Computational models can be used to optimize the production of bacteriophages. Here a model is described for production in a two-stage self-cycling process. Theoretical and practical considerations for modeling bacteriophage production are first introduced. The key experimental protocols required to estimate key kinetic parameters for the model, including determining variable infection rates as a function of substrate concentration, are described. ppSim is an open-source R-script that can simulate bacteriophage production to optimize productivity or minimize costs. The steps included to run the simulation using the experimentally determined infection parameters are described. An example is also presented, where a level sensor and cycle time are optimized to maximize bacteriophage productivity in two sequential 1-L bioreactors, resulting in a production rate of 4.46 × 1010 bacteriophage particles/hour. The protocols and programs described here will allow users to potentially optimize production of their own bacteriophage-bacteria pairing by effectively applying bacteriophage modeling.
Keywords: Bacteriophage dynamics; Computational modeling; Process optimization.