Jacob Davis
BioE Ph.D. Defense Presentation
July 5th, 2023     2:00 PM
EBB 4029
Zoom Meeting ID: 944 4214 1649 Passcode: 410838


Committee:
Eberhard Voit, Ph.D. (Advisor) (Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)
Sam Brown, Ph.D. (Advisor)  (School of Biological Sciences, Georgia Institute of Technology)
Melissa Kemp, Ph.D  (Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)
Arlene Stecenko, M.D. (Department of Pediatrics, Emory University School of Medicine)
Mark Styczynski, Ph.D (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)
Denis Tsygankov, Ph.D (Department of Biomedical Engineering, Georgia Institute of Technology)

EXPERIMENTAL AND COMPUTATIONAL ANALYSIS OF PATHOGEN EMERGENCE AND ANTIBIOTIC RESISTANCE IN A CYSTIC FIBROSIS AIRWAY INFECTION MODEL

    The human body harbors at least twice as many bacteria as it does human cells. Most of these bacteria are harmless, but the emergence of pathogens is common in many human body systems. Treatment of these infections is often done with antibiotics, which can have non-target effects and remove protective flora from the body. This project was designed to create a model system of airway bacterial communities that is amenable to the development of effective experimental and computational investigations that shed light on pathogen emergence and antibiotic resistance. For the experimental analysis, I transformed three bacterial species found in human airways with the goal of making them easily quantifiable with available microscopic and spectrophotometric techniques. The bacteria were grown individually and in combinations of species and their dynamics were studied, as well as the effects of pH on the system. Community resistance to a beta-lactam was studied by tracking the hydrolyzation of the antibiotic by non-targeted species, showing that non-focal species are important to consider when choosing an antibiotic treatment. To quantify interactions among the different species, mathematical models within the Lotka-Volterra framework were developed and parameterized. The existing framework was then expanded to incorporate antibiotic and metabolic data in the community model. Although the community size of the model system is small - to allow for comprehensive data generation - this experimental and mathematical system constitutes a prototype for investigating larger models that can be used to predict how pathogens survive in different communities and under altered environmental conditions and antibiotic treatments.