Bioinformatic data processing pipelines in support of next-generation sequencing-based HIV drug resistance testing: the Winnipeg Consensus

Optimization of genetic distance threshold for inferring the CRF01_AE molecular network based on next-generation sequencing

Introduction

HIV molecular network based on genetic distance (GD) has been extensively utilized. However, the GD threshold for the non-B subtype differs from that of subtype B. This study aimed to optimize the GD threshold for inferring the CRF01_AE molecular network.

Methods

Next-generation sequencing data of partial CRF01_AE pol sequences were obtained for 59 samples from 12 transmission pairs enrolled from a high-risk cohort during 2009 and 2014. The paired GD was calculated using the Tamura-Nei 93 model to infer a GD threshold range for HIV molecular networks.

Results

2,019 CRF01_AE pol sequences and information on recent HIV infection (RHI) from newly diagnosed individuals in Shenyang from 2016 to 2019 were collected to construct molecular networks to assess the ability of the inferred GD thresholds to predict recent transmission events. When HIV transmission occurs within a span of 1-4 years, the mean paired GD between the sequences of the donor and recipient within the same transmission pair were as follow: 0.008, 0.011, 0.013, and 0.023 substitutions/site. Using these four GD thresholds, it was found that 98.9%, 96.0%, 88.2%, and 40.4% of all randomly paired GD values from 12 transmission pairs were correctly identified as originating from the same transmission pairs. In the real world, as the GD threshold increased from 0.001 to 0.02 substitutions/site, the proportion of RHI within the molecular network gradually increased from 16.6% to 92.3%. Meanwhile, the proportion of links with RHI gradually decreased from 87.0% to 48.2%. The two curves intersected at a GD of 0.008 substitutions/site.

Discussion

A suitable range of GD thresholds, 0.008-0.013 substitutions/site, was identified to infer the CRF01_AE molecular transmission network and identify HIV transmission events that occurred within the past three years. This finding provides valuable data for selecting an appropriate GD thresholds in constructing molecular networks for non-B subtypes.

Validation of an HIV whole genome sequencing method for HIV drug resistance testing in an Australian clinical microbiology laboratory

Detection of HIV drug resistance (HIVDR) is vital to successful anti-retroviral therapy (ART). HIVDR testing to determine drug-resistance mutations is routinely performed in Australia to guide ART choice in newly diagnosed people living with HIV or in cases of treatment failure. In 2022, our clinical microbiology laboratory sought to validate a next-generation sequencing (NGS)-based HIVDR assay to replace the previous Sanger-sequencing (SS)-based ViroSeq. NGS solutions for HIVDR offer higher throughput, lower costs and higher sensitivity for variant detection. We sought to validate the previously described low-cost probe-based NGS method (veSEQ-HIV) for whole-genome recovery and HIVDR-testing in a diagnostic setting. veSEQ-HIV displayed 100% and 98% accuracy in major and minor mutation detection, respectively, and 100% accuracy of subtyping (provided > 1000 mapped reads were obtained). Pairwise comparison exhibited low inter-and intrarun variability across the whole-genome (Jaccard index [J] = 0.993; J = 0.972) and the Pol gene (J = 0.999; J = 0.999), respectively. veSEQ-HIV met all our pre-set criteria based on WHO recommendations and successfully replaced ViroSeq in our laboratory. Scaling-down veSEQ-HIV to a limited batch size and sequencing on Illumina iSeq. 100, allowed easy implementation of the assay into the workflow of a small sequencing laboratory with minimal staff and equipment and the ability to meet clinically relevant test turn-around times. As HIVDR-testing moves from SS- to NGS-based methods and new ART drugs come to market (particularly those with targets outside the Pol region), whole-genome recovery using veSEQ-HIV provides a robust, cost-effective and "future-proof" NGS method for HIVDR-testing.

Advancing HIV Drug Resistance Technologies and Strategies: Insights from South Africa's Experience and Future Directions for Resource-Limited Settings

Monitoring of HIV drug resistance (HIVDR) remains critical for ensuring countries attain and sustain the global goals for ending HIV as a public health threat by 2030. On an individual patient level, drug resistance results assist in ensuring unnecessary treatment switches are avoided and subsequent regimens are tailored on a case-by-case basis, should resistance be detected. Although there is a disparity in access to HIVDR testing in high-income countries compared to low- and middle-income countries (LMICS), more LMICs have now included HIVDR testing for individual patient management in some groups of patients. In this review, we describe different strategies for surveillance as well as where HIVDR testing can be implemented for individual patient management. In addition, we briefly review available technologies for HIVDR testing in LMICs, including Sanger sequencing, next-generation sequencing, and some point-of-care options. Finally, we describe how South Africa has implemented HIVDR testing in the public sector.

