Team:BostonU/Clotho

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<p  style="text-align:center;"><a href="https://2013.igem.org/Team:BostonU"><img src="https://static.igem.org/mediawiki/2013/2/2c/Marsh.png" width="800px" length="200px"></a></p>
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<li><a href="#">Our Team</a>
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<li><a href="https://2013.igem.org/Team:BostonU/Project_Overview">Project Overview and Abstract</a></li>
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                        <li><a href="https://2013.igem.org/Team:BostonU/MoCloChara">Introduction to MoClo and Characterization</a></li>
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                        <li><a href="https://2013.igem.org/Team:BostonU/QS">Quorum Sensing</a></li>
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<li><a href="https://2013.igem.org/Team:BostonU/Methodology ">Methodology Overview</a></li>
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<li><a href="#">Achievements</a>
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<li><a href="https://2013.igem.org/Team:BostonU/Data">Data Collected</a></li>
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<li><a href="https://2013.igem.org/Team:BostonU/Parts">Parts Submitted</a></li>
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<li><a href="https://2013.igem.org/Team:BostonU/MoClo">MoClo Kit</a></li>
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<li><a href="https://2013.igem.org/Team:BostonU/Protocols">Protocols</a></li>
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<li><a href="https://2013.igem.org/Team:BostonU/Clotho">Clotho and Eugene</a></li>
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<li><a href="https://2013.igem.org/Team:BostonU/NotebookQS">Quorum Sensing Notebook</a></li>
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<li><a href="#">Considerations</a>
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<li><a href="https://2013.igem.org/Team:BostonU/NEGEM">New England iGEM Regional Meeting</a></li>
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<li><a href="https://2013.igem.org/Team:BostonU/Human Practices">Human Practices</a></li>
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<li><a href="https://2013.igem.org/Team:BostonU/Safety">Safety</a></li>
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<li><a href="#">Acknowledgements</a>
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                    <li><a href="https://2013.igem.org/Team:BostonU/Collaborations">Collaborations</a></li>
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                    <li><a href="https://2013.igem.org/Team:BostonU/Acknowledgements">Acknowledgements</a></li>
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<h4>Clotho and Eugene</h4>
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<h5>Clotho Introduction</h5>
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<p><center><img src="http://www.bu.edu/ece/files/2011/06/300px-ClothoLogo.png" width="250px"></center></p>
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<h7><p><ul>Our project is focused on creating a standardized method for the characterization of genetic circuits in synthetic biology. In order to achieve this goal, it is necessary to have a platform that enables us to create the standardized data, organize it, and manage it efficiently. We have been utilizing <a href="http://clothocad.org">Clotho</a>, a synthetic biology software suite developed with tools for analyzing and organizing data.</p>
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<p>This section aims to describe how we have been using Clotho in our project. We divided the content into the <a href="http://wiki.bu.edu/ece-clotho/index.php/App_Information">Clotho Apps</a> we used, giving a brief explanation of how each app works and examples of situations in which they were useful for our project.</p>
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<h5>Blasto</h5><ul>
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<h7><p>Blasto can be used to verify DNA sequences by comparing a sequence with the expected sequence.  Blasto shows the percentage of the match and the number of gaps between sequences and where those gaps occur.  Users can create a collection of their parts and save sequences for easy comparison.</p></h7>
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<h8>Clotho Introduction<br /></h8>
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<h7><p><a href="www.eugenecad.org">Eugene</a>, a language based on Java, is both human and machine readable. Currently the language can be used to expedite the design process for new devices by providing a list of possible transcriptional units based on specific rules and parts available.</p>
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<p>The BostonU iGEM team used Eugene to determine the number of permutations for transcriptional units that can be assembled from the MoClo parts and devices specified by the user.  To eliminate extraneous permutations, the user must specify rules pertaining to the order and relationship between parts.  Eugene can be utilized via Clotho's Eugene Scriptor app.</p>
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<p>To write a Eugene script, one must first declare the parts that are being used and their properties.  Next, one must define the specific properties for each part.  To define the devices, structural rules must be made defining what parts are in each device. Content rules describe the relationships between parts. Lastly, the user can compute permutations and print out the results.</p>
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<p>Below is an example of a Eugene  script for a generic quorum sensing circuit.</p></h7>
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<h7><p dir="ltr">Our project is focused on creating a standardized method for the characterization of genetic circuits in synthetic biology. In order to achieve this goal, it is necessary to have a platform that enables us to create the standardized data, organize it and manage it efficiently. <a href="http://clothocad.org">Clotho</a> is a great synthetic biology tool that has been helping us with exactly that!
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This section aims to describe how we have been using Clotho in our project. We divided the content into the <a href="http://wiki.bu.edu/ece-clotho/index.php/App_Information">Clotho Apps</a> we used, giving a brief explanation of how each App works and examples of situations in which they were useful for our project.
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We hope you can all get good ideas on how to use Clotho on your projects and take advantage of this amazing tool!</p>
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<h7><p><a href="http://pigeoncad.org/">PigeonCAD</a> is a very useful tool for synthetic biology because it allows the user to visualize genetic devices. Using the Synthetic Biology Open Language (SBOL) and a simple code, the user can easily build a circuit <a href="http://pubs.acs.org/doi/abs/10.1021/sb400024s">(Bhatia et al., 2013)</a>. We used Pigeon to depict our genetic circuits.</p>
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<p>Depicted below is an example of a simple transcriptional unit depicted in SBOL with the corresponding Pigeon code.</p></h7>
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<h7><p dir="ltr"><a href="http://wiki.bu.edu/ece-clotho/index.php/SpreadIt_Oligos">SpreadIt Oligos</a> is an app that allows users to browse and input oligos from and into the data base. We used this app to add on additional oligos one at a time aside from spreadsheets of primers that were added by Bull Trowell. SpreadIt Oligos does what Bull Trowell does on a smaller scale. </p><br>
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<p><center><img src="https://static.igem.org/mediawiki/2013/3/38/Pigcode.png"></center></p>
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<p><h7>The <a href="http://pigeoncad.org/">PigeonCAD</a> website has additional examples.</h7></p>
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<p dir="ltr"><a href="http://wiki.bu.edu/ece-clotho/index.php/Bull_Trowell">Bull Trowel</a> is a very useful app for adding large amounts of Parts, Oligos, Vectors, Plasmids and etc from an excel sheet to Clotho`s inventory. In our case, we had a list of almost 200 primers that we designed in an Excel sheet that we wanted to include in our inventory. All of them could be added much faster and with lower mistake rate by using Bull Trowel. Below, there is an example of the interface of the app while we were adding our oligos and the Excel sheet from which we took the oligo sequences. </p><br>
 
