Difference between revisions of "Part:BBa K3396000"
 
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===Usage and Biology===
 
===Usage and Biology===
 
The DocS[1] module comes from The C. thermocellum scaffoldin and it could recognize and bind tightly to complementary Coh2 modules. The Coh2–DocS pair represents the interaction between two complementary families of protein modules that exhibit divergent specificities and affinities, ranging from one of the highest known affinity constants between two proteins to relatively low-affinity interactions.
 
The DocS[1] module comes from The C. thermocellum scaffoldin and it could recognize and bind tightly to complementary Coh2 modules. The Coh2–DocS pair represents the interaction between two complementary families of protein modules that exhibit divergent specificities and affinities, ranging from one of the highest known affinity constants between two proteins to relatively low-affinity interactions.
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<p style=" font-weight: bold; font-size:20px;"> Improvement by CU_Egypt team 2022 </p>
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<p style=" font-weight: bold; font-size:23px;"> Contribution by CU_Egypt team 2022 </p>
  
 +
DocS (Dockerin) is a cellulolytic enzyme in Clostridium thermocellum. Each cellulosomal enzyme has one or more catalytic modules as well as a single dockerin module. The scaffolding is multifunctional, with the nine Cohesin modules integrating nine dockerin-bearing enzymes into the complex and the carbohydrate-binding enzymes. The complex is bound to the cellulosic substrate by the Cellulose Binding Domain (CBM), and the C-terminal dockerin module is implicated in this process. The interaction between Cohesin and Dockerin happens in two different forms, called the dual binding mode, in a calcium-dependent manner due to the presence of a calcium-binding site in the dockerin protein.
  
−
From literature we found that the yield of expression of Docs is very low so we decided to tag it by GST to increase its stability and the yield. Also, we optimized the sequence to be expressed in E-coli. in addition, there is no characterization for Docs on the registry so we expressed and characterized it by different methods such as Agarose gel electrophoresis, SDS PAGE, transformation efficiency, affinity chromatography, and Bradford assay. it's proved by wet lab results that the expression yield of Docs has raised with tagging by GST.
+
The expression of Dockerin and Cohesin modules individually has been proven to yield low expression and very unstable proteins that are degraded upon expression, which hinders any attempts of producing any type of the modules alone.  
  
−
<p style=" font-weight: bold; font-size:14px;"> 1. Dry Lab </p>
+
Previous experiments proposed the expression of the Doc module in E. Coli fused with different large protein domains, which seemed to produce highly stable Dockerin that is soluble and acquired increased functionality regarding binding to the Cohesin module. Thus, we decided to test the expression GST tag and compare it to that expressed with His, to see if the fusion with GST would fit the theory and increase the yield and stability of DocS.
  
−
<p style=" font-weight: bold; font-size:12px;"> 1.1. Modeling </p>
+
We started by optimizing the sequence to fit the expression in E-coli. and added different both wet and dry lab characterization for Docs on the registry. The wet lab characterization was done by different methods such as Agarose gel electrophoresis, SDS PAGE, transformation efficiency, affinity chromatography, and Bradford assay.  
  
−
Docs has been tagged with GST and His for purification and increasing the yield by the GST tag. then the model designed by several tools to get the best model.
+
The Dry Lab results proved the theory as the binding affinity of GST-DocS to Cohesin was higher than that of His-DocS, moreover, wet lab results supported those results as the expression yield of Docs increased upon tagging by GST and successfully bound our expressed Cohesin and initiated the awaited signaling in our systems, So in conclusion, individual expression of the module could be carried out by this method and the Doc/Coh modules can be used by future iGEM teams for signaling purposes in any pathway that aims to target different diseases.
  
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<p style=" font-weight: bold; font-size:12px;"> Docs-GST </p>
+
 
 +
===Dry Lab Characterization===
 +
<html>
 +
Our dry lab work was to validate and predict the wet-lab results. This validation also helps in reducing experimental trials and only focuses on promising ones.  According to Benchmarking, we chose four tools for modeling, and the best models were chosen according to quality assessment parameters found in JSON files of the Swiss Model quality assessment ranking (please refer to our <a href="https://2022.igem.wiki/cu-egypt/ProteinModelling.html">Modeling page</a>.</p>)
 +
 