Added Value of Next Generation over Sanger Sequencing in Kenyan Youth with Extensive HIV-1 Drug Resistance

HIV-1 drug resistance testing in children and adolescents in low-resource settings is both important and challenging. New (more sensitive) drug resistance testing technologies may improve clinical care, but evaluation of their added value is limited. We assessed the potential added value of using next-generation sequencing (NGS) over Sanger sequencing for detecting nucleoside reverse transcriptase inhibitor (NRTI) and nonnucleoside reverse transcriptase inhibitor (NNRTI) drug resistance mutations (DRMs). Participants included 132 treatment-experienced Kenyan children and adolescents with diverse HIV-1 subtypes and with already high levels of drug resistance detected by Sanger sequencing. We examined overall and DRM-specific resistance and its predicted impact on antiretroviral therapy and evaluated the discrepancy between Sanger sequencing and six NGS thresholds (1%, 2%, 5%, 10%, 15%, and 20%). Depending on the NGS threshold, agreement between the two technologies was 62% to 88% for any DRM, 83% to 92% for NRTI DRMs, and 73% to 94% for NNRTI DRMs, with more DRMs detected at low NGS thresholds. NGS identified 96% to 100% of DRMs detected by Sanger sequencing, while Sanger identified 83% to 99% of DRMs detected by NGS. Higher discrepancy between technologies was associated with higher DRM prevalence. Even in this resistance-saturated cohort, 12% of participants had higher, potentially clinically relevant predicted resistance detected only by NGS. These findings, in a young, vulnerable Kenyan population with diverse HIV-1 subtypes and already high resistance levels, suggest potential benefits of more sensitive NGS over existing technology. Good agreement between technologies at high NGS thresholds supports their interchangeable use; however, the significance of DRMs identified at lower thresholds to patient care should be explored further. IMPORTANCE HIV-1 drug resistance in children and adolescents remains a significant problem in countries facing the highest burden of the HIV epidemic. Surveillance of HIV-1 drug resistance in children and adolescents is an important public health strategy, particularly in resource-limited settings, and yet, it is limited due mostly to cost and infrastructure constraints. Whether newer and more sensitive next-generation sequencing (NGS) adds substantial value beyond traditional Sanger sequencing in detecting HIV-1 drug resistance in real life settings remains an open and debatable question. In this paper, we attempt to address this issue by performing a comprehensive comparison of drug resistance identified by Sanger sequencing and six NGS thresholds. We conducted this study in a well-characterized, vulnerable cohort of children and adolescents living with diverse HIV-1 subtypes in Kenya and, importantly, failing antiretroviral therapy (ART) with already extensive drug resistance. Our findings suggest a potential added value of NGS over Sanger even in this unique cohort.

QuasiFlow: a Nextflow pipeline for analysis of NGS-based HIV-1 drug resistance data

Summary

Next-generation sequencing (NGS) enables reliable detection of resistance mutations in minority variants of human immunodeficiency virus type 1 (HIV-1). There is paucity of evidence for the association of minority resistance to treatment failure, and this requires evaluation. However, the tools for analyzing HIV-1 drug resistance (HIVDR) testing data are mostly web-based which requires uploading data to webservers. This is a challenge for laboratories with internet connectivity issues and instances with restricted data transfer across networks. We present QuasiFlow, a pipeline for reproducible analysis of NGS-based HIVDR testing data across different computing environments. Since QuasiFlow entirely depends on command-line tools and a local copy of the reference database, it eliminates challenges associated with uploading HIV-1 NGS data onto webservers. The pipeline takes raw sequence reads in FASTQ format as input and generates a user-friendly report in PDF/HTML format. The drug resistance scores obtained using QuasiFlow were 100% and 99.12% identical to those obtained using web-based HIVdb program and HyDRA web respectively at a mutation detection threshold of 20%.

Availability and implementation

QuasiFlow and corresponding documentation are publicly available at https://github.com/AlfredUg/QuasiFlow. The pipeline is implemented in Nextflow and requires regular updating of the Stanford HIV drug resistance interpretation algorithm.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Technologies for HIV-1 drug resistance testing: inventory and needs

PURPOSE OF REVIEW

HIV-1 drug resistance (HIV DR) testing is routinely performed by genotyping plasma viruses using Sanger population sequencing. Next-generation sequencing (NGS) is increasingly replacing standardized Sanger sequencing. This opens up new opportunities, but also brings challenges.

RECENT FINDINGS

The number of NGS applications and protocols for HIV DR testing is increasing. All of them are noninferior to Sanger sequencing when comparing NGS-derived consensus sequences to Sanger sequencing-derived sequences. In addition, NGS enables high-throughput sequencing of near full-length HIV-1 genomes and detection of low-abundance drug-resistant HIV-1 variants, although their clinical implications need further investigation. Several groups have defined remaining challenges in implementing NGS protocols for HIV-1 resistance testing. Some of them are already being addressed. One of the most important needs is quality management and consequently, if possible, standardization.

SUMMARY

The use of NGS technologies on HIV DR testing will allow unprecedented insights into genomic structures of virus populations that may be of immediate relevance to both clinical and research areas such as personalized antiretroviral treatment. Efforts continue to tackle the remaining challenges in NGS-based HIV DR testing.

