Tropism Prediction Research Articles

Prediction of Coreceptor Tropism in HIV-1 Subtype C in Botswana.

It remains unknown whether the C-C motif chemokine receptor type 5 (CCR5) coreceptor is still the predominant coreceptor used by Human Immunodeficiency Virus-1 (HIV-1) in Botswana, where the HIV-1 subtype C predominates. We sought to determine HIV-1C tropism in Botswana using genotypic tools, taking into account the effect of antiretroviral treatment (ART) and virologic suppression. HIV-1 gp120 V3 loop sequences from 5602 participants were analyzed for viral tropism using three coreceptor use predicting algorithms/tools: Geno2pheno, HIV-1C Web Position-Specific Score Matrices (WebPSSM) and the 11/25 charge rule. We then compared the demographic and clinical characteristics of people living with HIV (PLWH) harboring R5- versus X4-tropic viruses using χ2 and Wilcoxon rank sum tests for categorical and continuous data analysis, respectively. The three tools congruently predicted 64% of viruses as either R5-tropic or X4-tropic. Geno2pheno and the 11/25 charge rule had the highest concordance at 89%. We observed a significant difference in ART status between participants harboring X4- versus R5-tropic viruses. X4-tropic viruses were more frequent among PLWH receiving ART (χ2 test, p = 0.03). CCR5 is the predominant coreceptor used by HIV-1C strains circulating in Botswana, underlining the strong potential for CCR5 inhibitor use, even in PLWH with drug resistance. We suggest that the tools for coreceptor prediction should be used in combination.

Tropism prediction in HIV-1 variants circulating in Cuba, 2017-2019: Implications for the pathogenesis of infection and response to Maraviroc

Background: Tropism is determined by the ability of HIV-1 to bind to the receptors CCR5 or CXCR4 to enter the target cell, which has implications for the pathogenesis of the disease and affects treatment options. This study determined the relationship between the tropism of HIV-1 variants circulating in Cuba, with different variables, and the implications for the use of co-receptor inhibitors. Methods: Plasma samples from 69 of HIV-1 seropositive patients, period 2017-2019, were analyzed. Fragments of the env and pol regions of the virus were sequenced. The subtype and prediction of the viral phenotype, viral mutations, as well as the relationship of the phenotype and subtype with clinical, epidemiological, and virological variables were determined. Results: The recombinant CRF19_cpx (p=0.0234) showed a significant association with viruses that use the X4 and R5X4/X4 Co-receptor, even in untreated patients. Of the viruses studied, 78.26% presented at least one mutation associated with resistance to Maraviroc, although the patients had not received prior therapy with this drug. Conclusion: The preferential tropism for the CXCR4 co-receptor, detected in the CRF19_cpx variant, accompanied by greater viral replication and unrelated to the time of diagnosis of the patients, reinforces the hypothesis that viral variant is more pathogenic. The high frequency of polymorphisms and mutations that confer resistance to Maraviroc in the V2 and V3 regions of HIV-1 of the Cuban recombinant forms indicate that there could be a natural resistance to this antiretroviral.

HopPER: an adaptive model for probability estimation of influenza reassortment through host prediction

BackgroundInfluenza reassortment, a mechanism where influenza viruses exchange their RNA segments by co-infecting a single cell, has been implicated in several major pandemics since 19th century. Owing to the significant impact on public health and social stability, great attention has been received on the identification of influenza reassortment.MethodsWe proposed a novel computational method named HopPER (Host-prediction-based Probability Estimation of Reassortment), that sturdily estimates reassortment probabilities through host tropism prediction using 147 new features generated from seven physicochemical properties of amino acids. We conducted the experiments on a range of real and synthetic datasets and compared HopPER with several state-of-the-art methods.ResultsIt is shown that 280 out of 318 candidate reassortants have been successfully identified. Additionally, not only can HopPER be applied to complete genomes but its effectiveness on incomplete genomes is also demonstrated. The analysis of evolutionary success of avian, human and swine viruses generated through reassortment across different years using HopPER further revealed the reassortment history of the influenza viruses.ConclusionsOur study presents a novel method for the prediction of influenza reassortment. We hope this method could facilitate rapid reassortment detection and provide novel insights into the evolutionary patterns of influenza viruses.

