0709 203000 - Nairobi 0709 983000 - Kilifi
0709 203000 - NRB 0709 983000 - Kilifi
0709 203000 - NRB | 0709 983000 - Kilifi

Abstract

Validation of High-throughput Oxford Nanopore Technology for HIV-1 Transmitted/Founder Virus Identification

Byamukama D, Ndekezi C, Omara D, Nakyanzi A, Natwijuka F, Kato F, Mugaba S, Kimuda MP, Kapaata A, Nduati E, Kaleebu P, Balinda SN
Int J Infect Dis. 2025;

Permenent descriptor
https://doi.org/10.1016/j.ijid.2025.108138


HIV-1 transmitted/founder (T/F) viruses cause 80-90% of heterosexual transmissions, making their rapid identification vital for vaccine and cure development. Single-genome amplification (SGA) followed by Sanger sequencing is the gold standard for Transmitted/Founder detection, but low throughput and high cost limit its scalability. Here, we evaluated Oxford Nanopore Technology (ONT) as a high-throughput alternative. We sequenced 195 archived HIV-1 single genome amplicons (SGAs) from 20 acutely infected participants, encompassing both 3' and 5' genome halves. Libraries were prepared with end repair, native barcoding, and adapter ligation, then sequenced on a MinION MK1C device with R9.4 flow cells. Data processing included read, filtering, error correction, and haplotype reconstruction. T/F viruses were identified using Highlighter plots and by applying a criterion of intra-patient mean pairwise diversity <0.60%, together with phylogenetic clustering, with the sequence most closely related to the most recent common ancestor (MRCA) designated as the T/F virus. Phylogenetic analysis showed strong concordance between ONT and Sanger sequences, with 100% bootstrap support. ONT identified 35 of 39 T/F viruses detected by Sanger, achieving 89.70% sensitivity. Sequence similarity between ONT and Sanger derived T/Fs averaged of 99.81% (95% CI: 99.76-99.87%), ranging from 99.45-99.96%. These findings demonstrate ONT's promise as a reliable, high-throughput alternative for HIV-1 T/F identification. Advances such as the Dorado basecaller and Q20+ chemistry are expected to further improve ONT's accuracy, supporting its use in large-scale, resource-limited settings.