MinVar: A rapid and versatile tool for HIV-1 drug resistance genotyping by deep sequencing

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.

Absence of Proviral Human Immunodeficiency Virus (HIV) Type 1 Evolution in Early-Treated Individuals With HIV Switching to Dolutegravir Monotherapy During 48 Weeks

Human immunodeficiency virus type 1 (HIV-1) infection is treated with antiretroviral therapy (ART), usually consisting of 2-3 different drugs, referred to as combination ART (cART). Our recent randomized clinical trial comparing a switch to dolutegravir monotherapy with continuation of cART in early-treated individuals demonstrated sustained virological suppression over 48 weeks. Here, we characterize the longitudinal landscape of the HIV-1 reservoir in these participants, with particular attention to potential differences between treatment groups regarding evidence of evolution as a proxy for low-level replication. Near full-length HIV-1 proviral polymerase chain reaction and next-generation sequencing was applied to longitudinal peripheral blood mononuclear cell samples to assess proviral evolution and the potential emergence of drug resistance mutations (DRMs). Neither an increase in genetic distance nor diversity over time was detected in participants of both treatment groups. Single proviral analysis showed high proportions of defective proviruses and low DRM numbers. No evidence for evolution during dolutegravir monotherapy was found in these early-treated individuals.

Prevalence of HIV-1 drug resistance mutations in proviral DNA in the Swiss HIV Cohort Study, a retrospective study from 1995 to 2018

BACKGROUND

Genotypic resistance testing (GRT) is routinely performed upon diagnosis of HIV-1 infection or during virological failure using plasma viral RNA. An alternative source for GRT could be cellular HIV-1 DNA.

OBJECTIVES

A substantial number of participants in the Swiss HIV Cohort Study (SHCS) never received GRT. We applied a method that enables access to the near full-length proviral HIV-1 genome without requiring detectable viraemia.

METHODS

Nine hundred and sixty-two PBMC specimens were received. Our two-step nested PCR protocol was applied to generate two overlapping long-range amplicons of the HIV-1 genome, sequenced by next-generation sequencing (NGS) and analysed by MinVar, a pipeline to detect drug resistance mutations (DRMs).

RESULTS

Six hundred and eighty-one (70.8%) of the samples were successfully amplified, sequenced and analysed by MinVar. Only partial information of the pol gene was contained in 82/681 (12%), probably due to naturally occurring deletions in the proviral sequence. All common HIV-1 subtypes were successfully sequenced. We detected at least one major DRM at high frequency (≥15%) in 331/599 (55.3%) individuals. Excluding APOBEC-signature (G-to-A mutation) DRMs, 145/599 (24.2%) individuals carried at least one major DRM. RT-inhibitor DRMs were most prevalent. The experienced time on ART was significantly longer in DRM carriers (P = 0.001) independent of inclusion or exclusion of APOBEC-signature DRMs.

CONCLUSIONS

We successfully applied a reliable and efficient method to analyse near full-length HIV-1 proviral DNA and investigated DRMs in individuals with undetectable or low viraemia. Additionally, our data underscore the need for new computational tools to exclude APOBEC-related hypermutated NGS sequence reads for reporting DRMs.

Bioinformatics toolbox for exploring target mutation-induced drug resistance

Drug resistance is increasingly among the main issues affecting human health and threatening agriculture and food security. In particular, developing approaches to overcome target mutation-induced drug resistance has long been an essential part of biological research. During the past decade, many bioinformatics tools have been developed to explore this type of drug resistance, and they have become popular for elucidating drug resistance mechanisms in a low cost, fast and effective way. However, these resources are scattered and underutilized, and their strengths and limitations have not been systematically analyzed and compared. Here, we systematically surveyed 59 freely available bioinformatics tools for exploring target mutation-induced drug resistance. We analyzed and summarized these resources based on their functionality, data volume, data source, operating principle, performance, etc. And we concisely discussed the strengths, limitations and application examples of these tools. Specifically, we tested some predictive tools and offered some thoughts from the clinician's perspective. Hopefully, this work will provide a useful toolbox for researchers working in the biomedical, pesticide, bioinformatics and pharmaceutical engineering fields, and a good platform for non-specialists to quickly understand drug resistance prediction.

Frequency matters: comparison of drug resistance mutation detection by Sanger and next-generation sequencing in HIV-1

BACKGROUND

Next-generation sequencing (NGS) is gradually replacing Sanger sequencing (SS) as the primary method for HIV genotypic resistance testing. However, there are limited systematic data on comparability of these methods in a clinical setting for the presence of low-abundance drug resistance mutations (DRMs) and their dependency on the variant-calling thresholds.

METHODS

To compare the HIV-DRMs detected by SS and NGS, we included participants enrolled in the Swiss HIV Cohort Study (SHCS) with SS and NGS sequences available with sample collection dates ≤7 days apart. We tested for the presence of HIV-DRMs and compared the agreement between SS and NGS at different variant-calling thresholds.

RESULTS

We included 594 pairs of SS and NGS from 527 SHCS participants. Males accounted for 80.5% of the participants, 76.3% were ART naive at sample collection and 78.1% of the sequences were subtype B. Overall, we observed a good agreement (Cohen's kappa >0.80) for HIV-DRMs for variant-calling thresholds ≥5%. We observed an increase in low-abundance HIV-DRMs detected at lower thresholds [28/417 (6.7%) at 10%-25% to 293/812 (36.1%) at 1%-2% threshold]. However, such low-abundance HIV-DRMs were overrepresented in ART-naive participants and were in most cases not detected in previously sampled sequences suggesting high sequencing error for thresholds <3%.

CONCLUSIONS

We found high concordance between SS and NGS but also a substantial number of low-abundance HIV-DRMs detected only by NGS at lower variant-calling thresholds. Our findings suggest that a substantial fraction of the low-abundance HIV-DRMs detected at thresholds <3% may represent sequencing errors and hence should not be overinterpreted in clinical practice.

