Vrancken Bram, Rambaut Andrew, Suchard Marc A, Drummond Alexei, Baele Guy, Derdelinckx Inge, Van Wijngaerden Eric, Vandamme Anne-Mieke, Van Laethem Kristel, Lemey Philippe
Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.
Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom; Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America.
PLoS Comput Biol. 2014 Apr 3;10(4):e1003505. doi: 10.1371/journal.pcbi.1003505. eCollection 2014 Apr.
Transmission lies at the interface of human immunodeficiency virus type 1 (HIV-1) evolution within and among hosts and separates distinct selective pressures that impose differences in both the mode of diversification and the tempo of evolution. In the absence of comprehensive direct comparative analyses of the evolutionary processes at different biological scales, our understanding of how fast within-host HIV-1 evolutionary rates translate to lower rates at the between host level remains incomplete. Here, we address this by analyzing pol and env data from a large HIV-1 subtype C transmission chain for which both the timing and the direction is known for most transmission events. To this purpose, we develop a new transmission model in a Bayesian genealogical inference framework and demonstrate how to constrain the viral evolutionary history to be compatible with the transmission history while simultaneously inferring the within-host evolutionary and population dynamics. We show that accommodating a transmission bottleneck affords the best fit our data, but the sparse within-host HIV-1 sampling prevents accurate quantification of the concomitant loss in genetic diversity. We draw inference under the transmission model to estimate HIV-1 evolutionary rates among epidemiologically-related patients and demonstrate that they lie in between fast intra-host rates and lower rates among epidemiologically unrelated individuals infected with HIV subtype C. Using a new molecular clock approach, we quantify and find support for a lower evolutionary rate along branches that accommodate a transmission event or branches that represent the entire backbone of transmitted lineages in our transmission history. Finally, we recover the rate differences at the different biological scales for both synonymous and non-synonymous substitution rates, which is only compatible with the 'store and retrieve' hypothesis positing that viruses stored early in latently infected cells preferentially transmit or establish new infections upon reactivation.
传播处于1型人类免疫缺陷病毒（HIV-1）在宿主内部和宿主之间进化的界面，它分隔了不同的选择压力，这些压力在多样化模式和进化速度方面都造成了差异。在缺乏对不同生物尺度上进化过程进行全面直接比较分析的情况下，我们对宿主内HIV-1进化速度如何转化为较低的宿主间进化速度的理解仍然不完整。在这里，我们通过分析来自一个大型HIV-1 C亚型传播链的pol和env数据来解决这个问题，对于该传播链，大多数传播事件的时间和方向都是已知的。为此，我们在贝叶斯谱系推断框架中开发了一种新的传播模型，并展示了如何将病毒进化历史限制为与传播历史兼容，同时推断宿主内的进化和种群动态。我们表明，考虑传播瓶颈能使我们的数据拟合最佳，但宿主内HIV-1样本稀少，无法准确量化伴随的遗传多样性损失。我们在传播模型下进行推断，以估计与流行病学相关患者之间的HIV-1进化速度，并证明它们介于宿主内快速进化速度和感染HIV C亚型的流行病学无关个体之间的较低进化速度之间。使用一种新的分子钟方法，我们量化并发现支持沿着容纳传播事件的分支或代表我们传播历史中传播谱系整个主干的分支具有较低进化速度。最后，我们恢复了同义替换率和非同义替换率在不同生物尺度上的速率差异，这仅与“储存和检索”假说是一致的，该假说认为潜伏感染细胞中早期储存的病毒在重新激活时优先传播或建立新的感染。
