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Mathematical and Computational Modeling of Bacterial Motility and Swarming

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posted on 2015-04-17, 00:00 authored by Amy Lyn Buchmann
Multiscale computational and mathematical models play an important role in obtaining a better understanding of bacterial swarming and motility. For example, the very social Myxococcus xanthus, a bacterium commonly found in soil and known for its multicellular interactions, can be modeled using the subcellular element method. Using this model, the role of cell flexibility, cell-cell adhesion, and cellular reversal periods can be studied. To characterize cell-cell interactions, the contacts between cells in simulations are analyzed to determine how these properties influence the populations' ability to form and keep cell-cell connections. M. xanthus are able to share outer membrane proteins through direct cell contact, and the study of these properties is important for determining the populations' ability to efficiently share protein. The study of bacterial motility systems can also motivate advances in bioengineering. Microfluidics devices carry very small volumes of liquid though channels and have been used in many biological applications including drug discovery and development. In many microfluidic experiments, it would be useful to mix the fluid within the chamber. However, the traditional methods of mixing and pumping at large length scales don't work at small length scales. Bacterial carpets are created by attaching bacteria to a substrate while allowing their flagella to freely rotate and may provide a solution to this problem. The method of regularized stokeslets is implemented to model fluid flow above simulated bacterial carpets and compare findings to preliminary experimental studies.

History

Date Modified

2017-06-05

Defense Date

2015-03-26

Research Director(s)

Mark Alber

Committee Members

Zhiliang Xu Alexandra Jilkine Martina Bukač

Degree

  • Doctor of Philosophy

Degree Level

  • Doctoral Dissertation

Language

  • English

Alternate Identifier

etd-04172015-150013

Publisher

University of Notre Dame

Program Name

  • Applied and Computational Mathematics and Statistics

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