Predicting Influenza A Tropism with End-to-End Learning of Deep Networks.

The type of host that a virus can infect, referred to as host specificity or tropism, influences infectivity and thus is important for disease diagnosis, epidemic response, and prevention. Advances in DNA sequencing technology have enabled rapid metagenomic analyses of viruses, but the prediction of virus phenotype from genome sequences is an active area of research. As such, automatic prediction of host tropism from analysis of genomic information is of considerable utility. Previous research has applied machine learning methods to accomplish this task, although deep learning (particularly deep convolutional neural network, CNN) techniques have not yet been applied. These techniques have the ability to learn how to recognize critical hierarchical structures within the genome in a data-driven manner. We designed deep CNN models to identify host tropism for human and avian influenza A viruses based on protein sequences and performed a detailed analysis of the results. Our findings show that deep CNN techniques work as well as existing approaches (with 99% mean accuracy on the binary prediction task) while performing end-to-end learning of the prediction model (without the need to specify handcrafted features). The findings also show that these models, combined with standard principal component analysis, can be used to quantify and visualize viral strain similarity.

A16 Next-generation sequencing to detect transmitted drug resistance mutations in Romanian people who inject drugs

Romania has faced an HIV outbreak among people who inject drugs (PWID) since 2011. The introduction of so-called ‘legal highs’ (amphetamine-type stimulants) on the drug market a few years prior contributed substantially to this outbreak. Next-generation sequencing (NGS) provides the possibility to detect drug resistance mutations with higher sensitivity than Sanger sequencing. The aim of this study was to search for transmitted drug resistance (TDR) mutations in strains from PWID recently diagnosed with HIV infection by parallel use of Sanger sequencing and NGS. The study was conducted on strains from 34 PWID diagnosed with HIV infection between 2016 and 2017. Sequencing was performed for the pol (PR, RT, and INT) and env (V2-V3 loop) regions. Sanger sequencing was performed with the commercial ViroseqTMHIV-1 Genotyping system (Abbott Laboratories) and with an in-house protocol for the env gene. NGS was performed in the same genomic regions using Nextera DNA Library Preparation Kit (Illumina) and the Miseq instrument (Illumina). NGS data were processed for error correction, read mapping, and detection of drug resistance mutations with HIV-1 Deepchek analysis software. Geno2pheno algorithm was used for viral tropism prediction and the WHO 2009 list for TDRM analysis. By using NGS, we detected seven cases (20.6%) of TDR in PWID and only two cases (5.8%) with standard sequencing. The TDR mutations detected by NGS were K103N, K101EN, Y181C, T215S in RT gene, I54V and M46L in PR, and none in INT. Two NNRTI mutations (K103N and K101EN) were detected in the same sample. Most of the TDR identified were present in the minority population (between 1% and 2% of the total reads) explaining the higher sensitivity of NGS method compared with standard sequencing. No significant differences were observed between these two methods when tropism prediction was analyzed. The majority of the viruses circulating in this group were R5-tropic. All strains showed more resistance mutations when analyzed by deep sequencing than by Sanger sequencing and more than previously observed in other risk groups. NGS proved to be a sensitive tool to detect TDR in newly infected PWID.

A7 Co-receptor tropism determined by genotypic assay in HIV-1 non-B subtypes circulating in Cuba: Implications for pathogenesis and Maraviroc resistance

