Search

Objectives: Low-capital-layout sequencing options from Oxford Nanopore Technologies (ONT) could assist in expanding HIV drug resistance testing to resource-limited settings. HIV drug resistance mutations often occur as mixtures, but current ONT pipelines provide a consensus sequence only. Moreover, there is no integrated pipeline that provides a drug resistance report from an ONT sequence file without intervention from skilled bioinformaticists. We therefore investigated Nano-RECall, which provides seamless drug resistance interpretation while requiring low-read coverage ONT sequence data from affordable Flongle or MinION flow cells and which provides mutation mixtures similar to Sanger Sequencing., Methods: We compared Sanger sequencing to ONT sequencing of the same HIV-1 subtype C polymerase chain reaction (PCR) amplicons, respectively using RECall and the novel Nano-RECall bioinformatics pipelines. Amplicons were from separate assays: (a) Applied Biosystems HIV-1 Genotyping Kit (ThermoFisher) spanning protease (PR) to reverse transcriptase (RT) (PR-RT) (n = 46) and (b) homebrew integrase (IN) (n = 21). The agreement between Sanger sequences and ONT sequences was assessed at nucleotide level, and at codon level for Stanford HIV drug resistance database mutations at an optimal ONT read depth of 400 reads only., Results: The average sequence similarity between ONT and Sanger sequences was 99.3% (95% CI: 99.1%-99.4%) for PR-RT and 99.6% (95% CI: 99.4%-99.7%) for INT. Drug resistance mutations did not differ for 21 IN specimens; 8 mutations were detected by both ONT- and Sanger sequencing. For the 46 PR and RT specimens, 245 mutations were detected by either ONT or Sanger, of these 238 (97.1%) were detected by both., Conclusions: The Nano-RECall pipeline, freely available as a downloadable application on a Windows computer, provides Sanger-equivalent HIV drug resistance interpretation. This novel pipeline combined with a simple workflow and multiplexing samples on ONT flow-cells would contribute to making HIV drug resistance sequencing feasible for resource-limited settings., (© 2023 John Wiley & Sons Ltd.)

