Insights to HIV-1 coreceptor usage by estimating HLA adaptation with Bayesian generalized linear mixed models.

The mechanisms triggering the human immunodeficiency virus type I (HIV-1) to switch the coreceptor usage from CCR5 to CXCR4 during the course of infection are not entirely understood. While low CD4+ T cell counts are associated with CXCR4 usage, a predominance of CXCR4 usage with still high CD4+ T cell counts remains puzzling. Here, we explore the hypothesis that viral adaptation to the human leukocyte antigen (HLA) complex, especially to the HLA class II alleles, contributes to the coreceptor switch. To this end, we sequence the viral gag and env protein with corresponding HLA class I and II alleles of a new cohort of 312 treatment-naive, subtype C, chronically-infected HIV-1 patients from South Africa. To estimate HLA adaptation, we develop a novel computational approach using Bayesian generalized linear mixed models (GLMMs). Our model allows to consider the entire HLA repertoire without restricting the model to pre-learned HLA-polymorphisms. In addition, we correct for phylogenetic relatedness of the viruses within the model itself to account for founder effects. Using our model, we observe that CXCR4-using variants are more adapted than CCR5-using variants (p-value = 1.34e-2). Additionally, adapted CCR5-using variants have a significantly lower predicted false positive rate (FPR) by the geno2pheno[coreceptor] tool compared to the non-adapted CCR5-using variants (p-value = 2.21e-2), where a low FPR is associated with CXCR4 usage. Consequently, estimating HLA adaptation can be an asset in predicting not only coreceptor usage, but also an approaching coreceptor switch in CCR5-using variants. We propose the usage of Bayesian GLMMs for modeling virus-host adaptation in general.

Rapid Selection of Sotrovimab Escape Variants in Severe Acute Respiratory Syndrome Coronavirus 2 Omicron-Infected Immunocompromised Patients.

BACKGROUND: Monoclonal antibodies (mAbs) that target severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are predominantly less effective against Omicron variants. Immunocompromised patients often experience prolonged viral shedding, resulting in an increased risk of viral escape. METHODS: In an observational, prospective cohort, 57 patients infected with Omicron variants who received sotrovimab alone or in combination with remdesivir were followed. The study end points were a decrease in SARS-CoV-2 RNA <106 copies/mL in nasopharyngeal swabs at day 21 and the emergence of escape mutations at days 7, 14, and 21 after sotrovimab administration. All SARS-CoV-2 samples were analyzed using whole-genome sequencing. Individual variants within the quasispecies were subsequently quantified and further characterized using a pseudovirus neutralization assay. RESULTS: The majority of patients (43 of 57, 75.4%) were immunodeficient, predominantly due to immunosuppression after organ transplantation or hematologic malignancies. Infections by Omicron/BA.1 comprised 82.5%, while 17.5% were infected by Omicron/BA.2. Twenty-one days after sotrovimab administration, 12 of 43 (27.9%) immunodeficient patients had prolonged viral shedding compared with 1 of 14 (7.1%) immunocompetent patients (P = .011). Viral spike protein mutations, some specific for Omicron (e.g., P337S and/or E340D/V), emerged in 14 of 43 (32.6%) immunodeficient patients, substantially reducing sensitivity to sotrovimab in a pseudovirus neutralization assay. Combination therapy with remdesivir significantly reduced emergence of escape variants. CONCLUSIONS: Immunocompromised patients face a considerable risk of prolonged viral shedding and emergence of escape mutations after early therapy with sotrovimab. These findings underscore the importance of careful monitoring and the need for dedicated clinical trials in this patient population.

Simultaneous analysis of seven 16S rRNA hypervariable gene regions increases efficiency in marine bacterial diversity detection.

