The biotechnological production of valuable substances is typically complicated by the loss of microbial performance upon scale-up [1-3]. This challenge is mainly caused by discrepancies between homogeneous environmental conditions at laboratory scale, where organisms are optimized, and inhomogeneous conditions in large-scale bioreactors, where the production takes place. To improve strain selection and process development, it is thus of major interest to characterize these fluctuating conditions at large scales and investigate their impact on microbial cells. In this contribution, we will demonstrate the high potential of dynamic microfluidic single-cell cultivation combined with computational fluid dynamics (CFD) simulation of large-scale bioreactors. CFD simulations of a 300 L bioreactor were applied to characterize environmental conditions in large-scale bioreactors. So-called lifelines were determined by simulating multiphase turbulent flow and mass transport combined with particle tracing. Glucose availability experienced by the microorganism Corynebacterium glutamicum was traced. Resulting lifelines were discretized into low, medium and high glucose availability regimes. Discretized lifelines were used as feeding profiles of a dynamic microfluidic single-cell cultivation (dMSCC) system to investigate how the fluctuating glucose concentration affects cellular physiology and colony growth rate. The presented approach paves the way for an improved understanding of how the cellular lifelines of large-scale bioreactors influence the cellular response within growth and production. It also provides insights into how to understand the conditions in large-scale bioreactors from the view of a microorganism and the dependence of cell wellbeing on the observed conditions.

Reproducing dynamic environment in microfluidic single-cell cultivation based on computational lifeline analysis

ACS Fall 2021

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