A theoretical and experimental study of the population dynamics of bacteria and phage: implications for therapy Open Access

Govindan, Adithi (Spring 2020)

Permanent URL: https://etd.library.emory.edu/concern/etds/xw42n9023?locale=en



With the rise of infections caused by multidrug resistant organisms, alternative therapies such as phage therapy, have become of interest. Although phage therapy has successfully treated bacterial infections, in most cases bacteria evolve resistance to the phage treatment. In order to prevent or reduce the problem of resistance, it is important to address the conditions of phage-bacteria population dynamics conducive to bacterial resistance evolution.


Using mathematical modeling and in-vitro experiments, we explore three scenarios to determine if phage therapy can prevent the rise of resistance: I) phage cannot generate host range mutants so resistance to the phage can be acquired by single point mutations; II) phage are capable of evolving host range mutants that enable them to replicate on bacteria resistant to its ancestral phage; and III) a general resistance mechanism by which bacteria gain resistance to multiple phage, or mucoidy. Our theoretical and experimental results suggest that generally phage therapy, including phage cocktails, or a mixture of phages, is not effective in consistently preventing the rise of bacterial resistance. However, we observe that if phage treatment contains multiple phage, one of which as the capability of generating a host range mutation in response to resistant bacteria, the phage can prevent or delay the rise of resistant bacteria. We also observe a reduction in resistant bacteria in a population that is treated with a phage cocktail containing phage that can readily, without mutation, replicate on bacteria resistant to another phage in the population.


Although phage therapy is an alternative treatment for multi-drug resistant infections, we suggest the phage-bacterial dynamics should be studied to elucidate the conditions that give rise to bacteria resistant to treatment. Understanding these conditions can inform the future design of phage cocktails that to prevent the rise of resistance to treatment.

Table of Contents

Abstract - 1

Introduction - 3

Materials and Methods - 6

Research Plan - 10

Results - 11

Table 1: Parameters and variables for mathematical models - 11

Figure 1-11: Scenario I – One-point mutation to resistance - 12-22

Figure 12-16: Scenario II – Two-point mutations to resistance - 23-26

Figure 17-20: Scenario III – General resistance mechanism - 26-28

Discussion - 29

Caveats and excuses - 4

Future Directions - 34

References - 35

Appendix - 38

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