Circulation of Third-Generation Cephalosporin Resistant Salmonella Typhi in Mumbai, India.

We report the persistent circulation of third-generation cephalosporin resistant Salmonella Typhi in Mumbai, linked to the acquisition and maintenance of a previously characterized IncX3 plasmid carrying the ESBL gene blaSHV-12 and the fluoroquinolone resistance gene qnrB7 in the genetic context of a triple mutant also associated with fluoroquinolone resistance.

Establishing a national reference laboratory for antimicrobial resistance using a whole-genome sequencing framework: Nigeria's experience.

Whole-genome sequencing (WGS) is finding important applications in the surveillance of antimicrobial resistance (AMR), providing the most granular data and broadening the scope of niches and locations that can be surveilled. A common but often overlooked application of WGS is to replace or augment reference laboratory services for AMR surveillance. WGS has supplanted traditional strain subtyping in many comprehensive reference laboratories and is now the gold standard for rapidly ruling isolates into or out of suspected outbreak clusters. These and other properties give WGS the potential to serve in AMR reference functioning where a reference laboratory did not hitherto exist. In this perspective, we describe how we have employed a WGS approach, and an academic-public health system collaboration, to provide AMR reference laboratory services in Nigeria, as a model for leapfrogging to national AMR surveillance.

Train-the-Trainer as an Effective Approach to Building Global Networks of Experts in Genomic Surveillance of Antimicrobial Resistance (AMR).

Advanced genomics and sequencing technologies are increasingly becoming critical for global health applications such as pathogen and antimicrobial resistance (AMR) surveillance. Limited resources challenge capacity development in low- and middle-income countries (LMICs), with few countries having genomics facilities and adequately trained staff. Training research and public health experts who are directly involved in the establishment of such facilities offers an effective, but limited, solution to a growing need. Instead, training them to impart their knowledge and skills to others provides a sustainable model for scaling up the much needed capacity and capability for genomic sequencing and analysis locally with global impact. We designed and developed a Train-the-Trainer course integrating pedagogical aspects with genomic and bioinformatics activities. The course was delivered to 18 participants from 12 countries in Africa, Asia, and Latin America. A combination of teaching strategies culminating in a group project created a foundation for continued development at home institutions. Upon follow-up after 6 months, at least 40% of trainees had initiated training programs and collaborations to build capacity at local, national, and regional level. This work provides a framework for implementing a training and capacity building program for the application of genomics tools and resources in AMR surveillance.

High-Resolution Genomic Profiling of Carbapenem-Resistant Klebsiella pneumoniae Isolates: A Multicentric Retrospective Indian Study.

BACKGROUND: Carbapenem-resistant Klebsiella pneumoniae (CRKP) is a threat to public health in India because of its high dissemination, mortality, and limited treatment options. Its genomic variability is reflected in the diversity of sequence types, virulence factors, and antimicrobial resistance (AMR) mechanisms. This study aims to characterize the clonal relationships and genetic mechanisms of resistance and virulence in CRKP isolates in India. MATERIALS AND METHODS: We characterized 344 retrospective K. pneumoniae clinical isolates collected from 8 centers across India collected in 2013-2019. Susceptibility to antibiotics was tested with VITEK 2. Capsular types, multilocus sequence type, virulence genes, AMR determinants, plasmid replicon types, and a single-nucleotide polymorphism phylogeny were inferred from their whole genome sequences. RESULTS: Phylogenetic analysis of the 325 Klebsiella isolates that passed quality control revealed 3 groups: K. pneumoniae sensu stricto (n = 307), K. quasipneumoniae (n = 17), and K. variicola (n = 1). Sequencing and capsular diversity analysis of the 307 K. pneumoniae sensu stricto isolates revealed 28 sequence types, 26 K-locus types, and 11 O-locus types, with ST231, KL51, and O1V2 being predominant. blaOXA-48-like and blaNDM-1/5 were present in 73.2% and 24.4% of isolates, respectively. The major plasmid replicon types associated with carbapenase genes were IncF (51.0%) and Col group (35.0%). CONCLUSION: Our study documents for the first time the genetic diversity of K and O antigens circulating in India. The results demonstrate the practical applicability of genomic surveillance and its utility in tracking the population dynamics of CRKP. It alerts us to the urgency for longitudinal surveillance of these transmissible lineages.

