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

Oral Favipiravir Exposure and Pharmacodynamic Effects in Adult Outpatients With Acute Influenza

BACKGROUND

The pharmacokinetics of oral favipiravir and the relationships of plasma concentrations to antiviral effects are incompletely studied in influenza.

METHODS

Serial plasma samples were collected from adults with uncomplicated influenza who were randomized to favipiravir (1800 mg twice a day on day 1, 800 mg twice a day on days 2 to 5; n = 827) or placebo (n = 419) in 2 phase 3 trials. Post hoc analyses assessed the frequency of reaching an average minimum concentration (Cmin) ≥20 µg/mL, its association with antiviral efficacy, and factors associated with reduced favipiravir exposure.

RESULTS

Wide interindividual variability existed in favipiravir concentrations, and this regimen failed to reach an average Cmin>20 µg/mL in 41%-43% of participants. Those attaining this threshold showed greater reductions in nasopharyngeal infectious virus titers on treatment days 2 and 3 and lower viral titer area under the curve compared to those who did not. Those with average Cmin <20 µg/mL had over 2-fold higher mean ratios of the metabolite T-705M1 to favipiravir, consistent with greater metabolism, and were more likely to weigh >80 kg (61.5%-64%).

CONCLUSIONS

Higher favipiravir levels with average Cmin>20 µg/mL were associated with larger antiviral effects and more rapid illness alleviation compared to placebo and to favipiravir recipients with lower average Cmin values in uncomplicated influenza. Clinical Trials Registration . NCT1068912 and NCT01728753.

Favipiravir biotransformation by a side-stream partial nitritation sludge: Transformation mechanisms, pathways and toxicity evaluation

Information on biotransformation of antivirals in the side-stream partial nitritation (PN) process was limited. In this study, a side-stream PN sludge was adopted to investigate favipiravir biotransformation under controlled ammonium and pH levels. Results showed that free nitrous acid (FNA) was an important factor that inhibited ammonia oxidation and the cometabolic biodegradation of favipiravir induced by ammonia oxidizing bacteria (AOB). The removal efficiency of favipiravir reached 12.6% and 35.0% within 6 days at the average FNA concentrations of 0.07 and 0.02 mg-N L-1, respectively. AOB-induced cometabolism was the sole contributing mechanism to favipiravir removal, excluding AOB-induced metabolism and heterotrophic bacteria-induced biodegradation. The growth of Escherichia coli was inhibited by favipiravir, while the AOB-induced cometabolism facilitated the alleviation of the antimicrobial activities with the formed transformation products. The biotransformation pathways were proposed based on the roughly identified structures of transformation products, which mainly involved hydroxylation, nitration, dehydrogenation and covalent bond breaking under enzymatic conditions. The findings would provide insights on enriching AOB abundance and enhancing AOB-induced cometabolism under FNA stress when targeting higher removal of antivirals during the side-stream wastewater treatment processes.

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.

Developing an appropriate evolutionary baseline model for the study of SARS-CoV-2 patient samples

Over the past 3 years, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread through human populations in several waves, resulting in a global health crisis. In response, genomic surveillance efforts have proliferated in the hopes of tracking and anticipating the evolution of this virus, resulting in millions of patient isolates now being available in public databases. Yet, while there is a tremendous focus on identifying newly emerging adaptive viral variants, this quantification is far from trivial. Specifically, multiple co-occurring and interacting evolutionary processes are constantly in operation and must be jointly considered and modeled in order to perform accurate inference. We here outline critical individual components of such an evolutionary baseline model-mutation rates, recombination rates, the distribution of fitness effects, infection dynamics, and compartmentalization-and describe the current state of knowledge pertaining to the related parameters of each in SARS-CoV-2. We close with a series of recommendations for future clinical sampling, model construction, and statistical analysis.

Heterogeneity in viral populations increases the rate of deleterious mutation accumulation

RNA viruses have high mutation rates, with the majority of mutations being deleterious. We examine patterns of deleterious mutation accumulation over multiple rounds of viral replication, with a focus on how cellular coinfection and heterogeneity in viral output affect these patterns. Specifically, using agent-based intercellular simulations we find, in agreement with previous studies, that coinfection of cells by viruses relaxes the strength of purifying selection, and thereby increases the rate of deleterious mutation accumulation. We further find that cellular heterogeneity in viral output exacerbates the rate of deleterious mutation accumulation, regardless of whether this heterogeneity in viral output is stochastic or is due to variation in cellular multiplicity of infection. These results highlight the need to consider the unique life histories of viruses and their population structure to better understand observed patterns of viral evolution.