VPipe: an Automated Bioinformatics Platform for Assembly and Management of Viral Next-Generation Sequencing Data

Next-generation sequencing (NGS) is a powerful tool for detecting and investigating viral pathogens; however, analysis and management of the enormous amounts of data generated from these technologies remains a challenge. Here, we present VPipe (the Viral NGS Analysis Pipeline and Data Management System), an automated bioinformatics pipeline optimized for whole-genome assembly of viral sequences and identification of diverse species. VPipe automates the data quality control, assembly, and contig identification steps typically performed when analyzing NGS data. Users access the pipeline through a secure web-based portal, which provides an easy-to-use interface with advanced search capabilities for reviewing results. In addition, VPipe provides a centralized system for storing and analyzing NGS data, eliminating common bottlenecks in bioinformatics analyses for public health laboratories with limited on-site computational infrastructure. The performance of VPipe was validated through the analysis of publicly available NGS data sets for viral pathogens, generating high-quality assemblies for 12 data sets. VPipe also generated assemblies with greater contiguity than similar pipelines for 41 human respiratory syncytial virus isolates and 23 SARS-CoV-2 specimens. IMPORTANCE Computational infrastructure and bioinformatics analysis are bottlenecks in the application of NGS to viral pathogens. As of September 2021, VPipe has been used by the U.S. Centers for Disease Control and Prevention (CDC) and 12 state public health laboratories to characterize >17,500 and 1,500 clinical specimens and isolates, respectively. VPipe automates genome assembly for a wide range of viruses, including high-consequence pathogens such as SARS-CoV-2. Such automated functionality expedites public health responses to viral outbreaks and pathogen surveillance.

Next generation sequencing based in-house HIV genotyping method: validation report

Background

HIV genotyping has had a significant impact on the care and treatment of HIV/AIDS. At a clinical level, the test guides physicians on the choice of treatment regimens. At the surveillance level, it informs policy on consolidated treatment guidelines and microbial resistance control strategies. Until recently, the conventional test has utilized the Sanger sequencing (SS) method. Unlike Next Generation Sequencing (NGS), SS is limited by low data throughput and the inability of detecting low abundant drug-resistant variants. NGS can improve sensitivity and quantitatively identify low-abundance variants; in addition, it has the potential to improve efficiency as well as lowering costs when samples are batched. Despite the NGS benefits, its utilization in clinical drug resistance profiling is faced with mixed reactions. These are largely based on a lack of a consensus regarding the quality control strategy. Nonetheless, transitional views suggest validating the method against the gold-standard SS. Therefore, we present a validation report of an NGS-based in-house HIV genotyping method against the SS method in Uganda.

Results

Since there were no established proficiency test panels for NGS-based HIV genotyping, 15 clinical plasma samples for routine care were utilized. The use of clinical samples allowed for accuracy and precision studies. The workflow involved four main steps; viral RNA extraction, targeted amplicon generation, amplicon sequencing and data analysis. Accuracy of 98% with an average percentage error of 3% was reported for the NGS based assay against the SS platform demonstrating similar performance. The coefficient of variation (CV) findings for both the inter-run and inter-personnel precision showed no variability (CV ≤ 0%) at the relative abundance of ≥ 20%. For both inter-run and inter-personnel, a variation that affected the precision was observed at 1% frequency. Overall, for all the frequencies, CV registered a small range of (0–2%).

Conclusion

The NGS-based in-house HIV genotyping method fulfilled the minimum requirements that support its utilization for drug resistance profiling in a clinical setting of a low-income country. For more inclusive quality control studies, well-characterized wet panels need to be established.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12981-021-00390-8.

HIV-1 Drug Resistance Genotyping in Resource Limited Settings: Current and Future Perspectives in Sequencing Technologies

Affordable, sensitive, and scalable technologies are needed for monitoring antiretroviral treatment (ART) success with the goal of eradicating HIV-1 infection. This review discusses use of Sanger sequencing and next generation sequencing (NGS) methods for HIV-1 drug resistance (HIVDR) genotyping, focusing on their use in resource limited settings (RLS). Sanger sequencing remains the gold-standard method for detecting HIVDR mutations of clinical relevance but is mainly limited by high sequencing costs and low-throughput. NGS is becoming a more common sequencing method, with the ability to detect low-abundance drug-resistant variants and reduce per sample costs through sample pooling and massive parallel sequencing. However, use of NGS in RLS is mainly limited by infrastructure costs. Given these shortcomings, our review discusses sequencing technologies for HIVDR genotyping, focusing on common in-house and commercial assays, challenges with Sanger sequencing in keeping up with changes in HIV-1 treatment programs, as well as challenges with NGS that limit its implementation in RLS and in clinical diagnostics. We further discuss knowledge gaps and offer recommendations on how to overcome existing barriers for implementing HIVDR genotyping in RLS, to make informed clinical decisions that improve quality of life for people living with HIV.

