Team:SYSU-China/Project/Results

From 2013.igem.org

(Difference between revisions)
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<span>UPDATE <INS>09/22/2013</INS></span>
<span>UPDATE <INS>09/22/2013</INS></span>
<h1>An Introduction to Experiments Designing</h1>
<h1>An Introduction to Experiments Designing</h1>
-
<h1>The Cruel Guard</h1><h1>：Suicide Gene and Its Ancillary Facility</h1>
+
<p>
 +
The design of iPSC Safeguard pathway is simple and elegant. Basically, we can divide them into three major devices—the Suicide Gene, the MicroRNA-Target system and the Tet-off system, which has been described in detail in the Design module. For each device we had several candidates and before we finally assemble them into the whole pathway, we decided to test and characterize them carefully in the first place. The accurately quantitated parameters of each device then helped us set up a model and predicted which assembly scheme would work out best.
 +
In order to test the devices, elements were cloned into our two major plasmids backbone: pcDNA3.0(from Invitrogen) and p199(from。。。).The maps or design are shown in each parts of Results. We drove the Suicide Gene with CMV promoter to ensure a robust expression and prominent phenotype in cells. An eGFP was used to indicate the performance of Tet-off and MicroRNA-Target system, which could be quantitated through Image J and Western-Blot. All separately testing experiments were carried out via transient transfection in Bosc and HepG2, considering both the transfection efficiency and representation of liver cancer cell. Also, a survival experiment was done on liver cell to ensure that its miR122 level can successfully knockdown Suicide Gene with miR122 target-site.
 +
</p>
 +
<p>
 +
After confirmation of each device, we proceeded to working on iPSC and assembly of the whole pathway. The whole pathway was integrated into two p199 plasmids, one for regulating and one for response .Lenti-virus packaging these two plasmids was produced and 3 cell lines of iPSC, HepG2, Hela were transfected. This successfully gave us the stable cell line with our iPSC Safeguard design. Then further test and characterization of the pathway’s performance of working as a whole were carried out. All the data can be seen in >>>>>.
 +
</p>
 +
<h1>The Cruel Guard：Suicide Gene and Its Ancillary Facility</h1>
<h2>1.Comparison between Suicide Genes: who is the most tough killer?</h2>
<h2>1.Comparison between Suicide Genes: who is the most tough killer?</h2>
 +
<p>
 +
We collected several different Suicide Genes which functions in different pathways and patterns. In order to choose one that is most capable of inducing apoptosis in cancer cell, we first carried out a comparison experiment for these genes.
 +
</p>
 +
Figure1. Apoptosis rate comparison of different Suicide Genes using DAPI staining
 +
<img />
 +
<p>
 +
DAPI staining was carried out for each Suicide Gene and we found that apoptosis phenotype was most outstanding for RIP1, the >>>>>>. In order to quantitate the death rate, Flow Cytometry(FCM) was performed using PI staining. The results is amazing: the >>>>>>>
 +
</p>
<h2>2.Rescue scheme: a combination of Suicide Gene and MicroRNA-Target system.</h2>
<h2>2.Rescue scheme: a combination of Suicide Gene and MicroRNA-Target system.</h2>
 +
<p>
 +
Tough as the Suicide Gene is, what we expect from it was to protect instead of killing the innocent. This should work through cooperation of both Suicide Gene and MicroRNA-Target system: a killer and a detector. We carried out a rescue experiment with gradient-dosage MiR122 to verify that the MicroRNA-Target system do work in a proper range of MiR122 concentration. Here to work properly means it doesn’t knockdown Suicide Gene under concentration as low as cancer cell or iPSC, but can robustly repress it under concentration of liver cell. And surely we also refer to many papers of the miR122 level in different cell lines, and perform RT-qPCR to verify it.
 +
</p>
 +
Figure 2
 +
<h2>3.Controlling the switch: a combination of Suicide Gene and Tet-off system.</h2>
<h2>3.Controlling the switch: a combination of Suicide Gene and Tet-off system.</h2>
 +
Figure 3
<h2>4.The final test-run: combination of all three systems before setting up stable cell line.</h2>