Genome Sequencing Identifies Previously Unrecognized Klebsiella pneumoniae Outbreaks in Neonatal Intensive Care Units in the Philippines.

BACKGROUND: Klebsiella pneumoniae is a critically important pathogen in the Philippines. Isolates are commonly resistant to at least 2 classes of antibiotics, yet mechanisms and spread of its resistance are not well studied. METHODS: A retrospective sequencing survey was performed on carbapenem-, extended spectrum beta-lactam-, and cephalosporin-resistant Klebsiella pneumoniae isolated at 20 antimicrobial resistance (AMR) surveillance sentinel sites from 2015 through 2017. We characterized 259 isolates using biochemical methods, antimicrobial susceptibility testing, and whole-genome sequencing (WGS). Known AMR mechanisms were identified. Potential outbreaks were investigated by detecting clusters from epidemiologic, phenotypic, and genome-derived data. RESULTS: Prevalent AMR mechanisms detected include blaCTX-M-15 (76.8%) and blaNDM-1 (37.5%). An epidemic IncFII(Yp) plasmid carrying blaNDM-1 was also detected in 46 isolates from 6 sentinel sites and 14 different sequence types (STs). This plasmid was also identified as the main vehicle of carbapenem resistance in 2 previously unrecognized local outbreaks of ST348 and ST283 at 2 different sentinel sites. A third local outbreak of ST397 was also identified but without the IncFII(Yp) plasmid. Isolates in each outbreak site showed identical STs and K- and O-loci, and similar resistance profiles and AMR genes. All outbreak isolates were collected from blood of children aged < 1 year. CONCLUSION: WGS provided a better understanding of the epidemiology of multidrug resistant Klebsiella in the Philippines, which was not possible with only phenotypic and epidemiologic data. The identification of 3 previously unrecognized Klebsiella outbreaks highlights the utility of WGS in outbreak detection, as well as its importance in public health and in implementing infection control programs.

Complexity of Genomic Epidemiology of Carbapenem-Resistant Klebsiella pneumoniae Isolates in Colombia Urges the Reinforcement of Whole Genome Sequencing-Based Surveillance Programs.

BACKGROUND: Carbapenem-resistant Klebsiella pneumoniae (CRKP) is an emerging public health problem. This study explores the specifics of CRKP epidemiology in Colombia based on whole genome sequencing (WGS) of the National Reference Laboratory at Instituto Nacional de Salud (INS)'s 2013-2017 sample collection. METHODS: A total of 425 CRKP isolates from 21 departments were analyzed by HiSeq-X10®Illumina high-throughput sequencing. Bioinformatic analysis was performed, primarily using the pipelines developed collaboratively by the National Institute for Health Research Global Health Research Unit (GHRU) on Genomic Surveillance of Antimicrobial Resistance (AMR), and AGROSAVIA. RESULTS: Of the 425 CRKP isolates, 91.5% were carbapenemase-producing strains. The data support a recent expansion and the endemicity of CRKP in Colombia with the circulation of 7 high-risk clones, the most frequent being CG258 (48.39% of isolates). We identified genes encoding carbapenemases blaKPC-3, blaKPC-2, blaNDM-1, blaNDM-9, blaVIM-2, blaVIM-4, and blaVIM-24, and various mobile genetic elements (MGE). The virulence of CRKP isolates was low, but colibactin (clb3) was present in 25.2% of isolates, and a hypervirulent CRKP clone (CG380) was reported for the first time in Colombia. ST258, ST512, and ST4851 were characterized by low levels of diversity in the core genome (ANI > 99.9%). CONCLUSIONS: The study outlines complex CRKP epidemiology in Colombia. CG258 expanded clonally and carries specific carbapenemases in specific MGEs, while the other high-risk clones (CG147, CG307, and CG152) present a more diverse complement of carbapenemases. The specifics of the Colombian situation stress the importance of WGS-based surveillance to monitor evolutionary trends of sequence types (STs), MGE, and resistance and virulence genes.

