Characterization of Foodborne Outbreaks of Salmonella enterica Serovar Enteritidis with Whole-Genome Sequencing Single Nucleotide Polymorphism-Based Analysis for Surveillance and Outbreak Detection

Pathogenic characteristics of an aggregated diarrhea event caused by Plesiomonas shigelloides from stream

This study aimed to investigate the cause of a foodborne disease outbreak in Huzhou on August 14, 2023. Multiple enteropathogens were detected using FilmArray, and the pathogen was subsequently isolated and cultured from anal swabs of the cases and stream water. The isolated strains were identified using VITEK MS, and antimicrobial susceptibility test, pulsed field gel electrophoresis (PFGE) molecular typing, and whole genome sequencing (WGS) were performed on the isolates of Plesiomonas shigelloides. Gene annotation and sequence alignment were used to analyze the virulence genes and drug resistance genes of the strains. A phylogenetic tree was constructed based on single nucleotide polymorphism (SNP), and homology analysis was conducted to trace the origin of P. shigelloides. A total of 7 strains of P.shigelloides were isolated, with 3 from stream water and 4 from anal swabs. All 7 strains exhibited the same PFGE pattern and showed resistance to amikacin, trimethoprim-sulfamethoxazole, chloramphenicol, tetracycline, cefazolin, streptomycin, and florfenicol. The isolated strains carried the same resistance genes and virulence factors. In the sequences of the isolated strains from this outbreak, 11 mutation sites were detected. The phylogenetic tree based on SNP sites showed that these strains were homologous. This foodborne disease outbreak caused by P.shigelloides was the first reported in Huzhou. WGS can be used as a complementary method to PFGE for epidemiological investigations of disease outbreaks.

Genomic-wide analysis approach revealed genomic similarity for environmental Mexican S. Oranienburg genomes

As the human population grows, an increase in food trade is needed. This elevates the risk of epidemiological outbreaks. One of the prevalent pathogens associated with food production in Mexico has been Salmonella Oranienburg. Effective surveillance systems require microbial genetic knowledge. The objective of this work is to describe the genetic composition of Mexican S. Oranienburg genomes. For that, 53 strains from different environmental sources were isolated and sequenced. Additionally, 109 S. Oranienburg genomes were downloaded. Bioinformatic analyses were used to explore the clonal complex and genomic relatedness. A major clonal group formed by ST23 was identified comprising four STs. 202 SNPs were found the maximum difference among isolates. Virulence genes for host invasion and colonization as rpoS, fimbria type 1, and, T3SS were found common for all isolates. This study suggests that Mexican S. Oranienburg strains are potential pathogens circulating continuously in the region between host and non-host environments.

Characterizing the Genetic Diversity of Salmonella Isolated from U.S. Raw Inshell Pistachios Using Whole Genome Sequencing

The genetic diversity of 169 Salmonella isolates from pistachios collected from California storage silos during the 2010, 2011, and 2012 harvests (silo survey isolates) was determined by analyzing the whole genome sequence data using the CFSAN SNP pipeline developed by the U.S. Food and Drug Administration's Center for Food Safety and Applied Nutrition. Salmonella isolates clustered by serovars Agona, Enteritidis, Montevideo, Sandiego, Senftenberg, Liverpool, Tennessee, and Worthington in the phylogenetic tree. Within each serovar, isolates grouped into one or two clusters (≤14 SNPs). Two distinct clusters (>14 SNPs; A and B) were identified for Salmonella Enteritidis, Montevideo, and Liverpool for a total of 11 unique strains. Sequences of representative silo survey isolates clustered with sequences of Salmonella strains isolated from U.S. pistachio-associated samples collected between 2008 and 2018 available on the National Center for Biotechnology Information database, and, in all but two cases, not with sequences of Salmonella strains recovered from raw California almonds from 2001 through 2013. The genomic evidence suggests that strains of Salmonella Agona, Liverpool Cluster A, Montevideo Clusters A and B, Senftenberg, and Worthington have persisted in the California pistachio environment for ≥3 years and some of these strains have been reported exclusively in association with pistachios.

Challenges Associated with Investigating Salmonella Enteritidis with Low Genomic Diversity in New York State: The Impact of Adjusting Analytical Methods and Correlation with Epidemiological Data

Defining investigation-worthy genomic clusters among strains of Salmonella Enteritidis is challenging because of their highly clonal nature. We investigated a cluster identified by core genome multilocus sequence typing (cgMLST) consisting of 265 isolates with isolation dates spanning two and a half years. This cluster experienced chaining, growing to a range of 14 alleles. The volume of isolates and broad allele range of this cluster made it difficult to ascertain whether it represented a common-source outbreak. We explored laboratory-based methods to subdivide and refine this cluster. These methods included using cgMLST with a narrower allele range, whole genome multilocus sequence typing (wgMLST) and high-quality single-nucleotide polymorphism (hqSNP) analysis. At each analysis level, epidemiologists retroactively reviewed exposures, geography, and temporality for potential commonalities. Lowering the threshold to 0 alleles using cgMLST proved an effective method to refine this analysis, resulting in this large cluster being subdivided into 34 smaller clusters. Additional analysis by wgMLST and hqSNP provided enhanced cluster resolution, with the majority of clusters being further refined. These analysis methods combined with more stringent allele thresholds and layering of epidemiologic data proved useful in helping to subdivide this large cluster into actionable subclusters.

Genomic Surveillance of Salmonella from the Comunitat Valenciana (Spain)

Salmonella enterica subspecies enterica is one of the most important foodborne pathogens and the causative agent of salmonellosis, which affects both humans and animals producing numerous infections every year. The study and understanding of its epidemiology are key to monitoring and controlling these bacteria. With the development of whole-genome sequencing (WGS) technologies, surveillance based on traditional serotyping and phenotypic tests of resistance is being replaced by genomic surveillance. To introduce WGS as a routine methodology for the surveillance of food-borne Salmonella in the region, we applied this technology to analyze a set of 141 S. enterica isolates obtained from various food sources between 2010 and 2017 in the Comunitat Valenciana (Spain). For this, we performed an evaluation of the most relevant Salmonella typing methods, serotyping and sequence typing, using both traditional and in silico approaches. We extended the use of WGS to detect antimicrobial resistance determinants and predicted minimum inhibitory concentrations (MICs). Finally, to understand possible contaminant sources in this region and their relationship to antimicrobial resistance (AMR), we performed cluster detection combining single-nucleotide polymorphism (SNP) pairwise distances and phylogenetic and epidemiological data. The results of in silico serotyping with WGS data were highly congruent with those of serological analyses (98.5% concordance). Multi-locus sequence typing (MLST) profiles obtained with WGS information were also highly congruent with the sequence type (ST) assignment based on Sanger sequencing (91.9% coincidence). In silico identification of antimicrobial resistance determinants and minimum inhibitory concentrations revealed a high number of resistance genes and possible resistant isolates. A combined phylogenetic and epidemiological analysis with complete genome sequences revealed relationships among isolates indicative of possible common sources for isolates with separate sampling in time and space that had not been detected from epidemiological information. As a result, we demonstrate the usefulness of WGS and in silico methods to obtain an improved characterization of S. enterica enterica isolates, allowing better surveillance of the pathogen in food products and in potential environmental and clinical samples of related interest.

Prevalence and whole genome phylogenetic analysis reveal genetic relatedness between antibiotic resistance Salmonella in hatchlings and older chickens from farms in Nigeria

The presence of Salmonella in hatchlings is the single most important risk factor for the introduction of Salmonella into poultry farms, and resistant strains are particularly worrisome, as they could affect treatment outcomes in humans infected through consumption of contaminated poultry products. This study estimated Salmonella prevalence, determined resistance profiles of strains recovered from hatchlings in Nigeria, and determined genetic relatedness between hatchling strains and strains from poultry farms. In this study, 300 fecal samples were collected. Salmonella was isolated by culture and confirmed by PCR, and isolates were tested for susceptibility to antimicrobials by the disk diffusion method. Strains were pair-end sequenced, and genomes were used to obtain serotypes and antibiotic resistance genes. Whole-genome based phylogenetic analysis was used to determine genetic relatedness between these isolates and strains from previously characterized older chicken within the same geographical area. A prevalence of 10.7% was obtained belonging to 13 Salmonella serovars. Resistance to kanamycin (30/32), ciprofloxacin (22/32), nalidixic acid (22/32), and sulfonamides (22/32) were the most commonly observed phenotypic resistances. Twenty-two (68.8%) isolates showed multidrug resistance. In silico predictions identified 36 antimicrobial resistance genes. Four (12.5%) and 22 (68.8%) strains showed point mutations in gyrA and parC. Commonly observed acquired resistance genes included sul1, sul2, sul3, and tet(A) as well as a variety of aminoglycoside-modifying genes. Eleven (34.4%) isolates were predicted to have genes that confer resistance to fosfomycin (fosA7, fosB). A strain of S. Stanleyville was predicted to have optrA, which confers resistance to furazolidone. Strains of S. Kentucky, S. Muenster, and S. Menston obtained from hatchlings showed close genetic relatedness by having less than 30 SNPs difference to strains recovered from chickens at farms previously receiving hatchlings from the same sources.

