis and protein release.</div></p><br />
</div><br />
<div class="rightparagraph"><br />
</br></br></br></br></br><br />
<center><a href="https://static.igem.org/mediawiki/2013/7/74/PB_Fig3_Coli_Protein_Curve.png" target="_blank"><img width="100%" src="https://static.igem.org/mediawiki/2013/7/74/PB_Fig3_Coli_Protein_Curve.png"/></a></center> <br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<div id="Macrophages"></div><br />
<h2>Programmed drug delivery with LLO</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<i>Listeria monocytogenes</i> is a bacterial pathogen that replicates in the cytosol of mammalian cells. The pathogen is initially internalized in host phagosomes, then lyses them to obtain access to the cytosol. A single gene, LLO, is responsible for this activity and is sufficient to convey the phenotype to <i>E. coli</i>.<br />
</p><br />
<p>The LLO protein is activated by the low pH of the lysosme. By forming large pores in the lysosomal membrane, it allows protein delivery to the cytosol of macrophages (Higgins et al. 1999). Using <i>E. coli</i> as a protein vector means we don't need to isolate and purify the TDMH enzyme. </p><br />
<p>We hypothesized that a bacterial delivery system could be efficient and specific in targeting mycobacterial-infected macrophages. In effect, we might take advantage of the natural tendency of macrophages to phagocytose <i>E. coli</i> and their enzymatic payload.</p><br />
<p>Because LLO expression is known to be associated with Listeria pathogenicity, we took extra precautions in our cloning and experiments. These measures are detailed on our team safety page. Briefly, we worked in a Biosafety Level 2 lab under the supervision of two full-time lab managers. We researched and complied with French national and insitutional biosafety rules as they apply to this gene.</p><br />
</div><br />
<div class="rightparagraph"><br />
<center><img src="https://static.igem.org/mediawiki/2013/b/b7/PB_Killing_assay_macrophages1.png" width="80%"/></center><br />
<p><b>Figure 5</b> Experimental design of the killing assay inside the macrophages. We infected them with <i>M. smegmatis</i> and washed after 1 hour. Then, we infected them with <i>E. coli</i> and washed after 1 hour. The end of this final infection step refers to the time 0 on our graphs. At this time we started the observation under the microscope</p><br />
</div><br />
<div style="clear: both;"></div><br />
<br />
<h2><i>E. coli</i> and <i>M. smegmatis</i> coinfections</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;Figure 6 displays J774 macrophages one hour after coinfection with <i>E. coli</i> and <i>M. smegmatis</i>. As described in the methods, the <i>E. coli</i> express TDMH and LLO and fluorescent mRFP as a label. The <i>M. smegmatis</i> express GFP as a label, but are otherwise wild type.</p><br />
<p>The two movies displayed in figure 7 are time-lapse microscopy of live coinfected macrophages collected over a period of 6 hours. Fluorescence patterns revealing the localization of <i>E. coli</i> and <i>M. smegmatis</i> within the macrophages are relatively stable over this time period.</p><br />
</div><br />
<div class="rightparagraph"><br />
<p> We next applied quantitative microscopy to characterize the behavior of our system inside live macrophages. We imaged macrophage populations under several conditions and time points and scored their rates of infection with <i>E. coli</i>, <i>M. smegmatis</i> or both. In all we scored over 13,000 individual cells collected from more than 100 separate images.</p><br />
</div><br />
<div style="clear: both;"></div><br />
<div class="leftparagraph"><br />
<center><a href="https://static.igem.org/mediawiki/2013/5/52/PB_Fig4_Fresh_coinfection.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/5/52/PB_Fig4_Fresh_coinfection.png" width="100%"/></a></center><br />
</br><br />
<a href="https://static.igem.org/mediawiki/2013/5/51/PB_Fig4_Fresh_coinfection_zoom1.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/5/51/PB_Fig4_Fresh_coinfection_zoom1.png" width="48%"/></a><br />
<a href="https://static.igem.org/mediawiki/2013/c/c1/PB_Fig4_Fresh_coinfection_zoom2.png" target="_blank"><img src="https://static.igem.org/mediawiki/2013/c/c1/PB_Fig4_Fresh_coinfection_zoom2.png" width="48%" style="margin-left:3%"/></a><br />
<br />
<p><b>Figure 6</b> Coinfection of J774 macrophages with mycobacteria and <i>E. coli</i> expressing TDMH and LLO<div style="font-size:90%"> <i>E. coli</i> (red) express mRFP as a marker and <i>M. smegmatis</i> (green) express GFP as a marker. Macrophages are observed to take up Mycobateria, <i>E. coli</i>, neither or both. This image was collected one hour after introducing the bacteria to the macrophage culture and following extensive washing to remove free bacteria.</div></p><br />
</div><br />
<div class="rightparagraph"><br />
<iframe frameborder="0" style="margin-bottom:20px;" width="535" height="300" src="http://www.dailymotion.com/embed/video/x15jnu6"></iframe><br />
<iframe frameborder="0" width="535" height="300" src="http://www.dailymotion.com/embed/video/x15jnv8"></iframe><br />
<p><b>Figure 7</b> Temporal dynamics of macrophages coinfected with <i>E. coli</i> and <i>M. smegmatis.</i><div style="font-size:90%"><i>E. coli</i> and <i>M. smegmatis</i>, expressing mRFP and GFP respectively, were introduced to J774 macrophages. Fluorescent and bright field images were collected every 15 minutes for 6 hours. In these movies, the <i>E. coli</i> also express TDMH and LLO. Macrophages are observed to uptake <i>E. coli</i>, <i>M. smegmatis</i>, neither or both. The fluorescence patterns appear stable for these conditions and time period.</div></p><br />
<br />
</div><br />
<br />
<br />
<h2>pH influence </h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;We wanted to study the pH influence on <i>M. smegmatis</i> growth and on TDMH enzyme activity. We know that the phagosomal pH is usually acid (around 6) but can reach 4,5. We wondered if TDMH enzyme was working at this range of pH.</p><br />
<p>We studied 7 different buffers : 3 ; 4,5 ; 5,1 ; 6,4 ; 7,35 ; 8,2 and 8,8. </p><br />
<p> The Figure shows that at pH 3, <i>M. smegmatis</i> is not growing. Since it is an OD, we can't say if the bacteria is alive or dead. However, the OD is not growing which suggest that the bacteria is probably killed by TDMH.</p><br />
<br />
<br />
</div><br />
<div class="rightparagraph"><br />
<br />
<center> <img src="https://static.igem.org/mediawiki/2013/e/e4/PB_TBC_PH_indepedence.png" width="80%"/></center> <p><b>Figure 8</b> pH influence on TDMH enzyme activity <div style="font-size:90%"> We add to <i>M.smegmatis</i> the proteins of an induced control, the uninduced strain of Bl21 and the induced strain producing TDMH.</div></p><br />
</div><br />
<br />
<br />
<div style="clear: both;"></div><br />
<br />
<h2>Conclusions and continuing work</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;We have shown that <i>E. coli</i> can effectively kill mycobacteria in culture by expressing the TDMH enzyme, now a BioBrick. We have further shown that <i>E. coli</i> and mycobateria may co-localize within macrophages, where LLO-based systems can effectively deliver protein payloads.</p><br />
<p>In the coming weeks, we will continue to refine our cell culture techniques to precisely characterize the effectiveness of our system <i>in situ</i>, within the living macrophage.</p><br />
<p><b>Figure 9</b> The effect of TDMH-induced <i>E. coli</i> on macrophage infection rates after 3 hours.<div style="font-size:90%">We scored fluorescence microscopy images of macrophages exposed to both <i>E. coli</i> and <i>M. smegmatis</i> expressing fluorescent protein markers. The <i>E. coli</i> expressed LLO and were induced or uninduced for TDMH expression. For both treatments, we observed an increase in the infection rates of both bacteria after 3 hours. We attribute this to combination of the media with free bacteria, which macrophages continue to consume over the course of the experiment. TDMH induction slowed the increase in <i>E. coli</i> infection rates, which is likely due to the toxic effects of TDMH expression on <i>E. coli</i>, as shown in figure 4.</div></p><br />
</div><br />
<div class="rightparagraph"><br />
<center><img src="https://static.igem.org/mediawiki/2013/1/15/PB_Fig6_Image_Counts.png" width="80%"/></center><br />
</div><br />
<div style="clear: both;"><br />
<br />
<h2>Bibliography</h2><br />
<ul><br />
<li>Yang Y, Bhatti A, Ke D, Gonzalez-Juarrero M, Lenaerts A, Kremer L, Guerardel Y, Zhang P, Ojha AK (2012) : Exposure to a cutinase-like serine esterase triggers rapid lysis of multiple mycobacterial species. J Biol Chem. 2013 Jan 4;288(1):382-92.</li><br />
<li>Rajesh Jayachandran, Varadharajan Sundaramurthy, Benoit Combaluzier , Philipp Mueller, Hannelie Korf, Kris Huygen, Toru Miyazaki, Imke Albrecht, Jan Massner, Jean Pieters (2007) : Survival of Mycobacteria in Macrophages Is Mediated by Coronin 1-Dependent Activation of Calcineurin. Cell, Volume 130, Issue 1, 13 July 2007, Pages 12-14 </li><br />
</ul><br />
<br />
</div><br />
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<br />
<h2>Attributions</h2> <br />
<br />
<p>pET21 1519 plasmid was kindly provided by Anil Ojha of the University of Pittsburgh.</p><br />
<p> Murine cell line macrophages J774 were a gift from Nicole Guiso and Nicolas Hegerle from Pasteur institute (Unit of Molecular Prevention and Therapy of Human Diseases. </p><br />
<p> <i>Mycobacterium smegmatis</i> was a gift from Brigitte Gicquel from Pasteur institute (Unit Mycobacterial genetics). </p><br />
<p> <i>Mycobacterium smegmatis</i> expressing GFP was kindly provided by Stephane Canaan from CNRS (Laboratory of Enzymology at Interfaces and Physiology of Lipolysis). </p><br />
<p>The project itself was designed and accomplished by Camélia Bencherif and Iva Atanaskovic with consultation with Edwin Wintermute, Mathias Toulouze and Ariel Lindner.</p><br />
<p> We also discussed the project with Christopher Anderson from Berkeley University (Synthetic biology Anderson lab) about the feasibility, good points and critical points of the project. </p><br />
<p> We want to thank all these people that made Infiltrate project happen !</p><br />
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<div class="overbox"><br />
<div class="bkgr"><br />
<h2>Background</h2><br />
<p>CRISPR/Cas systems generate site-specific double-strand breaks and have recently been used for genome editing. </p><br />
</div><br />
<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>Successfully cloned gRNA anti-KAN, crRNA anti-KAN, tracrRNA-Cas9 and pRecA-LacZ into Biobrick backbones and therefore generated four new BioBricks. </li><br />
<li> Confirmation of site-specific binding and DNA double-strand breaks generated by the gRNA-Cas9 complex in the kanamycin resistance casette. </li><br />
<li><a href="https://2013.igem.org/Team:Paris_Bettencourt/Assembly_Standard">Testing the new assembly standard for our cloning.</a></li><br />
</ul><br />
<p></p><br />
</div><br />
<div class="biocriks"><br />
<h2>BioBricks</h2><br />
<ol><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137012">BBa_K1137012</br>(gRNA anti-KAN)</a></li><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137013">BBa_K1137013</br>(crRNA anti-KAN)</a></li> <br />
<li><a href="http://parts.igem.org/Part:BBa_K1137014">BBa_K1137014</br>(tracrRNA-Cas9)</a></li><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137015">BBa_K1137015</br>(pRecA-LacZ)</a></li><br />
</ol><br />
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<div class="aims"><br />
<h2>Aims</h2><br />
<p>Building a genotype sensor based on CRISPR/Cas that reports on the existence of an antibiotic resistance gene.</p><br />
</div><br />
<a href="#Aim"><br />
<div class="hlink"><br />
<h2>Skip to Aim</h2><br />
</div><br />
</a><br />
<a href="#Design"><br />
<div class="hlink"><br />
<h2>Skip to Design</h2><br />
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</a><br />
<a href="#Background"><br />
<div class="hlink"><br />
<h2>Skip to Background</h2><br />
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</a><br />
<a href="#Results"> <br />
<div class="hlink" style="margin-right:0px"><br />
<h2>Skip to Results</h2><br />
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<br />
<div id="Aim"></div><br />
<h2>Aim</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
We developed a sensor to detect whether a particular bacterial strain carries a specific antibiotic resistance gene. Our sensor system consists of <i>E.coli </i> lab strain and of a synthetic phagemid with a CRISPR/Cas system and LacZ as a reporter under the control of a pRecA promoter (SOS response promoter). <br /> If our CRISPR/Cas system can bind to the target (antibiotic resistance gene), the Cas9 generates at this specific target site a double strand break, which will induce the expression of our double-strand break SOS sensor (Figure. 1). Having the system on a phagemid, the sensor system will spread all over a population, to get a clear color output if the target has been detected. Depending on target sequence the system carries, we can identify different antibiotic resistances in a strain. This is a novel approach of detecting genes in bacterial strains. We used <i>E.coli</i> and a M13 phagemid to target the kanamycin resistance gene. <br /> This sensor is a proof of concept for a similar system in <i>Mycobacterium tuberculosis</i>. Such a system could potentially be used to test if a patient has TB and what type of resistance genes the specific strain contains to adapt the patient’s drug treatment.<br />
</div><br />
<div class="rightparagraph"><br />
<center> <img width="110%" src="https://static.igem.org/mediawiki/2013/2/2d/PB_13_TB_Sensor_Detect_Overview.png"/><br></center><br />
<p><b>Figure 1:</b> Detection and reporting of an antibiotic resistance gene with a CRISPR/Cas system. <div style="font-size:90%">After expression of the Cas9 and gRNA, the gRNA guides the Cas9 to the target sequence, the kanamycin resistance. There, the Cas9 generates a double strand break. This activates the SOS response. The reporter LacZ is under the pRECA promoter, which gets activated during the SOS response and we get a blue cell, if the resistance gene has successfully been detected. </div></p><br />
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<br />
<div id="Motivation"></div><br />
<h2>Motivation and existing TB sensors/tests</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Tuberculosis (TB) remains a major global health problem. While the treatment of this disease in countries with adequate medical care is fairly easy to detect and treat, it remains hard to treat and diagnose in poorer countries. <br><br />
Up to now, a high quality lab that uses modern diagnostics is a prerequisite for early, rapid and accurate detection of TB. Therefore, diagnosis of TB and drug resistant TB remains a particular challenge for laboratory systems, especially in developing countries.<br><br />
The lack of cheap, quick and accurate tests make it hard to control the Tuberculosis epidemic, which claims millions of lives every year in developing countries.<br><br />
Setting up a cheap, fast and culture-based method could therefore decrease diagnostic time and facilitate patient treatment.<br><br />
The most common method for diagnosing TB nowadays is sputum smear microscopy, in which bacteria are observed in sputum samples of patients under the microscope. However, this cannot be used to identify paucibacillary (containing just a few bacteria) or extrapulmonary (outside of the lungs) TB.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
Diagnosis methods using culture methods require laboratory infrastructure that is not widely available in countries with a high burden of TB and results are only available after a few weeks.<br />
Other conventional methods used to diagnose multidrug-resistant TB (MDR-TB) also rely on the culturing of specimens followed by drug susceptibility testing (DST). Results take weeks to obtain and not all laboratories have the capacity to perform DST of first-line or of second-line drugs.<br><br />
MTB/RIF is a new rapid molecular test that can diagnose TB and rifampicin-resistant TB within hours. Molecular tests, such as GeneXpert, unlike culture-based methods, are fast, accurate and can detect drug-resistant strains. But the high costs and need for laboratories make access an issue for developing countries.<br><br />
The new method, published in the Journal of Applied Microbiology, uses a microcalorimeter to detect heat produced by Mycobacterium tuberculosis, the bacterium that causes TB, on a growth medium. The study showed that detection takes 4–5 days but more sensitive microcalorimeters could detect tuberculosis in 24 hours.<br />
</p><br />
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<br />
<div id="Design"></div><br />
<h2>System Design</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
By taking advantage of the state of the art CRISPR/Cas research and combining it with phage diagnostics, we designed a sensor that is able to screen for a specific target gene. Our producer strain carries a helper plasmid that codes for the phage capsid proteins of M13 as well as our phagemid plasmid with our sensor system. Our sensor system consists out of three parts: the Cas9 gene under a constitutive promoter, the anti-KAN gRNA also under a constitutive promoter and the reporter element LacZ under the control of the pRecA promoter. As the helper plasmid doesn’t have a packaging sequence, only our sensor system phagemid is packed into the M13 capsids. As M13 is a lysogenic phage, the phagemid particles are exported into the media where they can be easily isolated and are ready to use to sense if an other strain contains our target sequence. <br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
As the phagemid is derived from M13, it infects only F+ (conjugated) cells. In our case, we conjugated our cells so that they can be easily infected. <p> Within the target strain, the Cas9 protein, as well as the gRNA get expressed. The gRNA then attaches to the Cas9 protein and guides the Cas9 to the target sequence (kanamycin resistance gene). Once bound to the sequence, the Cas9 protein generates a target specific double strand break. This double strand break leads to the cleavage of LexA. LexA is a protein bound to the pREC promoter that inhibits the expression of genes under the control of the pREC promoter. With the cleavage of LexA, the expression of our reporter LacZ is started, which leads in the presence of X-gal to a blue color output. <br />
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</p><br />
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<center><img src="https://static.igem.org/mediawiki/2013/1/15/PB_Detect_Design_GIF-loop.gif" width="80%"/></center><br />
<div style="margin-left:10%"><p><b>Figure 2:Course of the detection and reporting of an antibiotic resistance gene with the CRISPR/Cas system. </b> <div style="font-size:90%">After the plasmid has been released into the target cells, gRNA and Cas9 get expressed. The gRNA guides the Cas9 to the target, where it generates a double strand break. This activates the SOS response. As a results, LexA is cleaved which allows the expression of the reporter. In the presence of X-gal the cells turn blue. </div></p></div><br />
