Methodological Approach to Identify and Expand the Volume of Antimicrobial Resistance (AMR) Data in the Human Health Sector in Low- and Middle-Income Countries in Asia: Implications for Local and Regional AMR Surveillance Systems Strengthening.

Antimicrobial resistance (AMR) is a multifaceted global health problem disproportionately affecting low- and middle-income countries (LMICs). The Capturing data on Antimicrobial resistance Patterns and Trends in Use in Regions of Asia (CAPTURA) project was tasked to expand the volume of AMR and antimicrobial use data in Asia. The CAPTURA project used 2 data-collection streams: facility data and project metadata. Project metadata constituted information collected to map out data sources and assess data quality, while facility data referred to the retrospective data collected from healthcare facilities. A down-selection process, labelled "the funnel approach" by the project, was adopted to use the project metadata in prioritizing and selecting laboratories for retrospective AMR data collection. Moreover, the metadata served as a guide for understanding the AMR data once they were collected. The findings from CAPTURA's metadata add to the current discourse on the limitation of AMR data in LMICs. There is generally a low volume of AMR data generated as there is a lack of microbiology laboratories with sufficient antimicrobial susceptibility testing capacity. Many laboratories in Asia are still capturing data on paper, resulting in scattered or unused data not readily accessible or shareable for analyses. There is also a lack of clinical and epidemiological data captured, impeding interpretation and in-depth understanding of the AMR data. CAPTURA's experience in Asia suggests that there is a wide spectrum of capacity and capability of microbiology laboratories within a country and region. As local AMR surveillance is a crucial instrument to inform context-specific measures to combat AMR, it is important to understand and assess current capacity-building needs while implementing activities to enhance surveillance systems.

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.

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.

Phandango: an interactive viewer for bacterial population genomics.

SUMMARY: Fully exploiting the wealth of data in current bacterial population genomics datasets requires synthesizing and integrating different types of analysis across millions of base pairs in hundreds or thousands of isolates. Current approaches often use static representations of phylogenetic, epidemiological, statistical and evolutionary analysis results that are difficult to relate to one another. Phandango is an interactive application running in a web browser allowing fast exploration of large-scale population genomics datasets combining the output from multiple genomic analysis methods in an intuitive and interactive manner. AVAILABILITY AND IMPLEMENTATION: Phandango is a web application freely available for use at www.phandango.net and includes a diverse collection of datasets as examples. Source code together with a detailed wiki page is available on GitHub at https://github.com/jameshadfield/phandango.

Europe-wide expansion and eradication of multidrug-resistant Neisseria gonorrhoeae lineages: a genomic surveillance study.

BACKGROUND: Genomic surveillance using quality-assured whole-genome sequencing (WGS) together with epidemiological and antimicrobial resistance (AMR) data is essential to characterise the circulating Neisseria gonorrhoeae lineages and their association to patient groups (defined by demographic and epidemiological factors). In 2013, the European gonococcal population was characterised genomically for the first time. We describe the European gonococcal population in 2018 and identify emerging or vanishing lineages associated with AMR and epidemiological characteristics of patients, to elucidate recent changes in AMR and gonorrhoea epidemiology in Europe. METHODS: We did WGS on 2375 gonococcal isolates from 2018 (mainly Sept 1-Nov 30) in 26 EU and EEA countries. Molecular typing and AMR determinants were extracted from quality-checked genomic data. Association analyses identified links between genomic lineages, AMR, and epidemiological data. FINDINGS: Azithromycin-resistant N gonorrhoeae (8·0% [191/2375] in 2018) is rising in Europe due to the introduction or emergence and subsequent expansion of a novel N gonorrhoeae multi-antigen sequence typing (NG-MAST) genogroup, G12302 (132 [5·6%] of 2375; N gonorrhoeae sequence typing for antimicrobial resistance [NG-STAR] clonal complex [CC]168/63), carrying a mosaic mtrR promoter and mtrD sequence and found in 24 countries in 2018. CC63 was associated with pharyngeal infections in men who have sex with men. Susceptibility to ceftriaxone and cefixime is increasing, as the resistance-associated lineage, NG-MAST G1407 (51 [2·1%] of 2375), is progressively vanishing since 2009-10. INTERPRETATION: Enhanced gonococcal AMR surveillance is imperative worldwide. WGS, linked to epidemiological and AMR data, is essential to elucidate the dynamics in gonorrhoea epidemiology and gonococcal populations as well as to predict AMR. When feasible, WGS should supplement the national and international AMR surveillance programmes to elucidate AMR changes over time. In the EU and EEA, increasing low-level azithromycin resistance could threaten the recommended ceftriaxone-azithromycin dual therapy, and an evidence-based clinical azithromycin resistance breakpoint is needed. Nevertheless, increasing ceftriaxone susceptibility, declining cefixime resistance, and absence of known resistance mutations for new treatments (zoliflodacin, gepotidacin) are promising. FUNDING: European Centre for Disease Prevention and Control, Centre for Genomic Pathogen Surveillance, Örebro University Hospital, Wellcome.

