Tropism Prediction Research Articles

HIV Tropism Prediction: Digital Signal Processing-Based Bioinformatics Approach is Non-Sequence Alignment Dependent

Phenotypic and genotypic predictors forHIV/SIV tropism are available. The genotypic predictors are more rational. However, they are sequence alignment dependent only. Regrettably, non-homologous proteins are found to display common biological functionality. This indicates that sequence-dependent predictors cannot be trusted with appropriate classification of the HIV and SIV isolates, especially if the isolates belong to same tropic group but share divergent sequence alignment. There is therefore need for genotypic predictors that will incorporate embedded intrinsic biological characteristics of the HIV and SIV isolates in the determination of HIV tropism. Secondly, more than 30 positions with at least single mutation outside the V3 domain have been found to influence HIV Tropism. Disappointingly, the available sequence alignment-based HIV genotypic predictors engage only the hyper-variable region (V3) of the HIV gp120. This has resulted in inaccurate classification of HIV and SIV strains. Finally, available HIV genotypic predictors are found to lack the ability to identify and accurately evaluate the sequences of most HIV-1 non B clades, HIV-2 and SIV. Against this background, the ability of the Digital Signal Processing (DSP) Technique called Informational Spectrum Method (ISM), which does not engage sequence similarity but the embedded bio-functionalities of the entire gp120 sequence length to predict HIV and SIV tropism is therefore investigated. 83 isolates of HIV and SIV are subjected to ISM and three other procedures. Results are generated and findings correlated. For isolates, which are analyzable by the four procedures, the results from ISM and three other procedures are found to correlate. Using 50% affinity for the host CD4 as the cut-off, the tropism of the uncategorized isolates are predicted. ISM-based technique is adjudged a better procedure. It analyzes the sequences of all HIV (HIV-1 together with non B, and HIV-2) as well as SIV isolates including those that could not be investigated by other genotypic predictors. It engages the embedded biological characteristics rather than sequence similarity and utilizes the entire HIV gp120 sequence-length instead of V3 domain. This makes ISM-based procedure a better tool for over 180,000 isolates of HIV-1, HIV-2 and SIV in the UNIPROT database. Clinical approaches are unfeasible. This study recommends ISM technique principally for viral tropism prediction as it does not discriminate against HIV/SIVcategories. It suggests that further work be done to determine a suitable cut-off (as in geno2pheno[CORECEPTOR]), and the procedure in combination with other genotypic predictors be engaged in developing an algorithm for determining viral tropism.

X4 Tropic Virus Prediction Is Associated with a Nadir CD4 T-Cell Count below 100 Cells/mm3

Objective: The aim of this study was to evaluate tropism prediction performances of three algorithms [geno2pheno false-positive rate 10% (G2P10), position-specific scoring matrix (PSSM) and a combination of the 11/25 and net charge rules] and to investigate the viral and host factors potentially involved in the X4 or R5 prediction in human immunodeficiency virus-1 (HIV-1) patients. Methods: Viral tropism was determined in 179 HIV-1-infected patients eligible for CCR5 antagonist therapy. HIV-1 RNA or DNA was extracted and amplified for env gp120 sequencing. In parallel, demographic, viral, immunological and clinical determinants were analyzed. Results: According to the G2P10 algorithm, 48 patients harbored X4 or X4R5 virus. The tropism prediction was concordant for 87.7 and 88.2% of samples when comparing G2P10 with PSSM or with a combination of the 11/25 and net charge rules, respectively. X4 prediction was significantly associated with more than 35 amino acids in the V3 domain (p < 0.0001) and loss of an N-linked glycosylation site (p < 0.0001). Of the factors studied, only the nadir CD4 T-cell count was significantly associated with X4 tropism (p = 0.01). Conclusion: We determined that the X4 virus detection is closely linked to the nadir CD4 T-cell count below 100 cells/mm³ that must be taken into account when considering a CCR5 antagonist therapy switch.

The temporal increase in HIV-1 non-R5 tropism frequency among newly diagnosed patients from northern Poland is associated with clustered transmissions.

