Long-Read Sequencing with Hierarchical Clustering for Antiretroviral Resistance Profiling of Mixed Human Immunodeficiency Virus Quasispecies. - Ting-Leung Ng, Timothy; Junhao Su; Hiu-Yin Lao; Wui-Wang Lui; Chloe Toi-Mei Chan; Amy Wing-Sze Leung; Hoi-Ching Jim, Stephanie; Lam-Kwong Lee; Shehzad, Sheeba; King-Gee Tam, Kingsley; Siu-Sing Leung, Kenneth; Tang, Forrest; et al. (Clinical Chemistry, 2023)
BACKGROUND: HIV infections often develop drug resistance mutations (DRMs), which can increase the risk of virological failure. However, it has been difficult to determine if minor mutations occur in the same genome or in different virions using Sanger sequencing and short-read sequencing methods. Oxford Nanopore Technologies (ONT) sequencing may improve antiretroviral resistance profiling by allowing for long-read clustering. METHODS: A new ONT sequencing-based method for profiling DRMs in HIV quasispecies was developed and validated. The method used hierarchical clustering of long amplicons that cover regions associated with different types of antiretroviral drugs. A gradient series of an HIV plasmid and 2 plasma samples was prepared to validate the clustering performance. The ONT results were compared to those obtained with Sanger sequencing and Illumina sequencing in 77 HIV-positive plasma samples to evaluate the diagnostic performance. RESULTS: In the validation study, the abundance of detected quasispecies was concordant with the predicted result with the R² of > 0.99. During the diagnostic evaluation, 59/77 samples were successfully sequenced for DRMs. Among 18 failed samples, 17 were below the limit of detection of 303.9 copies/µL. Based on the receiver operating characteristic analysis, the ONT workflow achieved an F1 score of 0.96 with a cutoff of 0.4 variant allele frequency. Four cases were found to have quasispecies with DRMs, in which 2 harbored quasispecies with more than one class of DRMs. Treatment modifications were recommended for these cases. CONCLUSIONS: Long-read sequencing coupled with hierarchical clustering could differentiate the quasispecies resistance profiles in HIV-infected samples, providing a clearer picture for medical care.