In partial fulfillment of the requirements for the degree of

Doctor of Philosophy in Quantitative Biosciences

in the School of Biological Sciences

Rogelio A. Rodriguez-Gonzalez

Will defend his dissertation
COMPUTATIONAL MODELS OF PHAGE THERAPY FROM IN VITRO SETTINGS TO IN VIVO INFECTIONS

Tuesday, April 16, 2024

9:30am ET
Cherry Emerson Room 201B

Zoom link:

https://gatech.zoom.us/j/2290241987?pwd=elVmR3Z6OFlDeG5rRFA3YW4zU2lzdz09

Advisor:
Joshua Weitz, PhD, Previous affiliation: School of Biological Sciences, Georgia Institute of Technology. Current affiliation: Department of Biology, University of Maryland.

Committee members:

Sam Brown, PhD, School of Biological Sciences, Georgia Institute of Technology

Jennifer Curtis, PhD, School of Physics, Georgia Institute of Technology

Steve Diggle, PhD, School of Biological Sciences, Georgia Institute of Technology

Laurent Debarbieux, PhD, Department of Microbiology, Institut Pasteur

Abstract:

The antimicrobial resistance crisis poses a significant threat to global health, leading to millions of infections and fatalities annually. As an alternative to conventional antibiotics, phage therapy, utilizing lytic bacteriophages (viruses of bacteria) to target and eliminate specific bacterial pathogens, has emerged as a promising approach. However, phage therapy faces challenges, such as the evolution of phage resistance, prompting interest in combining phages with other antimicrobials like antibiotics. In addition, while case studies have demonstrated curative outcomes associated with phage therapy, larger clinical trials have yielded mixed results, indicating gaps in understanding when phage therapy succeeds or fails.

This thesis focuses on developing computational models to evaluate and enhance the efficacy of phage therapy across diverse in vitro and in vivo settings, using Pseudomonas aeruginosa as a model organism. Our models, ranging from well-mixed to spatially explicit contexts, explore the influence of host immune status, lung spatial structure, and phage-antibiotic interactions on bacterial infection dynamics and phage therapy outcomes.

In the first part, we implement a model of phage-antibiotic combination therapy, leveraging known evolutionary trade-offs between phage and antibiotic resistance, and assess its efficacy in an in vivo infection context. Next, we extend this model to investigate various treatment regimens, including simultaneous and sequential therapies, utilizing in vitro data to validate model simulation results. Finally, we examine the impact of host immune responses and lung spatial structure on phage therapy outcomes for acute P. aeruginosa pneumonia.

Our findings underscore the critical role of host innate immunity in shaping the success of phage-antibiotic combination therapies and reveal potential adverse effects of antibiotics on phage dynamics when administered simultaneously. Moreover, our results demonstrate that phage therapy can facilitate infection clearance in spatially structured environments contingent upon sufficiently active innate immune responses and suitable phage life history traits. Overall, this thesis advances our understanding of how host factors such as immune responses and lung structure influence phage therapy efficacy and sheds light on antibiotic-related mechanisms shaping phage dynamics.