The V3 loop of the HIV-1 envelope (env) gene is involved in binding to the chemokine receptors CCR5 and CXCR4, thus determining viral tropism. With the aim of genetically characterizing the C2V3 env region of HIV-1 samples from Cuban patients, naive to Maraviroc (MVC) therapy, 115 plasma samples were taken in the period of 2014–6 and analyzed by sequencing of the C2V3 region. HIV-1 subtyping was performed using COMET V.2 and Rega subtyping toolV.3 software. Subtypes were confirmed by phylogenetic analyses using Mega-6. Prediction of co-receptor tropism was performed using the geno2pheno algorithm. The viral mutations associated to MVC resistance were analyzed, as well as the association of the subtype with clinical, epidemiological, virological, and immunological variables. The subtypes detected using the C2V3 region were CRF20, 23, 24_BG (35 patients, 30.4%); Subtype B (33 patients, 28.7%); CRF19_cpx (30 patients, 26.1%); CRF18_cpx (10 patients, 8.7%); and others (7 patients, 6.1%). Overall, 60 per cent of the viruses exhibited R5 phenotype, 14.8 per cent were R5X4 and 25.2 per cent were X4. Interestingly, CRF19_cpx virus was associated with having phenotype X4 [46.7%, P = 0.0047, odds ratio (OR): 3.96, 95% confidence interval (95% CI): 1.59–9.84], with infection in young individuals (39.1%, P = 0.025, OR: 3,548; 95% CI: 1,136–11,077) and with higher values of viral load (P ≤ 0.05). The comparison of the amino acid sequences of the V3 loop showed differences between the B and non-B subtypes (P = 0.0001). Mutations reported to be associated with MVC resistance, were detected in 75.7 per cent of the samples, in positions 11 (6.1%), 13 (49.6%), 25 (6.1%), 316 (7.0%), 323 (11.3%), and 319 (3.5%) of Gp120, particularly in the recombinant forms CRF19_cpx and CRF_BGs. HIV variants that use the CXCR4 co-receptor were associated with more than 10 years of diagnosis, with older individuals, in the AIDS stage, with low CD4 counts and higher viral load levels (P < 0.05). The results support the hypothesis previously stated that CRF19_cpx viruses could be more pathogenic and would have limitations for the use of MVC. The high rate of mutations associated to MVC among non-B Cuban subtypes should be further studied.

HIV-1 tropism prediction by the XGboost and HMM methods

Human Immunodeficiency Virus 1 (HIV-1) co-receptor usage, called tropism, is associated with disease progression towards AIDS. Furthermore, the recently developed and developing drugs against co-receptors CCR5 or CXCR4 open a new thought for HIV-1 therapy. Thus, knowledge about tropism is critical for illness diagnosis and regimen prescription. To improve tropism prediction accuracy, we developed two novel methods, the extreme gradient boosting based XGBpred and the hidden Markov model based HMMpred. Both XGBpred and HMMpred achieved higher specificities (72.56% and 72.09%) than the state-of-the-art methods Geno2pheno (61.6%) and G2p_str (68.60%) in a 10-fold cross validation test at the same sensitivity of 93.73%. Moreover, XGBpred had more outstanding performances (with AUCs 0.9483, 0.9464) than HMMpred (0.8829, 0.8774) on the Hivcopred and Newdb (created in this work) datasets containing larger proportions of hard-to-predict dual tropic samples in the X4-using tropic samples. Therefore, we recommend the use of our novel method XGBpred to predict tropism. The two methods and datasets are available via http://spg.med.tsinghua.edu.cn:23334/XGBpred/. In addition, our models identified that positions 5, 11, 13, 18, 22, 24, and 25 were correlated with HIV-1 tropism.

Performance of Geno2Pheno[coreceptor] to infer coreceptor use in human immunodeficiency virus type 1 (HIV-1) subtype A

BackgroundAssessment of human immunodeficiency virus type 1 (HIV-1) coreceptor usage is required prior to treatment with the CCR5 antagonist maraviroc to exclude the presence of CXCR4-using (X4) strains. Genotype-based interpretation systems are mostly designed on subtype B and have been reported to be less accurate for subtype A/CRF02_AG. ObjectivesTo evaluate the performance of the widely used Geno2Pheno[coreceptor] (G2P[c]) algorithm for prediction of coreceptor usage with subtype A/CRF02_AG vs. subtype B. Study designCo-receptor tropism of 24 subtype A/CRF02_AG and 24 subtype B viruses was measured phenotypically by a homebrew single-cycle assay and genotypically by using G2P[c]. Samples with discrepant genotype-phenotype results were analyzed by next generation sequencing (NGS) and interpreted by the NGS Geno2Pheno algorithm (G2P[454]). ResultsAt 10% false positive rate (FPR), the G2P[c]/phenotype discordance rate was 12.5% (n = 3) for subtype A/CRF02_AG and 8.3% (n = 2) for subtype B. Minority X4 species escaping detection by bulk sequencing but documented by NGS explained the two subtype B and possibly one subtype A/CRF02_AG discordant case. The other two subtype A/CRF02_AG miscalled by G2P[c] could be explained by X4 overcalling at borderline FPR and/or by algorithm failure. DiscussionOur study did not demonstrate relevantly higher G2P[c] inaccuracy with subtype A/CRF02_AG with respect to subtype B. Genotype/phenotype discordances can be due to different reasons, including but not limited to, algorithm inaccuracy. Very large genotype/phenotype correlation panels are required to detect and explain the reason for any consistent difference in genotypic tropism prediction for subtype A/CRF02_AG vs. subtype B.