 +
 
 +
<p style=" font-weight: bold; font-size:14px;"> 1.1. Modeling </p>
 +
 
 +
Assembly of Docs was done with both GST and His tage to predict the stability of the protein upon fusion with the tag, then the models were built by several tools ab-initio-based and template-based modeling tools. the acquired models were ranked by Our created ranking code to get the best model For more information, please refer to our <a href="https://2022.igem.wiki/cu-egypt/ProgrammingClub.html">Programming club page code under the name of Modric.</a>.</p>
 +
 
 +
 
 +
<p style=" font-weight: bold; font-size:14px;"> GST-Docs </p>
  
 
<html>
 
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</html>
 
</html>
  
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                  Figure 1.: Predicted 3D structure of Docs-GST designed by RosettaFold tool.
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                Figure 1.: Predicted 3D structure of GST-Docs designed by RosettaFold tool displayed by Pymol.
  
  
 
<html>
 
<html>
−
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/doc-gst-score.png" style="margin-left:200px;" alt="" width="500" /></p>
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<style>
 +
table, th, td {
 +
  border:1px solid black; margin-left:auto;margin-right:auto;
 +
}
 +
</style>
 +
<body>
 +
<table style="width:65%">
 +
<table>
 +
  <tr>
 +
    <th>cbeta_deviations</th>
 +
    <th>clashscore</th>
 +
    <th>molprobity</th>
 +
    <th>ramachandran_favored</th>
 +
    <th>ramachandran_outliers</th>
 +
    <th>Qmean_4</th>
 +
    <th>Qmean_6</th>
 +
  </tr>
 +
  <tr>
 +
    <td>0</td>
 +
    <td>182.87</td>
 +
    <td>2.72</td>
 +
    <td>98.25</td>
 +
    <td>0.7</td>
 +
    <td>0.75816</td>
 +
    <td>1.025826</td>
 +
  </tr>
 +
</table>
 +
</body>
 
</html>
 
</html>
  
−
                                Table 1.: QA scores by SWISS model tool of Docs-GST structure.
 
  
 +
                              Table 1.: QA scores by SWISS model tool of GST-DocS structure.
  
  
−
 
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<p style=" font-weight: bold; font-size:14px;"> His-Docs </p>
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<p style=" font-weight: bold; font-size:12px;"> Docs-His </p>
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<html>
 
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</html>
 
</html>
  
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                      Figure 2.: Predicted 3D structure of Docs-His designed by TRrosetta tool.
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                  Figure 2.: Predicted 3D structure of His-Docs designed by TRrosetta tool displayed by Pymol.
  
  
 
<html>
 
<html>
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<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/doc-his-score.png" style="margin-left:200px;" alt="" width="500" /></p>
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<style>
 +
table, th, td {
 +
  border:1px solid black; margin-left:auto;margin-right:auto;
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}
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</style>
 +
<body>
 +
<table style="width:65%">
 +
<table>
 +
  <tr>
 +
    <th>cbeta_deviations</th>
 +
    <th>clashscore</th>
 +
    <th>molprobity</th>
 +
    <th>ramachandran_favored</th>
 +
    <th>ramachandran_outliers</th>
 +
    <th>Qmean_4</th>
 +
    <th>Qmean_6</th>
 +
  </tr>
 +
  <tr>
 +
    <td>1</td>
 +
    <td>2.53</td>
 +
    <td>1.69</td>
 +
    <td>85.33</td>
 +
    <td>1.33</td>
 +
    <td>-1.68577</td>
 +
    <td>-1.79068</td>
 +
  </tr>
 +
</table>
 +
</body>
 
</html>
 
</html>
  
−
                              Table 2.: QA scores by SWISS model tool of Docs-His structure.
 
  
  
 +
                              Table 2.: QA scores by SWISS model tool of His-Docs structure.
  
  
−
<p style=" font-weight: bold; font-size:12px;"> 1.2. Docking </p>
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<p style=" font-weight: bold; font-size:14px;"> 1.2. Docking </p>
 +
<html>
 +
The docking results showed that the fusion of GST to DocS increased its binding affinity score to Coh2 more than without the GST. Illustrating that GST increases the contact between both proteins. In addition, Galaxy and ClusPro docking results showed that the affinity when GST is fused to DocS is better than when fused to Coh2, this may be due to decreasing the overall non-interacting surface of the protein and consequently increasing the affinity. So, we ordered the four parts (His-DocS, GST-DocS, His-Coh2, GST-DocS) to prove our theory experimentally.
  
