Streptococcus pneumoniae typically express one of 92 serologically distinct capsule polysaccharide (cps) types (serotypes). Some of these serotypes are closely related to each other; using the commercially available typing antisera, these are assigned to common serogroups containing types that show cross-reactivity. In this serotyping scheme, factor antisera are used to allocate serotypes within a serogroup, based on patterns of reactions. This serotyping method is technically demanding, requires considerable experience and the reading of the results can be subjective. This study describes the analysis of the S. pneumoniae capsular operon genetic sequence to determine serotype distinguishing features and the development, evaluation and verification of an automated whole genome sequence (WGS)-based serotyping bioinformatics tool, PneumoCaT (Pneumococcal Capsule Typing). Initially, WGS data from 871 S. pneumoniae isolates were mapped to reference cps locus sequences for the 92 serotypes. Thirty-two of 92 serotypes could be unambiguously identified based on sequence similarities within the cps operon. The remaining 60 were allocated to one of 20 ‘genogroups’ that broadly correspond to the immunologically defined serogroups. By comparing the cps reference sequences for each genogroup, unique molecular differences were determined for serotypes within 18 of the 20 genogroups and verified using the set of 871 isolates. This information was used to design a decision-tree style algorithm within the PneumoCaT bioinformatics tool to predict to serotype level for 89/94 (92 + 2 molecular types/subtypes) from WGS data and to serogroup level for serogroups 24 and 32, which currently comprise 2.1% of UK referred, invasive isolates submitted to the National Reference Laboratory (NRL), Public Health England (June 2014–July 2015). PneumoCaT was evaluated with an internal validation set of 2065 UK isolates covering 72/92 serotypes, including 19 non-typeable isolates and an external validation set of 2964 isolates from Thailand (n = 2,531), USA (n = 181) and Iceland (n = 252). PneumoCaT was able to predict serotype in 99.1% of the typeable UK isolates and in 99.0% of the non-UK isolates. Concordance was evaluated in UK isolates where further investigation was possible; in 91.5% of the cases the predicted capsular type was concordant with the serologically derived serotype. Following retesting, concordance increased to 99.3% and in most resolved cases (97.8%; 135/138) discordance was shown to be caused by errors in original serotyping. Replicate testing demonstrated that PneumoCaT gave 100% reproducibility of the predicted serotype result. In summary, we have developed a WGS-based serotyping method that can predict capsular type to serotype level for 89/94 serotypes and to serogroup level for the remaining four. This approach could be integrated into routine typing workflows in reference laboratories, reducing the need for phenotypic immunological testing.

BackgroundDuring a substantial elevation in scarlet fever (SF) notifications in 2014 a national genomic study was undertaken of Streptococcus pyogenes (Group A Streptococci, GAS) isolates from patients with SF with comparison to isolates from patients with invasive disease (iGAS) to test the hypotheses that the increase in SF was due to either the introduction of one or more new/emerging strains in the population in England or the transmission of a known genetic element through the population of GAS by horizontal gene transfer (HGT) resulting in infections with an increased likelihood of causing SF. Isolates were collected to provide geographical representation, for approximately 5% SF isolates from each region from 1st April 2014 to 18th June 2014. Contemporaneous iGAS isolates for which genomic data were available were included for comparison. Data were analysed in order to determine emm gene sequence type, phylogenetic lineage and genomic clade representation, the presence of known prophage elements and the presence of genes known to confer pathogenicity and resistance to antibiotics.Results555 isolates were analysed, 303 from patients with SF and 252 from patients with iGAS. Isolates from patients with SF were of multiple distinct emm sequence types and phylogenetic lineages. Prior to data normalisation, emm3 was the predominant type (accounting for 42.9% of SF isolates, 130/303 95%CI 37.5–48.5; 14.7% higher than the percentage of emm3 isolates found in the iGAS isolates). Post-normalisation emm types, 4 and 12, were found to be over-represented in patients with SF versus iGAS (p < 0.001). A single gene, ssa, was over-represented in isolates from patients with SF. No single phage was found to be over represented in SF vs iGAS. However, a “meta-ssa” phage defined by the presence of :315.2, SPsP6, MGAS10750.3 or HK360ssa, was found to be over represented. The HKU360.vir phage was not detected yet the HKU360.ssa phage was present in 43/63 emm12 isolates but not found to be over-represented in isolates from patients with SF.ConclusionsThere is no evidence that the increased number of SF cases was a strain-specific or known mobile element specific phenomenon, as the increase in SF cases was associated with multiple lineages of GAS.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3603-z) contains supplementary material, which is available to authorized users.

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.

(1); one isolate had VIM-2 and IMP-18, and 7 carried no metallo-beta-lactamase (MBL) gene. Single nucleotide polymorphism analysis divided the isolates into distinct clusters; the NDM-1 isolate was an outlier, and the IMP isolates and 6/7 MBL-negative isolates clustered separately from the main set of 73 VIM-2 isolates. Within the VIM-2 set, there were at least 3 distinct clusters, including a tightly clustered set of isolates from 3 hospital laboratories consistent with an outbreak from a single introduction that was quickly brought under control and a much broader set dominated by isolates from a long-running outbreak in a London hospital likely seeded from an environmental source, requiring different control measures; isolates from 7 other hospital laboratories in London and southeast England were also included. Bayesian evolutionary analysis indicated that all the isolates shared a common ancestor dating back ϳ50 years (1960s), with the main VIM-2 set separating approximately 20 to 30 years ago. Accessory gene profiling revealed blocks of genes associated with particular clusters, with some having high similarity (>95%) to bacteriophage genes. WGS of widely found international lineages such as ST-111 provides the necessary resolution to inform epidemiological investigations and intervention policies. Concern over the increasing prevalence in hospitals of multiresistant bacteria, especially those that are resistant to carbapenem antibiotics, has prompted the use of typing methods that easily allow interlaboratory comparison of isolates. As a result, it has become clear that (i) high-risk clones of various Gram-negative bacteria, including Pseudomonas aeruginosa, can be found in many disparate locations, often with no obvious epidemiological links between the affected patients, and (ii) many of these clones are adept at acquiring various antibiotic resistance determinants (1, 2). These clones are commonly referred to as international lineages since they have been described in many countries across the globe. Epidemiological investigations of apparent outbreaks and interhospital spread of such lineages are confounded by the fact that they are so widely found; microbiological evidence of the same type must be considered alongside information about patient location and movement, for example, and patient location and movement information should be sufficiently robust to allow firm conclusions to be drawn. Greater resolution than that provided by conventional molecular typing methods, such as multilocus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE), and variable-number tandem repeat (VNTR) analysis, is essential if we are to infer or discount potential transmission pathways with confidence. Understanding these pathways will be critical for precise public health interventions to contain these highrisk clones effectively. Whole-genome sequencing (WGS) can provide this resolution and has been used to investigate outbreaks of Klebsiella pneumoniae ST-258 producing K. pneumoniae carbapenemase (KPC) enz...

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