Environmental DNA sequencing is the gold standard to reveal microbial community structures. In most applications, a one-fragment PCR approach is applied to amplify a taxonomic marker gene, usually a hypervariable region of the 16S rRNA gene. We used a new reverse complement (RC)-PCR-based assay that amplifies seven out of the nine hypervariable regions of the 16S rRNA gene, to interrogate bacterial communities in sediment samples collected from different coastal marine sites with an impact gradient. In parallel, we employed a traditional one-fragment analysis of the hypervariable V3-V4 region to investigate whether the RC-PCR reveals more of the 'unseen' diversity obtained by the one-fragment approach. As a benchmark for the full deck of diversity, we subjected the samples to PCR-free metagenomic sequencing. None of the two PCR-based approaches recorded the full taxonomic repertoire obtained from the metagenomics datasets. However, the RC-PCR approach detected 2.8 times more bacterial genera compared to the near-saturation sequenced V3-V4 samples. RC-PCR is an ideal compromise between the standard one-fragment approach and metagenomics sequencing and may guide future environmental sequencing studies, in which bacterial diversity is a central subject.

Characterization of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection Clusters Based on Integrated Genomic Surveillance, Outbreak Analysis and Contact Tracing in an Urban Setting.

BACKGROUND: Tracing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission chains is still a major challenge for public health authorities, when incidental contacts are not recalled or are not perceived as potential risk contacts. Viral sequencing can address key questions about SARS-CoV-2 evolution and may support reconstruction of viral transmission networks by integration of molecular epidemiology into classical contact tracing. METHODS: In collaboration with local public health authorities, we set up an integrated system of genomic surveillance in an urban setting, combining a) viral surveillance sequencing, b) genetically based identification of infection clusters in the population, c) integration of public health authority contact tracing data, and d) a user-friendly dashboard application as a central data analysis platform. RESULTS: Application of the integrated system from August to December 2020 enabled a characterization of viral population structure, analysis of 4 outbreaks at a maximum care hospital, and genetically based identification of 5 putative population infection clusters, all of which were confirmed by contact tracing. The system contributed to the development of improved hospital infection control and prevention measures and enabled the identification of previously unrecognized transmission chains, involving a martial arts gym and establishing a link between the hospital to the local population. CONCLUSIONS: Integrated systems of genomic surveillance could contribute to the monitoring and, potentially, improved management of SARS-CoV-2 transmission in the population.

geno2pheno[ngs-freq]: a genotypic interpretation system for identifying viral drug resistance using next-generation sequencing data.

Identifying resistance to antiretroviral drugs is crucial for ensuring the successful treatment of patients infected with viruses such as human immunodeficiency virus (HIV) or hepatitis C virus (HCV). In contrast to Sanger sequencing, next-generation sequencing (NGS) can detect resistance mutations in minority populations. Thus, genotypic resistance testing based on NGS data can offer novel, treatment-relevant insights. Since existing web services for analyzing resistance in NGS samples are subject to long processing times and follow strictly rules-based approaches, we developed geno2pheno[ngs-freq], a web service for rapidly identifying drug resistance in HIV-1 and HCV samples. By relying on frequency files that provide the read counts of nucleotides or codons along a viral genome, the time-intensive step of processing raw NGS data is eliminated. Once a frequency file has been uploaded, consensus sequences are generated for a set of user-defined prevalence cutoffs, such that the constructed sequences contain only those nucleotides whose codon prevalence exceeds a given cutoff. After locally aligning the sequences to a set of references, resistance is predicted using the well-established approaches of geno2pheno[resistance] and geno2pheno[hcv]. geno2pheno[ngs-freq] can assist clinical decision making by enabling users to explore resistance in viral populations with different abundances and is freely available at http://ngs.geno2pheno.org.

Eliminating Hepatitis C Virus Among Human Immunodeficiency Virus-Infected Men Who Have Sex With Men in Berlin: A Modeling Analysis.