−
Tagged Docs with GST and His has been docked with Coh2 tagged with GST and His by different tools to get the best model. Best docked structures were retrieved from ClusPro and Galaxy.
 
  
 +
All of the docking results were ranked using our code for calculating the binding affinity based on PRODIGY (please refer to our <a href="https://2022.igem.wiki/cu-egypt/ProgrammingClub.html">Programming club page a code under the name of son</a>.</p>
  
  
−
<p style=" font-weight: bold; font-size:12px;"> Docs-GST VS Coh-His by Cluspro </p>
 
  
 +
<p style=" font-weight: bold; font-size:14px;"> GST-Docs VS His-Coh by Cluspro </p>
  
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<html>
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<htchrome-extension://cbnaodkpfinfiipjblikofhlhlcickei/assets/images/logo/256.pngml>
 
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/gst-docs-his-coh-cluspro.png" style="margin-left:200px;" alt="" width="500" /></p>
 
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/gst-docs-his-coh-cluspro.png" style="margin-left:200px;" alt="" width="500" /></p>
 
</html>
 
</html>
  
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                  Figure 3.: Docked structure of Docs-GST VS Coh2-His designed by Cluspro.
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                Figure 3.: Docked structure of GST-Docs VS His-Coh2 designed by Cluspro displayed by Pymol.
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+
  
  
 +
<p style=" font-weight: bold; font-size:14px;"> GST-Docs VS His-Coh2 by Galaxy </p>
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/switches/gst-docs-galaxy.png" style="margin-left:200px;" alt="" width="500" /></p>
 +
</html>
  
 +
                Figure 4.: Docked structure of GST-Docs VS His-Coh2 designed by Galaxy visualized by Pymol.
  
