Recombinant Forms of HIV-1 in the Last Decade of the Epidemic in the Russian Federation.

Currently, HIV-1 displays a substantial level of genetic diversity on a global scale, partly attributed to its recombinant variants. This study seeks to identify and analyze HIV-1 recombinants in Russia during the last decade of the epidemic. A comprehensive examination was conducted, encompassing 3178 partial pol sequences. Subtyping was achieved through various programs including COMET, the Stanford Database, REGA, jpHMM, RIP, and RDP4 for recombination analysis. The study also involved phylogenetic analysis to trace the origins of the identified recombinants. Primary resistance (PrimDR) prevalence and Drug Resistance Mutations (DRMs) were assessed. The study uncovered an overall proportion of recombinants at 8.7%, with a statistically significant increase in their frequency observed over time (p < 0.001). The Northwestern (18.5%) and Siberian (15.0%) Federal Districts exhibited a high prevalence of recombinants, while the Volga (1.9%) and Ural (2.8%) Federal Districts had a lower prevalence. Among HIV-1 recombinants, a PrimDR prevalence of 11.4% was identified. Notably, significant differences in DRMs were observed, with a higher prevalence of M184V in sub-subtype A6 (p = 0.018) and K103N in CRF63_02A6 (p = 0.002). These findings underscore the increasing HIV-1 genetic diversity and highlight a substantial prevalence of PrimDR among its recombinant forms, emphasizing the necessity for ongoing systematic monitoring.

Prevalence of HIV-1 Drug-Resistance Genotypes Among Unique Recombinant Forms from Yunnan Province, China in 2016-2017.

To investigate the prevalence and characteristics of drug-resistance genotypes among unique recombinant forms (URFs) in HIV-1 infected people under long-term antiretroviral treatment failure from Yunnan Province. The plasma samples were collected from antiretroviral therapy (ART)-failure experienced individuals from 2016 to 2017 in Yunnan Province, China. The genotyping drug resistance of HIV-1 pol gene fragments was implemented using in-house assay. According to the analysis of RIP and MEGA 7.0, the HIV-1 strains related to URFs were screened for recombinant identification and drug resistance analysis. A total of 130 pol sequences of HIV-1 URF strains were obtained from 1,121 samples. The proportion of HIV-1 URF strains was 11.6% among the ART-failure individuals from 2016 to 2017 in Yunnan. The overall drug-resistance rate of HIV-1 URF strains was 56.9%. Meanwhile, the percentage of protease inhibitors, nucleoside reverse transcriptase inhibitors (NRTIs), and non-nucleoside reverse transcriptase inhibitors (NNRTIs) resistance was 3.8% (5/130), 36.2% (47/130), and 53.8% (70/130), respectively. Mutations such as M184V/I (35.4%) in NRTIs and K103N/R/S/T (25.4%), V179D/E/T/Y (18.9%), G190A/E/R/S (13.8%), and Y181C (9.2%) in NNRTIs were common among the HIV-1 URF strains relative to other mutations. Factors such as male, sexual transmission pathway, and source of the year 2017 were significantly correlated with the development of HIV-1 URF drug resistance. The emergence of the multiple recombinant forms identified in Yunnan indicates active transmission networks of HIV-1 of different HIV-1 subtype/circulating recombinant forms cross-infection in this region. Therefore, it is necessary to further monitor the molecular epidemiology and drug resistance of HIV-1 in Yunnan.

Characterization of New Recombinant Forms of HIV-1 From the Comunitat Valenciana (Spain) by Phylogenetic Incongruence.

