Identification of Escherichia coli and Shigella Species from Whole-Genome Sequences.

Escherichia coli and Shigella species are closely related and genetically constitute the same species. Differentiating between these two pathogens and accurately identifying the four species of Shigella are therefore challenging. The organism-specific bioinformatics whole-genome sequencing (WGS) typing pipelines at Public Health England are dependent on the initial identification of the bacterial species by use of a kmer-based approach. Of the 1,982 Escherichia coli and Shigella sp. isolates analyzed in this study, 1,957 (98.4%) had concordant results by both traditional biochemistry and serology (TB&S) and the kmer identification (ID) derived from the WGS data. Of the 25 mismatches identified, 10 were enteroinvasive E. coli isolates that were misidentified as Shigella flexneri or S. boydii by the kmer ID, and 8 were S. flexneri isolates misidentified by TB&S as S. boydii due to nonfunctional S. flexneri O antigen biosynthesis genes. Analysis of the population structure based on multilocus sequence typing (MLST) data derived from the WGS data showed that the remaining discrepant results belonged to clonal complex 288 (CC288), comprising both S. boydii and S. dysenteriae strains. Mismatches between the TB&S and kmer ID results were explained by the close phylogenetic relationship between the two species and were resolved with reference to the MLST data. Shigella can be differentiated from E. coli and accurately identified to the species level by use of kmer comparisons and MLST. Analysis of the WGS data provided explanations for the discordant results between TB&S and WGS data, revealed the true phylogenetic relationships between different species of Shigella, and identified emerging pathoadapted lineages.

Integration of Genomic and Other Epidemiologic Data to Investigate and Control a Cross-Institutional Outbreak of Streptococcus pyogenes.

Single-strain outbreaks of Streptococcus pyogenes infections are common and often go undetected. In 2013, two clusters of invasive group A Streptococcus (iGAS) infection were identified in independent but closely located care homes in Oxfordshire, United Kingdom. Investigation included visits to each home, chart review, staff survey, microbiologic sampling, and genome sequencing. S. pyogenes emm type 1.0, the most common circulating type nationally, was identified from all cases yielding GAS isolates. A tailored whole-genome reference population comprising epidemiologically relevant contemporaneous isolates and published isolates was assembled. Data were analyzed independently using whole-genome multilocus sequencing and single-nucleotide polymorphism analyses. Six isolates from staff and residents of the homes formed a single cluster that was separated from the reference population by both analytical approaches. No further cases occurred after mass chemoprophylaxis and enhanced infection control. Our findings demonstrate the ability of 2 independent analytical approaches to enable robust conclusions from nonstandardized whole-genome analysis to support public health practice.

Evaluation of an Optimal Epidemiological Typing Scheme for Legionella pneumophila with Whole-Genome Sequence Data Using Validation Guidelines.

Sequence-based typing (SBT), analogous to multilocus sequence typing (MLST), is the current "gold standard" typing method for investigation of legionellosis outbreaks caused by Legionella pneumophila However, as common sequence types (STs) cause many infections, some investigations remain unresolved. In this study, various whole-genome sequencing (WGS)-based methods were evaluated according to published guidelines, including (i) a single nucleotide polymorphism (SNP)-based method, (ii) extended MLST using different numbers of genes, (iii) determination of gene presence or absence, and (iv) a kmer-based method. L. pneumophila serogroup 1 isolates (n = 106) from the standard "typing panel," previously used by the European Society for Clinical Microbiology Study Group on Legionella Infections (ESGLI), were tested together with another 229 isolates. Over 98% of isolates were considered typeable using the SNP- and kmer-based methods. Percentages of isolates with complete extended MLST profiles ranged from 99.1% (50 genes) to 86.8% (1,455 genes), while only 41.5% produced a full profile with the gene presence/absence scheme. Replicates demonstrated that all methods offer 100% reproducibility. Indices of discrimination range from 0.972 (ribosomal MLST) to 0.999 (SNP based), and all values were higher than that achieved with SBT (0.940). Epidemiological concordance is generally inversely related to discriminatory power. We propose that an extended MLST scheme with ∼50 genes provides optimal epidemiological concordance while substantially improving the discrimination offered by SBT and can be used as part of a hierarchical typing scheme that should maintain backwards compatibility and increase discrimination where necessary. This analysis will be useful for the ESGLI to design a scheme that has the potential to become the new gold standard typing method for L. pneumophila.

Whole-genome sequencing and epidemiological analysis do not provide evidence for cross-transmission of mycobacterium abscessus in a cohort of pediatric cystic fibrosis patients.

BACKGROUND: Mycobacterium abscessus has emerged as a major pathogen in cystic fibrosis (CF) patients and has been associated with poor clinical outcomes, particularly following lung transplant. We investigated the acquisition of this bacterium in a cohort of pediatric CF patients. METHODS: Demographic and patient location data were used to uncover epidemiological links between patients with genetically related strains of M. abscessus that had been previously typed by variable-number tandem repeat profiling. Whole-genome sequencing was applied to 27 M. abscessus isolates from the 20 patients in this cohort to provide definitive data on the genetic relatedness of strains. RESULTS: Whole-genome sequencing data demonstrated that M. abscessus isolates from 16 patients were unrelated, differing by at least 34 single-nucleotide polymorphisms (SNPs) from any other isolate, suggesting that independent acquisition events have occurred. Only 2 clusters of very closely related (<25 SNPs) isolates from different patients were seen. The first cluster contained 8 isolates, differing by a maximum of 17 SNPs, from a sibling pair who had intense exposure to each other both inside and outside the hospital. The second cluster contained 3 isolates, differing by a maximum of 24 SNPs, from 2 individuals with no apparent epidemiological links. CONCLUSIONS: We have not demonstrated cross-transmission of M. abscessus within our hospital, except between 1 sibling pair. Alternative routes of acquisition of M. abscessus infection, in particular the environment, require further investigation.

MOST: a modified MLST typing tool based on short read sequencing.

Multilocus sequence typing (MLST) is an effective method to describe bacterial populations. Conventionally, MLST involves Polymerase Chain Reaction (PCR) amplification of housekeeping genes followed by Sanger DNA sequencing. Public Health England (PHE) is in the process of replacing the conventional MLST methodology with a method based on short read sequence data derived from Whole Genome Sequencing (WGS). This paper reports the comparison of the reliability of MLST results derived from WGS data, comparing mapping and assembly-based approaches to conventional methods using 323 bacterial genomes of diverse species. The sensitivity of the two WGS based methods were further investigated with 26 mixed and 29 low coverage genomic data sets from Salmonella enteridis and Streptococcus pneumoniae. Of the 323 samples, 92.9% (n = 300), 97.5% (n = 315) and 99.7% (n = 322) full MLST profiles were derived by the conventional method, assembly- and mapping-based approaches, respectively. The concordance between samples that were typed by conventional (92.9%) and both WGS methods was 100%. From the 55 mixed and low coverage genomes, 89.1% (n = 49) and 67.3% (n = 37) full MLST profiles were derived from the mapping and assembly based approaches, respectively. In conclusion, deriving MLST from WGS data is more sensitive than the conventional method. When comparing WGS based methods, the mapping based approach was the most sensitive. In addition, the mapping based approach described here derives quality metrics, which are difficult to determine quantitatively using conventional and WGS-assembly based approaches.

Identification of Salmonella for public health surveillance using whole genome sequencing.

In April 2015, Public Health England implemented whole genome sequencing (WGS) as a routine typing tool for public health surveillance of Salmonella, adopting a multilocus sequence typing (MLST) approach as a replacement for traditional serotyping. The WGS derived sequence type (ST) was compared to the phenotypic serotype for 6,887 isolates of S. enterica subspecies I, and of these, 6,616 (96%) were concordant. Of the 4% (n = 271) of isolates of subspecies I exhibiting a mismatch, 119 were due to a process error in the laboratory, 26 were likely caused by the serotype designation in the MLST database being incorrect and 126 occurred when two different serovars belonged to the same ST. The population structure of S. enterica subspecies II-IV differs markedly from that of subspecies I and, based on current data, defining the serovar from the clonal complex may be less appropriate for the classification of this group. Novel sequence types that were not present in the MLST database were identified in 8.6% of the total number of samples tested (including S. enterica subspecies I-IV and S. bongori) and these 654 isolates belonged to 326 novel STs. For S. enterica subspecies I, WGS MLST derived serotyping is a high throughput, accurate, robust, reliable typing method, well suited to routine public health surveillance. The combined output of ST and serovar supports the maintenance of traditional serovar nomenclature while providing additional insight on the true phylogenetic relationship between isolates.

An investigation of the diversity of strains of enteroaggregative Escherichia coli isolated from cases associated with a large multi-pathogen foodborne outbreak in the UK.

Following a large outbreak of foodborne gastrointestinal (GI) disease, a multiplex PCR approach was used retrospectively to investigate faecal specimens from 88 of the 413 reported cases. Gene targets from a range of bacterial GI pathogens were detected, including Salmonella species, Shigella species and Shiga toxin-producing Escherichia coli, with the majority (75%) of faecal specimens being PCR positive for aggR associated with the Enteroaggregative E. coli (EAEC) group. The 20 isolates of EAEC recovered from the outbreak specimens exhibited a range of serotypes, the most frequent being O104:H4 and O131:H27. None of the EAEC isolates had the Shiga toxin (stx) genes. Multilocus sequence typing and single nucleotide polymorphism analysis of the core genome confirmed the diverse phylogeny of the strains. The analysis also revealed a close phylogenetic relationship between the EAEC O104:H4 strains in this outbreak and the strain of E. coli O104:H4 associated with a large outbreak of haemolytic ureamic syndrome in Germany in 2011. Further analysis of the EAEC plasmids, encoding the key enteroaggregative virulence genes, showed diversity with respect to FIB/FII type, gene content and genomic architecture. Known EAEC virulence genes, such as aggR, aat and aap, were present in all but one of the strains. A variety of fimbrial genes were observed, including genes encoding all five known fimbrial types, AAF/1 to AAF/V. The AAI operon was present in its entirety in 15 of the EAEC strains, absent in three and present, but incomplete, in two isolates. EAEC is known to be a diverse pathotype and this study demonstrates that a high level of diversity in strains recovered from cases associated with a single outbreak. Although the EAEC in this study did not carry the stx genes, this outbreak provides further evidence of the pathogenic potential of the EAEC O104:H4 serotype.