Next-generation sequencing reveals large connected networks of intra-host HCV variants

Abstract

BackgroundNext-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.ResultsIntra-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.ConclusionsMost 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.

Antigenic cooperation among intrahost HCV variants organized into a complex network of cross-immunoreactivity

“…Surprisingly, a similar temporal pattern of diversity and diversion was observed for intrahost HCV populations (9,10). Furthermore, for HCV, the consistent increase in negative selection during chronic infection was observed (9)(10)(11)(12)(13). The late-stage HCV populations were shown to remain constant and homogeneous under the strong negative selection for years, indicating a high level of intrahost adaptation (9).…”

“…Whereas other models of host-viral interaction predict a constant increase in genetic heterogeneity of the intrahost viral population as a result of continuous immune escape (22)(23)(24)(25), the AC model predicts a different outcome of the intrahost HCV evolution: reduction in heterogeneity of the persistent viral population. This prediction is strongly supported by experimental observations of increasing negative selection during intrahost HCV evolution, long-term persistence of viral variants, and substantial heterogeneity loss associated with a strong negative selection after years of infection (9)(10)(11)(12)(13)(14).…”

“…Thus, in-hub variants can be viewed as playing an altruistic role in AC because they improve fitness of adjacent variants at their own fitness cost, whereas adjacent variants are selfish because they gain fitness at the expense of in-hub variants. These selfish variants remain in existence without eliciting strong specific immune responses and are predicted to persist under negative selection as was recently observed (9,(11)(12)(13)(14)(15). In contrast, altruistic variants are efficiently eliminated from the viral population while their immune responses are being continuously sustained.…”

Interferon alpha (IFNα)-induced TRIM22 interrupts HCV replication by ubiquitinating NS5A

“…The sequence of the HCV virus is constantly changing in the host. 36 Therefore, a large HCV mutation repertoire exists in every HCV patient. 37 To uncover the clinical association between the ubiquitinated sites and the resistance to IFNa, next generation sequencing should be used to determine the mutation status of NS5A at a population level because HCV has a highly dynamic mutational profile.…”

Spatiotemporal Reconstruction of the Introduction of Hepatitis C Virus into Scotland and Its Subsequent Regional Transmission

“…The accuracy of this strategy could be further improved by increasing the sample size from individual cities and analyzing sequences from recently infected individuals with current residential data. Another tool that could help improve HCV transmission inference studies is next-generation sequencing (NGS) which has recently been investigated for analyzing small-scale transmission events and within-patient connections (43)(44)(45). Minor sequence variants in one individual may predominate in a different individual, as illustrated by studies of liver transplants in patients with HCV (46,47), and NGS may enable the identification of connections involving minority variants which are not apparent using traditional sequencing techniques.…”