Recombination is one of the main processes shaping the evolution of HIV-1, with relevant consequences for its epidemiology. In fact, Circulating and Unique Recombinant Forms (CRFs and URFs) cause 23% of current infections. The routine analyses of antiretroviral resistance yield partial pol gene sequences that can be exploited for molecular epidemiology surveillance but also to study viral diversity and to detect potential recombinant samples. Among the pol sequences derived from a large sample dataset from the Comunitat Valenciana (Spain), we identified nine putative recombinant samples. We aimed at fully characterizing these samples and performing a detailed analysis of the corresponding recombination events. We obtained nearly full-genome sequences and used jpHMM and RDP4 to detect and characterize recombinant fragments. We assessed the confidence of these inferences by likelihood mapping and phylogenetic placement with topology congruence tests. Next, we performed a phylogenetic analysis of each putative recombinant fragment to determine its relationships to previously described recombinant forms. We found that two samples related to CRF44_BF whereas the rest corresponded to new URFs (two URF_AD, one URF_BG that can constitute a new CRF resulting from subtype B and CRF24_BG, and two URF_cpx composed of A, G, K, H, and J subtypes). These URFs have a complex recombination pattern that cannot be determined accurately. They seem to have arisen by successive recombination events among lineages, including other CRFs. Our results highlight the usefulness of routine surveillance analysis for the detection of new HIV-1 recombination forms and, at the same time, the need for full-genome sequencing and recombination detection guidelines to properly characterize this complex process.

Identification of New HIV-1 Circulating Recombinant Forms CRF81_cpx and CRF99_BF1 in Central Western Brazil and of Unique BF1 Recombinant Forms.

Intersubtype recombinants classified as circulating recombinant forms (CRFs) or unique recombinant forms (URFs) have been shown to play an important role in the complex and dynamic Brazilian HIV/AIDS epidemic. Previous pol region studies (2003-2013) in 828 patients from six states from Central Western, Northern and Northeastern Brazil reported variable rates of BF1, F1CB, BC, and CF1 mosaics. In this study HIV-1 subtype diversity BF1, F1CB, BC, and CF1 recombinants in pol were analyzed. Full/near-full/partial genome sequences were generated from F1CB and BF1 recombinants. Genomic DNA extracted from whole blood was used in nested-PCR to amplify four overlapping fragments encompassing the full HIV-1 genome. Phylogenetic trees were generated using the neighbor-joining/NJ method (MEGA 6.0). The time of the most recent common ancestor (TMRCA) of F1CB and BF1 clades was estimated using a Bayesian Markov Chain Monte Carlo approach (BEAST v1.8; BEAGLE). Bootscanning was used for recombination analyses (Simplot v3.5.1); separate NJ phylogenetic analysis of fragments confirmed subtypes. The phylogenetic analyses of protease/reverse-transcriptase sequences in 828 patients revealed 76% subtype B (n = 629), 6.4% subtype C (n = 53), 4.2% subtype F1 (n = 35), 13.4% intersubtype recombinants: 10.5% BF1 (n = 87), 2.3% BC (n = 19), 0.4% F1CB (n = 3), and 0.2% CF1 (n = 2). Two full and one partial BF1C genomes allowed the characterization of the CRF81_cpx that has 9 breakpoints dividing the genome into 10 subregions. Basic Local Alignment Search Tool searches (Los Alamos HIV Sequence Database) identified six other sequences with the same recombination profile in pol, five from Brazil, and one from Italy. The estimated median TMRCA of CRF81_cpx was 1999 (1992-2003). CRF60_BC-like sequences, originally described in Italy, were also found. Two full and one near full-length BF1 genomes led to the characterization of the new CRF99_BF1 that has six recombination breakpoints dividing the genome into seven subregions. Two new URFs BF1, with six recombination breakpoints and seven subregions were also characterized. The description of the first Brazilian BF1C CRF81_cpx and of the new CRF99_BF1 corroborate the important role of CRFs in the HIV/AIDS epidemic throughout Brazil. Our data also highlight the value of HIV-1 full-genome sequence studies in order to fully reveal the complexity of the epidemic in a huge country as Brazil.

Significant impact of non-B HIV-1 variants genetic diversity in Gabon on plasma HIV-1 RNA quantitation.