<br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Our system is highly modular as with the simple change of the gRNA target sequence (20bp), any gene of interest can be identified and targeted. This means that our system can be used for different applications and purposes, as for example a mutation screening. It is also not specified only for <i>E.coli</i> and the phage M13. Our whole system can be easily transferred to other phage systems that target other host bacteria. In our case, as we want to develop a sensor to test <i>Mycobacterium tuberculosis</i>, we could in principle transfer our system to mycobacteria phages. With what we are presenting here, we have a proof of concept in <i>E.coli</i>. By using host specific phages, we can easy identify specific bacteria and genes they carry. By building a library of phages with different gRNAs we could screen for many different genes in parallel including other resistances or pathogenic genes.<br />
<br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
For future perspectives, we plan to further test and improve the system so that in theory, we will generate a sensor that can be used without using high-tech laboratory facilities. This is very important, as easily to use sensors are needed in the developing countries in which tuberculosis is still a prevalent disease.<p><br />
In a prospective design study we imagine the development of a handkerchief, in which our phagemid system can be integrated. By spitting on the tissue, we get a bacterial sample that will be tested by phages. Depending on which phagemid is integrated into the handkerchief, we can test for the <i>Mycobacterium tuberculosis</i> in general as well as for the different antibiotic resistances. A handkerchief is easy to use and the blue color output easy to read out. As phages are acting very fast, an easily usable and fast sensor system is developed.<br />
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<br><br />
<img src="https://static.igem.org/mediawiki/2013/2/25/PB_designscenario.png" width="1100"/><br />
<p><b>Figure 3 </b> <div style="font-size:90%">your text here </div></p><br />
<br><br />
<div id="Background"></div><br />
<h2>Background</h2><br />
<h3>CRISPRs</h3><br />
<div class="leftparagraph"> <br />
<p>&nbsp;&nbsp;<br />
The mechanism we are using for our sensor is based on the CRISPR/Cas System. The CRISPR/Cas genome editing method, which recently became very popular, is derived from the bacterial “immune system”. CRISPRs are Clustered Regularly Interspaced Short Palindromic Repeats that are part of the bacterial genome. These loci contain multiple short repeats. In between the repeats are so called spacers that are sequences derived from extrachromosomal DNA, e.g. from invading viruses or plasmids (Figure 3). Within bacteria, those CRISPRs are naturally used to detect and destroy foreign DNA that is saved in the spacers.</p><br />
<p>In total the CRISPRs and the spacers form a so-called CRISPR array that is transcribed as one unit. CRISPR associated proteins (Cas proteins) are involved in further processing and action steps of the CRISPR system. There are many different regulation systems, here we describe the Cas9 system that will be used for our purposes (Figure 3).</p><br />
<p>The transcribed mRNA is processed into so called crRNA (CRISPR RNA), which includes the spacer sequence of foreign DNA. Together with a transactingCRISPR RNA (tracrRNA), the crRNA forms a duplex that is cleaved by RNaseII. The resulting hybrid serves as guide for the Cas9 protein that generates double strand breaks at the position the RNAs guide it to (Figure 3). By this double strand break the invading DNA is destroyed. The last years, researchers discovered the CRISPRs as a method for genome editing. </p><br />
<br><br><br><br><br><br />
<img src="https://static.igem.org/mediawiki/2013/4/43/PB_gRNA_%282%29.png" width="520"/><br />
<p><b>Figure 3:</b> CRISPR/Cas technology description (<a href="http://www.addgene.org/CRISPR/guide/" target="_blank">Addgene.org</a>).</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; By designing the spacer sequence, specific sequences in the genome can be targeted. With the provision of a sequence with homologous sequences, easy insertion can be done. This method can be used to insert mutations or new sequences nearly everywhere in the genome.<br><br />
Recently many papers have been published for genome editing in bacteria (Jinek et al., 2012, <a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Jiang2013" target="_blank">Jiang <i>et al</i>. 2013</a>), yeast (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#DiCarlo2013" target="_blank">DiCarlo <i>et al</i>. 2013</a>) and mammalian cells (Mali et al., 2013, Cong et al., 2013). They describe how to use the CRISPRs for different purposes. One requirement to target a sequence is a NGG at the end of the sequence. This NGG sequence is called PAM - protospacer adjacent motif, while the target sequence itself is called the protospacer, which should have a length of around 12 to 20 bp.</p><br />
<p>In our approach we test two different systems, the systems of DiCarlo et al. 2013 and Jiang et al. 2013. The system of Jiang is a system developed for bacteria and especially for <i>E.coli</i>. The system of DiCarlo is based on a paper of Mali et al. 2013 and adapted to yeast.</p><br />
<p>Different from the Jiang paper, the DiCarlo paper uses a gRNA (guideRNA) to guide the Cas9 (Figure 4). The gRNA is actually the RNA that results after transcribing and folding is the same complex as you get after the processing of the tracrRNA with the crRNA. It is hence an improvement, which makes the design and expression easier. But as the system hasn’t been tested before in bacteria, we will use both systems to make sure we get the desired results.</p><br />
<br><br />
<br><br />
<br><br />
<center><img src="https://static.igem.org/mediawiki/2013/6/64/PB_gRNA_%281%29.png" width="430"/></center><br />
<p><b>Figure 4:</b>Cas9 protein interacting with CRISPR gRNA<div style="font-size:90%">Illustration of Cas9 protein interacting with CRISPR gRNA to direct endonuclease activity proximal to the PAM sequence (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#DiCarlo2013" target="_blank">DiCarlo et al. 2013</a>) </div></p><br />
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<br />
<h3>RecA promoter</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Our reporter system consists out of the RecA promoter and LacZ. Originally, the RecA promoter of <i>E.coli</i> has its main role in the activation of the SOS repair system. It is regulated by the LexA repressor, which binds to the SOS box sequence of the promoter. DNA damage leads to an inducing signal, which then activates the RecA protein. In the SOS response the LexA repressor is cleaved by the RecA protein, so the full RecA expression can be reached. The RecA protein can then repair both single stranded and double stranded DNA breaks.</p><br />
<p>In our project RecA promoters used to detect double stranded DNA breaks in the region of antibiotic resistance genes caused by the CIRSPR/Cas system. To get the desired activation of the promoter, it is important to assure that no other stressing agents might activate the RecA promoter. Those agents could be UV light, X-ray, ionizing radiation and different types of DNA breaking compounds. </p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
The SOS response in <i>E.coli</i> could also get induced by engineered M13 phage infection that are defective in the minus-strand origin, and so unable to form the double stranded replicative stage.</p><br />
<p>In this case the single-stranded DNA would be the SOS-inducing signal. The wild type M13 phage doesn’t induce the SOS response (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Higashitani1992" target="_blank">Higashitani <i>et al</i>. 1992</a>). In another study genomes of phage M13 infected and uninfected <i>E.coli</i> strains were compared by oligonucleotide microarrays, where no stress response genes were scored as upregulated (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Karlsson2005" target="_blank">Karlsson <i>et al</i>. 2005</a>). Regarding the phagemids, an A UV-damaged oriC phagemid did not induce SOS response in a recipient cells oriF phagemids on the other hand did (Sommer et al. 1991). To make sure that our system functions reliably, we will test the activation of the RecA promoter at different stress inputs (UV, phage infection,…) by measuring the fluorescence of YFP driven by the RecA promoter.</p><br />
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<br />
<div id="Results"></div><br />
<h2>Progress and preliminary Results</h2><br />
<h3>Parts</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp; Up to this point we cloned each of our parts into BioBrick vectors. We cloned the <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Monday_30th_September.html">gRNA anti-Kan </a> into pSB1C3 and pSB1A3.We used for this the assembly standard BioBrick cloning as well the new proposed <a href="https://2013.igem.org/Team:Paris_Bettencourt/Assembly_Standard">Assembly Standard.</a>. Both assemblies were successful and proved by colony PCR as well as by sequencing. We also used both standards for cloning the <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Monday_30th_September.html">crRNA.</a>. <br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
Also this is verified by colony PCR and by sequencing. For the cloning of the tracrRNA-CAS9 part we used standard BioBrick cloning, inserted into pSB1A3 and sequence verified it. We achieved the same for the pRecA-LacZ part (pSB1C3 and pSB1A3 backbones) that was submitted to the parts registry. <br><br />
</div><br />
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<br><br />
<h3>Killing assay to verify targeting specificity</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp; For the characterization of the Cas9 and the gRNA anti-KAN we performed a <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Thursday_3rd_October.html">killing assay </a> . Therefore we co-transformed the Cas9 with gRNA anti-KAN into host bacteria that contain the KAN resistance gene cassette as well as without the cassette. In the KAN resistance bacteria, the CRISPR/Cas complex generated generate double strand breaks that killed the bacteria. After co-transforming the plasmids, we plated the bacteria on the one hand on the single antibiotic where the resistance is carried by the Cas9 plasmid as well as on the single antibiotic which resistance is present on the gRNA plasmid. As the two plasmids contain the same origin of replication, this will selesct for only the single plasmid and hence a non-functional CRISPR/Cas system. To get a working system, we plated the co-transformed bacteria on both antibiotics, of which the reistances were on the two plasmids. As we can see in Figure 5, if we select for both plasmids, we get a reduced number of colonies in the strain that contains the target sequence, the kanamycine resistance cassette. We attribute this reduced number to Cas9-induced cleavage of the chromosome specifically at the KanR casette, with about 99% efficiency. This leads after repeatedly double strand breaks generated by the CRISPR/Cas system to cell death which explaines the reduced colony number.<br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
<img src="https://static.igem.org/mediawiki/2013/0/01/PB_13_Results_detect_killing_assay.png" width="80%" style="margin-bottom:-80px;"/> <br />
<br><br />
<br><br />
<p><b>Figure 5: </b> CRISPR anti-Kan plasmids target specifically kanamycin resistant <i>E. coli</i>.<div style="font-size:90%"> We introduced our CRISPR-based DNA cleavage system to two strains of <i>E. coli</i>: one WT (blue bars) and one carrying a genomically integrated kanamycin resistance casette (KanR, blue bars). The strains were co-transformed with two plasmids. One with the Cas9 construct, the other with the anti-Kanamycin gRNA. WT <i>E. coli</i> could be efficiently transformed with one or both plasmids, as determined by selective plating. However, KanR <i>E. coli</i> could not be efficiently transformed with both. We attribute this to Cas9-induced cleavage of the chromosome specifically at the KanR casette, with about 99% efficiency.</div></p><br />
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<br />
<br><br />
<h3>Characterization of the reporter - under construction</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;To characterize the pRecA –LacZ construct, we induced double strand breaks with Mytomycin C (MMC) and analyzed the resulting LacZ expression levels with the Miller assay. The same time, we wanted to characterize our final system: our target strain with the kanamycin resistance gene that also carries the reporter and the Cas9. The gRNA is delivered by a phage. As positive control, we used MG1655, which has a constitutive expression of LacZ, as negative control the parental strain of the target strain, which doesn’t have a kanamycin resistance cassette but also has the reporter and Cas9.<br />
As it can be seen in Figure 6, we didn’t get any expression of LacZ beside in the positive control, the MG1655 strain. As we worry, that our reporter might be not functional, we started to characterize a reporter constructed by Ariel Lindner. This reporter is YFP under the control of pREC. We analyzed its expression rates by inducing double strand breaks with Mitomycin C and Niprofloxacin. The data generated by FACS analysis over time can be seen in Figure 7. We can clearly see an induction of the pREC promoter due to induction with MMC and Niprofloxacin. Due to time constraints, we were not able to successfully adapt our system to use this pREC-YFP reporter in our target strain. In previous iGEM years, there has already been a pREC-LacZ Biobricked constructed (Heidelberg 2012). In principle, our system couldbe completed, as a functional pREC-LacZ already exists. By adding the reporter of Heidelberg 2012 to our target strain with the Cas9, we should be able to get a functional sensor. This sensor can detect and report a specific DNA sequence due to a phagemid delivered gRNA that guides the present Cas9 to a target where the Cas9 generates a double strand break, which is reported by pREC-LacZ.<br />
</div></p><br />
</div><br />
<div style="clear: both;"></div><br />
<br><br />
<h3>Next steps</h3><br />
<div class="left paragraph"><br />
As previously mentioned, the reporter didn’t work as expected. This can have several reasons. As our other positive control (beside MG1655), the MMC induced strains carrying the reporter didn’t show any expression, it stands to reason that the reporter itself is not functional. Another reason could be, that the phagemid didn’t deliver the gRNA or not in enough amounts to show an effect of the complete working system.<br />
</div></p><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
To test, if the phagemid delivers the gRNA correctly, we will perform another killing assay as we have done it before with the difference that the gRNA is delivered by the phagemid. The strains are then plated to see, if there is a reduced number of colonies of the target strain with phagemid in comparison to a control strain and without added phages. We expect the results before the end of iGEM.<br />
</div><br />
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<br />
<h2>Literature</h2><br />
<div class="leftparagraph"><br />
<ul><br />
<li>James E. DiCarlo, Julie E. Norville, Prashant Mali, Xavier Rios, John Aach and George M. Church (2013).<i> Genome engineering in Saccharomyces cerevisiae using CRISPR-Cas systems.</i> Nucleic Acids Research. 2013, 1–8.</li><br />
<li id="">Antonio R. Fernandez de Henestrosa, Tomoo Ogi, Sayura Aoyagi, David Chafin, Jeffrey J. Hayes, Haruo Ohmori and Roger Woodgate (2000). <i>Identification of additional genes belonging to the LexA regulon in Escherichia coli.</i> Molecular Microbiology .2000 35(6), 1560-1572.</li><br />
<li id="">Higashitani N., Higashitani I.A., Roth A., Horiuchi A.K. (1992). <i>SOS Induction in Escherichia coli by Infection with Mutant Filamentous Phage That Are Defective in Initiation of Complementary-Strand DNA Synthesis.</i> Journal of Bacteriology. 174:1612-1618.</li><br />
<li id="">Wenyan Jiang, David Bikard, David Cox, Feng Zhang & Luciano A Marraffini (2013). <i>RNA-guided editing of bacterial genomes using CRISPR-Cas systems.</i> Nature Biotechnology. 31 (3), 233-2398.</li><br />
<li id="">Douglas H. Juers, Brian W. Matthews, and Reuben E. Huber (2012). <i>LacZ b-galactosidase: Structure and function of an enzyme of historical and molecular biological importance.</i> Protein Science. 2012, 21,1792—1807.</li><br />
<li id="">Karlsson F., Malmborg-Hager A.C., Albrekt A.S., Borrebaeck C.A.K. (2005). <i>Genome-wide comparison of phage M13-infected vs. uninfected Escherichia coli. </i> Can. J. Microbiol. 51:29-35.</li><br />
</ul><br />
</div><br />
<div class="rightparagraph"><br />
<ul><br />
<br />
<li id="">Kimberly L. Keller, Terri L. Overbeck-Carrick, Doris J. Beck (2001). <i>Survival and induction of SOS in Escherichia coli treated with cisplatin, UV irradiation, or mitomycin C are dependent on the function of the RecBC and RecFOR pathways of homologous recombination. </i> Mutation Research. 486, 2001, 21–29.</li><br />
<li id="">Kobayashi, Ichizo; and Handa, Naofumi (2009). <i>DNA Doublestrand Breaks and Their Consequences in Bacteria. </i> Encyclopedia of Life Sciences (ELS). John Wiley & Sons, Ltd: Chichester.</li><br />
<li id=""> Timothy K. Lu, Jayson Bowers, and Michael S. Koeris (2013). <i> Advancing bacteriophage-based microbial diagnostics with synthetic biology. </i>Trends in Biotechnology. April 2013, 31 (6), 325-227.</li><br />
<li id="">Anders Norman, Lars Hestbjerg Hansen, and Søren J. Sørensen (2004). <i>Construction of a ColD cda Promoter-Based SOS-Green Fluorescent Protein Whole-Cell Biosensor with Higher Sensitivity toward Genotoxic Compounds than Constructs Based on recA, umuDC, or sulA Promoters. </i> APPLIED AND ENVIRONMENTAL MICROBIOLOGY. May 2005, p. 2338–2346.</li> <br />
<li id="">Sommer S., Leitao A., Bernardi A., Bailone A., Devoret R. (1991). <i>Introduction of a UV-damaged replicon into a recipient cell is not a sufficient condition to produce an SOS-inducing signal.</i> Mutation Research/DNA Repair. 254:107-17.</li><br />
</ul><br />
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<br />
<h2>Attributions</h2> <br />
<br />
<p> Most of the strains and plasmids used for this project were kindly provided by the INSERM U1001 lab.</p><br />
<p> The Cas9 plasmid as well as the CRISPR plasmid were ordered from Addgene. The crRNA was designed after consultation with David Bikard.</p><br />
<p> The sequence of LacZ used in this project was taken from pBAC-BA-lacZ from Addgene. The corresponding pREC sequence is the natural sequence. The source for the sequence is EcoCyc.</p><br />
<p> The phaegmid template as well as the helper plasmid were provided by Monica Ortiz from the Endy Lab, Stanford.</p><br />
