Fungi Experimentation and Molecular Docking with U of Alberta iGEM


Consistency in Communication

In June of 2022, we realized that both our team and the U of Alberta iGEM team shared a common area of interest between our project topics: fungi. With the return of our northern provincial neighbors after taking a two year break from iGEM, we hoped that our two teams could work together and create a strong bond. Through this partnership, our objectives were to share each of our team’s strengths and areas of expertise. The U of Alberta iGEM team shared their knowledge in working with fungi safely and carried out several related experiments with our fungi samples, and in return, our team modeled the molecular dynamics of various transporter proteins with their project’s target toxin. Our project’s narratives surrounding the properties and function of nisin and Bacillomycin D (BMD), respectively, were significantly shaped by the antifungal experimentation and docking results we obtained for each other. Learn more about U of Alberta's project and their work with us here!

Figure 1. Zoom meeting with two of the members of U of Alberta iGEM!

A critical element to a successful partnership is consistent and open communication. Our teams made it a priority to update each other on the state of our project’s progress from June to October. The timeline was as followed:

Fungi Experimentation

Kirby-Bauer Disc Diffusion Tests With Nisin

To test whether nisin is antifungal, we collected samples of unknown fungi strains swabbed off of rotting fruit from our local grocery store, and known fungi strains from Francene Cusak from the University of Calgary. Josh McGinnis, a bioprospector and the CEO of EveryMan Bio, identified that there were likely common green molds (Penicillium, Cladosporium, Aspergillus, etc.) present on our swabbed fruit samples, however, further DNA analysis would be required for confirmation. Our known samples of fungi strains included Mucor ramanpianus, Penicillium claviforme, Rhizopus, Penicillium duclouxii, Penicillium commune, and Trichoderma viride - which are common fungal pathogens present on the surface of food (1,2).

Unfortunately, working with fungi presented a major problem for our lab. Even though we tried to make a DIY “fungi box” (which consisted of a large, plastic box, located in the back of our lab space away from our cloning and BC production experimentation) to keep our samples isolated from the rest of the lab, we still had several contamination issues with our other experiments. To comply with safety regulations, we knew we needed a different strategy if we were going to continue working with fungi.

After reading about the U of Alberta iGEM project on their Instagram page, we realized that both of our teams were working with fungi. We met with their Team Leader, Joseph, with the intent of exchanging fungi safety protocols. Because the U of Alberta iGEM team's lab was better equipped to handle BSL2 fungi, we drove all of our fungi samples, along with a sample of nisin, to their lab in Edmonton. Our fungi samples were plated in petri dishes, sealed with parafilm, and stacked in a styrofoam box which was resealed and placed in a cooler for transport. An aliquot of nisin was shipped in a similar manner using a styrofoam box and cooler.

Figure 2. After driving 3 hours north we were able to meet up with a few of the members of the U of Alberta iGEM team to drop off our fungi and nisin samples at their iGEM lab in Edmonton!

We also shared a series of protocols for preparing fungi inoculations and running Kirby Bauer disc diffusion tests with our nisin sample, so that the U of Alberta iGEM team was able to run our tests for us. U of Alberta iGEM modified our protocols to fit with their lab materials, and worked to optimize the conditions in order to achieve fungal lawn growth for our species.

Fungi Results

Nisin's Effectiveness Against Fruit Fungi

The first step in conducting our Kirby-Bauer experiments with nisin was to determine how to achieve lawn growth for our fungi samples. The first modification that the U of Alberta iGEM team made to our protocols was to use Meuller-Hinton (MH) agar supplemented with glucose instead of potato dextrose agar (PDA) to grow our fungi. Additionally, instead of making overnights from our plates, they decided to re-streak a single colony onto a new plate creating a subculture, resuspend it, and then plate it. Both of these modifications allowed for lawn growth to be achieved.

When we attempted to create lawn growth with our fungi samples, it took between 10 and 14 days to achieve only a somewhat uniform distribution on our plates. The U of Alberta iGEM team was able to expedite uniform lawn growth, taking between 2-4 days (depending on the species), by supplementing their MH media with glucose. They tested two different percentages, both 2% and 20% glucose (shown in Figure 3). Instead of growing the plates in their incubator, the U of Alberta iGEM team also used a safety cabinet maintained at room temperature, which allowed for a sterile environment, heat transfer, and good air flow.

Once U of Alberta iGEM successfully achieved fungal lawn growth, they were able to set up our first round of Kirby-Bauer disc diffusion tests using nisin. They divided the plates into quadrants according to our protocol, and tested 4 concentrations of nisin (stock nisin, 1:10, 1:20, and a water control).

