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

Highly Sensitive and Specific Detection and Serotyping of Five Prevalent Salmonella Serovars by Multiple Cross-Displacement Amplification

Salmonella is a common cause of foodborne disease worldwide, including Australia. More than 85% of outbreaks of human salmonellosis in Australia were caused by five Salmonella serovars. Rapid, accurate, and sensitive identification of Salmonella serovars is vital for diagnosis and public health surveillance. Recently, an isothermal amplification technique, termed multiple cross-displacement amplification (MCDA), has been employed to detect Salmonella at the species level. Herein, seven MCDA assays were developed and evaluated for rapid detection and differentiation of the five most common Salmonella serovars in Australia: Typhimurium, Enteritidis, Virchow, Saintpaul, and Infantis. MCDA primer sets were designed by targeting seven serovar/lineage-specific gene markers identified through genomic comparisons. The sensitivity and specificity of the seven MCDA assays were evaluated using 79 target strains and 32 nontarget strains. The assays were all highly sensitive and specific to target serovars, with the sensitivity ranging from 92.9% to 100% and the specificity from 93.3% to 100%. The limit of detection of the seven MCDA assays was 50 fg per reaction (10 copies) from pure DNA, and positive results were detected in as little as 8 minutes. These seven MCDA assays offer a rapid, accurate, and sensitive serotyping method. With further validation in clinically relevant conditions, these assays could be used for culture-independent serotyping of common Salmonella serovars directly from clinical samples.

A genoserotyping system for a fast and objective identification of Salmonella serotypes commonly isolated from poultry and pork food sectors in Belgium

Humans are mostly contaminated by Salmonella through the consumption of pork- and poultry-derived food products. Therefore, a strict monitoring of Salmonella serotypes in food-producing animals is needed to limit the transmission of the pathogen to humans. Additionally, Salmonella can lead to economic loss in the food sector. Previously, a genoserotyping method using the MOL-PCR and Luminex technology was developed for the identification of the 6 Salmonella serotypes, and their variants, subjected to an official control in the Belgian food sector. In this study, 3 additional assays using the same technology were developed for the rapid and cost-effective detection of 13 dangerous highly invasive serotypes or other serotypes frequently isolated from the Belgian poultry and pork sector, i.e. Agona, Anatum, Brandenburg, Choleraesuis, Derby, Enteritidis vaccine strains, Gallinarum var. Gallinarum/Pullorum, Livingstone, Mbandaka, Minnesota, Ohio, Rissen and Senftenberg. Moreover, the previously developed first MOL-PCR assay was improved for S. Paratyphi B and serogroup O:3 detection. Finally, a Decision Support System hosted by a web application was created for an automatic and objective interpretation of the Luminex raw data. The 3 new assays and the modifications of the first assay were validated with a 100% accuracy, using 553 Salmonella and non-Salmonella strains in total.

Emergence of a Novel Salmonella enterica Serotype Reading Clonal Group Is Linked to Its Expansion in Commercial Turkey Production, Resulting in Unanticipated Human Illness in North America

Two separate human outbreaks of Salmonella enterica serotype Reading occurred between 2017 and 2019 in the United States and Canada, and both outbreaks were linked to the consumption of raw turkey products. In this study, a comprehensive genomic investigation was conducted to reconstruct the evolutionary history of S. Reading from turkeys and to determine the genomic context of outbreaks involving this infrequently isolated Salmonella serotype. A total of 988 isolates of U.S. origin were examined using whole-genome-based approaches, including current and historical isolates from humans, meat, and live food animals. Broadly, isolates clustered into three major clades, with one apparently highly adapted turkey clade. Within the turkey clade, isolates clustered into three subclades, including an "emergent" clade that contained only isolates dated 2016 or later, with many of the isolates from these outbreaks. Genomic differences were identified between emergent and other turkey subclades, suggesting that the apparent success of currently circulating subclades is, in part, attributable to plasmid acquisitions conferring antimicrobial resistance, gain of phage-like sequences with cargo virulence factors, and mutations in systems that may be involved in beta-glucuronidase activity and resistance towards colicins. U.S. and Canadian outbreak isolates were found interspersed throughout the emergent subclade and the other circulating subclade. The emergence of a novel S Reading turkey subclade, coinciding temporally with expansion in commercial turkey production and with U.S. and Canadian human outbreaks, indicates that emergent strains with higher potential for niche success were likely vertically transferred and rapidly disseminated from a common source.IMPORTANCE Increasingly, outbreak investigations involving foodborne pathogens are difficult due to the interconnectedness of food animal production and distribution, and homogeneous nature of industry integration, necessitating high-resolution genomic investigations to determine their basis. Fortunately, surveillance and whole-genome sequencing, combined with the public availability of these data, enable comprehensive queries to determine underlying causes of such outbreaks. Utilizing this pipeline, it was determined that a novel clone of Salmonella Reading has emerged that coincided with increased abundance in raw turkey products and two outbreaks of human illness in North America. The rapid dissemination of this highly adapted and conserved clone indicates that it was likely obtained from a common source and rapidly disseminated across turkey production. Key genomic changes may have contributed to its apparent continued success in commercial turkeys and ability to cause illness in humans.