IntroductionCCR5 (R5) tropic viruses are associated with early stages of infection, whereas CXCR4 (X4) HIV-1 tropism has been associated with severe immunodeficiency. We investigated the temporal changes in the genotype-predicted tropism frequency and the phylogenetic relationships between the R5 and non-R5 clades.MethodsA cohort of 194 patients with a newly diagnosed HIV infection that was linked to their care from 2007 to 2014 was analyzed. Baseline plasma samples were used to assess the HIV-1 genotypic tropism with triplicate V3-loop sequencing. The non-R5 tropism prediction thresholds were assigned using a false positive rate (FPR) of 10 and 5.75% and associated with clinical and laboratory data. The transmission clusters were analyzed using pol sequences with a maximum likelihood and Bayesian inference.ResultsThe overall non-R5 tropism frequency for 5.75% FPR was 15.5% (n=30) and 27.8% (n=54) for 10% FPR. The frequency of the non-R5 tropism that was predicted using 5.75% FPR increased significantly from 2007 (0%) to 2014 (n=5/17, 29.4%) (p=0.004, rough slope +3.73%/year) and from 0% (2007) to 35.3% (2014, n=6/17) (p=0.071, rough slope +2.9%/year) using 10% FPR. Increase in the asymptomatic diagnoses over time was noted (p=0.05, rough slope +3.53%/year) along with a tendency to increase the lymphocyte CD4 nadir (p=0.069). Thirty-two clusters were identified, and non-R5 tropic viruses were found for 26 (30.95%) sequences contained within 14 (43.8%) clusters. Non-R5 tropism was associated with subtype D variants (p=0.0001) and the presence of CCR5 Δ32/wt genotype (p=0.052).ConclusionsR5 tropism predominates among the treatment of naive individuals, but the increases in the frequency of non-R5 tropic variants may limit the clinical efficacy of the co-receptor inhibitors. The rising prevalence of non-R5 HIV-1 may indicate transmission of X4 clades.

V3 net charge: additional tool in HIV-1 tropism prediction.

Genotype-based algorithms are valuable tools for the identification of patients eligible for CCR5 inhibitors administration in clinical practice. Among the available methods, geno2pheno[coreceptor] (G2P) is the most used online tool for tropism prediction. This study was conceived to assess if the combination of G2P prediction with V3 peptide net charge (NC) value could improve the accuracy of tropism prediction. A total of 172 V3 bulk sequences from 143 patients were analyzed by G2P and NC values. A phenotypic assay was performed by cloning the complete env gene and tropism determination was assessed on U87_CCR5(+)/CXCR4(+) cells. Sequences were stratified according to the agreement between NC values and G2P results. Of sequences predicted as X4 by G2P, 61% showed NC values higher than 5; similarly, 76% of sequences predicted as R5 by G2P had NC values below 4. Sequences with NC values between 4 and 5 were associated with different G2P predictions: 65% of samples were predicted as R5-tropic and 35% of sequences as X4-tropic. Sequences identified as X4 by NC value had at least one positive residue at positions known to be involved in tropism prediction and positive residues in position 32. These data supported the hypothesis that NC values between 4 and 5 could be associated with the presence of dual/mixed-tropic (DM) variants. The phenotypic assay performed on a subset of sequences confirmed the tropism prediction for concordant sequences and showed that NC values between 4 and 5 are associated with DM tropism. These results suggest that the combination of G2P and NC could increase the accuracy of tropism prediction. A more reliable identification of X4 variants would be useful for better selecting candidates for Maraviroc (MVC) administration, but also as a predictive marker in coreceptor switching, strongly associated with the phase of infection.

Predicting host tropism of influenza A virus proteins using random forest.

