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Evolutionary Dynamics of Accelerated Antiviral Resistance Development in Hypermutator Herpesvirus.

ABSTRACT: Antiviral therapy is constantly challenged by the emergence of resistant pathogens. At the same time, experimental approaches to understand and predict resistance are limited by long periods required for evolutionary processes. Here, we present a herpes simplex virus 1 mutant with impaired proofreading capacity and consequently elevated mutation rates. Comparing this hypermutator to parental wild type virus, we study the evolution of antiviral drug resistance in vitro. We model resistance development and elucidate underlying genetic changes against three antiviral substances. Our analyzes reveal no principle difference in the evolutionary behavior of both viruses, adaptive processes are overall similar, however significantly accelerated for the hypermutator. We conclude that hypermutator viruses are useful for modeling adaptation to antiviral therapy. They offer the benefit of expedited adaptation without introducing apparent bias and can therefore serve as an accelerator to predict natural evolution.

SUBMITTER: Hofler T

PROVIDER: S-EPMC11226790 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

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Evolutionary Dynamics of Accelerated Antiviral Resistance Development in Hypermutator Herpesvirus.

Höfler Thomas T Nascimento Mariana Mara MM Zeitlow Michaela M Kim Ji Yoon JY Trimpert Jakob J

Molecular biology and evolution 20240701 7

Antiviral therapy is constantly challenged by the emergence of resistant pathogens. At the same time, experimental approaches to understand and predict resistance are limited by long periods required for evolutionary processes. Here, we present a herpes simplex virus 1 mutant with impaired proofreading capacity and consequently elevated mutation rates. Comparing this hypermutator to parental wild type virus, we study the evolution of antiviral drug resistance in vitro. We model resistance develo ...[more]

PMID: 38879872

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Project description:The evolution of hypermutators in response to antibiotic treatment in both clinical and laboratory settings provides a unique context for the study of adaptive evolution. With increased mutation rates, the number of hitchhiker mutations within an evolving hypermutator population is remarkably high and presents substantial challenges in determining which mutations are adaptive. Intriguingly however, hypermutators also provide an opportunity to explore deeply the accessible evolutionary trajectories that lead to increased organism fitness, in this case the evolution of antibiotic resistance to the clinically relevant antibiotic tigecycline by the hospital pathogen Acinetobacter baumannii. Using a continuous culture system, AB210M, a clinically derived strain of A. baumannii, was evolved to tigecycline resistance. Analysis of the adapted populations showed that nearly all the successful lineages became hypermutators via movement of a mobile element to inactivate mutS. In addition, metagenomic analysis of population samples revealed another 896 mutations that occurred at a frequency greater than 5% in the population, while 38 phenotypically distinct individual colonies harbored a total of 1712 mutations. These mutations were scattered throughout the genome and affected ~40% of the coding sequences. The most highly mutated gene was adeS, a known tigecycline-resistance gene; however, adeS was not solely responsible for the high level of TGC resistance. Sixteen other genes stood out as potentially relevant to increased resistance. The five most prominent candidate genes (adeS, rpsJ, rrf, msbA, and gna) consistently re-emerged in subsequent replicate population studies suggesting they are likely to play a role in adaptation to tigecycline. Interestingly, the repeated evolution of a hypermutator phenotype in response to antibiotic stress illustrates not only a highly adaptive strategy to resistance, but also a remarkably efficient survey of successful evolutionary trajectories.

Project description:The emergence of drug resistant pathogens is a serious public health problem. It is a long-standing goal to predict rates of resistance evolution and design optimal treatment strategies accordingly. To this end, it is crucial to reveal the underlying causes of drug-specific differences in the evolutionary dynamics leading to resistance. However, it remains largely unknown why the rates of resistance evolution via spontaneous mutations and the diversity of mutational paths vary substantially between drugs. Here we comprehensively quantify the distribution of fitness effects (DFE) of mutations, a key determinant of evolutionary dynamics, in the presence of eight antibiotics representing the main modes of action. Using precise high-throughput fitness measurements for genome-wide Escherichia coli gene deletion strains, we find that the width of the DFE varies dramatically between antibiotics and, contrary to conventional wisdom, for some drugs the DFE width is lower than in the absence of stress. We show that this previously underappreciated divergence in DFE width among antibiotics is largely caused by their distinct drug-specific dose-response characteristics. Unlike the DFE, the magnitude of the changes in tolerated drug concentration resulting from genome-wide mutations is similar for most drugs but exceptionally small for the antibiotic nitrofurantoin, i.e., mutations generally have considerably smaller resistance effects for nitrofurantoin than for other drugs. A population genetics model predicts that resistance evolution for drugs with this property is severely limited and confined to reproducible mutational paths. We tested this prediction in laboratory evolution experiments using the "morbidostat", a device for evolving bacteria in well-controlled drug environments. Nitrofurantoin resistance indeed evolved extremely slowly via reproducible mutations-an almost paradoxical behavior since this drug causes DNA damage and increases the mutation rate. Overall, we identified novel quantitative characteristics of the evolutionary landscape that provide the conceptual foundation for predicting the dynamics of drug resistance evolution.

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Dataset Information

Evolutionary Dynamics of Accelerated Antiviral Resistance Development in Hypermutator Herpesvirus.

Publications

Evolutionary Dynamics of Accelerated Antiviral Resistance Development in Hypermutator Herpesvirus.

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