Institute for Cellular and Molecular Biology, University of Texas, Austin, Texas 78712.
Genetics. 2013 Oct;195(2):541-52. doi: 10.1534/genetics.113.154195. Epub 2013 Aug 9.
From population genetics theory, elevating the mutation rate of a large population should progressively reduce average fitness. If the fitness decline is large enough, the population will go extinct in a process known as lethal mutagenesis. Lethal mutagenesis has been endorsed in the virology literature as a promising approach to viral treatment, and several in vitro studies have forced viral extinction with high doses of mutagenic drugs. Yet only one empirical study has tested the genetic models underlying lethal mutagenesis, and the theory failed on even a qualitative level. Here we provide a new level of analysis of lethal mutagenesis by developing and evaluating models specifically tailored to empirical systems that may be used to test the theory. We first quantify a bias in the estimation of a critical parameter and consider whether that bias underlies the previously observed lack of concordance between theory and experiment. We then consider a seemingly ideal protocol that avoids this bias-mutagenesis of virions-but find that it is hampered by other problems. Finally, results that reveal difficulties in the mere interpretation of mutations assayed from double-strand genomes are derived. Our analyses expose unanticipated complexities in testing the theory. Nevertheless, the previous failure of the theory to predict experimental outcomes appears to reside in evolutionary mechanisms neglected by the theory (e.g., beneficial mutations) rather than from a mismatch between the empirical setup and model assumptions. This interpretation raises the specter that naive attempts at lethal mutagenesis may augment adaptation rather than retard it.
从群体遗传学理论来看，提高大群体的突变率应该会逐渐降低平均适合度。如果适合度下降足够大，那么这个种群将会在一个被称为致死性诱变的过程中灭绝。致死性诱变已被病毒学文献认可为一种有前途的病毒治疗方法，并且一些体外研究已经使用高剂量的诱变药物迫使病毒灭绝。然而，只有一项实证研究检验了致死性诱变的遗传模型，而该理论甚至在定性水平上都失败了。在这里，我们通过开发和评估专门针对可能用于测试该理论的经验系统的模型，为致死性诱变提供了一个新的分析水平。我们首先量化了一个关键参数估计中的偏差，并考虑该偏差是否是导致之前观察到的理论与实验之间缺乏一致性的原因。然后，我们考虑了一种看似理想的方案，即避免这种偏差——病毒粒子的诱变——但发现它受到其他问题的阻碍。最后，从双链基因组中检测到的突变的简单解释中得出了结果。我们的分析揭示了测试该理论的意想不到的复杂性。然而，该理论未能预测实验结果似乎是由于该理论忽略了进化机制（例如有益突变），而不是由于实验设置与模型假设之间不匹配。这种解释提出了一个可能性，即对致死性诱变的盲目尝试可能会加速而不是减缓适应性。