Molecular epidemiology of Salmonella Infantis in Europe: insights into the success of the bacterial host and its parasitic pESI-like megaplasmid

Salmonella Infantis is one of the five serovars most frequently causing human salmonellosis in Europe, mainly associated with poultry. A clone harbouring a conjugative plasmid of emerging S. Infantis (pESI)-like megaplasmid, carrying multidrug resistant (MDR) and extended-spectrum beta-lactamases (ESBL) genes, has spread in the Italian broiler chicken industry also causing human illness. This work is aimed at elucidating the molecular epidemiology of S. Infantis and pESI-like in Europe using whole-genome sequencing and bioinformatics analysis, and to investigate the genetic relatedness of S. Infantis clones and pESI-like from animals, meat, feed and humans provided by institutions of nine European countries. Two genotyping approaches were used: chromosome or plasmid SNP-based analysis and the minimum spanning tree (MST) algorithm based on core-genome multilocus sequence typing (cgMLST). The European S. Infantis population appeared heterogeneous, with different genetic clusters defined at core-genome level. However, pESI-like variants present in 64.1 % of the isolates were more genetically homogeneous and capable of infecting different clonal lineages in most of the countries. Two different pESI-like with ESBL genes (n=82) were observed: bla_CTX-M-1-positive in European isolates and bla_CTX-M-65-positive in American isolates (study outgroup). Both variants had toxin-antitoxin systems, resistance genes towards tetracyclines, trimethoprim, sulphonamides and aminoglycosides, heavy metals (merA) and disinfectants (qacEΔ). Worryingly, 66 % of the total isolates studied presented different gyrA chromosomal point mutations associated with (fluoro)quinolone resistance (MIC range 0.125–0.5 mg/L), while 18 % displayed transferable macrolide resistance mediated by mph, mef and erm(B) genes. Proper intervention strategies are needed to prevent further dissemination/transmission of MDR S. Infantis and pESI-like along the food chain in Europe.

Systematic Evaluation of Whole Genome Sequence-Based Predictions of Salmonella Serotype and Antimicrobial Resistance

Whole-genome sequencing (WGS) is used increasingly in public-health laboratories for typing and characterizing foodborne pathogens. To evaluate the performance of existing bioinformatic tools for in silico prediction of antimicrobial resistance (AMR) and serotypes of Salmonella enterica, WGS-based genotype predictions were compared with the results of traditional phenotyping assays. A total of 111 S. enterica isolates recovered from a Canadian baseline study on broiler chicken conducted in 2012-2013 were selected based on phenotypic resistance to 15 different antibiotics and isolates were subjected to WGS. Both SeqSero2 and SISTR accurately determined S. enterica serotypes, with full matches to laboratory results for 87.4 and 89.2% of isolates, respectively, and partial matches for the remaining isolates. Antimicrobial resistance genes (ARGs) were identified using several bioinformatics tools including the Comprehensive Antibiotic Resistance Database – Resistance Gene Identifier (CARD-RGI), Center for Genomic Epidemiology (CGE) ResFinder web tool, Short Read Sequence Typing for Bacterial Pathogens (SRST2 v 0.2.0), and k-mer alignment method (KMA v 1.17). All ARG identification tools had ≥ 99% accuracy for predicting resistance to all antibiotics tested except streptomycin (accuracy 94.6%). Evaluation of ARG detection in assembled versus raw-read WGS data found minimal observable differences that were gene- and coverage- dependent. Where initial phenotypic results indicated isolates were sensitive, yet ARGs were detected, repeat AMR testing corrected discrepancies. All tools failed to find resistance-determining genes for one gentamicin- and two streptomycin-resistant isolates. Further investigation found a single nucleotide polymorphism (SNP) in the nuoF coding region of one of the isolates which may be responsible for the observed streptomycin-resistant phenotype. Overall, WGS-based predictions of AMR and serotype were highly concordant with phenotype determination regardless of computational approach used.