Pan-Genome Analysis of Staphylococcus aureus Reveals Key Factors Influencing Genomic Plasticity

The massive quantities of bacterial genomic data being generated have facilitated in-depth analyses of bacteria for pan-genomic studies. However, the pan-genome compositions of one species differed significantly between different studies, so we used Staphylococcus aureus as a model organism to explore the influences driving bacterial pan-genome composition. We selected a series of diverse strains for pan-genomic analysis to explore the pan-genomic composition of S. aureus at the species level and the actual contribution of influencing factors (sequence type [ST], source of isolation, country of isolation, and date of collection) to pan-genome composition. We found that the distribution of core genes in bacterial populations restrained under different conditions differed significantly and showed "local core gene regions" in the same ST. Therefore, we propose that ST may be a key factor driving the dynamic distribution of bacterial genomes and that phylogenetic analyses using whole-genome alignment are no longer appropriate in populations containing multiple ST strains. Pan-genomic analysis showed that some of the housekeeping genes of multilocus sequence typing (MLST) are carried at less than 60% in S. aureus strains. Consequently, we propose a new set of marker genes for the classification of S. aureus, which provides a reference for finding a new set of housekeeping genes to apply to MLST. In this study, we explored the role of driving factors influencing pan-genome composition, providing new insights into the study of bacterial pan-genomes. IMPORTANCE We sought to explore the impact of driving factors influencing pan-genome composition using Staphylococcus aureus as a model organism to provide new insights for the study of bacterial pan-genomes. We believe that the sequence type (ST) of the strains under consideration plays a significant role in the dynamic distribution of bacterial genes. Our findings indicate that there are a certain number of essential genes in Staphylococcus aureus; however, the number of core genes is not as high as previously thought. The new classification method proposed herein suggests that a new set of housekeeping genes more suitable for Staphylococcus aureus must be identified to improve the current classification status of this species.

Population dynamics and antimicrobial resistance of Salmonella Derby ST40 from Shenzhen, China

Salmonella enterica subsp. enterica serovar Derby (S. Derby) is one of the most common serotypes responsible for salmonellosis in humans and animals. The two main sequence types (ST) observed in China are ST40 and ST71, with ST40 presently being the most common in Shenzhen. Recent years have seen an increasing number of cases of salmonella caused by ST40 S. Derby, but the epidemiology is not clear. We gathered 314 ST40 S. Derby isolates from food and patient samples for 11 years in Shenzhen; 76 globally prevalent representative strains were also collected. Whole-genome sequencing (WGS) combined with drug resistance phenotyping was used to examine population structural changes, inter-host associations, drug resistance characteristics, and the food-transmission risks of ST40 S. Derby in Shenzhen over this period. The S. enterica evolutionary tree is divided into five clades, and the strains isolated in Shenzhen were primarily concentrated in Clades 2, 4, and 5, and thus more closely related to strains from Asian (Thailand and Vietnam) than European countries. Our 11-year surveillance of S. Derby in Shenzhen showed that Clades 2, 4, and 5 are now the dominant epidemic branches, and branches 2 and 5 are heavily multi-drug resistant. The main resistance pattern is ampicillin-tetracycline-ciprofloxacin-chloramphenicol-nalidixic acid-streptomycin-sulfamethoxazole/trimethoprim. This may lead to a trend of increasing resistance to ST40 S. Derby in Shenzhen. Using a segmentation of ≤3 SNP among clone clusters, we discovered that Clades 2 and 4 contained multiple clonal clusters of both human- and food-derived strains. The food-derived strains were mainly isolated from pig liver, suggesting this food has a high risk of causing disease outbreaks in Shenzhen.

Genome-Wide Searching Single Nucleotide-Polymorphisms (SNPs) and SNPs-Targeting a Multiplex Primer for Identification of Common Salmonella Serotypes

A rapid and high-quality single-nucleotide polymorphisms (SNPs)-based method was developed to improve detection and reduce salmonellosis burden. In this study, whole-genome sequence (WGS) was used to investigate SNPs, the most common genetic marker for identifying bacteria. SNP-sites encompassing 15 sets of primers (666–863 bp) were selected and used to amplify the target Salmonella serovar strains, and the amplified products were sequenced. The prevalent Salmonella enterica subspecies enterica serovars, including Typhimurium; Enteritidis, Agona, enterica, Typhi, and Abony, were amplified and sequenced. The amplified sequences of six Salmonella serovars with 15 sets of SNP-sites encompassing primers were aligned, explored SNPs, and SNPs-carrying primers (23 sets) were designed to develop a multiplex PCR marker (m-PCR). Each primer exists in at least two SNPs bases at the 3′ end of each primer, such as one was wild, and another was a mismatched base by transition or transversion mutation. Thus, twenty-three sets of SNP primers (242–670 bp), including 13 genes (SBG, dedA, yacG, mrcB, mesJ, metN, rihA/B, modA, hutG, yehX, ybiY, moeB, and sopA), were developed for PCR confirmation of target Salmonella serovar strains. Finally, the SNPs in four genes, including fliA gene (S. Enteritidis), modA (S. Agona and S. enterica), sopA (S. Abony), and mrcB (S. Typhimurium and S. Typhi), were used for detection markers of six target Salmonella serotypes. We developed an m-PCR primer set in which Salmonella serovars were detected in a single reaction. Nevertheless, m-PCR was validated with 21 Salmonella isolates (at least one isolate was taken from one positive animal fecal, and n = 6 reference Salmonella strains) and non-Salmonella bacteria isolates. The SNP-based m-PCR method would identify prevalent Salmonella serotypes, minimize the infection, and control outbreaks.

Rapid phylogenetic analysis using open reading frame content patterns acquired by Oxford Nanopore sequencing

AIMS

Phylogenetic analysis based on core genome single nucleotide polymorphisms (cgSNPs) using whole-genome sequencing (WGS) is increasingly used in epidemiological investigations of bacteria. The approach, however, is both resource intensive and time-consuming. Oxford Nanopore Technologies (ONT) sequencing is capable of real-time data analysis but the high error rate hampers its application in cgSNP-based phylogenetic analysis. Here, we developed a cgSNP-independent phylogenetic analysis method using ONT read assemblies by focusing on open reading frame (ORF) content patterns.

METHODS AND RESULTS

WGS data of 66 Enterobacter hormaechei strains acquired by both ONT and Illumina sequencing and 162 strains obtained from NCBI database were converted to binary sequences based on the presence or absence of ORFs using BLASTn. Phylogenetic trees calculated from binary sequences (ORF trees) were compared with cgSNP trees derived from Illumina sequences. Clusters of closely related strains in the cgSNP trees formed comparable clusters in the ORF trees built with binary sequences, and the tree topologies between them were similar based on Fowlkes-Mallows index.

CONCLUSIONS

The ORF-based phylogenetic analysis using ONT sequencing may be useful in epidemiological investigations and offer advantages over the cgSNP-based approach.

SIGNIFICANCE AND IMPACT OF THE STUDY

Conversion of assembled WGS data to binary sequences based on the presence or absence of ORFs circumvents read error concerns with ONT sequencing. Since ONT sequencing generates data in real-time and does not require major investment, this ORF-based phylogenetic analysis method has the potential to enable phylogenetic and epidemiological analysis at the point of care.

The application of next generation sequencing technology in medical diagnostics: a perspective

Rapid isolation, characterization, and identification are prerequisites of any successful medical intervention to infectious disease treatment. This is a real challenge to the scientific as well as a medical community to find out a proper and robust method of pathogen detection. Classical cultural, as well as biochemical test-based identification, has its own limitations to their time-consuming and ineffectiveness for closely related pathovars. Molecular diagnostics became a popular alternative to classical techniques for the past couple of decades but it required some prior information to detect the pathogen successfully. Recently, with the advent of next-generation sequencing (NGS) technology identification, and characterization of almost all the pathogenic bacteria become possible without any information a priori. Metagenomic next generation sequencing is another specialized type of NGS that is profoundly utilized in medical biotechnology and diagnostics now a days. Therefore, the present review is focused on a brief introduction to NGS technology, its application in medical microbiology, and possible future aspects for the development of medical sciences.

