Technical Validation of a Hepatitis C Virus Whole Genome Sequencing Assay for Detection of Genotype and Antiviral Resistance in the Clinical Pathway.

Choice of direct acting antiviral (DAA) therapy for Hepatitis C Virus (HCV) in the United Kingdom and similar settings usually requires knowledge of the genotype and, in some cases, antiviral resistance (AVR) profile of the infecting virus. To determine these, most laboratories currently use Sanger technology, but next-generation sequencing (NGS) offers potential advantages in throughput and accuracy. However, NGS poses unique technical challenges, which require idiosyncratic development and technical validation approaches. This applies particularly to virology, where sequence diversity is high and the amount of starting genetic material is low, making it difficult to distinguish real data from artifacts. We describe the development and technical validation of a sequence capture-based HCV whole genome sequencing (WGS) assay to determine viral genotype and AVR profile. We use clinical samples of known subtypes and viral loads, and simulated FASTQ datasets to validate the analytical performances of both the wet laboratory and bioinformatic pipeline procedures. We show high concordance of the WGS assay compared to current "gold standard" Sanger assays. Specificity was 92.3 and 96.1% for AVR and genotyping, respectively. Discordances were due to the inability of Sanger assays to assign the correct subtype or accurately call mixed drug-resistant variants. We show high repeatability and reproducibility with >99.8% sequence similarity between sequence runs as well as high precision for variant frequency detection at >98.8% in the 95th percentile. Post-sequencing bioinformatics quality control workflows allow the accurate distinction between mixed infections, cross-contaminants and recombinant viruses at a threshold of >5% for the minority population. The sequence capture-based HCV WGS assay is more accurate than legacy AVR and genotyping assays. The assay has now been implemented in the clinical pathway of England's National Health Service HCV treatment programs, representing the first validated HCV WGS pipeline in clinical service. The data generated will additionally provide granular national-level genomic information for public health policy making and support the WHO HCV elimination strategy.

Comparison of Next-Generation Sequencing Technologies for Comprehensive Assessment of Full-Length Hepatitis C Viral Genomes.

Affordable next-generation sequencing (NGS) technologies for hepatitis C virus (HCV) may potentially identify both viral genotype and resistance genetic motifs in the era of directly acting antiviral (DAA) therapies. This study compared the ability of high-throughput NGS methods to generate full-length, deep, HCV sequence data sets and evaluated their utility for diagnostics and clinical assessment. NGS methods using (i) unselected HCV RNA (metagenomics), (ii) preenrichment of HCV RNA by probe capture, and (iii) HCV preamplification by PCR implemented in four United Kingdom centers were compared. Metrics of sequence coverage and depth, quasispecies diversity, and detection of DAA resistance-associated variants (RAVs), mixed HCV genotypes, and other coinfections were compared using a panel of samples with different viral loads, genotypes, and mixed HCV genotypes/subtypes [geno(sub)types]. Each NGS method generated near-complete genome sequences from more than 90% of samples. Enrichment methods and PCR preamplification generated greater sequence depth and were more effective for samples with low viral loads. All NGS methodologies accurately identified mixed HCV genotype infections. Consensus sequences generated by different NGS methods were generally concordant, and majority RAVs were consistently detected. However, methods differed in their ability to detect minor populations of RAVs. Metagenomic methods identified human pegivirus coinfections. NGS provided a rapid, inexpensive method for generating whole HCV genomes to define infecting genotypes, RAVs, comprehensive viral strain analysis, and quasispecies diversity. Enrichment methods are particularly suited for high-throughput analysis while providing the genotype and information on potential DAA resistance.

An outbreak of high-level azithromycin resistant Neisseria gonorrhoeae in England.

