Comparison of illumina and 454 deep sequencing in participants failing raltegravir-based antiretroviral therapy

Rate of response to initial antiretroviral therapy according to level of pre-existing HIV-1 drug resistance detected by next-generation sequencing in the strategic timing of antiretroviral treatment (START) study

OBJECTIVES

The main objective of this analysis was to evaluate the impact of pre-existing drug resistance by next-generation sequencing (NGS) on the risk of treatment failure (TF) of first-line regimens in participants enrolled in the START study.

METHODS

Stored plasma from participants with entry HIV RNA >1000 copies/mL were analysed using NGS (llumina MiSeq). Pre-existing drug resistance was defined using the mutations considered by the Stanford HIV Drug Resistance Database (HIVDB v8.6) to calculate the genotypic susceptibility score (GSS, estimating the number of active drugs) for the first-line regimen at the detection threshold windows of >20%, >5%, and >2% of the viral population. Survival analysis was conducted to evaluate the association between the GSS and risk of TF (viral load >200 copies/mL plus treatment change).

RESULTS

Baseline NGS data were available for 1380 antiretroviral therapy (ART)-naïve participants enrolled over 2009-2013. First-line ART included a non-nucleoside reverse transcriptase inhibitor (NNRTI) in 976 (71%), a boosted protease inhibitor in 297 (22%), or an integrase strand transfer inhibitor in 107 (8%). The proportions of participants with GSS <3 were 7% for >20%, 10% for >5%, and 17% for the >2% thresholds, respectively. The adjusted hazard ratio of TF associated with a GSS of 0-2.75 versus 3 in the subset of participants with mutations detected at the >2% threshold was 1.66 (95% confidence interval 1.01-2.74; p = 0.05) and 2.32 (95% confidence interval 1.32-4.09; p = 0.003) after restricting the analysis to participants who started an NNRTI-based regimen.

CONCLUSIONS

Up to 17% of participants initiated ART with a GSS <3 on the basis of NGS data. Minority variants were predictive of TF, especially for participants starting NNRTI-based regimens.

Primary resistance to integrase strand transfer inhibitors in Spain using ultrasensitive HIV-1 genotyping

BACKGROUND

Transmission of resistance mutations to integrase strand transfer inhibitors (INSTIs) in HIV-infected patients may compromise the efficacy of first-line antiretroviral regimens currently recommended worldwide. Continued surveillance of transmitted drug resistance (TDR) is thus warranted.

OBJECTIVES

We evaluated the rates and effects on virological outcomes of TDR in a 96 week prospective multicentre cohort study of ART-naive HIV-1-infected subjects initiating INSTI-based ART in Spain between April 2015 and December 2016.

METHODS

Pre-ART plasma samples were genotyped for integrase, protease and reverse transcriptase resistance using Sanger population sequencing or MiSeq™ using a ≥ 20% mutant sensitivity cut-off. Those present at 1%-19% of the virus population were considered to be low-frequency variants.

RESULTS

From a total of 214 available samples, 173 (80.8%), 210 (98.1%) and 214 (100.0%) were successfully amplified for integrase, reverse transcriptase and protease genes, respectively. Using a Sanger-like cut-off, the overall prevalence of any TDR, INSTI-, NRTI-, NNRTI- and protease inhibitor (PI)-associated mutations was 13.1%, 1.7%, 3.8%, 7.1% and 0.9%, respectively. Only three (1.7%) subjects had INSTI TDR (R263K, E138K and G163R), while minority variants with integrase TDR were detected in 9.6% of subjects. There were no virological failures during 96 weeks of follow-up in subjects harbouring TDR as majority variants.

CONCLUSIONS

Transmitted INSTI resistance remains rare in Spain and, to date, is not associated with virological failure to first-line INSTI-based regimens.

Impact of Human Immunodeficiency Virus Type 1 Minority Variants on the Virus Response to a Rilpivirine-Based First-line Regimen

Background

Minority resistant variants of human immunodeficiency virus type 1 (HIV-1) could influence the virological response to treatment based on nonnucleoside reverse transcriptase inhibitors (NNRTIs). Data on minority rilpivirine-resistant variants are scarce. This study used next-generation sequencing (NGS) to identify patients harboring minority resistant variants to nucleos(t)ide reverse transcriptase inhibitors and NNRTIs and to assess their influence on the virological response (VR).