BackgroundMajority of influenza A viruses reside and circulate among animal populations, seldom infecting humans due to host range restriction. Yet when some avian strains do acquire the ability to overcome species barrier, they might become adapted to humans, replicating efficiently and causing diseases, leading to potential pandemic. With the huge influenza A virus reservoir in wild birds, it is a cause for concern when a new influenza strain emerges with the ability to cross host species barrier, as shown in light of the recent H7N9 outbreak in China. Several influenza proteins have been shown to be major determinants in host tropism. Further understanding and determining host tropism would be important in identifying zoonotic influenza virus strains capable of crossing species barrier and infecting humans.ResultsIn this study, computational models for 11 influenza proteins have been constructed using the machine learning algorithm random forest for prediction of host tropism. The prediction models were trained on influenza protein sequences isolated from both avian and human samples, which were transformed into amino acid physicochemical properties feature vectors. The results were highly accurate prediction models (ACC>96.57; AUC>0.980; MCC>0.916) capable of determining host tropism of individual influenza proteins. In addition, features from all 11 proteins were used to construct a combined model to predict host tropism of influenza virus strains. This would help assess a novel influenza strain's host range capability.ConclusionsFrom the prediction models constructed, all achieved high prediction performance, indicating clear distinctions in both avian and human proteins. When used together as a host tropism prediction system, zoonotic strains could potentially be identified based on different protein prediction results. Understanding and predicting host tropism of influenza proteins lay an important foundation for future work in constructing computation models capable of directly predicting interspecies transmission of influenza viruses. The models are available for prediction at http://fluleap.bic.nus.edu.sg.

Genotypic prediction of tropism of highly diverse HIV-1 strains from Cameroon.

BackgroundThe use of CCR5 antagonists involves determination of HIV-1 tropism prior to initiation of treatment. HIV-1 tropism can be assessed either by phenotypic or genotypic methods. Genotypic methods are extensively used for tropism prediction. However, their validation in predicting tropism of viral isolates belonging to group M non-B subtypes remains challenging. In Cameroon, the genetic diversity of HIV-1 strains is the broadest reported worldwide. To facilitate the integration of CCR5 antagonists into clinical practice in this region, there is a need to evaluate the performance of genotypic methods for predicting tropism of highly diverse group M HIV-1 strains.MethodsTropism of diverse HIV-1 strains isolated from PBMCs from Cameroon was determined using the GHOST cell assay. Prediction, based on V3 sequences from matched plasma samples, was determined using bioinformatics algorithms and rules based on position 11/25 and net charge applied independently or combined according to Delobel's and Garrido's rules. Performance of genotypic methods was evaluated by comparing prediction generated with tropism assigned by the phenotypic assay.ResultsSpecificity for predicting R5-tropic virus was high, ranging from 83.7% to 97.7% depending on the genotypic methods used. Sensitivity for X4-tropic viruses was fairly low, ranging from 33.3% to 50%. In our study, overall, genotypic methods were less able to accurately predict X4-tropic virus belonging to subtype CRF02_AG. In addition, it was found that of the methods we used the Garrido rule has the highest sensitivity rate of over 50% with a specificity of 93%.ConclusionOur study demonstrated that overall, genotypic methods were less sensitive for accurate prediction of HIV-1 tropism in settings where diverse HIV-1 strains co-circulate. Our data suggest that further optimization of genotypic methods is needed and that larger studies to determine their utility for tropism prediction of diverse HIV-1 strains may be warranted.

Temporal increase in HIV-1 non-R5 tropism frequency among antiretroviral-naive patients from northern Poland.

IntroductionSequencing of the third hypervariable loop allows to identify genotype-based HIV tropism. R5-tropic viruses associated with early stages of infection are preferentially transmitted, while non-R5 HIV-1 tropism has been associated with severe immunodeficiency and lower lymphocyte CD4 nadir and may reflect delayed HIV diagnosis. In this study, we investigate the changes in tropism frequency from 2007 to 2013.Materials and MethodsStudy included 194 patients with confirmed HIV infection linked to care in 2007–2013. Baseline plasma samples from treatment naive patients were used for HIV-1 genotypic tropism assessment based on triplicate V3 loop sequencing. Non-R5 tropism prediction thresholds were assigned using a false positive rate (FPR) of 10% and 5.75% FPR and associated with clinical and laboratory data (age, gender, date of HIV diagnosis, route of transmission, CDC clinical category at diagnosis, pretreatment HIV viral load, baseline and nadir lymphocyte CD4 counts). For statistics, chi-square and Mann–Whitney U tests were used, time trends were examined using logistic regression (R statistical platform, v. 3.1.0) for binary variables and linear regression for continuous ones.ResultsOverall non-R5 tropism frequency for the 5.75% FPR was 15.5% and 27.8% for 10% FPR. Frequency of the non-R5 tropism predicted using 5.75% FPR increased significantly from 2007 (0%) to 2013 (25%) [OR: 1.44 (95% CI 1.14–1.86), p=0.003, rough slope +3.89%/year] (Figure 1a). With 10% FPR, the frequency changed from 7% (2007) to 33% (2013) [OR: 1.17 (95% CI 0.99–1.39), p=0.054, rough slope +3.0%/year] (Figure 1b). Baseline lymphocyte CD4 count and nadir, as well as pretreatment HIV-1 viral loads were stable over time of observation (r=0.014, p=0.84; r=0.13, p=0.085; r=0.016, p=0.83 for CD4 baseline, nadir and HIV load, respectively). Frequency of AIDS at HIV diagnosis increased from 21.4% in 2007 to 38.0% in 2013, however trend over time was insignificant [OR: 1.1 (95% CI 0.95–1.31), p=0.19]. Temporal trends for HIV transmission route, gender, non-B variant frequencies also were not significant.ConclusionsR5 tropism predominates among the treatment naive individuals but increase in the frequency of non-R5 tropic variants may limit clinical efficacy of the coreceptor inhibitors. Increased prevalence of non-R5 HIV-1 may be related to late care entry and higher number of AIDS diagnoses in the recent years.