The Not so Good, the Bad and the Ugly: Differential Bacterial Adhesion and Invasion Mediated by Salmonella PagN Allelic Variants

While advances in genomic sequencing have highlighted significant strain variability between and within Salmonella serovars, only a few protein variants have been directly related to evolutionary adaptation for survival, such as host specificity or differential virulence. The current study investigated whether allelic variation of the Salmonella adhesin/invasin PagN influences bacterial interaction with their receptors. The Salmonella enterica, subspecies enterica serovar Typhi (S. Typhi) allelic variant of PagN was found to bind significantly better to different enterocytes as well as to the extracellular matrix protein laminin than did the major Salmonella enterica, subspecies enterica serovar Typhimurium (S. Typhimurium) allele. The two alleles differed at amino acid residues 49 and 109 in two of the four predicted PagN surface loops, and residue substitution analysis revealed that a glutamic acid at residue 49 increased the adhesive and invasive properties of S. Typhi PagN. PagN sequence comparisons from 542 Salmonella strains for six representative S. enterica serovars and S. diarizonae further supported the role of glutamic acid at residues 49 and 109 in optimizing adhesion to cells and laminin, as well as for cell invasion. In summary, this study characterized unique residues in allelic variants of a virulence factor that participates in the colonization and invasive properties of different Salmonella stains, subspecies and serovars.

Genome-based Salmonella serotyping as the new gold standard

Salmonella enterica is the second most reported bacterial cause of food-borne infections in Europe. Therefore molecular surveillance activities based on pathogen subtyping are an important measure of controlling Salmonellosis by public health agencies. In Germany, at the federal level, this work is carried out by the National Reference Center for Salmonella and other Bacterial Enteric Pathogens (NRC). With rise of next generation sequencing techniques, the NRC has introduced whole-genome-based typing methods for S. enterica in 2016. In this study we report on the feasibility of genome-based in silico serotyping in the German setting using raw sequence reads. We found that SeqSero and seven gene MLST showed 98% and 95% concordance, respectively, with classical serotyping for the here evaluated serotypes, including the most common German serotypes S. Enteritidis and S. Typhimurium as well as less frequently found serotypes. The level of concordance increased to >99% when the results of both in silico methods were combined. However, both tools exhibited misidentification of monophasic variants, in particular monophasic S. Typhimurium and therefore need to be fine-tuned for reliable detection of this epidemiologically important variant. We conclude that with adjustments Salmonella genome-based serotyping might become the new gold standard.

Comparative genomic analysis reveals high intra-serovar plasticity within Salmonella Napoli isolated in 2005-2017

BACKGROUND

Salmonella enterica subsp. enterica serovar Napoli (S. Napoli) is among the top serovars causing human infections in Italy, although it is relatively uncommon in other European countries; it is mainly isolated from humans and the environment, but neither the reservoir nor its route of infection are clearly defined. This serovar is characterized by high genomic diversity, and molecular evidences revealed important similarities with typhoidal serovars.

RESULTS

179 S. Napoli genomes as well as 239 genomes of typhoidal and non-typhoidal serovars were analyzed in a comparative genomic study. Phylogenetic analysis and draft genome characterization in terms of Multi Locus Sequence Typing (MLST), plasmid replicons, Salmonella Pathogenicity Islands (SPIs), antimicrobial resistance genes (ARGs), phages, biocide and metal-tolerance genes confirm the high genetic variability of S. Napoli, also revealing a within-serovar phylogenetic structure more complex than previously known. Our work also confirms genomic similarity of S. Napoli to typhoidal serovars (S. Typhi and S. Paratyphi A), with S. Napoli samples clustering primarily according to ST, each being characterized by specific genomic traits. Moreover, two major subclades of S. Napoli can be clearly identified, with ST-474 being biphyletic. All STs span among isolation sources and years of isolation, highlighting the challenge this serovar poses to define its epidemiology and evolution. Altogether, S. Napoli strains carry less SPIs and less ARGs than other non-typhoidal serovars and seldom acquire plasmids. However, we here report the second case of an extended-spectrum β-lactamases (ESBLs) producing S. Napoli strain and the first cases of multidrug resistant (MDR) S. Napoli strains, all isolated from humans.