Investigation of drug resistance against protease, reverse transcriptase, and integrase inhibitors by next-generation sequencing in HIV-positive patients

Our aim was to investigate the mutations in protease (PR), reverse transcriptase (RT), and integrase (IN) gene regions in human immunodeficiency virus (HIV) using a single amplicon via next-generation sequencing (NGS). The study included plasma samples from 49 HIV-1-positive patients, which were referred for HIV-1 drug resistance testing during 2017. A nested polymerase chain reaction (PCR) was performed after the RNA extraction and one-step reverse transcription stages. The sequencing of the HIV genome in the PR, RT, and IN gene regions was carried out using MiSeq NGS technology. Sanger sequencing (SS) was used to analyze resistance mutations in the PR and RT gene regions using a ViroSeq HIV-1 Genotyping System. PCR products were analyzed with an ABI3500 GeneticAnalyzer (Applied Biosystems). Resistance mutations detected with NGS at frequencies above 20% were identical to the SS results. Resistance to at least one antiretroviral (ARV) drug was 22.4% (11 of 49) with NGS and 10.2% (5 of 49) with SS. At least one low-frequency resistance mutation was detected in 18.3% (9 of 49) of the samples. Low-frequency resistance mutations resulted in virological failure in only one patient. The cost of the analyses was reduced by sample pooling and multiplex analysis using the MiSeq system. This is the first study in Turkey to use NGS technologies for the detection of resistance mutations in all three gene (PR, RT, IN) regions using a single amplicon. Our findings suggest that NGS is more sensitive and cost-effective than the SS method.

Increased acquired protease inhibitor drug resistance mutations in minor HIV-1 quasispecies from infected patients suspected of failing on national second-line therapy in South Africa

BACKGROUND

HIV-1C has been shown to have a greater risk of virological failure and reduced susceptibility towards boosted protease inhibitors (bPIs), a component of second-line combination antiretroviral therapy (cART) in South Africa. This study entailed an evaluation of HIV-1 drug resistance-associated mutations (RAMs) among minor viral populations through high-throughput sequencing genotypic resistance testing (HTS-GRT) in patients on the South African national second-line cART regimen receiving bPIs.

METHODS

During 2017 and 2018, 67 patient samples were sequenced using high-throughput sequencing (HTS), of which 56 samples were included in the final analysis because the patient's treatment regimen was available at the time of sampling. All patients were receiving bPIs as part of their cART. Viral RNA was extracted, and complete pol genes were amplified and sequenced using Illumina HiSeq2500, followed by bioinformatics analysis to quantify the RAMs according to the Stanford HIV Drug Resistance Database.

RESULTS

Statistically significantly higher PI RAMs were observed in minor viral quasispecies (25%; 14/56) compared to non-nucleoside reverse transcriptase inhibitors (9%; 5/56; p = 0.042) and integrase inhibitor RAM (4%; 2/56; p = 0.002). The majority of the drug resistance mutations in the minor viral quasispecies were observed in the V82A mutation (n = 13) in protease and K65R (n = 5), K103N (n = 7) and M184V (n = 5) in reverse transcriptase.

CONCLUSIONS

HTS-GRT improved the identification of PI and reverse transcriptase inhibitor (RTI) RAMs in second-line cART patients from South Africa compared to the conventional GRT with ≥20% used in Sanger-based sequencing. Several RTI RAMs, such as K65R, M184V or K103N and PI RAM V82A, were identified in < 20% of the population. Deep sequencing could be of greater value in detecting acquired resistance mutations early.

Next Generation Sequencing for HIV-1 Drug Resistance Testing-A Special Issue Walkthrough

Drug resistance remains a global challenge in the fight against the HIV pandemic [...].

Low-Abundance Drug-Resistant HIV-1 Variants in Antiretroviral Drug-Naive Individuals: A Systematic Review of Detection Methods, Prevalence, and Clinical Impact

BACKGROUND

The presence of high-abundance drug-resistant HIV-1 jeopardizes success of antiretroviral therapy (ART). Despite numerous investigations, the clinical impact of low-abundance drug-resistant HIV-1 variants (LA-DRVs) at levels <15%-25% of the virus population in antiretroviral (ARV) drug-naive individuals remains controversial.

METHODS

We systematically reviewed 103 studies assessing prevalence, detection methods, technical and clinical detection cutoffs, and clinical significance of LA-DRVs in antiretroviral drug-naive adults.

RESULTS

In total, 14 919 ARV drug-naive individuals were included. Prevalence of LA-DRVs (ie, proportion of individuals harboring LA-DRVs) was 0%-100%. Technical detection cutoffs showed a 4 log range (0.001%-10%); 42/103 (40.8%) studies investigating the impact of LA-DRVs on ART; 25 studies included only individuals on first-line nonnucleoside reverse transcriptase inhibitor-based ART regimens. Eleven of those 25 studies (44.0%) reported a significantly association between preexisting LA-DRVs and risk of virological failure whereas 14/25 (56.0%) did not.

CONCLUSIONS

Comparability of the 103 studies is hampered by high heterogeneity of the studies' designs and use of different methods to detect LA-DRVs. Thus, evaluating clinical impact of LA-DRVs on first-line ART remains challenging. We, the WHO HIVResNet working group, defined central areas of future investigations to guide further efforts to implement ultrasensitive resistance testing in routine settings.

