Incorporating data-informed models to investigate the impact of bioreactor microenvironments

Large-scale bioreactors play a critical role in enhancing the bioeconomy and advancing biotechnology-related industries. In transitioning from the laboratory- to the industrial-scale, the complexity of these fluid systems increases, making microbial performance harder to predict. Computational fluid dynamics is a vital tool in exploring how the change in dynamics during scale-up affects these bioprocesses. Using a bioreactor simulation tool built within the OpenFOAM framework, we evaluate the evolution of the organism, P. putida, as it consumes glucose and excretes muconate, thereby interacting with and modifying its local environment. Parameters of the model for glucose uptake and muconate generation are adjusted using data from simplified experiments and the impact of microenvironments in the stirred-tank bioreactor sparged with oxygen gas are assessed as a function of reactor size. We discuss ongoing progress in the implementation of the coupled modeling strategies and approaches we propose for validation and extrapolation.