<h2>4.The final test-run: combination of all three systems before setting up stable cell line.</h2>
 +
<p>
 +
Because of the limitation of transient transfection method(efficiency, duration time), we don’t expect good results from this experiment. However, since establishment of stable cell line takes much time and troubleshooting, we may still do it as a complement.
 +
</p>
 +
Figure 4
<h2>5.Survival experiment of liver cell.</h2>
<h2>5.Survival experiment of liver cell.</h2>
 +
<p>
 +
With our collinear-regression model of MicroRNA-Target system, the knockdown efficiency predicted with a two-copy complete target-site and the miR122 concentration of liver cell would be >>>%, and the experiment shows that this gives a good rescue effect.
 +
</p>
 +
Figure 5
<h1>Simulated Testing of MicroRNA-Target Devices: Security Gate for Liver Cell.</h1>
<h1>Simulated Testing of MicroRNA-Target Devices: Security Gate for Liver Cell.</h1>
<h2>1.Performance comparison between two kinds of target-sites: CULT and Complete<a class="quote">[1]</a>.</h2>
<h2>1.Performance comparison between two kinds of target-sites: CULT and Complete<a class="quote">[1]</a>.</h2>
 +
<p>
 +
An orthogonal experiment was performed to make a comparison between the knock-down efficiency of different target-site under different concentration of MiR122. Two plasmids were co-transfected using PEI into Bosc cell line. Plasmids A expressed GFP whose mRNA carries different target-site of miR122 in its 3’ UTR. Plasmids B express MiR122. Target-site with most notable knock-down efficiency will be chosen for further characterization and construction.
 +
</p>
 +
<p>
 +
The miR122 expression plasmid used in this experiment also express a GFP, which is a bug originally neglected in our design. However, we find out that although this does interfere our results to some degree, we can still gain insight into different performance between target-sites. Also, this accident may be kind of an unexpected clue to a new discovery, which may be one of our future work>>>>
 +
</p>
 +
<p>
 +
After finding out this bug, we do quick-change to introduce a stop-codon into the CDS of GFP, which proves very efficient.
 +
</p>
 +
Figure1. Comparison of performance of different target-sites in knocking down GFP expression
 +
Plasmids construction
 +
Fluorescence
 +
 +
<img />
 +
<p>
 +
The result shows that with the same copy number, complete target-site works better than CULT target-site, which fits the results of the 2010 Heiderburg iGEM team. What’s more, two copies target-site works better than single site, which encourage us to further build target-sites of more copy number and quantitatively test their performance.
 +
</p>
<h2>2.Quantitative characterization of the complete-target-site series and the linear-regression model.</h2>
<h2>2.Quantitative characterization of the complete-target-site series and the linear-regression model.</h2>
 +
<p>
 +
In order to build a precisely controlled device, we decided to further characterized the complete-target-sites of 1\2\4 copy number and chose the most suitable one for pathway construction. To begin with we design another orthogonal experiment for the two variables, target-site-number N and MiR122 concentration M, with a more precise gradients for MiR122. But soon we found that would be too labour-costing. A better way is to replace it with 2 dosage-gradient experiment and a mathematic model.
 +
</p>
 +
<u><em>A.Dosage experiment testing performance of 2 copies complete target-site</em></u>
 +
<p>
 +
Plasmids A was the same as used in experiment 1, while plasmids B no longer expressed GFP due to the silencing mutation in CDS. In order to quantitate target-site performance under different concentration of MiR122, a dosage-gradient of plasmids B was set up and so was a parallel experiment groups to leave enough samples of each concentration for both Western Blot and RT-qPCR.
 +
</p>
 +
Figure2.
 +
Fluorescence
 +
Western Blot of GFP
 +
RT-qPCR of MiR122.
 +
<img />
 +
Knock down efficiency chart
 +
 +
<p>收样时间：48hr<br />Target-site: Complete 2-copies</p>
 +
<table width="536">
 +
<tr>
 +
<th scope="col">Mir122</th>
 +
<th scope="col">1</th>
 +
<th scope="col">4</th>
 +
<th scope="col">10</th>
 +
<th scope="col">28</th>
 +
<th scope="col">76</th>
 +
<th scope="col">161</th>
 +
</tr>
 +
