Multi-scale Predictions of Drug Resistance Epidemiology Identify Design Principles for Rational Drug Design

Leighow, Scott M.; Liu, Chuan; Inam, Haider; Zhao, Boyang; Pritchard, Justin R.

doi:10.1016/j.celrep.2020.02.108

Cited by 20 publications

(23 citation statements)

References 52 publications

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“…Secondly, the discovery of a direct influence of mutation bias on evolutionary adaptation parallels recent reports that driver mutations in cancer reflect the underlying biases of cancer-associated mutational processes, including exogenous effects of UV light and tobacco exposure, and endogenous effects of DNA mismatch repair and APOBEC activity [49][50][51]. The increased predictability of such changes, due to mutational effects, can inform rational drug design, as has been suggested for drugs for leukemia, prostate cancer, breast cancer, and gastrointestinal stromal tumors [26]. The same may be true for designing antibiotic treatments for mycobacteria, which evolve multi-drug resistance via a sequence of mutations, several of which interact epistatically, such that only a subset of possible mutational trajectories to multi-drug resistance are possible [52].…”

Section: Discussionmentioning

confidence: 61%

“…A growing body of evidence suggests that specific mutation biases influence the types of genetic changes that cause adaptation [5,[19][20][21][22][23][24][25][26], consistent with a small body of theoretical work on how biases in the introduction of variationboth low-level mutational biases and higher-level systemic biases-are expected to influence evolution [33][34][35][36]. Here, we have developed and applied a general approach to assess how the mutation spectrum shapes the spectrum of adaptive substitutions.…”

Section: Discussionmentioning

confidence: 67%

“…However, modeling here and in other work [35,36] shows that mutation bias can influence adaptation across a range of conditions, including conditions that induce clonal interference among concurrent mutations. More broadly, while theoretical arguments are surely helpful for sharpening our understanding, ultimately the prevalence and magnitude of the mutational influence on adaptation is an empirical question, and the impact of mutational biases has now been shown for several different types of mutations, in a range of systems from bacteriophage to birds to somatic evolution in human cancers [5,[19][20][21][22][23][24][25][26].…”

Section: Discussionmentioning

confidence: 99%

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Mutation bias shapes the spectrum of adaptive substitutions

Cano

Rozhonova

Stoltzfus

et al. 2021

Preprint

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Evolutionary adaptation often occurs via the fixation of beneficial point mutations, but different types of mutation may differ in their relative frequencies within the collection of substitutions contributing to adaptation in any given species. Recent studies have established that this spectrum of adaptive substitutions is enriched for classes of mutations that occur at higher rates. Yet, little is known at a quantitative level about the precise extent of this enrichment, or its dependence on other factors such as the beneficial mutation supply or demographic conditions. Here we address the extent to which the mutation spectrum shapes the spectrum of adaptive amino acid substitutions by applying a codon-based negative binomial regression model to three large data sets that include thousands of amino acid changes identified in natural and experimental adaptation in S. cerevisiae, E. coli, and M. tuberculosis. We find that the mutation spectrum has a strong and roughly proportional influence on the spectrum of adaptive substitutions in all three species. In fact, we find that by inferring the mutation rates that best explain the spectrum of adaptive substitutions, we can accurately recover species-specific mutational spectra obtained via mutation accumulation experiments. We complement this empirical analysis with simulations to determine the factors that influence how closely the spectrum of adaptive substitutions mirrors the spectrum of amino acid variants introduced by mutation, and find that the predictive power of mutation depends on multiple factors including population size and the breadth of the mutational target for adaptation.

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Section: Discussionmentioning

confidence: 61%

Section: Discussionmentioning

confidence: 67%

Section: Discussionmentioning

confidence: 99%

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Mutation bias shapes the spectrum of adaptive substitutions

Cano

Rozhonova

Stoltzfus

et al. 2021

Preprint

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“…By altering the pool of mutations available for selection, mutation spectra may determine the genetic basis of adaptation (10,13,14) and drive convergent evolution (15,16). Finally, from a practical standpoint, mutational biases can shape the evolution of resistance to antibiotics (11,17,18) and anticancer drugs (19). However, we lack direct experimental evidence demonstrating the fitness consequences of mutation spectra.…”

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confidence: 99%

Shifts in mutation spectra enhance access to beneficial mutations

Sane

Diwan

Bhat

et al. 2020

Preprint

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SUMMARYMutations are critical for evolutionary change. Although mutation spectra (mutational biases) vary greatly across organisms, we lack direct evidence of their evolutionary consequences. Here, we show experimentally that a biased spectrum alters the distribution of fitness effects in a bacterium, and should facilitate adaptation by increasing beneficial mutations and reducing genetic load. Adaptive walk simulations show that this advantage arises via better sampling of mutational classes that were poorly explored by the ancestor. Hence, reversing the spectrum of a biased ancestor is generally advantageous, while introducing bias in an unbiased ancestor is selectively neutral. Indeed, across bacterial lineages, evolutionary transitions in DNA repair enzymes – which shape spectra – typically reverse ancestral bias. These broad consequences of mutation spectra imply a major role in shaping evolutionary dynamics.

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“… 18 ). At the same time, multiple studies have now shown that adaptive substitutions are enriched for mutationally likely changes ( 5 , 19 – 27 ). For instance, the influence of a mutational bias favoring transitions is evident in the evolution of antibiotic resistance in Mycobacterium tuberculosis ( 5 ).…”

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confidence: 99%

Mutation bias shapes the spectrum of adaptive substitutions

Cano

Rozhoňová

Stoltzfus

et al. 2022

Proc. Natl. Acad. Sci. U.S.A.

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Evolutionary adaptation often occurs by the fixation of beneficial mutations. This mode of adaptation can be characterized quantitatively by a spectrum of adaptive substitutions, i.e., a distribution for types of changes fixed in adaptation. Recent work establishes that the changes involved in adaptation reflect common types of mutations, raising the question of how strongly the mutation spectrum shapes the spectrum of adaptive substitutions. We address this question with a codon-based model for the spectrum of adaptive amino acid substitutions, applied to three large datasets covering thousands of amino acid changes identified in natural and experimental adaptation in Saccharomyces cerevisiae, Escherichia coli, and Mycobacterium tuberculosis. Using species-specific mutation spectra based on prior knowledge, we find that the mutation spectrum has a proportional influence on the spectrum of adaptive substitutions in all three species. Indeed, we find that by inferring the mutation rates that best explain the spectrum of adaptive substitutions, we can accurately recover the species-specific mutation spectra. However, we also find that the predictive power of the model differs substantially between the three species. To better understand these differences, we use population simulations to explore the factors that influence how closely the spectrum of adaptive substitutions mirrors the mutation spectrum. The results show that the influence of the mutation spectrum decreases with increasing mutational supply (Nμ) and that predictive power is strongly affected by the number and diversity of beneficial mutations.

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Multi-scale Predictions of Drug Resistance Epidemiology Identify Design Principles for Rational Drug Design

Cited by 20 publications

References 52 publications

Mutation bias shapes the spectrum of adaptive substitutions

Mutation bias shapes the spectrum of adaptive substitutions

Shifts in mutation spectra enhance access to beneficial mutations

Mutation bias shapes the spectrum of adaptive substitutions

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