Difference between revisions of "Team:Technion Israel/Collaborations"
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importance of integrating a linker when fusing the proteins together. We would like to express our | importance of integrating a linker when fusing the proteins together. We would like to express our | ||
gratitude to the Aachen iGEM team for the valuable scientific work they have done for us. | gratitude to the Aachen iGEM team for the valuable scientific work they have done for us. | ||
| − | For more information please go to <a href="https://2016.igem.org/Team:Aachen">Aachen iGEM team’s Wiki page</a> | + | For more information please go to <a href="https://2016.igem.org/Team:Aachen">Aachen iGEM team’s Wiki page</a> |
</p> | </p> | ||
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Revision as of 13:04, 17 October 2016
Peshawar – Tutoring the first Pakistani team
Introduction
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
Introduction
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 came to the conclusion 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 photocaged serine as part of their project.
To do so we met with Prof. Meytal Landau (see: Attribution)
from the faculty of Biology at the Technion who provided information regarding different visualization tools available to aid us in this.
As we tried to simulate the photocaged serine ourselves using the Chemdraw software we encountered a few
obstacles. In order to overcome these obstacles, we contacted Einav Tayab-Fligelman, from Prof. Landau's
lab, whom kindly provided us with a PDB file with a visualization of the Photocaged serine.
Furthermore, we contacted Dr. Fabian Glaser (see: Attribution)
seeking assistance with the structure prediction. Dr. Glaser informed us that it would be impossible to
receive a credible result within the short timeframe available. As an alternative he suggested writing
a document describing the steps for an exhaustive computational work, including insights from the comparison
of the structures of Subtilisin E and the photocaged serine.
Finally we created a 3D visualization of Subtilisin E adjacent to the photocaged serine along with the suggested document.
Dr. Glaser was kind enough to proofread and give his scientific remarks (View PDF).
The inevitable conclusion of the document was that the mutated Subtilisin E would not fold to the right tertiary
structure. This information 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.
The work made by Aachen has a major significance to our project and it gives decisive evidence to the importance of integrating a linker when fusing the proteins together. 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
Introduction
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.
BGU - Prediction of chemoreceptor-ligand interactions
Introduction
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.
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