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<p dir="ltr"> Also, the description section helps to give meaning to the nickname and makes the inventory more user-friendly.</p>
 
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<a href="http://wiki.bu.edu/ece-clotho/index.php/Sequence_View">Sequence Viewer</a> is a very useful app to analyze sequences that are in the inventory . It allows us not only to view the sequences of DNA, but also to interact with it by highlighting specific portions that we are interested in. For example, we used sequence viewer to find and highlight restriction and fusion sites within the sequence.  </p><br>
 
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<a href=http://wiki.bu.edu/ece-clotho/index.php/SpreadIt_Features">SpreadIt Features</a> was a very useful tool while we were designing our MoClo primers. When we create primers for moclo, we need to make sure the genes for which we create the primers do not have certain restriction sites within them where our moclo enzymes will cut. We thus use the spreadit feature app to create features such as restriction sites by entering the sequence into the data base so that when viewing the gene sequence in sequence viewer, we can look for these restriction sites. Also, SpreadIt Features enabled us to create MoClo fusion sites as features to be analyzed in our sequences so we can better predict how and where ligation in MoClo reaction is occurring.</p><br>
 
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<h8>References</h8>
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[1] Xia, B., Bhatia, S., Bubenheim, B., Dadgar, M., Densmore, D., and Anderson, J.C. (2011) "Clotho: A Software Platform for the Creation of Synthetic Biological Systems, A Developer’s and User’s Guide for Clotho v2.0." <i>Methods in Enzymology</i> 498:97-135. doi: 10.1016/B978-0-12-385120-8.00005-X.<br>
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[2] Bilitchenko, L., Liu, A., Cheung, S., Weeding, E., Xia, B., Leguia, M., Anderson, J.C., and Densmore, D. (2011) "Eugene – A Domain Specific Language for Specifying and Constraining Synthetic Biological Parts, Devices, and Systems." <i>PLoS ONE</i> 6(4): e18882. doi:10.1371/journal.pone.0018882. <br>
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[3] Bhatia, S., and Densmore, D. (2013) "Pigeon: A Design Visualizer for Synthetic Biology." ACS Synthetic Biology 2(6):348–350. doi: 10.1021/sb400024s.
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<ul><a href="www.eugenecad.org">Eugene</a> is a language based off of Java which is both human and machine readable. Currently the language can speed up the designs of new parts by providing a list of possible transcriptional units based on specific rules and parts available.<br><br>
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Still in its beta stages, the BU iGEM team used Eugene to come up with list of possible transcriptional units that could be assembled from the Moclo parts we made. By specifying rules concerning fusion sites and restriction sites, we let Eugene do the designing for us, while we then selectively choose which transcriptional units to create. Below is a sample of Eugene script for which we used today. <h7>
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We were fortunate to be able to use Eugene through Clotho's Eugene Scriptor. The first task to do in writing a Eugene script is to define what the parts are. Notice that the language is very straightforward and intuitive.
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In this example above, we are defining our basic parts. Although the fusion/MoClo sites themselves are not basic parts, we consider them as a separate entities because they are essential when combining different MoClo parts. At this point, fusion sites as a separate part would be a more versatile method of using the language.<br>
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After defining which parts Eugene will be combining to together, the next step would be to identify  the device. In this case, different basic parts are combined to form a moclo level 0 part.<br>