Rapid Genomic Characterization and Global Surveillance of Klebsiella Using Pathogenwatch.

BACKGROUND: Klebsiella species, including the notable pathogen K. pneumoniae, are increasingly associated with antimicrobial resistance (AMR). Genome-based surveillance can inform interventions aimed at controlling AMR. However, its widespread implementation requires tools to streamline bioinformatic analyses and public health reporting. METHODS: We developed the web application Pathogenwatch, which implements analytics tailored to Klebsiella species for integration and visualization of genomic and epidemiological data. We populated Pathogenwatch with 16 537 public Klebsiella genomes to enable contextualization of user genomes. We demonstrated its features with 1636 genomes from 4 low- and middle-income countries (LMICs) participating in the NIHR Global Health Research Unit (GHRU) on AMR. RESULTS: Using Pathogenwatch, we found that GHRU genomes were dominated by a small number of epidemic drug-resistant clones of K. pneumoniae. However, differences in their distribution were observed (eg, ST258/512 dominated in Colombia, ST231 in India, ST307 in Nigeria, ST147 in the Philippines). Phylogenetic analyses including public genomes for contextualization enabled retrospective monitoring of their spread. In particular, we identified hospital outbreaks, detected introductions from abroad, and uncovered clonal expansions associated with resistance and virulence genes. Assessment of loci encoding O-antigens and capsule in K. pneumoniae, which represent possible vaccine candidates, showed that 3 O-types (O1-O3) represented 88.9% of all genomes, whereas capsule types were much more diverse. CONCLUSIONS: Pathogenwatch provides a free, accessible platform for real-time analysis of Klebsiella genomes to aid surveillance at local, national, and global levels. We have improved representation of genomes from GHRU participant countries, further facilitating ongoing surveillance.

Overcoming Data Bottlenecks in Genomic Pathogen Surveillance.

Performing whole genome sequencing (WGS) for the surveillance of antimicrobial resistance offers the ability to determine not only the antimicrobials to which rates of resistance are increasing, but also the evolutionary mechanisms and transmission routes responsible for the increase at local, national, and global scales. To derive WGS-based outputs, a series of processes are required, beginning with sample and metadata collection, followed by nucleic acid extraction, library preparation, sequencing, and analysis. Throughout this pathway there are many data-related operations required (informatics) combined with more biologically focused procedures (bioinformatics). For a laboratory aiming to implement pathogen genomics, the informatics and bioinformatics activities can be a barrier to starting on the journey; for a laboratory that has already started, these activities may become overwhelming. Here we describe these data bottlenecks and how they have been addressed in laboratories in India, Colombia, Nigeria, and the Philippines, as part of the National Institute for Health Research Global Health Research Unit on Genomic Surveillance of Antimicrobial Resistance. The approaches taken include the use of reproducible data parsing pipelines and genome sequence analysis workflows, using technologies such as Data-flo, the Nextflow workflow manager, and containerization of software dependencies. By overcoming barriers to WGS implementation in countries where genome sampling for some species may be underrepresented, a body of evidence can be built to determine the concordance of antimicrobial sensitivity testing and genome-derived resistance, and novel high-risk clones and unknown mechanisms of resistance can be discovered.

Clones and Clusters of Antimicrobial-Resistant Klebsiella From Southwestern Nigeria.

BACKGROUND: Klebsiella pneumoniae is a World Health Organization high-priority antibiotic-resistant pathogen. However, little is known about Klebsiella lineages circulating in Nigeria. METHODS: We performed whole-genome sequencing (WGS) of 141 Klebsiella isolated between 2016 and 2018 from clinical specimens at 3 antimicrobial-resistance (AMR) sentinel surveillance tertiary hospitals in southwestern Nigeria. We conducted in silico multilocus sequence typing; AMR gene, virulence gene, plasmid, and K and O loci profiling; as well as phylogenetic analyses, using publicly available tools and Nextflow pipelines. RESULTS: Phylogenetic analysis revealed that the majority of the 134 K. pneumoniae and 5 K. quasipneumoniae isolates from Nigeria characterized are closely related to globally disseminated multidrug-resistant clones. Of the 39 K. pneumoniae sequence types (STs) identified, the most common were ST307 (15%), ST5241 (12%), ST15 (~9%), and ST25 (~6%). ST5241, 1 of 10 novel STs detected, is a single locus variant of ST636 carrying dfrA14, tetD, qnrS, and oqxAB resistance genes. The extended-spectrum ß-lactamase (ESBL) gene blaCTX_M-15 was seen in 72% of K. pneumoniae genomes, while 8% encoded a carbapenemase. No isolate carried a combination of carbapenemase-producing genes. Four likely outbreak clusters from 1 facility, within STs 17, 25, 307, and 5241, were ESBL but not carbapenemase-bearing clones. CONCLUSIONS: This study uncovered known and novel K. pneumoniae lineages circulating in 3 hospitals in Southwest Nigeria that include multidrug-resistant ESBL producers. Carbapenemase-producing isolates remain uncommon. WGS retrospectively identified outbreak clusters, pointing to the value of genomic approaches in AMR surveillance for improving infection prevention and control in Nigerian hospitals.

Multiple major disease-associated clones of Legionella pneumophila have emerged recently and independently.

Legionella pneumophila is an environmental bacterium and the leading cause of Legionnaires' disease. Just five sequence types (ST), from more than 2000 currently described, cause nearly half of disease cases in northwest Europe. Here, we report the sequence and analyses of 364 L. pneumophila genomes, including 337 from the five disease-associated STs and 27 representative of the species diversity. Phylogenetic analyses revealed that the five STs have independent origins within a highly diverse species. The number of de novo mutations is extremely low with maximum pairwise single-nucleotide polymorphisms (SNPs) ranging from 19 (ST47) to 127 (ST1), which suggests emergences within the last century. Isolates sampled geographically far apart differ by only a few SNPs, demonstrating rapid dissemination. These five STs have been recombining recently, leading to a shared pool of allelic variants potentially contributing to their increased disease propensity. The oldest clone, ST1, has spread globally; between 1940 and 2000, four new clones have emerged in Europe, which show long-distance, rapid dispersal. That a large proportion of clinical cases is caused by recently emerged and internationally dispersed clones, linked by convergent evolution, is surprising for an environmental bacterium traditionally considered to be an opportunistic pathogen. To simultaneously explain recent emergence, rapid spread and increased disease association, we hypothesize that these STs have adapted to new man-made environmental niches, which may be linked by human infection and transmission.

SnapperDB: a database solution for routine sequencing analysis of bacterial isolates.

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.

BugMat and FindNeighbour: command line and server applications for investigating bacterial relatedness.

BACKGROUND: Large scale bacterial sequencing has made the determination of genetic relationships within large sequence collections of bacterial genomes derived from the same microbial species an increasingly common task. Solutions to the problem have application to public health (for example, in the detection of possible disease transmission), and as part of divide-and-conquer strategies selecting groups of similar isolates for computationally intensive methods of phylogenetic inference using (for example) maximal likelihood methods. However, the generation and maintenance of distance matrices is computationally intensive, and rapid methods of doing so are needed to allow translation of microbial genomics into public health actions. RESULTS: We developed, tested and deployed three solutions. BugMat is a fast C++ application which generates one-off in-memory distance matrices. FindNeighbour and FindNeighbour2 are server-side applications which build, maintain, and persist either complete (for FindNeighbour) or sparse (for FindNeighbour2) distance matrices given a set of sequences. FindNeighbour and BugMat use a variation model to accelerate computation, while FindNeighbour2 uses reference-based compression. Performance metrics show scalability into tens of thousands of sequences, with options for scaling further. CONCLUSION: Three applications, each with distinct strengths and weaknesses, are available for distance-matrix based analysis of large bacterial collections. Deployed as part of the Public Health England solution for M. tuberculosis genomic processing, they will have wide applicability.

