The Salmonella In Silico Typing Resource (SISTR): An Open Web-Accessible Tool for Rapidly Typing and Subtyping Draft Salmonella Genome Assemblies

Whole genome sequencing confirms source of pathogens associated with bacterial foodborne illness in pets fed raw pet food

Reports of raw meat pet food containing zoonotic foodborne bacteria, including Salmonella, Escherichia coli, and Listeria monocytogenes, are increasing. Contaminated raw pet food and biological waste from pets consuming those diets may pose a public health risk. The U.S. Food and Drug Administration Veterinary Laboratory Investigation and Response Network conducted 2 case investigations, involving 3 households with animal illnesses, which included medical record review, dietary and environmental exposure interviews, animal sample testing, and whole genome sequencing (WGS) of bacteria isolated from the pets and the raw pet food. For each case investigation, WGS with core genome multi-locus sequence typing analysis showed that the animal clinical isolates were closely related to one or more raw pet food bacterial isolates. WGS and genomic analysis of paired animal clinical and animal food isolates can confirm suspected outbreaks of animal foodborne illness.

Persistent Infection and Long-Term Carriage of Typhoidal and Nontyphoidal Salmonellae

The ability of pathogenic bacteria to affect higher organisms and cause disease is one of the most dramatic properties of microorganisms. Some pathogens can establish transient colonization only, but others are capable of infecting their host for many years or even for a lifetime. Long-term infection is called persistence, and this phenotype is fundamental for the biology of important human pathogens, including Helicobacter pylori, Mycobacterium tuberculosis, and Salmonella enterica Both typhoidal and nontyphoidal serovars of the species Salmonella enterica can cause persistent infection in humans; however, as these two Salmonella groups cause clinically distinct diseases, the characteristics of their persistent infections in humans differ significantly. Here, following a general summary of Salmonella pathogenicity, host specificity, epidemiology, and laboratory diagnosis, I review the current knowledge about Salmonella persistence and discuss the relevant epidemiology of persistence (including carrier rate, duration of shedding, and host and pathogen risk factors), the host response to Salmonella persistence, Salmonella genes involved in this lifestyle, as well as genetic and phenotypic changes acquired during prolonged infection within the host. Additionally, I highlight differences between the persistence of typhoidal and nontyphoidal Salmonella strains in humans and summarize the current gaps and limitations in our understanding, diagnosis, and curing of persistent Salmonella infections.

An improved DNA array-based classification method for the identification of Salmonella serotypes shows high concordance between traditional and genotypic testing

Previously we developed and tested the Salmonella GenoSerotyping Array (SGSA), which utilized oligonucleotide probes for O- and H- antigen biomarkers to perform accurate molecular serotyping of 57 Salmonella serotypes. Here we describe the development and validation of the ISO 17025 accredited second version of the SGSA (SGSA v. 2) with reliable and unambiguous molecular serotyping results for 112 serotypes of Salmonella which were verified both in silico and in vitro. Improvements included an expansion of the probe sets along with a new classifier tool for prediction of individual antigens and overall serotype from the array probe intensity results. The array classifier and probe sequences were validated in silico to high concordance using 36,153 draft genomes of diverse Salmonella serotypes assembled from public repositories. We obtained correct and unambiguous serotype assignments for 31,924 (88.30%) of the tested samples and a further 3,916 (10.83%) had fully concordant antigen predictions but could not be assigned to a single serotype. The SGSA v. 2 can directly use bacterial colonies with a limit of detection of 860 CFU/mL or purified DNA template at a concentration of 1.0 x 10⁻¹ ng/μl. The SGSA v. 2 was also validated in the wet laboratory and certified using panel of 406 samples representing 185 different serotypes with correct antigen and serotype determinations for 60.89% of the panel and 18.31% correctly identified but an ambiguous overall serotype determination.

Evaluation of whole-genome sequencing for outbreak detection of Verotoxigenic Escherichia coli O157:H7 from the Canadian perspective

BACKGROUND

Rapid and accurate identification of Verotoxigenic Escherichia coli (VTEC) O157:H7 is dependent on well-established, standardized and highly discriminatory typing methods. Currently, conventional subtyping tests for foodborne bacterial pathogen surveillance are rapidly being replaced with whole-genome sequencing (WGS) in public health laboratories. The capacity of WGS to revolutionize global foodborne disease surveillance has positioned this tool to become the new gold standard; however, to ensure evidence standards for public health decision making can still be achieved, the performance of WGS must be thoroughly validated against current gold standard methods prior to implementation. Here we aim to verify the performance of WGS in comparison to pulsed-field gel electrophoresis (PFGE) and multiple-locus variable-number tandem repeat analysis (MLVA) for eight retrospective outbreaks of VTEC O157:H7 from the Canadian perspective. Since real-time implementation and routine use of WGS in public health laboratories is highly reliant on standardized data analysis tools, we also provide a comparative analysis of two popular methodologies for WGS analyses; an in-house developed single nucleotide variant phylogenomics (SNVPhyl) pipeline and the BioNumerics whole genome multilocus sequence typing (wgMLST) tool. To provide a useful and consistent starting point for examining laboratory-based surveillance data for VTEC O157:H7 in Canada, we also aim to describe the number of genetic differences observed among outbreak-associated isolates.

RESULTS

WGS provided enhanced resolution over traditional subtyping methods, and accurately distinguished outbreak-related isolates from non-outbreak related isolates with high epidemiological concordance. WGS also illuminated potential linkages between sporadic cases of illness and contaminated food, and isolates spanning multiple years. The topologies generated by SNVPhyl and wgMLST were highly congruent with strong statistical support. Few genetic differences were observed among outbreak-related isolates (≤5 SNVs/ < 10 wgMLST alleles) unless the outbreak was suspected to be multi-strain.

CONCLUSIONS

This study validates the superiority of WGS and indicates the BioNumerics wgMLST schema is suitable for surveillance and cluster detection of VTEC O157:H7. These findings will provide a useful and consistent starting point for examining WGS data for prospective laboratory-based surveillance of VTEC O157:H7, but however, the data will continue to be interpreted according to context and in combination with epidemiological and food safety evidence to inform public-health decision making in Canada.

