Date Thesis Awarded

4-2018

Access Type

Honors Thesis -- Access Restricted On-Campus Only

Degree Name

Bachelors of Science (BS)

Department

Biology

Advisor

Helen Murphy

Committee Members

Oliver Kerscher

William Soto

Simon Joyce

Abstract

Microbes can enact massive change to themselves and their environment through the process of quorum sensing (QS). Through the chemical and metabolic processes of QS, microbes can determine the concentration of cooperative cells in their environment, and if a “quorum” is reached, alter genetic expression to modify microbe behavior and take advantage of resources. Often this altered behavior involves cooperative formations, as is the case of yeast strains like Saccharomyces Cerevisiae. This vastly abundant microbe serves as a convenient and effective model organism for studies examing microbial communication, as well as model for developing treatments for related-yeast Candida albicans infections. Part of the convenience of S. Cerevisiae lie in the wealth of information that exists concerning its genome and metabolism. However, social behavior remains one vital area requiring investigation for this model organism. This study focused on the genetic basis for QS behavior in S. cerevisiae, and the natural variation in this activity across clinical, wild, and medically-derived strains. To this end a program in Python Scikit-Image was developed capable of quantifying the social growth of S. cerevisiae colonies--a direct representation of QS behavior. Numerous screenings of S. cerevisiae strains were grown on variations of colony-inducing media containing different QS inducers. Considerable variation was observed in QS-associated social behavior between strains. While overall no autoinducing treatment proved significantly different from the other groups, the QS inducer phenyl ethanol proved consistently effective. These findings indicated the depth of natural variation in Saccharomyces QS. The second portion of the study focused on determining the genetic basis for QS behavior through a bulk segregant analysis. Variation in QS behavior was observed and measured among S. Cerevisiae segregants, and sorted into high QS and low QS bulks accordingly. The DNA extracted from these bulks will be analyzed to determine possible portions of the genome in relation to QS. These genomic sections, or QTLs, can provide insight into the genetic background for quorum sensing behavior in S. cerevisiae, and possibly more dangerous yeast species.

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