Methods

All the subjects, 541 HIV-1-infected patients started a first-line regimen containing rilpivirine. VR was defined as a HIV-1 RNA load <50 copies/mL at month 6 with continued suppression at month 12. NGS was performed at baseline (retrospectively) on the 454 GS-FLX platform (Roche).

Results

NGS revealed resistance-associated mutations accounting for 1% to <5% of variants in 17.2% of samples, for 5%-20% in 5.7% of samples, and for >20% in 29% of samples. We identified 43 (8.8%) and 36 (7.4%) patients who harbored rilpivirine-resistant variants with a 1% sensitivity threshold according to the French National Agency for Research on AIDS and Viral Hepatitis and Stanford algorithms, respectively. The VR was 96.9% at month 12. Detection of minority rilpivirine resistant variants was not associated with virological failure (VF). Multivariate analysis indicated that VF at month 12 was associated with a CD4 count <250 cells/µL at baseline, a slower decrease in viral load at month 3, and rilpivirine resistance at baseline using the Stanford algorithm with a 20% threshold.

Conclusions

Minority resistant variants had no impact on the VR of treatment-naive patients to a rilpivirine-based regimen.

Prevalence and clinical impact of minority resistant variants in patients failing an integrase inhibitor-based regimen by ultra-deep sequencing

Background

Integrase strand transfer inhibitors (INSTIs) are recommended by international guidelines as first-line therapy in antiretroviral-naive and -experienced HIV-1-infected patients.

Objectives

This study aimed at evaluating the prevalence at failure of INSTI-resistant variants and the impact of baseline minority resistant variants (MiRVs) on the virological response to an INSTI-based regimen.

Methods

Samples at failure of 134 patients failing a raltegravir-containing (n = 65), an elvitegravir-containing (n = 20) or a dolutegravir-containing (n = 49) regimen were sequenced by Sanger sequencing and ultra-deep sequencing (UDS). Baseline samples of patients with virological failure (VF) (n = 34) and of those with virological success (VS) (n = 31) under INSTI treatment were sequenced by UDS. Data were analysed using the SmartGene platform, and resistance was interpreted according to the ANRS algorithm version 27.

Results

At failure, the prevalence of at least one INSTI-resistant variant was 39.6% by Sanger sequencing and 57.5% by UDS, changing the interpretation of resistance in 17/134 (13%) patients. Among 53 patients harbouring at least one resistance mutation detected by both techniques, the most dominant INSTI resistance mutations were N155H (45%), Q148H/K/R (23%), T97A (19%) and Y143C (11%). There was no difference in prevalence of baseline MiRVs between patients with VF and those with VS. MiRVs found at baseline in patients with VF were not detected at failure either in majority or minority mutations.

Conclusions

UDS is more sensitive than Sanger sequencing at detecting INSTI MiRVs at treatment failure. The presence of MiRVs at failure could be important to the decision to switch to other INSTIs. However, there was no association between the presence of baseline MiRVs and the response to INSTI-based therapies in our study.

HIV-1 genotypic resistance testing using the Vela automated next-generation sequencing platform

Objectives

To evaluate the diagnostic performance of the Vela next-generation sequencing (NGS) system in conjunction with the Sentosa SQ HIV Genotyping Assay for genotyping HIV-1.

Methods

Plasma RNA was extracted and templates prepared with the Sentosa SX instrument before sequencing the HIV-1 polymerase on the Sentosa SQ301 Sequencer (PGM IonTorrent). The Vela NGS System was compared with direct sequencing and the 454 GS-FLX (Roche) and MiSeq (Illumina) systems for genotypic resistance testing on clinical samples.