The extinction time under mutational meltdown driven by high mutation rates

Mutational meltdown describes an eco-evolutionary process in which the accumulation of deleterious mutations causes a fitness decline that eventually leads to the extinction of a population. Possible applications of this concept include medical treatment of RNA virus infections based on mutagenic drugs that increase the mutation rate of the pathogen. To determine the usefulness and expected success of such an antiviral treatment, estimates of the expected time to mutational meltdown are necessary. Here, we compute the extinction time of a population under high mutation rates, using both analytical approaches and stochastic simulations. Extinction is the result of three consecutive processes: (a) initial accumulation of deleterious mutations due to the increased mutation pressure; (b) consecutive loss of the fittest haplotype due to Muller's ratchet; (c) rapid population decline toward extinction. We find accurate analytical results for the mean extinction time, which show that the deleterious mutation rate has the strongest effect on the extinction time. We confirm that intermediate-sized deleterious selection coefficients minimize the extinction time. Finally, our simulations show that the variation in extinction time, given a set of parameters, is surprisingly small.

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.

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.

US201 Study: A Phase 2, Randomized Proof-of-Concept Trial of Favipiravir for the Treatment of COVID-19

BACKGROUND

Favipiravir is used to treat influenza, and studies demonstrate that it has antiviral activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

METHODS

We performed a randomized, open-label, multicenter, phase 2 proof-of-concept trial of favipiravir in hospitalized adult patients with polymerase chain reaction (PCR)-positive coronavirus disease 2019 (COVID-19). Patients were randomized to standard of care (SOC) or favipiravir treatment (1800mg per os twice a day [b.i.d.] on day 1, followed by 1000mg b.i.d. for 13 days). The primary end point was time to viral clearance on day 29.

RESULTS

Fifty patients were enrolled and stratified by disease severity (critical disease, severe disease, or mild to moderate disease). Nineteen patients were censored from the event of viral clearance based on being SARS-CoV-2 PCR-negative at the study outset, being PCR-positive at day 29, or because of loss to follow-up. Data from the 31 remaining patients who achieved viral clearance show enhanced viral clearance in the favipiravir group compared with the SOC group by day 29, with 72% of the favipiravir group and 52% of the SOC group being evaluable for viral clearance through day 29. The median time to viral clearance was 16.0 days (90% CI, 12.0 to 29.0) in the favipiravir group and 30.0 days (90% CI, 12.0 to 31.0) in the SOC group. A post hoc analysis revealed an effect in the subgroup of patients who were neutralizing antibody-negative at randomization. Treatment-emergent adverse events were equally distributed between the groups.

CONCLUSIONS

We demonstrate that favipiravir can be safely administered to hospitalized adults with COVID-19 and believe that further studies are warranted.

CLINICALTRIALSGOV REGISTRATION

NCT04358549.

Interface-based design of the favipiravir-binding site in SARS-CoV-2 RNA-dependent RNA polymerase reveals mutations conferring resistance to chain termination

Favipiravir is a broad-spectrum inhibitor of viral RNA-dependent RNA polymerase (RdRp) currently being used to manage COVID-19. Accumulation of mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RdRp may facilitate antigenic drift, generating favipiravir resistance. Focussing on the chain-termination mechanism utilized by favipiravir, we used high-throughput interface-based protein design to generate > 100 000 designs of the favipiravir-binding site of RdRp and identify mutational hotspots. We identified several single-point mutants and designs having a sequence identity of 97%-98% with wild-type RdRp, suggesting that SARS-CoV-2 can develop favipiravir resistance with few mutations. Out of 134 mutations documented in the CoV-GLUE database, 63 specific mutations were already predicted as resistant in our calculations, thus attaining ˜ 47% correlation with the sequencing data. These findings improve our understanding of the potential signatures of adaptation in SARS-CoV-2 against favipiravir.

