Abstract
The face of hepatitis C virus (HCV) therapy is changing dramatically. Direct-acting antiviral agents (DAAs) specifically targeting HCV proteins have been developed and entered clinical practice in 2011. However, despite high sustained viral response (SVR) rates of more than 90%, a fraction of patients do not eliminate the virus and in these cases treatment failure has been associated with the selection of drug resistance mutations (RAMs). RAMs may be prevalent prior to the start of treatment, or can be selected under therapy, and furthermore they can persist after cessation of treatment. Additionally, certain DAAs have been approved only for distinct HCV genotypes and may even have subtype specificity. Thus, sequence analysis before start of therapy is instrumental for managing DAA-based treatment strategies. We have created the interpretation system geno2pheno[HCV] (g2p[HCV]) to analyse HCV sequence data with respect to viral subtype and to predict drug resistance. Extensive reviewing and weighting of literature related to HCV drug resistance was performed to create a comprehensive list of drug resistance rules for inhibitors of the HCV protease in non-structural protein 3 (NS3-protease: Boceprevir, Paritaprevir, Simeprevir, Asunaprevir, Grazoprevir and Telaprevir), the NS5A replicase factor (Daclatasvir, Ledipasvir, Elbasvir and Ombitasvir), and the NS5B RNA-dependent RNA polymerase (Dasabuvir and Sofosbuvir). Upon submission of up to eight sequences, g2p[HCV] aligns the input sequences, identifies the genomic region(s), predicts the HCV geno- and subtypes, and generates for each DAA a drug resistance prediction report. g2p[HCV] offers easy-to-use and fast subtype and resistance analysis of HCV sequences, is continuously updated and freely accessible under http://hcv.geno2pheno.org/index.php. The system was partially validated with respect to the NS3-protease inhibitors Boceprevir, Telaprevir and Simeprevir by using data generated with recombinant, phenotypic cell culture assays obtained from patients’ virus variants.
Highlights
Infection with hepatitis C virus (HCV) is a major health problem worldwide
We have developed geno2pheno[HCV] (g2p[HCV]), a web-service that supports the analysis of HCV sequence data with respect to geno- and subtypes and possible resistance against licensed Direct-acting antiviral agents (DAAs). g2p[HCV] is a new member of the geno2pheno family, a set of web-based interpretation tools for analyzing sequences of hepatitis B virus and human immunodeficiency virus [26,27,28]
The sequence information table: it contains the sequence identifier, the predicted subtype and the clade classification for subtype 1a sequences, the amino acid positions covered by the query, the list of amino acid substitutions doi:10.1371/journal.pone.0155869.g001
Summary
Infection with hepatitis C virus (HCV) is a major health problem worldwide. It is estimated that 130 to 150 million individuals are chronically infected with this virus [1]. Genome amplification by the HCV NS5B RNA-dependent RNA polymerase (RdRp) is characterized by a high error rate (~ 10−3 errors per round of replication [7,8]), due to the lack of a proof-reading mechanism. These two properties result in the high genomic variability of HCV that is reflected in the existence of seven distinct genotypes (1 to 7) with a pairwise nucleotide divergence (percentage of non-homologous genomic sites) of at least 30% and at least 67 distinct subtypes These two properties result in the high genomic variability of HCV that is reflected in the existence of seven distinct genotypes (1 to 7) with a pairwise nucleotide divergence (percentage of non-homologous genomic sites) of at least 30% and at least 67 distinct subtypes (e.g. 1a, 1b,. . .) with a pair-wise nucleotide divergence of at least 20% [9,10]
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