Genomic surveillance of Salmonella spp. in the Philippines during 2013-2014.

BACKGROUND: Increasing antimicrobial resistance (AMR) in Salmonella has been observed in the Philippines. We aimed to characterise the population and AMR mechanisms of Salmonella with whole genome sequencing (WGS) and compare it with laboratory surveillance methods. METHODS: The serotype, multilocus sequence type, AMR genes and relatedness between isolates were determined from the genomes of 148 Salmonella Typhi (S. Typhi) and 65 non-typhoidal Salmonella (NTS) collected by the Antimicrobial Resistance Surveillance Program during 2013-2014. Genotypic serotypes and AMR prediction were compared with phenotypic data. RESULTS: AMR rates in S. Typhi were low, with sparse acquisition of mutations associated with reduced susceptibility to fluoroquinolones or extended-spectrum beta-lactamases (ESBL) genes. By contrast, 75% of NTS isolates were insusceptible to at least one antimicrobial, with more than half carrying mutations and/or genes linked to fluoroquinolone resistance. ESBL genes were detected in five genomes, which also carried other AMR determinants. The population of S. Typhi was dominated by likely endemic genotype 3.0, which caused a putative local outbreak. The main NTS clades were global epidemic S. Enteritidis ST11 and S. Typhimurium monophasic variant (I,4,[5],12: i: -) ST34. CONCLUSION: We provide the first genomic characterisation of Salmonella from the Philippines and evidence of WGS utility for ongoing surveillance.

Genomic surveillance of methicillin-resistant Staphylococcus aureus in the Philippines, 2013-2014.

Methicillin-resistant Staphylococcus aureus (MRSA) remains one of the leading causes of both nosocomial and community infections worldwide. In the Philippines, MRSA rates have remained above 50% since 2010, but resistance to other antibiotics, including vancomycin, is low. The MRSA burden can be partially attributed to pathogen-specific characteristics of the circulating clones, but little was known about the S. aureus clones circulating in the Philippines. We sequenced the whole genomes of 116 S. aureus isolates collected in 2013-2014 within the Antimicrobial Resistance Surveillance Program. The multilocus sequence type, spa type, SCCmec type, presence of antimicrobial resistance (AMR) determinants and virulence genes and relatedness between the isolates were all derived from the sequence data. The concordance between phenotypic and genotypic resistance was also determined. The MRSA population in the Philippines comprised a limited number of genetic clones, including several international epidemic clones, such as CC30-spa-t019-SCCmec-IV-PVL+, CC5-SCCmec-typeIV and ST239-spa-t030-SCCmec-typeIII. The CC30 genomes were related to the South-West Pacific clone but formed a distinct, diverse lineage, with evidence of global dissemination. We showed independent acquisition of resistance to sulfamethoxazole/trimethoprim in various locations and genetic clones but mostly in paediatric patients with invasive infections. The concordance between phenotypic and genotypic resistance was 99.68% overall for eight antibiotics in seven classes. We have made the first comprehensive genomic survey of S. aureus in the Philippines, which bridges the gap in genomic data from the Western Pacific Region and will constitute the genetic background for contextualizing prospective surveillance.

A community-driven resource for genomic epidemiology and antimicrobial resistance prediction of Neisseria gonorrhoeae at Pathogenwatch.

