With the rapid global spread of SARS-CoV-2, tremendous efforts have been focused upon potential treatment strategies (Li and De Clercq 2020). Evolutionary theory has an important role to play in this search, and we here discuss one potentially under-appreciated research avenue. Within the field of population genetics, the phenomenon of mutational meltdown—in which a population may become extinct owing to the accumulation of deleterious mutations—has been well studied both theoretically and experimentally. The key to understanding this effect is a consideration of the efficacy of natural selection. Because there are many more ways to disrupt rather than to improve genomic function, the vast majority of new fitnessimpacting mutations are deleterious rather than beneficial. Thus, if mutation rates are increased, the result is a disproportionate excess of variants that are detrimental to the organism. Because natural selection will not be able to purge this input of deleterious mutations if the mutational pressure is sufficiently large, these variants may remain in the population and even reach fixation. This deleterious load further restricts the ability of natural selection to purge additional variants, allowing more deleterious mutations to accumulate and fix, and so on—a snowball effect that can result in the eventual loss of the population (i.e., mutational meltdown). Lynch and Gabriel (1990) and Lynch et al. (1993) described this model, which is dependent on the carrying capacity of the population, the absolute population growth rate, the deleterious effect of mutations, and the deleterious mutation rate. Under this model, if the input of deleterious mutations is sufficiently high, the number of reproducing individuals will decline. Though the model of lethal mutagenesis is also commonly noted in this regard (e.g., Bull et al. 2007), the mutational meltdown framework is in fact more general, and critically incorporates the stochastic effects inherent to natural populations (see Matuszewski et al. 2017). While meltdown has been discussed largely in the negative context of a threat to small or endangered populations, it also has relevance in the positive context of inducing the extinction of a viral population within a patient. One drug in particular, favipiravir, has been demonstrated to inhibit the RNA-dependent RNA polymerase (RdRp) of RNA viruses (Furuta et al. 2013; Baranovich et al. 2013), and in vitro studies in influenza A virus (IAV) have specifically examined the relevance of a mutational-meltdown model in the presence of this inhibitor. Bank et al. (2016), utilizing experimental passaging at different drug concentrations, described potential viral adaptation at low-concentrations. However, at higher concentrations, mutations accumulated at a nearly linear rate until a transition point was reached, at which a sharp increase in mutational accumulation was observed, followed by population collapse. Significantly, as opposed to targeting a specific genomic region, this input of deleterious mutations is a genome-wide effect, raining deleterious variants on all functionally essential genomic regions. Also working in IAV, Ormond et al. (2017) examined the combined effect of favipiravir with oseltamivir, a widely-used treatment with well-studied resistance mutations. A similar mutational meltdown outcome was observed, with the selective sweeps of oseltamivir-resistant mutations appearing to actually speed population decline, owing to the resulting hitchhiking of linked deleterious variants in the viral population (and see the related work of Pénnison et al. 2017). We believe that these results at least suggest the potential therapeutic value of inducing mutational meltdown in SARS-CoV-2 patient populations. While interest in favipiravir is currently motivating clinical trials, with initial results as of March 2020 suggesting faster viral clearance * Jeffrey D. Jensen Jeffrey.D.Jensen@asu.edu

