Even though we have many facilities and resources at our disposal, we cannot answer all questions concerning our project using laboratory experiments. Moreover, it is not feasible to carry out all possible lab experiments related to our project given our time and resources. Luckily, we can answer some of these questions by constructing computational models in so-called dry lab experiments. These computational models are mathematical representations of real world systems based on experimental determined parameters. These models are meant to help us understand and predict the behavior of such systems, which can lead to boundary conditions or design requirements for our bacteriophage based biopesticide.
The first model we are using describes how phages interact with their target bacteria on a population level scale. Modelling this interaction allows us to study the population dynamics of such a system and determine which parameters play a key role. Results of this model can lead to design requirements, such as the final required amount of toxin that has to be produced per cell, which then can be taken back to the wetlab.
Furthermore, we intend to expand this model to incorporate the build up of phage resistance to study how the ability of bacteria to become resistant to phages influences the population dynamics and thereby the effectiveness of our biopesticide.The model mentioned above only describes host phage interaction and thereby neglects any spatial effects, which might not be the best representation of the locust gut. To investigate the effect of space on phage propagation and toxin production we model the bacteria as a biofilm, which grow according to basic reaction-diffusion. Comparing the results of this model to the more simple model described above allows us to investigate the spatial effects.