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Interactions between evolutionary processes at high mutation rates.

ABSTRACT: Evolution at high mutation rates is minimally affected by six processes: mutation-selection balance, error catastrophes, Muller's Ratchet, robustness and compensatory evolution, and clonal interference. Including all of these processes in a tractable, analytical model is difficult, but they can be captured in simulations that utilize realistic genotype-phenotype-fitness maps, as done here by modeling RNA folding. Subjecting finite, asexual populations to a range of mutation rates revealed simple criteria that predict when particular evolutionary processes are important. Populations were initiated with a genotype encoding the most fit phenotype. When purifying selection was strong relative to mutation, the initial genotype was replaced by one more mutationally robust, and the maximally fit phenotype was maintained in a mutation-selection balance where the deleterious mutation rate determined mean fitness. With weaker purifying selection, the most fit genotypes were lost. Although loss of the best genotype was ongoing and might have led to a progressive fitness decline, continual compensatory evolution led to an approximate fitness equilibration. Per total genomic mutation rate, mean fitness was similar for strong and weak purifying selection. These results represent a first step at separating interactions between evolutionary processes at high mutation rate, but additional theory is needed to interpret some outcomes.

SUBMITTER: Keller TE

PROVIDER: S-EPMC3389706 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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Interactions between evolutionary processes at high mutation rates.

Keller Thomas E TE Wilke Claus O CO Bull James J JJ

Evolution; international journal of organic evolution 20120319 7

Evolution at high mutation rates is minimally affected by six processes: mutation-selection balance, error catastrophes, Muller's Ratchet, robustness and compensatory evolution, and clonal interference. Including all of these processes in a tractable, analytical model is difficult, but they can be captured in simulations that utilize realistic genotype-phenotype-fitness maps, as done here by modeling RNA folding. Subjecting finite, asexual populations to a range of mutation rates revealed simple ...[more]

PMID: 22759303

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Project description:Resistance to the frontline antibiotic rifampicin constitutes a challenge to the treatment and control of tuberculosis. Here, we analyzed the mutational landscape of Mycobacterium smegmatis during long-term evolution with increasing concentrations of rifampicin, using a mutation accumulation assay combined with whole-genome sequencing. Antibiotic treatment enhanced the acquisition of mutations, doubling the genome-wide mutation rate of the wild-type cells. While antibiotic exposure led to extinction of almost all wild-type lines, the hypermutable phenotype of the ΔnucS mutant strain (noncanonical mismatch repair deficient) provided an efficient response to the antibiotic, leading to high rates of survival. This adaptative advantage resulted in the emergence of higher levels of rifampicin resistance, an accelerated acquisition of drug resistance mutations in rpoB (β RNA polymerase), and a wider diversity of evolutionary pathways that led to drug resistance. Finally, this approach revealed a subset of adaptive genes under positive selection with rifampicin that could be associated with the development of antibiotic resistance. IMPORTANCE Rifampicin is the most important first-line antibiotic against mycobacterial infections, including tuberculosis, one of the top causes of death worldwide. Acquisition of rifampicin resistance constitutes a major global public health problem that makes the control of the disease challenging. Here, we performed an experimental evolution assay under antibiotic selection to analyze the response and adaptation of mycobacteria, leading to the acquisition of rifampicin resistance. This approach explored the total number of mutations that arose in the mycobacterial genomes under long-term rifampicin exposure, using whole-genome sequencing. Our results revealed the effect of rifampicin at a genomic level, identifying different mechanisms and multiple pathways leading to rifampicin resistance in mycobacteria. Moreover, this study detected that an increase in the rate of mutations led to enhanced levels of drug resistance and survival. In summary, all of these results could be useful to understand and prevent the emergence of drug-resistant isolates in mycobacterial infections.

Dataset Information

Interactions between evolutionary processes at high mutation rates.

Publications

Interactions between evolutionary processes at high mutation rates.

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