CONCLUSIONS

Our results provide evidence of genomic plasticity of S. Napoli, highlighting genomic similarity with typhoidal serovars and genomic features typical of non-typhoidal serovars, supporting the possibility of survival in different niches, both enteric and non-enteric. Presence of horizontally acquired ARGs and MDR profiles rises concerns regarding possible selective pressure exerted by human environment on this pathogen.

Prevalence of Salmonella Isolates and Their Distribution Based on Whole-Genome Sequence in a Chicken Slaughterhouse in Jiangsu, China

Salmonella has been known as the most important foodborne pathogen, which can infect humans via consuming contaminated food. Chicken meat has been known as an important vehicle to transmit Salmonella by the food supply chain. This study determined the prevalence, antimicrobial resistance, and genetic characteristics of Salmonella at different chicken slaughtering stages in East China. In total, 114 out of 200 (57%) samples were Salmonella positive, while Salmonella contamination was gradually increasing from the scalding and unhairing stage (17.5%) to the subdividing stage (70%) throughout the slaughtering. Whole-genome sequencing (WGS) was then performed to analyze the serotype, antimicrobial resistance gene profiles, and genetic relationship of all Salmonella isolates. The most common serotypes were S. Kentucky (51/114, 44.7%) and S. Enteritidis (37/114, 32.5%), which were distributed throughout the four slaughtering stages, and were also identified in the corresponding environments. The multilocus sequence typing (MLST) analysis revealed that seven sequence types (STs) were occupied by six different serotypes, respectively. Only S. Kentucky had two STs, ST314 was the predominant ST shared by 50 isolates, while the ST198 has 1 isolate. The antimicrobial resistance gene analysis demonstrated that most of the strains belonging to S. Kentucky (39/51, 76.5%) and S. Indiana (15, 100%) contained over five groups of antimicrobial resistance genes. Based on the core genome analysis, 50 S. Kentucky isolates were genetically identical, indicating that one S. Kentucky strain with the same genetic background was prevalent in the chicken slaughtering line. Although 37 S. Enteritidis isolates only had three different antimicrobial resistance gene profiles, the core genome sequence analysis subtyped these S. Enteritidis isolates into five different clusters, which revealed the diverse genetic background of S. Enteritidis in the slaughterhouse. The antimicrobial resistance phenotypes were consistent with the presence of the corresponding resistance genes of S. Kentucky and S. Enteritidis, including tetA, floR, blaTEM-1B, strA/B, sul1/sul2, and gyrA (D87Y). Our study observed a high prevalence of Salmonella in the chicken slaughter line and identified the slaughtering environment as a main source of causing Salmonella cross-contamination during chicken slaughtering. Further studies will be needed to limit the transmission of Salmonella in the slaughterhouse.

Performance and Accuracy of Four Open-Source Tools for In Silico Serotyping of Salmonella spp. Based on Whole-Genome Short-Read Sequencing Data

