Difference between revisions of "Team:Technion Israel/Collaborations"

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also consisted of an expression backbone- Promoter and RBS <a href="http://parts.igem.org/Part:BBa_J04500" ><b>(J04500)</b></a> and a terminator <a href="http://parts.igem.org/Part:BBa_B0015" ><b>(B0015)</b></a>.
 
also consisted of an expression backbone- Promoter and RBS <a href="http://parts.igem.org/Part:BBa_J04500" ><b>(J04500)</b></a> and a terminator <a href="http://parts.igem.org/Part:BBa_B0015" ><b>(B0015)</b></a>.
 
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<img src="https://static.igem.org/mediawiki/2016/5/57/T--Technion_Israel--AachenFig1.jpg" class="img-responsive img-center img-cont" style="cursor: pointer;"><br>
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<p class="text-center"><b>Fig. 1:</b> The expression system which was constructed by the Aachen iGEM team,
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containing the Tar-GFP fusion. The current expression system does not include a linker.</p>
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After building the expression system with the Tar receptor fused to GFP, the plasmid was transformed
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to a BL21 E. coli strain. To validate the expression, the cloned bacteria were tested in a Tecan plate
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reader and under a fluorescent microscope.<br>
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GFP signal was detected on the polar part of the membrane only in a small fraction of cells. The majority
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of bacteria showed fluorescence in the entire volume of the cell, an indication of the accumulation of the
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Tar receptor inside the cell, probably due to an impaired structure of the protein (Fig. 2).
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<img src="https://static.igem.org/mediawiki/2016/0/08/T--Technion_Israel--AachenFig2a.PNG" class="img-responsive img-center img-cont" width="350" height="350" style="cursor: pointer;"><br>
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<p class="text-center"><b>Fig. 2:</b> Fluorescent microscope results.</p>
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Revision as of 19:04, 18 October 2016

S.tar, by iGEM Technion 2016

S.tar, by iGEM Technion 2016


Peshawar – Tutoring the first Pakistani team

We provided guidance to iGEM Peshawar, the first team to represent Pakistan. We assisted them with various aspects of Mathematical Modelling, Human Practice and cloning.

An opportunity for collaboration unveiled itself when we learned that the Pakistani team from Peshawar University is focusing on detection as a project. During the initial conversation we were amazed to learn that said group is the first Pakistani team to compete in iGEM, thus they were in need of guidance with most aspects of the competition. We decided to aid them and share all the knowledge and experience that was accumulated in our project and in past Technion iGEM teams. To achieve this, we used different platforms for communications mainly a Facebook group, where the Peshawar team could get an immediate answer to any question they had, and multiple Skype sessions each with a different focus such as mathematical modeling, Human practices, Cloning and more.


Mathematical modeling

We aided in the modeling process of Peshawar’s system, specifically using differential equations and logic gates. The aim of the model was to predict the expression of the reporter protein as a function of the inducers’ concentration (View PDF).


Cloning

The Peshawar team had issues with the plasmid transformations into competent cells. After we got a full report on the exact steps they followed, we helped debugging their protocol.
We also shared our protocols of chemical transformation and competent cells preparation with them.
These instructions helped the team overcome their obstacles and proceed with the project.

Human practices

We shared the layout of our educational program with Peshawar. Moreover, we advised the team regarding an appeal to the government with a request to promote the education in the field of Synthetic Biology.



Aachen- Prediction of mutated Subtilisin E protease

We met with experts from the Technion to help us visualize the Subtilisin E and the photocaged serine in order to obtain insights regarding the structure of the mutated protein.

We contacted iGEM Aachen when we learned their project deals with protein inactivation, as we believed it might correspond with our Intein sub-project. After discussing the details, we concluded that the Intein protein would not be applicable to Aachen's system. Nevertheless, we decided to collaborate on different aspects of our projects.

iGEM Aachen asked us to visualize and model the structure of the Subtilisin E protease, which is mutated with a photo caged serine as part of their project.
After consulting with several professors from the faculty of Biology, we concluded that it would be impossible to finish this task properly in our period. As an alternative, we wrote a document describing the steps for an exhaustive computational work, including insights from the comparison of the structures of Subtilisin E and the photo-caged serine. (View PDF).
Finally, we constructed a 3D visualization of Subtilisin E adjacent to the photo-caged serine along with the above document. The information we have obtained was highly valuable and helpful to Aachen’s project.


In return, we asked Aachen to build a biobrick consisting of the Tar chemoreceptor fused to a GFP marker. We provided them all the information necessary for this task (View PDF). One of the greatest challenges in forming a fusion is finding the right linker which is meant to bridge between the proteins and assure that the proteins fold in a correct manner. Since we had some trouble finding the right linker, the Aachen team suggested to fuse the Tar to the GFP without a linker. The Tar (K777000) and the GFP (E0040) biobricks were obtained from the iGEM kit. The expression system constructed by the Aachen iGEM team, also consisted of an expression backbone- Promoter and RBS (J04500) and a terminator (B0015).


Fig. 1: The expression system which was constructed by the Aachen iGEM team, containing the Tar-GFP fusion. The current expression system does not include a linker.

After building the expression system with the Tar receptor fused to GFP, the plasmid was transformed to a BL21 E. coli strain. To validate the expression, the cloned bacteria were tested in a Tecan plate reader and under a fluorescent microscope.

GFP signal was detected on the polar part of the membrane only in a small fraction of cells. The majority of bacteria showed fluorescence in the entire volume of the cell, an indication of the accumulation of the Tar receptor inside the cell, probably due to an impaired structure of the protein (Fig. 2).

Fig. 2: Fluorescent microscope results.

Aachen's work was successful, providing us with a valuable result on the importance of a linker domain to connect the Tar receptor and the GFP marker. The work made by Aachen had a major significance to our project and We would like to express our gratitude to the Aachen iGEM team for the valuable scientific work they have done for us.
For more information please go to Aachen iGEM team’s Wiki page


TU Eindhoven - Writing a manual for the Rosetta software

We have written a manual for the operation of the Rosetta software together with iGEM TU Eindhoven.

Our collaboration with iGEM Eindhoven was a result from the challenges we faced using the Rosetta software suite in our project. When we took our very first steps with protein modeling using Rosetta we quickly discovered numerous problems and difficulties that occupied us for weeks before we even started using the software.

During our work, we realized how fast the process could have been if there was a guide detailing the necessary resources and steps needed for a complete beginner in Rosetta. We figured that this might be one of the reasons why so few iGEM teams have used Rosetta in the past despite its vast capabilities.

After getting great results from the software, we decided to share our experience and write this guide ourselves so that future iGEM teams can have a better starting point. We were delighted to find that we are not the only team using Rosetta this year and so we contacted iGEM Eindhoven and asked for their help with the guide. Their work on the guide – writing, sharing their protocols and experience was a valuable contribution that made the guide much more informative and comprehensive than we initially expected.Click here to see the full guide




BGU - Prediction of chemoreceptor-ligand interactions

We processed potential variants of chemoreceptors for iGEM BGU using the Rosetta software.

We have used the Rosetta software in order to predict protein structure and to check for ligand-protein interactions. Running the software and processing both the ligand binding domain (LBD) of the Tar chemoreceptor and BGU's substances of interest - Protocatechuic acid and Ethylene glycol, yielded dozens of LBD variants.
After the filtering process, a library of variants which should theoretically serve as attractant chemoreceptors, was obtained.

Fig. 1: 3D imaging of the variants in the library with the native receptor (wild type), each color represents a different variant.



< S.tar, by iGEM Technion 2016