Computational identification of physicochemical signatures for host tropism of influenza A virus.

Avian influenza viruses from migratory birds have managed to cross host species barriers and infected various hosts like human and swine. Epidemics and pandemics might occur when influenza viruses are adapted to humans, causing deaths and enormous economic loss. Receptor-binding specificity of the virus is one of the key factors for the transmission of influenza viruses across species. The determination of host tropism and understanding of molecular properties would help identify the mechanism why zoonotic influenza viruses can cross species barrier and infect humans. In this study, we have constructed computational models for host tropism prediction on human-adapted subtypes of influenza HA proteins using random forest. The feature vectors of the prediction models were generated based on seven physicochemical properties of amino acids from influenza sequences of three major hosts. Feature aggregation and associative rules were further applied to select top 20 features and extract host-associated physicochemical signatures on the combined model of nonspecific subtypes. The prediction model achieved high performance ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mtext>Accuracy</mml:mtext><mml:mo>=</mml:mo><mml:mn>0</mml:mn><mml:mo>.</mml:mo><mml:mn>9</mml:mn><mml:mn>4</mml:mn><mml:mn>8</mml:mn></mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mtext>Precision</mml:mtext><mml:mo>=</mml:mo><mml:mn>0</mml:mn><mml:mo>.</mml:mo><mml:mn>9</mml:mn><mml:mn>5</mml:mn><mml:mn>4</mml:mn></mml:math> , <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mtext>MCC</mml:mtext><mml:mo>=</mml:mo><mml:mn>0</mml:mn><mml:mo>.</mml:mo><mml:mn>9</mml:mn><mml:mn>2</mml:mn><mml:mn>2</mml:mn></mml:math> ). Support and confidence rates were calculated for the host class-association rules. The results indicated that secondary structure and normalized Van der Waals volume were identified as more important physicochemical signatures in determining the host tropism.

Coreceptor Tropism and Maraviroc Sensitivity of Clonally Derived Ethiopian HIV-1C Strains Using an in-house Phenotypic Assay and Commonly Used Genotypic Methods.

Genotypic Tropism Testing (GTT) tools are generally developed based on HIV-1 subtype B (HIV-1B) and used for HIV-1C as well but with a large discordance of prediction between different methods. We used an established phenotypic assay for comparison with GTT methods and for the determination of in vitro maraviroc sensitivity of pure R5-tropic and dual-tropic HIV-1C. Plasma was obtained from 58 HIV-1C infected Ethiopians. Envgp120 was cloned into a luciferase tagged NL4-3 plasmid. Phenotypic tropism was determined by in house method and the V3 sequences were analysed by five GTT methods. In vitro maraviroc sensitivity of R5-tropic and dual-tropic isolates were compared in the TZMbl cell-line. The phenotypes were classified as R5 in 92.4% and dual tropic (R5X4) in 7.6% of 79 clones. The concordance between phenotype and genotype ranged from 64.7% to 84.3% depending on the GTT method. Only 46.9% of the R5 phenotypes were predicted as R5 by all GTT tools while R5X4 phenotypes were predicted as X4 by four methods, but not by Raymond's method. All six tested phenotypic R5 clones, as well as five of six of dual tropic clones, showed a dose response to maraviroc. There is a high discordance between GTT methods, which underestimates the presence of R5 and overestimates X4 strains compared to a phenotypic assay. Currently available GTT algorithms should be further improved for tropism prediction in HIV-1C. Maraviroc has an in vitro activity against most HIV-1C viruses and could be considered as an alternative regimen in individuals infected with CCR5-tropic HIV-1C viruses.

Deep-Sequencing Analysis of the Dynamics of HIV-1 Quasiespecies in Naive Patients during a Short Exposure to Maraviroc.