Modeling poliovirus replication dynamics from live time-lapse single-cell imaging data

Viruses experience selective pressure on the timing and order of events during infection to maximize the number of viable offspring they produce. Additionally, they may experience variability in cellular environments encountered, as individual eukaryotic cells can display variation in gene expression among cells. This leads to a dynamic phenotypic landscape that viruses must face to replicate. To examine replication dynamics displayed by viruses faced with this variable landscape, we have developed a method for fitting a stochastic mechanistic model of viral infection to time-lapse imaging data from high-throughput single-cell poliovirus infection experiments. The model's mechanistic parameters provide estimates of several aspects associated with the virus's intracellular dynamics. We examine distributions of parameter estimates and assess their variability to gain insight into the root causes of variability in viral growth dynamics. We also fit our model to experiments performed under various drug treatments and examine which parameters differ under these conditions. We find that parameters associated with translation and early stage viral replication processes are essential for the model to capture experimentally observed dynamics. In aggregate, our results suggest that differences in viral growth data generated under different treatments can largely be captured by steps that occur early in the replication process.

Development and Effects of Influenza Antiviral Drugs

Influenza virus is a highly contagious zoonotic respiratory disease that causes seasonal outbreaks each year and unpredictable pandemics occasionally with high morbidity and mortality rates, posing a great threat to public health worldwide. Besides the limited effect of vaccines, the problem is exacerbated by the lack of drugs with strong antiviral activity against all flu strains. Currently, there are two classes of antiviral drugs available that are chemosynthetic and approved against influenza A virus for prophylactic and therapeutic treatment, but the appearance of drug-resistant virus strains is a serious issue that strikes at the core of influenza control. There is therefore an urgent need to develop new antiviral drugs. Many reports have shown that the development of novel bioactive plant extracts and microbial extracts has significant advantages in influenza treatment. This paper comprehensively reviews the development and effects of chemosynthetic drugs, plant extracts, and microbial extracts with influenza antiviral activity, hoping to provide some references for novel antiviral drug design and promising alternative candidates for further anti-influenza drug development.

Favipiravir in Therapy of Viral Infections

Favipiravir (FPV) is a novel antiviral drug acting as a competitive inhibitor of RNA-dependent RNA polymerase (RdRp), preventing viral transcription and replication. FPV was approved in Japan in 2014 for therapy of influenza unresponsive to standard antiviral therapies. FPV was also used in the therapy of Ebola virus disease (EVD) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In this review, we discuss the mechanisms of action, pharmacokinetic parameters, toxicity, and adverse effects of FPV, as well as clinical studies evaluating the use of FPV in the therapy of influenza virus (IV) infection, EVD, and SARS-CoV-2 infection, along with its effectiveness in treating other human RNA infections.

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.

Influenza virus polymerase inhibitors in clinical development

Purpose of review

We review antivirals inhibiting subunits of the influenza polymerase complex that are advancing in clinical development.

Recent findings

Favipiravir, pimodivir, and baloxavir are inhibitory in preclinical models for influenza A viruses, including pandemic threat viruses and those resistant to currently approved antivirals, and two (favipiravir and baloxavir) also inhibit influenza B viruses. All are orally administered, although the dosing regimens vary. The polymerase basic protein 1 transcriptase inhibitor favipiravir has shown inconsistent clinical effects in uncomplicated influenza, and is teratogenic effects in multiple species, contraindicating its use in pregnancy. The polymerase basic protein 2 cap-binding inhibitor pimodivir displays antiviral effects alone and in combination with oseltamivir in uncomplicated influenza, although variants with reduced susceptibility emerge frequently during monotherapy. Single doses of the polymerase acidic protein cap-dependent endonuclease inhibitor baloxavir are effective in alleviating symptoms and rapidly inhibiting viral replication in otherwise healthy and higher risk patients with acute influenza, although variants with reduced susceptibility emerge frequently during monotherapy. Combinations of newer polymerase inhibitors with neuraminidase inhibitors show synergy in preclinical models and are currently undergoing clinical testing in hospitalized patients.

Summary

These new polymerase inhibitors promise to add to the clinical management options and overall control strategies for influenza virus infections.

Destabilization of the human RED-SMU1 splicing complex as a basis for host-directed antiinfluenza strategy

New therapeutic strategies targeting influenza are actively sought due to limitations in current drugs available. Host-directed therapy is an emerging concept to target host functions involved in pathogen life cycles and/or pathogenesis, rather than pathogen components themselves. From this perspective, we focused on an essential host partner of influenza viruses, the RED-SMU1 splicing complex. Here, we identified two synthetic molecules targeting an α-helix/groove interface essential for RED-SMU1 complex assembly. We solved the structure of the SMU1 N-terminal domain in complex with RED or bound to one of the molecules identified to disrupt this complex. We show that these compounds inhibiting RED-SMU1 interaction also decrease endogenous RED-SMU1 levels and inhibit viral mRNA splicing and viral multiplication, while preserving cell viability. Overall, our data demonstrate the potential of RED-SMU1 destabilizing molecules as an antiviral therapy that could be active against a wide range of influenza viruses and be less prone to drug resistance.