Figure 3. The first set of Kirby-Bauer test results for nisin’s effectiveness against fungi, obtained by the UofA team on August 31st. Plates were divided into quadrants, each with different concentrations of nisin (stock, 1/10, 1/20, and water as a control). Lighter plates were made with 2% glucose and darker plates were made with 20% glucose.

Based on the U of Alberta iGEM team's results, nisin showed no effectiveness against any of the fungi species. No zone of inhibition was observed in any of the quadrants. This information was critical to how we shaped our Cellucoat narrative moving forwards. While we initially had classified nisin as both an antifungal and antimicrobial peptide, we felt it would be more accurate to classify it only as antimicrobial.

To explore other avenues of nisin’s effectiveness against fungi, we asked whether the U of Alberta iGEM team had any other strains in their lab. Because their project primarily works with Candida albicans, which literature has shown nisin to be effectives against, we asked if they could set up another round of KB tests for us. C. albicans is not a fruit pathogen, and is instead found in the gut (3). This inspired us to think about future applications for Cellucoat. Because our bacterial cellulose material functionalized with nisin is food-safe, it could have applications as an edible material to improve gut health (4).

Figure 4. The second set of Kirby-Bauer test results for nisin’s effectiveness against C. albicans obtained by the U of Alberta iGEM team on September 29th. Plates were divided into quadrants, each with different concentrations of nisin (stock, 1/10, 1/20, and water as a control).

Results from the second round of KB tests were similar to the first - nisin showed no inhibition against C. albicans. We set up tests in a similar manner, testing three different concentrations of nisin with a water control. No zone of inhibition was observed in any of the quadrants. Overall, through this partnership we were able to learn more about nisin’s properties as a preservative. Because nisin is not effective as an antifungal, we are now better informed to choose new peptides for future iterations of Cellucoat.

Modelling BMD

How can we use modeling to inform U of Alberta iGEM's project?

With us getting help with our Kirby Bauer tests, we looked into ways in which we could partner with their team. Upon discussion, we discovered they had a limitation in terms of modelling. The U of Alberta iGEM project involved the creation of a biosensing and treating system for fungal infections from Candida albicans. Specifically, they wanted to understand how their toxin Bacillomycin D (BMD), which would be responsible for treating the infections, would interact and work with the transporter proteins in their host cell that created this toxin. This is because BMD has never been expressed and secreted in the various ways they had hypothesized. However, due to wet lab resources and time constraints, they suggested that it might not be possible to observe this in the lab. Hence, we sought to begin working strategically with them to help them perform docking and molecular dynamics that could model and help us understand the binding dynamics and interactions between the toxin and transporter proteins. As a team, U of Alberta iGEM wanted to test out several transporter proteins to determine which one would be adequate in secreting the toxin BMD. These transporters are KrsE, SecYEG, TatABC, TolC, and YerP.

Docking is a bioinformatics modelling method to model the interactions between a molecule and a protein. We decided to perform docking simulations between the ligand (BMD) and proteins (Transporter proteins). This would enable us to understand the binding dynamics and give us an idea of how these transporter proteins could work in secreting BMD. Ultimately, these results would give the U of Alberta iGEM team an idea of which protein works best for BMD transportation.

Apart from the software used (see more on the molecular dynamics modelling page), we needed the “.pdb” files of these proteins that contained the atomic structures of these proteins. The team sent us their FASTA sequences for all the transporter proteins as the “.pdb” files were hard to gain access to. We then used “robetta fold” software that used machine learning techniques to predict the 3D structure of transporter proteins. We implemented this software for both KrsE and YerP. However, we found the PDB for SecYEG. Due to the complexity of TatABC and TolC proteins, we decided not to perform docking on them. However, we were able to perform docking on the other transporter proteins.

Docking Results

Finding the best transporter protein

From our docking simulations, it was revealed that all three transporter proteins had a fairly similar vina score. The vina score gives us a representation of how good the binding affinity of the protein is. The more negative it is, the less energy is needed to initiate binding and the better the binding of the two. We conclude that they would have a similar affinity to BMD. However, the results show that the KrsE transporter protein had the most negative vina score. This implies that we could empirically say that the KrsE transporter protein would be the best for the U of Alberta team to use in transporting their toxin BMD.

Protein + Ligand Vina Score Cavity Volume Center Docking Size
KrsE + BMD -7.6 518 1, 12, 1 29, 29, 29
SecYEG + BMD -7.3 342 17, 22, 26 29, 29, 29
Yerp + BMD -7.3 31002 50, 31, -9 35, 35, 35

Figure 5. Visualization of the binding of KrsE to BMD, contact residues of KrsE shown in red and BMD shown in blue.

Figure 6. Visualization of the binding of SecYEG to BMD, contact residues of SecYEG shown in red and BMD shown in blue.

Figure 7. Visualization of the binding of YerP to BMD, contact residues of YerP shown in red and BMD shown in blue.


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