A Review of Using Mathematical Modeling to Improve Our Understanding of Bacteriophage, Bacteria, and Eukaryotic Interactions

Kathryn M. Styles*, Aidan T. Brown*, Antonia P. Sagona*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Phage therapy, the therapeutic usage of viruses to treat bacterial infections, has many theoretical benefits in the ‘post antibiotic era.’ Nevertheless, there are currently no approved mainstream phage therapies. One reason for this is a lack of understanding of the complex interactions between bacteriophage, bacteria and eukaryotic hosts. These three-component interactions are complex, with non-linear or synergistic relationships, anatomical barriers and genetic or phenotypic heterogeneity all leading to disparity between performance and efficacy in in vivo versus in vitro environments. Realistic computer or mathematical models of these complex environments are a potential route to improve the predictive power of in vitro studies for the in vivo environment, and to streamline lab work. Here, we introduce and review the current status of mathematical modeling and highlight that data on genetic heterogeneity and mutational stochasticity, time delays and population densities could be critical in the development of realistic phage therapy models in the future. With this in mind, we aim to inform and encourage the collaboration and sharing of knowledge and expertise between microbiologists and theoretical modelers, synergising skills and smoothing the road to regulatory approval and widespread use of phage therapy.
Original languageEnglish
Article number724767
Pages (from-to)1-17
Number of pages17
JournalFrontiers in Microbiology
Volume12
DOIs
Publication statusPublished - 21 Sep 2021

Keywords

  • bacteriophage
  • mathematical modelling
  • phage therapy
  • simulations
  • stochasticity
  • heterogeneity
  • communicable disease
  • antibiotic alternative

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