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HIV-1 is characterized by remarkable genetic diversity resulting from its high replication rate, error-prone reverse transcriptase enzyme and recombination events. In Uganda, HIV-1 subtype diversity is mostly dominated by subtypes A, D, and A1/D Unique Recombinant Forms (URFs). In this study, deep sequences of HIV from patients with known antiretroviral therapy (ART) status were analyzed to determine the subtypes and to identify drug-resistance mutations circulating in the study population. Of the 187 participant samples processed for next-generation sequencing (NGS), 137 (73%) were successfully classified. The majority of HIV-1 strains were classified as subtype A (75, 55%), D (43, 31%), with other subtypes including C (3, 2%), A1/D (9, 7%) and CRF10_CD (1, <1%). Recombinant analysis of nine complete A1/D HIV genomes identified novel recombination patterns described herein. Furthermore, we report for the first time in Uganda, an HIV-1 CRF10_CD strain from a fisherfolk in a Lake Victoria Island fishing community. [ABSTRACT FROM AUTHOR]

We assessed the performance and clinical relevance of Illumina MiSeq next-generation sequencing (NGS) for HIV-1 genotyping compared with Sanger sequencing (SS). We analyzed 167 participants, 45 with virologic failure (VL ≥ 1000 copies/mL), i.e., cases, and 122 time-matched participants with virologic suppression (VL < 1000 copies/mL), i.e., controls, 12 months post-ART initiation. Major surveillance drug resistance mutations (SDRMs) detected by SS were all detectable by NGS. Among cases at 12 months, SS identified SDRMs in 32/45 (71.1%) while NGS identified SDRMs among 35/45 (77.8%), increasing the number of cases with SDRMs by 3/45 (6.7%). Participants identified with, and proportions of major SDRMs increased when NGS was used. NGS vs. SS at endpoint revealed for NNRTIs: 36/45 vs. 33/45; Y181C: 26/45 vs. 24/45; K103N: 9/45 vs. 6/45 participants with SDRMs, respectively. At baseline, NGS revealed major SDRMs in 9/45 (20%) cases without SDRMs by SS. Participant MBL/043, among the nine, the following major SDRMs existed: L90M to PIs, K65R and M184V to NRTIs, and Y181C and K103N to NNRTIs. The SDRMs among the nine increased SDRMs to NRTIs, NNRTIs, and PIs. Only 43/122 (25.7%) of participants had pre-treatment minority SDRMs. Also, 24.4% of the cases vs. 26.2 of controls had minority SDRMs (p = 0.802); minority SDRMs were not associated with virologic failure. NGS agreed with SS in HIV-1 genotyping but detected additional major SDRMs and identified more participants harboring major SDRMs, expanding the HIV DRM profile of this cohort. NGS could improve HIV genotyping to guide treatment decisions for enhancing ART efficacy, a cardinal pre-requisite in the pursuit of the UNAIDS 95-95-95 targets. [ABSTRACT FROM AUTHOR]

Background HIV poses significant challenges for vaccine development due to its high genetic mutation and recombination rates. Understanding the distribution of HIV subtypes (clades) across regions and populations is crucial. In this study, a systematic review of the past decade was conducted to characterize HIV-1/HIV-2 subtypes. Methods A comprehensive search was performed in PubMed, EMBASE, and CABI Global Health, yielding 454 studies from 91 countries. Results Globally, circulating recombinant forms (CRFs)/unique recombinant forms (URFs) accounted for 29% of HIV-1 strains, followed by subtype C (23%) and subtype A (17%). Among studies reporting subtype breakdowns in key populations, 62% of HIV infections among men who have sex with men (MSM) and 38% among people who inject drugs (PWIDs) were CRF/URFs. Latin America and the Caribbean exhibited a 25% increase in other CRFs (excluding CRF01_AE or CRF02_AG) prevalence between 2010–2015 and 2016–2021. Conclusions This review underscores the global distribution of HIV subtypes, with an increasing prevalence of CRFs and a lower prevalence of subtype C. Data on HIV-2 were limited. Understanding subtype diversity is crucial for vaccine development, which need to elicit immune responses capable of targeting various subtypes. Further research is needed to enhance our knowledge and address the challenges posed by HIV subtype diversity. [ABSTRACT FROM AUTHOR]