<p> The project itself was designed and accomplished by Nicolas Koutsoubelis, Anne Loechner and Marguerite Benony with consultation with Edwin Wintermute, Stanislas and Ariel Lindner.</p><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Project/DetectTeam:Paris Bettencourt/Project/Detect2013-10-28T23:57:47Z<p>Marguerite: </p>
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<div class="bkgr"><br />
<h2>Background</h2><br />
<p>CRISPR/Cas systems generate site-specific double-strand breaks and have recently been used for genome editing. </p><br />
</div><br />
<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>Successfully cloned gRNA anti-KAN, crRNA anti-KAN, tracrRNA-Cas9 and pRecA-LacZ into Biobrick backbones and therefore generated four new BioBricks. </li><br />
<li> Confirmation of site-specific binding and DNA double-strand breaks generated by the gRNA-Cas9 complex in the kanamycin resistance casette. </li><br />
<li><a href="https://2013.igem.org/Team:Paris_Bettencourt/Assembly_Standard">Testing the new assembly standard for our cloning.</a></li><br />
</ul><br />
<p></p><br />
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<div class="biocriks"><br />
<h2>BioBricks</h2><br />
<ol><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137012">BBa_K1137012</br>(gRNA anti-KAN)</a></li><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137013">BBa_K1137013</br>(crRNA anti-KAN)</a></li> <br />
<li><a href="http://parts.igem.org/Part:BBa_K1137014">BBa_K1137014</br>(tracrRNA-Cas9)</a></li><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137015">BBa_K1137015</br>(pRecA-LacZ)</a></li><br />
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<div class="aims"><br />
<h2>Aims</h2><br />
<p>Building a genotype sensor based on CRISPR/Cas that reports on the existence of an antibiotic resistance gene.</p><br />
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<a href="#Aim"><br />
<div class="hlink"><br />
<h2>Skip to Aim</h2><br />
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</a><br />
<a href="#Design"><br />
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<h2>Skip to Design</h2><br />
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<a href="#Background"><br />
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<h2>Skip to Background</h2><br />
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<a href="#Results"> <br />
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<h2>Skip to Results</h2><br />
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<div id="Aim"></div><br />
<h2>Aim</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
We developed a sensor to detect whether a particular bacterial strain carries a specific antibiotic resistance gene. Our sensor system consists of <i>E.coli </i> lab strain and of a synthetic phagemid with a CRISPR/Cas system and LacZ as a reporter under the control of a pRecA promoter (SOS response promoter). <br /> If our CRISPR/Cas system can bind to the target (antibiotic resistance gene), the Cas9 generates at this specific target site a double strand break, which will induce the expression of our double-strand break SOS sensor (Figure. 1). Having the system on a phagemid, the sensor system will spread all over a population, to get a clear color output if the target has been detected. Depending on target sequence the system carries, we can identify different antibiotic resistances in a strain. This is a novel approach of detecting genes in bacterial strains. We used <i>E.coli</i> and a M13 phagemid to target the kanamycin resistance gene. <br /> This sensor is a proof of concept for a similar system in <i>Mycobacterium tuberculosis</i>. Such a system could potentially be used to test if a patient has TB and what type of resistance genes the specific strain contains to adapt the patient’s drug treatment.<br />
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<div class="rightparagraph"><br />
<center> <img width="110%" src="https://static.igem.org/mediawiki/2013/2/2d/PB_13_TB_Sensor_Detect_Overview.png"/><br></center><br />
<p><b>Figure 1:</b> Detection and reporting of an antibiotic resistance gene with a CRISPR/Cas system. <div style="font-size:90%">After expression of the Cas9 and gRNA, the gRNA guides the Cas9 to the target sequence, the kanamycin resistance. There, the Cas9 generates a double strand break. This activates the SOS response. The reporter LacZ is under the pRECA promoter, which gets activated during the SOS response and we get a blue cell, if the resistance gene has successfully been detected. </div></p><br />
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<div id="Motivation"></div><br />
<h2>Motivation and existing TB sensors/tests</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Tuberculosis (TB) remains a major global health problem. While the treatment of this disease in countries with adequate medical care is fairly easy to detect and treat, it remains hard to treat and diagnose in poorer countries. <br><br />
Up to now, a high quality lab that uses modern diagnostics is a prerequisite for early, rapid and accurate detection of TB. Therefore, diagnosis of TB and drug resistant TB remains a particular challenge for laboratory systems, especially in developing countries.<br><br />
The lack of cheap, quick and accurate tests make it hard to control the Tuberculosis epidemic, which claims millions of lives every year in developing countries.<br><br />
Setting up a cheap, fast and culture-based method could therefore decrease diagnostic time and facilitate patient treatment.<br><br />
The most common method for diagnosing TB nowadays is sputum smear microscopy, in which bacteria are observed in sputum samples of patients under the microscope. However, this cannot be used to identify paucibacillary (containing just a few bacteria) or extrapulmonary (outside of the lungs) TB.<br />
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<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
Diagnosis methods using culture methods require laboratory infrastructure that is not widely available in countries with a high burden of TB and results are only available after a few weeks.<br />
Other conventional methods used to diagnose multidrug-resistant TB (MDR-TB) also rely on the culturing of specimens followed by drug susceptibility testing (DST). Results take weeks to obtain and not all laboratories have the capacity to perform DST of first-line or of second-line drugs.<br><br />
MTB/RIF is a new rapid molecular test that can diagnose TB and rifampicin-resistant TB within hours. Molecular tests, such as GeneXpert, unlike culture-based methods, are fast, accurate and can detect drug-resistant strains. But the high costs and need for laboratories make access an issue for developing countries.<br><br />
The new method, published in the Journal of Applied Microbiology, uses a microcalorimeter to detect heat produced by Mycobacterium tuberculosis, the bacterium that causes TB, on a growth medium. The study showed that detection takes 4–5 days but more sensitive microcalorimeters could detect tuberculosis in 24 hours.<br />
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<div id="Design"></div><br />
<h2>System Design</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
By taking advantage of the state of the art CRISPR/Cas research and combining it with phage diagnostics, we designed a sensor that is able to screen for a specific target gene. Our producer strain carries a helper plasmid that codes for the phage capsid proteins of M13 as well as our phagemid plasmid with our sensor system. Our sensor system consists out of three parts: the Cas9 gene under a constitutive promoter, the anti-KAN gRNA also under a constitutive promoter and the reporter element LacZ under the control of the pRecA promoter. As the helper plasmid doesn’t have a packaging sequence, only our sensor system phagemid is packed into the M13 capsids. As M13 is a lysogenic phage, the phagemid particles are exported into the media where they can be easily isolated and are ready to use to sense if an other strain contains our target sequence. <br />
</p><br />
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<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
As the phagemid is derived from M13, it infects only F+ (conjugated) cells. In our case, we conjugated our cells so that they can be easily infected. <p> Within the target strain, the Cas9 protein, as well as the gRNA get expressed. The gRNA then attaches to the Cas9 protein and guides the Cas9 to the target sequence (kanamycin resistance gene). Once bound to the sequence, the Cas9 protein generates a target specific double strand break. This double strand break leads to the cleavage of LexA. LexA is a protein bound to the pREC promoter that inhibits the expression of genes under the control of the pREC promoter. With the cleavage of LexA, the expression of our reporter LacZ is started, which leads in the presence of X-gal to a blue color output. <br />
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<center><img src="https://static.igem.org/mediawiki/2013/1/15/PB_Detect_Design_GIF-loop.gif" width="80%"/></center><br />
<div style="margin-left:10%"><p><b>Figure 2:Course of the detection and reporting of an antibiotic resistance gene with the CRISPR/Cas system. </b> <div style="font-size:90%">After the plasmid has been released into the target cells, gRNA and Cas9 get expressed. The gRNA guides the Cas9 to the target, where it generates a double strand break. This activates the SOS response. As a results, LexA is cleaved which allows the expression of the reporter. In the presence of X-gal the cells turn blue. </div></p></div><br />
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<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Our system is highly modular as with the simple change of the gRNA target sequence (20bp), any gene of interest can be identified and targeted. This means that our system can be used for different applications and purposes, as for example a mutation screening. It is also not specified only for <i>E.coli</i> and the phage M13. Our whole system can be easily transferred to other phage systems that target other host bacteria. In our case, as we want to develop a sensor to test <i>Mycobacterium tuberculosis</i>, we could in principle transfer our system to mycobacteria phages. With what we are presenting here, we have a proof of concept in <i>E.coli</i>. By using host specific phages, we can easy identify specific bacteria and genes they carry. By building a library of phages with different gRNAs we could screen for many different genes in parallel including other resistances or pathogenic genes.<br />
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</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
For future perspectives, we plan to further test and improve the system so that in theory, we will generate a sensor that can be used without using high-tech laboratory facilities. This is very important, as easily to use sensors are needed in the developing countries in which tuberculosis is still a prevalent disease.<p><br />
In a prospective design study we imagine the development of a handkerchief, in which our phagemid system can be integrated. By spitting on the tissue, we get a bacterial sample that will be tested by phages. Depending on which phagemid is integrated into the handkerchief, we can test for the <i>Mycobacterium tuberculosis</i> in general as well as for the different antibiotic resistances. A handkerchief is easy to use and the blue color output easy to read out. As phages are acting very fast, an easily usable and fast sensor system is developed.<br />
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<img src="https://static.igem.org/mediawiki/2013/2/25/PB_designscenario.png" width="1100"/><br />
<p><b>Figure 3 </b> <div style="font-size:90%">your text here </div></p><br />
<br />
<div id="Background"></div><br />
<h2>Background</h2><br />
<h3>CRISPRs</h3><br />
<div class="leftparagraph"> <br />
<p>&nbsp;&nbsp;<br />
The mechanism we are using for our sensor is based on the CRISPR/Cas System. The CRISPR/Cas genome editing method, which recently became very popular, is derived from the bacterial “immune system”. CRISPRs are Clustered Regularly Interspaced Short Palindromic Repeats that are part of the bacterial genome. These loci contain multiple short repeats. In between the repeats are so called spacers that are sequences derived from extrachromosomal DNA, e.g. from invading viruses or plasmids (Figure 3). Within bacteria, those CRISPRs are naturally used to detect and destroy foreign DNA that is saved in the spacers.</p><br />
<p>In total the CRISPRs and the spacers form a so-called CRISPR array that is transcribed as one unit. CRISPR associated proteins (Cas proteins) are involved in further processing and action steps of the CRISPR system. There are many different regulation systems, here we describe the Cas9 system that will be used for our purposes (Figure 3).</p><br />
<p>The transcribed mRNA is processed into so called crRNA (CRISPR RNA), which includes the spacer sequence of foreign DNA. Together with a transactingCRISPR RNA (tracrRNA), the crRNA forms a duplex that is cleaved by RNaseII. The resulting hybrid serves as guide for the Cas9 protein that generates double strand breaks at the position the RNAs guide it to (Figure 3). By this double strand break the invading DNA is destroyed. The last years, researchers discovered the CRISPRs as a method for genome editing. </p><br />
<br><br><br><br><br><br />
<img src="https://static.igem.org/mediawiki/2013/4/43/PB_gRNA_%282%29.png" width="520"/><br />
<p><b>Figure 3:</b> CRISPR/Cas technology description (<a href="http://www.addgene.org/CRISPR/guide/" target="_blank">Addgene.org</a>).</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; By designing the spacer sequence, specific sequences in the genome can be targeted. With the provision of a sequence with homologous sequences, easy insertion can be done. This method can be used to insert mutations or new sequences nearly everywhere in the genome.<br><br />
Recently many papers have been published for genome editing in bacteria (Jinek et al., 2012, <a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Jiang2013" target="_blank">Jiang <i>et al</i>. 2013</a>), yeast (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#DiCarlo2013" target="_blank">DiCarlo <i>et al</i>. 2013</a>) and mammalian cells (Mali et al., 2013, Cong et al., 2013). They describe how to use the CRISPRs for different purposes. One requirement to target a sequence is a NGG at the end of the sequence. This NGG sequence is called PAM - protospacer adjacent motif, while the target sequence itself is called the protospacer, which should have a length of around 12 to 20 bp.</p><br />
<p>In our approach we test two different systems, the systems of DiCarlo et al. 2013 and Jiang et al. 2013. The system of Jiang is a system developed for bacteria and especially for <i>E.coli</i>. The system of DiCarlo is based on a paper of Mali et al. 2013 and adapted to yeast.</p><br />
<p>Different from the Jiang paper, the DiCarlo paper uses a gRNA (guideRNA) to guide the Cas9 (Figure 4). The gRNA is actually the RNA that results after transcribing and folding is the same complex as you get after the processing of the tracrRNA with the crRNA. It is hence an improvement, which makes the design and expression easier. But as the system hasn’t been tested before in bacteria, we will use both systems to make sure we get the desired results.</p><br />
<br><br />
<br><br />
<br><br />
<center><img src="https://static.igem.org/mediawiki/2013/6/64/PB_gRNA_%281%29.png" width="430"/></center><br />
<p><b>Figure 4:</b>Cas9 protein interacting with CRISPR gRNA<div style="font-size:90%">Illustration of Cas9 protein interacting with CRISPR gRNA to direct endonuclease activity proximal to the PAM sequence (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#DiCarlo2013" target="_blank">DiCarlo et al. 2013</a>) </div></p><br />
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<br />
<h3>RecA promoter</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Our reporter system consists out of the RecA promoter and LacZ. Originally, the RecA promoter of <i>E.coli</i> has its main role in the activation of the SOS repair system. It is regulated by the LexA repressor, which binds to the SOS box sequence of the promoter. DNA damage leads to an inducing signal, which then activates the RecA protein. In the SOS response the LexA repressor is cleaved by the RecA protein, so the full RecA expression can be reached. The RecA protein can then repair both single stranded and double stranded DNA breaks.</p><br />
<p>In our project RecA promoters used to detect double stranded DNA breaks in the region of antibiotic resistance genes caused by the CIRSPR/Cas system. To get the desired activation of the promoter, it is important to assure that no other stressing agents might activate the RecA promoter. Those agents could be UV light, X-ray, ionizing radiation and different types of DNA breaking compounds. </p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
The SOS response in <i>E.coli</i> could also get induced by engineered M13 phage infection that are defective in the minus-strand origin, and so unable to form the double stranded replicative stage.</p><br />
<p>In this case the single-stranded DNA would be the SOS-inducing signal. The wild type M13 phage doesn’t induce the SOS response (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Higashitani1992" target="_blank">Higashitani <i>et al</i>. 1992</a>). In another study genomes of phage M13 infected and uninfected <i>E.coli</i> strains were compared by oligonucleotide microarrays, where no stress response genes were scored as upregulated (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Karlsson2005" target="_blank">Karlsson <i>et al</i>. 2005</a>). Regarding the phagemids, an A UV-damaged oriC phagemid did not induce SOS response in a recipient cells oriF phagemids on the other hand did (Sommer et al. 1991). To make sure that our system functions reliably, we will test the activation of the RecA promoter at different stress inputs (UV, phage infection,…) by measuring the fluorescence of YFP driven by the RecA promoter.</p><br />
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<div id="Results"></div><br />
<h2>Progress and preliminary Results</h2><br />
<h3>Parts</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp; Up to this point we cloned each of our parts into BioBrick vectors. We cloned the <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Monday_30th_September.html">gRNA anti-Kan </a> into pSB1C3 and pSB1A3.We used for this the assembly standard BioBrick cloning as well the new proposed <a href="https://2013.igem.org/Team:Paris_Bettencourt/Assembly_Standard">Assembly Standard.</a>. Both assemblies were successful and proved by colony PCR as well as by sequencing. We also used both standards for cloning the <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Monday_30th_September.html">crRNA.</a>. <br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