Diversity-Generating Machines: Genetics of Bacterial Sugar-Coating

Bacterial pathogens and commensals are surrounded by diverse surface polysaccharides which include capsules and lipopolysaccharides. These carbohydrates play a vital role in bacterial ecology and interactions with the environment. Here, we review recent rapid advancements in this field, which have improved our understanding of the roles, structures, and genetics of bacterial polysaccharide antigens. Genetic loci encoding the biosynthesis of these antigens may have evolved as bacterial diversity-generating machines, driven by selection from a variety of forces, including host immunity, bacteriophages, and cell-cell interactions. We argue that the high adaptive potential of polysaccharide antigens should be taken into account in the design of polysaccharide-targeting medical interventions like conjugate vaccines and phage-based therapies.

Complete Closed Genome Sequences of Three Salmonella enterica subsp. enterica Serovar Dublin Strains Isolated from Cattle at Harvest

Salmonella enterica subsp. enterica serovar Dublin is a host-adapted pathogen for cattle that can cause invasive disease in humans. To facilitate genomic comparisons characterizing virulence determinants of this pathogen, we present the complete genome sequences of three S. Dublin strains isolated from bovine sources at harvest.

Establishment of a suspension array for Pseudomonas aeruginosa O-antigen serotyping

Pseudomonas aeruginosa (P. aeruginosa) is widespread in the environment. It readily infects hospital and immunocompromised patients. Traditional biochemical and immunological diagnoses of P. aeruginosa infection cannot meet clinical demands. The variability of O-antigens is the primary basis for the serotyping schemes of many gram-negative bacteria, which is the most widely used method for pathogenic epidemiological purposes. In this study, we developed a suspension array that can accurately diagnose and identify 19 different P. aeruginosa O-antigen serotypes except O15, whose O-antigen gene cluster has not been characterized. In this assay, wzx/wzy genes were selected as the sero-specific gene for 18 serotypes other than O6, for which the glycosyltransferase gene wbpP was utilized. Meanwhile, the wzy_β gene was added to separate O2/16 from O5/18/20, and the insertion sequence (IS) in wzx was used to separate O17 from O11. Eighty-two clinical isolates were screened to test our assay. A total of 65 isolates (79.3%) could be serotyped, and the result were confirmed to be correct by sequencing. Sensitivity analysis indicated that at least 5 ng DNA or 10³ CFU cells could be detected using our suspension array. To our knowledge, this is the first report on serotyping P. aeruginosa by suspension array and may be of great value in the clinical diagnostics of P. aeruginosa infection.

A real-time PCR regimen for testing environmental samples for Salmonella enterica subsp. enterica serovars of concern to the poultry industry, with special focus on Salmonella Enteritidis

A real-time PCR (qPCR) regimen, using up to six genetic targets, was developed to rapidly detect Salmonella and in particular identify Salmonella Enteritidis. The test regimen was first evaluated using a reference culture collection of Salmonella to confirm the appropriateness of the selected targets, which included up to three genetic markers for discrimination of Salmonella Enteritidis from other Salmonella serovars commonly found in poultry facilities. The qPCR procedure was then compared with culture methods used to detect Salmonella using a collection of enrichment broths previously generated from 239 environmental samples collected from a large number of hatchery facilities across Canada over several years. The qPCR regimen facilitated specific detection of Salmonella Enteritidis, and on a sample basis, it showed excellent agreement with the culture methods. Moreover, in many cases, qPCR detected Salmonella earlier in the culture process than did the culture method. Application of this method will significantly shorten test times and allow more timely identification of infected poultry premises, thereby improving present programmes aimed at controlling Salmonella Enteritidis at the environmental source.

Whole genome sequencing analysis of multiple Salmonella serovars provides insights into phylogenetic relatedness, antimicrobial resistance, and virulence markers across humans, food animals and agriculture environmental sources

Background

Salmonella enterica is a significant foodborne pathogen, which can be transmitted via several distinct routes, and reports on acquisition of antimicrobial resistance (AMR) are increasing. To better understand the association between human Salmonella clinical isolates and the potential environmental/animal reservoirs, whole genome sequencing (WGS) was used to investigate the epidemiology and AMR patterns within Salmonella isolates from two adjacent US states.

Results

WGS data of 200 S. enterica isolates recovered from human (n = 44), swine (n = 32), poultry (n = 22), and farm environment (n = 102) were used for in silico prediction of serovar, distribution of virulence genes, and phylogenetically clustered using core genome single nucleotide polymorphism (SNP) and feature frequency profiling (FFP). Furthermore, AMR was studied both by genotypic prediction using five curated AMR databases, and compared to phenotypic AMR using broth microdilution. Core genome SNP-based and FFP-based phylogenetic trees showed consistent clustering of isolates into the respective serovars, and suggested clustering of isolates based on the source of isolation. The overall correlation of phenotypic and genotypic AMR was 87.61% and 97.13% for sensitivity and specificity, respectively. AMR and virulence genes clustered with the Salmonella serovars, while there were also associations between the presence of virulence genes in both animal/environmental isolates and human clinical samples.

Conclusions

WGS is a helpful tool for Salmonella phylogenetic analysis, AMR and virulence gene predictions. The clinical isolates clustered closely with animal and environmental isolates, suggesting that animals and environment are potential sources for dissemination of AMR and virulence genes between Salmonella serovars.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5137-4) contains supplementary material, which is available to authorized users.

Complete Genome and Plasmid Sequences of 32 Salmonella enterica Strains from 30 Serovars

We report here 32 completed closed genome sequences of strains representing 30 serotypes of Salmonella. These genome sequences will provide useful references for understanding the genetic variation within Salmonella enterica serotypes, particularly as references to aid in comparative genomics studies, as well as providing information for improving in silico serotyping accuracy.

Genomic Characterization of Extended-Spectrum Cephalosporin-Resistant Salmonella enterica in the Colombian Poultry Chain