In this study, we have characterized quasispecies dynamics and the evolution of viral tropism in naive HIV-1-infected patients treated with a short course of maraviroc monotherapy (ClinicalTrials.gov registration no. NCT01060618) independently of the tropism of the infecting virus. We randomly selected 20 patients infected with viruses displaying different basal tropisms-10 carrying R5 and 10 carrying dual/mixed X4 (DM/X4) viruses-at recruitment as determined by phenotypic assay (Trofile). Evolution of viral quasiespecies at the end of treatment was determined by ultradeep sequencing of the V3 region using a 454 Life Sciences Platform and geno2pheno (g2p) algorithm for viral tropism prediction. The false-positive rate (FPR) that defines the probability of classifying an R5 virus falsely as X4 was set at 10%. X4-specific HIV-1 viral load (VL) was calculated from sequences with an FPR of <3.75%. Virological response as defined as >1-log10 copies/ml reduction in VL was detected in 70% of patients independently of the basal tropism of the infecting virus. Viral tropism remained stable, and nonsignificant differences in FPR values before and after treatment were found for the majority of patients in both tropism groups. Only three patients (one with R5 and two with DM/X4 viruses) showed an increased (>1 log) X4 VL, and one patient harboring a DM/X4-tropic virus displayed a significant reduction in FPR values at the end of treatment. Fast changes in the composition of viral populations were observed in all patients after 10 days of maraviroc (MVC) monotherapy treatment, and a complete replacement of viral quasiespecies was found in 3/10 patients carrying R5-using viruses and 4/10 patients carrying DM/X4-using viruses.IMPORTANCE Initiation of treatment with maraviroc requires previous determination of viral tropism by genotypic or phenotypic methods because of the risk of treatment failure and selection of DM/X4-tropic variants. In this study, we confirm previous work showing that the virologic response to maraviroc is independent of basal tropism. By deep-sequencing analysis, we determined that fast changes in viral populations were due to the emergence of minority variants in some patients whereas in others generation of new strains was detected. The risk of DM/X4 selection was very low as FPR values remained stable, and only one patient showed a detrimental switch to DM/X4 variants. Our data show that some DM/X4 viruses are sensitive to maraviroc treatment probably because only a low proportion of DM/X4 viruses use preferentially the X4 receptor and contain authentically maraviroc-resistant viruses that are not accurately detected by current assays.

SCOTCH: subtype A coreceptor tropism classification in HIV-1.

The V3 loop of the gp120 glycoprotein of the Human Immunodeficiency Virus 1 (HIV-1) is considered to be responsible for viral coreceptor tropism. gp120 interacts with the CD4 receptor of the host cell and subsequently V3 binds either CCR5 or CXCR4. Due to the fact that the CCR5 coreceptor is targeted by entry inhibitors, a reliable prediction of the coreceptor usage of HIV-1 is of great interest for antiretroviral therapy. Although several methods for the prediction of coreceptor tropism are available, almost all of them have been developed based on only subtype B sequences, and it has been shown in several studies that the prediction of non-B sequences, in particular subtype A sequences, are less reliable. Thus, the aim of the current study was to develop a reliable prediction model for subtype A viruses. Our new model SCOTCH is based on a stacking approach of classifier ensembles and shows a significantly better performance for subtype A sequences compared to other available models. In particular for low false positive rates (between 0.05 and 0.2, i.e. recommendation in the German and European Guidelines for tropism prediction), SCOTCH shows significantly better prediction performances in terms of partial area under the curves and diagnostic odds ratios compared to existing tools, and thus can be used to reliably predict coreceptor tropism for subtype A sequences. SCOTCH can be downloaded/accessed at http://www.heiderlab.de.

