In silico microfluidic chip design to mimic microbial lifelines

Abstract

In recent years, biotechnological processes have gained increased interest due to their potential for high-value compound production and waste recycling. This shift towards biotechnology is driven by global challenges such as food security, climate change, and the transition to renewable resources. To address the limitations of large-scale fermentations, scale-down approaches have been recommended to minimize microbial performance losses during scale-up procedures. Computational fluid dynamics (CFD) coupled with omics-based technologies offer valuable insights into the environmental and intracellular
lifelines of cells. However, current laboratory-scale setups have certain limitations, emphasizing the need for dynamic microfluidic single-cell cultivation (dMSCC) devices. These devices enable the analysis of single-cell behavior in dynamic environments with high temporal resolution.

This thesis focuses on improving the amplitude control while maintaining temporal resolution in dMSCC devices. A new dMSCC device design was analyzed using a 2D model, which was experimentally validated. The results demonstrated that the design mechanism effectively generated concentration profiles resembling discrete and smooth lifelines, albeit with a relatively high response time (30 seconds). A mesh independence study indicated minimal deviations (2 %) in results for different mesh refinements, while complex geometric structures introduced greater variations.

The experimental validation of the 2D COMSOL Multiphysics model highlighted discrepancies between the experimental data and model predictions, both at the outlets of the microfluidic concentration gradient generator (μCGG) and inside the chamber (RMSE=0.1-0.75; >10% of experimental data). However,
the observed trends of the concentration profiles inside the chamber were well-captured. Optimization studies were conducted based on these findings, leading to valuable conclusions. Narrowing the chamber width increased the chip’s response time. Moreover, increasing the space between μCGG outlets
as well as increasing fluid velocity inside the μCGG (while keeping the maximum velocity constant) improved gradient width. The latter approach is preferred to maintain temporal resolution. A comparison between COMSOL Multiphysics (RMSE=0.14) and Ansys Fluent (RMSE=0.15) models revealed that Ansys Fluent better captures experimental trends but has lower prediction accuracy. Further investigations involved a Design of Experiments (DoE), which indicated that the current μCGG design is suitable for fluid velocities preferably lower than 1 · 10−5 m/s and tracers with high diffusion coefficients. These conclusions provide insights into optimizing dMSCC devices and contribute to the broader understanding of mimicking microbial lifelines.