Dynamics and Fate of Beneficial Mutations Under Lineage Contamination by Linked Deleterious Mutations

Genetic consequences of effective and suboptimal dosing with mutagenic drugs in a hamster model of SARS-CoV-2 infection

Mutagenic antiviral drugs have shown promise against multiple viruses, but concerns have been raised about whether their use might promote the emergence of new and harmful viral variants. Recently, genetic signatures associated with molnupiravir use have been identified in the global SARS-COV-2 population. Here, we examine the consequences of using favipiravir and molnupiravir to treat SARS-CoV-2 infection in a hamster model, comparing viral genome sequence data collected from (1) untreated hamsters, and (2) from hamsters receiving effective and suboptimal doses of treatment. We identify a broadly linear relationship between drug dose and the extent of variation in treated viral populations, with a high proportion of this variation being composed of variants at frequencies of less than 1 per cent, below typical thresholds for variant calling. Treatment with an effective dose of antiviral drug was associated with a gain of between 7 and 10 variants per viral genome relative to drug-free controls: even after a short period of treatment a population founded by a transmitted virus could contain multiple sequence differences to that of the original host. Treatment with a suboptimal dose of drug showed intermediate gains of variants. No dose-dependent signal was identified in the numbers of single-nucleotide variants reaching frequencies in excess of 5 per cent. We did not find evidence to support the emergence of drug resistance or of novel immune phenotypes. Our study suggests that where onward transmission occurs, a short period of treatment with mutagenic drugs may be sufficient to generate a significant increase in the number of viral variants transmitted.

Mutational meltdown in asexual populations doomed to extinction

Asexual populations are expected to accumulate deleterious mutations through a process known as Muller's ratchet. Lynch and colleagues proposed that the ratchet eventually results in a vicious cycle of mutation accumulation and population decline that drives populations to extinction. They called this phenomenon mutational meltdown. Here, we analyze mutational meltdown using a multi-type branching process model where, in the presence of mutation, populations are doomed to extinction. We analyse the change in size and composition of the population and the time of extinction under this model.

Human deleterious mutation rate implies high fitness variance, with declining mean fitness compensated by rarer beneficial mutations of larger effect

Each new human has an expected Ud = 2 - 10 new deleterious mutations. This deluge of deleterious mutations cannot all be purged, and therefore accumulate in a declining fitness ratchet. Using a novel simulation framework designed to efficiently handle genome-wide linkage disequilibria across many segregating sites, we find that rarer, beneficial mutations of larger effect are sufficient to compensate fitness declines due to the fixation of many slightly deleterious mutations. Drift barrier theory posits a similar asymmetric pattern of fixations to explain ratcheting genome size and complexity, but in our theory, the cause is Ud > 1 rather than small population size. In our simulations, Ud ~2 - 10 generates high within-population variance in relative fitness; two individuals will typically differ in fitness by 15-40%. Ud ~2 - 10 also slows net adaptation by ~13%-39%. Surprisingly, fixation rates are more sensitive to changes in the beneficial than the deleterious mutation rate, e.g. a 10% increase in overall mutation rate leads to faster adaptation; this puts to rest dysgenic fears about increasing mutation rates due to rising paternal age.

The divergence of mean phenotypes under persistent directional selection

Numerous organismal traits, particularly at the cellular level, are likely to be under persistent directional selection across phylogenetic lineages. Unless all mutations affecting such traits have large enough effects to be efficiently selected in all species, gradients in mean phenotypes are expected to arise as a consequence of differences in the power of random genetic drift, which varies by approximately five orders of magnitude across the Tree of Life. Prior theoretical work examining the conditions under which such gradients can arise focused on the simple situation in which all genomic sites affecting the trait have identical and constant mutational effects. Here, we extend this theory to incorporate the more biologically realistic situation in which mutational effects on a trait differ among nucleotide sites. Pursuit of such modifications leads to the development of semi-analytic expressions for the ways in which selective interference arises via linkage effects in single-effects models, which then extend to more complex scenarios. The theory developed clarifies the conditions under which mutations of different selective effects mutually interfere with each others' fixation and shows how variance in effects among sites can substantially modify and extend the expected scaling relationships between mean phenotypes and effective population sizes.

