Date Thesis Awarded

5-2018

Document Type

Honors Thesis

Degree Name

Bachelors of Science (BS)

Department

Mathematics

Advisor

Leah Shaw

Committee Members

Helen Murphy

Lawrence Leemis

Abstract

Biofilms are microbial communities that are anchored to a surface and enmeshed in a protective extracellular matrix, shielding the microorganisms from antibiotics and other environmental hazards. As such, eradication of biofilms in medical and industrial settings can be challenging. These communities require individuals to cooperate and produce goods that will be used by all members. Thus, these cooperators are susceptible to cheaters who do not produce public goods, yet benefit from them. However, some cooperators can exhibit kin recognition, in which case they cooperate exclusively with themselves and not with another cell type such as a cheater. In which conditions does a cheater strain dominate cooperators exhibiting kin recognition? We use a stochastic spatial simulation to simulate the inoculation and growth of a yeast biofilm and to model social interactions between strains such as cooperation, competition, cheating and kin recognition. We vary social interaction parameters and define quantitative metrics to measure spatial segregation and cell distribution throughout and at the outside surfaces of a biofilm. These metrics help explain how social interactions affect a biofilm spatially. Understanding the spatial effect of social interactions on a biofilm can eventually help determine the optimum conditions for designing an engineered cheater strain to disrupt cooperative yeast biofilms or yeast infections.

Available for download on Monday, May 04, 2020

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