BACKGROUND: Despite high hepatitis C virus (HCV) treatment rates, HCV incidence among human immunodeficiency virus (HIV)-infected men who have sex with men (HIV-infected MSM) in Germany rose before HCV direct-acting antivirals (DAAs). We model what intervention can achieve the World Health Organization (WHO) elimination target of an 80% reduction in HCV incidence by 2030 among HIV-infected MSM in Berlin. METHODS: An HCV transmission model among HIV-diagnosed MSM was calibrated to Berlin (rising HCV incidence and high rates of HCV testing and treatment). We modeled the HCV incidence among HIV-diagnosed MSM in Berlin until 2030 (relative to 2015 WHO baseline) under scenarios of DAA scale-up with or without behavior change (among HIV-diagnosed MSM and/or all MSM). RESULTS: Continuing current treatment rates will marginally reduce the HCV incidence among HIV-diagnosed MSM in Berlin by 2030. Scaling up DAA treatment rates, beginning in 2018, to 100% of newly diagnosed HCV infections within 3 months of diagnosis and 25% each year of previously diagnosed and untreated HCV infections could reduce the HCV incidence by 61% (95% confidence interval, 55.4%-66.7%) by 2030. The WHO target would likely be achieved by combining DAA scale-up with a 40% reduction in HCV transmission among HIV-diagnosed MSM and a 20% reduction among HIV-undiagnosed or HIV-uninfected MSM. DISCUSSION: HCV elimination among HIV-infected MSM in Berlin likely requires combining DAA scale-up with moderately effective behavioral interventions to reduce risk among all MSM.

Rapid Rebound of a Preexisting CXCR4-tropic Human Immunodeficiency Virus Variant After Allogeneic Transplantation With CCR5 Δ32 Homozygous Stem Cells.

Allogeneic stem cell transplantation (alloSCT) of homozygous CCR5 Δ32 stem cells once resulted in the cure of human immunodeficiency virus (HIV) infection. We have recently reported a viral breakthrough in a similar setting. Here, we demonstrate that the rapid rebound after alloSCT was related to a highly replicative CXCR4-tropic HIV variant, which could already be detected before alloSCT.

Impact of the HIV-1 genetic background and HIV-1 population size on the evolution of raltegravir resistance.

BACKGROUND: Emergence of resistance against integrase inhibitor raltegravir in human immunodeficiency virus type 1 (HIV-1) patients is generally associated with selection of one of three signature mutations: Y143C/R, Q148K/H/R or N155H, representing three distinct resistance pathways. The mechanisms that drive selection of a specific pathway are still poorly understood. We investigated the impact of the HIV-1 genetic background and population dynamics on the emergence of raltegravir resistance. Using deep sequencing we analyzed the integrase coding sequence (CDS) in longitudinal samples from five patients who initiated raltegravir plus optimized background therapy at viral loads > 5000 copies/ml. To investigate the role of the HIV-1 genetic background we created recombinant viruses containing the viral integrase coding region from pre-raltegravir samples from two patients in whom raltegravir resistance developed through different pathways. The in vitro selections performed with these recombinant viruses were designed to mimic natural population bottlenecks. RESULTS: Deep sequencing analysis of the viral integrase CDS revealed that the virological response to raltegravir containing therapy inversely correlated with the relative amount of unique sequence variants that emerged suggesting diversifying selection during drug pressure. In 4/5 patients multiple signature mutations representing different resistance pathways were observed. Interestingly, the resistant population can consist of a single resistant variant that completely dominates the population but also of multiple variants from different resistance pathways that coexist in the viral population. We also found evidence for increased diversification after stronger bottlenecks. In vitro selections with low viral titers, mimicking population bottlenecks, revealed that both recombinant viruses and HXB2 reference virus were able to select mutations from different resistance pathways, although typically only one resistance pathway emerged in each individual culture. CONCLUSIONS: The generation of a specific raltegravir resistant variant is not predisposed in the genetic background of the viral integrase CDS. Typically, in the early phases of therapy failure the sequence space is explored and multiple resistance pathways emerge and then compete for dominance which frequently results in a switch of the dominant population over time towards the fittest variant or even multiple variants of similar fitness that can coexist in the viral population.

Therapeutic Immune Recovery and Reduction of CXCR4-Tropic HIV-1.