Genotypic Resistance Testing of HIV-1 DNA in Peripheral Blood Mononuclear Cells

HIV-1 DNA exists in nonintegrated linear and circular episomal forms and as integrated proviruses. In patients with plasma viremia, most peripheral blood mononuclear cell (PBMC) HIV-1 DNA consists of recently produced nonintegrated virus DNA while in patients with prolonged virological suppression (VS) on antiretroviral therapy (ART), most PBMC HIV-1 DNA consists of proviral DNA produced months to years earlier. Drug-resistance mutations (DRMs) in PBMCs are more likely to coexist with ancestral wild-type virus populations than they are in plasma, explaining why next-generation sequencing is particularly useful for the detection of PBMC-associated DRMs. In patients with ongoing high levels of active virus replication, the DRMs detected in PBMCs and in plasma are usually highly concordant. However, in patients with lower levels of virus replication, it may take several months for plasma virus DRMs to reach detectable levels in PBMCs. This time lag explains why, in patients with VS, PBMC genotypic resistance testing (GRT) is less sensitive than historical plasma virus GRT, if previous episodes of virological failure and emergent DRMs were either not prolonged or not associated with high levels of plasma viremia. Despite the increasing use of PBMC GRT in patients with VS, few studies have examined the predictive value of DRMs on the response to a simplified ART regimen. In this review, we summarize what is known about PBMC HIV-1 DNA dynamics, particularly in patients with suppressed plasma viremia, the methods used for PBMC HIV-1 GRT, and the scenarios in which PBMC GRT has been used clinically.

Rapid genotyping of targeted viral samples using Illumina short-read sequencing data

The most important information about microorganisms might be their accurate genome sequence. Using current Next Generation Sequencing methods, sequencing data can be generated at an unprecedented pace. However, we still lack tools for the automated and accurate reference-based genotyping of viral sequencing reads. This paper presents our pipeline designed to reconstruct the dominant consensus genome of viral samples and analyze their within-host variability. We benchmarked our approach on numerous datasets and showed that the consensus genome of samples could be obtained reliably without further manual data curation. Our pipeline can be a valuable tool for fast identifying viral samples. The pipeline is publicly available on the project’s GitHub page (https://github.com/laczkol/QVG).

HIV-1 Drug Resistance Assay Using Ion Torrent Next Generation Sequencing and On-Instrument End-to-End Analysis Software

HIV-1 antiretroviral therapy management requires sequencing the protease, reverse transcriptase, and integrase portions of the HIV-1 pol gene. Most resistance testing is performed with Sanger sequencing, which has limited ability to detect minor variants. Next generation sequencing (NGS) platforms enable variant detection at frequencies as low as 1% allowing for earlier detection of resistance and modification of therapy. Implementation of NGS assays in the clinical laboratory is hindered by complicated assay design, cumbersome wet bench procedures, and the complexity of data analysis and bioinformatics. We developed a complete NGS protocol and companion analysis and reporting pipeline using AmpliSeq multiplex PCR, Ion Torrent S5 XL sequencing, and Stanford's HIVdb resistance algorithm. Implemented as a Torrent Suite software plugin, the pipeline runs automatically after sequencing. An optimum variant frequency threshold of 10% was determined by comparing Sanger sequences of archived samples from ViroSeq testing, resulting in a sensitivity of 98.2% and specificity of 99.0%. The majority (91%) of drug resistance mutations were detected by both Sanger and NGS, with 1.7% only by Sanger and 7.3% only by NGS. Variant calls were highly reproducible and there was no cross-reactivity to VZV, HBV, CMV, EBV, and HCV. The limit of detection was 500 copies/mL. The NGS assay performance was comparable to ViroSeq Sanger sequencing and has several advantages, including a publicly available end-to-end analysis and reporting plugin. The assay provides a straightforward path for implementation of NGS for HIV drug resistance testing in the laboratory setting without additional investment in bioinformatics infrastructure and resources.

New aspects of the Virus Life Cycle and Clinical Utility of Next Generation Sequencing based HIV-1 Resistance Testing in the Genomic, the Proviral and the Viral Reservoir of Peripheral Blood Mononuclear Cells

BACKGROUND

Typically, genotypic resistance testing is recommended at the start of antiretroviral therapy and is even mandatory in cases of virologic failure. The material of choice is plasma viral RNA. However, in patients with low viremia (viral load < 500 copies/ml), resistance testing by population-based sequencing is very difficult.

OBJECTIVE

Therefore, we aimed to investigate whether next generation sequencing (NGS) from proviral DNA and RNA could be an alternative.

MATERIAL AND METHODS

EDTA blood samples (n = 36) from routine clinical viral load testing were used for the study. Viral loads ranged from 96 to 390,000 copies/mL, with 100% of samples having low viremia. Distribution of subtypes A (n = 2), B (n = 16), C (n = 4), D (n = 2), G (1), CRF02 AG (n = 5), CRF01 AE (n = 5), undefined/mixed (n = 4). The extracted consensus sequences were uploaded to the Stanford HIV Drug Resistance Data Base and Geno2pheno for online analysis of drug resistance mutations and resistance factors.

RESULTS

A total of 2476 variants or drug resistance mutations (DRMs) were detected with Sanger sequencing, compared with 2892 variants with NGS. An average of 822/1008 variants were identified in plasma viral RNA by Sanger or NGS sequencing, 834/956 in cellular viral RNA, and 820/928 in cellular viral DNA.

CONCLUSIONS

Both methods are well suited for the detection of HIV substitutions or drug resistance mutations. Our results suggest that cellular RNA or cellular viral DNA is an informative alternative to plasma viral RNA for variant detection in patients with low viremia, as shown by the high correlation of variants in the different viral pools. And we show that by using UDS, a plus of two DRMs per patient becomes visible and that can make a big difference in the assessment of the expected resistance behavior of the virus.

Analytical Assessment of the Vela Diagnostics NGS Assay for HIV Genotyping and Resistance Testing: The Apulian Experience

Drug-resistance monitoring is one of the hardest challenges in HIV management. Next-generation sequencing (NGS) technologies speed up the detection of drug resistance, allowing the adjustment of antiretroviral therapy and enhancing the quality of life of people living with HIV. Recently, the NGS Sentosa^® SQ HIV Genotyping Assay (Vela Diagnostics) received approval for in vitro diagnostics use. This work is the first Italian evaluation of the performance of the Vela Diagnostics NGS platform, assessed with 420 HIV-1 clinical samples. A comparison with Sanger sequencing performance is also reported, highlighting the advantages and disadvantages of the Sentosa^® NGS assay. The precision of the technology was studied with reference specimens, while intra- and inter-assay reproducibility were evaluated for selected clinical samples. Vela Diagnostics’ NGS assay reached an 87% success rate through 30 runs of analysis in a real-world clinical context. The concordance with Sanger sequencing outcomes was equal to 97.2%. Several detected mismatches were due to NGS’s superior sensitivity to low-frequency variants. A high accuracy was observed in testing reference samples. Repeatability and reproducibility assays highlighted the good performance of the NGS platform. Beyond a few technical issues that call for further optimization, the key improvement will be a better balance between costs and processing speed. Once these issues have been solved, the Sentosa^® SQ HIV Genotyping Assay will be the way forward for HIV resistance testing.

