Harmonisation of in-silico next-generation sequencing based methods for diagnostics and surveillance.

Improvements in cost and speed of next generation sequencing (NGS) have provided a new pathway for delivering disease diagnosis, molecular typing, and detection of antimicrobial resistance (AMR). Numerous published methods and protocols exist, but a lack of harmonisation has hampered meaningful comparisons between results produced by different methods/protocols vital for global genomic diagnostics and surveillance. As an exemplar, this study evaluated the sensitivity and specificity of five well-established in-silico AMR detection software where the genotype results produced from running a panel of 436 Escherichia coli were compared to their AMR phenotypes, with the latter used as gold-standard. The pipelines exploited previously known genotype-phenotype associations. No significant differences in software performance were observed. As a consequence, efforts to harmonise AMR predictions from sequence data should focus on: (1) establishing universal minimum to assess performance thresholds (e.g. a control isolate panel, minimum sensitivity/specificity thresholds); (2) standardising AMR gene identifiers in reference databases and gene nomenclature; (3) producing consistent genotype/phenotype correlations. The study also revealed limitations of in-silico technology on detecting resistance to certain antimicrobials due to lack of specific fine-tuning options in bioinformatics tool or a lack of representation of resistance mechanisms in reference databases. Lastly, we noted user friendliness of tools was also an important consideration. Therefore, our recommendations are timely for widespread standardisation of bioinformatics for genomic diagnostics and surveillance globally.

Prevalence of hepatitis E virus in slaughter-age pigs in Scotland.

The prevalence of anti-HEV isotype-specific antibodies and viraemia were investigated in serum samples collected from slaughter-age pigs (aged 22-24 weeks) from 23 farms in Scotland. Of 176 serum samples tested, 29·0% (n = 51) were anti-HEV IgG positive, 36·9% (n = 65) anti-HEV IgA positive and 29·0% (n = 51) anti-HEV IgM positive. Overall seroprevalence (anti-HEV IgG+ and/or IgA+ and/or IgM+) was 61·4% (n = 108). HEV RNA was detected in 72/162 serum samples (44·4%). Partial sequence of ORF2 (98 nt) was obtained from eight HEV RNA-positive samples and phylogenetic analysis confirmed that they were all of genotype 3. This is the first report on the prevalence of HEV in pigs in Scotland. Given the increasing incidence of locally acquired HEV infection in the UK, evidence that HEV is a foodborne zoonosis emphasizes the need for surveillance in pigs.

Hemorragia intracerebral recurrente en amiloidosis primaria / Recurrent intracereberal haemorrhage in primary amyloidosis

No disponible

Development of a DNA microarray for simultaneous detection and genotyping of lyssaviruses.

The lyssavirus genus of the Rhabdoviridae family of viruses includes 7 genotypes and several non-assigned isolates. The source of lyssavirus infections is diverse with numerous reservoirs in a wide geographical area. In many parts of the world reservoir hosts can potentially be carrying one of several lyssavirus strains and possibly new divergent isolates await discovery. Accordingly, generic detection methods are required to be able to detect and discriminate all lyssaviruses and identify new divergent isolates. Here we have allied a sequence-independent amplification method to microarray to enable simultaneous detection and identification of all lyssavirus genotypes. To do so, lyssavirus RNA was converted to cDNA and amplified in a random PCR, labelled and hybridized to probes on the microarray chip before being statistically analysed. The probes were to a 405 bp region of the relatively conserved N gene. Here we demonstrate a microarray capable of detecting each of the seven lyssavirus genotypes. The random amplification of lyssavirus RNA and the numerous oligonucleotide probes on the microarray chip also offer the potential to detect novel lyssaviruses.