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Author Notes:

Correspondence to James Bull, bull@utexas.edu

All three authors contributed to all aspects of the paper, except that J.J.B. wrote the Mathematica files to generate the figures.

We thank Steve Abedon for comments and insight to the literature. Two reviewers gave useful advice on the manuscript.

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Subject:

Research Funding:

NIH grant numbers R01GM 122079 and P20GM 104420 (JJB), GM 091875 (BRL), and R01 GM124378 (IJM)

Keywords:

  • cocktail
  • dynamics
  • evolutionary prediction
  • mathematical model
  • within-host
  • Bacteria
  • Bacterial Infections
  • Bacteriophages
  • Biological Evolution
  • Computer Simulation
  • Humans
  • Models, Theoretical
  • Phage Therapy

Promises and pitfalls of in vivo evolution to improve phage therapy

Tools:

Journal Title:

Viruses

Volume:

Volume 11, Number 12

Publisher:

Type of Work:

Article | Final Publisher PDF

Abstract:

Phage therapy is the use of bacterial viruses (phages) to treat bacterial infections, a medical intervention long abandoned in the West but now experiencing a revival. Currently, therapeutic phages are often chosen based on limited criteria, sometimes merely an ability to plate on the pathogenic bacterium. Better treatment might result from an informed choice of phages. Here we consider whether phages used to treat the bacterial infection in a patient may specifically evolve to improve treatment on that patient or benefit subsequent patients. With mathematical and computational models, we explore in vivo evolution for four phage properties expected to influence therapeutic success: Generalized phage growth, phage decay rate, excreted enzymes to degrade protective bacterial layers, and growth on resistant bacteria. Within-host phage evolution is strongly aligned with treatment success for phage decay rate but only partially aligned for phage growth rate and growth on resistant bacteria. Excreted enzymes are mostly not selected for treatment success. Even when evolution and treatment success are aligned, evolution may not be rapid enough to keep pace with bacterial evolution for maximum benefit. An informed use of phages is invariably superior to naive reliance on within-host evolution.

Copyright information:

© 2019 by the authors. Licensee MDPI, Basel, Switzerland.

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
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