High-Throughput Metagenomics for Identification of Pathogens in the Clinical Settings

The application of sequencing technology is shifting from research to clinical laboratories owing to rapid technological developments and substantially reduced costs. However, although thousands of microorganisms are known to infect humans, identification of the etiological agents for many diseases remains challenging as only a small proportion of pathogens are identifiable by the current diagnostic methods. These challenges are compounded by the emergence of new pathogens. Hence, metagenomic next-generation sequencing (mNGS), an agnostic, unbiased, and comprehensive method for detection, and taxonomic characterization of microorganisms, has become an attractive strategy. Although many studies, and cases reports, have confirmed the success of mNGS in improving the diagnosis, treatment, and tracking of infectious diseases, several hurdles must still be overcome. It is, therefore, imperative that practitioners and clinicians understand both the benefits and limitations of mNGS when applying it to clinical practice. Interestingly, the emerging third-generation sequencing technologies may partially offset the disadvantages of mNGS. In this review, mainly: a) the history of sequencing technology; b) various NGS technologies, common platforms, and workflows for clinical applications; c) the application of NGS in pathogen identification; d) the global expert consensus on NGS-related methods in clinical applications; and e) challenges associated with diagnostic metagenomics are described.

Application of a Sanger-Based External Quality Assurance Strategy for the Transition of HIV-1 Drug Resistance Assays to Next Generation Sequencing

The National Institute of Allergy and Infectious Diseases (NIAID) Virology Quality Assurance (VQA) established a robust proficiency testing program for Sanger sequencing (SS)-based HIV-1 drug resistance (HIVDR) testing in 2001. While many of the lessons learned during the development of such programs may also apply to next generation sequencing (NGS)-based HIVDR assays, challenges remain for the ongoing evaluation of NGS-based testing. These challenges include a proper assessment of assay accuracy and the reproducibility of low abundance variant detection, intra- and inter-assay performance comparisons among laboratories using lab-defined tests, and different data analysis pipelines designed for NGS. In collaboration with the World Health Organization (WHO) Global HIVDR Laboratory Network and the Public Health Agency of Canada, the Rush VQA program distributed archived proficiency testing panels to ten laboratories to evaluate internally developed NGS assays. Consensus FASTA files were submitted using 5%, 10%, and 20% variant detection thresholds, and scored based on the same criteria used for SS. This small study showed that the SS External Quality Assurance (EQA) approach can be used as a transitional strategy for using NGS to generate SS-like data and for ongoing performance while using NGS data from the same quality control materials to further evaluate NGS assay performance.

A Comprehensive Genomics Solution for HIV Surveillance and Clinical Monitoring in Low-Income Settings

Viral genetic sequencing can be used to monitor the spread of HIV drug resistance, identify appropriate antiretroviral regimes, and characterize transmission dynamics. Despite decreasing costs, next-generation sequencing (NGS) is still prohibitively costly for routine use in generalized HIV epidemics in low- and middle-income countries. Here, we present veSEQ-HIV, a high-throughput, cost-effective NGS sequencing method and computational pipeline tailored specifically to HIV, which can be performed using leftover blood drawn for routine CD4 cell count testing. This method overcomes several major technical challenges that have prevented HIV sequencing from being used routinely in public health efforts; it is fast, robust, and cost-efficient, and generates full genomic sequences of diverse strains of HIV without bias. The complete veSEQ-HIV pipeline provides viral load estimates and quantitative summaries of drug resistance mutations; it also exploits information on within-host viral diversity to construct directed transmission networks. We evaluated the method's performance using 1,620 plasma samples collected from individuals attending 10 large urban clinics in Zambia as part of the HPTN 071-2 study (PopART Phylogenetics). Whole HIV genomes were recovered from 91% of samples with a viral load of >1,000 copies/ml. The cost of the assay (30 GBP per sample) compares favorably with existing VL and HIV genotyping tests, proving an affordable option for combining HIV clinical monitoring with molecular epidemiology and drug resistance surveillance in low-income settings.

Validation of Variant Assembly Using HAPHPIPE with Next-Generation Sequence Data from Viruses

Next-generation sequencing (NGS) offers a powerful opportunity to identify low-abundance, intra-host viral sequence variants, yet the focus of many bioinformatic tools on consensus sequence construction has precluded a thorough analysis of intra-host diversity. To take full advantage of the resolution of NGS data, we developed HAplotype PHylodynamics PIPEline (HAPHPIPE), an open-source tool for the de novo and reference-based assembly of viral NGS data, with both consensus sequence assembly and a focus on the quantification of intra-host variation through haplotype reconstruction. We validate and compare the consensus sequence assembly methods of HAPHPIPE to those of two alternative software packages, HyDRA and Geneious, using simulated HIV and empirical HIV, HCV, and SARS-CoV-2 datasets. Our validation methods included read mapping, genetic distance, and genetic diversity metrics. In simulated NGS data, HAPHPIPE generated pol consensus sequences significantly closer to the true consensus sequence than those produced by HyDRA and Geneious and performed comparably to Geneious for HIV gp120 sequences. Furthermore, using empirical data from multiple viruses, we demonstrate that HAPHPIPE can analyze larger sequence datasets due to its greater computational speed. Therefore, we contend that HAPHPIPE provides a more user-friendly platform for users with and without bioinformatics experience to implement current best practices for viral NGS assembly than other currently available options.