BACKGROUND: In the absence of therapy, CXCR4 (X4)-tropic human immunodeficiency virus type 1 (HIV-1) increases over time, associated with accelerated disease progression. In contrast, the majority of patients receiving long-term combination antiretroviral therapy (cART) present with CCR5 (R5)-tropic HIV-1 variants. It is unclear whether cART itself mediates the reduction of X4-tropic HIV-1. The current study aimed at assessing the tropism of viral integrates in patients' blood during fully suppressive cART. METHODS: The relative frequencies of X4-tropic proviral HIV-1 variants were determined by means of next-generation sequencing (False Positive Rate (FPR), 3.5%; R5- or X4 tropic variants occurring at less than 2% of the total virus population) for 35 treated patients in the Swiss HIV Cohort Study and followed longitudinally over time. Full viral suppression and a continuous CD4 T-cell recovery during cART were documented for all patients. Viral phylogenetic changes and sequence evolution were analyzed. RESULTS: The majority of patients (80%) experienced no frequency increase in X4-tropic proviruses during therapy. Although some proviral sequence evolution was demonstrable in >50% of these patients during therapy, this growing viral diversity was in no case paralleled by the emergence or expansion of X4-tropic provirus variants. In the remaining 20% of patients, the documented expansion of X4-tropic provirus was based on the outgrowth of single viral variants from minority populations already present before therapy initiation. CONCLUSION: Our study demonstrates that X4-tropic HIV sharply declines in most patients during successful therapy, which indicates a preferential tropism-dependent provirus elimination in the immunocompetent host. The recently implemented World Health Organization strategies of immediate therapy initiation are fully in line with this gradual loss of X4 tropism during therapy. Moreover, the early use of coreceptor antagonists against the remaining CCR5-tropic viruses may be indicated.

Revealing viral and cellular dynamics of HIV-1 at the single-cell level during early treatment periods.

While combination therapy completely suppresses HIV-1 replication in blood, functional virus persists in CD4+ T cell subsets in non-peripheral compartments that are not easily accessible. To fill this gap, we investigated tissue-homing properties of cells that transiently appear in the circulating blood. Through cell separation and in vitro stimulation, the HIV-1 "Gag and Envelope reactivation co-detection assay" (GERDA) enables sensitive detection of Gag+/Env+ protein-expressing cells down to about one cell per million using flow cytometry. By associating GERDA with proviral DNA and polyA-RNA transcripts, we corroborate the presence and functionality of HIV-1 in critical body compartments utilizing t-distributed stochastic neighbor embedding (tSNE) and density-based spatial clustering of applications with noise (DBSCAN) clustering with low viral activity in circulating cells early after diagnosis. We demonstrate transcriptional HIV-1 reactivation at any time, potentially giving rise to intact, infectious particles. With single-cell level resolution, GERDA attributes virus production to lymph-node-homing cells with central memory T cells (TCMs) as main players, critical for HIV-1 reservoir eradication.

APOBEC3G/F as one possible driving force for co-receptor switch of the human immunodeficiency virus-1.

Human immunodeficiency virus-1 tropism highly correlates with the amino acid (aa) composition of the third hypervariable region (V3) of gp120. A shift towards more positively charged aa is seen when binding to CXCR4 compared with CCR5 (X4 vs. R5 strains), especially positions 11 and 25 (11/25-rule) predicting X4 viruses in the presence of positively charged residues. At nucleotide levels, negatively or uncharged aa, e.g., aspartic and glutamic acid and glycine, which are encoded by the triplets GAN (guanine-adenosine-any nucleotide) or GGN are found more often in R5 strains. Positively charged aa such as arginine and lysine encoded by AAR or AGR (CGN) (R means A or G) are seen more frequently in X4 strains suggesting our hypothesis that a switch from R5 to X4 strains occurs via a G-to-A mutation. 1527 V3 sequences from three independent data sets of X4 and R5 strains were analysed with respect to their triplet composition. A higher number of G-containing triplets was found in R5 viruses, whereas X4 strains displayed a higher content of A-comprising triplets. These findings also support our hypothesis that G-to-A mutations are leading to the co-receptor switch from R5 to X4 strains. Causative agents for G-to-A mutations are the deaminases APOBEC3F and APOBEC3G. We therefore hypothesize that these proteins are one driving force facilitating the appearance of X4 variants. G-to-A mutations can lead to a switch from negatively to positively charged aa and a respective alteration of the net charge of gp120 resulting in a change of co-receptor usage.

