On Monday, January 28th, QBioS student Stephen Thomas presented his oral thesis proposal.
Dr. Sam Brown, School of Biological Sciences
Dr. Constantine Dovrolis, School of Computer Science; Georgia Institute of Technology
Dr. Joshua Weitz, School of Biological Sciences, Georgia Institute of Technology
Dr. Marvin Whiteley, School of Biological Sciences; Georgia Institute of Technology
Bacterial cells do not act strictly in isolation. They also interact, drawing on a rich repertoire of behavior that ranges from cooperation to antagonism. The collective behavior that results from these interactions carries important implications for human health (virulence), ecology (microbiomes), and industry (food production). Quorum sensing is one mechanism for effecting an interaction: bacteria release signal molecules that diffuse throughout the environment and influence the behavior of other cells. Mathematical models provide a framework for analyzing these diffusion-mediated interactions. This research extends existing models to clinically relevant environments where individual bacteria accumulate into small, spatially dispersed aggregates. The model considers collections of such aggregates as nodes in a network, with edges representing interactions between nodes. Both the network’s nodes and its edges evolve in time, creating a networked dynamical system. Reaction/diffusion partial differential equations, combined with population-level models of quorum sensing, characterize the dynamics of the network. A configuration model for aggregate formation provides a probabilistic description of network assembly. The resulting model predicts the evolution of aggregate networks and the resulting collective behavior of those networks. Predictions from the model may inform attempts to analyze, understand, or disrupt that behavior.