GCUP: rapid GPU-based HIV-1 co-receptor usage prediction for next-generation sequencing.

Next-generation sequencing (NGS) has a large potential in HIV diagnostics, and genotypic prediction models have been developed and successfully tested in the recent years. However, albeit being highly accurate, these computational models lack computational efficiency to reach their full potential. In this study, we demonstrate the use of graphics processing units (GPUs) in combination with a computational prediction model for HIV tropism. Our new model named gCUP, parallelized and optimized for GPU, is highly accurate and can classify >175 000 sequences per second on an NVIDIA GeForce GTX 460. The computational efficiency of our new model is the next step to enable NGS technologies to reach clinical significance in HIV diagnostics. Moreover, our approach is not limited to HIV tropism prediction, but can also be easily adapted to other settings, e.g. drug resistance prediction. The source code can be downloaded at http://www.heiderlab.de d.heider@wz-straubing.de.

A simple structure-based model for the prediction of HIV-1 co-receptor tropism.

BackgroundHuman Immunodeficiency Virus 1 enters host cells through interaction of its V3 loop (which is part of the gp120 protein) with the host cell receptor CD4 and one of two co-receptors, namely CCR5 or CXCR4. Entry inhibitors binding the CCR5 co-receptor can prevent viral entry. As these drugs are only available for CCR5-using viruses, accurate prediction of this so-called co-receptor tropism is important in order to ensure an effective personalized therapy. With the development of next-generation sequencing technologies, it is now possible to sequence representative subpopulations of the viral quasispecies.ResultsHere we present T-CUP 2.0, a model for predicting co-receptor tropism. Based on our recently published T-CUP model, we developed a more accurate and even faster solution. Similarly to its predecessor, T-CUP 2.0 models co-receptor tropism using information of the electrostatic potential and hydrophobicity of V3-loops. However, extracting this information from a simplified structural vacuum-model leads to more accurate and faster predictions. The area-under-the-ROC-curve (AUC) achieved with T-CUP 2.0 on the training set is 0.968±0.005 in a leave-one-patient-out cross-validation. When applied to an independent dataset, T-CUP 2.0 has an improved prediction accuracy of around 3% when compared to the original T-CUP.ConclusionsWe found that it is possible to model co-receptor tropism in HIV-1 based on a simplified structure-based model of the V3 loop. In this way, genotypic prediction of co-receptor tropism is very accurate, fast and can be applied to large datasets derived from next-generation sequencing technologies. The reduced complexity of the electrostatic modeling makes T-CUP 2.0 independent from third-party software, making it easy to install and use.