Background: HIV evolves rapidly and therefore infections with similar genetic sequences are likely linked by recent transmission events. Clusters of related infections can represent subpopulations with high rates of transmission. We describe the implementation of an automated near real-time system to monitor and characterise HIV transmission hotspots in British Columbia, Canada., Methods: In this implementation case study, we applied a monitoring system to the British Columbia drug treatment database, which holds more than 32 000 anonymised HIV genotypes for nearly 9000 residents of British Columbia living with HIV. On average, five to six new HIV genotypes are deposited in the database every day, which triggers an automated reanalysis of the entire database. We extracted clusters of five or more individuals with short phylogenetic distances between their respective HIV sequences. The system generated monthly reports of the growth and characteristics of clusters that were distributed to public health officers., Findings: In June, 2014, the monitoring system detected the expansion of a cluster by 11 new cases during 3 months, including eight cases with transmitted drug resistance. This cluster generally comprised young men who have sex with men. The subsequent report precipitated an enhanced public health follow-up to ensure linkage to care and treatment initiation in the affected subpopulation. Of the nine cases associated with this follow-up, all had already been linked to care and five cases had started treatment. Subsequent to the follow-up, three additional cases started treatment and most cases achieved suppressed viral loads. During the next 12 months, we detected 12 new cases in this cluster with reduction in the onward transmission of drug resistance., Interpretation: Our findings show the first application of an automated phylogenetic system monitoring a clinical database to detect a recent HIV outbreak and support the ensuing public health response. By making secondary use of routinely collected HIV genotypes, this approach is cost-effective, attains near real-time monitoring of new cases, and can be implemented in all settings in which HIV genotyping is the standard of care., Funding: BC Centre for Excellence in HIV/AIDS, the Canadian Institutes for Health Research, the Genome Canada-CIHR Partnership in Genomics and Personalized Health, and the US National Institute on Drug Abuse., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Persons with hepatitis C virus (HCV) genotype 1a (GT1a) infections harboring a baseline Q80K polymorphism in nonstructural protein 3 (NS3) have a reduced virologic response to simeprevir in combination with pegylated interferon-alfa and ribavirin. We aimed to develop, validate, and freely disseminate an NS3 clinical sequencing assay to detect the Q80K polymorphism and potentially other HCV NS3 drug resistance mutations. HCV RNA was extracted from frozen plasma using a NucliSENS easyMAG automated nucleic acid extractor, amplified by nested reverse transcription-PCR, and sequenced using Sanger and/or next-generation (MiSeq) methods. Sanger chromatograms were analyzed using in-house software (RECall), and nucleotide mixtures were called automatically. MiSeq reads were iteratively mapped to the H77 reference genome, and consensus NS3 sequences were generated with nucleotides present at >20% called as mixtures. The accuracy, precision, and sensitivity for detecting the Q80K polymorphism were assessed in 70 samples previously sequenced by an external laboratory. A comparison of the sequences generated by the Sanger and MiSeq methods with those determined by an external lab revealed >98.5% nucleotide sequence concordance and zero discordant calls of the Q80K polymorphism. The results were both highly repeatable and reproducible (>99.7% nucleotide concordance and 100% Q80K concordance). The limits of detection (>2 and ∼5 log10 IU/ml for the Sanger and MiSeq assays, respectively) are sufficiently low to allow genotyping in nearly all chronically infected treatment-naive persons. No systematic bias in the under- or overamplification of minority variants was observed. Coinfection with other viruses (e.g., HIV and hepatitis B virus [HBV]) did not affect the assay results. The two independent HCV NS3 sequencing assays with the automated analysis procedures described here are useful tools to screen for the Q80K polymorphism and other HCV protease inhibitor drug resistance mutations., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Background: The diversification of human immunodeficiency virus (HIV) is shaped by its transmission history. We therefore used a population based province wide HIV drug resistance database in British Columbia (BC), Canada, to evaluate the impact of clinical, demographic, and behavioral factors on rates of HIV transmission., Methods: We reconstructed molecular phylogenies from 27,296 anonymized bulk HIV pol sequences representing 7747 individuals in BC-about half the estimated HIV prevalence in BC. Infections were grouped into clusters based on phylogenetic distances, as a proxy for variation in transmission rates. Rates of cluster expansion were reconstructed from estimated dates of HIV seroconversion., Results: Our criteria grouped 4431 individuals into 744 clusters largely separated with respect to risk factors, including large established clusters predominated by injection drug users and more-recently emerging clusters comprising men who have sex with men. The mean log10 viral load of an individual's phylogenetic neighborhood (composed of 5 other individuals with shortest phylogenetic distances) increased their odds of appearing in a cluster by >2-fold per log10 viruses per milliliter., Conclusions: Hotspots of ongoing HIV transmission can be characterized in near real time by the secondary analysis of HIV resistance genotypes, providing an important potential resource for targeting public health initiatives for HIV prevention., (© The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Primer IDs (pIDs) are random oligonucleotide tags used in next-generation sequencing to identify sequences that originate from the same template. These tags are produced by degenerate primers during the reverse transcription of RNA molecules into cDNA. The use of pIDs helps to track the number of RNA molecules carried through amplification and sequencing, and allows resolution of inconsistencies between reads sharing a pID. Three potential issues complicate the above applications. First, multiple cDNAs may share a pID by chance; we found that while preventing any cDNAs from sharing a pID may be unfeasible, it is still practical to limit the number of these collisions. Secondly, a pID must be observed in at least three sequences to allow error correction; as such, pIDs observed only one or two times must be rejected. If the sequencing product contains copies from a high number of RT templates but produces few reads, our findings indicate that rejecting such pIDs will discard a great deal of data. Thirdly, the use of pIDs could influence amplification and sequencing. We examined the effects of several intrinsic and extrinsic factors on sequencing reads at both the individual and ensemble level., (© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Background: HIV patients on suppressive antiretroviral therapy have undetectable viremia making it impossible to screen plasma HIV tropism if regimen change is required during suppression. We investigated the prevalence and predictors of tropism switch from CCR5-using ("R5") to non-CCR5-using ("non-R5") before and after viral suppression in the initially therapy-naïve HOMER cohort from British Columbia, Canada., Methods: We compared pre-therapy and post-suppression viral genotypic tropism in patients who initiated on PI/NNRTI-based antiretroviral regimens between 1996-1999 (n = 462). Virologic suppression was defined as having two consecutive viral loads of <500 copies/mL, which was the sensitivity limit of most viral load assays at the time. Viral tropism was inferred by V3-loop-population-sequencing and geno2pheno[coreceptor] with cutoff at 5.75% false positive rate (FPR)., Results: When virologic suppression was defined as two-consecutive viral loads <500 copies/mL, 34 (9%) of the 397 patients with pre-therapy R5-virus switched to non-R5 at viral load rebound after a median of 19 months (IQR 8-41 months) of undetectable viremia. Duration of viral load suppression was not a predictor of switch, but lower CD4 count during suppression (median 400 versus 250 cells/mL) and an increased prevalence of pre-therapy non-R5 HIV by "deep" sequencing (median 0.2% versus 3.2%) were independently associated with switch (p = 0.03 and p<0.0001, respectively)., Conclusion: R5-to-non-R5 tropism switches in plasma virus after undetectable viremia were relatively rare events especially among patients with higher CD4 counts during virologic suppression. Our study supports the use of pre-suppression tropism results if maraviroc is being considered during virologic suppression in this subgroup of patients.

