Brief Report: HIV-1 Tropism During Primary Infections in France: 1996-2014

HIV-1 resistance genotyping by ultra-deep sequencing and 6-month virological response to first-line treatment

OBJECTIVES

To evaluate the routine use of the Sentosa ultra-deep sequencing (UDS) system for HIV-1 polymerase resistance genotyping in treatment-naïve individuals and to analyse the virological response (VR) to first-line antiretroviral treatment.

METHODS

HIV drug resistance was determined on 237 consecutive samples from treatment-naïve individuals using the Sentosa UDS platform with two mutation detection thresholds (3% and 20%). VR was defined as a plasma HIV-1 virus load <50 copies/mL after 6 months of treatment.

RESULTS

Resistance to at least one antiretroviral drug with a mutation threshold of 3% was identified in 29% and 16% of samples according to ANRS and Stanford algorithms, respectively. The ANRS algorithm also revealed reduced susceptibility to at least one protease inhibitor (PI) in 14.3% of samples, to one reverse transcriptase inhibitor in 12.7%, and to one integrase inhibitor (INSTI) in 5.1%. For a mutation threshold of 20%, resistance was identified in 24% and 13% of samples according to ANRS and Stanford algorithms, respectively. The 6 months VR was 87% and was similar in the 58% of patients given INSTI-based treatment, in the 16% given PI-based treatment and in the 9% given NNRTI-based treatment. Multivariate analysis indicated that the VR was correlated with the baseline HIV virus load and resistance to at least one PI at both 3% and 20% mutation detection thresholds (ANRS algorithm).

CONCLUSIONS

The Vela UDS platform is appropriate for determining antiretroviral resistance in patients on a first-line antiretroviral treatment. Further studies are needed on the use of UDS for therapeutic management.

Molecular Epidemiology of HIV-1 in Ghana: Subtype Distribution, Drug Resistance and Coreceptor Usage

The greatest HIV-1 genetic diversity is found in West/Central Africa due to the pandemic’s origins in this region, but this diversity remains understudied. We characterized HIV-1 subtype diversity (from both sub-genomic and full-genome viral sequences), drug resistance and coreceptor usage in 103 predominantly (90%) antiretroviral-naive individuals living with HIV-1 in Ghana. Full-genome HIV-1 subtyping confirmed the circulating recombinant form CRF02_AG as the dominant (53.9%) subtype in the region, with the complex recombinant 06_cpx (4%) present as well. Unique recombinants, most of which were mosaics containing CRF02_AG and/or 06_cpx, made up 37% of sequences, while “pure” subtypes were rare (<6%). Pretreatment resistance to at least one drug class was observed in 17% of the cohort, with NNRTI resistance being the most common (12%) and INSTI resistance being relatively rare (2%). CXCR4-using HIV-1 sequences were identified in 23% of participants. Overall, our findings advance our understanding of HIV-1 molecular epidemiology in Ghana. Extensive HIV-1 genetic diversity in the region appears to be fueling the ongoing creation of novel recombinants, the majority CRF02_AG-containing, in the region. The relatively high prevalence of pretreatment NNRTI resistance but low prevalence of INSTI resistance supports the use of INSTI-based first-line regimens in Ghana.

Mechanisms of HIV-1 evasion to the antiviral activity of chemokine CXCL12 indicate potential links with pathogenesis

HIV-1 infects CD4 T lymphocytes (CD4TL) through binding the chemokine receptors CCR5 or CXCR4. CXCR4-using viruses are considered more pathogenic, linked to accelerated depletion of CD4TL and progression to AIDS. However, counterexamples to this paradigm are common, suggesting heterogeneity in the virulence of CXCR4-using viruses. Here, we investigated the role of the CXCR4 chemokine CXCL12 as a driving force behind virus virulence. In vitro, CXCL12 prevents HIV-1 from binding CXCR4 and entering CD4TL, but its role in HIV-1 transmission and propagation remains speculative. Through analysis of thirty envelope glycoproteins (Envs) from patients at different stages of infection, mostly treatment-naïve, we first interrogated whether sensitivity of viruses to inhibition by CXCL12 varies over time in infection. Results show that Envs resistant (RES) to CXCL12 are frequent in patients experiencing low CD4TL levels, most often late in infection, only rarely at the time of primary infection. Sensitivity assays to soluble CD4 or broadly neutralizing antibodies further showed that RES Envs adopt a more closed conformation with distinct antigenicity, compared to CXCL12-sensitive (SENS) Envs. At the level of the host cell, our results suggest that resistance is not due to improved fusion or binding to CD4, but owes to viruses using particular CXCR4 molecules weakly accessible to CXCL12. We finally asked whether the low CD4TL levels in patients are related to increased pathogenicity of RES viruses. Resistance actually provides viruses with an enhanced capacity to enter naive CD4TL when surrounded by CXCL12, which mirrors their situation in lymphoid organs, and to deplete bystander activated effector memory cells. Therefore, RES viruses seem more likely to deregulate CD4TL homeostasis. This work improves our understanding of the pathophysiology and the transmission of HIV-1 and suggests that RES viruses' receptors could represent new therapeutic targets to help prevent CD4TL depletion in HIV+ patients on cART.