Genetic Diversity and Acquired Drug Resistance Mutations Detected by Deep Sequencing in Virologic Failures among Antiretroviral Treatment Experienced Human Immunodeficiency Virus-1 Patients in a Pastoralist Region of Ethiopia

Purpose

This study was conducted to investigate the drug resistance mutations and genetic diversity of HIV-1 in ART experienced patients in South Omo, Ethiopia.

Patients and Methods

A cross-sectional study conducted on 253 adult patients attending ART clinics for ≥6 months in South Omo. Samples with VL ≥1000 copies/mL were considered as virological failures (VF) and their reverse transcriptase gene codons 90–234 were sequenced using Illumina MiSeq. MinVar was used for the identification of the subtypes and drug resistance mutations. Phylogenetic tree was constructed by neighbor-joining method using the maximum likelihood model.

Results

The median duration of ART was 51 months and 18.6% (47/253) of the patients exhibited VF. Of 47 viraemic patients, the genome of 41 were sequenced and subtype C was dominant (87.8%) followed by recombinant subtype BC (4.9%), M-09-CPX (4.9) and BF1 (2.4%). Of 41 genotyped subjects, 85.4% (35/41) had at least one ADR mutation. Eighty-one percent (33/41) of viraemic patients harbored NRTI resistance mutations, and 48.8% (20/41) were positive for NNRTI resistance mutations, with 43.9% dual resistance mutations. Among NRTI resistance mutations, M184V (73.2%), K219Q (63.4%) and T215 (56.1%) complex were the most mutated positions, while the most common NNRTI resistance mutations were K103N (24.4%), K101E, P225H and V108I 7.5% each. Active tuberculosis (aOR=13, 95% CI= 3.46–29.69), immunological failure (aOR=3.61, 95% CI=1.26–10.39), opportunistic infections (aOR=8.39, 95% CI= 1.75–40.19), and poor adherence were significantly associated with virological failure, while rural residence (aOR 2.37; 95% CI: 1.62–9.10, P= 0.05), immunological failures (aOR 2.37; 95% CI: 1.62–9.10, P= 0.05) and high viral load (aOR 16; 95% CI: 5.35 51.59, P <0.001) were predictors of ADR mutation among the ART experienced and viraemic study subjects.

Conclusion

The study revealed considerable prevalence of VF and ADR mutation with the associated risk indicators. Regular virological monitoring and drug resistance genotyping methods should be implemented for better ART treatment outcomes of the nation.

Technology dictates algorithms: recent developments in read alignment

Aligning sequencing reads onto a reference is an essential step of the majority of genomic analysis pipelines. Computational algorithms for read alignment have evolved in accordance with technological advances, leading to today's diverse array of alignment methods. We provide a systematic survey of algorithmic foundations and methodologies across 107 alignment methods, for both short and long reads. We provide a rigorous experimental evaluation of 11 read aligners to demonstrate the effect of these underlying algorithms on speed and efficiency of read alignment. We discuss how general alignment algorithms have been tailored to the specific needs of various domains in biology.

Transmitted HIV-1 drug resistance in a large international cohort using next-generation sequencing: results from the Strategic Timing of Antiretroviral Treatment (START) study

OBJECTIVES

The aim of this analysis was to characterize transmitted drug resistance (TDR) in Strategic Timing of Antiretroviral Treatment (START) study participants by next-generation sequencing (NGS), a sensitive assay capable of detecting low-frequency variants.

METHODS

Stored plasma from participants with entry HIV RNA > 1000 copies/mL were analysed by NGS (Illumina MiSeq). TDR was based on the WHO 2009 surveillance definition with the addition of reverse transcriptase (RT) mutations T215N and E138K, and integrase strand transfer inhibitor (INSTI) surveillance mutations (Stanford HIVdb). Drug resistance mutations (DRMs) detected at three thresholds are reported: > 2%, 5% and 20% of the viral population.

RESULTS

Between 2009 and 2013, START enrolled 4684 antiretroviral therapy (ART)-naïve individuals in 35 countries. Baseline NGS data at study entry were available for 2902 participants. Overall prevalence rates of TDR using a detection threshold of 2%/5%/20% were 9.2%/5.6%/3.2% for nucleoside reverse transcriptase inhibitors (NRTIs), 9.2%/6.6%/4.9% for non-NRTIs, 11.4%/5.5%/2.4% for protease inhibitors (PIs) and 3.5%/1.6%/0.1% for INSTI DRMs and varied by geographic region. Using the 2% detection threshold, individual DRMs with the highest prevalence were: PI M46IL (5.5%), RT K103NS (3.5%), RT G190ASE (3.1%), T215ISCDVEN (2.5%), RT M41L (2.2%), RT K219QENR (1.7%) and PI D30N (1.6%). INSTI DRMs were detected almost exclusively below the 20% detection threshold, most commonly Y143H (0.4%), Q148R (0.4%) and T66I (0.4%).

CONCLUSIONS

Use of NGS in this study population resulted in the detection of a large proportion of low-level variants which would not have been detected by traditional Sanger sequencing. Global surveillance studies utilizing NGS should provide a more comprehensive assessment of TDR prevalence in different regions of the world.

Engagement in Care, Viral Suppression, Drug Resistance, and Reasons for Nonengagement After Home-Based Same-Day Antiretroviral Therapy Initiation in Lesotho: A Two-Year Follow-up of the CASCADE Trial

Background

The CASCADE trial showed that compared with usual care (UC), offering same-day (SD) antiretroviral therapy (ART) during home-based human immunodeficiency virus testing improved engagement in care and viral suppression 12 months after diagnosis. However, questions remain regarding long-term outcomes and the risk of propagating drug resistance.

Methods

After completion of the primary endpoint at 12 months, participants not in care in both arms were traced and encouraged to access care. At 24 months, the following outcomes were assessed in both arms: engagement in care, viral suppression, and reasons for nonengagement. Furthermore, we explored the acquisition of drug resistance mutations (DRMs) among SD arm nonlinkers.

