Mutation induced extinction in finite populations: lethal mutagenesis and lethal isolation

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.

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.

Noise-induced bistability in the fate of cancer phenotypic quasispecies: a bit-strings approach

Tumor cell populations are highly heterogeneous. Such heterogeneity, both at genotypic and phenotypic levels, is a key feature during tumorigenesis. How to investigate the impact of this heterogeneity in the dynamics of tumors cells becomes an important issue. Here we explore a stochastic model describing the competition dynamics between a pool of heterogeneous cancer cells with distinct phenotypes and healthy cells. This model is used to explore the role of demographic fluctuations on the transitions involving tumor clearance. Our results show that for large population sizes, when demographic fluctuations are negligible, there exists a sharp transition responsible for tumor cells extinction at increasing tumor cells' mutation rates. This result is consistent with a mean field model developed for the same system. The mean field model reveals only monostability scenarios, in which either the dominance of the tumor cells or the dominance of the healthy cells is found. Interestingly, the stochastic model shows that for small population sizes the monostability behavior disappears, involving the presence of noise-induced bistability. The impact of the initial populations of cells in the fate of the cell populations is investigated, as well as the transient times towards the healthy and the cancer states.

An Integrative Approach to Virus-Host Protein-Protein Interactions

Since cell regulation and protein expression can be dramatically altered upon infection by viruses, studying the mechanisms by which viruses infect cells and the regulatory networks they disrupt is essential to understanding viral pathogenicity. This line of study can also lead to discoveries about the workings of host cells themselves. Computational methods are rapidly being developed to investigate viral-host interactions, and here we highlight recent methods and the insights that they have revealed so far, with a particular focus on methods that integrate different types of data. We also review the challenges of working with viruses compared with traditional cellular biology, and the limitations of current experimental and informatics methods.

Two sides of the same coin: A population genetics perspective on lethal mutagenesis and mutational meltdown

The extinction of RNA virus populations upon application of a mutagenic drug is frequently referred to as evidence for the existence of an error threshold, above which the population cannot sustain the mutational load. To explain the extinction process after reaching this threshold, models of lethal mutagenesis have been proposed, in which extinction is described as a deterministic (and thus population size-independent) process. As a separate body of literature, the population genetics community has developed models of mutational meltdown, which focus on the stochastic (and thus population-size dependent) processes governing extinction. However, recent extensions of both models have blurred these boundaries. Here, we first clarify definitions in terms of assumptions, expectations, and relevant parameter spaces, and then assess similarities and differences. As concepts from both fields converge, we argue for a unified theoretical framework that is focused on the evolutionary processes at play, rather than dispute over terminology.

An experimental evaluation of drug-induced mutational meltdown as an antiviral treatment strategy

The rapid evolution of drug resistance remains a critical public health concern. The treatment of influenza A virus (IAV) has proven particularly challenging, due to the ability of the virus to develop resistance against current antivirals and vaccines. Here, we evaluate a novel antiviral drug therapy, favipiravir, for which the mechanism of action in IAV involves an interaction with the viral RNA-dependent RNA polymerase resulting in an effective increase in the viral mutation rate. We used an experimental evolution framework, combined with novel population genetic method development for inference from time-sampled data, to evaluate the effectiveness of favipiravir against IAV. Evaluating whole genome polymorphism data across 15 time points under multiple drug concentrations and in controls, we present the first evidence for the ability of IAV populations to effectively adapt to low concentrations of favipiravir. In contrast, under high concentrations, we observe population extinction, indicative of mutational meltdown. We discuss the observed dynamics with respect to the evolutionary forces at play and emphasize the utility of evolutionary theory to inform drug development.