<tr class="first-table-line">
 +
<td>GFP(Western Blot)</td>
 +
<td></td>
 +
<td></td>
 +
<td></td>
 +
<td></td>
 +
<td></td>
 +
<td></td>
 +
</tr>
 +
</table>
 +
 +
<p>
 +
The results show that MiR122 does have an dosage effect upon target-site. The concentration that have the best knock-down performance is about >>>>>, and RT-qPCR of different kinds of cell line shows that only liver cell is able to turn off this second switch of iPS-Safeguard and avoid the fate of apoptosis.
 +
</p>
 +
<p>
 +
<u><em>B.Performance of complete target-site of different copy number</em></u>
 +
</p>
 +
<p>
 +
To further characterized the several candidate target-site for our iPS-Safeguard, we design another gradient experiment and this time let target-site copy number be the variable. The MiR122 concentration is fixed at one that gives a best performance and since we’ve already known the relationship between plasmids concentration and MiR122 expression level, only a Western-Blot is needed.
 +
</p>
 +
Figure3.
 +
Fluorescence
 +
Western blot
 +
Knock down efficiency chart
 +
 +
<p>Mir122 concentration:0.75ug=</p>
 +
<table width="536">
 +
<tr>
 +
<th scope="col">Target-Site Number</th>
 +
<th scope="col">0</th>
 +
<th scope="col">1</th>
 +
<th scope="col">2</th>
 +
<th scope="col">4</th>
 +
</tr>
 +
<tr class="first-table-line">
 +
<td>GFP(Western Blot)</td>
 +
<td></td>
 +
<td></td>
 +
<td></td>
 +
<td></td>
 +
</tr>
 +
</table>
 +
<p>
 +
The results show that 4 copy target-site has the most brilliant knock-down efficiency, which is about〉〉〉〉, which conforms to the data given by 2010 Heiderburg using dual-fluorescent system. However, since we are on a tight schedule in this competition, we can’t wait until this results and have already adopt the 2 copy target-site for further construction. Has we needed a better knock-down efficiency later, we can replace the target-site conveniently with our restriction enzyme.
 +
</p>
 +
<p>
 +
C. the linear regression model for miR122-target system.
 +
</p>
 +
<p>
 +
The results of experiment A and B then provide enough data for Model construction. The （拟合了线性关系，用matlab 做出了这样的一幅图？总之就是一个建模过程的简单描述）. The model shows that(关于模型说明的问题的一个精简解释，说明了什么趋势，预测了什么事情)
 +
Figure4. Linear Regression Model for MicroRNA-Target Gate.
 +
</p>
 +
<img />
<h1>Dosage test of Tet-off system: Controlling Panel For iPSC.</h1>
<h1>Dosage test of Tet-off system: Controlling Panel For iPSC.</h1>
<h2>1.Trial test of two different Tet-off system: the switching performance between on and off states.</h2>
<h2>1.Trial test of two different Tet-off system: the switching performance between on and off states.</h2>
-
</DIV>
+
<p>
 +
<EM>
 +
<STRONG>Experiment Design:</STRONG><br />
 +
Two plasmids were co-transfected into Bosc cell line using PEI, plasmids A expressed tTA protein and one carries the TRE-tight element and while response to tTA protein, expressed eGFP (BBa>..). The well with only plasmids B characterized the basal leaky expression of TRE-tight element, which can be viewed as the first off-state. Well with both plasmids represents the on-state of the system, and the third well with dox represents the second off-state. Dox concentration was chosen according to protocols in order to give a best performance of the system and avoid hazard on cell growth.
 +
</EM>
 +
</p>
 +
Figure1. Comparison of on/off switch performance between two Tet-off systems.
 +
Plasmids construction
 +
Fluorescence of on/off switch of two Tet-off systems.
 +
 +
Western Blot of GFP expression level of on/off state of Tet-off systems.
 +
<img />
 +
<img />
 +
</DIV>
 +
<p>
 +
Conclusion:<br />
 +
The data shows that the two systems have different on/off expression levels, but both shows good response to Dox, which is low off-expression-not so high on-expression, and relatively high off-expression-robust on-expression. The variability in performance can be properly utilized according to the apoptosis condition conducted by Suicide Gene.
 +
</p>
 +
<DIV id="references">
 +
<h2References</h2>
 +
<p><a class="references">[1]</a>Hui Xu etc. Liver-Enriched Transcription Factors Regulate MicroRNA-122 That Targets CUTL1 During Liver Development.</p>
 +
<p><a class="references">[2]</a>Tet-Off and Tet-On Gene Expression Systems User Manual</p>
 +
</DIV>
<!--正 文 部 分 结 束-->
<!--正 文 部 分 结 束-->
      