Multi-Laboratory Comparison of Next-Generation to Sanger-Based Sequencing for HIV-1 Drug Resistance Genotyping

Next-generation sequencing (NGS) is increasingly used for HIV-1 drug resistance genotyping. NGS methods have the potential for a more sensitive detection of low-abundance variants (LAV) compared to standard Sanger sequencing (SS) methods. A standardized threshold for reporting LAV that generates data comparable to those derived from SS is needed to allow for the comparability of data from laboratories using NGS and SS. Ten HIV-1 specimens were tested in ten laboratories using Illumina MiSeq-based methods. The consensus sequences for each specimen using LAV thresholds of 5%, 10%, 15%, and 20% were compared to each other and to the consensus of the SS sequences (protease 4-99; reverse transcriptase 38-247). The concordance among laboratories' sequences at different thresholds was evaluated by pairwise sequence comparisons. NGS sequences generated using the 20% threshold were the most similar to the SS consensus (average 99.6% identity, range 96.1-100%), compared to 15% (99.4%, 88.5-100%), 10% (99.2%, 87.4-100%), or 5% (98.5%, 86.4-100%). The average sequence identity between laboratories using thresholds of 20%, 15%, 10%, and 5% was 99.1%, 98.7%, 98.3%, and 97.3%, respectively. Using the 20% threshold, we observed an excellent agreement between NGS and SS, but significant differences at lower thresholds. Understanding how variation in NGS methods influences sequence quality is essential for NGS-based HIV-1 drug resistance genotyping.

Novel opportunities for NGS-based one health surveillance of foodborne viruses

Foodborne viral infections rank among the top 5 causes of disease, with noroviruses and hepatitis A causing the greatest burden globally. Contamination of foods by infected food handlers or through environmental pollution are the main sources of foodborne illness, with a lesser role for consumption of products from infected animals. Viral partial genomic sequencing has been used for more than two decades to track foodborne outbreaks and whole genome or metagenomics next-generation-sequencing (NGS) are new additions to the toolbox of food microbiology laboratories. We discuss developments in the field of targeted and metagenomic NGS, with an emphasis on application in food virology, the challenges and possible solutions towards future routine application.

Dry Panels Supporting External Quality Assessment Programs for Next Generation Sequencing-Based HIV Drug Resistance Testing

External quality assessment (EQA) is a keystone element in the validation and implementation of next generation sequencing (NGS)-based HIV drug resistance testing (DRT). Software validation and evaluation is a critical element in NGS EQA programs. While the development, sharing, and adoption of wet lab protocols is coupled with the increasing access to NGS technology worldwide, rendering it easy to produce NGS data for HIV-DRT, bioinformatic data analysis remains a bottleneck for most of the diagnostic laboratories. Several computational tools have been made available, via free or commercial sources, to automate the conversion of raw NGS data into an actionable clinical report. Although different software platforms yield equivalent results when identical raw NGS datasets are analyzed for variations at higher abundance, discrepancies arise when variations at lower frequencies are considered. This implies that validation and performance assessment of the bioinformatics tools applied in NGS HIV-DRT is critical, and the origins of the observed discrepancies should be determined. Well-characterized reference NGS datasets with ground truth on the genotype composition at all examined loci and the exact frequencies of HIV variations they may harbor, so-called dry panels, would be essential in such cases. The strategic design and construction of such panels are challenging but imperative tasks in support of EQA programs for NGS-based HIV-DRT and the validation of relevant bioinformatics tools. Here, we present criteria that can guide the design of such dry panels, which were discussed in the Second International Winnipeg Symposium themed for EQA strategies for NGS HIVDR assays.

Quality Control of Next-Generation Sequencing-Based HIV-1 Drug Resistance Data in Clinical Laboratory Information Systems Framework

Next-generation sequencing (NGS) in HIV drug resistance (HIVDR) testing has the potential to improve both clinical and public health settings, however it challenges the normal operations of quality management systems to be more flexible due to its complexity, massive data generation, and rapidly evolving protocols. While guidelines for quality management in NGS data have previously been outlined, little guidance has been implemented for NGS-based HIVDR testing. This document summarizes quality control procedures for NGS-based HIVDR testing laboratories using a laboratory information systems (LIS) framework. Here, we focus in particular on the quality control measures applied on the final sequencing product aligned with the recommendations from the World Health Organization HIV Drug Resistance Laboratory Network.

Development and Application of Performance Assessment Criteria for Next-Generation Sequencing-Based HIV Drug Resistance Assays

Next-generation sequencing (NGS)-based HIV drug resistance (HIVDR) assays outperform conventional Sanger sequencing in scalability, sensitivity, and quantitative detection of minority resistance variants. Thus far, HIVDR assays have been applied primarily in research but rarely in clinical settings. One main obstacle is the lack of standardized validation and performance evaluation systems that allow regulatory agencies to benchmark and accredit new assays for clinical use. By revisiting the existing principles for molecular assay validation, here we propose a new validation and performance evaluation system that helps to both qualitatively and quantitatively assess the performance of an NGS-based HIVDR assay. To accomplish this, we constructed a 70-specimen proficiency test panel that includes plasmid mixtures at known ratios, viral RNA from infectious clones, and anonymized clinical specimens. We developed assessment criteria and benchmarks for NGS-based HIVDR assays and used these to assess data from five separate MiSeq runs performed in two experienced HIVDR laboratories. This proposed platform may help to pave the way for the standardization of NGS HIVDR assay validation and performance evaluation strategies for accreditation and quality assurance purposes in both research and clinical settings.

