Despite recent breakthroughs in treatment of hepatitis C virus (HCV) infection, we have limited understanding of how virus diversity generated within individuals impacts the evolution and spread of HCV variants at the population scale. Addressing this gap is important for identifying the main sources of disease transmission and evaluating the risk of drug-resistance mutations emerging and disseminating in a population.We have undertaken a high-resolution analysis of HCV within-host evolution from 4 individuals coinfected with human immunodeficiency virus 1 (HIV-1). We used long-read, deep-sequenced data of full-length HCV envelope glycoprotein, longitudinally sampled from acute to chronic HCV infection to investigate the underlying viral population and evolutionary dynamics.We found statistical support for population structure maintaining the within-host HCV genetic diversity in 3 out of 4 individuals. We also report the first population genetic estimate of the within-host recombination rate for HCV (0.28 × 10-7 recombination/site/year), which is considerably lower than that estimated for HIV-1 and the overall nucleotide substitution rate estimated during HCV infection.Our findings indicate that population structure and strong genetic linkage shapes within-host HCV evolutionary dynamics. These results will guide the future investigation of potential HCV drug resistance adaptation during infection, and at the population scale. © The Author(s) 2019. Published by Oxford University Press for the Infectious Diseases Society of America.
Hepatitis C virus (HCV) is a rapidly evolving RNA virus that has been classified into seven genotypes. All HCV genotypes cause chronic hepatitis, which ultimately leads to liver diseases such as cirrhosis. The genotypes are unevenly distributed across the globe, with genotypes 1 and 3 being the most prevalent. Until recently, molecular epidemiological studies of HCV evolution within the host and at the population level have been limited to the analyses of partial viral genome segments, as it has been technically challenging to amplify and sequence the full-length of the 9.6 kb HCV genome. Although recent improvements have been made in full genome sequencing methodologies, these protocols are still either limited to a specific genotype or cost-inefficient.In this study we describe a genotype-specific protocol for the amplification and sequencing of the near-full length genome of all six major HCV genotypes. We applied this protocol to 122 HCV positive clinical samples, and had a successful genome amplification rate of 90 %, when the viral load was greater than 15,000 IU/ml. The assay was shown to have a detection limit of 1-3 cDNA copies per reaction. The method was tested with both Illumina and PacBio single molecule, real-time (SMRT) sequencing technologies. Illumina sequencing resulted in deep coverage and allowed detection of rare variants as well as HCV co-infection with multiple genotypes. The application of the method with PacBio RS resulted in sequence reads greater than 9 kb that covered the near full-length HCV amplicon in a single read and enabled analysis of the near full-length quasispecies.The protocol described herein can be utilised for rapid amplification and sequencing of the near-full length HCV genome in a cost efficient manner suitable for a wide range of applications.
Characterization of hepatitis C virus (HCV) envelope diversification from acute to chronic infection within a sexually transmitted HCV cluster by using single-molecule, real-time sequencing.
In contrast to other available next-generation sequencing platforms, PacBio single-molecule, real-time (SMRT) sequencing has the advantage of generating long reads albeit with a relatively higher error rate in unprocessed data. Using this platform, we longitudinally sampled and sequenced the hepatitis C virus (HCV) envelope genome region (1,680 nucleotides [nt]) from individuals belonging to a cluster of sexually transmitted cases. All five subjects were coinfected with HIV-1 and a closely related strain of HCV genotype 4d. In total, 50 samples were analyzed by using SMRT sequencing. By using 7 passes of circular consensus sequencing, the error rate was reduced to 0.37%, and the median number of sequences was 612 per sample. A further reduction of insertions was achieved by alignment against a sample-specific reference sequence. However, in vitro recombination during PCR amplification could not be excluded. Phylogenetic analysis supported close relationships among HCV sequences from the four male subjects and subsequent transmission from one subject to his female partner. Transmission was characterized by a strong genetic bottleneck. Viral genetic diversity was low during acute infection and increased upon progression to chronicity but subsequently fluctuated during chronic infection, caused by the alternate detection of distinct coexisting lineages. SMRT sequencing combines long reads with sufficient depth for many phylogenetic analyses and can therefore provide insights into within-host HCV evolutionary dynamics without the need for haplotype reconstruction using statistical algorithms.IMPORTANCE Next-generation sequencing has revolutionized the study of genetically variable RNA virus populations, but for phylogenetic and evolutionary analyses, longer sequences than those generated by most available platforms, while minimizing the intrinsic error rate, are desired. Here, we demonstrate for the first time that PacBio SMRT sequencing technology can be used to generate full-length HCV envelope sequences at the single-molecule level, providing a data set with large sequencing depth for the characterization of intrahost viral dynamics. The selection of consensus reads derived from at least 7 full circular consensus sequencing rounds significantly reduced the intrinsic high error rate of this method. We used this method to genetically characterize a unique transmission cluster of sexually transmitted HCV infections, providing insight into the distinct evolutionary pathways in each patient over time and identifying the transmission-associated genetic bottleneck as well as fluctuations in viral genetic diversity over time, accompanied by dynamic shifts in viral subpopulations. Copyright © 2017 American Society for Microbiology.
Analysis of hepatitis C NS5A resistance associated polymorphisms using ultra deep single molecule real time (SMRT) sequencing.
Development of Hepatitis C virus (HCV) resistance against direct-acting antivirals (DAAs), including NS5A inhibitors, is an obstacle to successful treatment of HCV when DAAs are used in sub-optimal combinations. Furthermore, it has been shown that baseline (pre-existing) resistance against DAAs is present in treatment naïve-patients and this will potentially complicate future treatment strategies in different HCV genotypes (GTs). Thus the aim was to detect low levels of NS5A resistant associated variants (RAVs) in a limited sample set of treatment-naïve patients of HCV GT1a and 3a, since such polymorphisms can display in vitro resistance as high as 60000 fold. Ultra-deep single molecule real time (SMRT) sequencing with the Pacific Biosciences (PacBio) RSII instrument was used to detect these RAVs. The SMRT sequencing was conducted on ten samples; three of them positive with Sanger sequencing (GT1a Q30H and Y93N, and GT3a Y93H), five GT1a samples, and two GT3a non-positive samples. The same methods were applied to the HCV GT1a H77-plasmid in a dilution series, in order to determine the error rates of replication, which in turn was used to determine the limit of detection (LOD), as defined by mean + 3SD, of minority variants down to 0.24%. We found important baseline NS5A RAVs at levels between 0.24 and 0.5%, which could potentially have clinical relevance. This new method with low level detection of baseline RAVs could be useful in predicting the most cost-efficient combination of DAA treatment, and reduce the treatment duration for an HCV infected individual. Copyright © 2015 Elsevier B.V. All rights reserved.
Before starting chronic hepatitis C treatment, the viral genotype/subtype has to be accurately determined and potentially coupled with drug resistance testing. Due to the high genetic variability of the hepatitis C virus, this can be a demanding task that can potentially be streamlined by viral whole-genome sequencing using next-generation sequencing as demonstrated by an article in this issue of the Journal of Clinical Microbiology by E. Thomson, C. L. C. Ip, A. Badhan, M. T. Christiansen, W. Adamson, et al. (J Clin Microbiol. 54:2455-2469, 2016, http://dx.doi.org/10.1128/JCM.00330-16). Copyright © 2016, American Society for Microbiology. All Rights Reserved.