 +
 +
 +
<p style=" font-weight: bold; font-size:14px;"> His-Docs VS GST-Coh by ClusPro </p>
 +
 +
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/gst-coh2-dochis-cluspro.png" style="margin-left:200px;" alt="" width="500" /></p>
 +
</html>
 +
 +
                    Figure 5.: Docked structure of His-Docs VS GST-Coh2 designed by ClusPro visualized by Pymol.
 +
 +
 +
 +
<p style=" font-weight: bold; font-size:14px;"> His-Docs VS GST-Coh2 by Galaxy </p>
 +
 +
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/gst-coh2-dochis-galaxy.png" style="margin-left:200px;" alt="" width="500" /></p>
 +
</html>
 +
 +
                  Figure 6.: Docked structure of His-Docs VS GST-Coh2 designed by Galaxy visualized by Pymol.
 +
 +
 +
<p style=" font-weight: bold; font-size:14px;"> Binding energies of Docs VS Coh2 </p>
 +
 +
<html>
 +
<style>
 +
table, th, td {
 +
  border:1px solid black; margin-left:auto;margin-right:auto;
 +
}
 +
</style>
 +
<body>
 +
<table style="width:40%">
 +
<table>
 +
  <tr>
 +
    <th>Binnding affinities of DocS Vs Coh2 docking (kcal/mol)</th>
 +
  </tr>
 +
  <tr>
 +
    <th>Model</th>
 +
    <th>Galaxy</th>
 +
    <th>Cluspro</th>
 +
  </tr>
 +
  <tr>
 +
    <th>GST_Coh2 vs His_DocS</th>
 +
    <td>-13.153</td>
 +
    <td>-11.635</td>
 +
  </tr>
 +
  <tr>
 +
    <th>GST_DocS vs His_Coh2</th>
 +
    <td>-13.488</td>
 +
    <td>-14.026</td>
 +
  </tr>
 +
</table>
 +
</body>
 +
</html>
 +
 +
              Table 3.: Binding energies of Docs VS Coh2 tagged with GST and His docked using Galaxy and ClusPro.
 +
 +
<p style=" font-weight: bold; font-size:14px;"> 1. Functional Parameters </p>
 +
 +
<html>
 +
<style>
 +
table, th, td {
 +
  border:1px solid black; margin-left:auto;margin-right:auto;
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}
 +
</style>
 +
<body>
 +
<table style="width:20%">
 +
<table>
 +
  <tr>
 +
    <th>PI</th>
 +
    <td>5.30</td>
 +
  </tr>
 +
  <tr>
 +
    <th>Molecular Weight</th>
 +
    <td>16751.19 Da</td>
 +
  </tr>
 +
</table>
 +
</body>
 +
</html>
 +
 +
===Wet Lab Results===
 +
As we investigated the literature, we found that the Docs part yields little amount due to its suitability to proteolytic attack. Hence we tried to configure its expression by adding two different tags and followed this pipeline to prove our concept experimentally: we started with cloning in the pJET vector followed by the expression in the pGS-21a, then we performed two different kinds of lysis to extract the protein to find which lysis buffer will give better yield, and quantified the protein expression before and after induction using BCA assay. Ultimately, we tested the His-Doc affinity by the pulldown assay against the GST-Coh and GST Doc against His Coh.
 +
 +
<p style=" font-weight: bold; font-size:14px;"> Results of His-DocS </p>
 +
<p style=" font-weight: bold; font-size:14px;"> Ligation of His Doc with pJET cloning vector </p>
 +
We used T4 ligase to ligate His Doc with pJET cloning vector, so we incubated His Doc with pJET overnight at 15°C.
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/wetlab-results/ligation-his-doc.png" style="margin-left:200px;" alt="" width="500" /></p>
 +
</html>
 +
              Figure 4. This figure shows the ligation between His Doc and pJET, Results show the size of the
 +
                                the ligated plasmid is 3372 bp, as expected.
 +
<html>
 +
<p style=" font-weight: bold; font-size:14px;"> Transformation of His Doc in DH-5 alpha using pJET cloning vector </p>
 +
The transformation was done using the TSS buffer protocol, after trying three buffers which are Calcium chloride, Magnesium chloride, and a combination between Calcium chloride and Magnesium chloride, we optimized our protocol to use the TSS buffer protocol as it showed the best results with a transformation efficiency of His DOC in DH-5 alpha using pJET vector is 8.61×10<sup>4</sup> transformants/μg while in BL-21a using pGS-21a vector is 5×10<sup>3</sup> transformants/μg you can find the complete protocol optimization in our <a href="https://2022.igem.wiki/cu-egypt/ProtocolOptimization.html wiki page">Optimziation page.</a>.</p>.
 +
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/wetlab-results/his-doc-pjet.jpg" style="margin-left:200px;" alt="" width="500" /></p>
 +
</html>
 +
                      Figure 5. The transformed plate of His Doc + pJET using TSS buffer protocol
 +
 +
<p style=" font-weight: bold; font-size:14px;"> Transformation of His Doc in BL-21 using pGS-21a expression vector </p>
 +
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/wetlab-results/his-doc-pgs.jpg" style="margin-left:200px;" alt="" width="500" /></p>
 +
</html>
 +
                                        Figure 6. The transformed plate of His Doc + pGS-21a
 +
<p style=" font-weight: bold; font-size:14px;"> Affinity chromatography results for His Doc </p>
 +
Affinity chromatography is a technique to purify the protein to get the protein alone without the cell lysate. So, we performed affinity chromatography for total protein extraction to get pure His Doc to characterize it before the pull-down assay.
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/wetlab-results/standard-curve.jpg" style="margin-left:200px;" alt="" width="500" /></p>
 +
</html>
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/wetlab-results/affinity-of-his-doc.png" style="margin-left:200px;" alt="" width="500" /></p>
 +
</html>
 +
        Figure 7. This figure shows the BCA assay results of affinity chromatography for His Doc, As shown from the graph,
 +
          E1 of His Doc purified is higher than E2, meaning we purified our protein successfully.
 +
<p style=" font-weight: bold; font-size:14px;"> Comparison between chemical lysis and sonication for His DOC </p>
 +
We used two protein extraction methods: chemical lysis (chemical method) and sonication (physical method) to check which method is more effective for extracting His Doc. After we had the results, we optimized our protocol to use chemical lysis for His Doc
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/data-analysis/sonication-or-chemical/sonication-or-chemical/his-docs.jpg" style="margin-left:200px;" alt="" width="500" /></p>
 +
</html>
 +
                  Figure 8. This graph shows the difference between chemical lysis and sonication for His Doc.
 +
                     