The impact of frequently neglected model violations on bacterial recombination rate estimation: a case study in Mycobacterium canettii and Mycobacterium tuberculosis

Mycobacterium canettii is a causative agent of tuberculosis in humans, along with the members of the Mycobacterium tuberculosis complex. Frequently used as an outgroup to the M. tuberculosis complex in phylogenetic analyses, M. canettii is thought to offer the best proxy for the progenitor species that gave rise to the complex. Here, we leverage whole-genome sequencing data and biologically relevant population genomic models to compare the evolutionary dynamics driving variation in the recombining M. canettii with that in the nonrecombining M. tuberculosis complex, and discuss differences in observed genomic diversity in the light of expected levels of Hill-Robertson interference. In doing so, we highlight the methodological challenges of estimating recombination rates through traditional population genetic approaches using sequences called from populations of microorganisms and evaluate the likely mis-inference that arises owing to a neglect of common model violations including purifying selection, background selection, progeny skew, and population size change. In addition, we compare performance when full within-host polymorphism data are utilized, versus the more common approach of basing analyses on within-host consensus sequences.

The effect of weak clonal interference on average fitness trajectories in the presence of macroscopic epistasis

Adaptation dynamics on fitness landscapes is often studied theoretically in the strong-selection, weak-mutation regime. However, in a large population, multiple beneficial mutants can emerge before any of them fixes in the population. Competition between mutants is known as clonal interference, and while it is known to slow down the rate of adaptation (when compared to the strong-selection, weak-mutation model with the same parameters), how it affects the shape of long-term fitness trajectories in the presence of epistasis is an open question. Here, by considering how changes in fixation probabilities arising from weak clonal interference affect the dynamics of adaptation on fitness-parameterized landscapes, we find that the change in the shape of fitness trajectory arises only through changes in the supply of beneficial mutations (or equivalently, the beneficial mutation rate). Furthermore, a depletion of beneficial mutations as a population climbs up the fitness landscape can speed up the rescaled fitness trajectory (where adaptation speed is measured relative to its value at the start of the experiment), while an enhancement of the beneficial mutation rate does the opposite of slowing it down. Our findings suggest that by carrying out evolution experiments in both regimes (with and without clonal interference), one could potentially distinguish the different sources of macroscopic epistasis (fitness effect of mutations vs change in fraction of beneficial mutations).

Inferring the distribution of fitness effects in patient-sampled and experimental virus populations: two case studies

We here propose an analysis pipeline for inferring the distribution of fitness effects (DFE) from either patient-sampled or experimentally-evolved viral populations, that explicitly accounts for non-Wright-Fisher and non-equilibrium population dynamics inherent to pathogens. We examine the performance of this approach via extensive power and performance analyses, and highlight two illustrative applications - one from an experimentally-passaged RNA virus, and the other from a clinically-sampled DNA virus. Finally, we discuss how such DFE inference may shed light on major research questions in virus evolution, ranging from a quantification of the population genetic processes governing genome size, to the role of Hill-Robertson interference in dictating adaptive outcomes, to the potential design of novel therapeutic approaches to eradicate within-patient viral populations via induced mutational meltdown.

Soft selective sweeps: Addressing new definitions, evaluating competing models, and interpreting empirical outliers

The ability to accurately identify and quantify genetic signatures associated with soft selective sweeps based on patterns of nucleotide variation has remained controversial. We here provide counter viewpoints to recent publications in PLOS Genetics that have argued not only for the statistical identifiability of soft selective sweeps, but also for their pervasive evolutionary role in both Drosophila and HIV populations. We present evidence that these claims owe to a lack of consideration of competing evolutionary models, unjustified interpretations of empirical outliers, as well as to new definitions of the processes themselves. Our results highlight the dangers of fitting evolutionary models based on hypothesized and episodic processes without properly first considering common processes and, more generally, of the tendency in certain research areas to view pervasive positive selection as a foregone conclusion.