      

Revision as of 06:08, 22 September 2013

ipsc

UPDATE 09/22/2013

An Introduction to Experiments Designing

The design of iPSC Safeguard pathway is simple and elegant. Basically, we can divide them into three major devices—the Suicide Gene, the MicroRNA-Target system and the Tet-off system, which has been described in detail in the Design module. For each device we had several candidates and before we finally assemble them into the whole pathway, we decided to test and characterize them carefully in the first place. The accurately quantitated parameters of each device then helped us set up a model and predicted which assembly scheme would work out best. In order to test the devices, elements were cloned into our two major plasmids backbone: pcDNA3.0(from Invitrogen) and p199(from。。。).The maps or design are shown in each parts of Results. We drove the Suicide Gene with CMV promoter to ensure a robust expression and prominent phenotype in cells. An eGFP was used to indicate the performance of Tet-off and MicroRNA-Target system, which could be quantitated through Image J and Western-Blot. All separately testing experiments were carried out via transient transfection in Bosc and HepG2, considering both the transfection efficiency and representation of liver cancer cell. Also, a survival experiment was done on liver cell to ensure that its miR122 level can successfully knockdown Suicide Gene with miR122 target-site.

After confirmation of each device, we proceeded to working on iPSC and assembly of the whole pathway. The whole pathway was integrated into two p199 plasmids, one for regulating and one for response .Lenti-virus packaging these two plasmids was produced and 3 cell lines of iPSC, HepG2, Hela were transfected. This successfully gave us the stable cell line with our iPSC Safeguard design. Then further test and characterization of the pathway’s performance of working as a whole were carried out. All the data can be seen in >>>>>.

The Cruel Guard：Suicide Gene and Its Ancillary Facility

1.Comparison between Suicide Genes: who is the most tough killer?

We collected several different Suicide Genes which functions in different pathways and patterns. In order to choose one that is most capable of inducing apoptosis in cancer cell, we first carried out a comparison experiment for these genes.

Figure1. Apoptosis rate comparison of different Suicide Genes using DAPI staining

DAPI staining was carried out for each Suicide Gene and we found that apoptosis phenotype was most outstanding for RIP1, the >>>>>>. In order to quantitate the death rate, Flow Cytometry(FCM) was performed using PI staining. The results is amazing: the >>>>>>>

2.Rescue scheme: a combination of Suicide Gene and MicroRNA-Target system.

Tough as the Suicide Gene is, what we expect from it was to protect instead of killing the innocent. This should work through cooperation of both Suicide Gene and MicroRNA-Target system: a killer and a detector. We carried out a rescue experiment with gradient-dosage MiR122 to verify that the MicroRNA-Target system do work in a proper range of MiR122 concentration. Here to work properly means it doesn’t knockdown Suicide Gene under concentration as low as cancer cell or iPSC, but can robustly repress it under concentration of liver cell. And surely we also refer to many papers of the miR122 level in different cell lines, and perform RT-qPCR to verify it.

Figure 2

3.Controlling the switch: a combination of Suicide Gene and Tet-off system.

Figure 3

4.The final test-run: combination of all three systems before setting up stable cell line.

Because of the limitation of transient transfection method(efficiency, duration time), we don’t expect good results from this experiment. However, since establishment of stable cell line takes much time and troubleshooting, we may still do it as a complement.

Figure 4

5.Survival experiment of liver cell.

With our collinear-regression model of MicroRNA-Target system, the knockdown efficiency predicted with a two-copy complete target-site and the miR122 concentration of liver cell would be >>>%, and the experiment shows that this gives a good rescue effect.

Figure 5

Simulated Testing of MicroRNA-Target Devices: Security Gate for Liver Cell.

1.Performance comparison between two kinds of target-sites: CULT and Complete[1].

An orthogonal experiment was performed to make a comparison between the knock-down efficiency of different target-site under different concentration of MiR122. Two plasmids were co-transfected using PEI into Bosc cell line. Plasmids A expressed GFP whose mRNA carries different target-site of miR122 in its 3’ UTR. Plasmids B express MiR122. Target-site with most notable knock-down efficiency will be chosen for further characterization and construction.

The miR122 expression plasmid used in this experiment also express a GFP, which is a bug originally neglected in our design. However, we find out that although this does interfere our results to some degree, we can still gain insight into different performance between target-sites. Also, this accident may be kind of an unexpected clue to a new discovery, which may be one of our future work>>>>

After finding out this bug, we do quick-change to introduce a stop-codon into the CDS of GFP, which proves very efficient.

