Application of microfluidic systems in modelling impacts of environmental structure on stress-sensing by individual microbial cells

Harvey, Harry J.; Chubynsky, Mykyta V.; Sprittles, James E.; Shor, Leslie M.; Mooney, Sacha J.; Wildman, Ricky D.; Avery, Simon V.

Abstract

Environmental structure describes physical structure that can determine heterogenous spatial distribution of biotic and abiotic (nutrients, stressors etc.) components of a microorganism's microenvironment. This study investigated the impact of micrometre-scale structure on microbial stress sensing, using yeast cells exposed to copper in microfluidic devices comprising either complex soil-like architectures or simplified environmental structures. In the soil micromodels, the responses of individual cells to inflowing medium supplemented with high copper (using cells expressing a copper-responsive pCUP1-reporter fusion) could be described neither by spatial metrics developed to quantify proximity to environmental structures and surrounding space, nor by computational modelling of fluid flow in the systems. In contrast, the proximities of cells to structures did correlate with their responses to elevated copper in microfluidic chambers that contained simplified environmental structure. Here, cells within more open spaces showed the stronger responses to the copper-supplemented inflow. These insights highlight not only the importance of structure for microbial responses to their chemical environment, but also how predictive modelling of these interactions can depend on complexity of the system, even when deploying controlled laboratory conditions and microfluidics.

Citation

Harvey, H. J., Chubynsky, M. V., Sprittles, J. E., Shor, L. M., Mooney, S. J., Wildman, R. D., & Avery, S. V. (2022). Application of microfluidic systems in modelling impacts of environmental structure on stress-sensing by individual microbial cells. Computational and Structural Biotechnology Journal, 20, 128-138. https://doi.org/10.1016/j.csbj.2021.11.039

• Journal Article Type: Article
• Acceptance Date: Nov 28, 2021
• Online Publication Date: Dec 1, 2021
• Publication Date: 2022
• Deposit Date: Dec 10, 2021
• Publicly Available Date: Dec 10, 2021
• Journal: Computational and Structural Biotechnology Journal
• Electronic ISSN: 2001-0370
• Publisher: Research Network of Computational and Structural Biotechnology
• Peer Reviewed: Peer Reviewed
• Volume: 20
• Pages: 128-138
• DOI: https://doi.org/10.1016/j.csbj.2021.11.039
• Keywords: Computer Science Applications; Genetics; Biochemistry; Structural Biology; Biophysics; Biotechnology
• Public URL: https://nottingham-repository.worktribe.com/output/6916632
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S2001037021005043