Results

At 24 months, 64% (88/137) in the SD arm vs 59% (81/137) in the UC arm were in care (absolute difference [AD], 5%; 95% confidence interval [CI], −6 to16; P = .38) and 57% (78/137) vs 54% (74/137) had documented viral suppression (AD, 3%; 95% CI, −9 to 15; P = .28). Among 36 participants alive and not in care at 24 months with ascertained status, the majority rejected contact with the health system or were unwilling to take ART. Among 8 interviewed SD arm nonlinkers, 6 had not initiated ART upon enrollment, and no acquired DRMs were detected. Two had taken the initial 30-day ART supply and acquired DRMs.

Conclusions

SD ART resulted in higher rates of engagement in care and viral suppression at 12 months but not at 24 months. Leveling off between both arms was driven by linkage beyond 12 months in the UC arm. We did not observe compensatory long-term disengagement in the SD arm. These long-term results endorse SD ART initiation policies.

Clinical Trials Registration

NCT02692027.

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.

Emergence of Human Immunodeficiency Virus-1 Drug Resistance During the 3-Month World Health Organization-Recommended Enhanced Adherence Counseling Period in the CART-1 Cohort Study

Background

In resource-limited settings, the World Health Organization recommends enhanced adherence counseling (EAC) for individuals with an unsuppressed human immunodeficiency virus (HIV)-1 viral load (VL) and to remeasure VL after 3 months to avoid unnecessary regimen switches. In cases in which this follow-up VL remains unsuppressed, a regimen switch is indicated. We aimed to assess levels of HIV-1 drug resistance before and after the EAC period among people with ongoing viremia (≥80 c/mL) after EAC.

Methods

We included adult participants of the CART-1 cohort study conducted in Lesotho who had a VL ≥80 c/mL after EAC. Paired plasma samples (before and after EAC) were analyzed by next-generation sequencing. We assessed the prevalence of resistance-associated mutations and viral susceptibility scores to each participant’s antiretroviral therapy (ART) regimen (range, 0–3; 3 indicates complete susceptibility).

Results

Among 93 participants taking nonnucleoside reverse-transcriptase inhibitor-based ART with an initial VL ≥1000 copies/mL who received a follow-up VL test after EAC, 76 still had a VL ≥80 copies/mL after EAC, and paired samples were available for 57 of 76. The number of individuals without full susceptibility to any drug in their regimen increased from 31 of 57 (54.4%) before to 36 of 57 (63.2%) after EAC. Median susceptibility scores dropped from 0.5 (interquartile range [IQR] = 0.25–) to 0.25 (IQR = 0.25–1) during the EAC period (P = .16).

Conclusions

Despite high levels of resistance before EAC, we observed a slight decline in susceptibility scores after EAC. The risk of further accumulation of resistance during EAC has to be balanced against the benefit of avoiding unnecessary switches in those with spontaneous resuppression after EAC.

V-pipe: a computational pipeline for assessing viral genetic diversity from high-throughput data

Motivation

High-throughput sequencing technologies are used increasingly not only in viral genomics research but also in clinical surveillance and diagnostics. These technologies facilitate the assessment of the genetic diversity in intra-host virus populations, which affects transmission, virulence and pathogenesis of viral infections. However, there are two major challenges in analysing viral diversity. First, amplification and sequencing errors confound the identification of true biological variants, and second, the large data volumes represent computational limitations.

Results

To support viral high-throughput sequencing studies, we developed V-pipe, a bioinformatics pipeline combining various state-of-the-art statistical models and computational tools for automated end-to-end analyses of raw sequencing reads. V-pipe supports quality control, read mapping and alignment, low-frequency mutation calling, and inference of viral haplotypes. For generating high-quality read alignments, we developed a novel method, called ngshmmalign, based on profile hidden Markov models and tailored to small and highly diverse viral genomes. V-pipe also includes benchmarking functionality providing a standardized environment for comparative evaluations of different pipeline configurations. We demonstrate this capability by assessing the impact of three different read aligners (Bowtie 2, BWA MEM, ngshmmalign) and two different variant callers (LoFreq, ShoRAH) on the performance of calling single-nucleotide variants in intra-host virus populations. V-pipe supports various pipeline configurations and is implemented in a modular fashion to facilitate adaptations to the continuously changing technology landscape.

Availabilityand implementation

V-pipe is freely available at https://github.com/cbg-ethz/V-pipe.

Supplementary information

Supplementary data are available at Bioinformatics online.

Epidemiological data analysis of viral quasispecies in the next-generation sequencing era

The unprecedented coverage offered by next-generation sequencing (NGS) technology has facilitated the assessment of the population complexity of intra-host RNA viral populations at an unprecedented level of detail. Consequently, analysis of NGS datasets could be used to extract and infer crucial epidemiological and biomedical information on the levels of both infected individuals and susceptible populations, thus enabling the development of more effective prevention strategies and antiviral therapeutics. Such information includes drug resistance, infection stage, transmission clusters and structures of transmission networks. However, NGS data require sophisticated analysis dealing with millions of error-prone short reads per patient. Prior to the NGS era, epidemiological and phylogenetic analyses were geared toward Sanger sequencing technology; now, they must be redesigned to handle the large-scale NGS datasets and properly model the evolution of heterogeneous rapidly mutating viral populations. Additionally, dedicated epidemiological surveillance systems require big data analytics to handle millions of reads obtained from thousands of patients for rapid outbreak investigation and management. We survey bioinformatics tools analyzing NGS data for (i) characterization of intra-host viral population complexity including single nucleotide variant and haplotype calling; (ii) downstream epidemiological analysis and inference of drug-resistant mutations, age of infection and linkage between patients; and (iii) data collection and analytics in surveillance systems for fast response and control of outbreaks.

Recommendations for the introduction of metagenomic high-throughput sequencing in clinical virology, part I: Wet lab procedure

Metagenomic high-throughput sequencing (mHTS) is a hypothesis-free, universal pathogen detection technique for determination of the DNA/RNA sequences in a variety of sample types and infectious syndromes. mHTS is still in its early stages of translating into clinical application. To support the development, implementation and standardization of mHTS procedures for virus diagnostics, the European Society for Clinical Virology (ESCV) Network on Next-Generation Sequencing (ENNGS) has been established. The aim of ENNGS is to bring together professionals involved in mHTS for viral diagnostics to share methodologies and experiences, and to develop application recommendations. This manuscript aims to provide practical recommendations for the wet lab procedures necessary for implementation of mHTS for virus diagnostics and to give recommendations for development and validation of laboratory methods, including mHTS quality assurance, control and quality assessment protocols.