Inferring Demography and Selection in Organisms Characterized by Skewed Offspring Distributions

The recent increase in time-series population genomic data from experimental, natural, and ancient populations has been accompanied by a promising growth in methodologies for inferring demographic and selective parameters from such data. However, these methods have largely presumed that the populations of interest are well-described by the Kingman coalescent. In reality, many groups of organisms, including viruses, marine organisms, and some plants, protists, and fungi, typified by high variance in progeny number, may be best characterized by multiple-merger coalescent models. Estimation of population genetic parameters under Wright-Fisher assumptions for these organisms may thus be prone to serious mis-inference. We propose a novel method for the joint inference of demography and selection under the Ψ-coalescent model, termed Multiple-Merger Coalescent Approximate Bayesian Computation, or MMC-ABC. We first demonstrate mis-inference under the Kingman, and then exhibit the superior performance of MMC-ABC under conditions of skewed offspring distributions. In order to highlight the utility of this approach, we reanalyzed previously published drug-selection lines of influenza A virus. We jointly inferred the extent of progeny-skew inherent to viral replication and identified putative drug-resistance mutations.

Mutations in Influenza A Virus Neuraminidase and Hemagglutinin Confer Resistance against a Broadly Neutralizing Hemagglutinin Stem Antibody

Influenza A virus (IAV), a major cause of human morbidity and mortality, continuously evolves in response to selective pressures. Stem-directed, broadly neutralizing antibodies (sBnAbs) targeting the influenza virus hemagglutinin (HA) are a promising therapeutic strategy, but neutralization escape mutants can develop. We used an integrated approach combining viral passaging, deep sequencing, and protein structural analyses to define escape mutations and mechanisms of neutralization escape in vitro for the F10 sBnAb. IAV was propagated with escalating concentrations of F10 over serial passages in cultured cells to select for escape mutations. Viral sequence analysis revealed three mutations in HA and one in neuraminidase (NA). Introduction of these specific mutations into IAV through reverse genetics confirmed their roles in resistance to F10. Structural analyses revealed that the selected HA mutations (S123G, N460S, and N203V) are away from the F10 epitope but may indirectly impact influenza virus receptor binding, endosomal fusion, or budding. The NA mutation E329K, which was previously identified to be associated with antibody escape, affects the active site of NA, highlighting the importance of the balance between HA and NA function for viral survival. Thus, whole-genome population sequencing enables the identification of viral resistance mutations responding to antibody-induced selective pressure.IMPORTANCE Influenza A virus is a public health threat for which currently available vaccines are not always effective. Broadly neutralizing antibodies that bind to the highly conserved stem region of the influenza virus hemagglutinin (HA) can neutralize many influenza virus strains. To understand how influenza virus can become resistant or escape such antibodies, we propagated influenza A virus in vitro with escalating concentrations of antibody and analyzed viral populations by whole-genome sequencing. We identified HA mutations near and distal to the antibody binding epitope that conferred resistance to antibody neutralization. Additionally, we identified a neuraminidase (NA) mutation that allowed the virus to grow in the presence of high concentrations of the antibody. Virus carrying dual mutations in HA and NA also grew under high antibody concentrations. We show that NA mutations mediate the escape of neutralization by antibodies against HA, highlighting the importance of a balance between HA and NA for optimal virus function.

The mechanism of resistance to favipiravir in influenza

Favipiravir is a broad-spectrum antiviral that has shown promise in treatment of influenza virus infections, in particular due to the apparent lack of emergence of resistance mutations against the drug in cell culture or animal studies. We demonstrate here that a mutation in a conserved region of the viral RNA polymerase confers resistance to favipiravir in vitro and in cell culture. The resistance mutation has a cost to viral fitness, but this can be restored by a compensatory mutation in the polymerase. Our findings support the development of favipiravir-resistance diagnostic and surveillance testing strategies and reinforce the importance of considering combinations of therapies to treat influenza infections.

