Long-Read Sequencing with Hierarchical Clustering for Antiretroviral Resistance Profiling of Mixed Human Immunodeficiency Virus Quasispecies

Abstract

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.

Easing genomic surveillance: A comprehensive performance evaluation of long-read assemblers across multi-strain mixture data of HIV-1 and Other pathogenic viruses for constructing a user-friendly bioinformatic pipeline

“…A depth of coverage of 2,000 was selected, deemed sufficient for variant calling and quasispecies detection. 57 , 58 The resulting FASTQ files ( Table 3 ) were similar to those generated by an Oxford-ONT R9.4 chemistry using a Guppy 3.1.5 basecaller. Furthermore, this study benchmarked the assemblers using experimental data sourced from published studies (Extended data, Table S1).…”

From viral democratic genomes to viral wild bunch of quasispecies

“…In recently published studies, these technologies have been successfully used to perform sequencing of long-read single molecules in the range of 10-30 kilobases and have been applied to HIV, viral hepatitis, and SARS-CoV-2, which allowed obtaining single molecules covering viral genes and even genomes and studying within host viral epistasis. [146][147][148][149][150] Nevertheless, until recently, the error rate of these latter NGS technologies was high, around 10%, 145 which hampered a very accurate characterization of the quasispecies components. Improvements of these error rates will improve significantly quasispecies studies.…”