Transmission patterns of HIV-1 non-R5 strains in Poland

HIV-1 env sequencing enables predictions of viral coreceptor tropism and phylogenetic investigations of transmission events. The aim of the study was to estimate the contribution of non-R5 strains to the viral spread in Poland. Partial proviral env sequences were retrieved from baseline blood samples of patients with newly diagnosed HIV-1 infection between 2008-2014, including 46 patients with recent HIV-1 infection (RHI), and 246 individuals with long-term infection (LTHI). These sequences were subjected to the genotypic coreceptor tropism predictions and phylogenetic analyses to identify transmission clusters. Overall, 27 clusters with 57 sequences (19.5%) were detected, including 15 sequences (26.3%) from patients with RHI. The proportion of non-R5 strains among all study participants was 23.3% (68/292), and was comparable between patients with RHI and LTHI (11/46, 23.9% vs 57/246, 23.2%; p = 1.000). All 11 patients with non-R5 strains and RHI were men having sex with men (MSM). Among these patients, 4 had viral sequences grouped within phylogenetic cluster with another sequence of non-R5 strain obtained from patient with LTHI, indicating potential acquisition of non-R5 HIV-1 for at least 4/46 (8.7%) patients with RHI. We were unable to confirm the contribution of patients with RHI to the forward transmission of non-R5 strains, but a relatively high proportion of non-R5 strains among them deserves attention due to the limited susceptibility to CCR5 antagonists.

Prediction of coreceptor usage by five bioinformatics tools in a large Ethiopian HIV-1 subtype C cohort

Background

Genotypic tropism testing (GTT) has been developed largely on HIV-1 subtype B. Although a few reports have analysed the utility of GTT in other subtypes, more studies using HIV-1 subtype C (HIV-1C) are needed, considering the huge contribution of HIV-1C to the global epidemic.

Methods

Plasma was obtained from 420 treatment-naïve HIV-1C infected Ethiopians recruited 2009–2011. The V3 region was sequenced and the coreceptor usage was predicted by five tools: Geno2Pheno clinical–and clonal–models, PhenoSeq-C, C-PSSM and Raymond’s algorithm. The impact of baseline tropism on antiretroviral treatment (ART) outcome was evaluated.

Results

Of 352 patients with successful baseline V3 sequences, the proportion of predicted R5 virus varied between the methods by 12.5% (78.1%-90.6%). However, only 58.2% of the predictions were concordant and only 1.7% were predicted to be X4-tropic across the five methods. Compared pairwise, the highest concordance was between C-PSSM and Geno2Pheno clonal (86.4%). In bivariate intention to treat (ITT) analysis, R5 infected patients achieved treatment success more frequently than X4 infected at month six as predicted by Geno2Pheno clinical (77.8% vs 58.7%, P = 0.004) and at month 12 by C-PSSM (61.9% vs 46.6%, P = 0.038). However, in the multivariable analysis adjusted for age, gender, baseline CD4 and viral load, only tropism as predicted by C-PSSM showed an impact on month 12 (P = 0.04, OR 2.47, 95% CI 1.06–5.79).

Conclusion

Each of the bioinformatics models predicted R5 tropism with comparable frequency but there was a large discordance between the methods. Baseline tropism had an impact on outcome of first line ART at month 12 in multivariable ITT analysis but only based on prediction by C-PSSM which thus possibly could be used for predicting outcome of ART in HIV-1C infected Ethiopians.