Results

The Vela NGS system detected majority resistance mutations in subtype B and CRF02-AG samples at 500 copies/mL and minority variants with a sensitivity of 5% at 100 000 copies/mL. The Vela NGS system and direct sequencing identified resistance mutations with 97% concordance in 46 clinical samples. Vela identified 1/20 of the 1%-5% mutations identified by 454, 5/12 of the 5%-20% mutations and 60/61 of the >20% mutations. Vela identified 3/14 of the 1%-5% mutations identified by MiSeq, 0/2 of the 5%-20% mutations and 47/47 of the >20% mutations. The resistance mutation quantifications by Vela and 454 were concordant (bias: 2.31%), as were those by Vela and MiSeq (bias: 1.06%).

Conclusions

The Vela NGS system provides automated nucleic acid extraction, PCR reagent distribution, library preparation and bioinformatics analysis. The analytical performance was very good when compared with direct sequencing, but was less sensitive than two other NGS platforms for detecting minority variants.

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.

Capturing sequence diversity in metagenomes with comprehensive and scalable probe design

Metagenomic sequencing has the potential to transform microbial detection and characterization, but new tools are needed to improve its sensitivity. Here we present CATCH, a computational method to enhance nucleic acid capture for enrichment of diverse microbial taxa. CATCH designs optimal probe sets, with a specified number of oligonucleotides, that achieve full coverage of, and scale well with, known sequence diversity. We focus on applying CATCH to capture viral genomes in complex metagenomic samples. We design, synthesize, and validate multiple probe sets, including one that targets the whole genomes of the 356 viral species known to infect humans. Capture with these probe sets enriches unique viral content on average 18-fold, allowing us to assemble genomes that could not be recovered without enrichment, and accurately preserves within-sample diversity. We also use these probe sets to recover genomes from the 2018 Lassa fever outbreak in Nigeria and to improve detection of uncharacterized viral infections in human and mosquito samples. The results demonstrate that CATCH enables more sensitive and cost-effective metagenomic sequencing.

Nanopore-based detection and characterization of yam viruses

We here assessed the capability of the MinION sequencing approach to detect and characterize viruses infecting a water yam plant. This sequencing platform consistently revealed the presence of several plant virus species, including Dioscorea bacilliform virus, Yam mild mosaic virus and Yam chlorotic necrosis virus. A potentially novel ampelovirus was also detected by a complimentary Illumina sequencing approach. The full-length genome sequence of yam chlorotic necrosis virus was determined using Sanger sequencing, which enabled determination of the coverage and sequencing accuracy of the MinION technology. Whereas the total mean sequencing error rate of yam chlorotic necrosis virus-related MinION reads was 11.25%, we show that the consensus sequence obtained either by de novo assembly or after mapping the MinION reads on the virus genomic sequence was >99.8% identical with the Sanger-derived reference sequence. From the perspective of potential plant disease diagnostic applications of MinION sequencing, these degrees of sequencing accuracy demonstrate that the MinION approach can be used to both reliably detect and accurately sequence nearly full-length positive-sense single-strand polyadenylated RNA plant virus genomes.

Performance comparison of deep sequencing platforms for detecting HIV-1 variants in the pol gene

The present study compares the performances of an in-house sequencing protocol developed on MiSeq, the Sanger method, and the 454 GS-FLX for detecting and quantifying drug-resistant mutations (DRMs) in the human immunodeficiency virus polymerase gene (reverse transcriptase [RT] and protease [PR]). MiSeq sequencing identified all the resistance mutations detected by bulk sequencing (n = 84). Both the MiSeq and 454 GS-FLX platforms identified 67 DRMs in the RT and PR regions, but a further 25 DRMs were identified by only one or other of them. Pearson's analysis showed good concordance between the percentage of drug-resistant variants determined by MiSeq and 454 GS-FLX sequencing (ρ = .77, P < .0001). The MiSeq platform is as accurate as the 454 GS-FLX Roche system for determining RT and PR DRMs and could be used for monitoring human immunodeficiency virus type 1 drug resistance.

