HIV-1 Sequence Data Coverage in Central East Africa from 1959 to 2013

Increased Frequency of Inter-Subtype HIV-1 Recombinants Identified by Near Full-Length Virus Sequencing in Rwandan Acute Transmission Cohorts

Most studies of HIV-1 transmission have focused on subtypes B and C. In this study, we determined the genomic sequences of the transmitted founder (TF) viruses from acutely infected individuals enrolled between 2005 and 2011 into IAVI protocol C in Rwanda and have compared these isolates to viruses from more recent (2016–2019) acute/early infections in three at risk populations – MSM, high risk women (HRW), and discordant couples (DC). For the Protocol C samples, we utilized near full-length single genome (NFLG) amplification to generate 288 HIV-1 amplicons from 26 acutely infected seroconverters (SC), while for the 21 recent seroconverter samples (13 from HRW, two from DC, and six from MSM), we PCR amplified overlapping half-genomes. Using PacBio SMRT technology combined with the MDPseq workflow, we performed multiplex sequencing to obtain high accuracy sequences for each amplicon. Phylogenetic analyses indicated that the majority of recent transmitted viruses from DC and HRW clustered within those of the earlier Protocol C cohort. However, five of six sequences from the MSM cohort branched together and were greater than 97% identical. Recombination analyses revealed a high frequency (6/26; 23%) of unique inter-subtype recombination in Protocol C with 19% AC and 4% CD recombinant viruses, which contrasted with only 6.5% of recombinants defined by sequencing of the pol gene previously. The frequency of recombinants was significantly higher (12/21; 57%) in the more recent isolates, although, the five related viruses from the MSM cohort had identical recombination break points. While major drug resistance mutations were absent from Protocol C viruses, 4/21 of recent isolates exhibited transmitted nevirapine resistance. These results demonstrate the ongoing evolution and increased prevalence of recombinant and drug resistant transmitted viruses in Rwanda and highlight the importance of defining NFLG sequences to fully understand the nature of TF viruses and in particular the prevalence of unique recombinant forms (URFs) in transmission cohorts.

HIV-1 full-genome phylogenetics of generalized epidemics in sub-Saharan Africa: impact of missing nucleotide characters in next-generation sequences

To characterize HIV-1 transmission dynamics in regions where the burden of HIV-1 is greatest, the “Phylogenetics and Networks for Generalised HIV Epidemics in Africa” consortium (PANGEA-HIV) is sequencing full-genome viral isolates from across sub-Saharan Africa. We report the first 3,985 PANGEA-HIV consensus sequences from four cohort sites (Rakai Community Cohort Study, n = 2,833; MRC/UVRI Uganda, n = 701; Mochudi Prevention Project, n = 359; Africa Health Research Institute Resistance Cohort, n = 92). Next-generation sequencing success rates varied: more than 80% of the viral genome from the gag to the nef genes could be determined for all sequences from South Africa, 75% of sequences from Mochudi, 60% of sequences from MRC/UVRI Uganda, and 22% of sequences from Rakai. Partial sequencing failure was primarily associated with low viral load, increased for amplicons closer to the 3′ end of the genome, was not associated with subtype diversity except HIV-1 subtype D, and remained significantly associated with sampling location after controlling for other factors. We assessed the impact of the missing data patterns in PANGEA-HIV sequences on phylogeny reconstruction in simulations. We found a threshold in terms of taxon sampling below which the patchy distribution of missing characters in next-generation sequences (NGS) has an excess negative impact on the accuracy of HIV-1 phylogeny reconstruction, which is attributable to tree reconstruction artifacts that accumulate when branches in viral trees are long. The large number of PANGEA-HIV sequences provides unprecedented opportunities for evaluating HIV-1 transmission dynamics across sub-Saharan Africa and identifying prevention opportunities. Molecular epidemiological analyses of these data must proceed cautiously because sequence sampling remains below the identified threshold and a considerable negative impact of missing characters on phylogeny reconstruction is expected.