Search

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.

International audience; Background: Streptococcus equi subspecies equi (S.equi) is the cause of the highly contagious equine respiratory disease ‘strangles’. Approximately 10% of recovered animals can persistently carry the bacteria and transmit it to naïve animals. The global movement of horses is an ideal mechanism for widespread transmission to geographically distant locations.Objectives: Utilise whole-genome sequence data to disentangle the transmission of S. equi and subsequent outbreaks of strangles.Study design: In vitro analysis of micro-organisms.Methods: Isolates (n = 670) of S. equi were recovered from clinical samples submitted to multiple collaborating clinics and institutions globally. Following species confirmation, isolates underwent whole-genome sequencing using Illumina technology. Sequence reads passing quality control measures were assembled and uploaded to Pathogenwatch, which assigned a phylogeny based upon sequences of core genome alleles. Population structure was inferred using the population mixture analysis in BAPS.Results: BAPS clustered the isolates into six different clusters (BAPS 1-6) and showed dominant lineages in different geographical areas but also global transmission within the clusters. Sub-groups within the clusters highlighted multiple outbreaks at local, national and international scales and highlighted population structures and transmission dynamics within single locations. For example, four different strains collected over just seven months were identified in a single location. Sequence data also identified a statistically significant decline in BAPS-5 since 2010.Main limitations: Pathogenwatch has shown its utility in investigating S. equi transmission and population structure. However, it is based upon a curated set of 1286 core genome loci. Further investigations will need to be conducted using the full spectrum of data available from whole-genome sequencing.Conclusions: Pathogenwatch was used as a tool to rapidly identify and visualise the whole-genome sequence data of a large S. equi dataset. The data demonstrate widespread transmission of multiple S. equi lineages and provide strong evidence that asymptomatic carrier horses are perpetuating this dissemination.

EuSCAPE Working Group: Portugal - Manuela Caniça, Vera Manageiro 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 β-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. This work was funded by The Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Wellcome (grant nos. 098051 and 099202) and the NIHR Global Health Research Unit on Genomic Surveillance of Antimicrobial Resistance (NIHR 16/136/111). The EuSCAPE project was funded by ECDC through a specific framework contract (ECDC/2012/055) following an open call for tender (OJ/25/04/2012-PROC/2012/036). info:eu-repo/semantics/publishedVersion

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 beta-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.

Euro-GASP study group: INSA - Maria José Borrego Free PMC Article: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6010626/ 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. The European Centre for Disease Prevention and Control, The Centre for Genomic Pathogen Surveillance, Örebro University Hospital, and Wellcome. info:eu-repo/semantics/publishedVersion

The implementation of routine whole-genome sequencing (WGS) promises to transform our ability to monitor the emergence and spread of bacterial pathogens. Here we combined WGS data from 308 invasive Staphylococcus aureus isolates corresponding to a pan-European population snapshot, with epidemiological and resistance data. Geospatial visualization of the data is made possible by a generic software tool designed for public health purposes that is available at the project URL (http:// www.microreact.org/project/EkUvg9uY?tt=rc). Our analysis demonstrates that high-risk clones can be identified on the basis of population level properties such as clonal relatedness, abundance, and spatial structuring and by inferring virulence and resistance properties on the basis of gene content. We also show that in silico predictions of antibiotic resistance profiles are at least as reliable as phenotypic testing. We argue that this work provides a comprehensive road map illustrating the three vital components for future molecular epidemiological surveillance: (i) large-scale structured surveys, (ii) WGS, and (iii) communityoriented database infrastructure and analysis tools. IMPORTANCE The spread of antibiotic-resistant bacteria is a public health emergency of global concern, threatening medical intervention at every level of health care delivery. Several recent studies have demonstrated the promise of routine wholegenome sequencing (WGS) of bacterial pathogens for epidemiological surveillance, outbreak detection, and infection control. However, as this technology becomes more widely adopted, the key challenges of generating representative national and international data sets and the development of bioinformatic tools to manage and interpret the data become increasingly pertinent. This study provides a road map for the integration of WGS data into routine pathogen surveillance. We emphasize the importance of large-scale routine surveys to provide the population context for more targeted or localized investigation and the development of open-access bioinformatic tools to provide the means to combine and compare independently generated data with publicly available data sets.