Summary Next-generation sequencing (NGS) enables reliable detection of resistance mutations in minority variants of human immunodeficiency virus type 1 (HIV-1). There is paucity of evidence for the association of minority resistance to treatment failure, and this requires evaluation. However, the tools for analyzing HIV-1 drug resistance (HIVDR) testing data are mostly web-based which requires uploading data to webservers. This is a challenge for laboratories with internet connectivity issues and instances with restricted data transfer across networks. We present QuasiFlow, a pipeline for reproducible analysis of NGS-based HIVDR testing data across different computing environments. Since QuasiFlow entirely depends on command-line tools and a local copy of the reference database, it eliminates challenges associated with uploading HIV-1 NGS data onto webservers. The pipeline takes raw sequence reads in FASTQ format as input and generates a user-friendly report in PDF/HTML format. The drug resistance scores obtained using QuasiFlow were 100% and 99.12% identical to those obtained using web-based HIVdb program and HyDRA web respectively at a mutation detection threshold of 20%. Availability and implementation QuasiFlow and corresponding documentation are publicly available at https://github.com/AlfredUg/QuasiFlow. The pipeline is implemented in Nextflow and requires regular updating of the Stanford HIV drug resistance interpretation algorithm. Supplementary information Supplementary data are available at Bioinformatics Advances online. [ABSTRACT FROM AUTHOR]

HIV-TRAnsmission Cluster Engine (HIV-TRACE) and Cluster Picker are some of the most widely used programs for identifying HIV-1 transmission networks from nucleotide sequences. However, choosing between these tools is subjective and often a matter of personal preference. Because these software use different algorithms to detect HIV-1 transmission networks, their optimal use is better suited with different sequence data sets and under different scenarios. The performance of these tools has previously been evaluated across a range of genetic distance thresholds without an assessment of the differences in the structure of networks identified. In this study, we tested both programs on the same HIV-1 pol sequence data set (n = 2,017) from three Ugandan populations to examine their performance across different risk groups and evaluate the structure of networks identified. HIV-TRACE that uses a single-linkage algorithm identified more nodes in the same networks that were connected by sparse links than Cluster Picker. This suggests that the choice of the program used for identifying networks should depend on the study aims, the characteristics of the population being investigated, dynamics of the epidemic, sampling design, and the nature of research questions being addressed for optimum results. HIV-TRACE could be more applicable with larger data sets where the aim is to identify larger clusters that represent distinct transmission chains and in more diverse populations where infection has occurred over a period of time. In contrast, Cluster Picker is applicable in situations where more closely connected clusters are expected in the studied populations. [ABSTRACT FROM AUTHOR]

HIV drug resistance (HIVDR) is of increasing health concern, especially among key populations. We investigated the prevalence of virological suppression (VS), prevalence and correlates of HIVDR in HIV-infected women, enrolled in a high-risk cohort. We enrolled 267 women initiated on first-line antiretroviral therapy (ART) between 2015 and 2018. Participants' plasma samples were analyzed for HIV RNA viral load (VL) and genotypic resistance testing was performed on those with VL nonsuppression (defined as VL ≥1,000 copies/mL). We used the Stanford HIVDR database-algorithm to assess HIVDR mutations and logistic regression to assess risk factors for VL nonsuppression and HIVDR. We observed an overall VS prevalence of 76.0% (203/267) and detected respective acquired drug resistance prevalence to non-nucleoside reverse transcriptase inhibitors (NNRTIs) and nucleoside reverse transcriptase inhibitors (NRTIs) of 81.3% [confidence interval (CI) 67.4–91.1] and 45.8% (CI 31.4–60.8) among the 48 successfully genotyped VL nonsuppressors. NNRTI mutations were observed in 81.3% (39/48) of the genotyped participants and 45.8% (22/48) had both NRTI and NNRTI mutations. The mutation K103N was detected in 62.5% (30/48) of participants, 41.7% (20/48) had M184V/I, 14.6% had K65R, and 12.5% (6/48) had thymidine analog mutations (TAMs). None of the analyzed potential risk factors, including age and duration on ART, was significantly correlated with VL nonsuppression or HIVDR. Although high levels of NNRTI mutations support the transition to dolutegravir, the presence of NRTI mutations, especially TAMs, may compromise dolutegravir-based regimens or other second-line ART options. The moderate VS prevalence and high HIVDR prevalence therefore call for timely ART switching and intensive adherence counseling. [ABSTRACT FROM AUTHOR]