Salmonella enterica serovars have been isolated from Colombian broilers and broiler meat. The aim of this study was to investigate the diversity of ESBL/pAmpC genes in extended-spectrum cephalosporin resistant Salmonella enterica and the phylogeny of ESBL/pAmpC-carrying Salmonella using Whole Genome Sequencing (WGS). A total of 260 cefotaxime resistant Salmonella isolates, obtained between 2008 and 2013 from broiler farms, slaughterhouses and retail, were included. Isolates were screened by PCR for ESBL/pAmpC genes. Gene and plasmid subtyping and strain Multi Locus Sequence Typing was performed in silico for a selection of fully sequenced isolates. Core-genome-based analyses were performed per ST encountered. bla CMY-2-like was carried in 168 isolates, 52 carried bla CTX-M-2 group, 7 bla SHV, 5 a combination of bla CMY-2-like-bla SHV and 3 a combination of bla CMY-2-like-bla CTX-M-2 group. In 25 isolates no ESBL/pAmpC genes that were screened for were found. WGS characterization of 36 selected strains showed plasmid-encoded bla CMY-2 in 21, bla CTX-M-165 in 11 and bla SHV-12 in 7 strains. These genes were mostly carried on IncI1/ST12, IncQ1, and IncI1/ST231 plasmids, respectively. Finally, 17 strains belonged to S. Heidelberg ST15, 16 to S. Paratyphi B variant Java ST28, 1 to S. Enteritidis ST11, 1 to S. Kentucky ST152 and 1 to S. Albany ST292. Phylogenetic comparisons with publicly available genomes showed separate clustering of Colombian S. Heidelberg and S. Paratyphi B var. Java. In conclusion, resistance to extended-spectrum cephalosporins in Salmonella from Colombian poultry is mainly encoded by bla CMY-2 and bla CTX-M-165 genes. These genes are mostly associated with IncI1/ST12 and IncQ1 plasmids, respectively. Evolutionary divergence is observed between Colombian S. Heidelberg and S. Paratyphi B var. Java and those from other countries.

Molecular-based identification and detection of Salmonella in food production systems: current perspectives

Salmonella remains a prominent cause of foodborne illnesses and can originate from a wide range of food products. Given the continued presence of pathogenic Salmonella in food production systems, there is a consistent need to improve identification and detection methods that can identify this pathogen at all stages in food systems. Methods for subtyping have evolved over the years, and the introduction of whole genome sequencing and advancements in PCR technologies have greatly improved the resolution for differentiating strains within a particular serovar. This, in turn, has led to the continued improvement in Salmonella detection technologies for utilization in food production systems. In this review, the focus will be on recent advancements in these technologies, as well as potential issues associated with the application of these tools in food production. In addition, the recent and emerging research developments on Salmonella detection and identification methodologies and their potential application in food production systems will be discussed.

The Use of a Combined Bioinformatics Approach to Locate Antibiotic Resistance Genes on Plasmids From Whole Genome Sequences of Salmonella enterica Serovars From Humans in Ghana

In the current study, we identified plasmids carrying antimicrobial resistance genes in draft whole genome sequences of 16 selected Salmonella enterica isolates representing six different serovars from humans in Ghana. The plasmids and the location of resistance genes in the genomes were predicted using a combination of PlasmidFinder, ResFinder, plasmidSPAdes and BLAST genomic analysis tools. Subsequently, S1-PFGE was employed for analysis of plasmid profiles. Whole genome sequencing confirmed the presence of antimicrobial resistance genes in Salmonella isolates showing multidrug resistance phenotypically. ESBL, either blaTEM52-B or blaCTX-M15 were present in two cephalosporin resistant isolates of S. Virchow and S. Poona, respectively. The systematic genome analysis revealed the presence of different plasmids in different serovars, with or without insertion of antimicrobial resistance genes. In S. Enteritidis, resistance genes were carried predominantly on plasmids of IncN type, in S. Typhimurium on plasmids of IncFII(S)/IncFIB(S)/IncQ1 type. In S. Virchow and in S. Poona, resistance genes were detected on plasmids of IncX1 and TrfA/IncHI2/IncHI2A type, respectively. The latter two plasmids were described for the first time in these serovars. The combination of genomic analytical tools allowed nearly full mapping of the resistance plasmids in all Salmonella strains analyzed. The results suggest that the improved analytical approach used in the current study may be used to identify plasmids that are specifically associated with resistance phenotypes in whole genome sequences. Such knowledge would allow the development of rapid multidrug resistance tracking tools in Salmonella populations using WGS.

Automatic identification of optimal marker genes for phenotypic and taxonomic groups of microorganisms

Finding optimal markers for microorganisms important in the medical, agricultural, environmental or ecological fields is of great importance. Thousands of complete microbial genomes now available allow us, for the first time, to exhaustively identify marker proteins for groups of microbial organisms. In this work, we model the biological task as the well-known mathematical “hitting set” problem, solving it based on both greedy and randomized approximation algorithms. We identify unique markers for 17 phenotypic and taxonomic microbial groups, including proteins related to the nitrite reductase enzyme as markers for the non-anammox nitrifying bacteria group, and two transcription regulation proteins, nusG and yhiF, as markers for the Archaea and Escherichia/Shigella taxonomic groups, respectively. Additionally, we identify marker proteins for three subtypes of pathogenic E. coli, which previously had no known optimal markers. Practically, depending on the completeness of the database this algorithm can be used for identification of marker genes for any microbial group, these marker genes may be prime candidates for the understanding of the genetic basis of the group's phenotype or to help discover novel functions which are uniquely shared among a group of microbes. We show that our method is both theoretically and practically efficient, while establishing an upper bound on its time complexity and approximation ratio; thus, it promises to remain efficient and permit the identification of marker proteins that are specific to phenotypic or taxonomic groups, even as more and more bacterial genomes are being sequenced.

A Comparative Genomic Analysis Provides Novel Insights Into the Ecological Success of the Monophasic Salmonella Serovar 4,[5],12:i:

Over the past decades, Salmonella 4,[5],12:i:- has rapidly emerged and it is isolated with high frequency in the swine food chain. Although many studies have documented the epidemiological success of this serovar, few investigations have tried to explain this phenomenon from a genetic perspective. Here a comparative whole-genome analysis of 50 epidemiologically unrelated S. 4,[5],12:i:-, isolated in Italy from 2010 to 2016 was performed, characterizing them in terms of genetic elements potentially conferring resistance, tolerance and persistence characteristics. Phylogenetic analyses indicated interesting distinctions among the investigated isolates. The most striking genetic trait characterizing the analyzed isolates is the widespread presence of heavy metals tolerance gene cassettes: most of the strains possess genes expected to confer resistance to copper and silver, whereas about half of the isolates also contain the mercury tolerance gene merA. A functional assay showed that these genes might be useful for preventing the toxic effects of metals, thus supporting the hypothesis that they can contribute to the success of S. 4,[5],12:i:- in farming environments. In addition, the analysis of the distribution of type II toxin-antitoxin families indicated that these elements are abundant in this serovar, suggesting that this is another factor that might favor its successful spread.