Results of the first international HIV-1 coreceptor proficiency panel test

BackgroundQuality Assurance (QA) programs are essential to evaluate performance in diagnostics laboratories. ObjectivesWe present the results from the first QA for HIV-1 genotypic tropism testing, organized and coordinated by the Institute of Virology at the University of Cologne. Study design12 cell culture-derived viral strains of different HIV-1 clades from the NIH AIDS Reagent Program were sent to the participants to be processed with their standard diagnostic methods Fasta files containing the V3 region sequence were centrally analyzed at the Institute of Virology, Cologne. All samples were sent in parallel for phenotypic testing. Results36 laboratories from 16 countries reported genotypic results. The sequence-generation efficacy was 95.1%, while the phenotypic assays ESTA® and PhenXR only achieved results for 58.3% of the samples. All four X4 samples were identified by 31/36 laboratories, two laboratories amplified 3/4×4 samples, and three detected 2/4×4 samples.There was high concordance among the genotypic and phenotypic results, although differences in FPR values were detected. Most deficiencies in sequence editing did not result in wrong classification of X4 viruses as R5, with the exception of sample NRZ05 by laboratory 38, but in an overestimation of CXCR4 use. ConclusionsThis demonstrates that genotypic tropism prediction is a safe procedure for clinical purposes. As we used homogeneous cell culture samples and all sequence fasta files were centrally analyzed, variations in FPR values can only be attributed to sample preparation, RT-PCR or sequence editing protocols.

Performance comparison of next-generation sequencing platforms for determining HIV-1 coreceptor use

The coreceptor used by HIV-1 must be determined before a CCR5 antagonist, part of the arsenal of antiretroviral drugs, is prescribed because viruses that enter cells using the CXCR4 coreceptor are responsible for treatment failure. HIV-1 tropism is also correlated with disease progression and so must be determined for virological studies. Tropism can be determined by next-generation sequencing (NGS), but not all of these new technologies have been fully validated for use in clinical practice. The Illumina NGS technology is used in many laboratories but its ability to predict HIV-1 tropism has not been evaluated while the 454 GS-Junior (Roche) is used for routine diagnosis. The genotypic prediction of HIV-1 tropism is based on sequencing the V3 region and interpreting the results with an appropriate algorithm. We compared the performances of the MiSeq (Illumina) and 454 GS-Junior (Roche) systems with a reference phenotypic assay. We used clinical samples for the NGS tropism predictions and assessed their ability to quantify CXCR4-using variants. The data show that the Illumina platform can be used to detect minor CXCR4-using variants in clinical practice but technical optimization are needed to improve quantification.

HIV-1 Drug Susceptibility to Potential Second- and Third-Line Antiretroviral Regimens among Cameroonian Patients: Evidence from a Crosssectional Design

Scale-up of antiretroviral therapy (ART) and the growing number of long-term treated patients may favor multi-HIV drug resistance (HIVDR) in resource-limited settings. Understanding the burden of HIVDR with ART-exposure may provide new insights for an effective long-term management of infected patients. Sixty-six HIV-infected individuals (18 ART-naïve, 24 failing first-line, 24 failing second-line ART) living in Yaoundé-Cameroon were evaluated by sequencing protease-reverse transcriptase (PR-RT, n=62), envelope-V3 loop (V3, n=58) and integrase (IN, n=30) regions. Drug resistance mutations (DRMs) were interpreted using Stanford University HIV drug resistance database and geno2pheno, while viral tropism prediction was done using geno2pheno, position-specific scoring matrices (PSSM) and Net charge rule. Participants, from naïve, first- to second-line, had respectively 5.30, 4.85 and 4.66 log HIV RNA, and 532, 203 and 146 CD4 cells/mm3), and infected with diverse HIV-1 non-B clades (58.1% CRF02_AG). Among ART-naïve patients, 6.7% harbored K103N, 28.6% had IN accessory-mutations (L74I, E157Q) and 26.7% carried CXCR4-tropic viruses. At first-line failure, 79.2% harbored DRMs to nucleoside and non-nucleoside RT inhibitors, 33.3% had IN accessory-mutations (L68I, L74I, T97A, E157Q), and 47.4% carried CXCR4-tropic viruses. At second-line failure, 91.3% harbored multi-DRMs to PR-RT inhibitors (with 52.2% and 4.3% DRMs to second-generation NNRTIs and darunavir/r, respectively), 27.3% had IN accessory-mutations (L74I, T97A, E157EQ), and 37.5% carried CXCR4-tropic viruses. Levels of PR-RT resistance increases with ART-exposure, with needs for new ART-options following second-line failure. IN inhibitors and darunavir/r are potentially suitable for a third-line regimen, while the use of maraviroc, etravirine or rilpivirine, requires individual genotypic testing.