Next-Generation Sequencing for HIV Drug Resistance Testing: Laboratory, Clinical, and Implementation Considerations

Higher accessibility and decreasing costs of next generation sequencing (NGS), availability of commercial kits, and development of dedicated analysis pipelines, have allowed an increasing number of laboratories to adopt this technology for HIV drug resistance (HIVDR) genotyping. Conventional HIVDR genotyping is traditionally carried out using population-based Sanger sequencing, which has a limited capacity for reliable detection of variants present at intra-host frequencies below a threshold of approximately 20%. NGS has the potential to improve sensitivity and quantitatively identify low-abundance variants, improving efficiency and lowering costs. However, some challenges exist for the standardization and quality assurance of NGS-based HIVDR genotyping. In this paper, we highlight considerations of these challenges as related to laboratory, clinical, and implementation of NGS for HIV drug resistance testing. Several sources of variation and bias occur in each step of the general NGS workflow, i.e., starting material, sample type, PCR amplification, library preparation method, instrument and sequencing chemistry-inherent errors, and data analysis options and limitations. Additionally, adoption of NGS-based HIVDR genotyping, especially for clinical care, poses pressing challenges, especially for resource-poor settings, including infrastructure and equipment requirements and cost, logistic and supply chains, instrument service availability, personnel training, validated laboratory protocols, and standardized analysis outputs. The establishment of external quality assessment programs may help to address some of these challenges and is needed to proceed with NGS-based HIVDR genotyping adoption.

Are We Ready for NGS HIV Drug Resistance Testing? The Second "Winnipeg Consensus" Symposium

HIV drug resistance is a major global challenge to successful and sustainable antiretroviral therapy. Next-generation sequencing (NGS)-based HIV drug resistance (HIVDR) assays enable more sensitive and quantitative detection of drug-resistance-associated mutations (DRMs) and outperform Sanger sequencing approaches in detecting lower abundance resistance mutations. While NGS is likely to become the new standard for routine HIVDR testing, many technical and knowledge gaps remain to be resolved before its generalized adoption in regular clinical care, public health, and research. Recognizing this, we conceived and launched an international symposium series on NGS HIVDR, to bring together leading experts in the field to address these issues through in-depth discussions and brainstorming. Following the first symposium in 2018 (Winnipeg, MB Canada, 21-22 February, 2018), a second "Winnipeg Consensus" symposium was held in September 2019 in Winnipeg, Canada, and was focused on external quality assurance strategies for NGS HIVDR assays. In this paper, we summarize this second symposium's goals and highlights.

External Quality Assessment Program for Next-Generation Sequencing-Based HIV Drug Resistance Testing: Logistical Considerations

Next-generation sequencing (NGS) is likely to become the new standard method for HIV drug resistance (HIVDR) genotyping. Despite the significant advances in the development of wet-lab protocols and bioinformatic data processing pipelines, one often-missing critical component of an NGS HIVDR assay for clinical use is external quality assessment (EQA). EQA is essential for ensuring assay consistency and laboratory competency in performing routine biomedical assays, and the rollout of NGS HIVDR tests in clinical practice will require an EQA. In September 2019, the 2nd International Symposium on NGS HIVDR was held in Winnipeg, Canada. It convened a multidisciplinary panel of experts, including research scientists, clinicians, bioinformaticians, laboratory biologists, biostatisticians, and EQA experts. A themed discussion was conducted on EQA strategies towards such assays during the symposium. This article describes the logistical challenges identified and summarizes the opinions and recommendations derived from these discussions, which may inform the development of an inaugural EQA program for NGS HIVDR in the near future.

Pretreatment HIV drug resistance spread within transmission clusters in Mexico City

BACKGROUND

Pretreatment HIV drug resistance (HIVDR) to NNRTIs has consistently increased in Mexico City during the last decade.

OBJECTIVES

To infer the HIV genetic transmission network in Mexico City to describe the dynamics of the local HIV epidemic and spread of HIVDR.

PATIENTS AND METHODS

HIV pol sequences were obtained by next-generation sequencing from 2447 individuals before initiation of ART at the largest HIV clinic in Mexico City (April 2016 to June 2018). Pretreatment HIVDR was estimated using the Stanford algorithm at a Sanger-like threshold (≥20%). Genetic networks were inferred with HIV-TRACE, establishing putative transmission links with genetic distances <1.5%. We examined demographic associations among linked individuals with shared drug resistance mutations (DRMs) using a ≥ 2% threshold to include low-frequency variants.