Short Communication: HIV-DRLink: A Tool for Reporting Linked HIV-1 Drug Resistance Mutations in Large Single-Genome Data Sets Using the Stanford HIV Database

The prevalence of HIV-1 drug resistance is increasing worldwide and monitoring its emergence is important for the successful management of populations receiving combination antiretroviral therapy. It is likely that pre-existing drug resistance mutations linked on the same viral genomes are predictive of treatment failure. Because of the large number of sequences generated by ultrasensitive single-genome sequencing (uSGS) and other similar next-generation sequencing methods, it is difficult to assess each sequence individually for linked drug resistance mutations. Several software/programs exist to report the frequencies of individual mutations in large data sets, but they provide no information on linkage of resistance mutations. In this study, we report the HIV-DRLink program, a research tool that provides resistance mutation frequencies as well as their genetic linkage by parsing and summarizing the Sierra output from the Stanford HIV Database. The HIV-DRLink program should only be used on data sets generated by methods that eliminate artifacts due to polymerase chain reaction recombination, for example, standard single-genome sequencing or uSGS. HIV-DRLink is exclusively a research tool and is not intended to inform clinical decisions.

HCV Genetic Diversity Can Be Used to Infer Infection Recency and Time since Infection

HIV-1 genetic diversity can be used to infer time since infection (TSI) and infection recency. We adapted this approach for HCV and identified genomic regions with informative diversity. We included 72 HCV/HIV-1 coinfected participants of the Swiss HIV Cohort Study, for whom reliable estimates of infection date and viral sequences were available. Average pairwise diversity (APD) was calculated over each codon position for the entire open reading frame of HCV. Utilizing cross validation, we evaluated the correlation of APD with TSI, and its ability to infer TSI via a linear model. We additionally studied the ability of diversity to classify infections as recent (infected for <1 year) or chronic, using receiver-operator-characteristic area under the curve (ROC-AUC) in 50 patients whose infection could be unambiguously classified as either recent or chronic. Measuring HCV diversity over third or all codon positions gave similar performances, and notable improvement over first or second codon positions. APD calculated over the entire genome enabled classification of infection recency (ROC-AUC = 0.76). Additionally, APD correlated with TSI (R² = 0.33) and could predict TSI (mean absolute error = 1.67 years). Restricting the region over which APD was calculated to E2-NS2 further improved accuracy (ROC-AUC = 0.85, R² = 0.54, mean absolute error = 1.38 years). Genetic diversity in HCV correlates with TSI and is a proxy for infection recency and TSI, even several years post-infection.

Applying next-generation sequencing to unravel the mutational landscape in viral quasispecies

Next-generation sequencing (NGS) has revolutionized the scale and depth of biomedical sciences. Because of its unique ability for the detection of sub-clonal variants within genetically diverse populations, NGS has been successfully applied to analyze and quantify the exceptionally-high diversity within viral quasispecies, and many low-frequency drug- or vaccine-resistant mutations of therapeutic importance have been discovered. Although many works have intensively discussed the latest NGS approaches and applications in general, none of them has focused on applying NGS in viral quasispecies studies, mostly due to the limited ability of current NGS technologies to accurately detect and quantify rare viral variants. Here, we summarize several error-correction strategies that have been developed to enhance the detection accuracy of minority variants. We also discuss critical considerations for preparing a sequencing library from viral RNAs and for analyzing NGS data to unravel the mutational landscape.

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.

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.

External Quality Assessment for Next-Generation Sequencing-Based HIV Drug Resistance Testing: Unique Requirements and Challenges

Over the past decade, there has been an increase in the adoption of next generation sequencing (NGS) technologies for HIV drug resistance (HIVDR) testing. NGS far outweighs conventional Sanger sequencing as it has much higher throughput, lower cost when samples are batched and, most importantly, significantly higher sensitivities for variants present at low frequencies, which may have significant clinical implications. Despite the advantages of NGS, Sanger sequencing remains the gold standard for HIVDR testing, largely due to the lack of standardization of NGS-based HIVDR testing. One important aspect of standardization includes external quality assessment (EQA) strategies and programs. Current EQA for Sanger-based HIVDR testing includes proficiency testing where samples are sent to labs and the performance of the lab conducting such assays is evaluated. The current methods for Sanger-based EQA may not apply to NGS-based tests because of the fundamental differences in their technologies and outputs. Sanger-based genotyping reports drug resistance mutations (DRMs) data as dichotomous, whereas NGS-based HIVDR genotyping also reports DRMs as numerical data (percent abundance). Here we present an overview of the need to develop EQA for NGS-based HIVDR testing and some unique challenges that may be encountered.

Analysis of unusual and signature APOBEC-mutations in HIV-1 pol next-generation sequences

Introduction

At low mutation-detection thresholds, next generation sequencing (NGS) for HIV-1 genotypic resistance testing is susceptible to artifactual detection of mutations arising from PCR error and APOBEC-mediated G-to-A hypermutation.

Methods

We analyzed published HIV-1 pol Illumina NGS data to characterize the distribution of mutations at eight NGS mutation detection thresholds: 20%, 10%, 5%, 2%, 1%, 0.5%, 0.2%, and 0.1%. At each threshold, we determined proportions of amino acid mutations that were unusual (defined as having a prevalence <0.01% in HIV-1 group M sequences) or signature APOBEC mutations.

Results

Eight studies, containing 855 samples, in the NCBI Sequence Read Archive were analyzed. As detection thresholds were lowered, there was a progressive increase in the proportion of positions with usual and unusual mutations and in the proportion of all mutations that were unusual. The median proportion of positions with an unusual mutation increased gradually from 0% at the 20% threshold to 0.3% at the 1% threshold and then exponentially to 1.3% (0.5% threshold), 6.9% (0.2% threshold), and 23.2% (0.1% threshold). In two of three studies with available plasma HIV-1 RNA levels, the proportion of positions with unusual mutations was negatively associated with virus levels. Although the complete set of signature APOBEC mutations was much smaller than that of unusual mutations, the former outnumbered the latter in one-sixth of samples at the 0.5%, 1%, and 2% thresholds.