We compared the performance of four open-source in silico Salmonella typing tools (SeqSero, SeqSero2, Salmonella In Silico Typing Resource [SISTR], and Metric Oriented Sequence Typer [MOST]) to assess their potential for replacing laboratory serological testing with serovar predictions from whole-genome sequencing data. We conducted a retrospective analysis of 1,624 Salmonella isolates of 72 serovars submitted to the German National Salmonella Reference Laboratory between 1999 and 2019. All isolates are derived from animal and foodstuff origins. We conducted Illumina short-read sequencing and compared the in silico serovar prediction results with the results of routine laboratory serotyping. We found the best-performing in silico serovar prediction tool to be SISTR, with 94% correctly typed isolates, followed by SeqSero2 (87%), SeqSero (81%), and MOST (79%). Furthermore, we found that mapping-based tools like SeqSero and SeqSero2 (allele mode) were more reliable for the prediction of monophasic variants, while sequence type and cluster-based methods like MOST and SISTR (core-genome multilocus sequence type [cgMLST]), showed greater resilience when confronted with GC-biased sequencing data. We showed that the choice of library preparation kit could substantially affect O antigen detection, due to the low GC content of the wzx and wzy genes. Although the accuracy of computational serovar predictions is still not quite on par with traditional serotyping by Salmonella reference laboratories, the command-line tools investigated in this study perform a rapid, efficient, inexpensive, and reproducible analysis, which can be integrated into in-house characterization pipelines. Based on our results, we find SISTR most suitable for automated, routine serotyping for public health surveillance of Salmonella IMPORTANCE Salmonella spp. are important foodborne pathogens. To reduce the number of infected patients, it is essential to understand which subtypes of the bacteria cause disease outbreaks. Traditionally, characterization of Salmonella requires serological testing, a laboratory method by which Salmonella isolates can be classified into over 2,600 distinct subtypes, called serovars. Due to recent advances in whole-genome sequencing, many tools have been developed to replace traditional testing methods with computational analysis of genome sequences. It is crucial to validate that these tools, many already in use for routine surveillance, deliver accurate and reliable serovar information. In this study, we set out to compare which of the currently available open-source command-line tools is most suitable to replace serological testing. A thorough evaluation of the differing computational approaches is highly important to ensure the backward compatibility of serotyping data and to maintain comparability between laboratories.

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.

Development of a Novel mcr-6 to mcr-9 Multiplex PCR and Assessment of mcr-1 to mcr-9 Occurrence in Colistin-Resistant Salmonella enterica Isolates From Environment, Feed, Animals and Food (2011-2018) in Germany

The polymyxin antibiotic colistin has been used in decades for treatment and prevention of infectious diseases in livestock. Nowadays, it is even considered as last-line treatment option for severe human infections caused by multidrug- and carbapenem-resistant Gram-negative bacteria. Therefore, the discovery of plasmid-mediated mobile colistin resistance (mcr) genes raised major public health concern. The aim of our study was to analyze colistin-resistant Salmonella enterica strains from animals, food, feed and the environment collected at the National Reference Laboratory for Salmonella in Germany on the presence of mcr-1 to mcr-9 genes. Altogether 407 colistin-resistant (MIC >2 mg/L) Salmonella isolates received between 2011 and 2018 were selected and screened by PCR using a published mcr-1 to mcr-5 as well as a newly developed mcr-6 to mcr-9 multiplex PCR protocol. 254 of 407 (62.4%) isolates harbored either mcr-1 (n = 175), mcr-4 (n = 53), mcr-5 (n = 18) or mcr-1 and mcr-9 (n = 8). The number of mcr-positive isolates ranged from 19 (2017) to 64 (2012) per year. WGS revealed that none of our isolates harbored the mcr-9.1 gene. Instead, two novel mcr-9 variants were observed, which both were affected by frameshift mutations and are probably non-functional. The mcr-harboring isolates were mainly derived from animals (77.2%) or food (20.1%) and could be assigned to ten different Salmonella serovars. Many of the isolates were multidrug-resistant. Co-occurrence of mcr-1 and AmpC or ESBL genes was observed in eight isolates. Our findings suggest that mcr genes are widely spread among colistin-resistant Salmonella isolates from livestock and food in Germany. Potential transfer of mcr-harboring isolates along the food chain has to be considered critically.

Salmonella serotype assignment by sequencing analysis of intergenic regions of ribosomal RNA operons

