Enhancing HIV Genotyping and Drug-Resistance Detection in Low Viral Load Samples Through Exosome Enrichment Technology

Abstract

Genotypic drug-resistance testing for HIV-1 with low viral loads (VLs) (<1,000 copies/mL) is clinically important but technically challenging. Due to the overlapping physical size characteristics of HIV-1 viral particles (100–120 nm) and exosomes (40–150 nm), simultaneous enrichment of both using size separation technology may offer a new strategy to improve the success rate of genotypic resistance testing in low VL samples. To evaluate the application of exosome enrichment technology in genotypic drug resistance testing for HIV-1 in low VL samples. We conducted a study with the following design. Whole blood samples were collected from HIV/AIDS patients at the Guiyang Public Health Treatment Center, who had been receiving antiretroviral therapy for over 6 months, with HIV-1 RNA levels ranging from 20 to 1,000 copies/mL, between June 2023 and November 2024. Plasma was separated, and HIV-1 RNA genotypic resistance testing was performed both directly on the plasma and after exosome enrichment. The amplification success rates of HIV-1 genotypic resistance testing before and after exosome enrichment were compared, and resistance mutation sites were analyzed. Among the 26 participants, 22 were male (84.62%) and 4 were female (15.38%), with a median age of 36.5 years. Exosome enrichment technology achieved amplification success rates for the HIV-1 genotypic resistance testing in the RT & PR regions and the INSTI region of 65.38% (17/26) and 42.31% (11/26), respectively, significantly higher than the pre-enrichment success rates of 19.23% (5/26) and 15.38% (4/26). These differences were statistically significant (χ² = 11.34, p = 0.001; χ² = 4.62, p = 0.032). Genotypic sequencing revealed K103N and L74M resistance mutations in two samples. These findings indicate that exosome enrichment technology enhances the amplification success rate of HIV-1 genotypic resistance testing in low VL samples and identifies clinically relevant resistance mutation sites. This approach may provide an innovative solution for resistance testing in low VL samples.