Efficient In Vivo Liver-Directed Gene Editing Using CRISPR/Cas9

In vivo tissue-specific genome editing at the desired loci is still a challenge. Here, we report that AAV9-delivery of truncated guide RNAs (gRNAs) and Cas9 under the control of a computationally designed hepatocyte-specific promoter lead to liver-specific and sequence-specific targeting in the mouse factor IX (F9) gene. The efficiency of in vivo targeting was assessed by T7E1 assays, site-specific Sanger sequencing, and deep sequencing of on-target and putative off-target sites. Though AAV9 transduction was apparent in multiple tissues and organs, Cas9 expression was restricted mainly to the liver, with only minimal or no expression in other non-hepatic tissues. Consequently, the insertions and deletion (indel) frequency was robust in the liver (up to 50%) in the desired target loci of the F9 gene, with no evidence of targeting in other organs or other putative off-target sites. This resulted in a substantial loss of FIX activity and the emergence of a bleeding phenotype, consistent with hemophilia B. The in vivo efficacy of the truncated gRNA was as high as that of full-length gRNA. Cas9 expression was transient in neonates, representing an attractive "hit-and-run" paradigm. Our findings have potentially broad implications for somatic gene targeting in the liver using the CRISPR/Cas9 platform.

Current and emerging two-drug approaches for HIV-1 therapy in ART-naïve and ART-experienced, virologically suppressed patients

INTRODUCTION

Current guidelines recommend a 2-drug antiretroviral regimen as an alternative to triple antiretroviral therapy (ART) in selected patients to reduce long-term toxicity and costs.

AREAS COVERED

This review is intended to provide insight into the efficacy, safety and tolerability of 2-drug versus 3-drug ART in naïve and in treatment-experienced virologically-suppressed patients.

EXPERT OPINION

Dual therapy regimens are not feasible in HBV-coinfected individuals and should not be applied during pregnancy. Positive data on 2-drug ART in drug naïve patients are still limited, while, in virologically-suppressed individuals, several regimens have shown non-inferiority as compared to 3-drug regimens. The strongest evidence of efficacy applies to ritonavir-boosted PI regimens combined with lamivudine and to dolutegravir with rilpivirine. Dual therapies showed improved renal function and bone mineral density over tenofovir disoproxil fumarate-based 3-drug regimens. There are also great expectations for ongoing phase 3 trials testing dolutegravir with lamivudine. New and future single tablet co-formulations of dual regimens are expected to improve their suitability. Despite the lack of comparison with tenofovir alafenamide-based 3-drug regimens, the 2-drug regimens showing consistent non-inferiority and safety versus 3-drug regimens will challenge the current paradigm of 3-drug ART.

The Role of HIV-1 Drug-Resistant Minority Variants in Treatment Failure

Human immunodeficiency virus type 1 (HIV-1) drug resistance genotyping is recommended to help in the selection of antiretroviral therapy and to prevent virologic failure. There are several ultrasensitive assays able to detect HIV-1 drug-resistance minority variants (DRMVs) not detectable by standard population sequencing-based HIV genotyping assays. Presence of these DRMVs has been shown to be clinically relevant, but its impact does not appear to be uniform across drug classes. In this review, we summarize key evidence for the clinical impact of DRMVs across drug classes for both antiretroviral treatment-naive and antiretroviral treatment-experienced patients, and highlight areas where more supporting evidence is needed.

Large-scale SNP screenings identify markers linked with GCRV resistant traits through transcriptomes of individuals and cell lines in Ctenopharyngodon idella

Grass carp (Ctenopharyngodon idella) is an important economic species in freshwater aquaculture and its industry has been confined due to variety degeneration and frequent diseases. Marker-assisted selection is a feasible method for selective breeding of new varieties. Transcriptome data have greatly facilitated high-throughput single nucleotide polymorphism (SNP) marker discovery and phenotype association study. In this study, we gained a total of 25,981 and 5,775 high quality SNPs in two transcriptomes from individuals and cell lines, respectively. Comparative transcriptome analysis identified 413 and 832 grass carp reovirus (GCRV)-resistant-association SNPs as well as 1,381 and 1,606 GCRV-susceptible-association SNPs in individuals and cell lines, respectively. Integrated analysis indicated 22 genes with single SNP share common resistant/susceptible traits in two transcriptomes. Furthermore, we infected grass carp with GCRV, genotyping and association analyses were performed, and 9 in 22 SNPs were confirmed by PCR-RFLP. Meanwhile, mRNA expression profiles of 6 genes containing confirmed SNPs were examined by qRT-PCR. The results demonstrated that mRNA expressions were significant differences in resistant/susceptible individuals and cell lines. The present study develops an important strategy for high throughput screening of phenotype association genetic markers and the results will serve in grass carp breeding for GCRV resistance.