Whole Genome Multi-Locus Sequence Typing and Genomic Single Nucleotide Polymorphism Analysis for Epidemiological Typing of Pseudomonas aeruginosa From Indonesian Intensive Care Units

We have previously studied carbapenem non-susceptible Pseudomonas aeruginosa (CNPA) strains from intensive care units (ICUs) in a referral hospital in Jakarta, Indonesia (Pelegrin et al., 2019). We documented that CNPA transmissions and acquisitions among patients were variable over time and that these were not significantly reduced by a set of infection control measures. Three high risk international CNPA clones (sequence type (ST)235, ST823, ST357) dominated, and carbapenem resistance was due to carbapenemase-encoding genes and mutations in the porin OprD. Pelegrin et al. (2019) reported core genome analysis of these strains. We present a more refined and detailed whole genome-based analysis of major clones represented in the same dataset. As per our knowledge, this is the first study reporting Single Nucleotide Polymorphisms (wgSNP) analysis of Pseudomonas strains. With whole genome-based Multi Locus Sequence Typing (wgMLST) of the 3 CNPA clones (ST235, ST357 and ST823), three to eleven subgroups with up to 200 allelic variants were observed for each of the CNPA clones. Furthermore, we analyzed these CNPA clone clusters for the presence of wgSNP to redefine CNPA transmission events during hospitalization. A maximum number 35350 SNPs (including non-informative wgSNPs) and 398 SNPs (ST-specific_informative-wgSNPs) were found in ST235, 34,570 SNPs (including non-informative wgSNPs) and 111 SNPs (ST-specific_informative-wgSNPs) in ST357 and 26,443 SNPs (including non-informative SNPs) and 61 SNPs (ST-specific_informative-wgSNPs) in ST823. ST-specific_Informative-wgSNPs were commonly noticed in sensor-response regulator genes. However, the majority of non-informative wgSNPs was found in conserved hypothetical proteins or in uncharacterized proteins. Of note, antibiotic resistance and virulence genes segregated according to the wgSNP analyses. A total of 8 transmission chains for ST235 strains followed by 9 and 4 possible transmission chains for ST357 and ST823 were traceable on the basis of pairwise distances of informative-wgSNPs (0 to 4 SNPs) among the strains. The present study demonstrates the value of detailed whole genome sequence analysis for highly refined epidemiological analysis of P. aeruginosa.

Rapid Multilateral and Integrated Public Health Response to a Cross-City Outbreak of Salmonella Enteritidis Infections Combining Analytical, Molecular, and Genomic Epidemiological Analysis

On September 21, 2019, the Shenzhen and Dongguan Centers for Disease Control and Prevention received notification of a large cluster of suspected gastroenteritis involving primarily children who sought medical care at hospitals throughout two adjacent cities in China, Shenzhen, and Dongguan. A joint outbreak response was promptly initiated across jurisdictions in a concerted effort between clinical microbiologists, epidemiologists, and public health scientists. Concurrently, multiplex PCRs were used for rapid laboratory diagnosis of suspected cases; epidemiological investigations were conducted to identify the outbreak source, complemented by near real-time multicenter whole-genome analyses completed within 34 h. Epidemiological evidence indicated that all patients had consumed egg sandwiches served on September 20 as snacks to children and staff at a nursery in Dongguan, located near Shenzhen. Salmonella Enteritidis was isolated from case-patients, food handlers, kitchenware, and sandwiches with kitchen-made mayonnaise. Whole-genome single-nucleotide polymorphism (SNP)-based phylogenetic analysis demonstrated a well-supported cluster with pairwise distances of ≤1 SNP between genomes for outbreak-associated isolates, providing the definitive link between all samples. In comparison with historical isolates from the same geographical region, the minimum pairwise distance was >14 SNPs, suggesting a non-local outbreak source. Genomic source tracing revealed the possible transmission dynamics of a S. Enteritidis clone throughout a multi-provincial egg distribution network. The efficiency and scale with which multidisciplinary and integrated approaches were coordinated in this foodborne disease outbreak response was unprecedented in China, leading to the timely intervention of a large cross-jurisdiction Salmonella outbreak.

Characterisation of Salmonella Enteritidis ST11 and ST1925 Associated with Human Intestinal and Extra-Intestinal Infections in Singapore

Salmonella Enteritidis is a major foodborne pathogen worldwide. In this study, a total of 276 S. enteritidis isolates, collected between 2016 and 2017 from human, food and farm/slaughterhouse samples, were studied to enhance the understanding of the epidemiology of human salmonellosis in Singapore. Results showed all 276 isolates belonged either to ST1925 (70.3%) or ST11 (29.7%), with ST11 being significantly more frequent in extra-intestinal isolates and chicken isolates. Food isolates, most of which were from poultry, showed the highest prevalence of resistance (33–37%) against beta-lactams or beta-lactams/beta-lactamase inhibitor combination (ampicillin, piperacillin and ampicillin/sulbactam). The analysis showed the detection of genes associated with resistance to aminoglycoside genes (99.6%), tetracycline (55.1%), and beta-lactams (14.9%) of all isolates. Nine types of plasmids were found in 266 isolates; the most common incompatibility group profiles were IncFIB(S)-IncFII(S)-IncX1 (72.2%) and IncFIB(S)-IncFII(S) (15.8%). Most plasmid harbouring isolates from chicken (63.6%, 14/22) and from human (73.8%, 175/237) shared the same plasmid profile (IncFIB(S)-IncFII(S)-IncX1). SNP analysis showed clustering of several isolates from poultry food products and human isolates, suggesting phylogenetic relatedness among these isolates. Lastly, this study provides important epidemiological insights on the application of phenotypic and next-generation sequencing (NGS) tools for improved food safety and public health surveillance and outbreak investigation of S.enteritidis.

Development of Single Nucleotide Polymorphism (SNP)-Based Triplex PCR Marker for Serotype-Specific Escherichia coli Detection

Single-nucleotide polymorphisms (SNPs) are one of the most common forms of genetic variation and as such are powerful tools for the identification of bacterial strains, their genetic diversity, phylogenetic analysis, and outbreak surveillance. In this study, we used 15 sets of SNP-containing primers to amplify and sequence the target Escherichia coli. Based on the combination of the 15-sequence primer sets, each SNP site encompassing forward and reverse primer sequences (620–919 bp) were aligned and an SNP-based marker was designed. Each SNP marker exists in at least two SNP sites at the 3′ end of each primer; one natural and the other artificially created by transition or transversion mutation. Thus, 12 sets of SNP primers (225–488 bp) were developed for validation by amplifying the target E. coli. Finally, a temperature gradient triplex PCR kit was designed to detect target E. coli strains. The selected primers were amplified in three genes (ileS, thrB, and polB), with fragment sizes of 401, 337, and 232 bp for E. coli O157:H7, E. coli, and E. coli O145:H28, respectively. This allele-specific SNP-based triplex primer assay provides serotype-specific detection of E. coli strains in one reaction tube. The developed marker would be used to diagnose, investigate, and control food-borne E. coli outbreaks.

Antimicrobial Susceptibility of Lactobacillus delbrueckii subsp. lactis from Milk Products and Other Habitats

As components of many cheese starter cultures, strains of Lactobacillus delbrueckii subsp. lactis (LDL) must be tested for their antimicrobial susceptibility to avoid the potential horizontal transfer of antibiotic resistance (ABR) determinants in the human body or in the environment. To this end, a phenotypic test, as well as a screening for antibiotic resistance genes (ARGs) in genome sequences, is commonly performed. Historically, microbiological cutoffs (MCs), which are used to classify strains as either 'sensitive' or 'resistant' based on the minimal inhibitory concentrations (MICs) of a range of clinically-relevant antibiotics, have been defined for the whole group of the obligate homofermentative lactobacilli, which includes LDL among many other species. This often leads to inaccuracies in the appreciation of the ABR status of tested LDL strains and to false positive results. To define more accurate MCs for LDL, we analyzed the MIC profiles of strains originating from various habitats by using the broth microdilution method. These strains' genomes were sequenced and used to complement our analysis involving a search for ARGs, as well as to assess the phylogenetic proximity between strains. Of LDL strains, 52.1% displayed MICs that were higher than the defined MCs for kanamycin, 9.9% for chloramphenicol, and 5.6% for tetracycline, but no ARG was conclusively detected. On the other hand, all strains displayed MICs below the defined MCs for ampicillin, gentamycin, erythromycin, and clindamycin. Considering our results, we propose the adaptation of the MCs for six of the tested clinically-relevant antibiotics to improve the accuracy of phenotypic antibiotic testing.

Whole-Genome Analysis of Multidrug-Resistant Salmonella Enteritidis Strains Isolated from Poultry Sources in Korea

The Salmonella Enterica subsp. Enterica serovar Enteritidis is one of main serovars isolated from human patients with food poisoning and poultry without clinical signs. Consumption of poultry products contaminated with Salmonella Enteritidis is a common source of human salmonellosis; 82 Salmonella spp. were isolated from 291 samples of retail chicken meat, 201 one-day-old chicks, 30 internal organs of chickens, 156 chicken eggs, 100 duck eggs, 38 straw bedding samples, 18 samples of retail duck meat, and 19 swab samples from slaughterhouses in 2019 and 2020. An antibiotic susceptibility test was performed for all isolates, revealing 33 multidrug-resistant (MDR) strains. The whole genome of 33 MDR strains isolated in 2019 and 2020 and 10 strains isolated in 2011, 2012, and 2017 was sequenced using the MinION sequencing protocol. Within these 43 samples, 5 serovars were identified: S. Enteritidis, S. Agona, S. Virchow, S. Albany, and S. Bareilly. The most common serovar was S. Enteritidis (26/43), which showed the highest resistance to ampicillin (100%), followed by nalidixic acid (90%) and colistin (83%). Core genome multilocus sequence typing analysis showed that the S. Enteritidis strains isolated from different sources and in different years were clustered together. In addition, the S. Enteritidis strains isolated since 2011 consistently harbored the same antibiotic resistance patterns.