Conclusions

The marked increase in the proportion of positions with unusual mutations at thresholds below 1% and in samples with lower virus loads suggests that, at low thresholds, many unusual mutations are artifactual, reflecting PCR error or G-to-A hypermutation. Profiling the numbers of unusual and signature APOBEC pol mutations at different NGS mutation detection thresholds may be useful to avoid selecting a threshold that is too low and poses an unacceptable risk of identifying artifactual mutations.

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.

Low prevalence of transmitted HIV-1 drug resistance detected by a dried blood spot (DBS)-based next-generation sequencing (NGS) method in newly diagnosed individuals in Cameroon in the years 2015-16

Objectives

To determine the most recent prevalence, transmission patterns and risk factors of transmitted drug-resistance mutations (TDRMs) in Cameroon, we initiated a multicentre study monitoring HIV-1 drug resistance in newly HIV-1-diagnosed individuals using a novel next-generation sequencing (NGS) assay applicable to fingerprick dried blood spot (DBS) samples.

Methods

Fingerprick DBS samples and questionnaires were collected from 360 newly HIV-1-diagnosed individuals in four hospitals in urban areas in Cameroon in the years 2015-16. We developed an HIV-1 protease and reverse transcriptase drug resistance genotyping assay applicable to DBS samples and HIV-1 genomes of groups M, N and O. The WHO 2009 list of mutations for surveillance of transmitted drug-resistant HIV strains was used to analyse TDRMs.

Results

Applying our 'DBS-NGS-genotypic resistance test', baseline HIV-1 drug resistance data were successfully obtained from 82.8% (298/360) of newly diagnosed individuals. At nucleotide frequencies >15%, TDRMs to NRTIs were observed in 3.0% (9/298), to NNRTIs in 4.0% (12/298) and to PIs in 1.3% (3/240). The NNRTI mutation K103N was most commonly detected (2.7%). Expanding the analysis to low-abundance TDRMs, i.e. 3%-15%, 12 additional individuals (4.0%) harbouring TDRMs were identified. Having unprotected sex with a known HIV-1-positive person was significantly associated with the transmission of DRMs (adjusted OR 9.6; 95% CI 1.79-51.3).

Conclusions

The prevalence of transmitted HIV-1 drug resistance is currently low in the study sites in Cameroon. Evidence of some risky sexual behaviours depicts a public health problem with possible implications for the prevention of new HIV-1 infections.

Amino Acid Prevalence of HIV-1 pol Mutations by Direct Polymerase Chain Reaction and Single Genome Sequencing

The presence of many highly unusual HIV-1 mutations at a minority variant threshold by next-generation sequence (NGS) may indicate that a high proportion of variants at or just above the threshold represent PCR errors. The validity of this hypothesis depends on the concept that highly unusual mutations detected by population-based sequencing are also highly unusual within a person's virus population. Highly unusual mutations were defined as mutations with a prevalence <0.01% in group M HIV-1 direct PCR population-based Sanger sequences in the Stanford HIV Drug Resistance Database. Single genome Sanger sequences [single genome sequences (SGSs)] were analyzed because they are not subject to PCR error. Permutation analyses compared the proportion of highly unusual mutations in SGSs with the empirical frequencies of these mutations in repeated random selections of population-based sequences. We created a database of 11,258 pol SGSs in 963 plasma samples from 345 persons with active virus replication and analyzed the subset of samples containing 10 or more SGSs. Highly unusual mutations occurred more commonly in samples undergoing SGS compared with population-based sequencing in protease (3.9% vs. 0.8%; p < .001), reverse transcriptase (6.5% vs. 1.5%; p < .001), and integrase (5.0% vs. 1.8%; p < .001). Highly unusual mutations occur more commonly in SGSs than in population-based sequences. However, they comprise a small proportion of all SGS mutations supporting the concept that the presence of many highly unusual mutations just above an NGS threshold suggests that the threshold is too low.

Validation of publicly-available software used in analyzing NGS data for HIV-1 drug resistance mutations and transmission networks in a Washington, DC, Cohort

The DC Cohort is an ongoing longitudinal observational study of persons living with HIV. To better understand HIV-1 drug resistance and potential transmission clusters among these participants, we performed targeted, paired-end next-generation sequencing (NGS) of protease, reverse transcriptase and integrase amplicons. We elected to use free, publicly-available software (HyDRA Web, Stanford HIVdb and HIV-TRACE) for data analyses so that laboratory personnel without extensive bioinformatics expertise could use it; making the approach accessible and affordable for labs worldwide. With more laboratories transitioning away from Sanger-based chemistries to NGS platforms, lower frequency drug resistance mutations (DRMs) can be detected, yet their clinical relevance is uncertain. We looked at the impact choice in cutoff percentage had on number of DRMs detected and found an inverse correlation between the two. Longitudinal studies will be needed to determine whether low frequency DRMs are an early indicator of emerging resistance. We successfully validated this pipeline against a commercial pipeline, and another free, publicly-available pipeline. RT DRM results from HyDRA Web were compared to both SmartGene and PASeq Web; using the Mantel test, R2 values were 0.9332 (p<0.0001) and 0.9097 (p<0.0001), respectively. PR and IN DRM results from HyDRA Web were then compared with PASeq Web only; using the Mantel test, R2 values were 0.9993 (p<0.0001) and 0.9765 (p<0.0001), respectively. Drug resistance was highest for the NRTI drug class and lowest for the PI drug class in this cohort. RT DRM interpretation reports from this pipeline were also highly correlative compared to SmartGene pipeline; using the Spearman's Correlation, rs value was 0.97757 (p<0.0001). HIV-TRACE was used to identify potential transmission clusters to better understand potential linkages among an urban cohort of persons living with HIV; more individuals were male, of black race, with an HIV risk factor of either MSM or High-risk Heterosexual. Common DRMs existed among individuals within a cluster. In summary, we validated a comprehensive, easy-to-use and affordable NGS approach for tracking HIV-1 drug resistance and identifying potential transmission clusters within the community.