Identification of a permissive secondary mutation that restores the enzymatic activity of oseltamivir resistance mutation H275Y

Many oseltamivir resistance mutations exhibit fitness defects in the absence of drug pressure that hinders their propagation in hosts. Secondary permissive mutations can rescue fitness defects and facilitate the segregation of resistance mutations in viral populations. Previous studies have identified a panel of permissive or compensatory mutations in neuraminidase (NA) that restore the growth defect of the predominant oseltamivir resistance mutation (H275Y) in H1N1 influenza A. In prior work, we identified a hyperactive mutation (Y276F) that increased NA activity by approximately 70%. While Y276F had not been previously identified as a permissive mutation, we hypothesized that Y276F may counteract the defects caused by H275Y by buffering its reduced NA expression and enzyme activity. In this study we measured the relative fitness, NA activity, and surface expression, as well as sensitivity to oseltamivir, for several oseltamivir resistance mutations including H275Y in the wildtype or Y276F genetic background. Our results demonstrate that Y276F selectively rescues the fitness defect of H275Y by restoring its NA surface expression and enzymatic activity, elucidating the local compensatory structural impacts of Y276F on the adjacent H275Y. Importance The potential for influenza A virus (IAV) to cause pandemics makes understanding evolutionary mechanisms that impact drug resistance critical for developing surveillance and treatment strategies. Oseltamivir is the most widely used therapeutic strategy to treat IAV infections, but mutations in IAV can lead to drug resistance. The main oseltamivir resistance mutation, H275Y, occurs in the neuraminidase (NA) protein of IAV and reduces drug binding as well as NA function. Here, we identify a new helper mutation, Y276F that can rescue the functional defects of H275Y and contribute to the evolution of drug resistance in IAV.

Evolutionary Dynamics of Asexual Hypermutators Adapting to a Novel Environment

How microbes adapt to a novel environment is a central question in evolutionary biology. Although adaptive evolution must be fueled by beneficial mutations, whether higher mutation rates facilitate the rate of adaptive evolution remains unclear. To address this question, we cultured Escherichia coli hypermutating populations, in which a defective methyl-directed mismatch repair pathway causes a 140-fold increase in single-nucleotide mutation rates. In parallel with wild-type E. coli, populations were cultured in tubes containing Luria-Bertani broth, a complex medium known to promote the evolution of subpopulation structure. After 900 days of evolution, in three transfer schemes with different population-size bottlenecks, hypermutators always exhibited similar levels of improved fitness as controls. Fluctuation tests revealed that the mutation rates of hypermutator lines converged evolutionarily on those of wild-type populations, which may have contributed to the absence of fitness differences. Further genome-sequence analysis revealed that, although hypermutator populations have higher rates of genomic evolution, this largely reflects strong genetic linkage. Despite these linkage effects, the evolved population exhibits parallelism in fixed mutations, including those potentially related to biofilm formation, transcription regulation, and mutation-rate evolution. Together, these results are generally inconsistent with a hypothesized positive relationship between the mutation rate and the adaptive speed of evolution, and provide insight into how clonal adaptation occurs in novel environments.

Spike protein mutational landscape in India during the complete lockdown phase: Could Muller's ratchet be a future game-changer for COVID-19?

The dire need of effective preventive measures and treatment approaches against SARS-CoV-2 virus, causing COVID-19 pandemic, calls for an in-depth understanding of its evolutionary dynamics with attention to specific geographic locations, since lockdown and social distancing to prevent the virus spread could lead to distinct localized dynamics of virus evolution within and between countries owing to different environmental and host-specific selection pressures. To decipher any correlation between SARS-CoV-2 evolution and its epidemiology in India, we studied the mutational diversity of spike glycoprotein, the key player for the attachment, fusion and entry of virus to the host cell. For this, we analyzed the sequences of 630 Indian isolates as available in GISAID database till June 07, 2020 (during the time-period before the start of Unlock 1.0 in India on and from June 08, 2020), and detected the spike protein variants to emerge from two major ancestors – Wuhan-Hu-1/2019 and its D614G variant. Average stability of the docked spike protein – host receptor (S-R) complexes for these variants correlated strongly (R² = 0.96) with the fatality rates across Indian states. However, while more than half of the variants were found unique to India, 67% of all variants showed lower stability of S-R complex than the respective ancestral variants, indicating a possible fitness loss in recently emerged variants, despite a continuous increase in mutation rate. These results conform to the sharply declining fatality rate countrywide (>7-fold during April 11 – June 28, 2020). Altogether, while we propose the potential of S-R complex stability to track disease severity, we urge an immediate need to explore if SARS-CoV-2 is approaching mutational meltdown in India.