Microbiological quality and antimicrobial resistance characterization of Salmonella spp. in fresh milk value chains in Ghana

Consumer perception of poor hygiene of fresh milk products is a major barrier to promotion of milk consumption as an intervention to alleviate the burden of malnutrition in Ghana. Fresh milk is retailed raw, boiled, or processed into unfermented cheese and spontaneously fermented products in unlicensed outlets. In this study, we have determined microbiological quality of informally retailed fresh milk products and characterized the genomic diversity and antimicrobial resistance (AMR) patterns of non-typhoidal Salmonella (NTS) in implicated products. A total of 159 common dairy products were purchased from five traditional milk markets in Accra. Samples were analysed for concentrations of aerobic bacteria, total and fecal coliforms, Escherichia coli, staphylococci, lactic acid bacteria and yeast and moulds. The presence of Salmonella, E. coli O157:H7, Listeria monocytogenes and Staphylococcus aureus were determined. AMR of Salmonella against 18 antibiotics was experimentally determined. Genome sequencing of 19 Salmonella isolates allowed determination of serovars, antigenic profiles, prediction of AMR genes in silico and inference of phylogenetic relatedness between strains. Raw and heat-treated milk did not differ significantly in overall bacterial quality (P = 0.851). E. coli O157:H7 and Staphylococcus aureus were present in 34.3% and 12.9% of dairy products respectively. Multidrug resistant (MDR) Salmonella enterica serovars Muenster and Legon were identified in 11.8% and 5.9% of unfermented cheese samples respectively. Pan genome analysis revealed a total of 3712 core genes. All Salmonella strains were resistant to Trimethoprim/Sulfamethoxazole, Cefoxitin, Cefuroxime Axetil and Cefuroxime. Resistance to Chloramphenicol (18%) and Ciprofloxacin (100%), which are first line antibiotics used in treatment of NTS bacteremia in Ghana, was evident. AMR was attributed to presence and/or mutations in the following genes: golS, sdiA for cephalosporins, aac(6')-Iy, ant(9) for aminoglycosides, mdtK, gyrA, gyrB, parC, parE for quinolones and cat1, cat4 for phenicols. Phylogenetic analysis based on accessory genes clustered S. Legon strains separately from the S. Muenster strains. These strains were from different markets suggesting local circulation of related strains. Our study justifies consumer resistance to consumption of unripened soft cheese without further lethal heat treatment, and provides evidence that supports the Ghana Health Service recommendation for use of 3rd generation cephalosporins for the treatment of MDR NTS infections.

A genomic overview of the population structure of Salmonella

For many decades, Salmonella enterica has been subdivided by serological properties into serovars or further subdivided for epidemiological tracing by a variety of diagnostic tests with higher resolution. Recently, it has been proposed that so-called eBurst groups (eBGs) based on the alleles of seven housekeeping genes (legacy multilocus sequence typing [MLST]) corresponded to natural populations and could replace serotyping. However, this approach lacks the resolution needed for epidemiological tracing and the existence of natural populations had not been independently validated by independent criteria. Here, we describe EnteroBase, a web-based platform that assembles draft genomes from Illumina short reads in the public domain or that are uploaded by users. EnteroBase implements legacy MLST as well as ribosomal gene MLST (rMLST), core genome MLST (cgMLST), and whole genome MLST (wgMLST) and currently contains over 100,000 assembled genomes from Salmonella. It also provides graphical tools for visual interrogation of these genotypes and those based on core single nucleotide polymorphisms (SNPs). eBGs based on legacy MLST are largely consistent with eBGs based on rMLST, thus demonstrating that these correspond to natural populations. rMLST also facilitated the selection of representative genotypes for SNP analyses of the entire breadth of diversity within Salmonella. In contrast, cgMLST provides the resolution needed for epidemiological investigations. These observations show that genomic genotyping, with the assistance of EnteroBase, can be applied at all levels of diversity within the Salmonella genus.

Ceftriaxone-resistant Salmonella Typhi carries an IncI1-ST31 plasmid encoding CTX-M-15

PURPOSE

Ceftriaxone is the drug of choice for typhoid fever and the emergence of resistant Salmonella Typhi raises major concerns for treatment. There are an increasing number of sporadic reports of ceftriaxone-resistant S. Typhi and limiting the risk of treatment failure in the patient and outbreaks in the community must be prioritized. This study describes the use of whole genome sequencing to guide outbreak identification and case management.

METHODOLOGY

An isolate of ceftriaxone-resistant S. Typhi from the blood of a child taken in 2000 at the Popular Diagnostic Center, Dhaka, Bangladesh was subjected to whole genome sequencing, using an Illumina NextSeq 500 and analysis using Geneious software.Results/Key findings. Comparison with other ceftriaxone-resistant S. Typhi revealed an isolate from the Democratic Republic of the Congo in 2015 as the closest relative but no evidence of an outbreak. A plasmid belonging to incompatibility group I1 (IncI1-ST31) which included blaCTX-M-15 (ceftriaxone resistance) associated with ISEcp-1 was identified. High similarity (90 %) was seen with pS115, an IncI1 plasmid from S. Enteritidis, and with pESBL-EA11, an incI1 plasmid from E. coli (99 %) showing that S. Typhi has access to ceftriaxone resistance through the acquisition of common plasmids.

CONCLUSIONS

The transmission of ceftriaxone resistance from E. coli to S. Typhi is of concern because of clinical resistance to ceftriaxone, the main stay of typhoid treatment. Whole genome sequencing, albeit several years after the isolation, demonstrated the success of containment but clinical trials with alternative agents are urgently required.

Salmonella in Foods: A Reemerging Problem

The number of human salmonellosis within the European Union tended to increase since 2013. One of the reasons might be Salmonella Enteritidis rising in laying hens flocks by around 17% in 2015 vs 2014 and by 57% in 2016 vs 2015. The most important sources of food-borne Salmonella outbreaks are still eggs and egg products as well as ready-to-eat foods having a long shelf life. Specific actions are suggested to restart decreasing the number of human salmonellosis: (1) revision of sampling schemes to solve pathogen under detection in both animals and foods; (2) integration of microbiological criteria with fit for purpose performance objectives and food safety objectives; and (3) improvement of epidemiological investigations of human, food, and animal isolates by using whole-genome sequencing in order to effectively track salmonellosis and verify which prevention measures are most effective.

LOCUST: a custom sequence locus typer for classifying microbial isolates

Summary

LOCUST is a custom sequence locus typer tool for classifying microbial genomes. It provides a fully automated opportunity to customize the classification of genome-wide nucleotide variant data most relevant to biological research.

Availability and Implementation

Source code, demo data, and detailed documentation are freely available at http://sourceforge.net/projects/locustyper .

Contact

lbrinkac@jcvi.org.

Supplementary information

Supplementary data are available at Bioinformatics online.