Background: The clinical implications of emergent HIV drug resistance on samples with low-level viraemia (LLV <1000 copies/ml) remain unclear. We undertook the present analysis to evaluate the impact of emergent HIV drug resistance at LLV on the risk of subsequent virologic failure., Methods: One thousand, nine hundred and sixty-five patients had genotype results at LLV. Risk of virologic failure (≥1000 copies/ml) after LLV was evaluated by Kaplan-Meier analysis and Cox proportional hazards regression. Resistance was assessed using the Stanford algorithm or virtual phenotypes. Patients were grouped into four susceptibility categories ('GSS' or 'vPSS') during LLV, corresponding to the number of 'active' drugs prescribed: <1; 1-1.5; 2-2.5; and ≥3., Results: A total of 1702 patients with follow-up on constant therapy were eligible for analysis. Participants excluded due to changing therapy or loss to follow-up before their next observation had mostly similar characteristics to included participants. There was a 'dose-dependent' increase in the hazard ratio for virologic failure with susceptibility categories at LLV. Compared with a GSS of at least 3, hazard ratios for virologic failure were 1.4 for GSS 2-2.5; 2.0 for GSS 1-1.5; and 3.0 for GSS less than 1 (P < 0.001). Numerous sensitivity analyses confirmed these findings., Conclusion: Our results demonstrate that emergent HIV drug resistance at LLV is strongly associated with subsequent virologic failure. Furthermore, we uncovered a 'dose-dependent' increase in the hazard ratio for virologic failure with decreasing GSS estimated at the time of LLV. On the basis of these findings, we propose that resistance genotyping be encouraged for HIV-infected individuals on antiretroviral therapy experiencing low-level viraemia.

Changes in HIV tropism from R5 to non-R5 or development of drug resistance is often associated with virologic failure in patients treated with maraviroc, a CCR5 antagonist. We sought to examine changes in HIV envelope sequences and inferred tropism in patients who did not respond to maraviroc-based regimens. We selected 181 patients who experienced early virologic failure on maraviroc-containing therapy in the MOTIVATE trials. All patients had R5 HIV by the original Trofile assay before entry. We used population-based sequencing methods and the geno2pheno algorithm to examine changes in tropism and V3 sequences at the time of failure. Using deep sequencing, we assessed whether V3 sequences observed at failure emerged from preexisting subpopulations. From population genotyping data at failure, 90 patients had R5 results, and 91 had non-R5 results. Of the latter group, the geno2pheno false-positive rate (FPR) value fell from a median of 20 at screening to 1.1 at failure. By deep sequencing, the median percentage of non-R5 variants in these patients rose from 1.4% to 99.5% after a median of 4 weeks on maraviroc. In 70% of cases, deep sequencing could detect a pretreatment CXCR4-using subpopulation, which emerged at failure. Overall, there were two distinct patterns of failure of maraviroc. Patients failing with R5 generally had few V3 substitutions and low non-R5 prevalence by deep sequencing. Patients with non-R5 HIV who were failing developed very-high-prevalence non-R5 HIV (median, 99%) and had very low geno2pheno values.

