Stochastic processes strongly influence HIV-1 evolution during suboptimal protease-inhibitor therapy

It has long been assumed that HIV-1 evolution is best described by deterministic evolutionary models because of the large population size. Recently, however, it was suggested that the effective population size (N(e)) may be rather small, thereby allowing chance to influence evolution, a situation best described by a stochastic evolutionary model. To gain experimental evidence supporting one of the evolutionary models, we investigated whether the development of resistance to the protease inhibitor ritonavir affected the evolution of the env gene. Sequential serum samples from five patients treated with ritonavir were used for analysis of the protease gene and the V3 domain of the env gene. Multiple reverse transcription–PCR products were cloned, sequenced, and used to construct phylogenetic trees and to calculate the genetic variation and N(e). Genotypic resistance to ritonavir developed in all five patients, but each patient displayed a unique combination of mutations, indicating a stochastic element in the development of ritonavir resistance. Furthermore, development of resistance induced clear bottleneck effects in the env gene. The mean intrasample genetic variation, which ranged from 1.2% to 5.7% before treatment, decreased significantly (P < 0.025) during treatment. In agreement with these findings, N(e) was estimated to be very small (500–15,000) compared with the total HIV-1 RNA copy number. This study combines three independent observations, strong population bottlenecking, small N(e), and selection of different combinations of protease-resistance mutations, all of which indicate that HIV-1 evolution is best described by a stochastic evolutionary model.

长期以来，鉴于HIV-1庞大的种群规模，学界普遍认为其进化过程最适合用确定性进化模型加以阐释。然而近期有研究提出，HIV-1的有效种群规模（effective population size, N_e）可能相当有限，这使得随机因素得以对进化施加影响，此时则更契合随机进化模型的适用场景。为获取能够支持其中某一类进化模型的实验证据，本研究探究了蛋白酶抑制剂利托那韦（ritonavir）的耐药性产生是否会影响env基因的进化进程。我们采集了5名接受利托那韦治疗患者的连续血清样本，用以分析蛋白酶基因与env基因的V3结构域。对多份逆转录-聚合酶链式反应（reverse transcription–PCR, RT-PCR）产物进行克隆与测序，以此构建系统发育树，同时计算遗传变异度与有效种群规模N_e。结果显示，5名患者均对利托那韦产生了基因型耐药性，但每位患者的突变组合均存在独特性，这表明利托那韦耐药性的形成存在随机要素。此外，耐药性的诱导使env基因出现了显著的种群瓶颈效应。治疗前的样本内平均遗传变异度介于1.2%至5.7%之间，治疗期间该数值出现了显著下降（P < 0.025）。与上述发现相符的是，相较于HIV-1 RNA的总拷贝数，估算得到的有效种群规模N_e极小（500~15000）。本研究整合了三项独立观测结果：显著的种群瓶颈效应、极小的有效种群规模N_e，以及蛋白酶耐药突变组合的差异化选择，所有这些证据均表明，HIV-1的进化过程最适合用随机进化模型来描述。