Mathematical models and simulations are a great way to predict and analyze biological processes; in our case, we modeled PAH degradation pathways we designed to test their effectiveness and efficiency, as pointed out by some interviewees (mentioned in more detail on the Human Practices page). We modeled the degradation pathways for Chrysene, Naphthalene, Fluorene, and Phenanthrene, using MATLAB and its Symbio extension. Then, we ran a simulation of the change in concentration of different compounds during degradation. This allowed us to estimate the results of our project and figure out the ideal concentration of PAHs, as well as establish their effectiveness.
Our team designed degradation pathways to degrade key oil spill Polycyclic Aromatic Hydrocarbons - Chrysene, Naphthalene, Phenanthrene, and Fluorene. However, before conducting significant real lab work, we wanted to ensure that our pathways were designed appropriately and accurately. Based on some brainstorming sessions, the pathways seemed correct, but we wanted to make sure. For this purpose, we decided to use the MATLAB extension called Simbiology to theoretically model our constructs and observe the results. We developed these Symbio models by ourselves. The data for the amount of substances for each of the 4 PAH models was obtained from the Uniprot website and subsequently integrated into Symbio.
More information regarding our models
Each of the inputs and outputs of the pathway were modeled using the Species button of Simbiology, with a specific value attributed to them; in most cases, this value was 1.0, although released ATP from this process often had greater values such as 3.0 or 10.0. Then, the whole pathway was theoretically simulated using the Simbiology Model Analyzer Feature. The results were displayed through graphs, as shown above.
If we look at each of the model simulations' graphs, each of the PAH's byproducts that were released were all harmless to the environment, and each of the four PAHs gets completely degraded. Furthermore, this process additionally helped us identify a key error in our Chrysene and Phenanthrene degradation pathways, helping us gain new insights about our proposed pathways and allowing us to improve the design of our project.
With our pathway models, we concluded that Chrysene and Naphthalene were the two PAHs that would allow us the highest efficiency, effectiveness, and success rate overall. Furthermore, their relative success rates also helped clear concerns regarding potential ineffectiveness of PAH degradation. Finally, doing this allowing us to integrate interviewees' concerns to further solve issues with the potential execution of our team's project.