Challenges in the analysis of viral metagenomes

Genome sequencing technologies continue to develop with remarkable pace, yet analytical approaches for reconstructing and classifying viral genomes from mixed samples remain limited in their performance and usability. Existing solutions generally target expert users and often have unclear scope, making it challenging to critically evaluate their performance. There is a growing need for intuitive analytical tooling for researchers lacking specialist computing expertise and that is applicable in diverse experimental circumstances. Notable technical challenges have impeded progress; for example, fragments of viral genomes are typically orders of magnitude less abundant than those of host, bacteria, and/or other organisms in clinical and environmental metagenomes; observed viral genomes often deviate considerably from reference genomes demanding use of exhaustive alignment approaches; high intrapopulation viral diversity can lead to ambiguous sequence reconstruction; and finally, the relatively few documented viral reference genomes compared to the estimated number of distinct viral taxa renders classification problematic. Various software tools have been developed to accommodate the unique challenges and use cases associated with characterizing viral sequences; however, the quality of these tools varies, and their use often necessitates computing expertise or access to powerful computers, thus limiting their usefulness to many researchers. In this review, we consider the general and application-specific challenges posed by viral sequencing and analysis, outline the landscape of available tools and methodologies, and propose ways of overcoming the current barriers to effective analysis.

Antibiotic Resistome: Improving Detection and Quantification Accuracy for Comparative Metagenomics

The unprecedented rise of life-threatening antibiotic resistance (AR), combined with the unparalleled advances in DNA sequencing of genomes and metagenomes, has pushed the need for in silico detection of the resistance potential of clinical and environmental metagenomic samples through the quantification of AR genes (i.e., genes conferring antibiotic resistance). Therefore, determining an optimal methodology to quantitatively and accurately assess AR genes in a given environment is pivotal. Here, we optimized and improved existing AR detection methodologies from metagenomic datasets to properly consider AR-generating mutations in antibiotic target genes. Through comparative metagenomic analysis of previously published AR gene abundance in three publicly available metagenomes, we illustrate how mutation-generated resistance genes are either falsely assigned or neglected, which alters the detection and quantitation of the antibiotic resistome. In addition, we inspected factors influencing the outcome of AR gene quantification using metagenome simulation experiments, and identified that genome size, AR gene length, total number of metagenomics reads and selected sequencing platforms had pronounced effects on the level of detected AR. In conclusion, our proposed improvements in the current methodologies for accurate AR detection and resistome assessment show reliable results when tested on real and simulated metagenomic datasets.

Identification of minority resistance mutations in the HIV-1 integrase coding region using next generation sequencing

BACKGROUND

The current widely applied standard method to screen for HIV-1 genotypic resistance is based on Sanger population sequencing (Sseq), which does not allow for the identification of minority variants (MVs) below the limit of detection for the Sseq-method in patients receiving integrase strand-transfer inhibitors (INSTI). Next generation sequencing (NGS) has facilitated the detection of MVs at a much deeper level than Sseq.

OBJECTIVES

Here, we compared Illumina MiSeq and Sseq approaches to evaluate the detection of MVs involved in resistance to the three commonly used INSTI: raltegravir (RAL), elvitegravir (EVG) and dolutegravir (DTG).

STUDY DESIGN

NGS and Sseq were used to analyze RT-PCR products of the HIV-1 integrase coding region from six patients and in serial samples from two patients. NGS sequences were assembled and analyzed using the low frequency variant detection (LFVDT) tool in CLC genomic workbench.

RESULTS

Sseq detected INSTI resistance and accessory mutations in three of the patients (called INSTI Res+), while no resistance or accessory mutations were detected in the remaining three patients (called INSTI Res-). Additional INSTI resistance and/or accessory mutations were detected by NGS analysis of integrase sequences from all three INSTI Res+ and one INSTI Res- patient.

