How do monomorphic bacteria evolve? The Mycobacterium tuberculosis complex and the awkward population genetics of extreme clonality

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Authors

Christoph Stritt , Sebastien Gagneux

Abstract

Exchange of genetic material through sexual reproduction or horizontal gene transfer is ubiquitous in nature. Among the few outliers that rarely recombine and mainly evolve by de novo mutation are a group of deadly bacterial pathogens, including the causative agents of leprosy, plague, typhoid, and tuberculosis. The interplay of evolutionary processes is poorly understood in these organisms. Population genetic methods allowing to infer mutation, recombination, genetic drift, and natural selection make strong assumptions that are difficult to reconcile with clonal reproduction and fully linked genomes consisting mainly of coding regions. In this review, we highlight the challenges of extreme clonality by discussing population genetic inference with the Mycobacterium tuberculosis complex, a group of closely related obligate bacterial pathogens of mammals. We show how uncertainties underlying quantitative models and verbal arguments affect previous conclusions about the way these organisms evolve. A question mark remains behind various quantities of applied and theoretical interest, including mutation rates, the interpretation of nonsynonymous polymorphisms, or the role of genetic bottlenecks. Looking ahead, we discuss how new tools for evolutionary simulations, going beyond the traditional Wright-Fisher framework, promise a more rigorous treatment of basic evolutionary processes in clonal bacteria.

DOI

https://doi.org/10.32942/X2GW2P

Subjects

Evolution, Genetics and Genomics, Genomics, Life Sciences, Molecular Genetics, Pathogenic Microbiology, Population Biology

Keywords

clonality, mutation, recombination, genetic drift, natural selection, Simulation, monomorphic bacteria

Dates

Published: 2022-12-15 22:38

Last Updated: 2023-07-11 04:38

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License

CC-By Attribution-NonCommercial-NoDerivatives 4.0 International

Additional Metadata

Data and Code Availability Statement:
https://doi.org/10.5281/zenodo.8042695

Language:
English