BACKGROUND: Antimicrobial-resistant (AMR) Neisseria gonorrhoeae is an urgent threat to public health, as strains resistant to at least one of the two last-line antibiotics used in empiric therapy of gonorrhoea, ceftriaxone and azithromycin, have spread internationally. Whole genome sequencing (WGS) data can be used to identify new AMR clones and transmission networks and inform the development of point-of-care tests for antimicrobial susceptibility, novel antimicrobials and vaccines. Community-driven tools that provide an easy access to and analysis of genomic and epidemiological data is the way forward for public health surveillance. METHODS: Here we present a public health-focussed scheme for genomic epidemiology of N. gonorrhoeae at Pathogenwatch ( https://pathogen.watch/ngonorrhoeae ). An international advisory group of experts in epidemiology, public health, genetics and genomics of N. gonorrhoeae was convened to inform on the utility of current and future analytics in the platform. We implement backwards compatibility with MLST, NG-MAST and NG-STAR typing schemes as well as an exhaustive library of genetic AMR determinants linked to a genotypic prediction of resistance to eight antibiotics. A collection of over 12,000 N. gonorrhoeae genome sequences from public archives has been quality-checked, assembled and made public together with available metadata for contextualization. RESULTS: AMR prediction from genome data revealed specificity values over 99% for azithromycin, ciprofloxacin and ceftriaxone and sensitivity values around 99% for benzylpenicillin and tetracycline. A case study using the Pathogenwatch collection of N. gonorrhoeae public genomes showed the global expansion of an azithromycin-resistant lineage carrying a mosaic mtr over at least the last 10 years, emphasising the power of Pathogenwatch to explore and evaluate genomic epidemiology questions of public health concern. CONCLUSIONS: The N. gonorrhoeae scheme in Pathogenwatch provides customised bioinformatic pipelines guided by expert opinion that can be adapted to public health agencies and departments with little expertise in bioinformatics and lower-resourced settings with internet connection but limited computational infrastructure. The advisory group will assess and identify ongoing public health needs in the field of gonorrhoea, particularly regarding gonococcal AMR, in order to further enhance utility with modified or new analytic methods.

Genomic surveillance of Neisseria gonorrhoeae in the Philippines, 2013-2014.

Antimicrobial-resistant Neisseria gonorrhoeae is a major threat to public health and is of particular concern in the Western Pacific Region, where the incidence of gonorrhoea is high. The Antimicrobial Resistance Surveillance Program (ARSP) has been capturing information on resistant gonorrhoea since 1996, but genomic epidemiology studies on this pathogen are lacking in the Philippines. We sequenced the whole genomes of 21 N. gonorrhoeae isolates collected in 2013-2014 by ARSP. The multilocus sequence type, multiantigen sequence type, presence of determinants of antimicrobial resistance and relatedness among the isolates were all derived from the sequence data. The concordance between phenotypic and genotypic resistance was also determined. Ten of 21 isolates were resistant to penicillin, ciprofloxacin and tetracycline, due mainly to the presence of the blaTEM gene, the S91F mutation in the gyrA gene and the tetM gene, respectively. None of the isolates was resistant to ceftriaxone or cefixime. The concordance between phenotypic and genotypic resistance was 92.38% overall for five antibiotics in four classes. Despite the small number of isolates studied, they were genetically diverse, as shown by the sequence types, the N. gonorrhoeae multiantigen sequence typing types and the tree. Comparison with global genomes placed the Philippine genomes within global lineage A and led to the identification of an international transmission route. This first genomic survey of N. gonorrhoeae isolates collected by ARSP will be used to contextualize prospective surveillance. It highlights the importance of genomic surveillance in the Western Pacific and other endemic regions for understanding the spread of drug-resistant gonorrhoea worldwide.

A global resource for genomic predictions of antimicrobial resistance and surveillance of Salmonella Typhi at pathogenwatch.

As whole-genome sequencing capacity becomes increasingly decentralized, there is a growing opportunity for collaboration and the sharing of surveillance data within and between countries to inform typhoid control policies. This vision requires free, community-driven tools that facilitate access to genomic data for public health on a global scale. Here we present the Pathogenwatch scheme for Salmonella enterica serovar Typhi (S. Typhi), a web application enabling the rapid identification of genomic markers of antimicrobial resistance (AMR) and contextualization with public genomic data. We show that the clustering of S. Typhi genomes in Pathogenwatch is comparable to established bioinformatics methods, and that genomic predictions of AMR are highly concordant with phenotypic susceptibility data. We demonstrate the public health utility of Pathogenwatch with examples selected from >4,300 public genomes available in the application. Pathogenwatch provides an intuitive entry point to monitor of the emergence and spread of S. Typhi high risk clones.

Genomic surveillance of Acinetobacter baumannii in the Philippines, 2013-2014.

