Dataset Information

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

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

SUBMITTER: Ashton PM

PROVIDER: S-EPMC4824889 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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

Ashton Philip M PM Nair Satheesh S Peters Tansy M TM Bale Janet A JA Powell David G DG Painset Anaïs A Tewolde Rediat R Schaefer Ulf U Jenkins Claire C Dallman Timothy J TJ de Pinna Elizabeth M EM Grant Kathie A KA

PeerJ 20160405

In April 2015, Public Health England implemented whole genome sequencing (WGS) as a routine typing tool for public health surveillance of Salmonella, adopting a multilocus sequence typing (MLST) approach as a replacement for traditional serotyping. The WGS derived sequence type (ST) was compared to the phenotypic serotype for 6,887 isolates of S. enterica subspecies I, and of these, 6,616 (96%) were concordant. Of the 4% (n = 271) of isolates of subspecies I exhibiting a mismatch, 119 were due t ...[more]

PMID: 27069781

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Project description:Until recently, traditional serology and the Kauffmann White Scheme (KWS) have been the gold standard for Salmonella serotyping. Whole Genome Sequencing (WGS) has now emerged as an alternative in this field. Serotype information remains a cornerstone in food safety and public health activities to reduce the burden of salmonellosis. At the same time, recent advances in WGS have improved the ability to perform advanced pathogen characterization while improving trace back investigations to determine the source of foodborne illness during outbreaks. Serovar prediction based on WGS can be performed using in silico data analysis tools. Three such tools have been developed: (a). Salmonella in silico Typing Resource (SISTR), (b). SeqSero, and (c). in silico 7-gene MLST ST (Multilocus Sequence Typing Sub-Typing) which was generated using the SISTR platform. Public health officials around the world are diligently working to validate these tools for replacing traditional surveillance methods to provide a more powerful approach for molecular epidemiology in support of public health investigations. In this study, we report a retrospective analysis of our laboratory inventory of 1,041 Salmonella isolates collected between 1999 and 2017. These isolates are of public health significance since they all came from either food, feed or environmental swabs. They were all serotyped by both traditional serology and WGS using an in silico SeqSero tool for serovar prediction. Both predicted identical Salmonella serotypes in 899 isolates (86.4% of the 1,041 Salmonella isolates). SeqSero assignments differed from traditional serological testing in 80 isolates (7.7%) and no serotype prediction was ascertained from 62 isolates (5.9%). This retrospective study is an excellent example of using WGS and SeqSero as a data analysis tool to predict Salmonella serotypes that can provide numerous advantages including molecular and genetic details regarding the characteristics of the Salmonella isolates compared to traditional KWS serotyping. In conclusion, it is evident that using WGS and in silico tools for Salmonella serotyping might someday replace traditional serotyping.

Project description:Shiga toxin-producing Escherichia coli (STEC) are considered to be a significant threat to public health due to the severity of gastrointestinal symptoms associated with human infection. In England STEC O157 is the most commonly detected STEC serogroup, however, the implementation of PCR at local hospital laboratories has resulted in an increase in the detection of non-O157 STEC. The aim of this study was to evaluate the use of whole genome sequencing (WGS) for routine public health surveillance of non-O157 STEC by comparing this approach to phenotypic serotyping and PCR for subtyping the stx-encoding genes. Of the 102 isolates where phenotypic and genotypic serotyping could be compared, 98 gave fully concordant results. The most common non-O157 STEC serogroups detected were O146 (22) and O26 (18). All but one of the 38 isolates that could not be phenotypically serotyped (designated O unidentifiable or O rough) were serotyped using the WGS data. Of the 73 isolates where a flagella type was available by traditional phenotypic typing, all results matched the H-type derived from the WGS data. Of the 140 sequenced non-O157 isolates, 52 (37.1%) harboured stx1 only, 42 (30.0%) had stx2 only, 46 (32.9%) carried stx1 and stx2. Of these, stx subtyping PCR results were available for 131 isolates and 121 of these had concordant results with the stx subtype derived from the WGS data. Of the 10 discordant results, non-specific primer binding during PCR amplification, due to the similarity of the stx2 subtype gene sequences was the most likely cause. The results of this study showed WGS provided a reliable and robust one-step process for characterization of STEC. Deriving the full serotype from WGS data in real time has enabled us to report a higher level of strain discrimination while stx subtyping provides data on the pathogenic potential of each isolate, enabling us to predict clinical outcome of each case and to monitor the emergence of hyper-virulent strains.

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:ImportanceThe latest generation of benchtop DNA sequencing platforms can provide an accurate whole-genome sequence (WGS) for a broad range of bacteria in less than a day. These could be used to more effectively contain the spread of multidrug-resistant pathogens.ObjectiveTo compare WGS with standard clinical microbiology practice for the investigation of nosocomial outbreaks caused by multidrug-resistant bacteria, the identification of genetic determinants of antimicrobial resistance, and typing of other clinically important pathogens.Design, setting, and participantsA laboratory-based study of hospital inpatients with a range of bacterial infections at Cambridge University Hospitals NHS Foundation Trust, a secondary and tertiary referral center in England, comparing WGS with standard diagnostic microbiology using stored bacterial isolates and clinical information.Main outcomes and measuresSpecimens were taken and processed as part of routine clinical care, and cultured isolates stored and referred for additional reference laboratory testing as necessary. Isolates underwent DNA extraction and library preparation prior to sequencing on the Illumina MiSeq platform. Bioinformatic analyses were performed by persons blinded to the clinical, epidemiologic, and antimicrobial susceptibility data.ResultsWe investigated 2 putative nosocomial outbreaks, one caused by vancomycin-resistant Enterococcus faecium and the other by carbapenem-resistant Enterobacter cloacae; WGS accurately discriminated between outbreak and nonoutbreak isolates and was superior to conventional typing methods. We compared WGS with standard methods for the identification of the mechanism of carbapenem resistance in a range of gram-negative bacteria (Acinetobacter baumannii, E cloacae, Escherichia coli, and Klebsiella pneumoniae). This demonstrated concordance between phenotypic and genotypic results, and the ability to determine whether resistance was attributable to the presence of carbapenemases or other resistance mechanisms. Whole-genome sequencing was used to recapitulate reference laboratory typing of clinical isolates of Neisseria meningitidis and to provide extended phylogenetic analyses of these.Conclusions and relevanceThe speed, accuracy, and depth of information provided by WGS platforms to confirm or refute outbreaks in hospitals and the community, and to accurately define transmission of multidrug-resistant and other organisms, represents an important advance.

Dataset Information

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

Publications

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

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