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.

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.

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.

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.

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.

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.