Salmonella laboratorial detection is usually carried out by bacteriological culture and serological methods. Salmonella isolates are then classified into more than 2,650 serotypes with different somatic (O) and flagellar (H) antigenic combinations. More recently, DNA analysis methods were developed and applied for the identification of Salmonella serotypes, including intergenic spacer regions (ISRs) that separates DNA-encoding ribosomal subunits (rRNA gene) in Salmonella genomes. The present study aimed to evaluate the nucleotide diversity of the ISRs in 2 rRNA operons (rrnB and rrnH) for the assignment of Salmonella serotypes. A total of 63 Salmonella isolates (bacterial cultures) from 21 serotypes were obtained in the period of 2014 to 2017. DNA was extracted, and PCRs were used to detect the genus Salmonella and 4 important serotypes: Enteritidis, Gallinarum, Heidelberg, and Typhimurium. ISRs of the operons rrnB and rrnH were amplified by PCR and then sequenced. All sequence results were submitted to BLASTn search and were aligned in comparison to 72 Salmonella reference nucleotide sequences. The results demonstrated that 60 (95.2%) samples returned a sequence of the same serotype (determined by the traditional serological procedure) after searching in BLASTn and/or in the alignment with the reference sequences for both operons (rrnB and rrnH). These PCR-sequencing procedures had a general agreement index of 0.792 based on the Kappa analysis, 98.7% sensitivity value, 100% specificity, and 98.4% accuracy. Three different phylogenetic trees were generated from the alignments with the sequences of rrnH, rrnB, and rrnH plus rrnB and isolates clustered in specific branches according to the serotypes.

The EnteroBase user's guide, with case studies on Salmonella transmissions, Yersinia pestis phylogeny, and Escherichia core genomic diversity

EnteroBase is an integrated software environment that supports the identification of global population structures within several bacterial genera that include pathogens. Here, we provide an overview of how EnteroBase works, what it can do, and its future prospects. EnteroBase has currently assembled more than 300,000 genomes from Illumina short reads from Salmonella, Escherichia, Yersinia, Clostridioides, Helicobacter, Vibrio, and Moraxella and genotyped those assemblies by core genome multilocus sequence typing (cgMLST). Hierarchical clustering of cgMLST sequence types allows mapping a new bacterial strain to predefined population structures at multiple levels of resolution within a few hours after uploading its short reads. Case Study 1 illustrates this process for local transmissions of Salmonella enterica serovar Agama between neighboring social groups of badgers and humans. EnteroBase also supports single nucleotide polymorphism (SNP) calls from both genomic assemblies and after extraction from metagenomic sequences, as illustrated by Case Study 2 which summarizes the microevolution of Yersinia pestis over the last 5000 years of pandemic plague. EnteroBase can also provide a global overview of the genomic diversity within an entire genus, as illustrated by Case Study 3, which presents a novel, global overview of the population structure of all of the species, subspecies, and clades within Escherichia.

Detailed Evaluation of Data Analysis Tools for Subtyping of Bacterial Isolates Based on Whole Genome Sequencing: Neisseria meningitidis as a Proof of Concept

Whole genome sequencing is increasingly recognized as the most informative approach for characterization of bacterial isolates. Success of the routine use of this technology in public health laboratories depends on the availability of well-characterized and verified data analysis methods. However, multiple subtyping workflows are now often being used for a single organism, and differences between them are not always well described. Moreover, methodologies for comparison of subtyping workflows, and assessment of their performance are only beginning to emerge. Current work focuses on the detailed comparison of WGS-based subtyping workflows and evaluation of their suitability for the organism and the research context in question. We evaluated the performance of pipelines used for subtyping of Neisseria meningitidis, including the currently widely applied cgMLST approach and different SNP-based methods. In addition, the impact of the use of different tools for detection and filtering of recombinant regions and of different reference genomes were tested. Our benchmarking analysis included both assessment of technical performance of the pipelines and functional comparison of the generated genetic distance matrices and phylogenetic trees. It was carried out using replicate sequencing datasets of high- and low-coverage, consisting mainly of isolates belonging to the clonal complex 269. We demonstrated that cgMLST and some of the SNP-based subtyping workflows showed very good performance characteristics and highly similar genetic distance matrices and phylogenetic trees with isolates belonging to the same clonal complex. However, only two of the tested workflows demonstrated reproducible results for a group of more closely related isolates. Additionally, results of the SNP-based subtyping workflows were to some level dependent on the reference genome used. Interestingly, the use of recombination-filtering software generally reduced the similarity between the gene-by-gene and SNP-based methodologies for subtyping of N. meningitidis. Our study, where N. meningitidis was taken as an example, clearly highlights the need for more benchmarking comparative studies to eventually contribute to a justified use of a specific WGS data analysis workflow within an international public health laboratory context.