OBJECTIVES: To investigate a potential outbreak of high-level azithromycin resistant (HL-AziR) gonococcal infections diagnosed in eight patients attending a sexual health clinic in Leeds, North England, between November 2014 and March 2015. METHODS: Eight cases of infection with gonococci exhibiting azithromycin minimum inhibitory concentrations (MICs) ≥256 mg/L were identified from patients in Leeds as part of the routine service provided by the Sexually Transmitted Bacteria Reference Unit. All patient records were reviewed to collate epidemiological and clinical information including evaluation of patient management. Whole-genome sequencing (WGS) was performed on seven gonococcal isolates to determine Neisseria gonorrhoeae multiantigen sequence type (NG-MAST), WGS comparison and mutations in the 23S rRNA genes. RESULTS: All patients were heterosexual (five male, three female) from a range of ethnic backgrounds and from the Leeds area. Three patients were linked by partner notification. All patients were infected at genital sites and two women had pharyngeal infection also. Six patients received the recommended first-line therapy for uncomplicated gonorrhoea, one was treated for pelvic inflammatory disease and one received spectinomycin followed later by ciprofloxacin. Test of cure was achieved in seven patients and confirmed successful eradication. All seven isolates sequenced were identical by NG-MAST and WGS comparison, and contained an A2143G mutation in all four 23S rRNA alleles. CONCLUSIONS: Epidemiological and microbiological investigations confirm that an outbreak of a gonococcal strain showing HL-AziR is ongoing in the North of England. Every effort should be made to identify and curtail dissemination of this strain as it presents a significant threat to the current recommended front-line dual therapy.

QSLiMFinder: improved short linear motif prediction using specific query protein data.

MOTIVATION: The sensitivity of de novo short linear motif (SLiM) prediction is limited by the number of patterns (the motif space) being assessed for enrichment. QSLiMFinder uses specific query protein information to restrict the motif space and thereby increase the sensitivity and specificity of predictions. RESULTS: QSLiMFinder was extensively benchmarked using known SLiM-containing proteins and simulated protein interaction datasets of real human proteins. Exploiting prior knowledge of a query protein likely to be involved in a SLiM-mediated interaction increased the proportion of true positives correctly returned and reduced the proportion of datasets returning a false positive prediction. The biggest improvement was seen if a short region of the query protein flanking the interaction site was known. AVAILABILITY AND IMPLEMENTATION: All the tools and data used in this study, including QSLiMFinder and the SLiMBench benchmarking software, are freely available under a GNU license as part of SLiMSuite, at: http://bioware.soton.ac.uk.

A critical analysis of the combined usage of protein localization prediction methods: Increasing the number of independent data sets can reduce the accuracy of predicted mitochondrial localization.

In the absence of a comprehensive experimentally derived mitochondrial proteome, several bioinformatic approaches have been developed to aid the identification of novel mitochondrial disease genes within mapped nuclear genetic loci. Often, many classifiers are combined to increase the sensitivity and specificity of the predictions. Here we show that the greatest sensitivity and specificity are obtained by using a combination of seven carefully selected classifiers. We also show that increasing the number of independent prediction methods can paradoxically decrease the accuracy of predicting mitochondrial localization. This approach will help to accelerate the identification of new mitochondrial disease genes by providing a principled way for the selection for combination of appropriate prediction methods of mitochondrial localization of proteins.

Pathogenic expansions of the SCA6 locus are associated with a common CACNA1A haplotype across the globe: founder effect or predisposing chromosome?

Spinocerebellar ataxia type 6 (SCA6) is a common cause of dominantly inherited ataxia due to an expansion of the CAG repeat in the CACNA1A gene. Affected individuals from the same population share a common haplotype, raising the possibility that most SCA6 cases have descended from a small number of common founders across the globe. To test this hypothesis, we carried out haplotype analysis on SCA6 families from Europe, South America and the Far East, including an established de novo SCA6 expansion. A core CACNA1A disease haplotype was found in affected individuals across the globe. This was also present in the unaffected father of the de novo case, suggesting that the shared chromosome predisposes to the CAG repeat expansion at the SCA6 locus. The SCA6 expansion lies within a CpG island, which could act as a cis-acting element predisposing to repeat expansion as for other CAG/CTG repeat diseases. Polymorphic variation in this region may explain the high-risk haplotype found in SCA6 families.