Performance of genotypic algorithms for predicting tropism of HIV-1CRF02_AG subtype

BackgroundSeveral genotypic rules for predicting HIV-1 non-B subtypes tropism are commonly used, but there is no consensus about their performances. ObjectivesThree genotypic methods were compared for CRF02_AG HIV-1 tropism determination. Study designV3 env region of 178HIV-1 CRF02_AG from Pitié-Salpêtrière and Saint-Antoine Hospitals was sequenced from plasma HIV-1 RNA. HIV-1 tropism was determined by Geno2Pheno algorithm, false positive rate (FPR) 5% or 10%, the 11/25 rule or the combined criteria of the 11/25 and net charge rule. ResultsA concordance of 91.6% was observed between Geno2pheno 5% and the combined criteria. The results were nearly similar for the comparison between Geno2pheno 5% and the 11/25 rule. More mismatches were observed when Geno2pheno was used with the FPR 10%. A lower nadir CD4 cell count was associated with a discordance of tropism prediction between Geno2pheno 5% and the combined criteria or the 11/25 rule (p=0.02 and p=0.03, respectively). A lower HIV-1 viral load was associated with some discordance for the comparison of Geno2pheno 10% and the combined rule (p=0.02). ConclusionGeno2pheno FPR 5% or 10% predicted more X4-tropic viruses for this set of CRF02_AG sequences than the combined criteria or the 11/25 rule alone. Furthermore, Geno2pheno FPR 5% was more concordant with the 11/25 rule and the combined rule than Geno2pheno 10% to predict HIV-1 tropism. Overall, Geno2pheno 5% could be used to predict CRF02_AG tropism as well as other genotypic rules.

HIV coreceptor tropism among patients with newly diagnosed infection

Introduction: Coreceptor tropism is the ability of human immunodeficiency virus (HIV) to use CCR5 or CXCR4 coreceptor to enter the host cell. Tropism depends on the structure of the surface glycoprotein, involved in binding molecules to receptor and coreceptor. Viruses that CCR5use are named R5, viruses that CXCR4 use are X4-tropic, and dual/mixed (DM) viruses use either of the two. During early stages of HIV infection,R5 strains are usually present and with the progression of HIV disease, frequency of X4 occurs. Aim: The aim of the study was to analyze the coreceptor tropism in newly diagnosed HIV infected patients. Material and methods: The study group included 26 patients with newly diagnosed HIV infection, in the hospital care from 2010 to 2012 at the Clinic for Infectious and Tropical diseases of the Clinical Center of Serbia. Upon RNA isolation from plasma, PCR amplification and DNA sequencing of the V3 loop of the env gene were performed. The sequences were used for prediction of the coreceptor tropism, using the Geno2pheno bioinformatics algorithms. Results: R5 and X4 tropism were detected in 21/26 (81%) and 5/26 (19%) patients, respectively. Five out of twenty-six patients (19.2%) were in the C3 clinical stadium of the disease, and all of them were infected with R5-tropic virus. Fourteen out of twenty-five patients (56%) were late presenters of HIV infection, where 12 (86%) of them were infected with R5-tropic virus. Conclusion: Our results imply that the majority of HIV strains in patients, with newly diagnosed infection in Serbia, are characterized by R5 tropism. However, the prevalence of X4 strains is not negligible, indicating late presentation of newly diagnosed patients, but also possibly implying increased virulence of the circulating strains. Considering that CCR5 antagonists would not be effective in 19% of studied patients, the prediction of coreceptor tropism is undoubtedly very important.

Characteristics and spread to the native population of HIV-1 non-B subtypes in two European countries with high migration rate.