Geno2pheno[454]: a Web server for the prediction of HIV-1 coreceptor usage from next-generation sequencing data.

Inferring HIV-1 coreceptor usage from a genotype is becoming more and more important for the appropriate treatment of long-term patients. While results are already encouraging where standard bulk-nucleic acid sequencing methods are used, they are limited with respect to the detection of minor variants. In contrast, next-generation sequencing methods (ultradeep sequencing, pyrosequencing) are capable of sequencing virus quasispecies at very low quantities. However, as well as being very expensive, these methods generate vast amounts of data such that sequence analysis has to be automated by computer assistance. Here, we describe the geno2pheno[454] system which handles all processing and prediction steps involved in the prediction of coreceptor usage from massively parallel sequencing data. The system is split into a JAVA preprocessor which is run locally on the client side and a Web server which generates the prediction results. Predictions are based on the same prediction method as used in the geno2pheno[coreceptor] tool.

HIV-GRADE: a publicly available, rules-based drug resistance interpretation algorithm integrating bioinformatic knowledge.

BACKGROUND: Genotypic drug resistance testing provides essential information for guiding treatment in HIV-infected patients. It may either be used for identifying patients with transmitted drug resistance or to clarify reasons for treatment failure and to check for remaining treatment options. While different approaches for the interpretation of HIV sequence information are already available, no other available rules-based systems specifically have looked into the effects of combinations of drugs. HIV-GRADE (Genotypischer Resistenz Algorithmus Deutschland) was planned as a countrywide approach to establish standardized drug resistance interpretation in Germany and also to introduce rules for estimating the influence of mutations on drug combinations. The rules for HIV-GRADE are taken from the literature, clinical follow-up data and from a bioinformatics-driven interpretation system (geno2pheno([resistance])). HIV-GRADE presents the option of seeing the rules and results of other drug resistance algorithms for a given sequence simultaneously. METHODS: The HIV-GRADE rules-based interpretation system was developed by the members of the HIV-GRADE registered society. For continuous updates, this expert committee meets twice a year to analyze data from various sources. Besides data from clinical studies and the centers involved, published correlations for mutations with drug resistance and genotype-phenotype correlation data information from the bioinformatic models of geno2pheno are used to generate the rules for the HIV-GRADE interpretation system. A freely available online tool was developed on the basis of the Stanford HIVdb rules interpretation tool using the algorithm specification interface. Clinical validation of the interpretation system was performed on the data of treatment episodes consisting of sequence information, antiretroviral treatment and viral load, before and 3 months after treatment change. Data were analyzed using multiple linear regression. RESULTS: As the developed online tool allows easy comparison of different drug resistance interpretation systems, coefficients of determination (R(2)) were compared for the freely available rules-based systems. HIV-GRADE (R(2) = 0.40), Stanford HIVdb (R(2) = 0.40), REGA algorithm (R(2) = 0.36) and ANRS (R(2) = 0.35) had a very similar performance using this multiple linear regression model. CONCLUSION: The performance of HIV-GRADE is comparable to alternative rules-based interpretation systems. While there is still room for improvement, HIV-GRADE has been made publicly available to allow access to our approach regarding the interpretation of resistance against single drugs and drug combinations.

Deep sequencing to infer HIV-1 co-receptor usage: application to three clinical trials of maraviroc in treatment-experienced patients.