Complete Genome Sequence of a Ciprofloxacin-Resistant Salmonella enterica subsp. enterica Serovar Kentucky Sequence Type 198 Strain, PU131, Isolated from a Human Patient in Washington State

Strains of the ciprofloxacin-resistant (Cip^r) Salmonella enterica subsp. enterica serovar Kentucky sequence type 198 (ST198) have rapidly and extensively disseminated globally to become a major food safety and public health concern. Here, we report the complete genome sequence of a Cip^rS. Kentucky ST198 strain, PU131, isolated from a human patient in Washington State (USA).

Comparative analysis of core genome MLST and SNP typing within a European Salmonella serovar Enteritidis outbreak

Multi-country outbreaks of foodborne bacterial disease present challenges in their detection, tracking, and notification. As food is increasingly distributed across borders, such outbreaks are becoming more common. This increases the need for high-resolution, accessible, and replicable isolate typing schemes. Here we evaluate a core genome multilocus typing (cgMLST) scheme for the high-resolution reproducible typing of Salmonella enterica (S. enterica) isolates, by its application to a large European outbreak of S. enterica serovar Enteritidis. This outbreak had been extensively characterised using single nucleotide polymorphism (SNP)-based approaches. The cgMLST analysis was congruent with the original SNP-based analysis, the epidemiological data, and whole genome MLST (wgMLST) analysis. Combination of the cgMLST and epidemiological data confirmed that the genetic diversity among the isolates predated the outbreak, and was likely present at the infection source. There was consequently no link between country of isolation and genetic diversity, but the cgMLST clusters were congruent with date of isolation. Furthermore, comparison with publicly available Enteritidis isolate data demonstrated that the cgMLST scheme presented is highly scalable, enabling outbreaks to be contextualised within the Salmonella genus. The cgMLST scheme is therefore shown to be a standardised and scalable typing method, which allows Salmonella outbreaks to be analysed and compared across laboratories and jurisdictions.

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cgMLST is proposed as a universal typing scheme for Salmonella.

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cgMLST is congruent with SNP analyses and easier to implement across laboratories.

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Genomic data are consistent with the epidemiology of the outbreak.

Comparison of SNP-based subtyping workflows for bacterial isolates using WGS data, applied to Salmonella enterica serotype Typhimurium and serotype 1,4,[5],12:i:

Whole genome sequencing represents a promising new technology for subtyping of bacterial pathogens. Besides the technological advances which have pushed the approach forward, the last years have been marked by considerable evolution of the whole genome sequencing data analysis methods. Prior to application of the technology as a routine epidemiological typing tool, however, reliable and efficient data analysis strategies need to be identified among the wide variety of the emerged methodologies. In this work, we have compared three existing SNP-based subtyping workflows using a benchmark dataset of 32 Salmonella enterica subsp. enterica serovar Typhimurium and serovar 1,4,[5],12:i:- isolates including five isolates from a confirmed outbreak and three isolates obtained from the same patient at different time points. The analysis was carried out using the original (high-coverage) and a down-sampled (low-coverage) datasets and two different reference genomes. All three tested workflows, namely CSI Phylogeny-based workflow, CFSAN-based workflow and PHEnix-based workflow, were able to correctly group the confirmed outbreak isolates and isolates from the same patient with all combinations of reference genomes and datasets. However, the workflows differed strongly with respect to the SNP distances between isolates and sensitivity towards sequencing coverage, which could be linked to the specific data analysis strategies used therein. To demonstrate the effect of particular data analysis steps, several modifications of the existing workflows were also tested. This allowed us to propose data analysis schemes most suitable for routine SNP-based subtyping applied to S. Typhimurium and S. 1,4,[5],12:i:-. Results presented in this study illustrate the importance of using correct data analysis strategies and to define benchmark and fine-tune parameters applied within routine data analysis pipelines to obtain optimal results.

Comprehensive assessment of the quality of Salmonella whole genome sequence data available in public sequence databases using the Salmonella in silico Typing Resource (SISTR)

Public health and food safety institutions around the world are adopting whole genome sequencing (WGS) to replace conventional methods for characterizing Salmonella for use in surveillance and outbreak response. Falling costs and increased throughput of WGS have resulted in an explosion of data, but questions remain as to the reliability and robustness of the data. Due to the critical importance of serovar information to public health, it is essential to have reliable serovar assignments available for all of the Salmonella records. The current study used a systematic assessment and curation of all Salmonella in the sequence read archive (SRA) to assess the state of the data and their utility. A total of 67 758 genomes were assembled de novo and quality-assessed for their assembly metrics as well as species and serovar assignments. A total of 42 400 genomes passed all of the quality criteria but 30.16 % of genomes were deposited without serotype information. These data were used to compare the concordance of reported and predicted serovars for two in silico prediction tools, multi-locus sequence typing (MLST) and the Salmonella in silico Typing Resource (SISTR), which produced predictions that were fully concordant with 87.51 and 91.91 % of the tested isolates, respectively. Concordance of in silico predictions increased when serovar variants were grouped together, 89.25 % for MLST and 94.98 % for SISTR. This study represents the first large-scale validation of serovar information in public genomes and provides a large validated set of genomes, which can be used to benchmark new bioinformatics tools.

Completed Genome Sequences of Strains from 36 Serotypes of Salmonella

We report here the completed closed genome sequences of strains representing 36 serotypes of Salmonella. These genome sequences will provide useful references for understanding the genetic variation between serotypes, particularly as references for mapping of raw reads or to create assemblies of higher quality, as well as to aid in studies of comparative genomics of Salmonella.

MentaLiST - A fast MLST caller for large MLST schemes

MLST (multi-locus sequence typing) is a classic technique for genotyping bacteria, widely applied for pathogen outbreak surveillance. Traditionally, MLST is based on identifying sequence types from a small number of housekeeping genes. With the increasing availability of whole-genome sequencing data, MLST methods have evolved towards larger typing schemes, based on a few hundred genes [core genome MLST (cgMLST)] to a few thousand genes [whole genome MLST (wgMLST)]. Such large-scale MLST schemes have been shown to provide a finer resolution and are increasingly used in various contexts such as hospital outbreaks or foodborne pathogen outbreaks. This methodological shift raises new computational challenges, especially given the large size of the schemes involved. Very few available MLST callers are currently capable of dealing with large MLST schemes. We introduce MentaLiST, a new MLST caller, based on a k-mer voting algorithm and written in the Julia language, specifically designed and implemented to handle large typing schemes. We test it on real and simulated data to show that MentaLiST is faster than any other available MLST caller while providing the same or better accuracy, and is capable of dealing with MLST schemes with up to thousands of genes while requiring limited computational resources. MentaLiST source code and easy installation instructions using a Conda package are available at https://github.com/WGS-TB/MentaLiST.

Bacterial genome sequencing in clinical microbiology: a pathogen-oriented review

In recent years, whole-genome sequencing (WGS) has been perceived as a technology with the potential to revolutionise clinical microbiology. Herein, we reviewed the literature on the use of WGS for the most commonly encountered pathogens in clinical microbiology laboratories: Escherichia coli and other Enterobacteriaceae, Staphylococcus aureus and coagulase-negative staphylococci, streptococci and enterococci, mycobacteria and Chlamydia trachomatis. For each pathogen group, we focused on five different aspects: the genome characteristics, the most common genomic approaches and the clinical uses of WGS for (i) typing and outbreak analysis, (ii) virulence investigation and (iii) in silico antimicrobial susceptibility testing. Of all the clinical usages, the most frequent and straightforward usage was to type bacteria and to trace outbreaks back. A next step toward standardisation was made thanks to the development of several new genome-wide multi-locus sequence typing systems based on WGS data. Although virulence characterisation could help in various particular clinical settings, it was done mainly to describe outbreak strains. An increasing number of studies compared genotypic to phenotypic antibiotic susceptibility testing, with mostly promising results. However, routine implementation will preferentially be done in the workflow of particular pathogens, such as mycobacteria, rather than as a broadly applicable generic tool. Overall, concrete uses of WGS in routine clinical microbiology or infection control laboratories were done, but the next big challenges will be the standardisation and validation of the procedures and bioinformatics pipelines in order to reach clinical standards.

Rapid detection and serovar identification of common Salmonella enterica serovars in Canada using a new pyrosequencing assay

Serotyping of Salmonella enterica subsp. enterica is a critical step for foodborne salmonellosis investigation. To identify Salmonella enterica subsp. enterica serovars, we have developed a new assay based on a triplex polymerase chain reaction (PCR) with pyrosequencing for amplicon confirmation and phylogenetic discrimination of strains. The top 54 most prevalent serovars of S. enterica in Canada were examined with a total of 23 single-nucleotide polymorphisms (SNPs) and (or) single-nucleotide variations (SNVs) located on 3 genes (fliD, sopE2, and spaO). Seven of the most common serovars, Newport, Typhi, Javiana, Infantis, Thompson, Heidelberg, and Enteritidis, were successfully distinguished from the other serovars based on their unique SNP-SNV combinations. The remaining serovars, including Typhimurium, ssp I:4,[5],12:i:-, and Saintpaul, were further divided into 47 subgroups that demonstrate the relatedness to phylogenetic classifications of each serovar. This pyrosequencing assay is not only cost-effective, rapid, and user-friendly, but also provides phylogenetic information by analyzing 23 selected SNPs. With the added layer of confidence in the PCR results and the accuracy and speed of pyrosequencing, this novel method would benefit the food industry and provides a tool for rapid outbreak investigation through quick detection and identification of common S. enterica serovars in Canada.

Will the emergence of core genome MLST end the role of in silico MLST?

The technological advancement of molecular epidemiological analysis using next-generation sequencing (NGS) for foodborne pathogens has a groundbreaking impact over the past three years. In particular, the emergence of cg (core genome) multilocus sequence typing(MLST) has a significant impact. This is because this technology made it possible for many researchers to carry out molecular epidemiological analysis on foodborne pathogens in a common language, using common definitions. The resolution of core genome MLST (cgMLST) far surpasses that of MLST, which only uses seven (usually, in some cases five) housekeeping genes. Therefore, cgMLST would in no doubt terminate the role of conventional MLST as the molecular epidemiological tool. However, the role of MLST would probably not end all together. Rather, the sequence type (ST) of the conventional MLST is expected to be used as in silico MLST by a wider range of researchers than ever in the next 10 years. This is because, with the arrival of the NGS era, we have come to be able to obtain ST of conventional MLST by simply entering the NGS text file into one's own PC. In other words, acquisition of ST data is no longer limited to researchers aiming to conduct MLST for the first place. The impact of such a change is large. In silico MLST will continue to be used as a tool for understanding the broad characteristics of bacterial strains. This review aimed to summarize the main information on STs that have been accumulated for representative foodborne pathogens, in particular for potential NGS users in this new era who have been not familiar with MLST until now.

Pan-genome Analyses of the Species Salmonella enterica, and Identification of Genomic Markers Predictive for Species, Subspecies, and Serovar

Food safety is a global concern, with upward of 2.2 million deaths due to enteric disease every year. Current whole-genome sequencing platforms allow routine sequencing of enteric pathogens for surveillance, and during outbreaks; however, a remaining challenge is the identification of genomic markers that are predictive of strain groups that pose the most significant health threats to humans, or that can persist in specific environments. We have previously developed the software program Panseq, which identifies the pan-genome among a group of sequences, and the SuperPhy platform, which utilizes this pan-genome information to identify biomarkers that are predictive of groups of bacterial strains. In this study, we examined the pan-genome of 4893 genomes of Salmonella enterica, an enteric pathogen responsible for the loss of more disability adjusted life years than any other enteric pathogen. We identified a pan-genome of 25.3 Mbp, a strict core of 1.5 Mbp present in all genomes, and a conserved core of 3.2 Mbp found in at least 96% of these genomes. We also identified 404 genomic regions of 1000 bp that were specific to the species S. enterica. These species-specific regions were found to encode mostly hypothetical proteins, effectors, and other proteins related to virulence. For each of the six S. enterica subspecies, markers unique to each were identified. No serovar had pan-genome regions that were present in all of its genomes and absent in all other serovars; however, each serovar did have genomic regions that were universally present among all constituent members, and statistically predictive of the serovar. The phylogeny based on SNPs within the conserved core genome was found to be highly concordant to that produced by a phylogeny using the presence/absence of 1000 bp regions of the entire pan-genome. Future studies could use these predictive regions as components of a vaccine to prevent salmonellosis, as well as in simple and rapid diagnostic tests for both in silico and wet-lab applications, with uses ranging from food safety to public health. Lastly, the tools and methods described in this study could be applied as a pan-genomics framework to other population genomic studies seeking to identify markers for other bacterial species and their sub-groups.

