As the aim of our project is to construct a modular toolkit using co-cultures with three organism, we would have to conduct many experimental iterations to reach conclusive and reliable results. To avoid this tedious process, we, as many other scientists working in this field, turned our attention to computer based biological modeling to predict the behavior of our system.
In the realm of mathematical and computer based biology, scientist use algorithms, data structure and data visualization to create approximations of existing biological systems. This serves two important goals; One, to check wether the theoretical understanding of a process is correct. Of course, this can be done by constructing a model and checking if the cultures behave within reasonable correctness as the observations in the lab indicate.
The other goal of such modeling approach is to predict wether the behavior of the system are changed or other external influences are applied. This latter role is why we are using modeling in our project.
However, many of our team members lacked experience in this field. As such, we approached the Institute of Quantitative and Theoretical Biology at our university (Headed by Professor Oliver Ebenhöh) to discuss our approach.
The behavior of a coculture is complex. Modeling it in it’s entirety would be far too complex. As such we had to find a way to reduce this complexity. To achieve this, we began our work with laying out a few assumptions that would reduce the complexity of our system and give us a clear indicator of what went wrong if a prediction turned out to be incorrect.
In our model we assumed that:
- The consumption of metabolites, especially for growth, occurs in discreet units.
- All organisms have equal access to the metabolites.
- There are no organism specific limits to metabolite uptake or release.
- Every metabolite are constant and optimal except the ones we control with.
- Growth as well as metabolic reactions are limited by low avalability as well as the slowest enzyme reaction, respectively.
- There is no change in the speed of reactions.
- The capacity of the system for each organism is set and not calculated dynamically.
- While phosphate and nitrogen are important for growth, only a complete lack of carbon (as a stand-in for sugar in our model) will result in starvation of the organisms.
Assumption one is a consequence of the way our model is calculated, the others are there to reduce complexity. As stated above, this reduced complexity also reflects a reduction in realism, however, our model has produced results that in our mind, make a more complex approach unnecessary for now.
Our model is iterative and goes though the following equations for each organism and metabolite each iteration: