We determined the complete nucleotide sequences of three plasmids that encode CTX-M extended-spectrum β-lactamases (ESBLs) in pulsed-field gel electrophoresis-defined United Kingdom variants (strains A, C, and D) of the internationally prevalent Escherichia coli O25:H4-ST131 clone. Plasmid pEK499 (strain A; 117,536 bp) was a fusion of type FII and FIA replicons and harbored the following 10 antibiotic resistance genes conferring resistance to eight antibiotic classes: bla _CTX-M-15 , bla _OXA-1 , bla _TEM-1, aac6′-Ib-cr , mph (A), catB4 , tet (A), and the integron-borne dfrA7 , aadA5 , and sulI genes. pEK516 (strain D; 64,471 bp) belonged to incompatibility group IncFII and carried seven antibiotic resistance genes: bla _CTX-M-15 , bla _OXA-1 , bla _TEM-1 , aac6′-Ib-cr , catB4 , and tet (A), all as in pEK499. It also carried aac3-IIa , conferring gentamicin resistance, and was highly related to pC15-1a, a plasmid encoding the CTX-M-15 enzyme in Canada. By contrast, pEK204 (strain C; 93,732 bp) belonged to incompatibility group IncI1 and carried only two resistance genes, bla _CTX-M-3 and bla _TEM-1 . It probably arose by the transposition of Tn 3 and IS Ecp1 - bla _CTX-M-3 elements into a pCOLIb-P9-like plasmid. We conclude that (i) United Kingdom variants of the successful E. coli ST131 clone have acquired different plasmids encoding CTX-M ESBLs on separate occasions, (ii) the bla _CTX-M-3 and bla _CTX-M-15 genes on pEK204 and pEK499/pEK516 represent separate escape events, and (iii) IncFII plasmids harboring bla _CTX-M-15 have played a crucial role in the global spread of CTX-M-15 ESBLs in E. coli .

Summary: Real-time surveillance of infectious disease using whole genome sequencing data poses challenges in both result generation and communication. SnapperDB represents a set of tools to store bacterial variant data and facilitate reproducible and scalable analysis of bacterial populations. We also introduce the ‘SNP address’ nomenclature to describe the relationship between isolates in a population to the single nucleotide resolution. We announce the release of SnapperDB v1.0 a program for scalable routine SNP analysis and storage of microbial populations. Availability and implementation: SnapperDB is implemented as a python application under the open source BSD license. All code and user guides are available at https://github.com/phe-bioinformatics/snapperdb. Reference genomes and SnapperDB configs are available at https://github.com/phe-bioinformatics/snapperdb_references.

Background. National surveillance of gastrointestinal pathogens, such as Shiga toxin–producing Escherichia coli O157 (STEC O157), is key to rapidly identifying linked cases in the distributed food network to facilitate public health interventions. In this study, we used whole-genome sequencing (WGS) as a tool to inform national surveillance of STEC O157 in terms of identifying linked cases and clusters and guiding epidemiological investigation. Methods. We retrospectively analyzed 334 isolates randomly sampled from 1002 strains of STEC O157 received by the Gastrointestinal Bacteria Reference Unit at Public Health England, Colindale, in 2012. The genetic distance between each isolate, as estimated by WGS, was calculated and phylogenetic methods were used to place strains in an evolutionary context. Results. Estimates of linked clusters representing STEC O157 outbreaks in England and Wales increased by 2-fold when WGS was used instead of traditional typing techniques. The previously unidentified clusters were often widely geographically distributed and small in size. Phylogenetic analysis facilitated identification of temporally distinct cases sharing common exposures and delineating those that shared epidemiological and temporal links. Comparison with multi locus variable number tandem repeat analysis (MLVA) showed that although MLVA is as sensitive as WGS, WGS provides a more timely resolution to outbreak clustering. Conclusions. WGS has come of age as a molecular typing tool to inform national surveillance of STEC O157; it can be used in real time to provide the highest strain-level resolution for outbreak investigation. WGS allows linked cases to be identified with unprecedented specificity and sensitivity that will facilitate targeted and appropriate public health investigations.

Microevolution associated with emergence and expansion of new epidemic clones of bacterial pathogens holds the key to epidemiologic success. To determine microevolution associated with monophasic Salmonella Typhimurium during an epidemic, we performed comparative whole-genome sequencing and phylogenomic analysis of isolates from the United Kingdom and Italy during 2005–2012. These isolates formed a single clade distinct from recent monophasic epidemic clones previously described from North America and Spain. The UK monophasic epidemic clones showed a novel genomic island encoding resistance to heavy metals and a composite transposon encoding antimicrobial drug resistance genes not present in other Salmonella Typhimurium isolates, which may have contributed to epidemiologic success. A remarkable amount of genotypic variation accumulated during clonal expansion that occurred during the epidemic, including multiple independent acquisitions of a novel prophage carrying the sopE gene and multiple deletion events affecting the phase II flagellin locus. This high level of microevolution may affect antigenicity, pathogenicity, and transmission.

Streptococcus pneumoniaetypically 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 theS. pneumoniaecapsular 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 (PneumococcalCapsuleTyping). Initially, WGS data from 871S. pneumoniaeisolates 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.

Escherichia coli sequence types (STs) 69, 73, 95, and 131 are collectively responsible for a large proportion of E. coli urinary tract and bloodstream infections, and they differ markedly in their antibiotic susceptibilities. Here, we describe a novel PCR method to rapidly detect and distinguish these lineages. Three hundred eighteen published E. coli genomes were compared in order to identify signature sequences unique to each of the four major STs. The specificities of these sequences were assessed in silico by seeking them in an additional 98 genomes. A PCR assay was designed to amplify size-distinguishable fragments unique to the four lineages and was validated using 515 E. coli isolates of known STs. Genome comparisons identified 22 regions ranging in size from 335 bp to 26.5 kb that are unique to one or more of the four predominant E. coli STs, with two to 10 specific regions per ST. These regions predominantly harbor genes encoding hypothetical proteins and are within or adjacent to prophage sequences. Most (13/22) were highly conserved (>96.5% identity) in the genomes of their respective ST. The new assay correctly identified all 142 representatives of the four major STs in the validation set ( n = 515), with only two ST12 isolates misidentified as ST95. Compared with MLST, the assay has 100% sensitivity and 99.5% specificity. The rapid identification of major extraintestinal E. coli STs will benefit future epidemiological studies and could be developed to tailor antibiotic therapy to the different susceptibilities of these dominant lineages.