Genome Target Evaluator (GTEvaluator): A workflow exploiting genome dataset to measure the sensitivity and specificity of genetic markers

Most of the bacterial typing methods used to discriminate isolates in medical or food safety microbiology are based on genetic markers used as targets in PCR or hybridization experiments. These DNA typing methods are important tools for studying prevalence and epidemiology, for conducting surveillance, investigations and control of biological hazard sources. In that perspective, it is crucial to insure that the chosen genetic markers have the greatest specificity and sensitivity. The wealth of whole-genome sequences available for many bacterial species offers the opportunity to evaluate the performance of these genetic markers. In the present study, we have developed GTEvaluator, a bioinformatics workflow which ranks genetic markers depending on their sensitivity and specificity towards groups of well-defined genomes. GTEvaluator identifies the most performant genetic markers to target individuals among a population. The individuals (i.e. a group of genomes within a collection) are defined by any kind of particular phenotypic or biological properties inside a related population (i.e. collection of genomes). The performance of the genetic markers is computed by a distance value which takes into account both sensitivity and specificity. In this study we report two examples of GTEvaluator application. In the first example Bacillus phenotypic markers were evaluated for their capacity to distinguish B. cereus from B. thuringiensis. In the second experiment, GTEvaluator measured the performance of genetic markers dedicated to the molecular serotyping of Salmonella enterica. In one in silico experiment it was possible to test 64 markers onto 134 genomes corresponding to 14 different serotypes.

The Validation and Implications of Using Whole Genome Sequencing as a Replacement for Traditional Serotyping for a National Salmonella Reference Laboratory

Salmonella serotyping remains the gold-standard tool for the classification of Salmonella isolates and forms the basis of Canada’s national surveillance program for this priority foodborne pathogen. Public health officials have been increasingly looking toward whole genome sequencing (WGS) to provide a large set of data from which all the relevant information about an isolate can be mined. However, rigorous validation and careful consideration of potential implications in the replacement of traditional surveillance methodologies with WGS data analysis tools is needed. Two in silico tools for Salmonella serotyping have been developed, the Salmonella in silico Typing Resource (SISTR) and SeqSero, while seven gene MLST for serovar prediction can be adapted for in silico analysis. All three analysis methods were assessed and compared to traditional serotyping techniques using a set of 813 verified clinical and laboratory isolates, including 492 Canadian clinical isolates and 321 isolates of human and non-human sources. Successful results were obtained for 94.8, 88.2, and 88.3% of the isolates tested using SISTR, SeqSero, and MLST, respectively, indicating all would be suitable for maintaining historical records, surveillance systems, and communication structures currently in place and the choice of the platform used will ultimately depend on the users need. Results also pointed to the need to reframe serotyping in the genomic era as a test to understand the genes that are carried by an isolate, one which is not necessarily congruent with what is antigenically expressed. The adoption of WGS for serotyping will provide the simultaneous collection of information that can be used by multiple programs within the current surveillance paradigm; however, this does not negate the importance of the various programs or the role of serotyping going forward.

A Syst-OMICS Approach to Ensuring Food Safety and Reducing the Economic Burden of Salmonellosis

The Salmonella Syst-OMICS consortium is sequencing 4,500 Salmonella genomes and building an analysis pipeline for the study of Salmonella genome evolution, antibiotic resistance and virulence genes. Metadata, including phenotypic as well as genomic data, for isolates of the collection are provided through the Salmonella Foodborne Syst-OMICS database (SalFoS), at https://salfos.ibis.ulaval.ca/. Here, we present our strategy and the analysis of the first 3,377 genomes. Our data will be used to draw potential links between strains found in fresh produce, humans, animals and the environment. The ultimate goals are to understand how Salmonella evolves over time, improve the accuracy of diagnostic methods, develop control methods in the field, and identify prognostic markers for evidence-based decisions in epidemiology and surveillance.

Food Safety in the Age of Next Generation Sequencing, Bioinformatics, and Open Data Access

Public health labs and food regulatory agencies globally are embracing whole genome sequencing (WGS) as a revolutionary new method that is positioned to replace numerous existing diagnostic and microbial typing technologies with a single new target: the microbial draft genome. The ability to cheaply generate large amounts of microbial genome sequence data, combined with emerging policies of food regulatory and public health institutions making their microbial sequences increasingly available and public, has served to open up the field to the general scientific community. This open data access policy shift has resulted in a proliferation of data being deposited into sequence repositories and of novel bioinformatics software designed to analyze these vast datasets. There also has been a more recent drive for improved data sharing to achieve more effective global surveillance, public health and food safety. Such developments have heightened the need for enhanced analytical systems in order to process and interpret this new type of data in a timely fashion. In this review we outline the emergence of genomics, bioinformatics and open data in the context of food safety. We also survey major efforts to translate genomics and bioinformatics technologies out of the research lab and into routine use in modern food safety labs. We conclude by discussing the challenges and opportunities that remain, including those expected to play a major role in the future of food safety science.

The Importance of Bacterial Culture to Food Microbiology in the Age of Genomics

Culture-based and genomics methods provide different insights into the nature and behavior of bacteria. Maximizing the usefulness of both approaches requires recognizing their limitations and employing them appropriately. Genomic analysis excels at identifying bacteria and establishing the relatedness of isolates. Culture-based methods remain necessary for detection and enumeration, to determine viability, and to validate phenotype predictions made on the bias of genomic analysis. The purpose of this short paper is to discuss the application of culture-based analysis and genomics to the questions food microbiologists routinely need to ask regarding bacteria to ensure the safety of food and its economic production and distribution. To address these issues appropriate tools are required for the detection and enumeration of specific bacterial populations and the characterization of isolates for, identification, phylogenetics, and phenotype prediction.

The EpiQuant Framework for Computing Epidemiological Concordance of Microbial Subtyping Data

A fundamental assumption in the use and interpretation of microbial subtyping results for public health investigations is that isolates that appear to be related based on molecular subtyping data are expected to share commonalities with respect to their origin, history, and distribution. Critically, there is currently no approach for systematically assessing the underlying epidemiology of subtyping results. Our aim was to develop a method for directly quantifying the similarity between bacterial isolates using basic sampling metadata and to develop a framework for computing the epidemiological concordance of microbial typing results. We have developed an analytical model that summarizes the similarity of bacterial isolates using basic parameters typically provided in sampling records, using a novel framework (EpiQuant) developed in the R environment for statistical computing. We have applied the EpiQuant framework to a data set comprising 654 isolates of the enteric pathogen Campylobacter jejuni from Canadian surveillance data in order to examine the epidemiological concordance of clusters obtained by using two leading C. jejuni subtyping methods. The EpiQuant framework can be used to directly quantify the similarity of bacterial isolates based on basic sample metadata. These results can then be used to assess the concordance between microbial epidemiological and molecular data, facilitating the objective assessment of subtyping method performance and paving the way for the improved application of molecular subtyping data in investigations of infectious disease.

