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Updated: May 25, 2025

Author Spotlight: Investigating Bacteriophage-Induced Immune Responses in Gnotobiotic Mice

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Published on: January 26, 2024

Factors Affecting Phage-Bacteria Coevolution Dynamics.

Ghadeer Jdeed¹, Bogdana Kravchuk¹, Nina V Tikunova¹

¹Institute of Chemical Biology and Fundamental Medicine, Siberian Branch of Russian Academy of Sciences, Prospect Lavrentieva 8, Novosibirsk 630090, Russia.

|February 26, 2025

Summary

This summary is machine-generated.

Bacteriophage (phage) and bacteria coevolution is key for phage therapy. Understanding evolutionary dynamics helps predict host adaptation and optimize phage treatments against antibiotic-resistant bacteria.

Keywords:

arms race dynamics coevolution fluctuating selection dynamics host range expansion phage adaptation phage therapy

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Area of Science:

Microbiology
Evolutionary Biology
Genetics

Background:

Bacteriophages (phages) have coevolved with bacteria for billions of years.
The rise of antibiotic resistance increases the importance of phage therapy.
Investigating phage evolution dynamics offers insights for pre-adapting phages for therapeutic use.

Purpose of the Study:

To review key findings on phage-bacteria coevolution.
To focus on concepts describing phage-bacteria interactions.
To examine factors influencing interaction dynamics and their effects on coevolution.

Main Methods:

Review of existing research on phage-bacteria coevolutionary dynamics.
Analysis of theoretical models describing phage-bacteria interactions (arms race vs. fluctuating selection).
Synthesis of factors influencing the dominance of specific evolutionary dynamics.

Main Results:

Two primary models, arms race and fluctuating selection, describe phage-bacteria interactions.
Various factors influence which dynamics prevail in phage-host systems.
Coevolutionary dynamics impact bacterial and phage adaptation, coexistence, and stability.

Conclusions:

Understanding phage-bacteria coevolution is crucial for advancing phage therapy.
Identifying factors that drive specific evolutionary dynamics can inform therapeutic strategies.
The study of these dynamics is essential for predicting outcomes in phage-mediated treatments and managing antibiotic resistance.