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Title: A New Agent-Based Model for Bacterial Biofilm Growth
Authors: Sharo, Andrew
Advisors: Wingreen, Ned
Contributors: Austin, Robert
Department: Physics
Class Year: 2016
Abstract: Each year biology becomes a more quantitative field, creating vast amounts of data from experiments. As methods are developed to interpret these data, a researcher's desire to create and refine biological models becomes increasingly feasible. At the same time, researchers are coming to realize that biofilms, surface-bound communities of microorganisms, play important roles in human health, and are likely the dominant form of life on earth. In this thesis, we design, implement, and simulate a new agent-based model describing the dynamics of a growing Vibrio cholerae biofilm. The advantages of an agent-based model are perfectly suited to characterize the complex position and orientation of cells in a V. cholerae biofilm. Our model is grounded in our current understanding of the physics of adhesive polymers and cell movement at low Reynolds numbers. In order to replicate the adhesive cell-substrate forces found in a biofilm, our model uses anchors with Hookean springs. Additionally, our model uses a convex hull to approximate a polysaccharide-protein envelope. Building on an existing framework, we design an algorithm to implement our model and simulate growing biofilms. We compare our simulated biofilms to data gathered from confocal microscopy images of living biofilms. We identify several qualitative and quantitative features with which we compare simulated and living biofilms, such as edge cell orientation, effective volume per cell, and cell alignment with the z-axis. These comparisons demonstrate the effectiveness of our model and indicate several directions for improvement, such as implementing a mechanism to encourage symmetry breaking in early biofilms, as well as a mechanism for cell-cell attachment equivalent to the effects of RbmA in living biofilms.
Extent: 66 pages
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Physics, 1936-2016

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