Baseline HIV-1 tropism prediction in advanced immune suppressed patients: evidence of CXCR4 viruses in IDUs infected with recombinant forms

Until 2011, the main risk factor for the spread of HIV-1 in Romanian adult population was heterosexual contact. More recently, the number of HIV-1 new cases among IDUs significantly increased. This new subepidemic is characterized by circulation of particular forms of infective strains (CRF14_BG), high prevalence of HCV co-infections and infective endocarditis. Genotypic methods are currently used for testing viral tropism in HIV infected patients. Deep sequencing proved to have much higher sensitivity than population sequencing in detecting minority - CXCR4 tropic viruses. Previous studies suggested that the presence of CXCR4 phenotype at baseline is frequently associated with a faster disease progression. The aim of the study was to evaluate the viral tropism at the moment of HIV diagnostic in IDU patients. We have analyzed sequences from 19 IDUs that presented low CD4 counts (<200 cells/cmm) and/or CDC stage C when HIV-1 infection was diagnosed. They were compared with strains from 24 heterosexuals diagnosed at the same time with the IDUs were included in the study. RT PCR was performed to amplify the V3 loop. Population sequencing was done using BigDye chemistry and 3500 Genetic Analyzer. Deep-sequencing was performed on the GS Junior 454 sequencing platform and AVA software was used to analyze the output sequences. The tropism prediction was assessed by geno2pheno[coreceptor] bioinformatic algorithm and subtyping with REGA tool version 2.0. The IDU group was mainly infected with recombinant forms: CRF14_BG and recombinants between F1 and CRF14_BG (68.4%, 13/19); the heterosexuals had F1 subtype viruses (95.8%, 23/24). CXCR4 tropism was associated with IDUs and in particular with CRF14_BG (p=0.0027). All the CRF14_BG were X4 by population sequencing. Furthermore, when tested with deep sequencing the viral populations of CRF14_BG samples were exclusively X4 (no minority R5 populations). Dual tropic (CCR5 and CXCR4) populations were more frequent in F1 samples isolated from heterosexuals and predicted as X4 by population sequencing. We found concordance between the predictions of the two methods. In the heterosexual group both techniques predicted mainly CCR5 viruses. CXCR4 tropic CRF14_BG viruses were very common in IDUs at baseline. This may contribute to faster disease progression in this population than in heterosexuals infected with the F1 CCR5 tropic strains.

Genotypic Tropism Prediction from Paired Cell and Plasma Using Single and Replicate Sequences

HIV-1 tropism determination is necessary prior to CCR5 antagonist use as antiretroviral therapy. Genotypic prediction of coreceptor use is a practical alternative to phenotypic tests. Cell DNA and plasma RNA-based prediction has shown discordance in many studies. We evaluate paired cell and plasma either as single or replicate V3 sequences to assess prediction comparability. The HIV-1 partial env region was sequenced and tropism was predicted using geno2pheno and position-specific scoring matrices (PSSM). Nucleotide ambiguities at V3 were quantified and genetic distance (Protdist) was determined using BioEdit. Wilcoxon signed-rank test, t tests, and Spearman correlation were performed with Prism GraphPad5.0. Results are expressed as medians, with a level of significance of p<0.05, two tailed. Single (n=28) or replicate (n=26) paired cell/plasma sequences were obtained from 54 patients. Although the clonalfalse-positive rate (FPR) value from both compartments strongly correlated (r=0.86 p<0.0001), discordance in tropism prediction was observed in both singles and replicates using geno2pheno or PSSM. Applying clonalFPR(10%) 46% (25/54) were X4 tropic, with a plasma/cell discordance of 11% in singles and 23% in replicates. Genetic distance (p<0.0001) and clonalFPR value dispersion (p=0.003) were significantly higher among replicate sequences from cells. Discordance of viral tropism prediction is not uncommon and the use of replicates does not decrease its occurrence, but improves X4 sensitivity. Sequences from provirus had greater genetic distance and dispersion of clonalFPR values. This may suggest that DNA replicate assays may better represent the diversity of HIV-1 variants, but the clinical significance of these findings needs further evaluation.

Association of chemokine receptor gene variants with HIV-1 genotype predicted tropism.