Additional file 1: Table S1. List of studies included in the antimicrobial resistance benchmark analyses. Table S2. Point mutations and genes associated with antimicrobial resistance detected on the WHO 2016 reference panel. Table S3. Summary of the benchmark analysis. Table S4. List of genetic mechanisms detected on the test benchmark. Table S5. List of genetic mechanisms detected on the validation benchmark. Table S6. Public collections in N. gonorrhoeae Pathogenwatch. Table S7. Number of public N. gonorrhoeae genomes in Pathogenwatch by country.

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.

Additional file 3: Figure S1. Main Pathogenwatch layout. Figure S2. Combination of Pathogenwatch collections. Figure S3. Genome reports and cgMLST cluster view. Figure S4. Mapping of short reads from WHO U to the reference genome assembly. Figure S5. Minimum inhibitory concentration values for azithromycin in N. gonorrhoeae isolates with different combinations of antimicrobial resistance genetic mechanisms. Figure S6. Minimum inhibitory concentration values for ceftriaxone in N. gonorrhoeae isolates with different combinations of antimicrobial resistance genetic mechanisms. Figure S7. Minimum inhibitory concentration values for cefixime in N. gonorrhoeae isolates with different combinations of antimicrobial resistance genetic mechanisms. Figure S8. Minimum inhibitory concentration values for ciprofloxacin in N. gonorrhoeae isolates with different combinations of antimicrobial resistance genetic mechanisms. Figure S9. Minimum inhibitory concentration values for tetracycline in N. gonorrhoeae isolates with different combinations of antimicrobial resistance genetic mechanisms. Figure S10. Minimum inhibitory concentration values for benzylpenicillin in N. gonorrhoeae isolates with different combinations of antimicrobial resistance genetic mechanisms. Figure S11. Consistency of major N. gonorrhoeae population lineages and clusters observed in scientific publications with the Pathogenwatch phylogenetic trees. Figure S12. Geographical distribution of public N. gonorrhoeae genomes in Pathogenwatch.

Additional file 3: Figure S1. Main Pathogenwatch layout. Figure S2. Combination of Pathogenwatch collections. Figure S3. Genome reports and cgMLST cluster view. Figure S4. Mapping of short reads from WHO U to the reference genome assembly. Figure S5. Minimum inhibitory concentration values for azithromycin in N. gonorrhoeae isolates with different combinations of antimicrobial resistance genetic mechanisms. Figure S6. Minimum inhibitory concentration values for ceftriaxone in N. gonorrhoeae isolates with different combinations of antimicrobial resistance genetic mechanisms. Figure S7. Minimum inhibitory concentration values for cefixime in N. gonorrhoeae isolates with different combinations of antimicrobial resistance genetic mechanisms. Figure S8. Minimum inhibitory concentration values for ciprofloxacin in N. gonorrhoeae isolates with different combinations of antimicrobial resistance genetic mechanisms. Figure S9. Minimum inhibitory concentration values for tetracycline in N. gonorrhoeae isolates with different combinations of antimicrobial resistance genetic mechanisms. Figure S10. Minimum inhibitory concentration values for benzylpenicillin in N. gonorrhoeae isolates with different combinations of antimicrobial resistance genetic mechanisms. Figure S11. Consistency of major N. gonorrhoeae population lineages and clusters observed in scientific publications with the Pathogenwatch phylogenetic trees. Figure S12. Geographical distribution of public N. gonorrhoeae genomes in Pathogenwatch.

Additional file 1: Table S1. List of studies included in the antimicrobial resistance benchmark analyses. Table S2. Point mutations and genes associated with antimicrobial resistance detected on the WHO 2016 reference panel. Table S3. Summary of the benchmark analysis. Table S4. List of genetic mechanisms detected on the test benchmark. Table S5. List of genetic mechanisms detected on the validation benchmark. Table S6. Public collections in N. gonorrhoeae Pathogenwatch. Table S7. Number of public N. gonorrhoeae genomes in Pathogenwatch by country.

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., Whole genome sequencing data are increasingly becoming routinely available but generating actionable insights is challenging. Here, the authors describe Pathogenwatch, a web tool for genomic surveillance of S. Typhi, and demonstrate its use for antimicrobial resistance assignment and strain risk assessment.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance datagenerated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021.