Imposed mutational meltdown as an antiviral strategy

Following widespread infections of the most recent coronavirus known to infect humans, SARS‐CoV‐2, attention has turned to potential therapeutic options. With no drug or vaccine yet approved, one focal point of research is to evaluate the potential value of repurposing existing antiviral treatments, with the logical strategy being to identify at least a short‐term intervention to prevent within‐patient progression, while long‐term vaccine strategies unfold. Here, we offer an evolutionary/population‐genetic perspective on one approach that may overwhelm the capacity for pathogen defense (i.e., adaptation) – induced mutational meltdown – providing an overview of key concepts, review of previous theoretical and experimental work of relevance, and guidance for future research. Applied with appropriate care, including target specificity, induced mutational meltdown may provide a general, rapidly implemented approach for the within‐patient eradication of a wide range of pathogens or other undesirable microorganisms.

Low mutation rates promote the evolution of advantageous traits by preventing interference from deleterious mutations

We studied how mutation rates promote the evolution of advantageous traits in an asexual population. First, to examine the effects of mutation rates on the evolution of an advantageous trait (high competitive ability), we carried out simulation analyses with competition between individuals for survival. Second, to examine the mechanism underlying the promotion of advantageous trait evolution, we calculated the probabilities that new favorable effects of mutations on the phenotype were acquired and that existing favorable effects were maintained. In the simulation analyses, advantageous traits evolved in the population with a low mutation rate; however, when the mutation rate was extremely low, advantageous traits evolved slowly because few beneficial mutations occurred. Then, the numerical calculations showed that the probability of acquiring new favorable effects of mutations on the phenotype and the probability of maintaining existing favorable effects are high if the mutation rate is low. The former occurs because, if the mutation rate is high, multiple mutations may occur in a genome, and even if beneficial mutations occur, their favorable effects may be masked by simultaneously occurring deleterious mutations. However, if the mutation rate is low, it is likely that only one beneficial mutation occurs, and its favorable effect on the phenotype is direct. In conclusion, low mutation rates are advantageous because they promote favorable phenotypic effects of mutations without interference from deleterious mutations; these low rates not only prevent the occurrence of deleterious mutations but also help maintain existing beneficial mutations and promote the evolution of advantageous traits.

Interference Effects of Deleterious and Beneficial Mutations in Large Asexual Populations

Linked beneficial and deleterious mutations are known to decrease the fixation probability of a favorable mutation in large asexual populations. While the hindering effect of strongly deleterious mutations on adaptive evolution has been well studied, how weakly deleterious mutations, either in isolation or with superior beneficial mutations, influence the rate of adaptation has not been fully explored. When the selection against the deleterious mutations is weak, the beneficial mutant can fix in many genetic backgrounds, besides the one it arose on. Here, taking this factor into account, I obtain an accurate analytical expression for the fixation probability of a beneficial mutant in an asexual population at mutation-selection balance. I then exploit this result along with clonal interference theory to investigate the joint effect of linked beneficial and deleterious mutations on the rate of adaptation, and identify parameter regions where it is reduced due to interference by either beneficial or deleterious or both types of mutations. I also study the evolution of mutation rates in adapting asexual populations, and find that linked beneficial mutations have a stronger influence than the deleterious mutations on mutator fixation.

Increase in viability due to the accumulation of X chromosome mutations in Drosophila melanogaster males

To increase our understanding of the role of new X-chromosome mutations in adaptive evolution, single-X Drosophila melanogaster males were mated with attached-X chromosome females, allowing the male X chromosome to accumulate mutations over 28 generations. Contrary to our hypothesis that male viability would decrease over time, due to the accumulation and expression of X-linked recessive deleterious mutations in hemizygous males, viability significantly increased. This increase may be attributed to germinal selection and to new X-linked beneficial or compensatory mutations, possibly supporting the faster-X hypothesis.