 +
<p style=" font-weight: bold; font-size:14px;"> SDS PAGE for induced and non-induced samples of His Doc </p>
 +
SDS-PAGE depends on the molecular weight of the protein. We performed SDS-PAGE to ensure that our protein is in the exact size and to show the difference between induced and non-induced samples of His Doc.
 +
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/wetlab-results/hisdoc.jpg" style="margin-left:200px;" alt="" width="500" /></p>
 +
</html>
 +
            Figure 9. This figure shows the comparison between induced and non-induced samples of His Doc where well no.2 is
 +
            the non-induced sample, while well no.4 is the induced sample showing that our protein is induced effectively
 +
                            owing to our right choice of IPTG, time interval, and concentration
 +
<p style=" font-weight: bold; font-size:14px;"> Pull-down assay of His Coh with GST Doc and His Doc with GST Coh </p>
 +
Pull-down assay is a one-step technique used to test protein-protein interaction. Pull-down was performed to check and compare the interaction between His Doc against GST Coh and His Coh against GST Doc.
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/wetlab-results/coh-vs-doc.jpg" style="margin-left:200px;" alt="" width="500" /></p>
 +
</html>
 +
              Figure 10. This graph illustrates that the binding between His Doc with GST Coh is more stable than that
 +
                                                of His Coh with GST Doc.
  
 
===Reference===
 
===Reference===
−
[1] BARAK Y, HANDELSMAN T, NAKAR D, et al. Matching fusion protein systems for affinity analysis of two interacting families of proteins: the cohesin-dockerin interaction [J]. J Mol Recognit, 2005, 18(6): 491-501.
+
[1] BARAK Y, HANDELSMAN T, NAKAR D, et al. Matching fusion protein systems for affinity analysis of two interacting families of proteins: the cohesin-dockerin interaction [J]. J Mol Recognit, 2005, 18(6): 491-501.
 +
 
 +
[2] Kazutaka Sakka, Yuka Sugihara, Sadanari Jindou, Makiko Sakka, Minoru Inagaki, Kazuo Sakka, Tetsuya Kimura, Analysis of cohesin–dockerin interactions using mutant dockerin proteins, FEMS Microbiology Letters, Volume 314, Issue 1, January 2011, Pages 75–80, https://doi.org/10.1111/j.1574-6968.2010.02146.x
 +
 
 +
[3] Lawrie, J., Song, X., Niu, W., & Guo, J. (2018). A high throughput approach for the generation of orthogonally interacting protein pairs. Scientific Reports, 8. https://doi.org/10.1038/s41598-018-19281-6
 +
 
 +
[4] Wojciechowski, M., Różycki, B., Huy, P. D. Q., Li, M. S., Bayer, E. A., & Cieplak, M. (2018). Dual binding in cohesin-dockerin complexes: the energy landscape and the role of short, terminal segments of the dockerin module. Scientific reports, 8(1), 1-14.
 +
 
 +
 
  
  

Latest revision as of 03:28, 14 October 2022


DocS

The Coch2 module binds DocS (BBa_K3396000) modules constitutively.

Usage and Biology

The DocS[1] module comes from The C. thermocellum scaffoldin and it could recognize and bind tightly to complementary Coh2 modules. The Coh2–DocS pair represents the interaction between two complementary families of protein modules that exhibit divergent specificities and affinities, ranging from one of the highest known affinity constants between two proteins to relatively low-affinity interactions.


Sequence and Features


Assembly Compatibility:
  • 10
    COMPATIBLE WITH RFC[10]
  • 12
    COMPATIBLE WITH RFC[12]
  • 21
    COMPATIBLE WITH RFC[21]
  • 23
    COMPATIBLE WITH RFC[23]
  • 25
    COMPATIBLE WITH RFC[25]
  • 1000
    COMPATIBLE WITH RFC[1000]


Contribution by CU_Egypt team 2022

DocS (Dockerin) is a cellulolytic enzyme in Clostridium thermocellum. Each cellulosomal enzyme has one or more catalytic modules as well as a single dockerin module. The scaffolding is multifunctional, with the nine Cohesin modules integrating nine dockerin-bearing enzymes into the complex and the carbohydrate-binding enzymes. The complex is bound to the cellulosic substrate by the Cellulose Binding Domain (CBM), and the C-terminal dockerin module is implicated in this process. The interaction between Cohesin and Dockerin happens in two different forms, called the dual binding mode, in a calcium-dependent manner due to the presence of a calcium-binding site in the dockerin protein.

The expression of Dockerin and Cohesin modules individually has been proven to yield low expression and very unstable proteins that are degraded upon expression, which hinders any attempts of producing any type of the modules alone.

