In meeting with other iGEM teams for a collaboration or partnership, we found Team IISER Pune II. We realized we shared many common goals of our project in our first meeting, since we were both focused on creating antibodies and antibody fragments to bind to a particular biomarker. Throughout this partnership, we were able to gain some much-needed information about our chassis, E. coli SHuffle. We also showed them how to use resources such as ROSIE for protein modeling. Keep reading to learn more about our partnership.

Wet Lab
Wet Lab/Modeling DOE
Impact of our Parternship

Wet Lab

The wet lab portion of our partnership with IISER Pune II started off as troubleshooting collaboration about our BioBrick assembly and protein induction processes. Since we both utilized the E. coli SHuffle strain to produce antibodies (specifically IgGs, IgYs, scFvs, and VHHs), we had similar experimental designs. Hence, the natural step was to help each other troubleshoot protocols using this delicate strain. We found that it was difficult to locate proper documentation about many protocols for E. coli SHuffle as all the information was scattered across the internet. This, along with the increasing popularity of E. coli SHuffle for antibody production, led us to create a troubleshooting document on wet lab protocols specific for E. coli SHuffle for future iGEM teams to reference if they decide to use E. coli SHuffle. Our troubleshooting document is embedded below, but can also be found here.


Team Virginia and Team IISER Pune II shared the goal to synthesize antibodies and antibody fragments which bind to the biomarker of our respective diseases. Both of our teams planned to use protein modeling to determine which antibody had the strongest binding affinity to the biomarker. The parameters our teams considered included the orientation of each antibody/antibody fragment binding to the biomarker and the stability of the antibody/antibody fragments in different external conditions. In order to accomplish these more complex models, a structural model (i.e. a PDB file) of each antibody needed to be constructed.
Our team had experience using AlphaFold to generate monomer models and the ROSIE server to generate multimer and full sized IgG models, so we shared this knowledge with Team IISER Pune II. This became crucial to the success of their project as they needed to model the molecular dynamics and stability of their scFv. Simultaneously, Team IISER Pune II shared a novel statistical design, called "Design of Experiment" (DOE) in which multiple variables were altered to both minimize the number of experiments to be done and maximize the chance of finding the true ideal conditions with all variables present in the system. Both of these advantages proved to be useful over the conventional one-factor-at-a-time (OFAT) method our team was planning to use to evaluate the productivity of our antibody production.

Wet Lab/Modeling Design of Experiments (DOE) Partnership

After the initial introduction of the DOE modeling system, we both learned that this experiment can be expanded into a wet lab-modeling (Dry Lab as IISER Pune II refers to it as) DOE partnership. With their crucial expertise in DOE statistical analysis, we were able to evaluate the production of our antibodies and antibody fragments within the time and resources given to us. Specifically, it helps us determine optimal conditions such as incubation time and incubation temperature after induction so that our E. coli SHuffle can produce high yield of target protein. In exchange, we performed protein induction experiments with varying incubation times and temperatures with our McPC603 scFv. These inductions were verified with SDS-PAGE gels that specifically follow their protocol to avoid confounding variables in our experimental design. We provided this critical wet lab data to the IISER Pune II team so that they could expand their model to other antibodies other than their specific antibodies. This increases the accuracy and application of their model as the dataset is expanded. Gel images from our wet lab data are found in our Results page. After sending them our data, the results from their model are shown below.

Unfortunately, there was no statistical significance between any of the variables. Possible errors may arrive from low expression results from our vector in the first place, and inconsistent wet lab procedures. Further testing and experimental changes are needed to improve the model, in which we can improve the model significantly. For more information about this DOE partnership, see the IISER Pune II modeling page.


Our Education partnership with the IISER Pune 2 team began with the idea of a joint blog partnership. We created blogs about our project, iGEM, synthetic biology, and applications of synthetic biology in iGEM. These articles highlighted important lab/scientific techniques and equipment that were used to reach conclusions about these phenomenons. Other articles explained the field of synthetic biology and looked at it in the context of iGEM. The audience of the blog was high school students interested in STEM and therefore, we aimed to give students an introduction to many lab techniques. As high schoolers, we often heard terms such as PCR and gel electrophoresis, but we did not know the exact definition. With this blog, we hope to expose high schoolers to synthetic biology terms and to foster a potential interest in synthetic biology. These blog articles are relevant to our project as it contributes to the education of high school students about synthetic biology especially through the context of our projects and other iGEM projects. For example, one of the posts we created explained all of the synthetic biology techniques we used in the development of our device, AtheroSHuffle.
Our teams also partnered on an episode of our podcast, America’s Number 1 Killer… Atherosclerosis where we each shared 2 different previous iGEM projects that piqued our interest in different fields. The purpose of this was to educate our audience about synthetic biology as a field and address the use of synthetic biology as a possible solution to many global problems. The Education partnership with IISER Pune II brings a global perspective to two of our education activities, allowing us to reach a broader audience.

An example of a blog post we wrote. Click here to see our blog

Impact of our Partnership

Our partnership with the IISER Pune II not only guided the direction, but also the impact of our project. The wet lab aspect of the partnership sought to aid future teams that decide to use E. coli SHuffle, which is becoming an increasingly popular method of antibody production. Our modeling and DOE partnership optimized the conditions of our project so that we both can create accurate and useful devices for our target audience. Our Education partnership broke down global barriers in an effort to educate our target audience in synthetic biology in the context of iGEM and our individual projects.