We partnered with the iGEM team at the University of Calgary.
Fungi is a center point for both of our team and the iGEM team at the University of Calgary. U of C was having difficulty maintaining lab sterility in the presence of their fungal species, causing results of all kinds to be affected. For these reasons, and others, they reached out to our team for advice and to offer a collaborative relationship. After a series of conversations it was decided that our team would perform disc diffusion assays, while U of C would perform Molecular Dynamics Modeling on some speculative transporter proteins for our toxin.
Our team speculated that the lipopeptide Bacillomycin D would be capable of self secretion given its chemical properties. However, we also decided that the use of transport proteins in our biosensor platform could prove useful if our initial speculation failed. Due to the complexity of our transport proteins, it was decided that docking simulations, not molecular dynamics, would be the optimal analysis tool. Since we were working with one another for nearly the whole season on a series of objectives; each having the capacity to radically alter the future steps in our respective projects, we re-classified our relationship as a partnership.
Three KB tests were performed throughout the season. Results from the first test proved the same as our second attempt and are therefore not presented here. Furthermore, much of the data was lost/corrupted in a data transfer process. The remaining two experiments demonstrated no visible inhibition zones at any nisin concentration, Figure 2 A-E. After careful consideration, we concluded that nisin inactivation may be the most critical, and likely source of error. Nisin can become inert after light exposure, and is affected by temperature fluctuations (prolonged room temperature for example). Steps were taken to maintain the nisin in its optimal environment, however, exposure to sunlight and room light did occur while preparing discs for plating. In totality however, we concluded that there is a low probability of nisin deactivation and are confident in our results.
Quadrant 1 - Stock nisin | Quadrant 2 - 1/10 nisin | Quadrant 3 - 1/20 nisin | Quadrant 4 - negative control |
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100 μL nisin | 10 μL nisin + 90 μL ddH₂O | 5 μL nisin + 95 μL ddH₂O | 100 μL ddH₂O |
Interested readers can find the docking results from U of C on their wiki.
Their results demonstrate that bacillomycin D is capable of binding to all three speculative transport proteins with a similar affinity. Since our project did not get to the point where transporters were necessary, predicting how this information could have been useful is difficult. It is definitely the case however, that this modeling greatly narrowed the scope of our protein search, thereby saving our team a great deal of time had we reached this point. Furthermore, the results provide a quantitative comparison between the predicted and in-vivo effect of Bacillomycin D transport; narrowing optimizations that may have been required.