Genomic evidence of environmental and resident Salmonella Senftenberg and Montevideo contamination in the pistachio supply-chain

Pistachios have been implicated in two salmonellosis outbreaks and multiple recalls in the U.S. This study performed an in-depth retrospective data analysis of Salmonella associated with pistachios as well as a storage study to evaluate the survivability of Salmonella on inoculated inshell pistachios to further understand the genetics and microbiological dynamics of this commodity-pathogen pair. The retrospective data analysis on isolates associated with pistachios was performed utilizing short-read and long-read sequencing technologies. The sequence data were analyzed using two methods: the FDA's Center for Food Safety and Applied Nutrition Single Nucleotide Polymorphism (SNP) analysis and Whole Genome Multilocus Sequence Typing (wgMLST). The year-long storage study evaluated the survival of five strains of Salmonella on pistachios stored at 25 °C at 35% and 54% relative humidity (RH). Our results demonstrate: i) evidence of persistent Salmonella Senftenberg and Salmonella Montevideo strains in pistachio environments, some of which may be due to clonal resident strains and some of which may be due to preharvest contamination; ii) presence of the Copper Homeostasis and Silver Resistance Island (CHASRI) in Salmonella Senftenberg and Montevideo strains in the pistachio supply chain; and iii) the use of metagenomic analysis is a novel tool for determining the composition of serovar survival in a cocktail inoculated storage study.

Epidemiological Analysis of Salmonella enterica subsp. enterica Serovar Dublin in German Cattle Herds Using Whole-Genome Sequencing

Salmonella enterica subsp. enterica serovar Dublin is a cattle-adapted serovar that causes enteritis and systemic diseases in animals. In Germany, S. Dublin is not detected or is very rarely detected in some federal states but is endemic in certain regions. Information on detailed genetic characteristics of S. Dublin is not available. An understanding of the paths and spreading of S. Dublin within and between regions and over time is essential to establish effective control strategies. Whole-genome sequencing (WGS) and bioinformatic analysis were used to explore the genetic traits of S. Dublin and to determine their epidemiological context. Seventy-four S. Dublin strains collected in 2005 to 2018 from 10 federal states were studied. The phylogeny was analyzed using core-genome single-nucleotide polymorphisms (cgSNPs) and core-genome multilocus sequence typing. Genomic clusters at 100 cgSNPs, 40 cgSNPs, and 15 cgSNPs were selected for molecular epidemiology. WGS-based genoserotyping confirmed serotyping. Important specific virulence determinants were detected in all strains, but multidrug resistance in German S. Dublin organisms is uncommon. Use of different thresholds for cgSNP analysis enabled a broad view and also a detailed view of the occurrence of S. Dublin in Germany. Genomic clusters could be allocated nationwide, to a limited number of federal states, or to special regions only. Results indicate both persistence and spread of S. Dublin within and between federal states in short and longer time periods. However, to detect possible routes of infection or persistence of S. Dublin indicated by genomic analysis, information on the management of the cattle farms and contacts with corresponding farms are essential.

IMPORTANCESalmonella enterica subsp. enterica serovar Dublin is a bovine host-adapted serovar that causes up to 50% of all registered outbreaks of salmonellosis in cattle in Germany. S. Dublin is not detected or is only rarely detected in some federal states but has been endemic in certain regions of the country for a long time. Information on genetic traits of the causative strains is essential to determine routes of infection. WGS and bioinformatic analysis should be used to explore the genetic characteristics of S. Dublin. Combining the genomic features of S. Dublin strains with information on the management of the cattle farms concerned should enable the detection of possible routes of infection or persistence of S. Dublin. This approach is regarded as a prerequisite to developing effective intervention strategies.

Comparison of Conventional Molecular and Whole-Genome Sequencing Methods for Differentiating Salmonella enterica Serovar Schwarzengrund Isolates Obtained from Food and Animal Sources

Over the last decade, Salmonella enterica serovar Schwarzengrund has become more prevalent in Asia, Europe, and the US with the simultaneous emergence of multidrug-resistant isolates. As these pathogens are responsible for many sporadic illnesses and chronic complications, as well as outbreaks over many countries, improved surveillance is urgently needed. For 20 years, pulsed-field gel electrophoresis (PFGE) has been the gold standard for determining bacterial relatedness by targeting genome-wide restriction enzyme polymorphisms. Despite its utility, recent studies have reported that PFGE results correlate poorly with that of closely related outbreak strains and clonally dominant endemic strains. Due to these concerns, alternative amplification-based molecular methods for bacterial strain typing have been developed, including clustered regular interspaced short palindromic repeats (CRISPR) and multilocus sequence typing (MLST). Furthermore, as the cost of sequencing continues to decrease, whole genome sequencing (WGS) is poised to replace other molecular strain typing methods. In this study, we assessed the discriminatory power of PFGE, CRISPR, MLST, and WGS methods to differentiate between 23 epidemiologically unrelated S. enterica serovar Schwarzengrund isolates collected over an 18-year period from distinct locations in Taiwan. The discriminatory index (DI) of each method for different isolates was calculated, resulting in values between 0 (not discriminatory) and 1 (highly discriminatory). Our results showed that WGS has the greatest resolution (DI = 0.982) compared to PFGE (DI = 0.938), CRISPR (DI = 0.906), and MLST (DI = 0.463) methods. In conclusion, the WGS typing approach was shown to be the most sensitive for S. enterica serovar Schwarzengrund fingerprinting.

Assessment of Genetic Stability During Serial In Vitro Passage and In Vivo Carriage

In this study, our objective was to evaluate the genetic stability of foodborne bacterial pathogens during serial passage in vitro and persistent in vivo carriage. Six strains of Listeria, Campylobacter, Escherichia, Salmonella, and Vibrio were serially passaged 20 times. Three colonies were picked for whole-genome sequencing (WGS) from passes P0, P5, P10, P15, and P20. In addition, isolates of Salmonella and Escherichia from three patients with persistent infections were sequenced. Genetic stability was evaluated in terms of variations detected in high-quality single-nucleotide polymorphism (hqSNP), core genome multilocus sequence typing (cgMLST), seven-gene MLST, and determinants encoding serotype, antimicrobial resistance (AMR), and virulence. During serial passage, increasing diversity was observed in Listeria, Salmonella, and Vibrio as measured by hqSNPs (from median of 0 SNPs to median of 3-5 SNPs, depending on the organism) and to a lesser extent with cgMLST (from median of 0 alleles to median of 0-5 alleles), while Escherichia and Campylobacter genomes showed minimal variation. The serotype, AMR, and virulence markers remained stable in all organisms. Isolates from persistent infections lasting up to 10 weeks remained genetically stable. However, isolates from a persistent Salmonella enterica ser. Montevideo infection spanning 9 years showed early heterogeneity leading to the emergence of one predominant genotype that continued to evolve over the years, including gains and losses of AMR markers. While the hqSNP and cgMLST variation observed during the serial passage was minimal, culture passages should be limited to as few times as possible before WGS. Our WGS data show that in vivo carriage lasting for a few weeks did not appear to alter the genotype. Longer persistent infections spanning for years, particularly in the presence of selective pressure, may cause changes in the genotype making it challenging to differentiate persistent infections from reinfections.

Elucidation of global and national genomic epidemiology of Salmonella enterica serovar Enteritidis through multilevel genome typing

Salmonella enterica serovar Enteritidis is a major cause of foodborne Salmonella infections and outbreaks in humans. Effective surveillance and timely outbreak detection are essential for public health control. Multilevel genome typing (MGT) with multiple levels of resolution has been previously demonstrated as a promising tool for this purpose. In this study, we developed MGT with nine levels for S. Enteritidis and characterised the genomic epidemiology of S. Enteritidis in detail. We examined 26 670 publicly available S. Enteritidis genome sequences from isolates spanning 101 years from 86 countries to reveal their spatial and temporal distributions. Using the lower resolution MGT levels, globally prevalent and regionally restricted sequence types (STs) were identified; avian associated MGT4-STs were found that were common in human cases in the USA; temporal trends were observed in the UK with MGT5-STs from 2014 to 2018 revealing both long lived endemic STs and the rapid expansion of new STs. Using MGT3 to MGT6, we identified multidrug resistance (MDR) associated STs at various MGT levels, which improves precision of detection and global tracking of MDR clones. We also found that the majority of the global S. Enteritidis population fell within two predominant lineages, which had significantly different propensity of causing large scale outbreaks. An online open MGT database has been established for unified international surveillance of S. Enteritidis. We demonstrated that MGT provides a flexible and high-resolution genome typing tool for S. Enteritidis surveillance and outbreak detection.

Whole-Genome Analysis of Salmonella enterica Serovar Enteritidis Isolates in Outbreak Linked to Online Food Delivery, Shenzhen, China, 2018

In July 2018, an outbreak of 10 cases of Salmonella enterica serovar Enteritidis infection occurred in Shenzhen, China. Outbreak investigation complemented by whole-genome sequencing traced the source to food ordered online. Our investigation highlights the role of online food delivery platforms as a new mode of foodborne disease transmission.

Tracking Salmonella enterica by whole genome sequencing of isolates recovered from broiler chickens in a poultry production system

Salmonella enterica is a major cause of foodborne diseases, and is also an important pathogenic bacterium in poultry industry. Whole genome sequencing (WGS) has become a crucial molecular typing technology used for the surveillance of the pathogenic bacteria. In the present study, we adopted WGS for tracking transmission of S. enterica in the production chain of broiler chickens. A total of 74 S. enterica strains were isolated from the different steps of breeding and slaughtering in a large production enterprise in Sichuan Province, China. The isolation rate of Salmonella was the highest in procedure of defeathering (50.0%) and evisceration (36.7%). Serotype identification showed that 74 Salmonella isolates included 7 serotypes, among which Mbandaka accounted for the highest proportions (35.1%). WGS revealed that 74 strains belonged to 7 different sequence types (STs), as well as 7 different ribosomal STs and 35 core genome STs. cgMLST-based Minimum Spanning Trees and phylogenetic tree based on the SNPs indicated that three serotypes, Mbandaka, Indiana and Kentucky, could be clonally transmitted between broiler farm and slaughterhouse. Heterogeneous resistant phenotypes and genotypes were found in two serotypes, Indiana and Kentucky. Our study indicated WGS in an accurate tool for molecular typing of S. enterica. Routine surveillance of S. enterica in the production chain of broiler chickens is needed.

Retrospective whole-genome comparison of Salmonella enterica serovar Enteritidis from foodborne outbreaks in Southern Brazil

Salmonella enterica serovar Enteritidis is frequently isolated from animal-source foods associated with human salmonellosis outbreaks. This serovar was spread to animal (mainly poultry) farms worldwide in the 1980s, and it is still detected in foods produced in many countries, including Brazil. The present study reports a retrospective genome-wide comparison of S. Enteritidis from foodborne outbreaks in Southern Brazil in the last two decades. Fifty-two S. Enteritidis isolates were obtained from foodborne outbreaks occurring in different cities of the Brazilian southernmost State, Rio Grande do Sul (RS), from 2003 to 2015. Whole-genome sequences (WGS) from these isolates were obtained and comparatively analyzed with 65 additional genomes from NCBI. Phylogenetic and Bayesian analyses were performed to study temporal evolution. Genes related to antibiotic resistance and virulence were also evaluated. The results demonstrated that all S. Enteritidis isolates from Southern Brazil clustered in the global epidemic clade disseminated worldwide originally in the 1980s. Temporal analysis demonstrated that all Brazilian isolates had a tMRCA (time to most recent common ancestor) in 1986 with an effective population size (N_e) increase soon after until 1992, then becoming constant up to now. In Southern Brazil, there was a significant decrease in the spreading of S. Enteritidis in the last decade. In addition, three antibiotic resistance genes were detected in all isolates: aac(6')-Iaa, mdfA, and tet(34). These results demonstrate the high frequency of one only specific S. Enteritidis lineage (global epidemic clade) in foodborne outbreaks from Southern Brazil in the last two decades.

Genomic diversity of Salmonella enterica isolated from papaya samples collected during multiple outbreaks in 2017

In 2017, the US Food and Drug Administration investigated the sources of multiple outbreaks of salmonellosis. Epidemiologic and traceback investigations identified Maradol papayas as the suspect vehicles. During the investigations, the genomes of 55 Salmonella enterica that were isolated from papaya samples were sequenced. Serovar assignments and phylogenetic analysis placed the 55 isolates into ten distinct groups, each representing a different serovar. Within-serovar SNP differences are generally between 0 and 20 SNPs, while the median between-serovar distance is 51 812 SNPs. We observed two groups with SNP distances between 21 and 100 SNPs. These relatively large within-serovar SNP distances may indicate that the isolates represent either diverse populations or multiple, genetically distinct subpopulations. Further inspection of these cases with traceback evidence allowed us to identify an 11th population. We observed that high levels of genomic diversity from individual firms is possible, with one firm yielding five of the ten serovars. Also, high levels of diversity are possible within small geographic regions, as five of the serovars were isolated from papayas that originated from farms located in Armería and Tecomán, Colima. In addition, we identified AMR genes that are present in three of the serovars studied here (aph(3')-lb, aph(6)-ld, tet(C), fosA7, and qnrB19) and we detected the presence of the plasmid IncHI2A among S. Urbana isolates.

Molecular Epidemiology of Salmonellosis in Florida, USA, 2017-2018

The state of Florida reports a high burden of non-typhoidal Salmonella enterica with approximately two times higher than the national incidence. We retrospectively analyzed the population structure and molecular epidemiology of 1,709 clinical isolates from 2017 and 2018. We found 115 different serotypes. Rarefaction suggested that the serotype richness did not differ between children under 2 years of age and older children and adults and, there are ~22 well-characterized dominant serotypes. There were distinct differences in dominant serotypes between Florida and the USA as a whole, even though S. Enteritidis and S. Newport were the dominant serotypes in Florida and nationally. S. Javiana, S. Sandiego, and S. IV 50:z4, z23:- occurred more frequently in Florida than nationally. Legacy Multi Locus Sequence Typing (MLST) was of limited use for differentiating clinical Salmonella isolates beyond the serotype level. We utilized core genome MLST (cgMLST) hierarchical clusters (HC) to identify potential outbreaks and compared them to outbreaks detected by Pulse Field Gel Electrophoresis (PFGE) surveillance for five dominant serotypes (Enteritidis, Newport, Javiana, Typhimurium, and Bareilly). Single nucleotide polymorphism (SNP) phylogenetic-analysis of cgMLST HC at allelic distance 5 or less (HC5) corroborated PFGE detected outbreaks and generated well-segregated SNP distance-based clades for all studied serotypes. We propose “combination approach” comprising “HC5 clustering,” as efficient tool to trigger Salmonella outbreak investigations, and “SNP-based analysis,” for higher resolution phylogeny to confirm an outbreak. We also applied this approach to identify case clusters, more distant in time and place than traditional outbreaks but may have been infected from a common source, comparing 176 Florida clinical isolates and 1,341 non-clinical isolates across USA, of most prevalent serotype Enteritidis collected during 2017–2018. Several clusters of closely related isolates (0–4 SNP apart) within HC5 clusters were detected and some included isolates from poultry from different states in the US, spanning time periods over 1 year. Two SNP-clusters within the same HC5 cluster included isolates with the same multidrug-resistant profile from both humans and poultry, supporting the epidemiological link. These clusters likely reflect the vertical transmission of Salmonella clones from higher levels in the breeding pyramid to production flocks.

Epidemiology and Characterization of CTX-M-55-Type Extended-Spectrum β-Lactamase-Producing Salmonella enterica Serovar Enteritidis Isolated from Patients in Shanghai, China

The emergence of extended-spectrum β-lactamase-producing Salmonella enterica serovar Enteritidis (ESBL-SE) in humans and foods has gained global attention. In particular, CTX-M-type ESBL-SE are increasingly being detected from various sample types. The aim of this study was to comprehensively analyze the epidemiology and characteristics of bla_CTX-M-55-carrying ESBL-SE isolates of clinical origin in Shanghai, China. A total of 292 S. Enteritidis isolates were recovered from the feces and blood of outpatients and inpatients between 2006 and 2014. Overall, there was a high frequency of cefotaxime-resistant isolates (97.3%), which was significantly higher (p < 0.01) than that of isolates resistant to the other tested antibiotics. All S. Enteritidis isolates exhibited resistance to ≥1 antibiotic, and 98.0% were multidrug resistant. A total of 233 isolates were identified as ESBL-SE, 166 of which were CTX-M type. Six subtypes of CTX-M-encoding genes were detected, among which bla_CTX-M-55 (91.6%, 152/166) was the most prevalent genotype. There was high genetic similarity among bla_CTX-M-55-positive ESBL-SE. The bla_CTX-M-55 gene in the ESBL-SE donor strains could be easily transferred into Enterobacteriaceae recipient strains. This study highlights that CTX-M-55 should be considered an important surveillance target in Shanghai, China. Cephalosporins, especially cefotaxime, must be used with caution in empirical treatment for Salmonella infections.

Integrated Whole-Genome Sequencing Infrastructure for Outbreak Detection and Source Tracing of Salmonella enterica Serotype Enteritidis

As an important foodborne pathogen, Salmonella enterica serotype Enteritidis is recognized as one of the most common causes of human salmonellosis globally. Outbreak detection for this highly homogenous serotype, however, has remained challenging. Rapid advances in sequencing technologies have presented whole-genome sequencing (WGS) as a significant advancement for source tracing and molecular typing of foodborne pathogens. A retrospective analysis was conducted using Salmonella Enteritidis isolates (n = 65) from 11 epidemiologically confirmed outbreaks and a collection of contemporaneous sporadic isolates (n = 258) during 2007-2017 to evaluate the performance of WGS in delineating outbreak-associated isolates. Whole-genome single-nucleotide polymorphism (SNP)-based phylogenetic analysis revealed well-supported clades in concordance with epidemiological evidence and pairwise distances of ≤3 SNPs for all outbreaks. WGS-based framework of outbreak detection was thus proposed and applied prospectively to investigate isolates (n = 66) from nine outbreaks during 2018-2019. We further demonstrated the superior discriminatory power and accuracy of WGS to resolve and delineate outbreaks for pragmatic food source tracing. The proposed integrated WGS framework is the first in China for Salmonella Enteritidis and has the potential to serve as a paradigm for outbreak detection and source tracing of Salmonella throughout the stages of food production, as well as expanded to other foodborne pathogens.

cgMLST@Taiwan: A web service platform for Vibrio cholerae cgMLST profiling and global strain tracking

BACKGROUND

Cholera, a rapidly dehydrating diarrheal disease caused by toxigenic Vibrio cholerae, is a leading cause of morbidity and mortality in some regions of the world. Core genome multilocus sequence typing (cgMLST) is a promising approach in generating genetic fingerprints from whole-genome sequencing (WGS) data for strain comparison among laboratories.

METHODS

We constructed a V. cholerae core gene allele database using an in-house developed computational pipeline, a database with cgMLST profiles converted from genomic sequences from the National Center for Biotechnology Information, and built a REST-based web accessible via the Internet.

RESULTS

We built a web service platform-cgMLST@Taiwan and installed a V. cholerae allele database, a cgMLST profile database, and computational tools for generating V. cholerae cgMLST profiles (based on 3,017 core genes), performing rapid global strain tracking, and clustering analysis of cgMLST profiles. This web-based platform provides services to researchers, public health microbiologists, and physicians who use WGS data for the investigation of cholera outbreaks and tracking of V. cholerae strain transmission across countries and geographic regions. The cgMLST@Taiwan is accessible at http://rdvd.cdc.gov.tw/cgMLST.

Diverse lineages of multidrug resistant clinical Salmonella enterica and a cryptic outbreak in New Hampshire, USA revealed from a year-long genomic surveillance

Salmonella enterica, the causative agent of gastrointestinal diseases and typhoid fever, is a human and animal pathogen that causes significant mortality and morbidity worldwide. In this study, we examine the genomic diversity and phylogenetic relationships of 63 S. enterica isolates from human-derived clinical specimens submitted to the Department of Health and Human Services (DHHS) in the state of New Hampshire, USA in 2017. We found a remarkably large genomic, phylogenetic and serotype variation among the S. enterica isolates, dominated by serotypes Enteritidis (sequence type [ST] 11), Heidelberg (ST 15) and Typhimurium (ST 19). Analysis of the distribution of single nucleotide polymorphisms in the core genome suggests that the ST 15 cluster is likely a previously undetected or cryptic outbreak event that occurred in the south/southeastern part of New Hampshire in August-September. We found that nearly all of the clinical S. enterica isolates carried horizontally acquired genes that confer resistance to multiple classes of antimicrobials, most notably aminoglycosides, fluoroquinolones and macrolides. Majority of the isolates (76.2%) carry at least four resistance determinants per genome. We also detected the genes mdtK and mdsABC that encode multidrug efflux pumps and the gene sdiA that encodes a regulator for a third multidrug resistance pump. Our results indicate rapid microevolution and geographical dissemination of multidrug resistant lineages over a short time span. These findings are critical to aid the DHHS and similar public health laboratories in the development of effective disease control measures, epidemiological studies and treatment options for serious Salmonella infections.

Virulence and resistance genes profiles and clonal relationships of non-typhoidal food-borne Salmonella strains isolated in Tunisia by whole genome sequencing

Whole genome sequencing (WGS) has made impressive progress in the field of molecular biology. Its most common application for public health is in the area of surveillance of food-borne diseases. WGS has the potential for providing a large amount of information, such as the identification of the strain type, the characterization of antibiotic resistance and virulence, and phylogeny. In our study, thirty-nine non-typhoidal Salmonella strains were isolated from diverse sources in Tunisia. Non-typhoidal Salmonella are among the most common pathogens contaminating food animals. The presence of virulence and antimicrobial resistance determinants in those strains were investigated using whole genome sequencing (WGS) and appropriate data analysis. The genomes were screened for several Salmonella virulence genes using the Virulence Factor Database VFDB. Twelve different virulence profiles, which correspond to the 12 identified serovars, were recognized. Several antimicrobial resistance genes were also detected: aac (6')-Iaa, sul1, tetA, bla-TEM and qnrS genes. Phylogenetic relationships among the strains were further assessed by a cgMLST analysis. The resulting phylogenetic tree consisted of several clusters consistently with the in silico multilocus sequence typing (MLST) and serotyping. Our findings demonstrated that WGS and subsequent data analysis provided an accurate tool for genetic characterization of bacterial strains compared to usual molecular typing techniques. To the best of our knowledge, this is the first report of an application of WGS for genetic characterization of food-borne Tunisian strains.

Comparison of conventional molecular and whole-genome sequencing methods for subtyping Salmonella enterica serovar Enteritidis strains from Tunisia

We sought to determine the relative value of conventional molecular methods and whole-genome sequencing (WGS) for subtyping Salmonella enterica serovar Enteritidis recovered from 2000 to 2015 in Tunisia and to investigate the genetic diversity of this serotype. A total of 175 Salmonella Enteritidis isolates were recovered from human, animal, and foodborne outbreak samples. Pulsed-field gel electrophoresis (PFGE), multiple locus variable-number tandem repeat analysis (MLVA), and whole-genome sequencing were performed. Eight pulsotypes were detected for all isolates with PFGE (DI = 0.518). Forty-five Salmonella Enteritidis isolates were selected for the MLVA and WGS techniques. Eighteen MLVA profiles were identified and classified into two major clusters (DI = 0.889). Core genome multilocus typing (cgMLST) analysis revealed 16 profiles (DI = 0.785). Whole-genome analysis indicated 660 single-nucleotide polymorphism (SNP) divergences dividing these isolates into 43 haplotypes (DI = 0.997). The phylogenetic tree supported the classification of Salmonella Enteritidis isolates into two distinct lineages subdivided into five clades and seven subclades. Pairwise SNP differences between the isolates ranged between 302 and 350. We observed about 311 SNP differences between the two foodborne outbreaks, while only less or equal to 4 SNP differences within each outbreak. SNP-based WGS typing showed an excellent discriminatory power comparing with the conventional methods such as PFGE and MLVA. Besides, we demonstrate the added value of WGS as a complementary subtyping method to discriminate outbreak from non-outbreak isolates belonging to common subtypes. It is important to continue the survey of Salmonella Enteritidis lineages in Tunisia using WGS.

Development of a High-Resolution Single-Nucleotide Polymorphism Strain-Typing Assay Using Whole Genome-Based Analyses for the Lactobacillus acidophilus Probiotic Strain

Lactobacillus acidophilus is one of the most commonly used industrial products worldwide. Since its probiotic efficacy is strain-specific, the identification of probiotics at both the species and strain levels is necessary. However, neither phenotypic nor conventional genotypic methods have enabled the effective differentiation of L. acidophilus strains. In this study, a whole-genome sequence-based analysis was carried out to establish high-resolution strain typing of 41 L. acidophilus strains (including commercial isolates and reference strains) using the cano-wgMLST_BacCompare analytics platform; consequently, a strain-specific discrimination method for the probiotic strain LA1063 was developed. Using a core-genome multilocus sequence-typing (cgMLST) scheme based on 1390 highly conserved genes, 41 strains could be assigned to 34 sequence types. Subsequently, we screened a set of 92 loci with a discriminatory power equal to that of the 1390 loci cgMLST scheme. A strain-specific polymerase chain reaction combined with a multiplex minisequencing method was developed based on four (phoU, secY, tilS, and uvrA_1) out of 21 loci, which could be discriminated between LA1063 and other L. acidophilus strains using the cgMLST data. We confirmed that the strain-specific single-nucleotide polymorphisms method could be used to quickly and accurately identify the L. acidophilus probiotic strain LA1063 in commercial products.

Comparing serotyping with whole-genome sequencing for subtyping of non-typhoidal Salmonella enterica: a large-scale analysis of 37 serotypes with a public health impact in the USA

Serotyping has traditionally been used for subtyping of non-typhoidal Salmonella (NTS) isolates. However, its discriminatory power is limited, which impairs its use for epidemiological investigations of source attribution. Whole-genome sequencing (WGS) analysis allows more accurate subtyping of strains. However, because of the relative newness and cost of routine WGS, large-scale studies involving NTS WGS are still rare. We aimed to revisit the big picture of subtyping NTS with a public health impact by using traditional serotyping (i.e. reaction between antisera and surface antigens) and comparing the results with those obtained using WGS. For this purpose, we analysed 18 282 sequences of isolates belonging to 37 serotypes with a public health impact that were recovered in the USA between 2006 and 2017 from multiple sources, and were available at the National Center for Biotechnology Information (NCBI). Phylogenetic trees were reconstructed for each serotype using the core genome for the identification of genetic subpopulations. We demonstrated that WGS-based subtyping allows better identification of sources potentially linked with human infection and emerging subpopulations, along with providing information on the risk of dissemination of plasmids and acquired antimicrobial resistance genes (AARGs). In addition, by reconstructing a phylogenetic tree with representative isolates from all serotypes (n=370), we demonstrated genetic variability within and between serotypes, which formed monophyletic, polyphyletic and paraphyletic clades. Moreover, we found (in the entire data set) an increased detection rate for AARGs linked to key antimicrobials (such as quinolones and extended-spectrum cephalosporins) over time. The outputs of this large-scale analysis reveal new insights into the genetic diversity within and between serotypes; the polyphyly and paraphyly of certain serotypes may suggest that the subtyping of NTS to serotypes may not be sufficient. Moreover, the results and the methods presented here, leading to differentiation between genetic subpopulations based on their potential risk to public health, as well as narrowing down the possible sources of these infections, may be used as a baseline for subtyping of future NTS infections and help efforts to mitigate and prevent infections in the USA and globally.

Prospective Salmonella Enteritidis surveillance and outbreak detection using whole genome sequencing, Minnesota 2015-2017

Clusters of Salmonella Enteritidis cases were identified by the Minnesota Department of Health using both pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) single nucleotide polymorphism analysis from 1 January 2015 through 31 December 2017. The median turnaround time for obtaining WGS results was 11 days longer than for PFGE (12 vs. 1 day). WGS analysis more than doubled the number of clusters compared to PFGE analysis, but reduced the total number of cases included in clusters by 34%. The median cluster size was two cases for WGS compared to four for PFGE, and the median duration of WGS clusters was 27 days shorter than PFGE clusters. While the percentage of PFGE clusters with a confirmed source (46%) was higher than WGS clusters (32%), a higher percentage of cases in clusters that were confirmed as outbreaks reported the vehicle or exposure of interest for WGS (78%) than PFGE (46%). WGS cluster size was a significant predictor of an outbreak source being confirmed. WGS data have enhanced S. Enteritidis cluster investigations in Minnesota by improving the specificity of cluster case definitions and has become an integral part of the S. Enteritidis surveillance process.

Genomic Comparison of Salmonella Enteritidis Strains Isolated from Laying Hens and Humans in the Abruzzi Region during 2018

Salmonellosis is a major cause of bacterial foodborne infection. Since 2016, an increased number of cases of gastroenteritis caused by Salmonella enterica serovar Enteritidis linked to eggs produced in Poland has been reported in Europe. In Italy, S. Enteritidis is one of the three most commonly reported serotypes, associated mainly with the consumption of contaminated eggs and derived products. In our work, we analysed 61 strains of S. Enteritidis obtained from humans and farms in the Abruzzi region, Italy, in 2018. We used Multiple-Loci Variable-Number Tandem Repeat (VNTR) analysis (MLVA)-based typing and Whole-Genome Sequencing (WGS) tools to identify closely related strains and perform cluster analysis. We found two clusters of genetically similar strains. The first one was present in the local farms and isolated from human cases and had single-linkage distance of no more than two core genes and less than five Single-Nucleotide Polymorphisms (SNPs). The second cluster contained strains isolated from humans and from a dessert (tiramisù) sample that shared identical core genome and were assigned the same SNP address. Cluster 2 isolates were found to be genetically similar to an S. Enteritidis strain from a multi-country outbreak linked to Polish eggs.

A One Health investigation of Salmonella enterica serovar Wangata in north-eastern New South Wales, Australia, 2016-2017

Salmonella enterica serovar Wangata (S. Wangata) is an important cause of endemic salmonellosis in Australia, with human infections occurring from undefined sources. This investigation sought to examine possible environmental and zoonotic sources for human infections with S. Wangata in north-eastern New South Wales (NSW), Australia. The investigation adopted a One Health approach and was comprised of three complimentary components: a case–control study examining human risk factors; environmental and animal sampling; and genomic analysis of human, animal and environmental isolates. Forty-eight human S. Wangata cases were interviewed during a 6-month period from November 2016 to April 2017, together with 55 Salmonella Typhimurium (S. Typhimurium) controls and 130 neighbourhood controls. Indirect contact with bats/flying foxes (S. Typhimurium controls (adjusted odds ratio (aOR) 2.63, 95% confidence interval (CI) 1.06–6.48)) (neighbourhood controls (aOR 8.33, 95% CI 2.58–26.83)), wild frogs (aOR 3.65, 95% CI 1.32–10.07) and wild birds (aOR 6.93, 95% CI 2.29–21.00) were statistically associated with illness in multivariable analyses. S. Wangata was detected in dog faeces, wildlife scats and a compost specimen collected from the outdoor environments of cases’ residences. In addition, S. Wangata was detected in the faeces of wild birds and sea turtles in the investigation area. Genomic analysis revealed that S. Wangata isolates were relatively clonal. Our findings suggest that S. Wangata is present in the environment and may have a reservoir in wildlife populations in north-eastern NSW. Further investigation is required to better understand the occurrence of Salmonella in wildlife groups and to identify possible transmission pathways for human infections.

PulseNet and the Changing Paradigm of Laboratory-Based Surveillance for Foodborne Diseases

PulseNet, the National Molecular Subtyping Network for Foodborne Disease Surveillance, was established in 1996 through a collaboration with the Centers for Disease Control and Prevention; the US Department of Agriculture, Food Safety and Inspection Service; the US Food and Drug Administration; 4 state public health laboratories; and the Association of Public Health Laboratories. The network has since expanded to include 83 state, local, and food regulatory public health laboratories. In 2016, PulseNet was estimated to be helping prevent an estimated 270 000 foodborne illnesses annually. PulseNet is undergoing a transformation toward whole-genome sequencing (WGS), which provides better discriminatory power and precision than pulsed-field gel electrophoresis (PFGE). WGS improves the detection of outbreak clusters and could replace many traditional reference identification and characterization methods. This article highlights the contributions made by public health laboratories in transforming PulseNet's surveillance and describes how the transformation is changing local and national surveillance practices. Our data show that WGS is better at identifying clusters than PFGE, especially for clonal organisms such as Salmonella Enteritidis. The need to develop prioritization schemes for cluster follow-up and additional resources for both public health laboratory and epidemiology departments will be critical as PulseNet implements WGS for foodborne disease surveillance in the United States.

Typing methods based on whole genome sequencing data

Whole genome sequencing (WGS) of foodborne pathogens has become an effective method for investigating the information contained in the genome sequence of bacterial pathogens. In addition, its highly discriminative power enables the comparison of genetic relatedness between bacteria even on a sub-species level. For this reason, WGS is being implemented worldwide and across sectors (human, veterinary, food, and environment) for the investigation of disease outbreaks, source attribution, and improved risk characterization models. In order to extract relevant information from the large quantity and complex data produced by WGS, a host of bioinformatics tools has been developed, allowing users to analyze and interpret sequencing data, starting from simple gene-searches to complex phylogenetic studies. Depending on the research question, the complexity of the dataset and their bioinformatics skill set, users can choose between a great variety of tools for the analysis of WGS data. In this review, we describe the relevant approaches for phylogenomic studies for outbreak studies and give an overview of selected tools for the characterization of foodborne pathogens based on WGS data. Despite the efforts of the last years, harmonization and standardization of typing tools are still urgently needed to allow for an easy comparison of data between laboratories, moving towards a one health worldwide surveillance system for foodborne pathogens.

Genomic diversity affects the accuracy of bacterial single-nucleotide polymorphism-calling pipelines

BACKGROUND

Accurately identifying single-nucleotide polymorphisms (SNPs) from bacterial sequencing data is an essential requirement for using genomics to track transmission and predict important phenotypes such as antimicrobial resistance. However, most previous performance evaluations of SNP calling have been restricted to eukaryotic (human) data. Additionally, bacterial SNP calling requires choosing an appropriate reference genome to align reads to, which, together with the bioinformatic pipeline, affects the accuracy and completeness of a set of SNP calls obtained. This study evaluates the performance of 209 SNP-calling pipelines using a combination of simulated data from 254 strains of 10 clinically common bacteria and real data from environmentally sourced and genomically diverse isolates within the genera Citrobacter, Enterobacter, Escherichia, and Klebsiella.

RESULTS

We evaluated the performance of 209 SNP-calling pipelines, aligning reads to genomes of the same or a divergent strain. Irrespective of pipeline, a principal determinant of reliable SNP calling was reference genome selection. Across multiple taxa, there was a strong inverse relationship between pipeline sensitivity and precision, and the Mash distance (a proxy for average nucleotide divergence) between reads and reference genome. The effect was especially pronounced for diverse, recombinogenic bacteria such as Escherichia coli but less dominant for clonal species such as Mycobacterium tuberculosis.

CONCLUSIONS

The accuracy of SNP calling for a given species is compromised by increasing intra-species diversity. When reads were aligned to the same genome from which they were sequenced, among the highest-performing pipelines was Novoalign/GATK. By contrast, when reads were aligned to particularly divergent genomes, the highest-performing pipelines often used the aligners NextGenMap or SMALT, and/or the variant callers LoFreq, mpileup, or Strelka.

BacPipe: A Rapid, User-Friendly Whole-Genome Sequencing Pipeline for Clinical Diagnostic Bacteriology

Despite rapid advances in whole genome sequencing (WGS) technologies, their integration into routine microbiological diagnostics has been hampered by the lack of standardized downstream bioinformatics analysis. We developed a comprehensive and computationally low-resource bioinformatics pipeline (BacPipe) enabling direct analyses of bacterial whole-genome sequences (raw reads or contigs) obtained from second- or third-generation sequencing technologies. A graphical user interface was developed to visualize real-time progression of the analysis. The scalability and speed of BacPipe in handling large datasets was demonstrated using 4,139 Illumina paired-end sequence files of publicly available bacterial genomes (2.9–5.4 Mb) from the European Nucleotide Archive. BacPipe is integrated in EBI-SELECTA, a project-specific portal (H2020-COMPARE), and is available as an independent docker image that can be used across Windows- and Unix-based systems. BacPipe offers a fully automated “one-stop” bacterial WGS analysis pipeline to overcome the major hurdle of WGS data analysis in hospitals and public-health and for infection control monitoring.

