Quantitative Biosciences Thesis Proposal
School of Biological Sciences
Thesis Advisor: Dr. Marvin Whiteley
Open to the Community
Title: Emergent behaviors of Aggregatibacter actinomycetemcomitans during polymicrobial infection
Thursday, September 19th, 2019, 10:00 am
Clough Undergraduate Learning Commons, Room #423
Dr. Peter Yunker (School of Physics, Georgia Institute of Technology)
Dr. Steve Diggle (School of Biological Sciences, Georgia Institute of Technology)
Dr. Samuel Brown (School of Biological Sciences, Georgia Institute of Technology)
Dr. William Ratcliff (School of Biological Sciences, Georgia Institute of Technology)
Dr. David Weiss (School of Medicine, Emory University)
Periodontitis (gum disease), which affects nearly half of the US population, is caused by a complex microbial consortium rather than a single pathogenic agent. Over 700 unique species are identified in this polymicrobial disease and a subset of these microbes form a highly dense and structured biofilm below the gum line (subgingival pocket). Within this polymicrobial community, the Gram negative bacterium Aggregatibacter actinomycetemcomitans (Aa) is a key pathogen during the development of periodontal disease. While the oral community is dynamic and highly complex, I will focus on two aspects that impact Aa physiology during human infection: interaction with co-infecting microbes (Aim 1) and the growth rate of Aa (Aim 2).
Our lab utilizes a two-species model system to study polymicrobial interactions between Aa and its synergistic partner Streptococcus gordonii (Sg). Aa and Sg have a complex relationship in which Aa uses lactic acid produced by Sg as a preferred carbon source, while providing a benefit to Sg through the detoxification of Sg-produced hydrogen peroxide. The goal of Specific Aim 1 is to evaluate whether the interactions between Aa-Sg are critical for enhancing bacterial fitness in response to environmental disturbance that occurs during infection, specifically invasion by other co-infecting oral bacteria. Confocal microscopy will be used to observe the temporal-spatial dynamics of fluorescently-labeled Aa-Sg communities and explore equilibrium properties (subaim 1.1). Then we will challenge the Aa-Sg community with other oral bacteria and determine the role that metabolic interactions between Aa and Sg play in preventing invasion (subaim 1.2).
Bacterial generation time impacts the efficacy of most antimicrobial treatments. The generation times of pathogens are largely unknown in vivo due to inaccessibility of standard experimental methods. The goal of Specific Aim 2 is to quantify the heterogeneity in generation time in human infections using Aa as a model system. I will first build a model to correlate bacterial generation times with transcriptional signatures (subaim 2.1) and then quantify the heterogeneity of generation times within bacterial human-associated communities (subaim 2.2). The successful completion of these goals will provide mechanistic insights to effective treatment of polymicrobial infections.