Institut Des Sciences de l'Evolution de Montpellier, Université de Montpellier II--CNRS (UMR 5554), 34095 Montpellier Cedex 5, France.
Philos Trans R Soc Lond B Biol Sci. 2010 Jun 27;365(1548):1953-63. doi: 10.1098/rstb.2010.0058.
The lethal mutagenesis hypothesis states that within-host populations of pathogens can be driven to extinction when the load of deleterious mutations is artificially increased with a mutagen, and becomes too high for the population to be maintained. Although chemical mutagens have been shown to lead to important reductions in viral titres for a wide variety of RNA viruses, the theoretical underpinnings of this process are still not clearly established. A few recent models sought to describe lethal mutagenesis but they often relied on restrictive assumptions. We extend this earlier work in two novel directions. First, we derive the dynamics of the genetic load in a multivariate Gaussian fitness landscape akin to classical quantitative genetics models. This fitness landscape yields a continuous distribution of mutation effects on fitness, ranging from deleterious to beneficial (i.e. compensatory) mutations. We also include an additional class of lethal mutations. Second, we couple this evolutionary model with an epidemiological model accounting for the within-host dynamics of the pathogen. We derive the epidemiological and evolutionary equilibrium of the system. At this equilibrium, the density of the pathogen is expected to decrease linearly with the genomic mutation rate U. We also provide a simple expression for the critical mutation rate leading to extinction. Stochastic simulations show that these predictions are accurate for a broad range of parameter values. As they depend on a small set of measurable epidemiological and evolutionary parameters, we used available information on several viruses to make quantitative and testable predictions on critical mutation rates. In the light of this model, we discuss the feasibility of lethal mutagenesis as an efficient therapeutic strategy.
致死性诱变假说指出,当病原体在体内的种群因诱变剂而人为增加有害突变的负荷,使其达到无法维持种群的高负荷时,就会导致其灭绝。虽然化学诱变剂已被证明可导致多种 RNA 病毒的病毒滴度显著降低,但这一过程的理论基础仍未得到明确确立。最近有一些模型试图描述致死性诱变,但它们往往依赖于限制性假设。我们在两个新的方向上扩展了这项早期工作。首先,我们推导出了类似于经典数量遗传学模型的多元高斯适应度景观中的遗传负荷动力学。这种适应度景观产生了一个连续的突变对适应度影响的分布,从有害突变到有益突变(即补偿突变)。我们还包括了另一种致死突变。其次,我们将这种进化模型与一个考虑病原体体内动态的流行病学模型耦合。我们推导出了系统的流行病学和进化平衡。在这个平衡点,病原体的密度预计会随着基因组突变率 U 线性下降。我们还提供了一个简单的表达式来表示导致灭绝的临界突变率。随机模拟表明,这些预测对于广泛的参数值都是准确的。由于它们依赖于一小部分可测量的流行病学和进化参数,我们利用了几种病毒的现有信息,对临界突变率进行了定量和可检验的预测。根据这个模型,我们讨论了致死性诱变作为一种有效的治疗策略的可行性。