Modeling the Migration and Growth of Shewanella Oneidensis MR‐1 in a Diffusion‐Dominated Microfluidic Gradient Chamber Under the Influence of an Antibiotic Concentration Gradient
Abstract
Motility and chemotaxis allow bacteria to migrate from areas that become depleted in energy yielding substrates to more favorable locations, possibly enhancing the biodegradation of pollutants in soil and groundwater. However, in some cases substrates are co‐mingled with one or more toxic solutes that inhibit pollutant degradation and/or microbial growth, and the impacts on motility and chemotaxis represent a knowledge gap. In this study, a one‐dimensional diffusion reaction model is developed and used to simulate dissimilatory biological reduction of nitrate to ammonia (DNRA) presented in a previously published microfluidic gradient chamber (MGC) experiment, where spatial abundances of Shewanella oneidensis MR‐1 cells were recorded over 5 days in a diffusion limited porous media domain as it degraded nitrate and lactate introduced from opposite boundaries, and at one boundary co‐mixed with the antibiotic ciprofloxacin. The model considers S. oneidensis chemotaxis toward nitrate and nitrite, random motility, and growth inhibition by ciprofloxacin. Parameters were adjusted within ranges commonly reported in the literature to obtain results that agreed with the data. Simulation results indicate that motility and not chemotaxis, in combination with inhibition of cell growth by ciprofloxacin, controls the distribution of cells in the toxic region (containing ciprofloxacin) of the MGC. This suggests that cell motility may facilitate nitrate removal in soil and groundwater by enabling microorganisms to migrate toward nitrate contaminated regions with elevated antibiotic concentrations.
Copyright and License (English)
© 2025 The Author(s). Biotechnology and Bioengineering published by Wiley Periodicals LLC. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Acknowledgement (English)
The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing Lonestart5 and Lonestar6 resources that have contributed to the research results reported within this paper. URL: http://www.tacc.utexas.edu. The authors also acknowledge support from endowment funds provided by the Bettie Margaret Smith Chair in Environmental Health Engineering.
Supplemental Material
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bit28991-sup-0001-SI_submission_biotech_bioeng_submission2_highresfig.docx
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Additional details
- The University of Texas at Austin
- Bettie Margaret Smith Chair in Environmental Health Engineering -
- Available
-
2025-04-16Version of record
- Caltech groups
- Division of Biology and Biological Engineering (BBE)
- Publication Status
- Published