Figure1. Comparison of performance of different target-sites in knocking down GFP expression Plasmids construction Fluorescence

The result shows that with the same copy number, complete target-site works better than CULT target-site, which fits the results of the 2010 Heiderburg iGEM team. What’s more, two copies target-site works better than single site, which encourage us to further build target-sites of more copy number and quantitatively test their performance.

2.Quantitative characterization of the complete-target-site series and the linear-regression model.

In order to build a precisely controlled device, we decided to further characterized the complete-target-sites of 1\2\4 copy number and chose the most suitable one for pathway construction. To begin with we design another orthogonal experiment for the two variables, target-site-number N and MiR122 concentration M, with a more precise gradients for MiR122. But soon we found that would be too labour-costing. A better way is to replace it with 2 dosage-gradient experiment and a mathematic model.

A.Dosage experiment testing performance of 2 copies complete target-site

Plasmids A was the same as used in experiment 1, while plasmids B no longer expressed GFP due to the silencing mutation in CDS. In order to quantitate target-site performance under different concentration of MiR122, a dosage-gradient of plasmids B was set up and so was a parallel experiment groups to leave enough samples of each concentration for both Western Blot and RT-qPCR.

Figure2. Fluorescence Western Blot of GFP RT-qPCR of MiR122. Knock down efficiency chart

收样时间：48hr
Target-site: Complete 2-copies

Mir122 1 4 10 28 76 161
GFP(Western Blot)

The results show that MiR122 does have an dosage effect upon target-site. The concentration that have the best knock-down performance is about >>>>>, and RT-qPCR of different kinds of cell line shows that only liver cell is able to turn off this second switch of iPS-Safeguard and avoid the fate of apoptosis.

B.Performance of complete target-site of different copy number

To further characterized the several candidate target-site for our iPS-Safeguard, we design another gradient experiment and this time let target-site copy number be the variable. The MiR122 concentration is fixed at one that gives a best performance and since we’ve already known the relationship between plasmids concentration and MiR122 expression level, only a Western-Blot is needed.

Figure3. Fluorescence Western blot Knock down efficiency chart

Mir122 concentration:0.75ug=

Target-Site Number 0 1 2 4
GFP(Western Blot)

The results show that 4 copy target-site has the most brilliant knock-down efficiency, which is about〉〉〉〉, which conforms to the data given by 2010 Heiderburg using dual-fluorescent system. However, since we are on a tight schedule in this competition, we can’t wait until this results and have already adopt the 2 copy target-site for further construction. Has we needed a better knock-down efficiency later, we can replace the target-site conveniently with our restriction enzyme.

C. the linear regression model for miR122-target system.

The results of experiment A and B then provide enough data for Model construction. The （拟合了线性关系，用matlab 做出了这样的一幅图？总之就是一个建模过程的简单描述）. The model shows that(关于模型说明的问题的一个精简解释，说明了什么趋势，预测了什么事情) Figure4. Linear Regression Model for MicroRNA-Target Gate.

Dosage test of Tet-off system: Controlling Panel For iPSC.

1.Trial test of two different Tet-off system: the switching performance between on and off states.

Experiment Design:
Two plasmids were co-transfected into Bosc cell line using PEI, plasmids A expressed tTA protein and one carries the TRE-tight element and while response to tTA protein, expressed eGFP (BBa>..). The well with only plasmids B characterized the basal leaky expression of TRE-tight element, which can be viewed as the first off-state. Well with both plasmids represents the on-state of the system, and the third well with dox represents the second off-state. Dox concentration was chosen according to protocols in order to give a best performance of the system and avoid hazard on cell growth.

Figure1. Comparison of on/off switch performance between two Tet-off systems. Plasmids construction Fluorescence of on/off switch of two Tet-off systems. Western Blot of GFP expression level of on/off state of Tet-off systems.

Conclusion:
The data shows that the two systems have different on/off expression levels, but both shows good response to Dox, which is low off-expression-not so high on-expression, and relatively high off-expression-robust on-expression. The variability in performance can be properly utilized according to the apoptosis condition conducted by Suicide Gene.

[1]Hui Xu etc. Liver-Enriched Transcription Factors Regulate MicroRNA-122 That Targets CUTL1 During Liver Development.

[2]Tet-Off and Tet-On Gene Expression Systems User Manual

Sun Yat-Sen University, Guangzhou, China

Address: 135# Xingang Rd.(W.), Haizhu Guangzhou, P.R.China

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