Multiscale modeling: A mathematical-based tool for bioprocess design, control and scale up/down

Source abstract

Abstract Performance of an industrial microbial strain can be determined not only by its genome but also by the environment surrounding it. Typically, microorganisms are isolated from natural environments where they have evolved to cope with environmental restrictions and interactions. However, when a microorganism is subject to a synthetically designed environment, like in industrial bioreactors, natural environmental pressures may not be present, forcing the microbe to behave differently. Hence, a microorganism needs to adapt expressing certain metabolic phenotypes that in its turn may alter the environment. Given this double-way conditioning, it is necessary to understand how microorganisms perform in a particular isolated environment through a multiscale modeling approach. At the macro scale, bioreactor modeling, which frequently assumes well mixed and homogeneous vessels, may not be sufficient to properly describe bioreactor’s performance. On the other hand, addressing the culture by only modeling cells via metabolic models may result in a limited perspective at the micro scale. In this work, a mathematical tool is used to recreate observed metabolic behavior as a response to a highly dynamic environment in a bioreactor. Two mathematical models at different scales are coupled via specific q-rates to produce a tool that can be used to understand two-way interactions leading to improved bioreactor design or control but also for scaling purposes. The model at the macro scale follows a compartment-based approach by which hydrodynamics and substrate concentration gradients are recreated. These concentration gradients impose a metabolic response on the cells, which is modeled by a kinetic metabolic model.