OBJECTIVE: Acinetobacter baumannii is an opportunistic nosocomial pathogen that has increasingly become resistant to carbapenems worldwide. In the Philippines, rates of carbapenem resistance and multidrug resistance are above 50%. We undertook a genomic study of carbapenem-resistant A. baumannii in the Philippines to characterize the population diversity and antimicrobial resistance mechanisms. METHODS: We sequenced the whole genomes of 117 A. baumannii isolates recovered by 16 hospitals in the Philippines between 2013 and 2014. From the genome sequences, we determined the multilocus sequence type, presence of acquired determinants of antimicrobial resistance and relatedness between isolates. We also compared the phenotypic and genotypic resistance results. RESULTS: Carbapenem resistance was mainly explained by acquisition of the class-D ß-lactamase gene blaOXA-23. The concordance between phenotypic and genotypic resistance to imipenem was 98.15%, and it was 94.97% overall for the seven antibiotics analysed. Twenty-two different sequence types were identified, including 7 novel types. The population was dominated by the high-risk international clone 2 (i.e. clonal complex 92), in particular by ST195 and ST208 and their single locus variants. Using whole-genome sequencing, we identified local clusters representing potentially undetected nosocomial outbreaks, as well as multihospital clusters that indicated interhospital dissemination. Comparison with global genomes suggested that the establishment of carbapenem-resistant international clone 2 in the Philippines is likely the result of clonal expansion and geographical dissemination, and at least partly explained by inadequate hospital infection control and prevention. DISCUSSION: This is the first extensive genomic study of carbapenem-resistant A. baumannii in the Philippines, and it underscores the importance of hospital infection control and prevention measures to contain high-risk clones.

Genomic surveillance of Pseudomonas aeruginosa in the Philippines, 2013-2014.

Pseudomonas aeruginosa is an opportunistic pathogen that often causes nosocomial infections resistant to treatment. Rates of antimicrobial resistance (AMR) are increasing, as are rates of multidrug-resistant (MDR) and possible extensively drug-resistant (XDR) infections. Our objective was to characterize the molecular epidemiology and AMR mechanisms of this pathogen. We sequenced the whole genome for each of 176 P. aeruginosa isolates collected in the Philippines in 2013-2014; derived the multilocus sequence type (MLST), presence of AMR determinants and relatedness between isolates; and determined concordance between phenotypic and genotypic resistance. Carbapenem resistance was associated with loss of function of the OprD porin and acquisition of the metallo-ß-lactamase (MBL) gene bla VIM. Concordance between phenotypic and genotypic resistance was 93.27% overall for six antibiotics in three classes, but varied among aminoglycosides. The population of P. aeruginosa was diverse, with clonal expansions of XDR genomes belonging to MLSTs ST235, ST244, ST309 and ST773. We found evidence of persistence or reintroduction of the predominant clone ST235 in one hospital, and of transfer between hospitals. Most of the ST235 genomes formed a distinct lineage from global genomes, thus raising the possibility that they may be unique to the Philippines. In addition, long-read sequencing of one representative XDR ST235 isolate identified an integron carrying multiple resistance genes (including bla VIM-2), with differences in gene composition and synteny from the P. aeruginosa class 1 integrons described previously. The survey bridges the gap in genomic data from the Western Pacific Region and will be useful for ongoing surveillance; it also highlights the importance of curtailing the spread of ST235 within the Philippines.

Globetrotting strangles: the unbridled national and international transmission of Streptococcus equi between horses.

The equine disease strangles, which is characterized by the formation of abscesses in the lymph nodes of the head and neck, is one of the most frequently diagnosed infectious diseases of horses around the world. The causal agent, Streptococcus equi subspecies equi, establishes a persistent infection in approximately 10 % of animals that recover from the acute disease. Such 'carrier' animals appear healthy and are rarely identified during routine veterinary examinations pre-purchase or transit, but can transmit S. equi to naïve animals initiating new episodes of disease. Here, we report the analysis and visualization of phylogenomic and epidemiological data for 670 isolates of S. equi recovered from 19 different countries using a new core-genome multilocus sequence typing (cgMLST) web bioresource. Genetic relationships among all 670 S. equi isolates were determined at high resolution, revealing national and international transmission events that drive this endemic disease in horse populations throughout the world. Our data argue for the recognition of the international importance of strangles by the Office International des Épizooties to highlight the health, welfare and economic cost of this disease. The Pathogenwatch cgMLST web bioresource described herein is available for tailored genomic analysis of populations of S. equi and its close relative S. equi subspecies zooepidemicus that are recovered from horses and other animals, including humans, throughout the world. This article contains data hosted by Microreact.

