Dataset Information

Routine Whole-Genome Sequencing for Outbreak Investigations of Staphylococcus aureus in a National Reference Center.

ABSTRACT: The French National Reference Center for Staphylococci currently uses DNA arrays and spa typing for the initial epidemiological characterization of Staphylococcus aureus strains. We here describe the use of whole-genome sequencing (WGS) to investigate retrospectively four distinct and virulent S. aureus lineages [clonal complexes (CCs): CC1, CC5, CC8, CC30] involved in hospital and community outbreaks or sporadic infections in France. We used a WGS bioinformatics pipeline based on de novo assembly (reference-free approach), single nucleotide polymorphism analysis, and on the inclusion of epidemiological markers. We examined the phylogeographic diversity of the French dominant hospital-acquired CC8-MRSA (methicillin-resistant S. aureus) Lyon clone through WGS analysis which did not demonstrate evidence of large-scale geographic clustering. We analyzed sporadic cases along with two outbreaks of a CC1-MSSA (methicillin-susceptible S. aureus) clone containing the Panton-Valentine leukocidin (PVL) and results showed that two sporadic cases were closely related. We investigated an outbreak of PVL-positive CC30-MSSA in a school environment and were able to reconstruct the transmission history between eight families. We explored different outbreaks among newborns due to the CC5-MRSA Geraldine clone and we found evidence of an unsuspected link between two otherwise distinct outbreaks. Here, WGS provides the resolving power to disprove transmission events indicated by conventional methods (same sequence type, spa type, toxin profile, and antibiotic resistance profile) and, most importantly, WGS can reveal unsuspected transmission events. Therefore, WGS allows to better describe and understand outbreaks and (inter-)national dissemination of S. aureus lineages. Our findings underscore the importance of adding WGS for (inter-)national surveillance of infections caused by virulent clones of S. aureus but also substantiate the fact that technological optimization at the bioinformatics level is still urgently needed for routine use. However, the greatest limitation of WGS analysis is the completeness and the correctness of the reference database being used and the conversion of floods of data into actionable results. The WGS bioinformatics pipeline (EpiSeqTM) we used here can easily generate a uniform database and associated metadata for epidemiological applications.

SUBMITTER: Durand G

PROVIDER: S-EPMC5869177 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Routine Whole-Genome Sequencing for Outbreak Investigations of Staphylococcus aureus in a National Reference Center.

Durand Geraldine G Javerliat Fabien F Bes Michèle M Veyrieras Jean-Baptiste JB Guigon Ghislaine G Mugnier Nathalie N Schicklin Stéphane S Kaneko Gaël G Santiago-Allexant Emmanuelle E Bouchiat Coralie C Martins-Simões Patrícia P Laurent Frederic F Van Belkum Alex A Vandenesch François F Tristan Anne A

Frontiers in microbiology 20180320

The French National Reference Center for Staphylococci currently uses DNA arrays and spa typing for the initial epidemiological characterization of Staphylococcus aureus strains. We here describe the use of whole-genome sequencing (WGS) to investigate retrospectively four distinct and virulent S. aureus lineages [clonal complexes (CCs): CC1, CC5, CC8, CC30] involved in hospital and community outbreaks or sporadic infections in France. We used a WGS bioinformatics pipeline ba ...[more]

PMID: 29616014

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Project description:Whole-genome sequencing (WGS) makes it possible to determine the relatedness of bacterial isolates at a high resolution, thereby helping to characterize outbreaks. However, for Staphylococcus aureus, the accumulation of within-host diversity during carriage might limit the interpretation of sequencing data. In this study, we hypothesized the converse, namely, that within-host diversity can in fact be exploited to reveal the involvement of long-term carriers (LTCs) in outbreaks. We analyzed WGS data from 20 historical outbreaks and applied phylogenetic methods to assess genetic relatedness and to estimate the time to most recent common ancestor (TMRCA). The findings were compared with the routine investigation results and epidemiological evidence. Outbreaks with epidemiological evidence for an LTC source had a mean estimated TMRCA (adjusted for outbreak duration) of 243 days (95% highest posterior density interval [HPD], 143 to 343 days) compared with 55 days (95% HPD, 28 to 81 days) for outbreaks lacking epidemiological evidence for an LTC (P = 0.004). A threshold of 156 days predicted LTC involvement with a sensitivity of 0.875 and a specificity of 1. We also found 6/20 outbreaks included isolates with differing antimicrobial susceptibility profiles; however, these had only modestly increased pairwise diversity (mean 17.5 single nucleotide variants [SNVs] [95% confidence interval {CI}, 17.3 to 17.8]) compared with isolates with identical antibiograms (12.7 SNVs [95% CI, 12.5 to 12.8]) (P < 0.0001). Additionally, for 2 outbreaks, WGS identified 1 or more isolates that were genetically distinct despite having the outbreak pulsed-field gel electrophoresis (PFGE) pulsotype. The duration-adjusted TMRCA allowed the involvement of LTCs in outbreaks to be identified and could be used to decide whether screening for long-term carriage (e.g., in health care workers) is warranted. Requiring identical antibiograms to trigger investigation could miss important contributors to outbreaks.

