Back

Ultrasensitive single-genome sequencing reveals strong purifying selection in acute HIV-1 infection

Capoferri, A. A.; Boltz, V. F.; Shao, W.; Halpern, C.; Thomas, R.; Phanuphak, N.; Trautmann, L.; Vasan, S.; Sacdalan, C.; Sripliechan, S.; Mellors, J. W.; Coffin, J. M.; Rausch, J. W.; Kearney, M. F.

2026-08-26 microbiology
10.64898/2026.08.21.746200 bioRxiv
Show abstract

HIV transmission from one individual to another occurs by one or a small number of virions followed by spread and genetic diversification into a complex quasispecies. To understand the early events in this process, we investigated how HIV-1 genomes diversify within the first two to three weeks after transmission by use of ultra-deep single subgenomic sequencing of over 10,000 plasma RNA genomes in each of a cohort of 15 individuals in acute infection. This approach confirmed transmission of one or a few transmitted/founder (TF) viral lineages and very limited early divergence from the founder sequences. Most observed variants that differed from the TF included single nucleotide changes attributable to HIV-1 reverse transcriptase (RT) error or host APOBEC3G/F activity. Comparing the number of expected versus observed changes after transmission indicated that most de novo mutations do not persist in the virus population, consistent with strong purifying selection. We found little evidence that early diversification is driven by reversions to subtype consensus or by cytotoxic T lymphocyte pressure, although rare multi-mutation lineages suggest occasional influences. Together, these findings indicate that early HIV-1 evolution is influenced by stochastic and host-mediated mutational processes (e.g., APOBEC3G/F) filtered by strong purifying selection. The strong purifying selection observed in the early weeks of HIV-1 infection may provide an opportunity to investigate the potential of new interventions to induce viremic control, such as combinations of broadly neutralizing antibodies, cellular immunotherapy, or mRNA therapeutic vaccination.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.