Critical amino acid residues and potential N-linked glycosylation sites contribute to circulating recombinant form 01_AE pathogenesis in Northeast China

Prediction of the Co-receptor usage of the main worldwide HIV-1 subtypes, CRF, and CRF35-AD in Iranian patients via the five genotypic tools

HIV-1 has various subtypes and CRFs, each with unique genetic attributes that impact the virus's spread, disease development, and response to treatment in different populations. Determining V3 tropism is crucial for utilizing CCR5 antagonists and understanding why certain HIV-1 subtypes are more pathogenic than others are. Genotypic coreceptor usage of 603 major subtypes of A, B, C, AE, and CRF35-AD is investigated via five bioinformatics tools (PhenoSeq, WebPSSM, Geno2Pheno, Net charge, and the 11/25 rule). This study examined crown motifs, N-glycosylation sites, and T8V mutations in all subtypes. R5 viruses are common in subtypes A, B, C, and CRF35-AD. These data indicate that R5 viruses in subtypes A and B are more prone to crown motif formation. The first report assessed the tropism of common HIV-1 subtypes and reported that CCR5 inhibitors could help treat patients with all subtypes but not AE. WebPSSM is a suitable method for determining HIV-1 tropism in different subtypes. Finally, large cohorts to assess virological response to CCR5 inhibitors would provide deep insight into the practicality of genotypic methods in clinical settings.

Multiple third-generation recombinants formed by CRF55_01B and CRF07_BC in newly diagnosed HIV-1 infected patients in Shenzhen city, China

In the evolution landscape of HIV, the coexistence of multiple subtypes has led to new, complex recombinants, posing public health challenges. CRF55_01B, first identified among MSM in Shenzhen, China, has spread rapidly across China. In this study, 47 plasma samples from newly diagnosed HIV-1 CRF55_01B patients in Shenzhen, of which the genotype was only identified by the routine HIV drug resistance test, were collected. Multiple gene regions were acquired using Sanger and next-generation sequencing methods, followed by the phylogenetic reconstruction, recombination breakpoint scanning, Bayesian molecular clock, and the prediction of coreceptors. From 47 samples, we found seven new unique recombinants formed by CRF55_01B and CRF07_BC, which shared similar breakpoints in certain gene regions and primarily utilized CCR5 receptors. All of the most recent common ancestors of subregions for these recombinants were estimated to be later than CRF55_01B and CRF07_BC, potentially suggesting they are the third-generation recombinants formed by CRF55_01B and CRF07_BC as parents. The continuous emergence of new recombinants highlights the increasing complexity of circulating strains in Shenzhen, and also suggests that subtype analysis using partial pol gene may lead to an overestimation of the major subtype strains and an underestimation of new complex HIV recombinants. Consequently, to effectively address and mitigate the complex HIV epidemic, there is an urgent need for expanded monitoring and the optimization of testing methodologies.

Young MSM changed temporal HIV-1 epidemic pattern in Heilongjiang Province, China

Background

Human immunodeficiency virus type 1 (HIV-1) epidemic in China is featured by geographical diversity of epidemic patterns. Understanding the characteristics of regional HIV-1 epidemic allows carrying out targeted prevention and controlling measures. This seven-year cross-sectional study was conducted in Heilongjiang, one province of Northeast China, where newly diagnosed infection is fast increasing yearly, but temporal HIV-1 epidemic trend is largely unknown.

Methods

Information of 1,006 newly diagnosed HIV-1-infected participants were collected before antiretroviral therapy during 2010-2016 in Heilongjiang province. HIV-1 genotype was identified based on the viral gag and env gene sequences. Recent infection was determined by Limiting-Antigen Avidity assays. Comparison analyses on the median ages, CD4 counts, proportions of stratified age groups and CD4 count groups, and rates of recent HIV-1 infection among different population and sampling times were performed to understand temporal HIV-1 epidemic features.

Results

Homosexual contact among men who have sex with men (MSM) was the main transmission route and CRF01_AE was the most dominant HIV-1 genotype. During 2010-2016, the HIV-1 epidemic showed three new changes: the median age continued to decline, the cases with a CD4 count more than 500 cells/μl (CD4hi cases) disproportionally expanded, and the recent HIV-1 infection rate steadily increased. MSM cases determined the temporal trend of HIV-1 epidemic here. Increase of young MSM cases (aged <30 years) made the main contribution to the younger age trend of MSM cases. These young MSM exhibited a higher median CD4 count, a higher proportion of CD4hi cases, and a higher rate of recent HIV-1 infection than cases aged 30 years and more. MSM infected by CRF01_AE virus mostly affected HIV-1 epidemic patterns among MSM population.

Conclusion

Young MSM have become a new hotspot and vulnerable group for HIV-1 transmission in Heilongjiang Province, Northeast China. The rapid increase in the number of young MSM cases, mainly those with CRF01_AE infection, changed temporal HIV-1 epidemic pattern here. Measures for prevention and control of HIV-1 infection among this population are urgently needed in the future.

The first third-generation HIV-1 circulating recombinant form (CRF114_0155) identified in central China

A novel circulating recombinant form (CRF) was identified in eight HIV-1-infected patients without direct epidemiological relationships in Henan Province, Central China. Recombination analysis indicated that the genome of this novel CRF comprises five segments: three inherited from CRF01_AE cluster-4 and two from CRF55_01B. Therefore, the CRF was designated CRF114_0155. It is not only the first novel CRF identified in Henan Province but also the first third-generation CRF of HIV-1 and the first CRF descendant of CRF55_01B. Bayesian inference of phylogeny dated the most recent common ancestor of the CRF114_0155 cluster to 2010. The emergence of CRF114_0155 reflects that the genotype constitution of HIV-1 has become more complex and that stricter intervention measures should be implemented in central China.

Phenotypic and Genotypic Co-receptor Tropism Testing in HIV-1 Epidemic Region of Tanzania Where Multiple Non-B Subtypes Co-circulate

HIV human immunodeficiency virus type I (HIV-1) entry inhibitor potency is dependent on viral co-receptor tropisms and thereby tropism determination is clinically important. However, phenotypic tropisms of HIV-1 non-B subtypes have been poorly investigated and the genotypic prediction algorithms remain insufficiently validated. To clarify this issue, we recruited 52 treatment-naïve, HIV-1-infected patients in Tanzania, where multiple HIV-1 non-B subtypes co-circulate. Sequence analysis of 93 infectious envelope clones isolated from their plasma viral RNA revealed the co-circulation of subtypes A1, C, D, and inter-subtype recombinant forms (isRFs). Phenotypic tropism assays revealed that lentivirus reporters pseudotyped with 75 (80.6%) and 5 (5.4%) envelope clones could establish infection toward U87.CD4 cells expressing CCR5 (R5) and CXCR4 (X4), respectively; whereas the remaining 13 (14%) clones could infect both cells. Genotypic analyses by widely used algorithms including V3 net charge, Geno2pheno, WebPSSM, and PhenoSeq showed that almost all phenotypic X4-tropic clones and only 15 of 75 phenotypic R5-tropic clones were concordantly predicted. However, the remaining 60 phenotypic R5-tropic clones were discordantly predicted by at least one algorithm. In particular, 2 phenotypic R5-tropic clones were discordantly predicted by all algorithms tested. Taken together, the results demonstrate the limitation of currently available genotypic algorithms for predicting co-receptor inference among co-circulating multiple non-B subtypes and emerging isRFs. Also, the phenotypic tropism dataset presented here could be valuable for retraining of the widely used genotypic prediction algorithms to enhance their performance.