Abrupt transitions to tumor extinction: a phenotypic quasispecies model

The dynamics of heterogeneous tumor cell populations competing with healthy cells is an important topic in cancer research with deep implications in biomedicine. Multitude of theoretical and computational models have addressed this issue, especially focusing on the nature of the transitions governing tumor clearance as some relevant model parameters are tuned. In this contribution, we analyze a mathematical model of unstable tumor progression using the quasispecies framework. Our aim is to define a minimal model incorporating the dynamics of competition between healthy cells and a heterogeneous population of cancer cell phenotypes involving changes in replication-related genes (i.e., proto-oncogenes and tumor suppressor genes), in genes responsible for genomic stability, and in house-keeping genes. Such mutations or loss of genes result into different phenotypes with increased proliferation rates and/or increased genomic instabilities. Despite bifurcations in the classical deterministic quasispecies model are typically given by smooth, continuous shifts (i.e., transcritical bifurcations), we here identify a novel type of bifurcation causing an abrupt transition to tumor extinction. Such a bifurcation, named as trans-heteroclinic, is characterized by the exchange of stability between two distant fixed points (that do not collide) involving tumor persistence and tumor clearance. The increase of mutation and/or the decrease of the replication rate of tumor cells involves this catastrophic shift of tumor cell populations. The transient times near bifurcation thresholds are also characterized, showing a power law dependence of exponent [Formula: see text] of the transients as mutation is changed near the bifurcation value. These results are discussed in the context of targeted cancer therapy as a possible therapeutic strategy to force a catastrophic shift by simultaneously delivering mutagenic and cytotoxic drugs inside tumor cells.

Impact of increased mutagenesis on adaptation to high temperature in bacteriophage Qβ

RNA viruses replicate with very high error rates, which makes them more sensitive to additional increases in this parameter. This fact has inspired an antiviral strategy named lethal mutagenesis, which is based on the artificial increase of the error rate above a threshold incompatible with virus infectivity. A relevant issue concerning lethal mutagenesis is whether incomplete treatments might enhance the adaptive possibilities of viruses. We have addressed this question by subjecting an RNA virus, the bacteriophage Qβ, to different transmission regimes in the presence or the absence of sublethal concentrations of the mutagenic nucleoside analogue 5-azacytidine (AZC). Populations obtained were subsequently exposed to a non-optimal temperature and analyzed to determine their consensus sequences. Our results show that previously mutagenized populations rapidly fixed a specific set of mutations upon propagation at the new temperature, suggesting that the expansion of the mutant spectrum caused by AZC has an influence on later evolutionary behavior.

Causes of evolutionary rate variation among protein sites

It has long been recognized that certain sites within a protein, such as sites in the protein core or catalytic residues in enzymes, are evolutionarily more conserved than other sites. However, our understanding of rate variation among sites remains surprisingly limited. Recent progress to address this includes the development of a wide array of reliable methods to estimate site-specific substitution rates from sequence alignments. In addition, several molecular traits have been identified that correlate with site-specific mutation rates, and novel mechanistic biophysical models have been proposed to explain the observed correlations. Nonetheless, current models explain, at best, approximately 60% of the observed variance, highlighting the limitations of current methods and models and the need for new research directions.

Theories of Lethal Mutagenesis: From Error Catastrophe to Lethal Defection

RNA viruses get extinct in a process called lethal mutagenesis when subjected to an increase in their mutation rate, for instance, by the action of mutagenic drugs. Several approaches have been proposed to understand this phenomenon. The extinction of RNA viruses by increased mutational pressure was inspired by the concept of the error threshold. The now classic quasispecies model predicts the existence of a limit to the mutation rate beyond which the genetic information of the wild type could not be efficiently transmitted to the next generation. This limit was called the error threshold, and for mutation rates larger than this threshold, the quasispecies was said to enter into error catastrophe. This transition has been assumed to foster the extinction of the whole population. Alternative explanations of lethal mutagenesis have been proposed recently. In the first place, a distinction is made between the error threshold and the extinction threshold, the mutation rate beyond which a population gets extinct. Extinction is explained from the effect the mutation rate has, throughout the mutational load, on the reproductive ability of the whole population. Secondly, lethal defection takes also into account the effect of interactions within mutant spectra, which have been shown to be determinant for the understanding the extinction of RNA virus due to an augmented mutational pressure. Nonetheless, some relevant issues concerning lethal mutagenesis are not completely understood yet, as so survival of the flattest, i.e. the development of resistance to lethal mutagenesis by evolving towards mutationally more robust regions of sequence space, or sublethal mutagenesis, i.e., the increase of the mutation rate below the extinction threshold which may boost the adaptability of RNA virus, increasing their ability to develop resistance to drugs (including mutagens). A better design of antiviral therapies will still require an improvement of our knowledge about lethal mutagenesis.

