We were lucky enough to run into several teams this iGEM cycle who were working on similar projects. The common ground allowed us to discuss, learn and benefit from each other. In two instances, this moved beyond a collaboration into a richer relationship - where our teams worked extensively together over multiple aspects of the project.
Team Virginia
We partnered with iGEM team Virginia throughout this iGEM season. Team Virginia has been working on developing a diagnostic kit for
atherosclerosis, by expressing antibodies using the SHuffle E.coli strain. Since both our projects involved healthcare and the same chassis
for antibody production, we decided it would be a great opportunity to learn from them and help out in any way we could. We collaborated
extensively in terms of Wet Lab, Dry Lab and Human Practices.
Wet Lab
Since both the teams were using the same chassis - SHuffle E.coli - we decided to collaborate on finding the most efficient way to use the same.SHuffle E.coli is an engineered strain that was created to be able to produce complex, disulfide-bonded proteins cytoplasmically. The strain's oxidative cytoplasm results from mutations made in reductive pathways (trx-, gor-); alternate reductive pathways (ahPc*) have been added to make the mutations non-lethal.
Additionally, the strain also expresses a disulfide-bond isomerase (DsbC) in its cytoplasm. The result is a platform that is modular and simple to genetically modify, and can be used to generate antibodies and fragments in a variety of forms with higher yields than periplasmic expression in other strains. It is an easy and manipulable system for the cheap production of complex proteins like antibodies.
SHuffle E.coli has never been used by any iGEM team before for the production of antibodies. Team Virginia has been working on making a diagnostic kit for Atherosclerosis with the use of full-length antibodies and scFvs produced in SHuffle E.coli. Similarly, we have been working on making therapeutic antibodies against Dengue with the same strain.
Our teams decided to collaborate with each other to design a document that can act like a manual for future iGEM Teams who decide to work with Shuffle, using the advice of our mentors, experts and our personal experience with the strain. This document can act as a troubleshooting guide for everyone experimenting with the strain.
The document includes analysis and instruction for the following protocols:
- Considerations for constructing devices in SHuffle
- Transformation methods for SHuffle
- Competency for SHuffle strains
- Electro Competency
- Protein Expression
- Protein Purification
- Harvesting
- Western Blot
More information on our Contributions
page.
Dry Lab
Our team and Team Virginia both hope that our products will, at some point, reach the market for public consumption. For this, it was necessary for us to come up with an optimised process for mass production in the SHuffle E.coli system. For this, we collaborated on conducting statistical Design of Experiments or DoE with Team Virginia.We compiled a list of all the factors that could possibly affect yield of the protein, and shortlisted some that we suspected would be most significant, with help from our mentors and various experts. We created statistically designed experiments to study the interactions between these factors and to identify the optimal values for production.
Our team chose the following parameters:
- Optical density (OD) at the time of induction
- IPTG (Inducer) Concentration
- Temperature
- Period of incubation (Time post-induction)
- Temperature of incubation
We ran SDS-PAGE Gels on cell lysate of experiments with chosen values of these factors, and used BSA standards on SDS-PAGE gels to quantify the yield of the protein.
The response surface plot of the relationship between temperature and time.
Detailed results are available on our Modelling page.
Human Practices and Education
We participated in a Podcast series organised by Team Virginia. The podcast hosted a special episode featuring our project and our team members speaking about their inspirational iGEM Projects in the Therapeutic and Manufacturing track. It was a great experience. We also co-authored a blogpost with Team Virginia. The blogpost talks about iGEM Competition and Synthetic Biology. We also touch up on Neglected Tropical Diseases (NTDs) since Dengue is one such NTD.Team MIT_MAHE
We were extremely lucky to meet Team MIT_MAHE at the All India iGEM Meet 2022. We were both Indian teams working with protein expression
and purification. Both teams were using similar plasmid vectors as well. Vibriosis is a bacterial disease primarily observed in marine,
estuarine, and occasionally, freshwater fish. It is caused by bacteria of the genus Vibrio and is a significant reason for mortality in
pisciculture operations. MIT_MAHE has been working on a small peptide therapeutic for the same.
Dry Lab
MIT_Mahe and our team collaborated extensively on the modelling part of our projects. We had access to supercomputing resources in the form of our institute's PARAM Brahma, which we utilised to help them run longer Molecular Dynamics simulations than their resources allowed, in addition to our own work.We also created an elaborate manual on how to use AlphaFold software for predicting protein structures along with one for running molecular dynamic simulations. Both the manuals act as a guide in understanding the technicalities, usage and guidelines on how to go about the entire process of running these models.
AlphaFold Manual
AlphaFold is a program developed by DeepMind, a subsidiary of Alphabet, which performs predictions of protein structure using artificial neural network. The program is designed as a deep learning system. AlphaFold has been instrumental in helping both of us predict the structures of the proteins we synthesised in our chassis. The manual has been divided into two parts, one for people who have supercomputing resources to use the AlphaFold software and one for those who do not have adequate computing resources. ColabFold, a fast and easy-to-use software for the prediction of protein structures and homo- and hetero-dimer complexes, can be used by everyone with basic computing resources.
Moleculer Dynamics Simulation Manual
A contribution from our team, we had help from Team MIT_MAHE to formulate this manual which speaks elaborately about the details and instructions for running Molecular Dynamics Simulations. Like the Structure prediction manual, this guidebook also contains different sections on how to use these simulations with or without supercomputing resources. More details are available on our Contributions page.
Wet Lab
Our teams used the prokaryotic E.coli chassis for expressing our proteins. However, while looking at different avenues and chassis for protein expression, we got the opportunity to explore many other systems which can be tried out to maximise and optimise protein production.Any future iGEM Team that aims to do protein expression and purification would benefit from checking out all the available options beforehand.
Human Practices
As a part of our Human Practices collaboration, our team and MIT_MAHE team organised a Biosafety Webinar. The aim of this webinar was to make the masses aware about the important Biosafety measures to be followed while working with synthetic biology in the real world.We invited Dr Vinod Jyothikumar to deliver this presentation. He has received his Ph.D. in Pharmaceutical & Bio-medical Sciences from Strathclyde University, Glasgow, UK, in 2010 and post-doctoral experience from the University of Guelph, Canada - 2011. He has executed various safety projects within research laboratories across reputed academic institutions in Europe, the US, and industry settings. It was an extremely fun and educational experience. We learnt a lot about Biosafety practices in the field of SynBio. The participants also got the opportunity to ask Dr Jyothikumar questions and clarify our doubts and misconceptions in the question-answer session.
MIT_MAHE also helped us by sharing our survey in their University and in their local area. This allowed us to obtain regional data from a different part of the country. MIT_MAHE were referred to doctors via the academia at Kasturba Medical College (KMC), a well-known hospital located in their city. They couldn't meet the KMC doctors directly due to the festival season, but interacted with a clinic doctor and an infectious disease doctor from Kerala for us. They helped us understand the disease from the point of view of the healthcare system.