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Validation of a Genotype-Independent Hepatitis C Virus Near-Whole Genome Sequencing Assay.

ABSTRACT: Despite the effectiveness of direct-acting antiviral agents in treating hepatitis C virus (HCV), cases of treatment failure have been associated with the emergence of resistance-associated substitutions. To better guide clinical decision-making, we developed and validated a near-whole-genome HCV genotype-independent next-generation sequencing strategy. HCV genotype 1-6 samples from direct-acting antiviral agent treatment-naïve and -treated HCV-infected individuals were included. Viral RNA was extracted using a NucliSens easyMAG and amplified using nested reverse transcription-polymerase chain reaction. Libraries were prepared using Nextera XT and sequenced on the Illumina MiSeq sequencing platform. Data were processed by an in-house pipeline (MiCall). Nucleotide consensus sequences were aligned to reference strain sequences for resistance-associated substitution identification and compared to NS3, NS5a, and NS5b sequence data obtained from a validated in-house assay optimized for HCV genotype 1. Sequencing success rates (defined as achieving >100-fold read coverage) approaching 90% were observed for most genotypes in samples with a viral load >5 log₁₀ IU/mL. This genotype-independent sequencing method resulted in >99.8% nucleotide concordance with the genotype 1-optimized method, and 100% agreement in genotype assignment with paired line probe assay-based genotypes. The assay demonstrated high intra-run repeatability and inter-run reproducibility at detecting substitutions above 2% prevalence. This study highlights the performance of a freely available laboratory and bioinformatic approach for reliable HCV genotyping and resistance-associated substitution detection regardless of genotype.

SUBMITTER: Lapointe HR

PROVIDER: S-EPMC8473162 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Choice of direct acting antiviral (DAA) therapy for Hepatitis C Virus (HCV) in the United Kingdom and similar settings usually requires knowledge of the genotype and, in some cases, antiviral resistance (AVR) profile of the infecting virus. To determine these, most laboratories currently use Sanger technology, but next-generation sequencing (NGS) offers potential advantages in throughput and accuracy. However, NGS poses unique technical challenges, which require idiosyncratic development and technical validation approaches. This applies particularly to virology, where sequence diversity is high and the amount of starting genetic material is low, making it difficult to distinguish real data from artifacts. We describe the development and technical validation of a sequence capture-based HCV whole genome sequencing (WGS) assay to determine viral genotype and AVR profile. We use clinical samples of known subtypes and viral loads, and simulated FASTQ datasets to validate the analytical performances of both the wet laboratory and bioinformatic pipeline procedures. We show high concordance of the WGS assay compared to current "gold standard" Sanger assays. Specificity was 92.3 and 96.1% for AVR and genotyping, respectively. Discordances were due to the inability of Sanger assays to assign the correct subtype or accurately call mixed drug-resistant variants. We show high repeatability and reproducibility with >99.8% sequence similarity between sequence runs as well as high precision for variant frequency detection at >98.8% in the 95th percentile. Post-sequencing bioinformatics quality control workflows allow the accurate distinction between mixed infections, cross-contaminants and recombinant viruses at a threshold of >5% for the minority population. The sequence capture-based HCV WGS assay is more accurate than legacy AVR and genotyping assays. The assay has now been implemented in the clinical pathway of England's National Health Service HCV treatment programs, representing the first validated HCV WGS pipeline in clinical service. The data generated will additionally provide granular national-level genomic information for public health policy making and support the WHO HCV elimination strategy.

Dataset Information

Validation of a Genotype-Independent Hepatitis C Virus Near-Whole Genome Sequencing Assay.

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