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After defining our MoClo level 0 devices, the next step is to define level MoClo Level 1 devices. In this case, a level 1 device is designated to include a promotor, rbs, gene and terminator. Additional rules are added as needed.
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For instance, we are creating rules to make sure the Moclo sites of subsequent parts are the same so they are able to be ligated together. In the picture the rule is expressed for Promoter and RBS. Also, we have to be consistent with the design of the MoClo parts, it means that the part can`t be flanked by the same MoClo sites as show in the second rule.  <br>
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Although we did not have the chance to use Eugene extensively, we do hope to use it more hand in hand with our experiments as we continue to create novel Moclo parts. <h7>
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Latest revision as of 03:16, 28 September 2013



Clotho and Eugene


Clotho Introduction

    Our project is focused on creating a standardized method for the characterization of genetic circuits in synthetic biology. In order to achieve this goal, it is necessary to have a platform that enables us to create the standardized data, organize it, and manage it efficiently. We have been utilizing Clotho, a synthetic biology software suite developed with tools for analyzing and organizing data.

    This section aims to describe how we have been using Clotho in our project. We divided the content into the Clotho Apps we used, giving a brief explanation of how each app works and examples of situations in which they were useful for our project.

Blasto

    Blasto can be used to verify DNA sequences by comparing a sequence with the expected sequence. Blasto shows the percentage of the match and the number of gaps between sequences and where those gaps occur. Users can create a collection of their parts and save sequences for easy comparison.



Eugene

    Eugene, a language based on Java, is both human and machine readable. Currently the language can be used to expedite the design process for new devices by providing a list of possible transcriptional units based on specific rules and parts available.

    The BostonU iGEM team used Eugene to determine the number of permutations for transcriptional units that can be assembled from the MoClo parts and devices specified by the user. To eliminate extraneous permutations, the user must specify rules pertaining to the order and relationship between parts. Eugene can be utilized via Clotho's Eugene Scriptor app.

    To write a Eugene script, one must first declare the parts that are being used and their properties. Next, one must define the specific properties for each part. To define the devices, structural rules must be made defining what parts are in each device. Content rules describe the relationships between parts. Lastly, the user can compute permutations and print out the results.

    Below is an example of a Eugene script for a generic quorum sensing circuit.



PigeonCAD


    PigeonCAD is a very useful tool for synthetic biology because it allows the user to visualize genetic devices. Using the Synthetic Biology Open Language (SBOL) and a simple code, the user can easily build a circuit (Bhatia et al., 2013). We used Pigeon to depict our genetic circuits.

    Depicted below is an example of a simple transcriptional unit depicted in SBOL with the corresponding Pigeon code.

    The PigeonCAD website has additional examples.



References

[1] Xia, B., Bhatia, S., Bubenheim, B., Dadgar, M., Densmore, D., and Anderson, J.C. (2011) "Clotho: A Software Platform for the Creation of Synthetic Biological Systems, A Developer’s and User’s Guide for Clotho v2.0." Methods in Enzymology 498:97-135. doi: 10.1016/B978-0-12-385120-8.00005-X.
[2] Bilitchenko, L., Liu, A., Cheung, S., Weeding, E., Xia, B., Leguia, M., Anderson, J.C., and Densmore, D. (2011) "Eugene – A Domain Specific Language for Specifying and Constraining Synthetic Biological Parts, Devices, and Systems." PLoS ONE 6(4): e18882. doi:10.1371/journal.pone.0018882.
[3] Bhatia, S., and Densmore, D. (2013) "Pigeon: A Design Visualizer for Synthetic Biology." ACS Synthetic Biology 2(6):348–350. doi: 10.1021/sb400024s.




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