Full-Length Envelope Analyzer (FLEA): A tool for longitudinal analysis of viral amplicons

Next generation sequencing of viral populations has advanced our understanding of viral population dynamics, the development of drug resistance, and escape from host immune responses. Many applications require complete gene sequences, which can be impossible to reconstruct from short reads. HIV env, the protein of interest for HIV vaccine studies, is exceptionally challenging for long-read sequencing and analysis due to its length, high substitution rate, and extensive indel variation. While long-read sequencing is attractive in this setting, the analysis of such data is not well handled by existing methods. To address this, we introduce FLEA (Full-Length Envelope Analyzer), which performs end-to-end analysis and visualization of long-read sequencing data. FLEA consists of both a pipeline (optionally run on a high-performance cluster), and a client-side web application that provides interactive results. The pipeline transforms FASTQ reads into high-quality consensus sequences (HQCSs) and uses them to build a codon-aware multiple sequence alignment. The resulting alignment is then used to infer phylogenies, selection pressure, and evolutionary dynamics. The web application provides publication-quality plots and interactive visualizations, including an annotated viral alignment browser, time series plots of evolutionary dynamics, visualizations of gene-wide selective pressures (such as dN/dS) across time and across protein structure, and a phylogenetic tree browser. We demonstrate how FLEA may be used to process Pacific Biosciences HIV env data and describe recent examples of its use. Simulations show how FLEA dramatically reduces the error rate of this sequencing platform, providing an accurate portrait of complex and variable HIV env populations. A public instance of FLEA is hosted at http://flea.datamonkey.org. The Python source code for the FLEA pipeline can be found at https://github.com/veg/flea-pipeline. The client-side application is available at https://github.com/veg/flea-web-app. A live demo of the P018 results can be found at http://flea.murrell.group/view/P018.

Viral populations constantly evolve and diversify. In this article we introduce a method, FLEA, for reconstructing and visualizing the details of evolutionary changes. FLEA specifically processes data from sequencing platforms that generate reads that are long, but error-prone. To study the evolutionary dynamics of entire genes during viral infection, data is collected via long-read sequencing at discrete time points, allowing us to understand how the virus changes over time. However, the experimental and sequencing process is imperfect, so the resulting data contain not only real evolutionary changes, but also mutations and other genetic artifacts caused by sequencing errors. Our method corrects most of these errors by combining thousands of erroneous sequences into a much smaller number of unique consensus sequences that represent biologically meaningful variation. The resulting high-quality sequences are used for further analysis, such as building an evolutionary tree that tracks and interprets the genetic changes in the viral population over time. FLEA is open source, and is freely available online.

UK circulating strains of human parainfluenza 3: an amplicon based next generation sequencing method and phylogenetic analysis

Background: Human parainfluenza viruses type 3 (HPIV3) are a prominent cause of respiratory infection with a significant impact in both pediatric and transplant patient cohorts.  Currently there is a paucity of whole genome sequence data that would allow for detailed epidemiological and phylogenetic analysis of circulating strains in the UK. Although it is known that HPIV3 peaks annually in the UK, to date there are no whole genome sequences of HPIV3 UK strains available.  Methods: Clinical strains were obtained from HPIV3 positive respiratory patient samples collected between 2011 and 2015.  These were then amplified using an amplicon based method, sequenced on the Illumina platform and assembled using a new robust bioinformatics pipeline. Phylogenetic analysis was carried out in the context of other epidemiological studies and whole genome sequence data currently available with stringent exclusion of significantly culture-adapted strains of HPIV3. Results: In the current paper we have presented twenty full genome sequences of UK circulating strains of HPIV3 and a detailed phylogenetic analysis thereof.  We have analysed the variability along the HPIV3 genome and identified a short hypervariable region in the non-coding segment between the M (matrix) and F (fusion) genes. The epidemiological classifications obtained by using this region and whole genome data were then compared and found to be identical. Conclusions: The majority of HPIV3 strains were observed at different geographical locations and with a wide temporal spread, reflecting the global distribution of HPIV3. Consistent with previous data, a particular subcluster or strain was not identified as specific to the UK, suggesting that a number of genetically diverse strains circulate at any one time. A small hypervariable region in the HPIV3 genome was identified and it was shown that, in the absence of full genome data, this region could be used for epidemiological surveillance of HPIV3.

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

INTRODUCTION

Next-generation sequencing (NGS) has several advantages over conventional Sanger sequencing for HIV drug resistance (HIVDR) genotyping, including detection and quantitation of low-abundance variants bearing drug resistance mutations (DRMs). However, the high HIV genomic diversity, unprecedented large volume of data, complexity of analysis and potential for error pose significant challenges for data processing. Several NGS analysis pipelines have been developed and used in HIVDR research; however, the absence of uniformity in data processing strategies results in lack of consistency and comparability of outputs from different pipelines. To fill this gap, an international symposium on bioinformatic strategies for NGS-based HIVDR testing was held in February 2018 in Winnipeg, Canada, convening laboratory scientists, bioinformaticians and clinicians involved in four recently developed, publicly available NGS HIVDR pipelines. The goal of this symposium was to establish a consensus on effective bioinformatic strategies for NGS data management and its use for HIVDR reporting.

DISCUSSION

Essential functionalities of an NGS HIVDR pipeline were divided into five analytic blocks: (1) NGS read quality control (QC)/quality assurance (QA); (2) NGS read alignment and reference mapping; (3) HIV variant calling and variant QC; (4) NGS HIVDR reporting; and (5) extended data applications and additional considerations for data management. The consensuses reached among the participants on all major aspects of these blocks are summarized here. They encompass not only recommended data management and analysis strategies, but also detailed bioinformatic approaches that help ensure accuracy of the derived HIVDR analysis outputs for both research and potential clinical use.

CONCLUSIONS

While NGS is being adopted more broadly in HIVDR testing laboratories, data processing is often a bottleneck hindering its generalized application. The proposed standardization of NGS read QC/QA, read alignment and reference mapping, variant calling and QC, HIVDR reporting and relevant data management strategies in this "Winnipeg Consensus" may serve as a starting guideline for NGS HIVDR data processing that informs the refinement of existing pipelines and those yet to be developed. Moreover, the bioinformatic strategies presented here may apply more broadly to NGS data analysis of microbes harbouring significant genomic diversity.