Project description:BackgroundThe emergence of meticillin-resistant Staphylococcus aureus (MRSA) that can persist in the community and replace existing hospital-adapted lineages of MRSA means that it is necessary to understand transmission dynamics in terms of hospitals and the community as one entity. We assessed the use of whole-genome sequencing to enhance detection of MRSA transmission between these settings.MethodsWe studied a putative MRSA outbreak on a special care baby unit (SCBU) at a National Health Service Foundation Trust in Cambridge, UK. We used whole-genome sequencing to validate and expand findings from an infection-control team who assessed the outbreak through conventional analysis of epidemiological data and antibiogram profiles. We sequenced isolates from all colonised patients in the SCBU, and sequenced MRSA isolates from patients in the hospital or community with the same antibiotic susceptibility profile as the outbreak strain.FindingsThe hospital infection-control team identified 12 infants colonised with MRSA in a 6 month period in 2011, who were suspected of being linked, but a persistent outbreak could not be confirmed with conventional methods. With whole-genome sequencing, we identified 26 related cases of MRSA carriage, and showed transmission occurred within the SCBU, between mothers on a postnatal ward, and in the community. The outbreak MRSA type was a new sequence type (ST) 2371, which is closely related to ST22, but contains genes encoding Panton-Valentine leucocidin. Whole-genome sequencing data were used to propose and confirm that MRSA carriage by a staff member had allowed the outbreak to persist during periods without known infection on the SCBU and after a deep clean.InterpretationWhole-genome sequencing holds great promise for rapid, accurate, and comprehensive identification of bacterial transmission pathways in hospital and community settings, with concomitant reductions in infections, morbidity, and costs.FundingUK Clinical Research Collaboration Translational Infection Research Initiative, Wellcome Trust, Health Protection Agency, and the National Institute for Health Research Cambridge Biomedical Research Centre.

Project description:UnlabelledThe 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) community-oriented database infrastructure and analysis tools.ImportanceThe 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 whole-genome 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.

Project description:Biofilms are a frequent cause of food contamination of potentially pathogenic bacteria, such as Staphylococcus aureus. Given its vast role in human disease, the possible impact of biofilm-producing S. aureus isolates in a food processing environment is evident. Sixty-nine S. aureus isolates collected from one firm following multiple staphylococcal food poisoning outbreak investigations were utilized for this analysis. Strain evaluations were performed to establish virulence determinants and the evolutionary relationships using data generated by shotgun whole-genome sequencing (WGS), along with end point polymerase chain reaction (PCR) and in vitro phenotypic assessments. S. aureus isolates were grouped into six well-supported clades in the phylogenetic tree, with the relationships within the clades indicating a strong degree of clonal structure. Our analysis identified four major sequence types 47.8% ST1, 31.9% ST45, 7.2% ST5, and 7.2% ST30 and two major spa types 47.8% t127 and 29.0% t3783. Extrapolated staphylococcal enterotoxin (SE) analysis found that all isolates were positive for at least 1 of the 23 SEs and/or SE-like toxin genes. Enterotoxigenic assessments found that 93% of the isolates expressed a classical SE(A-E). SE gene concurrence was observed at 96.2%, based on PCR and WGS results. In total, 46 gene targets were distinguished. This included genes that encode for adhesion and biofilm synthesis such as clfA, clfB, bbp, ebpS, ica, bap and agr. Our evaluation found agr group III to be the most prevalent at 55%, followed by 35% for agr group I. All isolates harbored the complete intercellular adhesion operon that is recognized to contain genes responsible for the adhesion step of biofilm formation by encoding proteins involved in the syntheses of the biofilm matrix. Phenotypic characterization of biofilm formation was evaluated three times, with each test completed in triplicate and accomplished utilizing the microtiter plate method and Congo red agar (CRA). The microtiter plate results indicated moderate to high biofilm formation for 96% of the isolates, with 4% exhibiting weak to no biofilm development. CRA results yielded all positive to intermediate results. The potential to inadvertently transfer pathogenic bacteria from the environment into food products creates challenges to any firm and may result in adulterated food.

Project description:Despite being a well-established research method, the use of whole-genome sequencing (WGS) for routine molecular typing and pathogen characterization remains a substantial challenge due to the required bioinformatics resources and/or expertise. Moreover, many national reference laboratories and centers, as well as other laboratories working under a quality system, require extensive validation to demonstrate that employed methods are "fit-for-purpose" and provide high-quality results. A harmonized framework with guidelines for the validation of WGS workflows does currently, however, not exist yet, despite several recent case studies highlighting the urgent need thereof. We present a validation strategy focusing specifically on the exhaustive characterization of the bioinformatics analysis of a WGS workflow designed to replace conventionally employed molecular typing methods for microbial isolates in a representative small-scale laboratory, using the pathogen Neisseria meningitidis as a proof-of-concept. We adapted several classically employed performance metrics specifically toward three different bioinformatics assays: resistance gene characterization (based on the ARG-ANNOT, ResFinder, CARD, and NDARO databases), several commonly employed typing schemas (including, among others, core genome multilocus sequence typing), and serogroup determination. We analyzed a core validation dataset of 67 well-characterized samples typed by means of classical genotypic and/or phenotypic methods that were sequenced in-house, allowing to evaluate repeatability, reproducibility, accuracy, precision, sensitivity, and specificity of the different bioinformatics assays. We also analyzed an extended validation dataset composed of publicly available WGS data for 64 samples by comparing results of the different bioinformatics assays against results obtained from commonly used bioinformatics tools. We demonstrate high performance, with values for all performance metrics >87%, >97%, and >90% for the resistance gene characterization, sequence typing, and serogroup determination assays, respectively, for both validation datasets. Our WGS workflow has been made publicly available as a "push-button" pipeline for Illumina data at https://galaxy.sciensano.be to showcase its implementation for non-profit and/or academic usage. Our validation strategy can be adapted to other WGS workflows for other pathogens of interest and demonstrates the added value and feasibility of employing WGS with the aim of being integrated into routine use in an applied public health setting.

Dataset Information

Routine Whole-Genome Sequencing for Outbreak Investigations of Staphylococcus aureus in a National Reference Center.

Publications

Routine Whole-Genome Sequencing for Outbreak Investigations of <i>Staphylococcus aureus</i> in a National Reference Center.

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