Also this is verified by colony PCR and by sequencing. For the cloning of the tracrRNA-CAS9 part we used standard BioBrick cloning, inserted into pSB1A3 and sequence verified it. We achieved the same for the pRecA-LacZ part (pSB1C3 and pSB1A3 backbones) that was submitted to the parts registry. <br><br />
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<br><br />
<h3>Killing assay to verify targeting specificity</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp; For the characterization of the Cas9 and the gRNA anti-KAN we performed a <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Thursday_3rd_October.html">killing assay </a> . Therefore we co-transformed the Cas9 with gRNA anti-KAN into host bacteria that contain the KAN resistance gene cassette as well as without the cassette. In the KAN resistance bacteria, the CRISPR/Cas complex generated generate double strand breaks that killed the bacteria. After co-transforming the plasmids, we plated the bacteria on the one hand on the single antibiotic where the resistance is carried by the Cas9 plasmid as well as on the single antibiotic which resistance is present on the gRNA plasmid. As the two plasmids contain the same origin of replication, this will selesct for only the single plasmid and hence a non-functional CRISPR/Cas system. To get a working system, we plated the co-transformed bacteria on both antibiotics, of which the reistances were on the two plasmids. As we can see in Figure 5, if we select for both plasmids, we get a reduced number of colonies in the strain that contains the target sequence, the kanamycine resistance cassette. We attribute this reduced number to Cas9-induced cleavage of the chromosome specifically at the KanR casette, with about 99% efficiency. This leads after repeatedly double strand breaks generated by the CRISPR/Cas system to cell death which explaines the reduced colony number.<br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
<img src="https://static.igem.org/mediawiki/2013/0/01/PB_13_Results_detect_killing_assay.png" width="80%" style="margin-bottom:-80px;"/> <br />
<br><br />
<br><br />
<p><b>Figure 5: </b> CRISPR anti-Kan plasmids target specifically kanamycin resistant <i>E. coli</i>.<div style="font-size:90%"> We introduced our CRISPR-based DNA cleavage system to two strains of <i>E. coli</i>: one WT (blue bars) and one carrying a genomically integrated kanamycin resistance casette (KanR, blue bars). The strains were co-transformed with two plasmids. One with the Cas9 construct, the other with the anti-Kanamycin gRNA. WT <i>E. coli</i> could be efficiently transformed with one or both plasmids, as determined by selective plating. However, KanR <i>E. coli</i> could not be efficiently transformed with both. We attribute this to Cas9-induced cleavage of the chromosome specifically at the KanR casette, with about 99% efficiency.</div></p><br />
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<br><br />
<h3>Characterization of the reporter - under construction</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;To characterize the pRecA –LacZ construct, we induced double strand breaks with Mytomycin C (MMC) and analyzed the resulting LacZ expression levels with the Miller assay. The same time, we wanted to characterize our final system: our target strain with the kanamycin resistance gene that also carries the reporter and the Cas9. The gRNA is delivered by a phage. As positive control, we used MG1655, which has a constitutive expression of LacZ, as negative control the parental strain of the target strain, which doesn’t have a kanamycin resistance cassette but also has the reporter and Cas9.<br />
As it can be seen in Figure 6, we didn’t get any expression of LacZ beside in the positive control, the MG1655 strain. As we worry, that our reporter might be not functional, we started to characterize a reporter constructed by Ariel Lindner. This reporter is YFP under the control of pREC. We analyzed its expression rates by inducing double strand breaks with Mitomycin C and Niprofloxacin. The data generated by FACS analysis over time can be seen in Figure 7. We can clearly see an induction of the pREC promoter due to induction with MMC and Niprofloxacin. Due to time constraints, we were not able to successfully adapt our system to use this pREC-YFP reporter in our target strain. In previous iGEM years, there has already been a pREC-LacZ Biobricked constructed (Heidelberg 2012). In principle, our system couldbe completed, as a functional pREC-LacZ already exists. By adding the reporter of Heidelberg 2012 to our target strain with the Cas9, we should be able to get a functional sensor. This sensor can detect and report a specific DNA sequence due to a phagemid delivered gRNA that guides the present Cas9 to a target where the Cas9 generates a double strand break, which is reported by pREC-LacZ.<br />
</div></p><br />
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<br><br />
<h3>Next steps</h3><br />
<div class="left paragraph"><br />
As previously mentioned, the reporter didn’t work as expected. This can have several reasons. As our other positive control (beside MG1655), the MMC induced strains carrying the reporter didn’t show any expression, it stands to reason that the reporter itself is not functional. Another reason could be, that the phagemid didn’t deliver the gRNA or not in enough amounts to show an effect of the complete working system.<br />
</div></p><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
To test, if the phagemid delivers the gRNA correctly, we will perform another killing assay as we have done it before with the difference that the gRNA is delivered by the phagemid. The strains are then plated to see, if there is a reduced number of colonies of the target strain with phagemid in comparison to a control strain and without added phages. We expect the results before the end of iGEM.<br />
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<br />
<h2>Literature</h2><br />
<div class="leftparagraph"><br />
<ul><br />
<li>James E. DiCarlo, Julie E. Norville, Prashant Mali, Xavier Rios, John Aach and George M. Church (2013).<i> Genome engineering in Saccharomyces cerevisiae using CRISPR-Cas systems.</i> Nucleic Acids Research. 2013, 1–8.</li><br />
<li id="">Antonio R. Fernandez de Henestrosa, Tomoo Ogi, Sayura Aoyagi, David Chafin, Jeffrey J. Hayes, Haruo Ohmori and Roger Woodgate (2000). <i>Identification of additional genes belonging to the LexA regulon in Escherichia coli.</i> Molecular Microbiology .2000 35(6), 1560-1572.</li><br />
<li id="">Higashitani N., Higashitani I.A., Roth A., Horiuchi A.K. (1992). <i>SOS Induction in Escherichia coli by Infection with Mutant Filamentous Phage That Are Defective in Initiation of Complementary-Strand DNA Synthesis.</i> Journal of Bacteriology. 174:1612-1618.</li><br />
<li id="">Wenyan Jiang, David Bikard, David Cox, Feng Zhang & Luciano A Marraffini (2013). <i>RNA-guided editing of bacterial genomes using CRISPR-Cas systems.</i> Nature Biotechnology. 31 (3), 233-2398.</li><br />
<li id="">Douglas H. Juers, Brian W. Matthews, and Reuben E. Huber (2012). <i>LacZ b-galactosidase: Structure and function of an enzyme of historical and molecular biological importance.</i> Protein Science. 2012, 21,1792—1807.</li><br />
<li id="">Karlsson F., Malmborg-Hager A.C., Albrekt A.S., Borrebaeck C.A.K. (2005). <i>Genome-wide comparison of phage M13-infected vs. uninfected Escherichia coli. </i> Can. J. Microbiol. 51:29-35.</li><br />
</ul><br />
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<div class="rightparagraph"><br />
<ul><br />
<br />
<li id="">Kimberly L. Keller, Terri L. Overbeck-Carrick, Doris J. Beck (2001). <i>Survival and induction of SOS in Escherichia coli treated with cisplatin, UV irradiation, or mitomycin C are dependent on the function of the RecBC and RecFOR pathways of homologous recombination. </i> Mutation Research. 486, 2001, 21–29.</li><br />
<li id="">Kobayashi, Ichizo; and Handa, Naofumi (2009). <i>DNA Doublestrand Breaks and Their Consequences in Bacteria. </i> Encyclopedia of Life Sciences (ELS). John Wiley & Sons, Ltd: Chichester.</li><br />
<li id=""> Timothy K. Lu, Jayson Bowers, and Michael S. Koeris (2013). <i> Advancing bacteriophage-based microbial diagnostics with synthetic biology. </i>Trends in Biotechnology. April 2013, 31 (6), 325-227.</li><br />
<li id="">Anders Norman, Lars Hestbjerg Hansen, and Søren J. Sørensen (2004). <i>Construction of a ColD cda Promoter-Based SOS-Green Fluorescent Protein Whole-Cell Biosensor with Higher Sensitivity toward Genotoxic Compounds than Constructs Based on recA, umuDC, or sulA Promoters. </i> APPLIED AND ENVIRONMENTAL MICROBIOLOGY. May 2005, p. 2338–2346.</li> <br />
<li id="">Sommer S., Leitao A., Bernardi A., Bailone A., Devoret R. (1991). <i>Introduction of a UV-damaged replicon into a recipient cell is not a sufficient condition to produce an SOS-inducing signal.</i> Mutation Research/DNA Repair. 254:107-17.</li><br />
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<h2>Attributions</h2> <br />
<br />
<p> Most of the strains and plasmids used for this project were kindly provided by the INSERM U1001 lab.</p><br />
<p> The Cas9 plasmid as well as the CRISPR plasmid were ordered from Addgene. The crRNA was designed after consultation with David Bikard.</p><br />
<p> The sequence of LacZ used in this project was taken from pBAC-BA-lacZ from Addgene. The corresponding pREC sequence is the natural sequence. The source for the sequence is EcoCyc.</p><br />
<p> The phaegmid template as well as the helper plasmid were provided by Monica Ortiz from the Endy Lab, Stanford.</p><br />
<p> The project itself was designed and accomplished by Nicolas Koutsoubelis, Anne Loechner and Marguerite Benony with consultation with Edwin Wintermute, Stanislas and Ariel Lindner.</p><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Project/DetectTeam:Paris Bettencourt/Project/Detect2013-10-28T23:53:58Z<p>Marguerite: </p>
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<div class="bkgr"><br />
<h2>Background</h2><br />
<p>CRISPR/Cas systems generate site-specific double-strand breaks and have recently been used for genome editing. </p><br />
</div><br />
<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>Successfully cloned gRNA anti-KAN, crRNA anti-KAN, tracrRNA-Cas9 and pRecA-LacZ into Biobrick backbones and therefore generated four new BioBricks. </li><br />
<li> Confirmation of site-specific binding and DNA double-strand breaks generated by the gRNA-Cas9 complex in the kanamycin resistance casette. </li><br />
<li><a href="https://2013.igem.org/Team:Paris_Bettencourt/Assembly_Standard">Testing the new assembly standard for our cloning.</a></li><br />
</ul><br />
<p></p><br />
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<div class="biocriks"><br />
<h2>BioBricks</h2><br />
<ol><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137012">BBa_K1137012</br>(gRNA anti-KAN)</a></li><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137013">BBa_K1137013</br>(crRNA anti-KAN)</a></li> <br />
<li><a href="http://parts.igem.org/Part:BBa_K1137014">BBa_K1137014</br>(tracrRNA-Cas9)</a></li><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137015">BBa_K1137015</br>(pRecA-LacZ)</a></li><br />
</ol><br />
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<div class="aims"><br />
<h2>Aims</h2><br />
<p>Building a genotype sensor based on CRISPR/Cas that reports on the existence of an antibiotic resistance gene.</p><br />
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<a href="#Aim"><br />
<div class="hlink"><br />
<h2>Skip to Aim</h2><br />
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</a><br />
<a href="#Design"><br />
<div class="hlink"><br />
<h2>Skip to Design</h2><br />
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</a><br />
<a href="#Background"><br />
<div class="hlink"><br />
<h2>Skip to Background</h2><br />
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</a><br />
<a href="#Results"> <br />
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<h2>Skip to Results</h2><br />
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<div id="Aim"></div><br />
<h2>Aim</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
We developed a sensor to detect whether a particular bacterial strain carries a specific antibiotic resistance gene. Our sensor system consists of <i>E.coli </i> lab strain and of a synthetic phagemid with a CRISPR/Cas system and LacZ as a reporter under the control of a pRecA promoter (SOS response promoter). <br /> If our CRISPR/Cas system can bind to the target (antibiotic resistance gene), the Cas9 generates at this specific target site a double strand break, which will induce the expression of our double-strand break SOS sensor (Figure. 1). Having the system on a phagemid, the sensor system will spread all over a population, to get a clear color output if the target has been detected. Depending on target sequence the system carries, we can identify different antibiotic resistances in a strain. This is a novel approach of detecting genes in bacterial strains. We used <i>E.coli</i> and a M13 phagemid to target the kanamycin resistance gene. <br /> This sensor is a proof of concept for a similar system in <i>Mycobacterium tuberculosis</i>. Such a system could potentially be used to test if a patient has TB and what type of resistance genes the specific strain contains to adapt the patient’s drug treatment.<br />
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<div class="rightparagraph"><br />
<center> <img width="110%" src="https://static.igem.org/mediawiki/2013/2/2d/PB_13_TB_Sensor_Detect_Overview.png"/><br></center><br />
<p><b>Figure 1:</b> Detection and reporting of an antibiotic resistance gene with a CRISPR/Cas system. <div style="font-size:90%">After expression of the Cas9 and gRNA, the gRNA guides the Cas9 to the target sequence, the kanamycin resistance. There, the Cas9 generates a double strand break. This activates the SOS response. The reporter LacZ is under the pRECA promoter, which gets activated during the SOS response and we get a blue cell, if the resistance gene has successfully been detected. </div></p><br />
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<br />
<div id="Motivation"></div><br />
<h2>Motivation and existing TB sensors/tests</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Tuberculosis (TB) remains a major global health problem. While the treatment of this disease in countries with adequate medical care is fairly easy to detect and treat, it remains hard to treat and diagnose in poorer countries. <br><br />
Up to now, a high quality lab that uses modern diagnostics is a prerequisite for early, rapid and accurate detection of TB. Therefore, diagnosis of TB and drug resistant TB remains a particular challenge for laboratory systems, especially in developing countries.<br><br />
The lack of cheap, quick and accurate tests make it hard to control the Tuberculosis epidemic, which claims millions of lives every year in developing countries.<br><br />
Setting up a cheap, fast and culture-based method could therefore decrease diagnostic time and facilitate patient treatment.<br><br />
The most common method for diagnosing TB nowadays is sputum smear microscopy, in which bacteria are observed in sputum samples of patients under the microscope. However, this cannot be used to identify paucibacillary (containing just a few bacteria) or extrapulmonary (outside of the lungs) TB.<br />
</p><br />
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<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
Diagnosis methods using culture methods require laboratory infrastructure that is not widely available in countries with a high burden of TB and results are only available after a few weeks.<br />
Other conventional methods used to diagnose multidrug-resistant TB (MDR-TB) also rely on the culturing of specimens followed by drug susceptibility testing (DST). Results take weeks to obtain and not all laboratories have the capacity to perform DST of first-line or of second-line drugs.<br><br />
MTB/RIF is a new rapid molecular test that can diagnose TB and rifampicin-resistant TB within hours. Molecular tests, such as GeneXpert, unlike culture-based methods, are fast, accurate and can detect drug-resistant strains. But the high costs and need for laboratories make access an issue for developing countries.<br><br />
The new method, published in the Journal of Applied Microbiology, uses a microcalorimeter to detect heat produced by Mycobacterium tuberculosis, the bacterium that causes TB, on a growth medium. The study showed that detection takes 4–5 days but more sensitive microcalorimeters could detect tuberculosis in 24 hours.<br />
</p><br />
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<br />
<div id="Design"></div><br />
<h2>System Design</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
By taking advantage of the state of the art CRISPR/Cas research and combining it with phage diagnostics, we designed a sensor that is able to screen for a specific target gene. Our producer strain carries a helper plasmid that codes for the phage capsid proteins of M13 as well as our phagemid plasmid with our sensor system. Our sensor system consists out of three parts: the Cas9 gene under a constitutive promoter, the anti-KAN gRNA also under a constitutive promoter and the reporter element LacZ under the control of the pRecA promoter. As the helper plasmid doesn’t have a packaging sequence, only our sensor system phagemid is packed into the M13 capsids. As M13 is a lysogenic phage, the phagemid particles are exported into the media where they can be easily isolated and are ready to use to sense if an other strain contains our target sequence. <br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
As the phagemid is derived from M13, it infects only F+ (conjugated) cells. In our case, we conjugated our cells so that they can be easily infected. <p> Within the target strain, the Cas9 protein, as well as the gRNA get expressed. The gRNA then attaches to the Cas9 protein and guides the Cas9 to the target sequence (kanamycin resistance gene). Once bound to the sequence, the Cas9 protein generates a target specific double strand break. This double strand break leads to the cleavage of LexA. LexA is a protein bound to the pREC promoter that inhibits the expression of genes under the control of the pREC promoter. With the cleavage of LexA, the expression of our reporter LacZ is started, which leads in the presence of X-gal to a blue color output. <br />
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<center><img src="https://static.igem.org/mediawiki/2013/1/15/PB_Detect_Design_GIF-loop.gif" width="80%"/></center><br />
<div style="margin-left:10%"><p><b>Figure 2:Course of the detection and reporting of an antibiotic resistance gene with the CRISPR/Cas system. </b> <div style="font-size:90%">After the plasmid has been released into the target cells, gRNA and Cas9 get expressed. The gRNA guides the Cas9 to the target, where it generates a double strand break. This activates the SOS response. As a results, LexA is cleaved which allows the expression of the reporter. In the presence of X-gal the cells turn blue. </div></p></div><br />