BACKGROUND: The Maraviroc versus Optimized Therapy in Viremic Antiretroviral Treatment-Experienced Patients (MOTIVATE) studies compared maraviroc versus placebo in treatment-experienced patients with CCR5-using (R5) human immunodeficiency virus type 1 (HIV-1), screened using the original Trofile assay. A subset with non-R5 HIV infection entered the A4001029 trial. We retrospectively examined the performance of a genotypic tropism assay based on deep sequencing of the HIV env V3 loop in predicting virologic response to maraviroc in these trials. METHODS: V3 amplicons were prepared from 1827 screening plasma samples and sequenced on a Roche/454 GS-FLX to a depth of >3000 sequences/sample. Samples were considered non-R5 if ≥2% of their viral population scored greater than or equal to -4.75 or ≤3.5 using the PSSM(x4/R5) or geno2pheno algorithms, respectively. RESULTS: Deep sequencing identified more than twice as many maraviroc recipients as having non-R5 HIV, compared with the original Trofile. With use of genotyping, we determined that 49% of maraviroc recipients with R5 HIV at screening had a week 48 viral load <50 copies/mL versus 26% of recipients with non-R5. Corresponding percentages were 46% and 23% with screening by Trofile. In cases in which screening assays differed, median week 8 log10 copies/mL viral load decrease favored 454. Other parameters predicted by genotyping included likelihood of changing to non-R5 tropism. CONCLUSIONS: This large study establishes deep V3 sequencing as a promising tool for identifying treatment-experienced individuals who could benefit from CCR5-antagonist-containing regimens.

Deep V3 sequencing for HIV type 1 tropism in treatment-naive patients: a reanalysis of the MERIT trial of maraviroc.

BACKGROUND: Deep sequencing is a highly sensitive technique that can detect and quantify the proportion of non-R5 human immunodeficiency virus (HIV) variants, including small minorities, that may emerge and cause virologic failure in patients who receive maraviroc-containing regimens. We retrospectively tested the ability of deep sequencing to predict response to a maraviroc-containing regimen in the Maraviroc versus Efavirenz in Treatment-Naive Patients (MERIT) trial. Results were compared with those obtained using the Enhanced Sensitivity Trofile Assay (ESTA), which is widely used in clinical practice. METHODS: Screening plasma samples from treatment-naive patients who received maraviroc and efavirenz in the MERIT trial were assessed. Samples were extracted, and the V3 region of HIV type 1 glycoprotein 120 was amplified in triplicate and combined in equal quantities before sequencing on a Roche/454 Genome Sequencer-FLX (n = 859). Tropism was inferred from third variable (V3) sequences, with samples classified as non-R5 if ≥2% of the viral population scored ≤3.5 using geno2pheno. RESULTS: Deep sequencing distinguished between responders and nonresponders to maraviroc. Among patients identified as having R5-HIV by deep sequencing, 67% of maraviroc recipients and 69% of efavirenz recipients had a plasma viral load <50 copies/mL at week 48, similar to the ESTA results: 68% and 68%, respectively. CONCLUSIONS: Reanalysis of the MERIT trial using deep V3 loop sequencing indicates that, had patients originally been screened using this method, the maraviroc arm would have likely been found to be noninferior to the efavirenz arm.

High concordance between the position-specific scoring matrix and geno2pheno algorithms for genotypic interpretation of HIV-1 tropism: V3 length as the major cause of disagreement.

The agreement between the position-specific scoring matrix (PSSM) and geno2pheno as tools for genotypic interpretation of HIV-1 tropism using 800 clinical specimens was assessed. There was an overall concordance of 88%. Disagreement was found mostly in specimens with short V3 lengths (<35 amino acids). Thus, consideration of V3 lengths should improve the predictability of HIV-1 tropism using genotypic algorithms.

HIV-1 mutational pathways under multidrug therapy.