Previous experiments proposed the expression of the Doc module in E. Coli fused with different large protein domains, which seemed to produce highly stable Dockerin that is soluble and acquired increased functionality regarding binding to the Cohesin module. Thus, we decided to test the expression GST tag and compare it to that expressed with His, to see if the fusion with GST would fit the theory and increase the yield and stability of DocS.

We started by optimizing the sequence to fit the expression in E-coli. and added different both wet and dry lab characterization for Docs on the registry. The wet lab characterization was done by different methods such as Agarose gel electrophoresis, SDS PAGE, transformation efficiency, affinity chromatography, and Bradford assay.

The Dry Lab results proved the theory as the binding affinity of GST-DocS to Cohesin was higher than that of His-DocS, moreover, wet lab results supported those results as the expression yield of Docs increased upon tagging by GST and successfully bound our expressed Cohesin and initiated the awaited signaling in our systems, So in conclusion, individual expression of the module could be carried out by this method and the Doc/Coh modules can be used by future iGEM teams for signaling purposes in any pathway that aims to target different diseases.


Dry Lab Characterization

Our dry lab work was to validate and predict the wet-lab results. This validation also helps in reducing experimental trials and only focuses on promising ones. According to Benchmarking, we chose four tools for modeling, and the best models were chosen according to quality assessment parameters found in JSON files of the Swiss Model quality assessment ranking (please refer to our Modeling page.

)

1.1. Modeling

Assembly of Docs was done with both GST and His tage to predict the stability of the protein upon fusion with the tag, then the models were built by several tools ab-initio-based and template-based modeling tools. the acquired models were ranked by Our created ranking code to get the best model For more information, please refer to our Programming club page code under the name of Modric..

GST-Docs 

                Figure 1.: Predicted 3D structure of GST-Docs designed by RosettaFold tool displayed by Pymol.


cbeta_deviations clashscore molprobity ramachandran_favored ramachandran_outliers Qmean_4 Qmean_6
0 182.87 2.72 98.25 0.7 0.75816 1.025826 


                              Table 1.: QA scores by SWISS model tool of GST-DocS structure.


His-Docs 

                 Figure 2.: Predicted 3D structure of His-Docs designed by TRrosetta tool displayed by Pymol.


cbeta_deviations clashscore molprobity ramachandran_favored ramachandran_outliers Qmean_4 Qmean_6
1 2.53 1.69 85.33 1.33 -1.68577 -1.79068 


                              Table 2.: QA scores by SWISS model tool of His-Docs structure.


1.2. Docking

The docking results showed that the fusion of GST to DocS increased its binding affinity score to Coh2 more than without the GST. Illustrating that GST increases the contact between both proteins. In addition, Galaxy and ClusPro docking results showed that the affinity when GST is fused to DocS is better than when fused to Coh2, this may be due to decreasing the overall non-interacting surface of the protein and consequently increasing the affinity. So, we ordered the four parts (His-DocS, GST-DocS, His-Coh2, GST-DocS) to prove our theory experimentally. All of the docking results were ranked using our code for calculating the binding affinity based on PRODIGY (please refer to our Programming club page a code under the name of son.

GST-Docs VS His-Coh by Cluspro 

               Figure 3.: Docked structure of GST-Docs VS His-Coh2 designed by Cluspro displayed by Pymol.


GST-Docs VS His-Coh2 by Galaxy 

                Figure 4.: Docked structure of GST-Docs VS His-Coh2 designed by Galaxy visualized by Pymol.


His-Docs VS GST-Coh by ClusPro 


                   Figure 5.: Docked structure of His-Docs VS GST-Coh2 designed by ClusPro visualized by Pymol.


His-Docs VS GST-Coh2 by Galaxy 


                  Figure 6.: Docked structure of His-Docs VS GST-Coh2 designed by Galaxy visualized by Pymol.


Binding energies of Docs VS Coh2

Binnding affinities of DocS Vs Coh2 docking (kcal/mol)
Model Galaxy Cluspro
GST_Coh2 vs His_DocS -13.153 -11.635
GST_DocS vs His_Coh2 -13.488 -14.026 

             Table 3.: Binding energies of Docs VS Coh2 tagged with GST and His docked using Galaxy and ClusPro.