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BacPipe is an automated whole genome sequencing pipeline

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Interactive user-friendly GUI

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BacPipe can process raw reads, contigs, or scaffolds

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Time-to-analysis for a 5 Mb genome is ∼30–40 min

The Transformation of Reference Microbiology Methods and Surveillance for Salmonella With the Use of Whole Genome Sequencing in England and Wales

The use of whole genome sequencing (WGS) as a method for supporting outbreak investigations, studying Salmonella microbial populations and improving understanding of pathogenicity has been well-described (1–3). However, performing WGS on a discrete dataset does not pose the same challenges as implementing WGS as a routine, reference microbiology service for public health surveillance. Challenges include translating WGS data into a useable format for laboratory reporting, clinical case management, Salmonella surveillance, and outbreak investigation as well as meeting the requirement to communicate that information in an understandable and universal language for clinical and public health action. Public Health England have been routinely sequencing all referred presumptive Salmonella isolates since 2014 which has transformed our approach to reference microbiology and surveillance. Here we describe an overview of the integrated methods for cross-disciplinary working, describe the challenges and provide a perspective on how WGS has impacted the laboratory and surveillance processes in England and Wales.

A Simple and Robust Statistical Method to Define Genetic Relatedness of Samples Related to Outbreaks at the Genomic Scale - Application to Retrospective Salmonella Foodborne Outbreak Investigations

The investigation of foodborne outbreaks (FBOs) from genomic data typically relies on inspecting the relatedness of samples through a phylogenomic tree computed on either SNPs, genes, kmers, or alleles (i.e., cgMLST and wgMLST). The phylogenomic reconstruction is often time-consuming, computation-intensive and depends on hidden assumptions, pipelines implementation and their parameterization. In the context of FBO investigations, robust links between isolates are required in a timely manner to trigger appropriate management actions. Here, we propose a non-parametric statistical method to assert the relatedness of samples (i.e., outbreak cases) or whether to reject them (i.e., non-outbreak cases). With typical computation running within minutes on a desktop computer, we benchmarked the ability of three non-parametric statistical tests (i.e., Wilcoxon rank-sum, Kolmogorov-Smirnov and Kruskal-Wallis) on six different genomic features (i.e., SNPs, SNPs excluding recombination events, genes, kmers, cgMLST alleles, and wgMLST alleles) to discriminate outbreak cases (i.e., positive control: C+) from non-outbreak cases (i.e., negative control: C-). We leveraged four well-characterized and retrospectively investigated FBOs of Salmonella Typhimurium and its monophasic variant S. 1,4,[5],12:i:- from France, setting positive and negative controls in all the assays. We show that the approaches relying on pairwise SNP differences distinguished all four considered outbreaks in contrast to the other tested genomic features (i.e., genes, kmers, cgMLST alleles, and wgMLST alleles). The freely available non-parametric method written in R has been designed to be independent of both the phylogenomic reconstruction and the detection methods of genomic features (i.e., SNPs, genes, kmers, or alleles), making it widely and easily usable to anybody working on genomic data from suspected samples.

Salmonella enterica Serotype 4,[5],12:i:- in Swine in the United States Midwest: An Emerging Multidrug-Resistant Clade

Background

Salmonella 4,[5],12:i:-, a worldwide emerging pathogen that causes many food-borne outbreaks mostly attributed to pig and pig products, is expanding in the United States.

Methods

Whole-genome sequencing was applied to conduct multiple comparisons of 659 S. 4,[5],12:i:- and 325 Salmonella Typhimurium from different sources and locations (ie, the United States and Europe) to assess their genetic heterogeneity, with a focus on strains recovered from swine in the US Midwest. In addition, the presence of resistance genes and other virulence factors was detected and the antimicrobial resistance phenotypes of 50 and 22 isolates of livestock and human origin, respectively, was determined.

Results

The S. 4,5,12:i:- strains formed two main clades regardless of their source and geographic origin. Most (84%) of the US isolates recovered in 2014-2016, including those (48 of 51) recovered from swine in the US Midwest, were part of an emerging clade. In this clade, multiple genotypic resistance determinants were predominant, including resistance against ampicillin, streptomycin, sulfonamides, and tetracyclines. Phenotypic resistance to enrofloxacin (11 of 50) and ceftiofur (9 of 50) was found in conjunction with the presence of plasmid-mediated resistance genes (qnrB19/qnrB2/qnrS1 and blaCMY-2/blaSHV-12, respectively). Higher similarity was also found between S. 4,[5],12:i:- from the emerging clade and S. Typhimurium from Europe than with S. Typhimurium from the United States.

Conclusions

Salmonella 4,[5],12:i:- currently circulating in swine in the US Midwest are likely to be part of an emerging multidrug-resistant clade first reported in Europe, and can carry plasmid-mediated resistance genes that may be transmitted horizontally to other bacteria, and thus may represent a public health concern.

Multidrug-Resistant Salmonella I 4,[5],12:i:- and Salmonella Infantis Infections Linked to Whole Roasted Pigs from a Single Slaughter and Processing Facility

We describe two outbreaks of multidrug-resistant (MDR) Salmonella I 4,[5],12:i:- infection, occurring in 2015 to 2016, linked to pork products, including whole roaster pigs sold raw from a single Washington slaughter and processing facility (establishment A). Food histories from 80 ill persons were compared with food histories reported in the FoodNet 2006 to 2007 survey of healthy persons from all 10 U.S. FoodNet sites who reported these exposures in the week before interview. Antimicrobial susceptibility testing and whole genome sequencing were conducted on selected clinical, food, and environmental isolates. During 2015, a total of 192 ill persons were identified from five states; among ill persons with available information, 30 (17%) of 180 were hospitalized, and none died. More ill persons than healthy survey respondents consumed pork (74 versus 43%, P < 0.001). Seventeen (23%) of 73 ill persons for which a response was available reported attending an event where whole roaster pig was served in the 7 days before illness onset. All 25 clinical isolates tested from the 2015 outbreak and a subsequent 2016 smaller outbreak (n = 15) linked to establishment A demonstrated MDR. Whole genome sequencing of clinical, environmental, and food isolates (n = 69) collected in both investigations revealed one clade of highly related isolates, supporting epidemiologic and traceback data that establishment A as the source of both outbreaks. These investigations highlight that whole roaster pigs, an uncommon food vehicle for MDR Salmonella I 4,[5],12:i:- outbreaks, will need further attention from food safety researchers and educators for developing science-based consumer guidelines, specifically with a focus on the preparation process.

Outbreaks of Salmonella illness associated with frozen raw breaded chicken products in Canada, 2015-2019

Frozen raw breaded chicken products (FRBCP) have been identified as a risk factor for Salmonella infection in Canada. In 2017, Canada implemented whole genome sequencing (WGS) for clinical and non-clinical Salmonella isolates, which increased understanding of the relatedness of Salmonella isolates, resulting in an increased number of Salmonella outbreak investigations. A total of 18 outbreaks and 584 laboratory-confirmed cases have been associated with FRBCP or chicken since 2017. The introduction of WGS provided the evidence needed to support a new requirement to control the risk of Salmonella in FRBCP produced for retail sale.

Status and potential of bacterial genomics for public health practice: a scoping review

BACKGROUND

Next-generation sequencing (NGS) is increasingly being translated into routine public health practice, affecting the surveillance and control of many pathogens. The purpose of this scoping review is to identify and characterize the recent literature concerning the application of bacterial pathogen genomics for public health practice and to assess the added value, challenges, and needs related to its implementation from an epidemiologist's perspective.

METHODS

In this scoping review, a systematic PubMed search with forward and backward snowballing was performed to identify manuscripts in English published between January 2015 and September 2018. Included studies had to describe the application of NGS on bacterial isolates within a public health setting. The studied pathogen, year of publication, country, number of isolates, sampling fraction, setting, public health application, study aim, level of implementation, time orientation of the NGS analyses, and key findings were extracted from each study. Due to a large heterogeneity of settings, applications, pathogens, and study measurements, a descriptive narrative synthesis of the eligible studies was performed.

RESULTS

Out of the 275 included articles, 164 were outbreak investigations, 70 focused on strategy-oriented surveillance, and 41 on control-oriented surveillance. Main applications included the use of whole-genome sequencing (WGS) data for (1) source tracing, (2) early outbreak detection, (3) unraveling transmission dynamics, (4) monitoring drug resistance, (5) detecting cross-border transmission events, (6) identifying the emergence of strains with enhanced virulence or zoonotic potential, and (7) assessing the impact of prevention and control programs. The superior resolution over conventional typing methods to infer transmission routes was reported as an added value, as well as the ability to simultaneously characterize the resistome and virulome of the studied pathogen. However, the full potential of pathogen genomics can only be reached through its integration with high-quality contextual data.

CONCLUSIONS

For several pathogens, it is time for a shift from proof-of-concept studies to routine use of WGS during outbreak investigations and surveillance activities. However, some implementation challenges from the epidemiologist's perspective remain, such as data integration, quality of contextual data, sampling strategies, and meaningful interpretations. Interdisciplinary, inter-sectoral, and international collaborations are key for an appropriate genomics-informed surveillance.