Integrating whole-genome sequencing within the National Antimicrobial Resistance Surveillance Program in the Philippines.

National networks of laboratory-based surveillance of antimicrobial resistance (AMR) monitor resistance trends and disseminate these data to AMR stakeholders. Whole-genome sequencing (WGS) can support surveillance by pinpointing resistance mechanisms and uncovering transmission patterns. However, genomic surveillance is rare in low- and middle-income countries. Here, we implement WGS within the established Antimicrobial Resistance Surveillance Program of the Philippines via a binational collaboration. In parallel, we characterize bacterial populations of key bug-drug combinations via a retrospective sequencing survey. By linking the resistance phenotypes to genomic data, we reveal the interplay of genetic lineages (strains), AMR mechanisms, and AMR vehicles underlying the expansion of specific resistance phenotypes that coincide with the growing carbapenem resistance rates observed since 2010. Our results enhance our understanding of the drivers of carbapenem resistance in the Philippines, while also serving as the genetic background to contextualize ongoing local prospective surveillance.

PANINI: Pangenome Neighbour Identification for Bacterial Populations.

The standard workhorse for genomic analysis of the evolution of bacterial populations is phylogenetic modelling of mutations in the core genome. However, a notable amount of information about evolutionary and transmission processes in diverse populations can be lost unless the accessory genome is also taken into consideration. Here, we introduce panini (Pangenome Neighbour Identification for Bacterial Populations), a computationally scalable method for identifying the neighbours for each isolate in a data set using unsupervised machine learning with stochastic neighbour embedding based on the t-SNE (t-distributed stochastic neighbour embedding) algorithm. panini is browser-based and integrates with the Microreact platform for rapid online visualization and exploration of both core and accessory genome evolutionary signals, together with relevant epidemiological, geographical, temporal and other metadata. Several case studies with single- and multi-clone pneumococcal populations are presented to demonstrate the ability to identify biologically important signals from gene content data. panini is available at http://panini.pathogen.watch and code at http://gitlab.com/cgps/panini.

Diversification of Colonization Factors in a Multidrug-Resistant Escherichia coli Lineage Evolving under Negative Frequency-Dependent Selection.

Escherichia coli is a major cause of bloodstream and urinary tract infections globally. The wide dissemination of multidrug-resistant (MDR) strains of extraintestinal pathogenic E. coli (ExPEC) poses a rapidly increasing public health burden due to narrowed treatment options and increased risk of failure to clear an infection. Here, we present a detailed population genomic analysis of the ExPEC ST131 clone, in which we seek explanations for its success as an emerging pathogenic strain beyond the acquisition of antimicrobial resistance (AMR) genes. We show evidence for evolution toward separate ecological niches for the main clades of ST131 and differential evolution of anaerobic metabolism, key colonization, and virulence factors. We further demonstrate that negative frequency-dependent selection acting across accessory loci is a major mechanism that has shaped the population evolution of this pathogen.IMPORTANCE Infections with multidrug-resistant (MDR) strains of Escherichia coli are a significant global public health concern. To combat these pathogens, we need a deeper understanding of how they evolved from their background populations. By understanding the processes that underpin their emergence, we can design new strategies to limit evolution of new clones and combat existing clones. By combining population genomics with modelling approaches, we show that dominant MDR clones of E. coli are under the influence of negative frequency-dependent selection, preventing them from rising to fixation in a population. Furthermore, we show that this selection acts on genes involved in anaerobic metabolism, suggesting that this key trait, and the ability to colonize human intestinal tracts, is a key step in the evolution of MDR clones of E. coli.

Epidemic of carbapenem-resistant Klebsiella pneumoniae in Europe is driven by nosocomial spread.