1. Functional Parameters

PI 5.30
Molecular Weight 16751.19 Da

Wet Lab Results

As we investigated the literature, we found that the Docs part yields little amount due to its suitability to proteolytic attack. Hence we tried to configure its expression by adding two different tags and followed this pipeline to prove our concept experimentally: we started with cloning in the pJET vector followed by the expression in the pGS-21a, then we performed two different kinds of lysis to extract the protein to find which lysis buffer will give better yield, and quantified the protein expression before and after induction using BCA assay. Ultimately, we tested the His-Doc affinity by the pulldown assay against the GST-Coh and GST Doc against His Coh.

Results of His-DocS

Ligation of His Doc with pJET cloning vector

We used T4 ligase to ligate His Doc with pJET cloning vector, so we incubated His Doc with pJET overnight at 15°C. 

              Figure 4. This figure shows the ligation between His Doc and pJET, Results show the size of the 
                               the ligated plasmid is 3372 bp, as expected.

Transformation of His Doc in DH-5 alpha using pJET cloning vector

The transformation was done using the TSS buffer protocol, after trying three buffers which are Calcium chloride, Magnesium chloride, and a combination between Calcium chloride and Magnesium chloride, we optimized our protocol to use the TSS buffer protocol as it showed the best results with a transformation efficiency of His DOC in DH-5 alpha using pJET vector is 8.61×104 transformants/μg while in BL-21a using pGS-21a vector is 5×103 transformants/μg you can find the complete protocol optimization in our Optimziation page..

. 

                      Figure 5. The transformed plate of His Doc + pJET using TSS buffer protocol

Transformation of His Doc in BL-21 using pGS-21a expression vector 

                                       Figure 6. The transformed plate of His Doc + pGS-21a

Affinity chromatography results for His Doc

Affinity chromatography is a technique to purify the protein to get the protein alone without the cell lysate. So, we performed affinity chromatography for total protein extraction to get pure His Doc to characterize it before the pull-down assay. 

        Figure 7. This figure shows the BCA assay results of affinity chromatography for His Doc, As shown from the graph, 
         E1 of His Doc purified is higher than E2, meaning we purified our protein successfully.

Comparison between chemical lysis and sonication for His DOC

We used two protein extraction methods: chemical lysis (chemical method) and sonication (physical method) to check which method is more effective for extracting His Doc. After we had the results, we optimized our protocol to use chemical lysis for His Doc 

                  Figure 8. This graph shows the difference between chemical lysis and sonication for His Doc.

SDS PAGE for induced and non-induced samples of His Doc

SDS-PAGE depends on the molecular weight of the protein. We performed SDS-PAGE to ensure that our protein is in the exact size and to show the difference between induced and non-induced samples of His Doc. 

           Figure 9. This figure shows the comparison between induced and non-induced samples of His Doc where well no.2 is 
           the non-induced sample, while well no.4 is the induced sample showing that our protein is induced effectively 
                            owing to our right choice of IPTG, time interval, and concentration

Pull-down assay of His Coh with GST Doc and His Doc with GST Coh

Pull-down assay is a one-step technique used to test protein-protein interaction. Pull-down was performed to check and compare the interaction between His Doc against GST Coh and His Coh against GST Doc. 

              Figure 10. This graph illustrates that the binding between His Doc with GST Coh is more stable than that 
                                                of His Coh with GST Doc.

Reference

[1] BARAK Y, HANDELSMAN T, NAKAR D, et al. Matching fusion protein systems for affinity analysis of two interacting families of proteins: the cohesin-dockerin interaction [J]. J Mol Recognit, 2005, 18(6): 491-501.

[2] Kazutaka Sakka, Yuka Sugihara, Sadanari Jindou, Makiko Sakka, Minoru Inagaki, Kazuo Sakka, Tetsuya Kimura, Analysis of cohesin–dockerin interactions using mutant dockerin proteins, FEMS Microbiology Letters, Volume 314, Issue 1, January 2011, Pages 75–80, https://doi.org/10.1111/j.1574-6968.2010.02146.x

[3] Lawrie, J., Song, X., Niu, W., & Guo, J. (2018). A high throughput approach for the generation of orthogonally interacting protein pairs. Scientific Reports, 8. https://doi.org/10.1038/s41598-018-19281-6

[4] Wojciechowski, M., Różycki, B., Huy, P. D. Q., Li, M. S., Bayer, E. A., & Cieplak, M. (2018). Dual binding in cohesin-dockerin complexes: the energy landscape and the role of short, terminal segments of the dockerin module. Scientific reports, 8(1), 1-14.