Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis
Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis
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DOI：
10.1038/s41467-019-09139-4
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发表时间：
2019-03-29
影响因子：
16.6
通讯作者：
Wagman, Jennifer
中科院分区：
文献类型：
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作者：
Ratmann, Oliver;Grabowski, M. Kate;Wagman, Jennifer
为了防止撒哈拉以南非洲出现新的1型人体免疫缺陷病毒（艾滋病毒-1）感染，艾滋病规划署建议针对感染和传播该病毒的高风险人群采取干预措施。然而，人们往往不清楚这些“来源”人口是谁，在哪里。在这里，我们展示了病毒深度测序如何用于重建HIV-1传播网络并推断这些网络中的传播方向。我们能够从乌干达Rakai区的大量感染者样本中对病毒进行深度测序，重建部分传播网络，并推断其中的传播方向，估计错误率为16.3% [8.8-28.3%]。在这种错误率下，深度序列遗传学不能在法律的背景下用于针对个人，但对于人口水平的流行病传播来源的推断来说足够低。该技术为确定来源人群的特征和非洲艾滋病毒-1预防干预措施的目标提供了新的机会。
To prevent new infections with human immunodeficiency virus type 1 (HIV-1) in sub-Saharan Africa, UNAIDS recommends targeting interventions to populations that are at high risk of acquiring and passing on the virus. Yet it is often unclear who and where these 'source' populations are. Here we demonstrate how viral deep-sequencing can be used to reconstruct HIV-1 transmission networks and to infer the direction of transmission in these networks. We are able to deep-sequence virus from a large population-based sample of infected individuals in Rakai District, Uganda, reconstruct partial transmission networks, and infer the direction of transmission within them at an estimated error rate of 16.3% [8.8-28.3%]. With this error rate, deep-sequence phylogenetics cannot be used against individuals in legal contexts, but is sufficiently low for population-level inferences into the sources of epidemic spread. The technique presents new opportunities for characterizing source populations and for targeting of HIV-1 prevention interventions in Africa.