Nanopore sequencing enhances the detection of low-frequency variants and mutational linkage in HIV-1 drug resistance

Background: Accurate detection of HIV-1 drug resistance mutations (DRMs) is essential for optimising antiretroviral therapy (ART). Although Sanger sequencing remains the clinical standard, it has limited sensitivity for low-frequency variants and cannot resolve mutation linkage within viral genomes, both of which may contribute to multidrug resistance and treatment failure. Long-read sequencing enables simultaneous detection of minor variants and viral haplotype reconstruction, allowing high-resolution analysis of DRM linkage and intra-host viral diversity. Methods: In this retrospective comparative study, 230 plasma samples from people living with HIV who underwent drug resistance testing at Beijing Ditan Hospital between Aug 2024 and July 2025 were analysed using the nanopore-based G-seq500 platform. DRM profiles and subtype classifications were compared with Sanger sequencing, and discordant mutations were validated by next-generation sequencing (NGS). Long-read sequencing data were further used for haplotype reconstruction. Findings: Among 230 participants, 145 were ART-naïve and 85 were ART-experienced. The overall concordance rate between G-seq500 and Sanger sequencing for DRM detection was 93%. All additional mutations identified by G-seq500 in discordant samples were confirmed by NGS and were predominantly low-frequency variants. Subtyping concordance between the two methods was 93·9%. Haplotype reconstruction showed that nearly half of the samples contained multiple viral haplotypes. Multiple DRMs were frequently detected within the same viral haplotype, suggesting the presence of linked multidrug-resistant viral populations. Interpretation: G-seq500 sequencing showed performance comparable to Sanger sequencing for HIV-1 DRM detection while improving sensitivity for low-frequency variants. Long-read sequencing additionally enabled viral haplotype reconstruction and DRM linkage analysis, providing higher-resolution insights into intra-host HIV-1 diversity and drug resistance.