<br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Our system is highly modular as with the simple change of the gRNA target sequence (20bp), any gene of interest can be identified and targeted. This means that our system can be used for different applications and purposes, as for example a mutation screening. It is also not specified only for <i>E.coli</i> and the phage M13. Our whole system can be easily transferred to other phage systems that target other host bacteria. In our case, as we want to develop a sensor to test <i>Mycobacterium tuberculosis</i>, we could in principle transfer our system to mycobacteria phages. With what we are presenting here, we have a proof of concept in <i>E.coli</i>. By using host specific phages, we can easy identify specific bacteria and genes they carry. By building a library of phages with different gRNAs we could screen for many different genes in parallel including other resistances or pathogenic genes.<br />
<br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
For future perspectives, we plan to further test and improve the system so that in theory, we will generate a sensor that can be used without using high-tech laboratory facilities. This is very important, as easily to use sensors are needed in the developing countries in which tuberculosis is still a prevalent disease.<p><br />
In a prospective design study we imagine the development of a handkerchief, in which our phagemid system can be integrated. By spitting on the tissue, we get a bacterial sample that will be tested by phages. Depending on which phagemid is integrated into the handkerchief, we can test for the <i>Mycobacterium tuberculosis</i> in general as well as for the different antibiotic resistances. A handkerchief is easy to use and the blue color output easy to read out. As phages are acting very fast, an easily usable and fast sensor system is developed.<br />
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<br><br />
<img src="https://static.igem.org/mediawiki/2013/2/25/PB_designscenario.png" width="1100"/><br />
<p><b>Figure 3:description here </div></p></div><br />
<br><br />
<div id="Background"></div><br />
<h2>Background</h2><br />
<h3>CRISPRs</h3><br />
<div class="leftparagraph"> <br />
<p>&nbsp;&nbsp;<br />
The mechanism we are using for our sensor is based on the CRISPR/Cas System. The CRISPR/Cas genome editing method, which recently became very popular, is derived from the bacterial “immune system”. CRISPRs are Clustered Regularly Interspaced Short Palindromic Repeats that are part of the bacterial genome. These loci contain multiple short repeats. In between the repeats are so called spacers that are sequences derived from extrachromosomal DNA, e.g. from invading viruses or plasmids (Figure 3). Within bacteria, those CRISPRs are naturally used to detect and destroy foreign DNA that is saved in the spacers.</p><br />
<p>In total the CRISPRs and the spacers form a so-called CRISPR array that is transcribed as one unit. CRISPR associated proteins (Cas proteins) are involved in further processing and action steps of the CRISPR system. There are many different regulation systems, here we describe the Cas9 system that will be used for our purposes (Figure 3).</p><br />
<p>The transcribed mRNA is processed into so called crRNA (CRISPR RNA), which includes the spacer sequence of foreign DNA. Together with a transactingCRISPR RNA (tracrRNA), the crRNA forms a duplex that is cleaved by RNaseII. The resulting hybrid serves as guide for the Cas9 protein that generates double strand breaks at the position the RNAs guide it to (Figure 3). By this double strand break the invading DNA is destroyed. The last years, researchers discovered the CRISPRs as a method for genome editing. </p><br />
<br><br><br><br><br><br />
<img src="https://static.igem.org/mediawiki/2013/4/43/PB_gRNA_%282%29.png" width="520"/><br />
<p><b>Figure 3:</b> CRISPR/Cas technology description (<a href="http://www.addgene.org/CRISPR/guide/" target="_blank">Addgene.org</a>).</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; By designing the spacer sequence, specific sequences in the genome can be targeted. With the provision of a sequence with homologous sequences, easy insertion can be done. This method can be used to insert mutations or new sequences nearly everywhere in the genome.<br><br />
Recently many papers have been published for genome editing in bacteria (Jinek et al., 2012, <a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Jiang2013" target="_blank">Jiang <i>et al</i>. 2013</a>), yeast (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#DiCarlo2013" target="_blank">DiCarlo <i>et al</i>. 2013</a>) and mammalian cells (Mali et al., 2013, Cong et al., 2013). They describe how to use the CRISPRs for different purposes. One requirement to target a sequence is a NGG at the end of the sequence. This NGG sequence is called PAM - protospacer adjacent motif, while the target sequence itself is called the protospacer, which should have a length of around 12 to 20 bp.</p><br />
<p>In our approach we test two different systems, the systems of DiCarlo et al. 2013 and Jiang et al. 2013. The system of Jiang is a system developed for bacteria and especially for <i>E.coli</i>. The system of DiCarlo is based on a paper of Mali et al. 2013 and adapted to yeast.</p><br />
<p>Different from the Jiang paper, the DiCarlo paper uses a gRNA (guideRNA) to guide the Cas9 (Figure 4). The gRNA is actually the RNA that results after transcribing and folding is the same complex as you get after the processing of the tracrRNA with the crRNA. It is hence an improvement, which makes the design and expression easier. But as the system hasn’t been tested before in bacteria, we will use both systems to make sure we get the desired results.</p><br />
<br><br />
<br><br />
<br><br />
<center><img src="https://static.igem.org/mediawiki/2013/6/64/PB_gRNA_%281%29.png" width="430"/></center><br />
<p><b>Figure 4:</b>Cas9 protein interacting with CRISPR gRNA<div style="font-size:90%">Illustration of Cas9 protein interacting with CRISPR gRNA to direct endonuclease activity proximal to the PAM sequence (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#DiCarlo2013" target="_blank">DiCarlo et al. 2013</a>) </div></p><br />
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<br />
<h3>RecA promoter</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Our reporter system consists out of the RecA promoter and LacZ. Originally, the RecA promoter of <i>E.coli</i> has its main role in the activation of the SOS repair system. It is regulated by the LexA repressor, which binds to the SOS box sequence of the promoter. DNA damage leads to an inducing signal, which then activates the RecA protein. In the SOS response the LexA repressor is cleaved by the RecA protein, so the full RecA expression can be reached. The RecA protein can then repair both single stranded and double stranded DNA breaks.</p><br />
<p>In our project RecA promoters used to detect double stranded DNA breaks in the region of antibiotic resistance genes caused by the CIRSPR/Cas system. To get the desired activation of the promoter, it is important to assure that no other stressing agents might activate the RecA promoter. Those agents could be UV light, X-ray, ionizing radiation and different types of DNA breaking compounds. </p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
The SOS response in <i>E.coli</i> could also get induced by engineered M13 phage infection that are defective in the minus-strand origin, and so unable to form the double stranded replicative stage.</p><br />
<p>In this case the single-stranded DNA would be the SOS-inducing signal. The wild type M13 phage doesn’t induce the SOS response (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Higashitani1992" target="_blank">Higashitani <i>et al</i>. 1992</a>). In another study genomes of phage M13 infected and uninfected <i>E.coli</i> strains were compared by oligonucleotide microarrays, where no stress response genes were scored as upregulated (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Karlsson2005" target="_blank">Karlsson <i>et al</i>. 2005</a>). Regarding the phagemids, an A UV-damaged oriC phagemid did not induce SOS response in a recipient cells oriF phagemids on the other hand did (Sommer et al. 1991). To make sure that our system functions reliably, we will test the activation of the RecA promoter at different stress inputs (UV, phage infection,…) by measuring the fluorescence of YFP driven by the RecA promoter.</p><br />
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<br />
<div id="Results"></div><br />
<h2>Progress and preliminary Results</h2><br />
<h3>Parts</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp; Up to this point we cloned each of our parts into BioBrick vectors. We cloned the <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Monday_30th_September.html">gRNA anti-Kan </a> into pSB1C3 and pSB1A3.We used for this the assembly standard BioBrick cloning as well the new proposed <a href="https://2013.igem.org/Team:Paris_Bettencourt/Assembly_Standard">Assembly Standard.</a>. Both assemblies were successful and proved by colony PCR as well as by sequencing. We also used both standards for cloning the <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Monday_30th_September.html">crRNA.</a>. <br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
Also this is verified by colony PCR and by sequencing. For the cloning of the tracrRNA-CAS9 part we used standard BioBrick cloning, inserted into pSB1A3 and sequence verified it. We achieved the same for the pRecA-LacZ part (pSB1C3 and pSB1A3 backbones) that was submitted to the parts registry. <br><br />
</div><br />
<div style="clear: both;"></div><br />
<br><br />
<h3>Killing assay to verify targeting specificity</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp; For the characterization of the Cas9 and the gRNA anti-KAN we performed a <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Thursday_3rd_October.html">killing assay </a> . Therefore we co-transformed the Cas9 with gRNA anti-KAN into host bacteria that contain the KAN resistance gene cassette as well as without the cassette. In the KAN resistance bacteria, the CRISPR/Cas complex generated generate double strand breaks that killed the bacteria. After co-transforming the plasmids, we plated the bacteria on the one hand on the single antibiotic where the resistance is carried by the Cas9 plasmid as well as on the single antibiotic which resistance is present on the gRNA plasmid. As the two plasmids contain the same origin of replication, this will selesct for only the single plasmid and hence a non-functional CRISPR/Cas system. To get a working system, we plated the co-transformed bacteria on both antibiotics, of which the reistances were on the two plasmids. As we can see in Figure 5, if we select for both plasmids, we get a reduced number of colonies in the strain that contains the target sequence, the kanamycine resistance cassette. We attribute this reduced number to Cas9-induced cleavage of the chromosome specifically at the KanR casette, with about 99% efficiency. This leads after repeatedly double strand breaks generated by the CRISPR/Cas system to cell death which explaines the reduced colony number.<br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
<img src="https://static.igem.org/mediawiki/2013/0/01/PB_13_Results_detect_killing_assay.png" width="80%" style="margin-bottom:-80px;"/> <br />
<br><br />
<br><br />
<p><b>Figure 5: </b> CRISPR anti-Kan plasmids target specifically kanamycin resistant <i>E. coli</i>.<div style="font-size:90%"> We introduced our CRISPR-based DNA cleavage system to two strains of <i>E. coli</i>: one WT (blue bars) and one carrying a genomically integrated kanamycin resistance casette (KanR, blue bars). The strains were co-transformed with two plasmids. One with the Cas9 construct, the other with the anti-Kanamycin gRNA. WT <i>E. coli</i> could be efficiently transformed with one or both plasmids, as determined by selective plating. However, KanR <i>E. coli</i> could not be efficiently transformed with both. We attribute this to Cas9-induced cleavage of the chromosome specifically at the KanR casette, with about 99% efficiency.</div></p><br />
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<br />
<br><br />
<h3>Characterization of the reporter - under construction</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;To characterize the pRecA –LacZ construct, we induced double strand breaks with Mytomycin C (MMC) and analyzed the resulting LacZ expression levels with the Miller assay. The same time, we wanted to characterize our final system: our target strain with the kanamycin resistance gene that also carries the reporter and the Cas9. The gRNA is delivered by a phage. As positive control, we used MG1655, which has a constitutive expression of LacZ, as negative control the parental strain of the target strain, which doesn’t have a kanamycin resistance cassette but also has the reporter and Cas9.<br />
As it can be seen in Figure 6, we didn’t get any expression of LacZ beside in the positive control, the MG1655 strain. As we worry, that our reporter might be not functional, we started to characterize a reporter constructed by Ariel Lindner. This reporter is YFP under the control of pREC. We analyzed its expression rates by inducing double strand breaks with Mitomycin C and Niprofloxacin. The data generated by FACS analysis over time can be seen in Figure 7. We can clearly see an induction of the pREC promoter due to induction with MMC and Niprofloxacin. Due to time constraints, we were not able to successfully adapt our system to use this pREC-YFP reporter in our target strain. In previous iGEM years, there has already been a pREC-LacZ Biobricked constructed (Heidelberg 2012). In principle, our system couldbe completed, as a functional pREC-LacZ already exists. By adding the reporter of Heidelberg 2012 to our target strain with the Cas9, we should be able to get a functional sensor. This sensor can detect and report a specific DNA sequence due to a phagemid delivered gRNA that guides the present Cas9 to a target where the Cas9 generates a double strand break, which is reported by pREC-LacZ.<br />
</div></p><br />
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<div style="clear: both;"></div><br />
<br><br />
<h3>Next steps</h3><br />
<div class="left paragraph"><br />
As previously mentioned, the reporter didn’t work as expected. This can have several reasons. As our other positive control (beside MG1655), the MMC induced strains carrying the reporter didn’t show any expression, it stands to reason that the reporter itself is not functional. Another reason could be, that the phagemid didn’t deliver the gRNA or not in enough amounts to show an effect of the complete working system.<br />
</div></p><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
To test, if the phagemid delivers the gRNA correctly, we will perform another killing assay as we have done it before with the difference that the gRNA is delivered by the phagemid. The strains are then plated to see, if there is a reduced number of colonies of the target strain with phagemid in comparison to a control strain and without added phages. We expect the results before the end of iGEM.<br />
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<br />
<h2>Literature</h2><br />
<div class="leftparagraph"><br />
<ul><br />
<li>James E. DiCarlo, Julie E. Norville, Prashant Mali, Xavier Rios, John Aach and George M. Church (2013).<i> Genome engineering in Saccharomyces cerevisiae using CRISPR-Cas systems.</i> Nucleic Acids Research. 2013, 1–8.</li><br />
<li id="">Antonio R. Fernandez de Henestrosa, Tomoo Ogi, Sayura Aoyagi, David Chafin, Jeffrey J. Hayes, Haruo Ohmori and Roger Woodgate (2000). <i>Identification of additional genes belonging to the LexA regulon in Escherichia coli.</i> Molecular Microbiology .2000 35(6), 1560-1572.</li><br />
<li id="">Higashitani N., Higashitani I.A., Roth A., Horiuchi A.K. (1992). <i>SOS Induction in Escherichia coli by Infection with Mutant Filamentous Phage That Are Defective in Initiation of Complementary-Strand DNA Synthesis.</i> Journal of Bacteriology. 174:1612-1618.</li><br />
<li id="">Wenyan Jiang, David Bikard, David Cox, Feng Zhang & Luciano A Marraffini (2013). <i>RNA-guided editing of bacterial genomes using CRISPR-Cas systems.</i> Nature Biotechnology. 31 (3), 233-2398.</li><br />
<li id="">Douglas H. Juers, Brian W. Matthews, and Reuben E. Huber (2012). <i>LacZ b-galactosidase: Structure and function of an enzyme of historical and molecular biological importance.</i> Protein Science. 2012, 21,1792—1807.</li><br />
<li id="">Karlsson F., Malmborg-Hager A.C., Albrekt A.S., Borrebaeck C.A.K. (2005). <i>Genome-wide comparison of phage M13-infected vs. uninfected Escherichia coli. </i> Can. J. Microbiol. 51:29-35.</li><br />
</ul><br />
</div><br />
<div class="rightparagraph"><br />
<ul><br />
<br />
<li id="">Kimberly L. Keller, Terri L. Overbeck-Carrick, Doris J. Beck (2001). <i>Survival and induction of SOS in Escherichia coli treated with cisplatin, UV irradiation, or mitomycin C are dependent on the function of the RecBC and RecFOR pathways of homologous recombination. </i> Mutation Research. 486, 2001, 21–29.</li><br />
<li id="">Kobayashi, Ichizo; and Handa, Naofumi (2009). <i>DNA Doublestrand Breaks and Their Consequences in Bacteria. </i> Encyclopedia of Life Sciences (ELS). John Wiley & Sons, Ltd: Chichester.</li><br />
<li id=""> Timothy K. Lu, Jayson Bowers, and Michael S. Koeris (2013). <i> Advancing bacteriophage-based microbial diagnostics with synthetic biology. </i>Trends in Biotechnology. April 2013, 31 (6), 325-227.</li><br />
<li id="">Anders Norman, Lars Hestbjerg Hansen, and Søren J. Sørensen (2004). <i>Construction of a ColD cda Promoter-Based SOS-Green Fluorescent Protein Whole-Cell Biosensor with Higher Sensitivity toward Genotoxic Compounds than Constructs Based on recA, umuDC, or sulA Promoters. </i> APPLIED AND ENVIRONMENTAL MICROBIOLOGY. May 2005, p. 2338–2346.</li> <br />
<li id="">Sommer S., Leitao A., Bernardi A., Bailone A., Devoret R. (1991). <i>Introduction of a UV-damaged replicon into a recipient cell is not a sufficient condition to produce an SOS-inducing signal.</i> Mutation Research/DNA Repair. 254:107-17.</li><br />
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<h2>Attributions</h2> <br />
<br />
<p> Most of the strains and plasmids used for this project were kindly provided by the INSERM U1001 lab.</p><br />
<p> The Cas9 plasmid as well as the CRISPR plasmid were ordered from Addgene. The crRNA was designed after consultation with David Bikard.</p><br />
<p> The sequence of LacZ used in this project was taken from pBAC-BA-lacZ from Addgene. The corresponding pREC sequence is the natural sequence. The source for the sequence is EcoCyc.</p><br />
<p> The phaegmid template as well as the helper plasmid were provided by Monica Ortiz from the Endy Lab, Stanford.</p><br />
