Next-generation sequencing for the clinical management of hepatitis C virus infections: does one test fits all purposes?

While the prospect of viral cure is higher than ever for individuals infected with the hepatitis C virus (HCV) due to ground-breaking progress in antiviral treatment, success rates are still negatively influenced by HCV's high genetic variability. This genetic diversity is represented in the circulation of various genotypes and subtypes, mixed infections, recombinant forms and the presence of numerous drug resistant variants among infected individuals. Common misclassifications by commercial genotyping assays in combination with the limitations of currently used targeted population sequencing approaches have encouraged researchers to exploit alternative methods for the clinical management of HCV infections. Next-generation sequencing (NGS), a revolutionary and powerful tool with a variety of applications in clinical virology, can characterize viral diversity and depict viral dynamics in an ultra-wide and ultra-deep manner. The level of detail it provides makes it the method of choice for the diagnosis and clinical assessment of HCV infections. The sequence library provided by NGS is of a higher magnitude and sensitivity than data generated by conventional methods. Therefore, these technologies are helpful to guide clinical practice and at the same time highly valuable for epidemiological studies. The decreasing costs of NGS to determine genotypes, mixed infections, recombinant strains and drug resistant variants will soon make it feasible to employ NGS in clinical laboratories, to assist in the daily care of patients with HCV.

Study on SARS-CoV-2 strains in Iran reveals potential contribution of co-infection with and recombination between different strains to the emergence of new strains.

We aimed to describe SARS-CoV-2 strains in Iranians from nine distributed cities infected during two months expanding late 2020 and early 2021 by genotyping known informative single nucleotide in five PCR amplicons. Two variants associated with haplotype H1 (clade G) and nine additional variants associated with other haplotypes were genotyped, respectively, in RNA isolates of 244 and 85 individuals. The variants associated with the H1a (GR) and H1b (GH) haplotypes were most prevalent, indicating a significant change in infection pattern with passage of time. The most important findings were that recombinant genomes and co-infection, respectively, were surmised in 44.7% and 12.9% of the samples extensively genotyped. Partners of many of the recombinations were relatively common strains. Co-existing viruses were among those currently circulating in Iran. In addition to random mutations, co-infection with different existing strains and recombination between their genomes may significantly contribute to the emergence of new SARS-CoV-2 strains.

Signature of natural resistance in NS3 protease revealed by deep sequencing of HCV strains circulating in Iran.

A tremendous upscale of screening and treatment strategies is required to achieve elimination of the hepatitis C virus (HCV) in Iran by 2030. Among treated patients, at least 5-10% is expected to experience treatment failure. To efficiently retreat cases with prior exposure to NS5A and NS5B drugs, knowledge on the natural prevalence of NS3 resistance is key. The NS3 region of 32 samples from sixteen Iranian HCV patients, among which 6 injecting drug users, was amplified and subjected to deep sequencing. Amplification and sequencing were successful in 29 samples. The reads were assembled to consensus sequences and showed that 6 patients were infected with HCV1a (37.5%), 7 with HCV1b (43.8%) and 3 with HCV3a (18.7%). Nucleotide identities were shared for >97% between intra-host sequences. Two patients were infected with natural resistant viruses, of which one solely comprising low frequency variants. Inferred phylogenies showed that Iranian sequences clustered together for HCV1a and HCV1b, while for HCV3a a potential recombination event was detected. We firstly report the use of deep sequencing for HCV in Iran, demonstrate the use of NS3 inhibitors as salvage therapy in case of retreatment and stress the importance for Iran to prioritize drug users for screening and treatment.

Development of an In-House TaqMan Real Time RT-PCR Assay to Quantify Hepatitis C Virus RNA in Serum and Peripheral Blood Mononuclear Cells in Patients With Chronic Hepatitis C Virus Infection.

BACKGROUND: Viral load measurements are commonly used to monitor HCV infection in patients with chronic diseases or determining the number of HCV-genomes in serum samples of patients after sustained virological response. However, in some patients, HCV viral load in serum samples is too low to be detected by PCR, especially after treatment. OBJECTIVES: The aim of this study was to develop a highly specific, sensitive, and reproducible in-house quantitative PCR using specific primers and probe cited in highly conservative region of HCV genome that allows simultaneous detection of HCV genotypes 1 - 4. MATERIALS AND METHODS: In this study, three sets of primer pairs and a TaqMan probe for amplification and detection of selected region within 5'-non-coding (5'NCR) of four HCV genotypes were used. Using plasmid containing 5'NCR region of HCV, standard curve, threshold, and threshold cycle (CT) values were determined. Real-time and nested PCR were performed on HCV genotypes 1 - 4 extracted from plasma and peripheral blood mononuclear cells (PBMCs) samples collected from patients with chronic HCV infection. RESULTS: The lower limit detection of this in-house HCV real-time RT-PCR was determined as 100 RNA copies/mL. Inter- and intra-assay coefficient of variation (CV) of this in-house HCV real-time RT-PCR ranged from 0.9% to 1.8% and 1.76% to 3.94%, respectively. The viral load of the genotyped samples ranged from 2.0 × 10(6) ± 0.31 to 2.7 × 10(5) ± 0.46 copies/mL in serum samples and 5 × 10(2) ± 0.36 to 4.0 × 10(3) ± 0.51 copies/10(6) cells/mL of PBMCs. CONCLUSIONS: The quite sensitive in-house TaqMan real time RT-PCR assay was able to detect and quantify all four main HCV genotypes prevailing around all geographical regions of Iran.