Genome-wide capture sequencing to detect hepatitis C virus at the end of antiviral therapy

Abstract Background Viral relapse is a major concern in hepatitis C virus (HCV) antiviral therapy. Currently, there are no satisfactory methods to predict viral relapse, especially in the era of direct acting antivirals in which the virus often quickly becomes undetectable using PCR-based approaches that focus on a small viral region. Next-generation sequencing (NGS) provides an alternative option for viral detection in a genome-wide manner. However, owing to the overwhelming dominance of human genetic content in clinical specimens, direct detection of HCV by NGS has a low sensitivity and hence viral enrichment is required. Methods Based on template-dependent multiple displacement amplification (tdMDA), an improved method for whole genome amplification (Wang et al., 2017. Biotechniques 63, 21–27), we evaluated two strategies to enhance the sensitivity of NGS-based HCV detection: duplex-specific nuclease (DSN)-mediated depletion of human sequences and HCV probe-based capture sequencing. Results In DSN-mediated depletion, human sequences were significantly reduced in the two HCV serum samples tested, 65.3% → 55.6% → 33.7% (#4727) and 68.6% → 56% → 21% (#4970), respectively for no normalization, self- and driver-applied normalization. However, this approach was associated with a loss of HCV sequences perhaps due to its micro-homology with the human genome. In capture sequencing, HCV-mapped sequencing reads occupied 96.8% (#4727) and 22.14% (#4970) in NGS data, equivalent to 1936x and 7380x enrichment, respectively. Capture sequencing was then applied to ten serum samples collected at the end of HCV antiviral therapy. Interestingly, the number of HCV-mapped reads was significantly higher in relapsed patients (n = 5) than those from patients with sustained virological response (SVR) (n = 5), 102.4 ± 72.3 vs. 2.6 ± 0.55, p = 0.014. Conclusions Our data provides concept evidence for a highly sensitive HCV detection by capture sequencing. The abundance difference of HCV sequencing reads at the end of HCV antiviral therapy could be applied to predict treatment outcomes.