中文翻译：

---

将突变崩溃视为一种潜在的 SARS-CoV-2 治疗策略

随着 SARS-CoV-2 在全球的迅速传播，人们在潜在的治疗策略上付出了巨大的努力（Li 和 De Clercq 2020）。进化论在这项研究中发挥着重要作用，我们在这里讨论一个可能被低估的研究途径。在种群遗传学领域，突变崩溃现象——由于有害突变的积累，种群可能灭绝——在理论上和实验上都得到了很好的研究。理解这种效应的关键是考虑自然选择的功效。因为有更多的方法来破坏而不是改善基因组功能，所以绝大多数新的影响健康的突变是有害的而不是有益的。因此，如果突变率增加，结果是对生物体有害的变体过多。因为如果突变压力足够大，自然选择将无法清除这种有害突变的输入，因此这些变体可能会保留在种群中，甚至达到固定。这种有害负荷进一步限制了自然选择清除其他变异的能力，允许更多有害突变积累和修复，等等——雪球效应可能导致种群最终丧失（即突变崩溃）。林奇和加布里埃尔（1990）和林奇等人。（1993）描述了这个模型，它取决于种群的承载能力、绝对种群增长率、突变的有害影响和有害突变率。在这个模型下，如果有害突变的输入足够高，繁殖个体的数量就会下降。尽管致命诱变模型在这方面也很常见（例如，Bull 等人，2007 年），但突变崩溃框架实际上更为普遍，并且批判性地结合了自然种群固有的随机效应（参见 Matuszewski 等人，2017 年） ）。虽然在对小型或濒危人群构成威胁的负面背景下讨论了崩溃，但它在诱导患者体内病毒种群灭绝的积极背景下也具有相关性。特别是一种药物 favipiravir 已被证明可抑制 RNA 病毒的 RNA 依赖性 RNA 聚合酶 (RdRp) (Furuta et al. 2013; Baranovich et al. 2013)，甲型流感病毒 (IAV) 的体外研究专门检查了在这种抑制剂存在的情况下突变熔毁模型的相关性。银行等。(2016)，利用不同药物浓度的实验传代，描述了低浓度的潜在病毒适应。然而，在更高的浓度下，突变以几乎线性的速率积累，直到达到一个过渡点，在该点观察到突变积累急剧增加，随后种群崩溃。重要的是，与靶向特定基因组区域相反，这种有害突变的输入是一种全基因组效应，会在所有功能必需的基因组区域上产生有害变异。Ormond 等人也在 IAV 工作。（2017）检查了法匹拉韦与奥司他韦的联合作用，一种广泛使用的治疗方法，具有经过充分研究的抗性突变。观察到类似的突变崩溃结果，由于病毒种群中相关有害变异的搭便车（参见 Pénnison et al. 2017 的相关工作），奥司他韦耐药突变的选择性扫描似乎实际上加速了种群下降. 我们相信，这些结果至少表明了在 SARS-CoV-2 患者群体中诱导突变消融的潜在治疗价值。虽然目前对法匹拉韦的兴趣正在激发临床试验，但截至 2020 年 3 月的初步结果表明病毒清除速度更快 * Jeffrey D. Jensen Jeffrey.D.Jensen@asu.edu 由于病毒种群中相关有害变异的搭便车（参见 Pénnison et al. 2017 的相关工作），对奥司他韦耐药突变的选择性扫描似乎实际上加速了种群下降。我们相信，这些结果至少表明了在 SARS-CoV-2 患者群体中诱导突变消融的潜在治疗价值。虽然目前对法匹拉韦的兴趣正在激发临床试验，但截至 2020 年 3 月的初步结果表明病毒清除速度更快 * Jeffrey D. Jensen Jeffrey.D.Jensen@asu.edu 由于病毒种群中相关有害变异的搭便车（参见 Pénnison et al. 2017 的相关工作），对奥司他韦耐药突变的选择性扫描似乎实际上加速了种群下降。我们相信，这些结果至少表明了在 SARS-CoV-2 患者群体中诱导突变消融的潜在治疗价值。虽然目前对法匹拉韦的兴趣正在激发临床试验，但截至 2020 年 3 月的初步结果表明病毒清除速度更快 * Jeffrey D. Jensen Jeffrey.D.Jensen@asu.edu 我们相信，这些结果至少表明了在 SARS-CoV-2 患者群体中诱导突变消融的潜在治疗价值。虽然目前对法匹拉韦的兴趣正在激发临床试验，但截至 2020 年 3 月的初步结果表明病毒清除速度更快 * Jeffrey D. Jensen Jeffrey.D.Jensen@asu.edu 我们相信，这些结果至少表明了在 SARS-CoV-2 患者群体中诱导突变消融的潜在治疗价值。虽然目前对法匹拉韦的兴趣正在激发临床试验，但截至 2020 年 3 月的初步结果表明病毒清除速度更快 * Jeffrey D. Jensen Jeffrey.D.Jensen@asu.edu