BACKGROUND: Genotype-derived drug resistance profiles are a valuable asset in HIV-1 therapy decisions. Therapy decisions could be further improved, both in terms of predicting length of current therapy success and in preserving followup therapy options, through better knowledge of mutational pathways- here defined as specific locations on the viral genome which, when mutant, alter the risk that additional specific mutations arise. We limit the search to locations in the reverse transcriptase region of the HIV-1 genome which host resistance mutations to nucleoside (NRTI) and non-nucleoside (NNRTI) reverse transcriptase inhibitors (as listed in the 2008 International AIDS Society report), or which were mutant at therapy start in 5% or more of the therapies studied. METHODS: A Cox proportional hazards model was fit to each location with the hazard of a mutation at that location during therapy proportional to the presence/absence of mutations at the remaining locations at therapy start. A pathway from preexisting to occurring mutation was indicated if the covariate was both selected as important via smoothly clipped absolute deviation (a form of regularized regression) and had a small p-value. The Cox model also allowed controlling for non-genetic parameters and potential nuisance factors such as viral resistance and number of previous therapies. Results were based on 1981 therapies given to 1495 distinct patients drawn from the EuResist database. RESULTS: The strongest influence on the hazard of developing NRTI resistance was having more than four previous therapies, not any one existing resistance mutation. Known NRTI resistance pathways were shown, and previously speculated inhibition between the thymidine analog pathways was evidenced. Evidence was found for a number of specific pathways between NRTI and NNRTI resistance sites. A number of common mutations were shown to increase the hazard of developing both NRTI and NNRTI resistance. Viral resistance to the therapy compounds did not materially effect the hazard of mutation in our model. CONCLUSIONS: The accuracy of therapy outcome prediction tools may be increased by including the number of previous treatments, and by considering locations in the HIV genome which increase the hazard of developing resistance mutations.

Genotypic tropism testing by massively parallel sequencing: qualitative and quantitative analysis.

BACKGROUND: Inferring viral tropism from genotype is a fast and inexpensive alternative to phenotypic testing. While being highly predictive when performed on clonal samples, sensitivity of predicting CXCR4-using (X4) variants drops substantially in clinical isolates. This is mainly attributed to minor variants not detected by standard bulk-sequencing. Massively parallel sequencing (MPS) detects single clones thereby being much more sensitive. Using this technology we wanted to improve genotypic prediction of coreceptor usage. METHODS: Plasma samples from 55 antiretroviral-treated patients tested for coreceptor usage with the Monogram Trofile Assay were sequenced with standard population-based approaches. Fourteen of these samples were selected for further analysis with MPS. Tropism was predicted from each sequence with geno2pheno[coreceptor]. RESULTS: Prediction based on bulk-sequencing yielded 59.1% sensitivity and 90.9% specificity compared to the trofile assay. With MPS, 7600 reads were generated on average per isolate. Minorities of sequences with high confidence in CXCR4-usage were found in all samples, irrespective of phenotype. When using the default false-positive-rate of geno2pheno[coreceptor] (10%), and defining a minority cutoff of 5%, the results were concordant in all but one isolate. CONCLUSIONS: The combination of MPS and coreceptor usage prediction results in a fast and accurate alternative to phenotypic assays. The detection of X4-viruses in all isolates suggests that coreceptor usage as well as fitness of minorities is important for therapy outcome. The high sensitivity of this technology in combination with a quantitative description of the viral population may allow implementing meaningful cutoffs for predicting response to CCR5-antagonists in the presence of X4-minorities.

Improved prediction of HIV­1 coreceptor usage with sequence information from the second hypervariable loop of gp120.

BACKGROUND: Human immunodeficiency virus type 1 (HIV­1) uses the CD4 receptor and a coreceptor to gain cell entry. Coreceptor usage is mainly determined by the V3 loop of gp120. Therefore, coreceptor usage is currently inferred from the genotype on the basis of V3 alone. However, several mutations outside V3 have been repeatedly reported to influence coreceptor usage. In this study, the impact of the V2 loop on coreceptor usage prediction was analyzed. METHODS: Sequences were analyzed for differences at specific positions and position­independent features with the Fisher exact and Student t tests. Prediction models were trained with support vector machines and evaluated in cross­validation on clonal data. Models trained on the clonal data set were validated on 2 clinical data sets. RESULTS: Several mutations and position­independent features within V2 were statistically significantly different between R5 and X4 viruses. Cross­validation on the clonal data set revealed a statistically significantly higher area under the receiver operating characteristic curve if features of both loops were used, compared with those using only V2 or V3 alone. Similar results were found with clinically derived data sets. CONCLUSIONS: The ability of the V2 loop to improve coreceptor usage prediction has been shown in a large data set. Utilization of this information can lead to considerable improvements in the prediction of coreceptor use both on clonal data sets and on clinically derived data sets.