Human immunodeficiency virus type 1 (HIV-1) V3 loop sequence can be used to infer viral coreceptor use. The effect of input copy number on population-based sequencing of the V3 loop of HIV-1 was examined through replicate deep and population-based sequencing of samples with known tropism, a heterogeneous clinical sample (624 population-based sequences and 47 deep-sequencing replicates), and a large cohort of clinical samples from phase III clinical trials of maraviroc including the MOTIVATE/A4001029 studies (n = 1,521). Proviral DNA from two independent samples from each of 101 patients from the MOTIVATE/A4001029 studies was also analyzed. Cumulative technical error occurred at a rate of 3 × 10(-4) mismatches/bp, without observed effect on inferred tropism. Increasing PCR replication increased minority species detection with an ~10% minority population detected in 18% of cases using a single replicate at a viral load of 1,072 copies/ml and in 44% of cases using three replicates. The nucleotide prevalence detected by population-based and deep sequencing were highly correlated (Spearman's ρ, 0.73), and the accuracy increased with increasing input copy number (P < 0.001). Triplicate sequencing was able to predict tropism changes in the MOTIVATE/A4001029 studies for both low (P = 0.05) and high (P = 0.02) viral loads. Sequences derived from independently extracted and processed samples of proviral DNA for the same patient were equivalent to replicates from the same extraction (P = 0.45) and had correlated position-specific scoring matrix scores (Spearman's ρ, 0.75; P << 0.001); however, concordance in tropism inference was only 83%. Input copy number and PCR replication are important factors in minority species detection in samples with significant heterogeneity.

Background: MERIT was a randomized trial comparing maraviroc (MVC) + Combivir versus efavirenz (EFV) + Combivir in drug-naive patients screened as having R5 HIV-1 by the original Trofile assay (OTA). We retrospectively evaluated treatment response after rescreening for viral tropism using population-based V3-loop sequencing., Methods: HIV env V3-loop was amplified in triplicate using reverse transcriptase-polymerase chain reaction from stored screening plasma and sequenced. Automated base calling was performed using custom software (RECall) and tropism inferred by geno2pheno (5.75% false-positive rate). Tropism results by genotype were compared with those of OTA and Enhanced Sensitivity Trofile assay (ESTA), where all results were available (n = 876)., Results: Approximately 8% of patients screened as having R5 virus by OTA were classified as having non-R5 virus by V3-loop genotyping. These patients were less likely to have early or sustained week-48 treatment response to MVC, but not EFV. When restricted to patients with R5 virus by genotype, reanalysis of the primary study endpoint (plasma viral load <50 copies/mL at week 48) showed noninferiority of MVC twice daily to EFV (67% vs. 68%). Rescreening by genotype and ESTA had 84% concordance; patients receiving MVC twice daily rescreened as having R5 virus had greater than 1 log10 copies per milliliter decrease in viral load over those rescreened as having non-R5 virus. Where genotype and ESTA screening results were discordant outcomes were similar., Conclusions: The exclusion of ∼8% of patients with CXCR4-using virus by population-based sequencing would likely have resulted in noninferior responses in the MVC twice-daily and EFV arms. Rescreening by ESTA and population-based sequencing predicted similar virological response.