<p> The project itself was designed and accomplished by Nicolas Koutsoubelis, Anne Loechner and Marguerite Benony with consultation with Edwin Wintermute, Stanislas and Ariel Lindner.</p><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Project/DetectTeam:Paris Bettencourt/Project/Detect2013-10-28T23:53:18Z<p>Marguerite: </p>
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<div class="bkgr"><br />
<h2>Background</h2><br />
<p>CRISPR/Cas systems generate site-specific double-strand breaks and have recently been used for genome editing. </p><br />
</div><br />
<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>Successfully cloned gRNA anti-KAN, crRNA anti-KAN, tracrRNA-Cas9 and pRecA-LacZ into Biobrick backbones and therefore generated four new BioBricks. </li><br />
<li> Confirmation of site-specific binding and DNA double-strand breaks generated by the gRNA-Cas9 complex in the kanamycin resistance casette. </li><br />
<li><a href="https://2013.igem.org/Team:Paris_Bettencourt/Assembly_Standard">Testing the new assembly standard for our cloning.</a></li><br />
</ul><br />
<p></p><br />
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<h2>BioBricks</h2><br />
<ol><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137012">BBa_K1137012</br>(gRNA anti-KAN)</a></li><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137013">BBa_K1137013</br>(crRNA anti-KAN)</a></li> <br />
<li><a href="http://parts.igem.org/Part:BBa_K1137014">BBa_K1137014</br>(tracrRNA-Cas9)</a></li><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137015">BBa_K1137015</br>(pRecA-LacZ)</a></li><br />
</ol><br />
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<div class="aims"><br />
<h2>Aims</h2><br />
<p>Building a genotype sensor based on CRISPR/Cas that reports on the existence of an antibiotic resistance gene.</p><br />
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<a href="#Aim"><br />
<div class="hlink"><br />
<h2>Skip to Aim</h2><br />
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</a><br />
<a href="#Design"><br />
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<h2>Skip to Design</h2><br />
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</a><br />
<a href="#Background"><br />
<div class="hlink"><br />
<h2>Skip to Background</h2><br />
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</a><br />
<a href="#Results"> <br />
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<h2>Skip to Results</h2><br />
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<div id="Aim"></div><br />
<h2>Aim</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
We developed a sensor to detect whether a particular bacterial strain carries a specific antibiotic resistance gene. Our sensor system consists of <i>E.coli </i> lab strain and of a synthetic phagemid with a CRISPR/Cas system and LacZ as a reporter under the control of a pRecA promoter (SOS response promoter). <br /> If our CRISPR/Cas system can bind to the target (antibiotic resistance gene), the Cas9 generates at this specific target site a double strand break, which will induce the expression of our double-strand break SOS sensor (Figure. 1). Having the system on a phagemid, the sensor system will spread all over a population, to get a clear color output if the target has been detected. Depending on target sequence the system carries, we can identify different antibiotic resistances in a strain. This is a novel approach of detecting genes in bacterial strains. We used <i>E.coli</i> and a M13 phagemid to target the kanamycin resistance gene. <br /> This sensor is a proof of concept for a similar system in <i>Mycobacterium tuberculosis</i>. Such a system could potentially be used to test if a patient has TB and what type of resistance genes the specific strain contains to adapt the patient’s drug treatment.<br />
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<div class="rightparagraph"><br />
<center> <img width="110%" src="https://static.igem.org/mediawiki/2013/2/2d/PB_13_TB_Sensor_Detect_Overview.png"/><br></center><br />
<p><b>Figure 1:</b> Detection and reporting of an antibiotic resistance gene with a CRISPR/Cas system. <div style="font-size:90%">After expression of the Cas9 and gRNA, the gRNA guides the Cas9 to the target sequence, the kanamycin resistance. There, the Cas9 generates a double strand break. This activates the SOS response. The reporter LacZ is under the pRECA promoter, which gets activated during the SOS response and we get a blue cell, if the resistance gene has successfully been detected. </div></p><br />
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<br />
<div id="Motivation"></div><br />
<h2>Motivation and existing TB sensors/tests</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Tuberculosis (TB) remains a major global health problem. While the treatment of this disease in countries with adequate medical care is fairly easy to detect and treat, it remains hard to treat and diagnose in poorer countries. <br><br />
Up to now, a high quality lab that uses modern diagnostics is a prerequisite for early, rapid and accurate detection of TB. Therefore, diagnosis of TB and drug resistant TB remains a particular challenge for laboratory systems, especially in developing countries.<br><br />
The lack of cheap, quick and accurate tests make it hard to control the Tuberculosis epidemic, which claims millions of lives every year in developing countries.<br><br />
Setting up a cheap, fast and culture-based method could therefore decrease diagnostic time and facilitate patient treatment.<br><br />
The most common method for diagnosing TB nowadays is sputum smear microscopy, in which bacteria are observed in sputum samples of patients under the microscope. However, this cannot be used to identify paucibacillary (containing just a few bacteria) or extrapulmonary (outside of the lungs) TB.<br />
</p><br />
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<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
Diagnosis methods using culture methods require laboratory infrastructure that is not widely available in countries with a high burden of TB and results are only available after a few weeks.<br />
Other conventional methods used to diagnose multidrug-resistant TB (MDR-TB) also rely on the culturing of specimens followed by drug susceptibility testing (DST). Results take weeks to obtain and not all laboratories have the capacity to perform DST of first-line or of second-line drugs.<br><br />
MTB/RIF is a new rapid molecular test that can diagnose TB and rifampicin-resistant TB within hours. Molecular tests, such as GeneXpert, unlike culture-based methods, are fast, accurate and can detect drug-resistant strains. But the high costs and need for laboratories make access an issue for developing countries.<br><br />
The new method, published in the Journal of Applied Microbiology, uses a microcalorimeter to detect heat produced by Mycobacterium tuberculosis, the bacterium that causes TB, on a growth medium. The study showed that detection takes 4–5 days but more sensitive microcalorimeters could detect tuberculosis in 24 hours.<br />
</p><br />
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<br />
<div id="Design"></div><br />
<h2>System Design</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
By taking advantage of the state of the art CRISPR/Cas research and combining it with phage diagnostics, we designed a sensor that is able to screen for a specific target gene. Our producer strain carries a helper plasmid that codes for the phage capsid proteins of M13 as well as our phagemid plasmid with our sensor system. Our sensor system consists out of three parts: the Cas9 gene under a constitutive promoter, the anti-KAN gRNA also under a constitutive promoter and the reporter element LacZ under the control of the pRecA promoter. As the helper plasmid doesn’t have a packaging sequence, only our sensor system phagemid is packed into the M13 capsids. As M13 is a lysogenic phage, the phagemid particles are exported into the media where they can be easily isolated and are ready to use to sense if an other strain contains our target sequence. <br />
</p><br />
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<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
As the phagemid is derived from M13, it infects only F+ (conjugated) cells. In our case, we conjugated our cells so that they can be easily infected. <p> Within the target strain, the Cas9 protein, as well as the gRNA get expressed. The gRNA then attaches to the Cas9 protein and guides the Cas9 to the target sequence (kanamycin resistance gene). Once bound to the sequence, the Cas9 protein generates a target specific double strand break. This double strand break leads to the cleavage of LexA. LexA is a protein bound to the pREC promoter that inhibits the expression of genes under the control of the pREC promoter. With the cleavage of LexA, the expression of our reporter LacZ is started, which leads in the presence of X-gal to a blue color output. <br />
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<center><img src="https://static.igem.org/mediawiki/2013/1/15/PB_Detect_Design_GIF-loop.gif" width="80%"/></center><br />
<div style="margin-left:10%"><p><b>Figure 2:Course of the detection and reporting of an antibiotic resistance gene with the CRISPR/Cas system. </b> <div style="font-size:90%">After the plasmid has been released into the target cells, gRNA and Cas9 get expressed. The gRNA guides the Cas9 to the target, where it generates a double strand break. This activates the SOS response. As a results, LexA is cleaved which allows the expression of the reporter. In the presence of X-gal the cells turn blue. </div></p></div><br />
<br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Our system is highly modular as with the simple change of the gRNA target sequence (20bp), any gene of interest can be identified and targeted. This means that our system can be used for different applications and purposes, as for example a mutation screening. It is also not specified only for <i>E.coli</i> and the phage M13. Our whole system can be easily transferred to other phage systems that target other host bacteria. In our case, as we want to develop a sensor to test <i>Mycobacterium tuberculosis</i>, we could in principle transfer our system to mycobacteria phages. With what we are presenting here, we have a proof of concept in <i>E.coli</i>. By using host specific phages, we can easy identify specific bacteria and genes they carry. By building a library of phages with different gRNAs we could screen for many different genes in parallel including other resistances or pathogenic genes.<br />
<br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
For future perspectives, we plan to further test and improve the system so that in theory, we will generate a sensor that can be used without using high-tech laboratory facilities. This is very important, as easily to use sensors are needed in the developing countries in which tuberculosis is still a prevalent disease.<p><br />
In a prospective design study we imagine the development of a handkerchief, in which our phagemid system can be integrated. By spitting on the tissue, we get a bacterial sample that will be tested by phages. Depending on which phagemid is integrated into the handkerchief, we can test for the <i>Mycobacterium tuberculosis</i> in general as well as for the different antibiotic resistances. A handkerchief is easy to use and the blue color output easy to read out. As phages are acting very fast, an easily usable and fast sensor system is developed.<br />
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<br><br />
<img src="https://static.igem.org/mediawiki/2013/2/25/PB_designscenario.png" width="1100"/><br />
<div style="margin-left:10%"><p><b>Figure 3:description here </div></p></div><br />
<br />
<div id="Background"></div><br />
<h2>Background</h2><br />
<h3>CRISPRs</h3><br />
<div class="leftparagraph"> <br />
<p>&nbsp;&nbsp;<br />
The mechanism we are using for our sensor is based on the CRISPR/Cas System. The CRISPR/Cas genome editing method, which recently became very popular, is derived from the bacterial “immune system”. CRISPRs are Clustered Regularly Interspaced Short Palindromic Repeats that are part of the bacterial genome. These loci contain multiple short repeats. In between the repeats are so called spacers that are sequences derived from extrachromosomal DNA, e.g. from invading viruses or plasmids (Figure 3). Within bacteria, those CRISPRs are naturally used to detect and destroy foreign DNA that is saved in the spacers.</p><br />
<p>In total the CRISPRs and the spacers form a so-called CRISPR array that is transcribed as one unit. CRISPR associated proteins (Cas proteins) are involved in further processing and action steps of the CRISPR system. There are many different regulation systems, here we describe the Cas9 system that will be used for our purposes (Figure 3).</p><br />
<p>The transcribed mRNA is processed into so called crRNA (CRISPR RNA), which includes the spacer sequence of foreign DNA. Together with a transactingCRISPR RNA (tracrRNA), the crRNA forms a duplex that is cleaved by RNaseII. The resulting hybrid serves as guide for the Cas9 protein that generates double strand breaks at the position the RNAs guide it to (Figure 3). By this double strand break the invading DNA is destroyed. The last years, researchers discovered the CRISPRs as a method for genome editing. </p><br />
<br><br><br><br><br><br />
<img src="https://static.igem.org/mediawiki/2013/4/43/PB_gRNA_%282%29.png" width="520"/><br />
<p><b>Figure 3:</b> CRISPR/Cas technology description (<a href="http://www.addgene.org/CRISPR/guide/" target="_blank">Addgene.org</a>).</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; By designing the spacer sequence, specific sequences in the genome can be targeted. With the provision of a sequence with homologous sequences, easy insertion can be done. This method can be used to insert mutations or new sequences nearly everywhere in the genome.<br><br />
Recently many papers have been published for genome editing in bacteria (Jinek et al., 2012, <a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Jiang2013" target="_blank">Jiang <i>et al</i>. 2013</a>), yeast (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#DiCarlo2013" target="_blank">DiCarlo <i>et al</i>. 2013</a>) and mammalian cells (Mali et al., 2013, Cong et al., 2013). They describe how to use the CRISPRs for different purposes. One requirement to target a sequence is a NGG at the end of the sequence. This NGG sequence is called PAM - protospacer adjacent motif, while the target sequence itself is called the protospacer, which should have a length of around 12 to 20 bp.</p><br />
<p>In our approach we test two different systems, the systems of DiCarlo et al. 2013 and Jiang et al. 2013. The system of Jiang is a system developed for bacteria and especially for <i>E.coli</i>. The system of DiCarlo is based on a paper of Mali et al. 2013 and adapted to yeast.</p><br />
<p>Different from the Jiang paper, the DiCarlo paper uses a gRNA (guideRNA) to guide the Cas9 (Figure 4). The gRNA is actually the RNA that results after transcribing and folding is the same complex as you get after the processing of the tracrRNA with the crRNA. It is hence an improvement, which makes the design and expression easier. But as the system hasn’t been tested before in bacteria, we will use both systems to make sure we get the desired results.</p><br />
<br><br />
<br><br />
<br><br />
<center><img src="https://static.igem.org/mediawiki/2013/6/64/PB_gRNA_%281%29.png" width="430"/></center><br />
<p><b>Figure 4:</b>Cas9 protein interacting with CRISPR gRNA<div style="font-size:90%">Illustration of Cas9 protein interacting with CRISPR gRNA to direct endonuclease activity proximal to the PAM sequence (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#DiCarlo2013" target="_blank">DiCarlo et al. 2013</a>) </div></p><br />
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<br />
<h3>RecA promoter</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Our reporter system consists out of the RecA promoter and LacZ. Originally, the RecA promoter of <i>E.coli</i> has its main role in the activation of the SOS repair system. It is regulated by the LexA repressor, which binds to the SOS box sequence of the promoter. DNA damage leads to an inducing signal, which then activates the RecA protein. In the SOS response the LexA repressor is cleaved by the RecA protein, so the full RecA expression can be reached. The RecA protein can then repair both single stranded and double stranded DNA breaks.</p><br />
<p>In our project RecA promoters used to detect double stranded DNA breaks in the region of antibiotic resistance genes caused by the CIRSPR/Cas system. To get the desired activation of the promoter, it is important to assure that no other stressing agents might activate the RecA promoter. Those agents could be UV light, X-ray, ionizing radiation and different types of DNA breaking compounds. </p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
The SOS response in <i>E.coli</i> could also get induced by engineered M13 phage infection that are defective in the minus-strand origin, and so unable to form the double stranded replicative stage.</p><br />
<p>In this case the single-stranded DNA would be the SOS-inducing signal. The wild type M13 phage doesn’t induce the SOS response (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Higashitani1992" target="_blank">Higashitani <i>et al</i>. 1992</a>). In another study genomes of phage M13 infected and uninfected <i>E.coli</i> strains were compared by oligonucleotide microarrays, where no stress response genes were scored as upregulated (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Karlsson2005" target="_blank">Karlsson <i>et al</i>. 2005</a>). Regarding the phagemids, an A UV-damaged oriC phagemid did not induce SOS response in a recipient cells oriF phagemids on the other hand did (Sommer et al. 1991). To make sure that our system functions reliably, we will test the activation of the RecA promoter at different stress inputs (UV, phage infection,…) by measuring the fluorescence of YFP driven by the RecA promoter.</p><br />
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<br />
<div id="Results"></div><br />
<h2>Progress and preliminary Results</h2><br />
<h3>Parts</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp; Up to this point we cloned each of our parts into BioBrick vectors. We cloned the <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Monday_30th_September.html">gRNA anti-Kan </a> into pSB1C3 and pSB1A3.We used for this the assembly standard BioBrick cloning as well the new proposed <a href="https://2013.igem.org/Team:Paris_Bettencourt/Assembly_Standard">Assembly Standard.</a>. Both assemblies were successful and proved by colony PCR as well as by sequencing. We also used both standards for cloning the <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Monday_30th_September.html">crRNA.</a>. <br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
Also this is verified by colony PCR and by sequencing. For the cloning of the tracrRNA-CAS9 part we used standard BioBrick cloning, inserted into pSB1A3 and sequence verified it. We achieved the same for the pRecA-LacZ part (pSB1C3 and pSB1A3 backbones) that was submitted to the parts registry. <br><br />