As a switch from chemokine (C-C motif) receptor 5 [CCR5 (R5)] to chemokine (C-X-C motif) receptor 4 [CXCR4 (X4)] HIV-1 tropism is associated with symptomatic and AIDS stages of infection, while chemokine receptor gene variants modify the tempo of HIV disease progression, we aimed to analyse the association between pretreatment HIV-1 tropism and chemokine polymorphisms known to restrict disease progression. V3 genotype tropism prediction was performed in a group of 221 treatment-naïve patients, with subsequent CCR5 Δ32 (rs333), CCR2 V64I (rs1799864), CCR5 promoter (-627 C/T; rs1799988) and CX3CR1 V249I (rs3732378) genotyping performed in 206 patients. Alleles with a protective effect were assigned positive values while risk alleles were assigned negative values to calculate genetic scores. χ(2) tests, Mann-Whitney U-tests and logistic and linear regression models were used for statistical analyses. R5 tropism was found in 85.5% of patients (n = 189) using a false positive rate (FPR) of 5.75% and in 72.8% of patients (n = 161) using an FPR of 10%. A higher frequency of the 5.75% FPR predicted R5 tropism was associated with the CX3CR1 A allele (P = 0.027). Lower additive genetic scores were associated with an increased frequency of 5.75% FPR predicted R5 tropism (P = 0.0059), with the trend confirmed by logistic regression [odds ratio (OR) 0.5819; 95% confidence interval (CI) 0.3457-0.9795; P = 0.0416]. Viral load tended to increase with decreasing genetic score in the logistic regression analysis (slope = -0.127 ± 0.076; P = 0.095; r(2) = 0.161). The CX3CR1 A allele and lower genetic scores may restrict the switch of HIV-1 tropism from R5 to X4. This effect may be associated with the amount of co-receptor on the cell surface. Chemokine receptor gene polymorphisms influence both disease progression and tropism variability.

Association of host tropism of Middle East syndrome coronavirus with the amino acid structure of host cell receptor dipeptidyl peptidase 4.

The Middle East syndrome coronavirus (MERS-CoV) is a recently emerging betacoronavirus with high fatality. Recently, dipeptidyle peptidase (CD26, DPP4) was identified as the host cell receptor for MERS-CoV. Interestingly, despite of common presence of DPP4 receptors the binding and infection of various cells shows imminent variability. In this report, we provide a tool for prediction of the host tropism of the virus based on the host receptor binding interface. We found out that, in the binding of MERS-CoV to cells the amino acid residues in lancets 4 and 5 of DPP4 receptor, namely K267, Q286, T288, R317, R336, Q344 A291, L294, and I295 are involved. Changes in these residues correspond to profound decrease in virus binding to cells. The nine residues at the interface between the virus spikes and the lancets 4 and 5 of host DPP4 can be used as a predictive tool for the host tropism and virus affinity to host cell receptors.

Viral Tropism and Antiretroviral Drug Resistance in HIV-1 Subtype C-Infected Patients Failing Highly Active Antiretroviral Therapy in Johannesburg, South Africa

Reports show that up to 30% of antiretroviral drug-naive patients in Johannesburg have CXCR4-utilizing HIV-1 subtype C. We assessed whether HIV-1 subtype C-infected individuals failing highly active antiretroviral therapy (HAART) have a higher proportion of CXCR4-utilizing viruses compared to antiretroviral drug-naive patients. The V3 loop was sequenced from plasma from 100 randomly selected HAART-failing patients, and tropism was established using predictive algorithms. All patients harbored HIV-1 subtype C with at least one antiretroviral drug resistance mutation. Viral tropism prediction in individuals failing HAART revealed similar proportions (29%) of X4-utilizing viruses compared to antiretroviral drug-naive patients (30%). Findings are in contrast to reports from Durban in which 60% of HAART-failing subjects harbored X4/dual/mixed-tropic viruses. Despite differences in proportions of X4-tropism within South Africa, the high proportion of thymidine analogue mutations (TAMs) and CXCR4-utilizing HIV-1 highlights the need for intensified monitoring of HAART patients and the predicament of diminishing drug options, including CCR5 antagonists, for patients failing therapy.