RESULTS

Pretreatment HIVDR reached 14.8% (95% CI 13.4%-16.2%) in the cohort overall and 9.6% (8.5%-10.8%) to NNRTIs. Putative links with at least one other sequence were found for 963/2447 (39%) sequences, forming 326 clusters (2-20 individuals). The inferred network was assortative by age and municipality (P < 0.001). Clustering individuals were younger [adjusted OR (aOR) per year = 0.96, 95% CI 0.95-0.97, P < 0.001] and less likely to include women (aOR = 0.46, 95% CI 0.28-0.75, P = 0.002). Among clustering individuals, 175/963 (18%) shared DRMs (involving 66 clusters), of which 66/175 (38%) shared K103N/S (24 clusters). Eight municipalities (out of 75) harboured 65% of persons sharing DRMs. Among all persons sharing DRMs, those sharing K103N were younger (aOR = 0.93, 95% CI 0.88-0.98, P = 0.003).

CONCLUSIONS

Our analyses suggest age- and geographically associated transmission of DRMs within the HIV genetic network in Mexico City, warranting continuous monitoring and focused interventions.

Performance comparison of next generation sequencing analysis pipelines for HIV-1 drug resistance testing

Next generation sequencing (NGS) is a trending new standard for genotypic HIV-1 drug resistance (HIVDR) testing. Many NGS HIVDR data analysis pipelines have been independently developed, each with variable outputs and data management protocols. Standardization of such analytical methods and comparison of available pipelines are lacking, yet may impact subsequent HIVDR interpretation and other downstream applications. Here we compared the performance of five NGS HIVDR pipelines using proficiency panel samples from NIAID Virology Quality Assurance (VQA) program. Ten VQA panel specimens were genotyped by each of six international laboratories using their own in-house NGS assays. Raw NGS data were then processed using each of the five different pipelines including HyDRA, MiCall, PASeq, Hivmmer and DEEPGEN. All pipelines detected amino acid variants (AAVs) at full range of frequencies (1~100%) and demonstrated good linearity as compared to the reference frequency values. While the sensitivity in detecting low abundance AAVs, with frequencies between 1~20%, is less a concern for all pipelines, their specificity dramatically decreased at AAV frequencies <2%, suggesting that 2% threshold may be a more reliable reporting threshold for ensured specificity in AAV calling and reporting. More variations were observed among the pipelines when low abundance AAVs are concerned, likely due to differences in their NGS read quality control strategies. Findings from this study highlight the need for standardized strategies for NGS HIVDR data analysis, especially for the detection of minority HIVDR variants.

MiDRMpol: A High-Throughput Multiplexed Amplicon Sequencing Workflow to Quantify HIV-1 Drug Resistance Mutations against Protease, Reverse Transcriptase, and Integrase Inhibitors

The detection of drug resistance mutations (DRMs) in minor viral populations is of potential clinical importance. However, sophisticated computational infrastructure and competence for analysis of high-throughput sequencing (HTS) data lack at most diagnostic laboratories. Thus, we have proposed a new pipeline, MiDRMpol, to quantify DRM from the HIV-1 pol region. The gag-vpu region of 87 plasma samples from HIV-infected individuals from three cohorts was amplified and sequenced by Illumina HiSeq2500. The sequence reads were adapter-trimmed, followed by analysis using in-house scripts. Samples from Swedish and Ethiopian cohorts were also sequenced by Sanger sequencing. The pipeline was validated against the online tool PASeq (Polymorphism Analysis by Sequencing). Based on an error rate of <1%, a value of >1% was set as reliable to consider a minor variant. Both pipelines detected the mutations in the dominant viral populations, while discrepancies were observed in minor viral populations. In five HIV-1 subtype C samples, minor mutations were detected at the <5% level by MiDRMpol but not by PASeq. MiDRMpol is a computationally as well as labor efficient bioinformatics pipeline for the detection of DRM from HTS data. It identifies minor viral populations (<20%) of DRMs. Our method can be incorporated into large-scale surveillance of HIV-1 DRM.

A MiSeq-HyDRA platform for enhanced HIV drug resistance genotyping and surveillance

Conventional HIV drug resistance (HIVDR) genotyping utilizes Sanger sequencing (SS) methods, which are limited by low data throughput and the inability of detecting low abundant drug resistant variants (LADRVs). Here we present a next generation sequencing (NGS)-based HIVDR typing platform that leverages the advantages of Illumina MiSeq and HyDRA Web. The platform consists of a fully validated sample processing protocol and HyDRA web, an open web portal that allows automated customizable NGS-based HIVDR data processing. This platform was characterized and validated using a panel of HIV-spiked plasma representing all major HIV-1 subtypes, pedigreed plasmids, HIVDR proficiency specimens and clinical specimens. All examined major HIV-1 subtypes were consistently amplified at viral loads of ≥1,000 copies/ml. The gross error rate of this platform was determined at 0.21%, and minor variations were reliably detected down to 0.50% in plasmid mixtures. All HIVDR mutations identifiable by SS were detected by the MiSeq-HyDRA protocol, while LADRVs at frequencies of 1~15% were detected by MiSeq-HyDRA only. As compared to SS approaches, the MiSeq-HyDRA platform has several notable advantages including reduced cost and labour, and increased sensitivity for LADRVs, making it suitable for routine HIVDR monitoring for both patient care and surveillance purposes.