UK circulating strains of human parainfluenza 3: an amplicon based next generation sequencing method and phylogenetic analysis

Background: Human parainfluenza viruses type 3 (HPIV3) are a prominent cause of respiratory infection with a significant impact in both pediatric and transplant patient cohorts.  Currently there is a paucity of whole genome sequence data that would allow for detailed epidemiological and phylogenetic analysis of circulating strains in the UK. Although it is known that HPIV3 peaks annually in the UK, to date there are no whole genome sequences of HPIV3 UK strains available.  Methods: Clinical strains were obtained from HPIV3 positive respiratory patient samples collected between 2011 and 2015.  These were then amplified using an amplicon based method, sequenced on the Illumina platform and assembled using a new robust bioinformatics pipeline. Phylogenetic analysis was carried out in the context of other epidemiological studies and whole genome sequence data currently available with stringent exclusion of significantly culture-adapted strains of HPIV3. Results: In the current paper we have presented twenty full genome sequences of UK circulating strains of HPIV3 and a detailed phylogenetic analysis thereof.  We have analysed the variability along the HPIV3 genome and identified a short hypervariable region in the non-coding segment between the M (matrix) and F (fusion) genes. The epidemiological classifications obtained by using this region and whole genome data were then compared and found to be identical. Conclusions: The majority of HPIV3 strains were observed at different geographical locations and with a wide temporal spread, reflecting the global distribution of HPIV3. Consistent with previous data, a particular subcluster or strain was not identified as specific to the UK, suggesting that a number of genetically diverse strains circulate at any one time. A small hypervariable region in the HPIV3 genome was identified and it was shown that, in the absence of full genome data, this region could be used for epidemiological surveillance of HPIV3.

Sanger and Next Generation Sequencing Approaches to Evaluate HIV-1 Virus in Blood Compartments

The implementation of antiretroviral treatment combined with the monitoring of drug resistance mutations improves the quality of life of HIV-1 positive patients. The drug resistance mutation patterns and viral genotypes are currently analyzed by DNA sequencing of the virus in the plasma of patients. However, the virus compartmentalizes, and different T cell subsets may harbor distinct viral subsets. In this study, we compared the patterns of HIV distribution in cell-free (blood plasma) and cell-associated viruses (peripheral blood mononuclear cells, PBMCs) derived from ART-treated patients by using Sanger sequencing- and Next-Generation sequencing-based HIV assay. CD4⁺CD45RA⁻RO⁺ memory T-cells were isolated from PBMCs using a BD FACSAria instrument. HIV pol (protease and reverse transcriptase) was RT-PCR or PCR amplified from the plasma and the T-cell subset, respectively. Sequences were obtained using Sanger sequencing and Next-Generation Sequencing (NGS). Sanger sequences were aligned and edited using RECall software (beta v3.03). The Stanford HIV database was used to evaluate drug resistance mutations. Illumina MiSeq platform and HyDRA Web were used to generate and analyze NGS data, respectively. Our results show a high correlation between Sanger sequencing and NGS results. However, some major and minor drug resistance mutations were only observed by NGS, albeit at different frequencies. Analysis of low-frequency drugs resistance mutations and virus distribution in the blood compartments may provide information to allow a more sustainable response to therapy and better disease management.

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.

Comparison of an In Vitro Diagnostic Next-Generation Sequencing Assay with Sanger Sequencing for HIV-1 Genotypic Resistance Testing

The ability of next-generation sequencing (NGS) technologies to detect low frequency HIV-1 drug resistance mutations (DRMs) not detected by dideoxynucleotide Sanger sequencing has potential advantages for improved patient outcomes. We compared the performance of an in vitro diagnostic (IVD) NGS assay, the Sentosa SQ HIV genotyping assay for HIV-1 genotypic resistance testing, with Sanger sequencing on 138 protease/reverse transcriptase (RT) and 39 integrase sequences. The NGS assay used a 5% threshold for reporting low-frequency variants. The level of complete plus partial nucleotide sequence concordance between Sanger sequencing and NGS was 99.9%. Among the 138 protease/RT sequences, a mean of 6.4 DRMs was identified by both Sanger and NGS, a mean of 0.5 DRM was detected by NGS alone, and a mean of 0.1 DRM was detected by Sanger sequencing alone. Among the 39 integrase sequences, a mean of 1.6 DRMs was detected by both Sanger sequencing and NGS and a mean of 0.15 DRM was detected by NGS alone. Compared with Sanger sequencing, NGS estimated higher levels of resistance to one or more antiretroviral drugs for 18.2% of protease/RT sequences and 5.1% of integrase sequences. There was little evidence for technical artifacts in the NGS sequences, but the G-to-A hypermutation was detected in three samples. In conclusion, the IVD NGS assay evaluated in this study was highly concordant with Sanger sequencing. At the 5% threshold for reporting minority variants, NGS appeared to attain a modestly increased sensitivity for detecting low-frequency DRMs without compromising sequence accuracy.

Next-Generation Human Immunodeficiency Virus Sequencing for Patient Management and Drug Resistance Surveillance

High-quality, simplified, and low-cost human immunodeficiency virus (HIV) drug resistance tests that are able to provide timely actionable HIV resistance data at individual, population, and programmatic levels are needed to confront the emerging drug-resistant HIV epidemic. Next-generation sequencing technologies embedded in automated cloud-computing analysis environments are ideally suited for such endeavor. Whereas NGS can reduce costs over Sanger sequencing, automated analysis pipelines make NGS accessible to molecular laboratories regardless of the available bioinformatic skills. They can also produce highly structured, high-quality data that could be examined by healthcare officials and program managers on a real-time basis to allow timely public health action. Here we discuss the opportunities and challenges of such an approach.

Promises and pitfalls of Illumina sequencing for HIV resistance genotyping

Genetic sequencing ("genotyping") plays a critical role in the modern clinical management of HIV infection. This virus evolves rapidly within patients because of its error-prone reverse transcriptase and short generation time. Consequently, HIV variants with mutations that confer resistance to one or more antiretroviral drugs can emerge during sub-optimal treatment. There are now multiple HIV drug resistance interpretation algorithms that take the region of the HIV genome encoding the major drug targets as inputs; expert use of these algorithms can significantly improve to clinical outcomes in HIV treatment. Next-generation sequencing has the potential to revolutionize HIV resistance genotyping by lowering the threshold that rare but clinically significant HIV variants can be detected reproducibly, and by conferring improved cost-effectiveness in high-throughput scenarios. In this review, we discuss the relative merits and challenges of deploying the Illumina MiSeq instrument for clinical HIV genotyping.