Association of X4 tropism with disease progression in antiretroviral-treated children and adolescents living with HIV/AIDS in São Paulo, Brazil

Management of children with HIV/AIDS is specially challenging. Age-related issues do not allow for direct transposition of adult observations to this population. CXCR4 tropism has been associated with disease progression in adults. The geno2pheno web-base is a friendly tool to predict viral tropism on envelope V3 sequences, generating a false positive rate for a CXCR4 prediction. We evaluated the association of HIV-1 tropism prediction with clinical and laboratory outcome of 73 children with HIV/AIDS in São Paulo, Brazil. The CXCR4 tropism was strongly associated with a lower (nadir) CD4 documented during follow-up (p<0.0001) and with disease severity (clinical event and/or CD4 below 200cells/mm3) at the last observation, using commonly applied clinical cutoffs, such as 10%FPRclonal (p=0.001). When variables obtained during follow-up are included, both treatment adherence and viral tropism show a significant association with disease severity. As for viremia suppression, 30% (22/73) were undetectable at the last observation, with only adherence strongly associated with suppression after adjustment. The study brings further support to the notion that antiretroviral treatment adherence is pivotal to management of HIV disease, but suggests that tropism prediction may provide an additional prognostic marker to monitor HIV disease in children.

Frequency and Predictors of HIV-1 Co-receptor Switch in Treatment Naive Patients

BackgroundDetermination of HIV-1 co-receptor use is a necessity before initiation of a CCR5 antagonist but the longevity of a CCR5-use prediction remains unknown.MethodsGenotypic co-receptor tropism determination was performed in 225 newly diagnosed individuals consulting an AIDS Reference Centre. Samples were collected at diagnosis and at initiation of antiretroviral therapy or just before closure of the study for patients who did not initiate therapy. For individuals with a discordant tropism prediction on the two longitudinal samples, analysis of intermediate samples and single genome sequencing of proviral DNA was performed to confirm the tropism switch. Deep sequencing was done to identify minor CXCR4 or CCR5-using populations in the initial sample.ResultsOverall, tropism switches were rare (7.6%). Only a geno2pheno false positive rate of <50% at baseline was retained as predictive for a subsequent switch from CCR5-use only to predicted CXCR4-use. Minor CXCR4-using virus populations were detected in the first sample of 9 of the 14 R5-to-X4 switchers but the subsequent outgrowth of these minor populations was documented in only 3.ConclusionsWith the current guidelines for treatment initiation at CD4+ T cell counts of <500 cells/mm3, co-receptor switch between diagnosis and starting antiretroviral therapy is rare. Patients with R5 viruses and a geno2pheno FPR of <50% are more prone to subsequent co-receptor switch than patients with an FPR of >50% and will need repeat tropism testing if initiation of maraviroc is considered and previous testing dates from more than a year before.

HIV-1 tropism: a comparison between RNA and proviral DNA in routine clinical samples from Chilean patients

BackgroundHIV in Chile has a notification rate of 0.01%. Coreceptor antagonists are a family of antiretroviral drugs that are used with the prior knowledge of patients HIV-1 tropism. Viral RNA-based tropism detection requires a plasma viral load ≥1000 copies/mL, while proviral DNA-based detection can be performed regardless of plasma viral load. This test is useful in patients with low or undetectable viral loads and would benefit with a proper therapy. The aim of this study was to determine the correlation between HIV RNA and proviral genotypic DNA tropism tests.FindingsForty three Chilean patients were examined using population-based V3 sequencing, and a geno2pheno false-positive rate (FPR) cutoff values of 5, 5.75, 10 and 20%. With cutoff 5.75% a concordance of 88.4% in tropism prediction was found after a simultaneous comparison between HIV tropism assessment by RNA and DNA. In total, five discrepancies (11.6%) were found, 3 patients were RNA-R5/DNA-X4 and two were RNA-X4/DNA-R5. Proviral DNA enabled the prediction of tropism in patients with a low or undetectable viral load. For cutoff 5 and 5.75% genotypic testing using proviral DNA showed a similar sensitivity for X4 as RNA. We found that the highest sensitivity for detecting the X4 strain occurred with proviral DNA and cutoff of 10 and 20%. Viral loads were higher among X4 strain carriers than among R5 strain carriers (p < 0.05).ConclusionsA high degree of concordance was found between tropism testing with RNA and testing with proviral DNA. Our results suggest that proviral DNA-based genotypic tropism testing is a useful option for patients with low or undetectable viral load who require a different therapy.

