Nano-RECall provides an integrated pipeline for HIV-1 drug resistance testing from Oxford Nanopore sequence data

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.

Near real-time monitoring of HIV transmission hotspots from routine HIV genotyping: an implementation case study

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.

The impact of clinical, demographic and risk factors on rates of HIV transmission: a population-based phylogenetic analysis in British Columbia, Canada

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.

HIV drug resistance detected during low-level viraemia is associated with subsequent virologic failure

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.

Theoretical and experimental assessment of degenerate primer tagging in ultra-deep applications of next-generation sequencing

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.

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.

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.

Effects of Human Leukocyte Antigen Class I Genetic Parameters on Clinical Outcomes and Survival after Initiation of Highly Active Antiretroviral Therapy

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.