The Population Genetics of Collateral Resistance and Sensitivity

Ardell, Sarah M.; Kryazhimskiy, Sergey

doi:10.1101/2020.08.25.267484

Cited by 7 publications

(4 citation statements)

References 131 publications

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“…S11; SI Section 4). These limited anti-correlations suggest that the long-term tradeoffs observed at the population level (2) might not necessarily reflect an underlying physiological constraint, but may actually be an emergent property of their in vivo evolutionary dynamics (30).…”

Section: Resultsmentioning

confidence: 99%

Quantifying the adaptive landscape of commensal gut bacteria using high-resolution lineage tracking

Wong

Good

2022

Preprint

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Gut microbiota can adapt to their host environment by rapidly acquiring new mutations. However, the dynamics of this process are difficult to characterize in dominant gut species in their complex in vivo environment. Here we show that the fine-scale dynamics of genome-wide transposon libraries can enable quantitative inferences of these in vivo evolutionary forces. By analyzing >400,000 lineages across four human Bacteroides strains in gnotobiotic mice, we observed positive selection on thousands of previously hidden mutations – most of which were unrelated to their original gene knockouts. The spectrum of fitness benefits varied between species, and displayed diverse tradeoffs over time and in different dietary conditions. These results suggest that within-host adaptations arise from an intense competition between numerous contending mutations, which can strongly influence their emergent evolutionary tradeoffs.

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Section: Resultsmentioning

confidence: 99%

Quantifying the adaptive landscape of commensal gut bacteria using high-resolution lineage tracking

Wong

Good

2022

Preprint

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“…More complex patterns of correlated fitness changes across conditions, such as those that underlie more generalist phenotypes, can result from more general relationships between fitness effects in different environments. Recent experimental and theoretical work has also analyzed how these distributions of mutational effects across environments can lead to an interplay between chance and contingency in determining both the typical pleiotropic consequences of adaptation and the predictability of these effects (Jerison et al 2020;Ardell and Kryazhimskiy 2020).…”

Section: Introductionmentioning

confidence: 99%

Dynamics and variability in the pleiotropic effects of adaptation in laboratory budding yeast populations

Bakerlee

Phillips

et al. 2021

eLife

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Evolutionary adaptation to a constant environment is driven by the accumulation of mutations which can have a range of unrealized pleiotropic effects in other environments. These pleiotropic consequences of adaptation can influence the emergence of specialists or generalists, and are critical for evolution in temporally or spatially fluctuating environments. While many experiments have examined the pleiotropic effects of adaptation at a snapshot in time, very few have observed the dynamics by which these effects emerge and evolve. Here, we propagated hundreds of diploid and haploid laboratory budding yeast populations in each of three environments, and then assayed their fitness in multiple environments over 1000 generations of evolution. We find that replicate populations evolved in the same condition share common patterns of pleiotropic effects across other environments, which emerge within the first several hundred generations of evolution. However, we also find dynamic and environment-specific variability within these trends: variability in pleiotropic effects tends to increase over time, with the extent of variability depending on the evolution environment. These results suggest shifting and overlapping contributions of chance and contingency to the pleiotropic effects of adaptation, which could influence evolutionary trajectories in complex environments that fluctuate across space and time.

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“…In addition, recent studies that support the role of contingency in evolution might be explained by the specificity of mutation effects, adaptive landscape topography or environmental context [62,63]. In the public health arena, the abstraction has obvious connections to continued efforts to explain and predict the evolution of antibiotic resistance and support modern efforts that invoke increasingly modern theory and experimental approaches to understand the nature of how mutations influence drug resistance [64,65,66,67].…”

Section: Discussionmentioning

confidence: 99%

The mutation effect reaction norm (Mu-RN) highlights environmentally dependent mutation effects and epistatic interactions

Ogbunugafor

2021

Preprint

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Measuring the fitness effects of mutations and epistasis remain central yet provocative concepts in evolutionary and population genetics. In addition to the baseline complexity that arises from the notion that genetic information can interact in a nonlinear way, recent studies have revealed that interactions can change as a function of environmental context. Here I propose the fusion of measurements of the effect of mutations and physiological epistasis with the reaction norm, a central abstraction used to depict genotype by environment interactions. In doing so, I formalize the notion of a "mutation effect reaction norm" (MERN) as an instrument through which one can analyze or depict the phenotypic consequences of interactions between mutations across environmental contexts. I demonstrate its utility through a discussion of the signature of mutations that undermine reverse evolution of antimicrobial resistance. In closing, I argue that the mutation effect reaction norm may help us resolve the dynamism of evolution across fitness seascapes through specific insight into how mutation effects and interactions are modulated by environmental context.

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The Population Genetics of Collateral Resistance and Sensitivity

Cited by 7 publications

References 131 publications

Quantifying the adaptive landscape of commensal gut bacteria using high-resolution lineage tracking

Quantifying the adaptive landscape of commensal gut bacteria using high-resolution lineage tracking

Dynamics and variability in the pleiotropic effects of adaptation in laboratory budding yeast populations

The mutation effect reaction norm (Mu-RN) highlights environmentally dependent mutation effects and epistatic interactions

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