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Dynamics of bacterial phenotype selection in a colonized host
1Department of Mathematics, Vanderbilt University, Nashville, TN 37240, USA. glenn.f.webb@vanderbilt.edu
Summary
Helicobacter pylori population dynamics in animal models reveal microbial evolution. This study quantifies phenotype changes, showing how mutation and selection drive bacterial adaptation during host colonization.
Area of Science:
- Microbial population dynamics
- Evolutionary biology
- Host-pathogen interactions
Background:
- Helicobacter pylori exhibits phenotype variability, particularly in Lewis antigen expression.
- This variability is driven by high mutation frequencies, providing a substrate for host-driven selection.
- Understanding these dynamics is crucial for modeling microbial evolution in vivo.
Purpose of the Study:
- To establish a quantifiable experimental model for in vivo microbial phenotype evolution using H. pylori colonization.
- To track H. pylori phenotype variability from initial inoculation to quasispecies establishment in animal hosts.
- To develop and apply a mathematical model to interpret colonization data and understand evolutionary processes.
Main Methods:
- Experimental colonization of mice and gerbils with H. pylori.
- Tracking of phenotype variability (Lewis antigen expression) over time (>10^3 generations).
- Development of a mathematical model to analyze population dynamics, distinguishing selection and mutation.
Main Results:
- Successful colonization and quasispecies establishment were observed in animal models.
- Data allowed for tracking of H. pylori phenotype evolution in a large population (>10^4 individuals).
- The mathematical model successfully quantified the roles of initial diversity, mutation, and selection.
Conclusions:
- H. pylori colonization in animal hosts provides a robust model for studying in vivo microbial evolution.
- The study quantifies the interplay between mutation, selection, and initial diversity in shaping microbial populations.
- The developed mathematical model offers a general framework for analyzing phenotype evolution in biological systems.