Merging molecular mechanism and evolution: theory and computation at the interface of biophysics and evolutionary population genetics

The variation among sequences and structures in nature is both determined by physical laws and by evolutionary history. However, these two factors are traditionally investigated by disciplines with different emphasis and philosophy-molecular biophysics on one hand and evolutionary population genetics in another. Here, we review recent theoretical and computational approaches that address the crucial need to integrate these two disciplines. We first articulate the elements of these approaches. Then, we survey their contribution to our mechanistic understanding of molecular evolution, the polymorphisms in coding region, the distribution of fitness effects (DFE) of mutations, the observed folding stability of proteins in nature, and the distribution of protein folds in genomes.

Variability in mutational fitness effects prevents full lethal transitions in large quasispecies populations

The distribution of mutational fitness effects (DMFE) is crucial to the evolutionary fate of quasispecies. In this article we analyze the effect of the DMFE on the dynamics of a large quasispecies by means of a phenotypic version of the classic Eigen's model that incorporates beneficial, neutral, deleterious, and lethal mutations. By parameterizing the model with available experimental data on the DMFE of Vesicular stomatitis virus (VSV) and Tobacco etch virus (TEV), we found that increasing mutation does not totally push the entire viral quasispecies towards deleterious or lethal regions of the phenotypic sequence space. The probability of finding regions in the parameter space of the general model that results in a quasispecies only composed by lethal phenotypes is extremely small at equilibrium and in transient times. The implications of our findings can be extended to other scenarios, such as lethal mutagenesis or genomically unstable cancer, where increased mutagenesis has been suggested as a potential therapy.

Extinction of hepatitis C virus by ribavirin in hepatoma cells involves lethal mutagenesis

Lethal mutagenesis, or virus extinction produced by enhanced mutation rates, is under investigation as an antiviral strategy that aims at counteracting the adaptive capacity of viral quasispecies, and avoiding selection of antiviral-escape mutants. To explore lethal mutagenesis of hepatitis C virus (HCV), it is important to establish whether ribavirin, the purine nucleoside analogue used in anti-HCV therapy, acts as a mutagenic agent during virus replication in cell culture. Here we report the effect of ribavirin during serial passages of HCV in human hepatoma Huh-7.5 cells, regarding viral progeny production and complexity of mutant spectra. Ribavirin produced an increase of mutant spectrum complexity and of the transition types associated with ribavirin mutagenesis, resulting in HCV extinction. Ribavirin-mediated depletion of intracellular GTP was not the major contributory factor to mutagenesis since mycophenolic acid evoked a similar decrease in GTP without an increase in mutant spectrum complexity. The intracellular concentration of the other nucleoside-triphosphates was elevated as a result of ribavirin treatment. Mycophenolic acid extinguished HCV without an intervening mutagenic activity. Ribavirin-mediated, but not mycophenolic acid-mediated, extinction of HCV occurred via a decrease of specific infectivity, a feature typical of lethal mutagenesis. We discuss some possibilities to explain disparate results on ribavirin mutagenesis of HCV.

Distinct groups of repetitive families preserved in mammals correspond to different periods of regulatory innovations in vertebrates

BACKGROUND

Mammalian genomes are repositories of repetitive DNA sequences derived from transposable elements (TEs). Typically, TEs generate multiple, mostly inactive copies of themselves, commonly known as repetitive families or families of repeats. Recently, we proposed that families of TEs originate in small populations by genetic drift and that the origin of small subpopulations from larger populations can be fueled by biological innovations.

RESULTS

We report three distinct groups of repetitive families preserved in the human genome that expanded and declined during the three previously described periods of regulatory innovations in vertebrate genomes. The first group originated prior to the evolutionary separation of the mammalian and bird lineages and the second one during subsequent diversification of the mammalian lineages prior to the origin of eutherian lineages. The third group of families is primate-specific.

CONCLUSIONS

The observed correlation implies a relationship between regulatory innovations and the origin of repetitive families. Consistent with our previous hypothesis, it is proposed that regulatory innovations fueled the origin of new subpopulations in which new repetitive families became fixed by genetic drift.