Next-generation sequencing reveals large connected networks of intra-host HCV variants.
Next-generation sequencing reveals large connected networks of intra-host HCV variants.
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DOI：
10.1186/1471-2164-15-s5-s4
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发表时间：
2014
期刊：
影响因子：
4.4
通讯作者：
Khudyakov Y
中科院分区：
文献类型：
--
作者：
Campo DS;Dimitrova Z;Yamasaki L;Skums P;Lau DT;Vaughan G;Forbi JC;Teo CG;Khudyakov Y
下一代测序（NGS）允许从感染患者中采样许多病毒变体。这提供了一个新的机会，代表和研究丙型肝炎病毒（HCV）的突变景观在单一主机。从58例慢性感染患者中广泛采集HCV E1/E2区的宿主内变异体。在NGS错误校正后，从每个样品获得的读数和变体的平均数目分别为3202和464。计算每对变体之间的距离，并为每个患者创建网络，其中每个节点是变体，如果两个节点之间的核苷酸距离为1，则两个节点通过链接连接。这项工作集中在具有> 5%的所有读数的大组分上，其平均占患者中发现的所有读数的93.7%。在组分上计算的任何两个变体之间的距离与核苷酸距离强烈相关（r = 0.9499; p = 0.0001），比用相邻连接树获得的相关性更好（r = 0.7624; p = 0.0001）。在每例患者中，部件分离良好，部件之间的平均距离（6.53%）是每个部件内的平均距离（0.68%）的10倍。计算了非同义变化与同义变化的比率，一些患者（6.9%）在强阴性和阳性选择下显示出网络的混合物。所有组分对计算机随机采样都具有鲁棒性;即使在随机去除85%的所有读数后，新子样本中最大的连接组分仍涉及82.4%的剩余节点。体外采样显示，原始样品中存在的93.02%的组分也在实验复制品中发现，两者中均发现了81.6%的读数。当模拟共享病毒的传播事件时，所有模拟的传播事件中有91.2%的传播源中存在所有成分。大多数宿主内变异体被组织成不同的单突变组分，这些组分彼此分离良好，代表病毒变异体之间的遗传距离，对采样具有鲁棒性，可重现性，并且可能在传播事件期间接种。在NGS的促进下，大组分为宿主内病毒群体的遗传分析和理解传播、免疫逃逸和耐药性提供了一个新的进化框架。
Next-generation sequencing (NGS) allows for sampling numerous viral variants from infected patients. This provides a novel opportunity to represent and study the mutational landscape of Hepatitis C Virus (HCV) within a single host. Intra-host variants of the HCV E1/E2 region were extensively sampled from 58 chronically infected patients. After NGS error correction, the average number of reads and variants obtained from each sample were 3202 and 464, respectively. The distance between each pair of variants was calculated and networks were created for each patient, where each node is a variant and two nodes are connected by a link if the nucleotide distance between them is 1. The work focused on large components having > 5% of all reads, which in average account for 93.7% of all reads found in a patient. The distance between any two variants calculated over the component correlated strongly with nucleotide distances (r = 0.9499; p = 0.0001), a better correlation than the one obtained with Neighbour-Joining trees (r = 0.7624; p = 0.0001). In each patient, components were well separated, with the average distance between (6.53%) being 10 times greater than within each component (0.68%). The ratio of nonsynonymous to synonymous changes was calculated and some patients (6.9%) showed a mixture of networks under strong negative and positive selection. All components were robust to in silico stochastic sampling; even after randomly removing 85% of all reads, the largest connected component in the new subsample still involved 82.4% of remaining nodes. In vitro sampling showed that 93.02% of components present in the original sample were also found in experimental replicas, with 81.6% of reads found in both. When syringe-sharing transmission events were simulated, 91.2% of all simulated transmission events seeded all components present in the source. Most intra-host variants are organized into distinct single-mutation components that are: well separated from each other, represent genetic distances between viral variants, robust to sampling, reproducible and likely seeded during transmission events. Facilitated by NGS, large components offer a novel evolutionary framework for genetic analysis of intra-host viral populations and understanding transmission, immune escape and drug resistance.