CONCLUSION

Our observations suggested that NGS demonstrated a higher sensitivity than sSEQ in the identification of INSTI relevant MVs both in patients at treatment baseline and in patients receiving INSTI therapy. Thus NGS can be a valuable tool in monitoring of antiretroviral minority resistance in patients receiving INSTI therapy.

QQ-SNV: single nucleotide variant detection at low frequency by comparing the quality quantiles

Background

Next generation sequencing enables studying heterogeneous populations of viral infections. When the sequencing is done at high coverage depth (“deep sequencing”), low frequency variants can be detected. Here we present QQ-SNV (http://sourceforge.net/projects/qqsnv), a logistic regression classifier model developed for the Illumina sequencing platforms that uses the quantiles of the quality scores, to distinguish true single nucleotide variants from sequencing errors based on the estimated SNV probability. To train the model, we created a dataset of an in silico mixture of five HIV-1 plasmids. Testing of our method in comparison to the existing methods LoFreq, ShoRAH, and V-Phaser 2 was performed on two HIV and four HCV plasmid mixture datasets and one influenza H1N1 clinical dataset.

Results

For default application of QQ-SNV, variants were called using a SNV probability cutoff of 0.5 (QQ-SNV_D). To improve the sensitivity we used a SNV probability cutoff of 0.0001 (QQ-SNV_HS). To also increase specificity, SNVs called were overruled when their frequency was below the 80^th percentile calculated on the distribution of error frequencies (QQ-SNV_HS-P80).

When comparing QQ-SNV versus the other methods on the plasmid mixture test sets, QQ-SNV_D performed similarly to the existing approaches. QQ-SNV_HS was more sensitive on all test sets but with more false positives. QQ-SNV_HS-P80 was found to be the most accurate method over all test sets by balancing sensitivity and specificity. When applied to a paired-end HCV sequencing study, with lowest spiked-in true frequency of 0.5 %, QQ-SNV_HS-P80 revealed a sensitivity of 100 % (vs. 40–60 % for the existing methods) and a specificity of 100 % (vs. 98.0–99.7 % for the existing methods). In addition, QQ-SNV required the least overall computation time to process the test sets.

Finally, when testing on a clinical sample, four putative true variants with frequency below 0.5 % were consistently detected by QQ-SNV_HS-P80 from different generations of Illumina sequencers.

Conclusions

We developed and successfully evaluated a novel method, called QQ-SNV, for highly efficient single nucleotide variant calling on Illumina deep sequencing virology data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0812-9) contains supplementary material, which is available to authorized users.

Next-generation sequencing (NGS) for assessment of microbial water quality: current progress, challenges, and future opportunities

Water quality is an emergent property of a complex system comprised of interacting microbial populations and introduced microbial and chemical contaminants. Studies leveraging next-generation sequencing (NGS) technologies are providing new insights into the ecology of microbially mediated processes that influence fresh water quality such as algal blooms, contaminant biodegradation, and pathogen dissemination. In addition, sequencing methods targeting small subunit (SSU) rRNA hypervariable regions have allowed identification of signature microbial species that serve as bioindicators for sewage contamination in these environments. Beyond amplicon sequencing, metagenomic and metatranscriptomic analyses of microbial communities in fresh water environments reveal the genetic capabilities and interplay of waterborne microorganisms, shedding light on the mechanisms for production and biodegradation of toxins and other contaminants. This review discusses the challenges and benefits of applying NGS-based methods to water quality research and assessment. We will consider the suitability and biases inherent in the application of NGS as a screening tool for assessment of biological risks and discuss the potential and limitations for direct quantitative interpretation of NGS data. Secondly, we will examine case studies from recent literature where NGS based methods have been applied to topics in water quality assessment, including development of bioindicators for sewage pollution and microbial source tracking, characterizing the distribution of toxin and antibiotic resistance genes in water samples, and investigating mechanisms of biodegradation of harmful pollutants that threaten water quality. Finally, we provide a short review of emerging NGS platforms and their potential applications to the next generation of water quality assessment tools.