Genotypic HIV drug resistance testing is routinely used to guide clinical decisions. While genotyping methods can be standardized, a slow, labor-intensive, and subjective manual sequence interpretation step is required. We therefore performed external validation of our custom software RECall, a fully automated sequence analysis pipeline. HIV-1 drug resistance genotyping was performed on 981 clinical samples at the Stanford Diagnostic Virology Laboratory. Sequencing trace files were first interpreted manually by a laboratory technician and subsequently reanalyzed by RECall, without intervention. The relative performances of the two methods were assessed by determination of the concordance of nucleotide base calls, identification of key resistance-associated substitutions, and HIV drug resistance susceptibility scoring by the Stanford Sierra algorithm. RECall is freely available at http://pssm.cfenet.ubc.ca. In total, 875 of 981 sequences were analyzed by both human and RECall interpretation. RECall analysis required minimal hands-on time and resulted in a 25-fold improvement in processing speed (∼150 technician-hours versus ∼6 computation-hours). Excellent concordance was obtained between human and automated RECall interpretation (99.7% agreement for >1,000,000 bases compared). Nearly all discordances (99.4%) were due to nucleotide mixtures being called by one method but not the other. Similarly, 98.6% of key antiretroviral resistance-associated mutations observed were identified by both methods, resulting in 98.5% concordance of resistance susceptibility interpretations. This automated sequence analysis tool provides both standardization of analysis and a significant improvement in data workflow. The time-consuming, error-prone, and dreadfully boring manual sequence analysis step is replaced with a fully automated system without compromising the accuracy of reported HIV drug resistance data.

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.

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.

Background: The MOTIVATE-1 and 2 studies compared maraviroc (MVC) along with optimized background therapy (OBT) vs. placebo along with OBT in treatment-experienced patients screened as having R5-HIV (original Monogram Trofile). A subset screened with non-R5 HIV were treated with MVC or placebo along with OBT in a sister safety trial, A4001029. This analysis retrospectively examined the performance of population-based sequence analysis of HIV-1 env V3-loop to predict coreceptor tropism., Methods: Triplicate V3-loop sequences were generated using stored screening plasma samples and data was processed using custom software ('ReCall'), blinded to clinical response. Tropism was inferred using geno2pheno ('g2p'; 5% false positive rate). Primary outcomes were viral load changes after starting maraviroc; and concordance with prior screening Trofile results., Results: Genotype and Trofile results were available for 1164 individuals with virological outcome data (N = 169 non-R5 by Trofile). Compared with Trofile, V3 genotyping had a specificity of 92.6% and a sensitivity of 67.4% for detecting non-R5 virus. However, when compared with clinical outcome, virological responses were consistently similar between Trofile and V3 genotype at weeks 8 and 24 following the initiation of therapy for patients categorized as R5., Conclusion: Despite differences in sensitivity for predicting non-R5 HIV, week 8 and 24 week virological responses were similar in this treatment-experienced population. These findings suggest the potential utility of V3 genotyping as an accessible assay to select patients who may benefit from maraviroc treatment. Optimization of the predictive tropism algorithm may lead to further improvement in the clinical utility of HIV genotypic tropism assays.

Background: Human leukocyte antigen (HLA) class I variation influences the progression of untreated human immunodeficiency virus (HIV) disease; however, it is not known whether HLA class I variation may influence clinical outcomes after initiation of highly active antiretroviral therapy (HAART)., Methods: Associations between HLA class I genotypes and pretherapy clinical parameters were investigated in a cohort of 765 antiretroviral-naive adults initiating HAART. Cox proportional hazards regression was used to investigate the effects of HLA class I genotypes on time to suppression of the viral load to <500 HIV RNA copies/mL, time to an increase in the CD4 cell count to >100 cells/mm(3) above the baseline count, and time to nonaccidental death over a >5-year period after initiation of HAART., Results: Homozygosity at any HLA class I locus and possession of common HLA alleles were associated with a higher pretherapy viral load (P<.05). In multivariate analyses controlling for sociodemographic and clinical parameters at baseline, HLA class I homozygosity was significantly associated with a poorer CD4 cell response (P=.008), whereas possession of uncommon HLA alleles was associated with slower virologic suppression after initiation of HAART (P=.02). We observed no significant association between HLA parameters and time to nonaccidental death after initiation of HAART (P>.05, univariate analysis)., Conclusion: HLA class I zygosity-dependent and frequency-dependent effects may influence short-term HAART outcomes, and, thus, they deserve further investigation. No effects of these HLA parameters on survival after initiation of HAART were observed.