Genome analysis following a national increase in Scarlet Fever in England 2014.

BACKGROUND: During 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. RESULTS: 555 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. CONCLUSIONS: There 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.

Genomic determination of minimum multi-locus sequence typing schemas to represent the genomic phylogeny of Mycoplasma hominis.

BACKGROUND: Mycoplasma hominis is an opportunistic human pathogen, associated with clinically diverse disease. Currently, there is no standardised method for typing M. hominis, which would aid in understanding pathogen epidemiology and transmission. Due to availability and costs of whole genome sequencing and the challenges in obtaining adequate M. hominis DNA, the use of whole genome sequence analysis to provide clinical guidance is unpractical for this bacterial species as well as other fastidious organisms. RESULTS: This study identified pan-genome set of 700 genes found to be present in four published reference genomes. A subset of 417 genes was identified to be core genome for 18 isolates and 1 reference. Leave-one-out analysis of the core genes highlighted set of 48 genes that are required to recapture the original phylogenetic relationships observed using whole genome SNP analysis. Three 7-locus MLST schemas with high diversity index (97%) and low dN/dS ratios (0.1, 0.13, and 0.11) were derived that could be used to confer good discrimination between strains and could be of practical use in future studies direct on clinical specimens. CONCLUSIONS: The genes proposed in this study could be utilised to design a cost-effective and rapid PCR-based MLST assay that could be applied directly to clinical isolates, without prior isolation. This study includes additional genomic analysis revealing high levels of genetic heterogeneity among this species. This provides a novel and evidence based approach for the development of MLST schema that accurately represent genomic phylogeny for use in epidemiology and transmission studies.

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.

Whole-genome sequencing for national surveillance of Shiga toxin-producing Escherichia coli O157.

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.

High-Resolution Analysis by Whole-Genome Sequencing of an International Lineage (Sequence Type 111) of Pseudomonas aeruginosa Associated with Metallo-Carbapenemases in the United Kingdom.

Whole-genome sequencing (WGS) was carried out on 87 isolates of sequence type 111 (ST-111) of Pseudomonas aeruginosa collected between 2005 and 2014 from 65 patients and 12 environmental isolates from 24 hospital laboratories across the United Kingdom on an Illumina HiSeq instrument. Most isolates (73) carried VIM-2, but others carried IMP-1 or IMP-13 (5) or NDM-1 (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 ∼50 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.

Metaproteomics analysis reveals the adaptation process for the chicken gut microbiota.

The animal gastrointestinal tract houses a large microbial community, the gut microbiota, that confers many benefits to its host, such as protection from pathogens and provision of essential metabolites. Metagenomic approaches have defined the chicken fecal microbiota in other studies, but here, we wished to assess the correlation between the metagenome and the bacterial proteome in order to better understand the healthy chicken gut microbiota. Here, we performed high-throughput sequencing of 16S rRNA gene amplicons and metaproteomics analysis of fecal samples to determine microbial gut composition and protein expression. 16 rRNA gene sequencing analysis identified Clostridiales, Bacteroidaceae, and Lactobacillaceae species as the most abundant species in the gut. For metaproteomics analysis, peptides were generated by using the Fasp method and subsequently fractionated by strong anion exchanges. Metaproteomics analysis identified 3,673 proteins. Among the most frequently identified proteins, 380 proteins belonged to Lactobacillus spp., 155 belonged to Clostridium spp., and 66 belonged to Streptococcus spp. The most frequently identified proteins were heat shock chaperones, including 349 GroEL proteins, from many bacterial species, whereas the most abundant enzymes were pyruvate kinases, as judged by the number of peptides identified per protein (spectral counting). Gene ontology and KEGG pathway analyses revealed the functions and locations of the identified proteins. The findings of both metaproteomics and 16S rRNA sequencing analyses are discussed.