Recombination is an important feature of HIV evolution, occurring both within and between the major branches of diversity (subtypes). The Ugandan epidemic is primarily composed of two subtypes, A1 and D, that have been co-circulating for 50 years, frequently recombining in dually infected patients. Here, we investigate the frequency of recombinants in this population and the location of breakpoints along the genome. As part of the PANGEA-HIV consortium, 1,472 consensus genome sequences over 5 kb have been obtained from 1,857 samples collected by the MRC/UVRI & LSHTM Research unit in Uganda, 465 (31.6 per cent) of which were near full-length sequences (>8 kb). Using the subtyping tool SCUEAL, we find that of the near full-length dataset, 233 (50.1 per cent) genomes contained only one subtype, 30.8 per cent A1 (n  = 143), 17.6 per cent D (n  = 82), and 1.7 per cent C (n  = 8), while 49.9 per cent (n  = 232) contained more than one subtype (including A1/D (n  = 164), A1/C (n  = 13), C/D (n  = 9); A1/C/D (n  = 13), and 33 complex types). K -means clustering of the recombinant A1/D genomes revealed a section of envelope (C2gp120-TMgp41) is often inherited intact, whilst a generalized linear model was used to demonstrate significantly fewer breakpoints in the gag–pol and envelope C2-TM regions compared with accessory gene regions. Despite similar recombination patterns in many recombinants, no clearly supported circulating recombinant form (CRF) was found, there was limited evidence of the transmission of breakpoints, and the vast majority (153/164; 93 per cent) of the A1/D recombinants appear to be unique recombinant forms. Thus, recombination is pervasive with clear biases in breakpoint location, but CRFs are not a significant feature, characteristic of a complex, and diverse epidemic. [ABSTRACT FROM AUTHOR]

Objectives: We examined virological outcomes, patterns of acquired HIV drug resistance (ADR), correlates of virological failure (VF) and acquired drug resistance among fisherfolk on first-line ART.Methods: We enrolled 1169 adults on ART for a median duration of 6, 12, 24, 36 and ≥48 months and used a pooled VL testing approach to identify VF (VL ≥1000 copies/mL). We performed genotyping among VF cases and determined correlates of VF and ADR by logistic regression.Results: The overall virological suppression rate was 91.7% and ADR was detected in 71/97 (73.2%) VF cases. The most prevalent mutations were M184V/I (53.6%) for NRTIs and K103N (39.2%) for NNRTIs. Thymidine analogue mutations were detected in 21.6% of VF cases while PI mutations were absent. A zidovudine-based ART regimen, duration on ART (≥24 months) and secondary/higher education level were significantly associated with VF. A nevirapine-based regimen [adjusted OR (aOR): 1.87; 95% CI: 0.03-0.54)] and VL ≥10000 copies/mL (aOR: 3.48; 95% CI: 1.37-8.85) were ADR correlates. The pooling strategies for VL testing with a negative predictive value (NPV) of ≥95.2% saved US $20320 (43.5%) in VL testing costs.Conclusions: We observed high virological suppression rates among these highly mobile fisherfolk; however, there was widespread ADR among those with VF at the first VL testing prior to intensive adherence counselling. Timely treatment switching and adherence support is recommended for better treatment outcomes. Adoption of pooled VL testing could be cost effective, particularly in resource-limited settings. [ABSTRACT FROM AUTHOR]