</div><br />
<div style="clear: both;"></div><br />
<br><br />
<h3>Killing assay to verify targeting specificity</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp; For the characterization of the Cas9 and the gRNA anti-KAN we performed a <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Thursday_3rd_October.html">killing assay </a> . Therefore we co-transformed the Cas9 with gRNA anti-KAN into host bacteria that contain the KAN resistance gene cassette as well as without the cassette. In the KAN resistance bacteria, the CRISPR/Cas complex generated generate double strand breaks that killed the bacteria. After co-transforming the plasmids, we plated the bacteria on the one hand on the single antibiotic where the resistance is carried by the Cas9 plasmid as well as on the single antibiotic which resistance is present on the gRNA plasmid. As the two plasmids contain the same origin of replication, this will selesct for only the single plasmid and hence a non-functional CRISPR/Cas system. To get a working system, we plated the co-transformed bacteria on both antibiotics, of which the reistances were on the two plasmids. As we can see in Figure 5, if we select for both plasmids, we get a reduced number of colonies in the strain that contains the target sequence, the kanamycine resistance cassette. We attribute this reduced number to Cas9-induced cleavage of the chromosome specifically at the KanR casette, with about 99% efficiency. This leads after repeatedly double strand breaks generated by the CRISPR/Cas system to cell death which explaines the reduced colony number.<br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
<img src="https://static.igem.org/mediawiki/2013/0/01/PB_13_Results_detect_killing_assay.png" width="80%" style="margin-bottom:-80px;"/> <br />
<br><br />
<br><br />
<p><b>Figure 5: </b> CRISPR anti-Kan plasmids target specifically kanamycin resistant <i>E. coli</i>.<div style="font-size:90%"> We introduced our CRISPR-based DNA cleavage system to two strains of <i>E. coli</i>: one WT (blue bars) and one carrying a genomically integrated kanamycin resistance casette (KanR, blue bars). The strains were co-transformed with two plasmids. One with the Cas9 construct, the other with the anti-Kanamycin gRNA. WT <i>E. coli</i> could be efficiently transformed with one or both plasmids, as determined by selective plating. However, KanR <i>E. coli</i> could not be efficiently transformed with both. We attribute this to Cas9-induced cleavage of the chromosome specifically at the KanR casette, with about 99% efficiency.</div></p><br />
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<br />
<br><br />
<h3>Characterization of the reporter - under construction</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;To characterize the pRecA –LacZ construct, we induced double strand breaks with Mytomycin C (MMC) and analyzed the resulting LacZ expression levels with the Miller assay. The same time, we wanted to characterize our final system: our target strain with the kanamycin resistance gene that also carries the reporter and the Cas9. The gRNA is delivered by a phage. As positive control, we used MG1655, which has a constitutive expression of LacZ, as negative control the parental strain of the target strain, which doesn’t have a kanamycin resistance cassette but also has the reporter and Cas9.<br />
As it can be seen in Figure 6, we didn’t get any expression of LacZ beside in the positive control, the MG1655 strain. As we worry, that our reporter might be not functional, we started to characterize a reporter constructed by Ariel Lindner. This reporter is YFP under the control of pREC. We analyzed its expression rates by inducing double strand breaks with Mitomycin C and Niprofloxacin. The data generated by FACS analysis over time can be seen in Figure 7. We can clearly see an induction of the pREC promoter due to induction with MMC and Niprofloxacin. Due to time constraints, we were not able to successfully adapt our system to use this pREC-YFP reporter in our target strain. In previous iGEM years, there has already been a pREC-LacZ Biobricked constructed (Heidelberg 2012). In principle, our system couldbe completed, as a functional pREC-LacZ already exists. By adding the reporter of Heidelberg 2012 to our target strain with the Cas9, we should be able to get a functional sensor. This sensor can detect and report a specific DNA sequence due to a phagemid delivered gRNA that guides the present Cas9 to a target where the Cas9 generates a double strand break, which is reported by pREC-LacZ.<br />
</div></p><br />
</div><br />
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<br><br />
<h3>Next steps</h3><br />
<div class="left paragraph"><br />
As previously mentioned, the reporter didn’t work as expected. This can have several reasons. As our other positive control (beside MG1655), the MMC induced strains carrying the reporter didn’t show any expression, it stands to reason that the reporter itself is not functional. Another reason could be, that the phagemid didn’t deliver the gRNA or not in enough amounts to show an effect of the complete working system.<br />
</div></p><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
To test, if the phagemid delivers the gRNA correctly, we will perform another killing assay as we have done it before with the difference that the gRNA is delivered by the phagemid. The strains are then plated to see, if there is a reduced number of colonies of the target strain with phagemid in comparison to a control strain and without added phages. We expect the results before the end of iGEM.<br />
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<br />
<h2>Literature</h2><br />
<div class="leftparagraph"><br />
<ul><br />
<li>James E. DiCarlo, Julie E. Norville, Prashant Mali, Xavier Rios, John Aach and George M. Church (2013).<i> Genome engineering in Saccharomyces cerevisiae using CRISPR-Cas systems.</i> Nucleic Acids Research. 2013, 1–8.</li><br />
<li id="">Antonio R. Fernandez de Henestrosa, Tomoo Ogi, Sayura Aoyagi, David Chafin, Jeffrey J. Hayes, Haruo Ohmori and Roger Woodgate (2000). <i>Identification of additional genes belonging to the LexA regulon in Escherichia coli.</i> Molecular Microbiology .2000 35(6), 1560-1572.</li><br />
<li id="">Higashitani N., Higashitani I.A., Roth A., Horiuchi A.K. (1992). <i>SOS Induction in Escherichia coli by Infection with Mutant Filamentous Phage That Are Defective in Initiation of Complementary-Strand DNA Synthesis.</i> Journal of Bacteriology. 174:1612-1618.</li><br />
<li id="">Wenyan Jiang, David Bikard, David Cox, Feng Zhang & Luciano A Marraffini (2013). <i>RNA-guided editing of bacterial genomes using CRISPR-Cas systems.</i> Nature Biotechnology. 31 (3), 233-2398.</li><br />
<li id="">Douglas H. Juers, Brian W. Matthews, and Reuben E. Huber (2012). <i>LacZ b-galactosidase: Structure and function of an enzyme of historical and molecular biological importance.</i> Protein Science. 2012, 21,1792—1807.</li><br />
<li id="">Karlsson F., Malmborg-Hager A.C., Albrekt A.S., Borrebaeck C.A.K. (2005). <i>Genome-wide comparison of phage M13-infected vs. uninfected Escherichia coli. </i> Can. J. Microbiol. 51:29-35.</li><br />
</ul><br />
</div><br />
<div class="rightparagraph"><br />
<ul><br />
<br />
<li id="">Kimberly L. Keller, Terri L. Overbeck-Carrick, Doris J. Beck (2001). <i>Survival and induction of SOS in Escherichia coli treated with cisplatin, UV irradiation, or mitomycin C are dependent on the function of the RecBC and RecFOR pathways of homologous recombination. </i> Mutation Research. 486, 2001, 21–29.</li><br />
<li id="">Kobayashi, Ichizo; and Handa, Naofumi (2009). <i>DNA Doublestrand Breaks and Their Consequences in Bacteria. </i> Encyclopedia of Life Sciences (ELS). John Wiley & Sons, Ltd: Chichester.</li><br />
<li id=""> Timothy K. Lu, Jayson Bowers, and Michael S. Koeris (2013). <i> Advancing bacteriophage-based microbial diagnostics with synthetic biology. </i>Trends in Biotechnology. April 2013, 31 (6), 325-227.</li><br />
<li id="">Anders Norman, Lars Hestbjerg Hansen, and Søren J. Sørensen (2004). <i>Construction of a ColD cda Promoter-Based SOS-Green Fluorescent Protein Whole-Cell Biosensor with Higher Sensitivity toward Genotoxic Compounds than Constructs Based on recA, umuDC, or sulA Promoters. </i> APPLIED AND ENVIRONMENTAL MICROBIOLOGY. May 2005, p. 2338–2346.</li> <br />
<li id="">Sommer S., Leitao A., Bernardi A., Bailone A., Devoret R. (1991). <i>Introduction of a UV-damaged replicon into a recipient cell is not a sufficient condition to produce an SOS-inducing signal.</i> Mutation Research/DNA Repair. 254:107-17.</li><br />
</ul><br />
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<br />
<h2>Attributions</h2> <br />
<br />
<p> Most of the strains and plasmids used for this project were kindly provided by the INSERM U1001 lab.</p><br />
<p> The Cas9 plasmid as well as the CRISPR plasmid were ordered from Addgene. The crRNA was designed after consultation with David Bikard.</p><br />
<p> The sequence of LacZ used in this project was taken from pBAC-BA-lacZ from Addgene. The corresponding pREC sequence is the natural sequence. The source for the sequence is EcoCyc.</p><br />
<p> The phaegmid template as well as the helper plasmid were provided by Monica Ortiz from the Endy Lab, Stanford.</p><br />
<p> The project itself was designed and accomplished by Nicolas Koutsoubelis, Anne Loechner and Marguerite Benony with consultation with Edwin Wintermute, Stanislas and Ariel Lindner.</p><br />
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{{:Team:Paris_Bettencourt/footer}}</div>Margueritehttp://2013.igem.org/Team:Paris_Bettencourt/Project/DetectTeam:Paris Bettencourt/Project/Detect2013-10-28T23:51:00Z<p>Marguerite: </p>
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<div class="bkgr"><br />
<h2>Background</h2><br />
<p>CRISPR/Cas systems generate site-specific double-strand breaks and have recently been used for genome editing. </p><br />
</div><br />
<div class="results"><br />
<h2>Results</h2><br />
<ul><br />
<li>Successfully cloned gRNA anti-KAN, crRNA anti-KAN, tracrRNA-Cas9 and pRecA-LacZ into Biobrick backbones and therefore generated four new BioBricks. </li><br />
<li> Confirmation of site-specific binding and DNA double-strand breaks generated by the gRNA-Cas9 complex in the kanamycin resistance casette. </li><br />
<li><a href="https://2013.igem.org/Team:Paris_Bettencourt/Assembly_Standard">Testing the new assembly standard for our cloning.</a></li><br />
</ul><br />
<p></p><br />
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<div class="biocriks"><br />
<h2>BioBricks</h2><br />
<ol><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137012">BBa_K1137012</br>(gRNA anti-KAN)</a></li><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137013">BBa_K1137013</br>(crRNA anti-KAN)</a></li> <br />
<li><a href="http://parts.igem.org/Part:BBa_K1137014">BBa_K1137014</br>(tracrRNA-Cas9)</a></li><br />
<li><a href="http://parts.igem.org/Part:BBa_K1137015">BBa_K1137015</br>(pRecA-LacZ)</a></li><br />
</ol><br />
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<div class="aims"><br />
<h2>Aims</h2><br />
<p>Building a genotype sensor based on CRISPR/Cas that reports on the existence of an antibiotic resistance gene.</p><br />
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<a href="#Aim"><br />
<div class="hlink"><br />
<h2>Skip to Aim</h2><br />
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</a><br />
<a href="#Design"><br />
<div class="hlink"><br />
<h2>Skip to Design</h2><br />
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</a><br />
<a href="#Background"><br />
<div class="hlink"><br />
<h2>Skip to Background</h2><br />
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</a><br />
<a href="#Results"> <br />
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<h2>Skip to Results</h2><br />
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<br />
<div id="Aim"></div><br />
<h2>Aim</h2><br />
<div class="leftparagraph"><br />
<p> &nbsp;&nbsp;<br />
We developed a sensor to detect whether a particular bacterial strain carries a specific antibiotic resistance gene. Our sensor system consists of <i>E.coli </i> lab strain and of a synthetic phagemid with a CRISPR/Cas system and LacZ as a reporter under the control of a pRecA promoter (SOS response promoter). <br /> If our CRISPR/Cas system can bind to the target (antibiotic resistance gene), the Cas9 generates at this specific target site a double strand break, which will induce the expression of our double-strand break SOS sensor (Figure. 1). Having the system on a phagemid, the sensor system will spread all over a population, to get a clear color output if the target has been detected. Depending on target sequence the system carries, we can identify different antibiotic resistances in a strain. This is a novel approach of detecting genes in bacterial strains. We used <i>E.coli</i> and a M13 phagemid to target the kanamycin resistance gene. <br /> This sensor is a proof of concept for a similar system in <i>Mycobacterium tuberculosis</i>. Such a system could potentially be used to test if a patient has TB and what type of resistance genes the specific strain contains to adapt the patient’s drug treatment.<br />
</div><br />
<div class="rightparagraph"><br />
<center> <img width="110%" src="https://static.igem.org/mediawiki/2013/2/2d/PB_13_TB_Sensor_Detect_Overview.png"/><br></center><br />
<p><b>Figure 1:</b> Detection and reporting of an antibiotic resistance gene with a CRISPR/Cas system. <div style="font-size:90%">After expression of the Cas9 and gRNA, the gRNA guides the Cas9 to the target sequence, the kanamycin resistance. There, the Cas9 generates a double strand break. This activates the SOS response. The reporter LacZ is under the pRECA promoter, which gets activated during the SOS response and we get a blue cell, if the resistance gene has successfully been detected. </div></p><br />
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<br />
<div id="Motivation"></div><br />
<h2>Motivation and existing TB sensors/tests</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Tuberculosis (TB) remains a major global health problem. While the treatment of this disease in countries with adequate medical care is fairly easy to detect and treat, it remains hard to treat and diagnose in poorer countries. <br><br />
Up to now, a high quality lab that uses modern diagnostics is a prerequisite for early, rapid and accurate detection of TB. Therefore, diagnosis of TB and drug resistant TB remains a particular challenge for laboratory systems, especially in developing countries.<br><br />
The lack of cheap, quick and accurate tests make it hard to control the Tuberculosis epidemic, which claims millions of lives every year in developing countries.<br><br />
Setting up a cheap, fast and culture-based method could therefore decrease diagnostic time and facilitate patient treatment.<br><br />
The most common method for diagnosing TB nowadays is sputum smear microscopy, in which bacteria are observed in sputum samples of patients under the microscope. However, this cannot be used to identify paucibacillary (containing just a few bacteria) or extrapulmonary (outside of the lungs) TB.<br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
Diagnosis methods using culture methods require laboratory infrastructure that is not widely available in countries with a high burden of TB and results are only available after a few weeks.<br />
Other conventional methods used to diagnose multidrug-resistant TB (MDR-TB) also rely on the culturing of specimens followed by drug susceptibility testing (DST). Results take weeks to obtain and not all laboratories have the capacity to perform DST of first-line or of second-line drugs.<br><br />
MTB/RIF is a new rapid molecular test that can diagnose TB and rifampicin-resistant TB within hours. Molecular tests, such as GeneXpert, unlike culture-based methods, are fast, accurate and can detect drug-resistant strains. But the high costs and need for laboratories make access an issue for developing countries.<br><br />
The new method, published in the Journal of Applied Microbiology, uses a microcalorimeter to detect heat produced by Mycobacterium tuberculosis, the bacterium that causes TB, on a growth medium. The study showed that detection takes 4–5 days but more sensitive microcalorimeters could detect tuberculosis in 24 hours.<br />
</p><br />
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<br />
<div id="Design"></div><br />
<h2>System Design</h2><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
By taking advantage of the state of the art CRISPR/Cas research and combining it with phage diagnostics, we designed a sensor that is able to screen for a specific target gene. Our producer strain carries a helper plasmid that codes for the phage capsid proteins of M13 as well as our phagemid plasmid with our sensor system. Our sensor system consists out of three parts: the Cas9 gene under a constitutive promoter, the anti-KAN gRNA also under a constitutive promoter and the reporter element LacZ under the control of the pRecA promoter. As the helper plasmid doesn’t have a packaging sequence, only our sensor system phagemid is packed into the M13 capsids. As M13 is a lysogenic phage, the phagemid particles are exported into the media where they can be easily isolated and are ready to use to sense if an other strain contains our target sequence. <br />
</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
As the phagemid is derived from M13, it infects only F+ (conjugated) cells. In our case, we conjugated our cells so that they can be easily infected. <p> Within the target strain, the Cas9 protein, as well as the gRNA get expressed. The gRNA then attaches to the Cas9 protein and guides the Cas9 to the target sequence (kanamycin resistance gene). Once bound to the sequence, the Cas9 protein generates a target specific double strand break. This double strand break leads to the cleavage of LexA. LexA is a protein bound to the pREC promoter that inhibits the expression of genes under the control of the pREC promoter. With the cleavage of LexA, the expression of our reporter LacZ is started, which leads in the presence of X-gal to a blue color output. <br />
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<center><img src="https://static.igem.org/mediawiki/2013/1/15/PB_Detect_Design_GIF-loop.gif" width="80%"/></center><br />
<div style="margin-left:10%"><p><b>Figure 2:Course of the detection and reporting of an antibiotic resistance gene with the CRISPR/Cas system. </b> <div style="font-size:90%">After the plasmid has been released into the target cells, gRNA and Cas9 get expressed. The gRNA guides the Cas9 to the target, where it generates a double strand break. This activates the SOS response. As a results, LexA is cleaved which allows the expression of the reporter. In the presence of X-gal the cells turn blue. </div></p></div><br />