Performance assessment of the Illumina massively parallel sequencing platform for deep sequencing analysis of viral minority variants

Massively parallel sequencing (MPS) technology has opened new avenues to study viral dynamics and treatment-induced resistance mechanisms of infections such as human immunodeficiency virus (HIV) and hepatitis C virus (HCV). Whereas the Roche/454 platform has been used widely for the detection of low-frequent drug resistant variants, more recently developed short-read MPS technologies have the advantage of delivering a higher sequencing depth at a lower cost per sequenced base. This study assesses the performance characteristics of Illumina MPS technology for the characterization of genetic variability in viral populations by deep sequencing. The reported results from MPS experiments comprising HIV and HCV plasmids demonstrate that a 0.5-1% lower limit of detection can be achieved readily with Illumina MPS while retaining good accuracy also at low frequencies. Deep sequencing of a set of clinical samples (12 HIV and 9 HCV patients), designed at a similar budget for both MPS platforms, reveals a comparable lower limit of detection for Illumina and Roche/454. Finally, this study shows the possibility to apply Illumina's paired-end sequencing as a strategy to assess linkage between different mutations identified in individual viral subspecies. These results support the use of Illumina as another MPS platform of choice for deep sequencing of viral minority species.

Evaluation of GS Junior and MiSeq next-generation sequencing technologies as an alternative to Trugene population sequencing in the clinical HIV laboratory

Population HIV-1 sequencing is currently the method of choice for the identification and follow-up of HIV-1 antiretroviral drug resistance. It has limited sensitivity and results in a consensus sequence showing the most prevalent nucleotide per position. Moreover concomitant sequencing and interpretation of the results for several samples together is laborious and time consuming. In this study, the practical use of GS Junior and MiSeq bench-top next generation sequencing (NGS) platforms as an alternative to Trugene Sanger-based population sequencing in the clinical HIV laboratory was assessed. DeepChek(®)-HIV TherapyEdge software was used for processing all the protease and reverse transcriptase sequences and for resistance interpretation. Plasma samples from nine HIV-1 carriers, representing the major HIV-1 subtypes in Israel, were compared. The total number of amino acid substitutions identified in the nine samples by GS Junior (232 substitutions) and MiSeq (243 substitutions) was similar and higher than Trugene (181 substitutions), emphasizing the advantage of deep sequencing on population sequencing. More than 80% of the identified substitutions were identical between the GS Junior and MiSeq platforms, most of which (184 of 199) at similar frequency. Low abundance substitutions accounted for 20.9% of the MiSeq and 21.9% of the GS Junior output, the majority of which were not detected by Trugene. More drug resistance mutations were identified by both the NGS platforms, primarily, but not only, at low abundance. In conclusion, in combination with DeepChek, both GS Junior and MiSeq were found to be more sensitive than Trugene and adequate for HIV-1 resistance analysis in the clinical HIV laboratory.

Retroviral vectors for analysis of viral mutagenesis and recombination

Retrovirus population diversity within infected hosts is commonly high due in part to elevated rates of replication, mutation, and recombination. This high genetic diversity often complicates the development of effective diagnostics, vaccines, and antiviral drugs. This review highlights the diverse vectors and approaches that have been used to examine mutation and recombination in retroviruses. Retroviral vectors for these purposes can broadly be divided into two categories: those that utilize reporter genes as mutation or recombination targets and those that utilize viral genes as targets of mutation or recombination. Reporter gene vectors greatly facilitate the detection, quantification, and characterization of mutants and/or recombinants, but may not fully recapitulate the patterns of mutagenesis or recombination observed in native viral gene sequences. In contrast, the detection of mutations or recombination events directly in viral genes is more biologically relevant but also typically more challenging and inefficient. We will highlight the advantages and disadvantages of the various vectors and approaches used as well as propose ways in which they could be improved.

Short communication: HIV-1 gag genetic variation in a single acutely infected participant defined by high-resolution deep sequencing

Acute HIV-1 infection is characterized by the rapid generation of highly diverse genetic variants to adapt to the new host environment. Understanding the dynamics of viral genetic variation at this stage of infection is critical for vaccine design efforts and early drug treatment. Here, using a high-resolution deep sequencing approach targeting the HIV-1 gag region, we reveal very early immune pressure with dramatic subpopulation shifts in a single acutely infected participant providing further insight into the genetic dynamics of acute HIV-1 infection.