Evaluations of HIV-1 RNA viral load assays are lacking in Central Africa. The main objective of our study was to assess the reliability of HIV-1 RNA results obtained with three different assays for samples collected in Gabon. A total of 137 plasma specimens were assessed for HIV-1 RNA using the Abbott RealTime HIV-1® and Nuclisens HIV-1 EasyQ® version 2.0 assays. It included HIV-1 non-B samples (n = 113) representing six subtypes, 10 CRFs and 18 URFs from patients infected with HIV-1 and treated with antiretrovirals that were found HIV-1 RNA positive (≥300 copies/ml) with the Generic HIV viral load® assay; and samples (n = 24) from untreated individuals infected with HIV-1 but showing undetectable (<300 copies/ml) results with the Biocentric kit. For samples found positive with the Generic HIV viral load® test, correlation coefficients obtained between the three techniques were relatively low (R = 0.65 between Generic HIV viral load® and Abbott RealTime HIV-1®, 0.50 between Generic HIV viral load® and Nuclisens HIV-1 EasyQ®, and 0.66 between Abbott RealTime HIV-1® and Nuclisens HIV-1 EasyQ®). Discrepancies by at least one log10 were obtained for 19.6%, 33.7%, and 20% of samples, respectively, irrespective of genotype. Most of samples (22/24) from untreated study patients, found negative with the Biocentric kit, were also found negative with the two other techniques. In Central Africa, HIV-1 genetic diversity remains challenging for viral load testing. Further studies are required in the same area to confirm the presence of HIV-1 strains that are not amplified with at least two different viral load assays.

Automated subtyping of HIV-1 genetic sequences for clinical and surveillance purposes: performance evaluation of the new REGA version 3 and seven other tools.

BACKGROUND: To investigate differences in pathogenesis, diagnosis and resistance pathways between HIV-1 subtypes, an accurate subtyping tool for large datasets is needed. We aimed to evaluate the performance of automated subtyping tools to classify the different subtypes and circulating recombinant forms using pol, the most sequenced region in clinical practice. We also present the upgraded version 3 of the Rega HIV subtyping tool (REGAv3). METHODOLOGY: HIV-1 pol sequences (PR+RT) for 4674 patients retrieved from the Portuguese HIV Drug Resistance Database, and 1872 pol sequences trimmed from full-length genomes retrieved from the Los Alamos database were classified with statistical-based tools such as COMET, jpHMM and STAR; similarity-based tools such as NCBI and Stanford; and phylogenetic-based tools such as REGA version 2 (REGAv2), REGAv3, and SCUEAL. The performance of these tools, for pol, and for PR and RT separately, was compared in terms of reproducibility, sensitivity and specificity with respect to the gold standard which was manual phylogenetic analysis of the pol region. RESULTS: The sensitivity and specificity for subtypes B and C was more than 96% for seven tools, but was variable for other subtypes such as A, D, F and G. With regard to the most common circulating recombinant forms (CRFs), the sensitivity and specificity for CRF01_AE was ~99% with statistical-based tools, with phylogenetic-based tools and with Stanford, one of the similarity based tools. CRF02_AG was correctly identified for more than 96% by COMET, REGAv3, Stanford and STAR. All the tools reached a specificity of more than 97% for most of the subtypes and the two main CRFs (CRF01_AE and CRF02_AG). Other CRFs were identified only by COMET, REGAv2, REGAv3, and SCUEAL and with variable sensitivity. When analyzing sequences for PR and RT separately, the performance for PR was generally lower and variable between the tools. Similarity and statistical-based tools were 100% reproducible, but this was lower for phylogenetic-based tools such as REGA (~99%) and SCUEAL (~96%). CONCLUSIONS: REGAv3 had an improved performance for subtype B and CRF02_AG compared to REGAv2 and is now able to also identify all epidemiologically relevant CRFs. In general the best performing tools, in alphabetical order, were COMET, jpHMM, REGAv3, and SCUEAL when analyzing pure subtypes in the pol region, and COMET and REGAv3 when analyzing most of the CRFs. Based on this study, we recommend to confirm subtyping with 2 well performing tools, and be cautious with the interpretation of short sequences.