Phylogenetic inference is useful in characterising HIV transmission networks and assessing where prevention is likely to have the greatest impact. However, estimating parameters that influence the network structure is still scarce, but important in evaluating determinants of HIV spread. We analyzed 2017 HIV pol sequences (728 Lake Victoria fisherfolk communities (FFCs), 592 female sex workers (FSWs) and 697 general population (GP)) to identify transmission networks on Maximum Likelihood (ML) phylogenetic trees and refined them using time-resolved phylogenies. Network generative models were fitted to the observed degree distributions and network parameters, and corrected Akaike Information Criteria and Bayesian Information Criteria values were estimated. 347 (17.2%) HIV sequences were linked on ML trees (maximum genetic distance ≤4.5%, ≥95% bootstrap support) and, of these, 303 (86.7%) that consisted of pure A1 (n = 168) and D (n = 135) subtypes were analyzed in BEAST v1.8.4. The majority of networks (at least 40%) were found at a time depth of ≤5 years. The waring and yule models fitted best networks of FFCs and FSWs respectively while the negative binomial model fitted best networks in the GP. The network structure in the HIV-hyperendemic FFCs is likely to be scale-free and shaped by preferential attachment, in contrast to the GP. The findings support the targeting of interventions for FFCs in a timely manner for effective epidemic control. Interventions ought to be tailored according to the dynamics of the HIV epidemic in the target population and understanding the network structure is critical in ensuring the success of HIV prevention programs. [ABSTRACT FROM AUTHOR]

The General Population Cohort (GPC) in south-western Uganda has a low HIV-1 incidence rate (<1%). However, new infections continue to emerge. In this research, 3796 HIV-1 pol sequences (GPC: n = 1418, non-GPC sites: n = 1223, Central Uganda: n = 1010 and Eastern Uganda: n = 145) generated between 2003–2015 were analysed using phylogenetic methods with demographic data to understand HIV-1 transmission in this cohort and inform the epidemic response. HIV-1 subtype A1 was the most prevalent strain in the GPC area (GPC and non-GPC sites) (39.8%), central (45.9%) and eastern (52.4%) Uganda. However, in the GPC alone, subtype D was the predominant subtype (39.1%). Of the 524 transmission clusters identified by Cluster Picker, all large clusters (≥5 individuals, n = 8) involved individuals from the GPC. In a multivariate analysis, clustering was strongly associated with being female (adjusted Odds Ratio, aOR = 1.28; 95% CI, 1.06–1.54), being >25 years (aOR = 1.52; 95% CI, 1.16–2.0) and being a resident in the GPC (aOR = 6.90; 95% CI, 5.22–9.21). Phylogeographic analysis showed significant viral dissemination (Bayes Factor test, BF > 3) from the GPC without significant viral introductions (BF < 3) into the GPC. The findings suggest localized HIV-1 transmission in the GPC. Intensifying geographically focused combination interventions in the GPC would contribute towards controlling HIV-1 infections. [ABSTRACT FROM AUTHOR]

Across sub-Saharan Africa, key populations with elevated HIV-1 incidence and/or prevalence have been identified, but their contribution to disease spread remains unclear. We performed viral deep-sequence phylogenetic analyses to quantify transmission dynamics between the general population (GP), fisherfolk communities (FF), and women at high risk of infection and their clients (WHR) in central and southwestern Uganda. Between August 2014 and August 2017, 6185 HIV-1 positive individuals were enrolled in 3 GP and 10 FF communities, 3 WHR enrollment sites. A total of 2531 antiretroviral therapy (ART) naïve participants with plasma viral load >1000 copies/mL were deep-sequenced. One hundred and twenty-three transmission networks were reconstructed, including 105 phylogenetically highly supported source–recipient pairs. Only one pair involved a WHR and male participant, suggesting that improved population sampling is needed to assess empirically the role of WHR to the transmission dynamics. More transmissions were observed from the GP communities to FF communities than vice versa, with an estimated flow ratio of 1.56 (95% CrI 0.68–3.72), indicating that fishing communities on Lake Victoria are not a net source of transmission flow to neighboring communities further inland. Men contributed disproportionally to HIV-1 transmission flow regardless of age, suggesting that prevention efforts need to better aid men to engage with and stay in care. [ABSTRACT FROM AUTHOR]