BackgroundNon-B subtypes account for at least 50 % of HIV-1 infections diagnosed in Belgium and Luxembourg. They are considered to be acquired through heterosexual contacts and infect primarily individuals of foreign origin. Information on the extent to which non-B subtypes spread to the local population is incomplete.MethodsPol and env gene sequences were collected from 410 non-subtype B infections. Profound subtyping was performed using 5 subtyping tools and sequences of both pol and env. Demographic information, disease markers (viral load, CD4 count) and viral characteristics (co-receptor tropism) were compared between subtypes. Maximum likelihood phylogenetic trees were constructed and examined for clustering.ResultsThe majority of non-B infections were diagnosed in patients originating from Africa (55.8 %), individuals born in Western Europe represented 30.5 %. Heterosexual transmission was the most frequently reported transmission route (79.9 %), MSM transmission accounted for 12.2 % and was significantly more frequently reported for Western Europeans (25.7 % versus 4.3 % for individuals originating from other regions; p < 0.001). Subtypes A and C and the circulating recombinant forms CRF01_AE and CRF02_AG were the most represented and were included in the comparative analysis. Native Western Europeans were underrepresented for subtype A (14.5 %) and overrepresented for CRF01_AE (38.6 %). The frequency of MSM transmission was the highest for CRF01_AE (18.2 %) and the lowest for subtype A (0 %). No differences in age, gender, viral load or CD4 count were observed. Prevalence of CXCR4-use differed between subtypes but largely depended on the tropism prediction algorithm applied. Indications for novel intersubtype recombinants were found in 20 patients (6.3 %). Phylogenetic analysis revealed only few and small clusters of local transmission but could document one cluster of CRF02_AG transmission among Belgian MSM.ConclusionsThe extent to which non-B subtypes spread in the native Belgian-Luxembourg population is higher than expected, with 30.5 % of the non-B infections diagnosed in native Western Europeans. These infections resulted from hetero- as well as homosexual transmission. Introduction of non-B variants in the local high at risk population of MSM may lead to new sub-epidemics and/or increased genetic variability and is an evolution that needs to be closely monitored.

HIV co-receptor tropism prediction remains stable over time in treatment-naïve patients.

HIV co-receptor tropism determination is essential before prescribing the CCR5 antagonist maraviroc. British HIV Association guidelines suggest tropism testing may remain valid for only 90 days in antiretroviral-naïve patients. We aimed to determine the accuracy of this figure. Tropism was assessed in 26 antiretroviral-naïve patients with ongoing viral replication, sampled yearly from first clinic visit. The V3 region of HIV-1 was sequenced in triplicate, then tropism predicted using the Geno2Pheno system. Baseline tropism prediction remained valid for a median of 52 months (range 7-81). For 19/26 individuals baseline tropism remained unchanged throughout a median of 54 months follow-up; 18 R5 tropic and 1 X4 tropic. In seven patients (27%) baseline tropism switched at least once (range 1-4 switches) during follow-up; however, their baseline tropism prediction remained valid for a median of 45 months. Co-receptor tropism in treatment-naïve patients with ongoing viral replication appears highly stable over time, suggesting that baseline genotypic tropism prediction may be valid for a longer duration in patients delaying ART initiation. In this study, baseline tropism prediction remained valid for a median of 52 months, suggesting current guidelines recommending repeat testing after 90 days may be excessively conservative in their assessment of tropism stability.

Effects of sequence alterations on results from genotypic tropism testing

Backgroundgeno2pheno[coreceptor] is a bioinformatic method for genotypic tropism determination (GTD) which has been extensively validated. ObjectivesGTD can be affected by sequencing/base-calling variability and unreliable representation of minority populations in Sanger bulk sequencing. This study aims at quantifying the robustness of geno2pheno[coreceptor] with respect to these issues. GTD with a single amplification or in triplicate (henceforth singleton/triplicate) is considered. Study DesignFrom a dataset containing 67,997HIV-1 V3 nucleotide sequences, two datasets simulating sequencing variability were created. Further two datasets were created to simulate unreliable representation of minority variants. After interpretation of all sequences with geno2pheno[coreceptor], probabilities of change of predicted tropism were calculated. Resultsgeno2pheno[coreceptor] tends to report reduced false-positive rates (FPRs) when sequence alterations are present. Triplicate FPRs tend to be lower than singleton FPRs, resulting in a bias towards classifying viruses as X4-capable. Alterations introduced into nucleotide sequences by simulation change singleton predicted tropism with a probability≤2%. Triplicate prediction lowers this probability for predicted X4 tropism, but raises it for predicted R5 tropism≤6%. Simulated limited detection of minority variants in X4 sequences resulted in unchanged predicted tropism with probability above 90% as compared to probability above 98% with triplicate FPRs. Conclusionsgeno2pheno[coreceptor] proved to be robust when sequence alterations are present and when detectable minorities are missed by bulk sequencing. Changes in tropism prediction due to sequence alterations as well as triplicate prediction are much more likely to result in false X4-capable predictions than in false R5 predictions.