Favipiravir is a broad-spectrum antiviral that has shown promise in treatment of influenza virus infections. While emergence of resistance has been observed for many antiinfluenza drugs, to date, clinical trials and laboratory studies of favipiravir have not yielded resistant viruses. Here we show evolution of resistance to favipiravir in the pandemic H1N1 influenza A virus in a laboratory setting. We found that two mutations were required for robust resistance to favipiravir. We demonstrate that a K229R mutation in motif F of the PB1 subunit of the influenza virus RNA-dependent RNA polymerase (RdRP) confers resistance to favipiravir in vitro and in cell culture. This mutation has a cost to viral fitness, but fitness can be restored by a P653L mutation in the PA subunit of the polymerase. K229R also conferred favipiravir resistance to RNA polymerases of other influenza A virus strains, and its location within a highly conserved structural feature of the RdRP suggests that other RNA viruses might also acquire resistance through mutations in motif F. The mutations identified here could be used to screen influenza virus-infected patients treated with favipiravir for the emergence of resistance.

The Combined Effect of Oseltamivir and Favipiravir on Influenza A Virus Evolution

Influenza virus inflicts a heavy death toll annually and resistance to existing antiviral drugs has generated interest in the development of agents with novel mechanisms of action. Favipiravir is an antiviral drug that acts by increasing the genome-wide mutation rate of influenza A virus (IAV). Potential synergistic benefits of combining oseltamivir and favipiravir have been demonstrated in animal models of influenza, but the population-level effects of combining the drugs are unknown. In order to elucidate the underlying evolutionary processes at play, we performed genome-wide sequencing of IAV experimental populations subjected to serial passaging in vitro under a combined protocol of oseltamivir and favipiravir. We describe the interplay between mutation, selection, and genetic drift that ultimately culminates in population extinction. In particular, selective sweeps around oseltamivir resistance mutations reduce genome-wide variation while deleterious mutations hitchhike to fixation given the increased mutational load generated by favipiravir. This latter effect reduces viral fitness and accelerates extinction compared with IAV populations treated with favipiravir alone, but risks spreading both established and newly emerging mutations, including possible drug resistance mutations, if transmission occurs before the viral populations are eradicated.

Resistance of Echovirus 11 to ClO2 Is Associated with Enhanced Host Receptor Use, Altered Entry Routes, and High Fitness

Waterborne viruses can exhibit resistance to common water disinfectants, yet the mechanisms that allow them to tolerate disinfection are poorly understood. Here, we generated echovirus 11 (E11) with resistance to chlorine dioxide (ClO₂) by experimental evolution, and we assessed the associated genotypic and phenotypic traits. ClO₂ resistance emerged after E11 populations were repeatedly reduced (either by ClO₂-exposure or by dilution) and then regrown in cell culture. The resistance was linked to an improved capacity of E11 to bind to its host cells, which was further attributed to two potential causes: first, the resistant E11 populations possessed mutations that caused amino acid substitutions from ClO₂-labile to ClO₂-stable residues in the viral proteins, which likely increased the chemical stability of the capsid toward ClO₂. Second, resistant E11 mutants exhibited the capacity to utilize alternative cell receptors for host binding. Interestingly, the emergence of ClO₂ resistance resulted in an enhanced replicative fitness compared to the less resistant starting population. Overall this study contributes to a better understanding of the mechanism underlying disinfection resistance in waterborne viruses, and processes that drive resistance development.

Experimental adaptation of human echovirus 11 to ultraviolet radiation leads to resistance to disinfection and ribavirin

Ultraviolet light in the UVC range is a commonly used disinfectant to control viruses in clinical settings and water treatment. However, it is currently unknown whether human viral pathogens may develop resistance to such stressor. Here, we investigate the adaptation of an enteric pathogen, human echovirus 11, to disinfection by UVC, and characterized the underlying phenotypic and genotypic changes. Repeated exposure to UVC lead to a reduction in the UVC inactivation rate of approximately 15 per cent compared to that of the wild-type and the control populations. Time-series next-generation sequencing data revealed that this adaptation to UVC was accompanied by a decrease in the virus mutation rate. The inactivation efficiency of UVC was additionally compromised by a shift from first-order to biphasic inactivation kinetics, a form of 'viral persistence' present in the UVC resistant and control populations. Importantly, populations with biphasic inactivation kinetics also exhibited resistance to ribavirin, an antiviral drug that, as UVC, interferes with the viral replication. Overall, the ability of echovirus 11 to adapt to UVC is limited, but it may have relevant consequences for disinfection in clinical settings and water treatment plants.

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.