Genotypic testing on HIV-1 DNA as a tool to assess HIV-1 co-receptor usage in clinical practice: results from the DIVA study group

PurposeWe have developed a sequencing assay for determining the usage of the genotypic HIV-1 co-receptor using peripheral blood mononuclear cell (PBMC) DNA in virologically suppressed HIV-1 infected patients. Our specific aims were to (1) evaluate the efficiency of V3 sequences in B versus non-B subtypes, (2) compare the efficiency of V3 sequences and tropism prediction using whole blood and PBMCs for DNA extraction, (3) compare the efficiency of V3 sequences and tropism prediction using a single versus a triplicate round of amplification.ResultsThe overall rate of successful V3 sequences ranged from 100 % in samples with >3,000 copies HIV-1 DNA/106 PBMCs to 60 % in samples with <100 copies total HIV-1 DNA /106 PBMCs. Analysis of 143 paired PBMCs and whole-blood samples showed successful V3 sequences rates of 77.6 % for PBMCs and 83.9 % for whole blood. These rates are in agreement with the tropism prediction obtained using the geno2pheno co-receptor algorithm, namely, 92.1 % with a false-positive rate (FPR) of 10 or 20 % and of 96.5 % with an FPR of 5.75 %. The agreement between tropism prediction values using single versus triplicate amplification was 98.2 % (56/57) of patients using an FPR of 20 % and 92.9 % (53/57) using an FPR of 10 or 5.75 %. For 63.0 % (36/57) of patients, the FPR obtained via the single amplification procedure was superimposable to all three FPRs obtained by triplicate amplification.ConclusionsOur results show the feasibility and consistency of genotypic testing on HIV-1 DNA tropism, supporting its possible use for selecting patients with suppressed plasma HIV-1 RNA as candidates for CCR5-antagonist treatment. The high agreement between tropism prediction by single and triple amplification does not support the use of triplicate amplification in clinical practice.

Arginine insertion and loss of N-linked glycosylation site in HIV-1 envelope V3 region confer CXCR4-tropism

The third variable region (V3) of HIV-1 envelope glycoprotein gp120 plays a key role in determination of viral coreceptor usage (tropism). However, which combinations of mutations in V3 confer a tropism shift is still unclear. A unique pattern of mutations in antiretroviral therapy-naive HIV-1 patient was observed associated with the HIV-1 tropism shift CCR5 to CXCR4. The insertion of arginine at position 11 and the loss of the N-linked glycosylation site were indispensable for acquiring pure CXCR4-tropism, which were confirmed by cell-cell fusion assay and phenotype analysis of recombinant HIV-1 variants. The same pattern of mutations in V3 and the associated tropism shift were identified in two of 53 other patients (3.8%) with CD4+ cell count <200/mm3. The combination of arginine insertion and loss of N-linked glycosylation site usually confers CXCR4-tropism. Awareness of this rule will help to confirm the tropism prediction from V3 sequences by conventional rules.

A CASE-BASED REASONING SYSTEM FOR GENOTYPIC PREDICTION OF HIV-1 CO-RECEPTOR TROPISM

Accurate co-receptor tropism (CRT) determination is critical for making treatment decisions in HIV management. We created a genotypic tropism prediction tool by utilizing the case-based reasoning (CBR) technique that attempts to solve new problems through applying the solution from similar past problems. V3 loop sequences from 732 clinical samples with diverse characteristics were used to build a case library. Additional sequence and molecular properties of the V3 loop were examined and used for similarity assessment. A similarity metric was defined based on each attribute's frequency in the CXCR4-using viruses. We implemented three other genotype-based tropism predictors, support vector machines (SVM), position specific scoring matrices (PSSM), and the 11/25 rule, and evaluated their performance as the ability to predict CRT compared to Monogram's enhanced sensitivity Trofile(®) assay (ESTA). Overall concordance of the CBR based tropism prediction algorithm was 81%, as compared to ESTA. Sensitivity to detect CXCR4 usage was 90% and specificity was at 73%. In comparison, sensitivity of the SVM, PSSM, and the 11/25 rule were 85%, 81%, and 36% respectively while achieving a specificity of 90% by SVM, 75% by PSSM, and 97% by the 11/25 rule. When we evaluated these predictors in an unseen dataset, higher sensitivity was achieved by the CBR algorithm (87%), compared to SVM (82%), PSSM (76%), and the 11/25 rule (33%), while maintaining similar level of specificity. Overall this study suggests that CBR can be utilized as a genotypic tropism prediction tool, and can achieve improved performance in independent datasets compared to model or rule based methods.