<br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Our system is highly modular as with the simple change of the gRNA target sequence (20bp), any gene of interest can be identified and targeted. This means that our system can be used for different applications and purposes, as for example a mutation screening. It is also not specified only for <i>E.coli</i> and the phage M13. Our whole system can be easily transferred to other phage systems that target other host bacteria. In our case, as we want to develop a sensor to test <i>Mycobacterium tuberculosis</i>, we could in principle transfer our system to mycobacteria phages. With what we are presenting here, we have a proof of concept in <i>E.coli</i>. By using host specific phages, we can easy identify specific bacteria and genes they carry. By building a library of phages with different gRNAs we could screen for many different genes in parallel including other resistances or pathogenic genes.<br />
<br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
For future perspectives, we plan to further test and improve the system so that in theory, we will generate a sensor that can be used without using high-tech laboratory facilities. This is very important, as easily to use sensors are needed in the developing countries in which tuberculosis is still a prevalent disease.<p><br />
In a prospective design study we imagine the development of a handkerchief, in which our phagemid system can be integrated. By spitting on the tissue, we get a bacterial sample that will be tested by phages. Depending on which phagemid is integrated into the handkerchief, we can test for the <i>Mycobacterium tuberculosis</i> in general as well as for the different antibiotic resistances. A handkerchief is easy to use and the blue color output easy to read out. As phages are acting very fast, an easily usable and fast sensor system is developed.<br />
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<br><br />
<img src="https://static.igem.org/mediawiki/2013/2/25/PB_designscenario.png" width="1100"/><br />
<br />
<div id="Background"></div><br />
<h2>Background</h2><br />
<h3>CRISPRs</h3><br />
<div class="leftparagraph"> <br />
<p>&nbsp;&nbsp;<br />
The mechanism we are using for our sensor is based on the CRISPR/Cas System. The CRISPR/Cas genome editing method, which recently became very popular, is derived from the bacterial “immune system”. CRISPRs are Clustered Regularly Interspaced Short Palindromic Repeats that are part of the bacterial genome. These loci contain multiple short repeats. In between the repeats are so called spacers that are sequences derived from extrachromosomal DNA, e.g. from invading viruses or plasmids (Figure 3). Within bacteria, those CRISPRs are naturally used to detect and destroy foreign DNA that is saved in the spacers.</p><br />
<p>In total the CRISPRs and the spacers form a so-called CRISPR array that is transcribed as one unit. CRISPR associated proteins (Cas proteins) are involved in further processing and action steps of the CRISPR system. There are many different regulation systems, here we describe the Cas9 system that will be used for our purposes (Figure 3).</p><br />
<p>The transcribed mRNA is processed into so called crRNA (CRISPR RNA), which includes the spacer sequence of foreign DNA. Together with a transactingCRISPR RNA (tracrRNA), the crRNA forms a duplex that is cleaved by RNaseII. The resulting hybrid serves as guide for the Cas9 protein that generates double strand breaks at the position the RNAs guide it to (Figure 3). By this double strand break the invading DNA is destroyed. The last years, researchers discovered the CRISPRs as a method for genome editing. </p><br />
<br><br><br><br><br><br />
<img src="https://static.igem.org/mediawiki/2013/4/43/PB_gRNA_%282%29.png" width="520"/><br />
<p><b>Figure 3:</b> CRISPR/Cas technology description (<a href="http://www.addgene.org/CRISPR/guide/" target="_blank">Addgene.org</a>).</p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; By designing the spacer sequence, specific sequences in the genome can be targeted. With the provision of a sequence with homologous sequences, easy insertion can be done. This method can be used to insert mutations or new sequences nearly everywhere in the genome.<br><br />
Recently many papers have been published for genome editing in bacteria (Jinek et al., 2012, <a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Jiang2013" target="_blank">Jiang <i>et al</i>. 2013</a>), yeast (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#DiCarlo2013" target="_blank">DiCarlo <i>et al</i>. 2013</a>) and mammalian cells (Mali et al., 2013, Cong et al., 2013). They describe how to use the CRISPRs for different purposes. One requirement to target a sequence is a NGG at the end of the sequence. This NGG sequence is called PAM - protospacer adjacent motif, while the target sequence itself is called the protospacer, which should have a length of around 12 to 20 bp.</p><br />
<p>In our approach we test two different systems, the systems of DiCarlo et al. 2013 and Jiang et al. 2013. The system of Jiang is a system developed for bacteria and especially for <i>E.coli</i>. The system of DiCarlo is based on a paper of Mali et al. 2013 and adapted to yeast.</p><br />
<p>Different from the Jiang paper, the DiCarlo paper uses a gRNA (guideRNA) to guide the Cas9 (Figure 4). The gRNA is actually the RNA that results after transcribing and folding is the same complex as you get after the processing of the tracrRNA with the crRNA. It is hence an improvement, which makes the design and expression easier. But as the system hasn’t been tested before in bacteria, we will use both systems to make sure we get the desired results.</p><br />
<br><br />
<br><br />
<br><br />
<center><img src="https://static.igem.org/mediawiki/2013/6/64/PB_gRNA_%281%29.png" width="430"/></center><br />
<p><b>Figure 4:</b>Cas9 protein interacting with CRISPR gRNA<div style="font-size:90%">Illustration of Cas9 protein interacting with CRISPR gRNA to direct endonuclease activity proximal to the PAM sequence (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#DiCarlo2013" target="_blank">DiCarlo et al. 2013</a>) </div></p><br />
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<br />
<h3>RecA promoter</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;<br />
Our reporter system consists out of the RecA promoter and LacZ. Originally, the RecA promoter of <i>E.coli</i> has its main role in the activation of the SOS repair system. It is regulated by the LexA repressor, which binds to the SOS box sequence of the promoter. DNA damage leads to an inducing signal, which then activates the RecA protein. In the SOS response the LexA repressor is cleaved by the RecA protein, so the full RecA expression can be reached. The RecA protein can then repair both single stranded and double stranded DNA breaks.</p><br />
<p>In our project RecA promoters used to detect double stranded DNA breaks in the region of antibiotic resistance genes caused by the CIRSPR/Cas system. To get the desired activation of the promoter, it is important to assure that no other stressing agents might activate the RecA promoter. Those agents could be UV light, X-ray, ionizing radiation and different types of DNA breaking compounds. </p><br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp;<br />
The SOS response in <i>E.coli</i> could also get induced by engineered M13 phage infection that are defective in the minus-strand origin, and so unable to form the double stranded replicative stage.</p><br />
<p>In this case the single-stranded DNA would be the SOS-inducing signal. The wild type M13 phage doesn’t induce the SOS response (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Higashitani1992" target="_blank">Higashitani <i>et al</i>. 1992</a>). In another study genomes of phage M13 infected and uninfected <i>E.coli</i> strains were compared by oligonucleotide microarrays, where no stress response genes were scored as upregulated (<a href="https://2013.igem.org/Team:Paris_Bettencourt/Bibliography#Karlsson2005" target="_blank">Karlsson <i>et al</i>. 2005</a>). Regarding the phagemids, an A UV-damaged oriC phagemid did not induce SOS response in a recipient cells oriF phagemids on the other hand did (Sommer et al. 1991). To make sure that our system functions reliably, we will test the activation of the RecA promoter at different stress inputs (UV, phage infection,…) by measuring the fluorescence of YFP driven by the RecA promoter.</p><br />
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<br />
<div id="Results"></div><br />
<h2>Progress and preliminary Results</h2><br />
<h3>Parts</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp; Up to this point we cloned each of our parts into BioBrick vectors. We cloned the <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Monday_30th_September.html">gRNA anti-Kan </a> into pSB1C3 and pSB1A3.We used for this the assembly standard BioBrick cloning as well the new proposed <a href="https://2013.igem.org/Team:Paris_Bettencourt/Assembly_Standard">Assembly Standard.</a>. Both assemblies were successful and proved by colony PCR as well as by sequencing. We also used both standards for cloning the <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Monday_30th_September.html">crRNA.</a>. <br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
Also this is verified by colony PCR and by sequencing. For the cloning of the tracrRNA-CAS9 part we used standard BioBrick cloning, inserted into pSB1A3 and sequence verified it. We achieved the same for the pRecA-LacZ part (pSB1C3 and pSB1A3 backbones) that was submitted to the parts registry. <br><br />
</div><br />
<div style="clear: both;"></div><br />
<br><br />
<h3>Killing assay to verify targeting specificity</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp; For the characterization of the Cas9 and the gRNA anti-KAN we performed a <a href="https://2013.igem.org/Team:Paris_Bettencourt/Notebook/Phage_Sensor/Thursday_3rd_October.html">killing assay </a> . Therefore we co-transformed the Cas9 with gRNA anti-KAN into host bacteria that contain the KAN resistance gene cassette as well as without the cassette. In the KAN resistance bacteria, the CRISPR/Cas complex generated generate double strand breaks that killed the bacteria. After co-transforming the plasmids, we plated the bacteria on the one hand on the single antibiotic where the resistance is carried by the Cas9 plasmid as well as on the single antibiotic which resistance is present on the gRNA plasmid. As the two plasmids contain the same origin of replication, this will selesct for only the single plasmid and hence a non-functional CRISPR/Cas system. To get a working system, we plated the co-transformed bacteria on both antibiotics, of which the reistances were on the two plasmids. As we can see in Figure 5, if we select for both plasmids, we get a reduced number of colonies in the strain that contains the target sequence, the kanamycine resistance cassette. We attribute this reduced number to Cas9-induced cleavage of the chromosome specifically at the KanR casette, with about 99% efficiency. This leads after repeatedly double strand breaks generated by the CRISPR/Cas system to cell death which explaines the reduced colony number.<br />
</div><br />
<div class="rightparagraph"><br />
<p>&nbsp;&nbsp; <br />
<img src="https://static.igem.org/mediawiki/2013/0/01/PB_13_Results_detect_killing_assay.png" width="80%" style="margin-bottom:-80px;"/> <br />
<br><br />
<br><br />
<p><b>Figure 5: </b> CRISPR anti-Kan plasmids target specifically kanamycin resistant <i>E. coli</i>.<div style="font-size:90%"> We introduced our CRISPR-based DNA cleavage system to two strains of <i>E. coli</i>: one WT (blue bars) and one carrying a genomically integrated kanamycin resistance casette (KanR, blue bars). The strains were co-transformed with two plasmids. One with the Cas9 construct, the other with the anti-Kanamycin gRNA. WT <i>E. coli</i> could be efficiently transformed with one or both plasmids, as determined by selective plating. However, KanR <i>E. coli</i> could not be efficiently transformed with both. We attribute this to Cas9-induced cleavage of the chromosome specifically at the KanR casette, with about 99% efficiency.</div></p><br />
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<br />
<br><br />
<h3>Characterization of the reporter - under construction</h3><br />
<div class="leftparagraph"><br />
<p>&nbsp;&nbsp;To characterize the pRecA –LacZ construct, we induced double strand breaks with Mytomycin C (MMC) and analyzed the resulting LacZ expression levels with the Miller assay. The same time, we wanted to characterize our final system: our target strain with the kanamycin resistance gene that also carries the reporter and the Cas9. The gRNA is delivered by a phage. As positive control, we used MG1655, which has a constitutive expression of LacZ, as negative control the parental strain of the target strain, which doesn’t have a kanamycin resistance cassette but also has the reporter and Cas9.<br />
As it can be seen in Figure 6, we didn’t get any expression of LacZ beside in the positive control, the MG1655 strain. As we worry, that our reporter might be not functional, we started to characterize a reporter constructed by Ariel Lindner. This reporter is YFP under the control of pREC. We analyzed its expression rates by inducing double strand breaks with Mitomycin C and Niprofloxacin. The data generated by FACS analysis over time can be seen in Figure 7. We can clearly see an induction of the pREC promoter due to induction with MMC and Niprofloxacin. Due to time constraints, we were not able to successfully adapt our system to use this pREC-YFP reporter in our target strain. In previous iGEM years, there has already been a pREC-LacZ Biobricked constructed (Heidelberg 2012). In principle, our system couldbe completed, as a functional pREC-LacZ already exists. By adding the reporter of Heidelberg 2012 to our target strain with the Cas9, we should be able to get a functional sensor. This sensor can detect and report a specific DNA sequence due to a phagemid delivered gRNA that guides the present Cas9 to a target where the Cas9 generates a double strand break, which is reported by pREC-LacZ.<br />
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<h3>Next steps</h3><br />
<div class="left paragraph"><br />
As previously mentioned, the reporter didn’t work as expected. This can have several reasons. As our other positive control (beside MG1655), the MMC induced strains carrying the reporter didn’t show any expression, it stands to reason that the reporter itself is not functional. Another reason could be, that the phagemid didn’t deliver the gRNA or not in enough amounts to show an effect of the complete working system.<br />
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<p>&nbsp;&nbsp; <br />
To test, if the phagemid delivers the gRNA correctly, we will perform another killing assay as we have done it before with the difference that the gRNA is delivered by the phagemid. The strains are then plated to see, if there is a reduced number of colonies of the target strain with phagemid in comparison to a control strain and without added phages. We expect the results before the end of iGEM.<br />
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<h2>Literature</h2><br />
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<ul><br />
<li>James E. DiCarlo, Julie E. Norville, Prashant Mali, Xavier Rios, John Aach and George M. Church (2013).<i> Genome engineering in Saccharomyces cerevisiae using CRISPR-Cas systems.</i> Nucleic Acids Research. 2013, 1–8.</li><br />
<li id="">Antonio R. Fernandez de Henestrosa, Tomoo Ogi, Sayura Aoyagi, David Chafin, Jeffrey J. Hayes, Haruo Ohmori and Roger Woodgate (2000). <i>Identification of additional genes belonging to the LexA regulon in Escherichia coli.</i> Molecular Microbiology .2000 35(6), 1560-1572.</li><br />
<li id="">Higashitani N., Higashitani I.A., Roth A., Horiuchi A.K. (1992). <i>SOS Induction in Escherichia coli by Infection with Mutant Filamentous Phage That Are Defective in Initiation of Complementary-Strand DNA Synthesis.</i> Journal of Bacteriology. 174:1612-1618.</li><br />
<li id="">Wenyan Jiang, David Bikard, David Cox, Feng Zhang & Luciano A Marraffini (2013). <i>RNA-guided editing of bacterial genomes using CRISPR-Cas systems.</i> Nature Biotechnology. 31 (3), 233-2398.</li><br />
<li id="">Douglas H. Juers, Brian W. Matthews, and Reuben E. Huber (2012). <i>LacZ b-galactosidase: Structure and function of an enzyme of historical and molecular biological importance.</i> Protein Science. 2012, 21,1792—1807.</li><br />
<li id="">Karlsson F., Malmborg-Hager A.C., Albrekt A.S., Borrebaeck C.A.K. (2005). <i>Genome-wide comparison of phage M13-infected vs. uninfected Escherichia coli. </i> Can. J. Microbiol. 51:29-35.</li><br />
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<div class="rightparagraph"><br />
<ul><br />
<br />
<li id="">Kimberly L. Keller, Terri L. Overbeck-Carrick, Doris J. Beck (2001). <i>Survival and induction of SOS in Escherichia coli treated with cisplatin, UV irradiation, or mitomycin C are dependent on the function of the RecBC and RecFOR pathways of homologous recombination. </i> Mutation Research. 486, 2001, 21–29.</li><br />
<li id="">Kobayashi, Ichizo; and Handa, Naofumi (2009). <i>DNA Doublestrand Breaks and Their Consequences in Bacteria. </i> Encyclopedia of Life Sciences (ELS). John Wiley & Sons, Ltd: Chichester.</li><br />
<li id=""> Timothy K. Lu, Jayson Bowers, and Michael S. Koeris (2013). <i> Advancing bacteriophage-based microbial diagnostics with synthetic biology. </i>Trends in Biotechnology. April 2013, 31 (6), 325-227.</li><br />
<li id="">Anders Norman, Lars Hestbjerg Hansen, and Søren J. Sørensen (2004). <i>Construction of a ColD cda Promoter-Based SOS-Green Fluorescent Protein Whole-Cell Biosensor with Higher Sensitivity toward Genotoxic Compounds than Constructs Based on recA, umuDC, or sulA Promoters. </i> APPLIED AND ENVIRONMENTAL MICROBIOLOGY. May 2005, p. 2338–2346.</li> <br />
<li id="">Sommer S., Leitao A., Bernardi A., Bailone A., Devoret R. (1991). <i>Introduction of a UV-damaged replicon into a recipient cell is not a sufficient condition to produce an SOS-inducing signal.</i> Mutation Research/DNA Repair. 254:107-17.</li><br />
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<h2>Attributions</h2> <br />
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<p> Most of the strains and plasmids used for this project were kindly provided by the INSERM U1001 lab.</p><br />
<p> The Cas9 plasmid as well as the CRISPR plasmid were ordered from Addgene. The crRNA was designed after consultation with David Bikard.</p><br />
<p> The sequence of LacZ used in this project was taken from pBAC-BA-lacZ from Addgene. The corresponding pREC sequence is the natural sequence. The source for the sequence is EcoCyc.</p><br />
<p> The phaegmid template as well as the helper plasmid were provided by Monica Ortiz from the Endy Lab, Stanford.</p><br />
<p> The project itself was designed and accomplished by Nicolas Koutsoubelis, Anne Loechner and Marguerite Benony with consultation with Edwin Wintermute, Stanislas and Ariel Lindner.</p><br />
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