Public health interventions to control the current epidemic of carbapenem-resistant Klebsiella pneumoniae rely on a comprehensive understanding of its emergence and spread over a wide range of geographical scales. We analysed the genome sequences and epidemiological data of >1,700 K. pneumoniae samples isolated from patients in 244 hospitals in 32 countries during the European Survey of Carbapenemase-Producing Enterobacteriaceae. We demonstrate that carbapenemase acquisition is the main cause of carbapenem resistance and that it occurred across diverse phylogenetic backgrounds. However, 477 of 682 (69.9%) carbapenemase-positive isolates are concentrated in four clonal lineages, sequence types 11, 15, 101, 258/512 and their derivatives. Combined analysis of the genetic and geographic distances between isolates with different ß-lactam resistance determinants suggests that the propensity of K. pneumoniae to spread in hospital environments correlates with the degree of resistance and that carbapenemase-positive isolates have the highest transmissibility. Indeed, we found that over half of the hospitals that contributed carbapenemase-positive isolates probably experienced within-hospital transmission, and interhospital spread is far more frequent within, rather than between, countries. Finally, we propose a value of 21 for the number of single nucleotide polymorphisms that optimizes the discrimination of hospital clusters and detail the international spread of the successful epidemic lineage, ST258/512.

Public health surveillance of multidrug-resistant clones of Neisseria gonorrhoeae in Europe: a genomic survey.

BACKGROUND: Traditional methods for molecular epidemiology of Neisseria gonorrhoeae are suboptimal. Whole-genome sequencing (WGS) offers ideal resolution to describe population dynamics and to predict and infer transmission of antimicrobial resistance, and can enhance infection control through linkage with epidemiological data. We used WGS, in conjunction with linked epidemiological and phenotypic data, to describe the gonococcal population in 20 European countries. We aimed to detail changes in phenotypic antimicrobial resistance levels (and the reasons for these changes) and strain distribution (with a focus on antimicrobial resistance strains in risk groups), and to predict antimicrobial resistance from WGS data. METHODS: We carried out an observational study, in which we sequenced isolates taken from patients with gonorrhoea from the European Gonococcal Antimicrobial Surveillance Programme in 20 countries from September to November, 2013. We also developed a web platform that we used for automated antimicrobial resistance prediction, molecular typing (N gonorrhoeae multi-antigen sequence typing [NG-MAST] and multilocus sequence typing), and phylogenetic clustering in conjunction with epidemiological and phenotypic data. FINDINGS: The multidrug-resistant NG-MAST genogroup G1407 was predominant and accounted for the most cephalosporin resistance, but the prevalence of this genogroup decreased from 248 (23%) of 1066 isolates in a previous study from 2009-10 to 174 (17%) of 1054 isolates in this survey in 2013. This genogroup previously showed an association with men who have sex with men, but changed to an association with heterosexual people (odds ratio=4·29). WGS provided substantially improved resolution and accuracy over NG-MAST and multilocus sequence typing, predicted antimicrobial resistance relatively well, and identified discrepant isolates, mixed infections or contaminants, and multidrug-resistant clades linked to risk groups. INTERPRETATION: To our knowledge, we provide the first use of joint analysis of WGS and epidemiological data in an international programme for regional surveillance of sexually transmitted infections. WGS provided enhanced understanding of the distribution of antimicrobial resistance clones, including replacement with clones that were more susceptible to antimicrobials, in several risk groups nationally and regionally. We provide a framework for genomic surveillance of gonococci through standardised sampling, use of WGS, and a shared information architecture for interpretation and dissemination by use of open access software. FUNDING: The European Centre for Disease Prevention and Control, The Centre for Genomic Pathogen Surveillance, Örebro University Hospital, and Wellcome.

Microreact: visualizing and sharing data for genomic epidemiology and phylogeography.

Visualization is frequently used to aid our interpretation of complex datasets. Within microbial genomics, visualizing the relationships between multiple genomes as a tree provides a framework onto which associated data (geographical, temporal, phenotypic and epidemiological) are added to generate hypotheses and to explore the dynamics of the system under investigation. Selected static images are then used within publications to highlight the key findings to a wider audience. However, these images are a very inadequate way of exploring and interpreting the richness of the data. There is, therefore, a need for flexible, interactive software that presents the population genomic outputs and associated data in a user-friendly manner for a wide range of end users, from trained bioinformaticians to front-line epidemiologists and health workers. Here, we present Microreact, a web application for the easy visualization of datasets consisting of any combination of trees, geographical, temporal and associated metadata. Data files can be uploaded to Microreact directly via the web browser or by linking to their location (e.g. from Google Drive/Dropbox or via API), and an integrated visualization via trees, maps, timelines and tables provides interactive querying of the data. The visualization can be shared as a permanent web link among collaborators, or embedded within publications to enable readers to explore and download the data. Microreact can act as an end point for any tool or bioinformatic pipeline that ultimately generates a tree, and provides a simple, yet powerful, visualization method that will aid research and discovery and the open sharing of datasets.