Single-Nucleotide Polymorphisms in the Whole-Genome Sequence Data of Shiga Toxin-Producing Escherichia coli O157:H7/H- Strains by Cultivation

Nine Shiga toxin-producing Escherichia coli O157:H7/H- (O157) strains were serially cultured three times on LB agar plates. After each sub-culture, five colonies were picked for DNA isolation and whole genome sequence (WGS) analysis. After exclusion of possible recombination-related SNPs, 11, 9, and 34 single-nucleotide polymorphisms (SNPs) were detected in genes in the backbone, O-island, and mobile elements gene categories. This suggested that those SNPs due to cultivation could influence the threshold value set for molecular epidemiological studies of O157. Significant differences were observed by the Kruskal-Wallis test (P < 0.01) when the number of the SNPs in a strain was compared to that in other strains. This indicated that a specific number of strains could be used for setting the threshold value in molecular epidemiological studies. Due to cultivation, the SNPs were also detected in genes in a few core genome or core gene sets, suggesting that those SNPs could affect studies of phylogeny as well as molecular epidemiology. To improve the accuracy of phylogenetic and molecular epidemiological studies, genes in which the SNPs have arisen due to cultivation should be excluded from WGS data.

Infection control in the new age of genomic epidemiology

With the growing importance of infectious diseases in health care and communicable disease outbreaks garnering increasing attention, new technologies are playing a greater role in helping us prevent health care-associated infections and provide optimal public health. The microbiology laboratory has always played a large role in infection control by providing tools to identify, characterize, and track pathogens. Recently, advances in DNA sequencing technology have ushered in a new era of genomic epidemiology, where traditional molecular diagnostics and genotyping methods are being enhanced and even replaced by genomics-based methods to aid epidemiologic investigations of communicable diseases. The ability to analyze and compare entire pathogen genomes has allowed for unprecedented resolution into how and why infectious diseases spread. As these genomics-based methods continue to improve in speed, cost, and accuracy, they will be increasingly used to inform and guide infection control and public health practices.

Navigating Microbiological Food Safety in the Era of Whole-Genome Sequencing

The epidemiological investigation of a foodborne outbreak, including identification of related cases, source attribution, and development of intervention strategies, relies heavily on the ability to subtype the etiological agent at a high enough resolution to differentiate related from nonrelated cases. Historically, several different molecular subtyping methods have been used for this purpose; however, emerging techniques, such as single nucleotide polymorphism (SNP)-based techniques, that use whole-genome sequencing (WGS) offer a resolution that was previously not possible. With WGS, unlike traditional subtyping methods that lack complete information, data can be used to elucidate phylogenetic relationships and disease-causing lineages can be tracked and monitored over time. The subtyping resolution and evolutionary context provided by WGS data allow investigators to connect related illnesses that would be missed by traditional techniques. The added advantage of data generated by WGS is that these data can also be used for secondary analyses, such as virulence gene detection, antibiotic resistance gene profiling, synteny comparisons, mobile genetic element identification, and geographic attribution. In addition, several software packages are now available to generate in silico results for traditional molecular subtyping methods from the whole-genome sequence, allowing for efficient comparison with historical databases. Metagenomic approaches using next-generation sequencing have also been successful in the detection of nonculturable foodborne pathogens. This review addresses state-of-the-art techniques in microbial WGS and analysis and then discusses how this technology can be used to help support food safety investigations. Retrospective outbreak investigations using WGS are presented to provide organism-specific examples of the benefits, and challenges, associated with WGS in comparison to traditional molecular subtyping techniques.

Draft Genome Sequences of Two Salmonella enterica Strains Isolated from Sprouted Chia and Flax Seed Powders

A 2014 foodborne salmonellosis outbreak in Canada and the United States implicated, for the first time, sprouted chia seed powder as the vehicle of transmission. Here, we report the draft whole genome sequences of two Salmonella enterica strains isolated from sprouted powders related to the aforementioned outbreak.

A Primer on Infectious Disease Bacterial Genomics

The number of large-scale genomics projects is increasing due to the availability of affordable high-throughput sequencing (HTS) technologies. The use of HTS for bacterial infectious disease research is attractive because one whole-genome sequencing (WGS) run can replace multiple assays for bacterial typing, molecular epidemiology investigations, and more in-depth pathogenomic studies. The computational resources and bioinformatics expertise required to accommodate and analyze the large amounts of data pose new challenges for researchers embarking on genomics projects for the first time. Here, we present a comprehensive overview of a bacterial genomics projects from beginning to end, with a particular focus on the planning and computational requirements for HTS data, and provide a general understanding of the analytical concepts to develop a workflow that will meet the objectives and goals of HTS projects.

Application of Whole-Genome Sequencing Data for O-Specific Antigen Analysis and In Silico Serotyping of Pseudomonas aeruginosa Isolates

Accurate typing methods are required for efficient infection control. The emergence of whole-genome sequencing (WGS) technologies has enabled the development of genome-based methods applicable for routine typing and surveillance of bacterial pathogens. In this study, we developed the Pseudomonas aeruginosa serotyper (PAst) program, which enabled in silico serotyping of P. aeruginosa isolates using WGS data. PAst has been made publically available as a web service and aptly facilitates high-throughput serotyping analysis. The program overcomes critical issues such as the loss of in vitro typeability often associated with P. aeruginosa isolates from chronic infections and quickly determines the serogroup of an isolate based on the sequence of the O-specific antigen (OSA) gene cluster. Here, PAst analysis of 1,649 genomes resulted in successful serogroup assignments in 99.27% of the cases. This frequency is rarely achievable by conventional serotyping methods. The limited number of nontypeable isolates found using PAst was the result of either a complete absence of OSA genes in the genomes or the artifact of genomic misassembly. With PAst, P. aeruginosa serotype data can be obtained from WGS information alone. PAst is a highly efficient alternative to conventional serotyping methods in relation to outbreak surveillance of serotype O12 and other high-risk clones, while maintaining backward compatibility to historical serotype data.

Draft Whole-Genome Sequences of 25 Salmonella enterica Strains Representing 24 Serovars

We report the draft genome sequences of 25 Salmonella enterica strains representing 24 different serotypes, many of which were not available in public repositories during our selection process. These draft genomes will provide useful reference for the genetic variation between serotypes and aid in the development of molecular typing tools.