Mesoscale Modeling of the Bacillus Thuringiensis Sporulation Network Based on Stochastic Kinetics and Its Application for in Silico Scale-Down

Bacillus thuringiensis is a gram positive bacterium that is capable of synthesizing entomotoxines during the sporulation process. This work proposes a mesoscale model capable of describing the evolution of Bacillus thuringiensis sporulation process. The model was developed using stochastic kinetics and solving the master equation with a virtual cluster composed of 35 computers from a student’s computer room. Virtualization is the key strategy to gain computer power in an opportunistic way, it allows to the local users have priority while accessing resources and allows to the virtual cluster exploit the idle time of such resources, providing new capacities for research at a very low cost (close to zero). The results confirm the presence of a mixture of two Gaussian populations for phosphorylated Spo0A. Finally, it was evaluated the effect of oxygen gradients on the production of spores by oscillating the effect of KinA on the reaction of Spo0A phosphorylation.