Multidrug-Resistant Salmonella enterica Serovar Rissen Clusters Detected in Azores Archipelago, Portugal

Gastrointestinal infections caused by nontyphoidal Salmonella (NTS) remain one of the main causes of foodborne illness worldwide. Within the multiple existing Salmonella enterica serovars, the serovar Rissen is rarely reported, particularly as a cause of human salmonellosis. Between 2015 and 2017, the Portuguese National Reference Laboratory of Gastrointestinal Infections observed an increase in the number of clinical cases caused by multidrug-resistant (MDR) S. enterica serovar Rissen, particularly from the Azores archipelago. In the present study, we analyzed by whole genome sequencing (WGS) all clinical, animal, food, and environmental isolates received up to 2017 in the Portuguese Reference Laboratories. As such, through a wgMLST-based gene-by-gene analysis, we aimed to identify potential epidemiological clusters linking clinical and samples from multiple sources, while gaining insight into the genetic diversity of S. enterica serovar Rissen. We also investigated the genetic basis driving the observed multidrug resistance. By integrating 60 novel genomes with all publicly available serovar Rissen genomes, we observed a low degree of genetic diversity within this serovar. Nevertheless, the majority of Portuguese isolates showed high degree of genetic relatedness and a potential link to pork production. An in-depth analysis of these isolates revealed the existence of two major clusters from the Azores archipelago composed of MDR isolates, most of which were resistant to at least five antimicrobials. Considering the well-known spread of MDR between gastrointestinal bacteria, the identification of MDR circulating clones should constitute an alert to public health authorities. Finally, this study constitutes the starting point for the implementation of the "One Health" approach for Salmonella surveillance in Portugal.

Multiplex ligation reaction based on probe melting curve analysis: a pragmatic approach for the identification of 30 common Salmonella serovars

BACKGROUND

While Salmonella serotyping is of paramount importance for the disease intervention of salmonellosis, a fast and easy-to-operate molecular serotyping solution remains elusive. We have developed a multiplex ligation reaction based on probe melting curve analysis (MLMA) for the identification of 30 common Salmonella serovars.

METHODS

Serovar-specific primers and probes were designed based on a comparison of gene targets (wzx and wzy encoding for somatic antigen biosynthesis; fliC and fljB for flagellar antigens) from 5868 Salmonella genomes. The ssaR gene, a type III secretion system component, was included for the confirmation of Salmonella.

RESULTS

All gene targets were detected and gave expected Tm values during assay evaluation. Cross reactions were not demonstrated between the 30 serovars (n = 211), or with an additional 120 serovars (n = 120) and other Enterobacteriaceae (n = 3). The limit of identification for all targets ranged from using 1.2 ng/μL to 1.56 ng/μL of DNA. The intra- and inter-assay standard deviations and the coefficients of variation were no more than 0.5 °C and less than 1% respectively, indicating high reproducibility. From consecutive outpatient stool samples (n = 3590) collected over a 10-month period at 11 sentinel hospitals in Shenzhen, China, we conducted a multicenter study using the traditional Salmonella identification workflow and the MLMA assay workflow in parallel. From Salmonella isolates (n = 496, 13.8%) derived by both workflows, total agreement (kappa = 1.0) between the MLMA assay and conventional serotyping was demonstrated.

CONCLUSIONS

With an assay time of 2.5 h, this simple assay has shown promising potential to provide rapid and high-throughput identification of Salmonella serovars for clinical and public health laboratories to facilitate timely surveillance of salmonellosis.

Koutsoumanis K, Allende A, Alvarez-Ordóñez A, Bolton D, Bover-Cid S, Chemaly M, Davies R, De Cesare A, Hilbert F, Lindqvist R, Nauta M, Peixe L, Ru G, Simmons M, Skandamis P, Suffredini E, Jenkins C, Malorny B, Ribeiro Duarte AS, Torpdahl M, da Silva Felício MT, Guerra B, Rossi M, Herman L. Whole genome sequencing and metagenomics for outbreak investigation, source attribution and risk assessment of food-borne microorganisms

This Opinion considers the application of whole genome sequencing (WGS) and metagenomics for outbreak investigation, source attribution and risk assessment of food‐borne pathogens. WGS offers the highest level of bacterial strain discrimination for food‐borne outbreak investigation and source‐attribution as well as potential for more precise hazard identification, thereby facilitating more targeted risk assessment and risk management. WGS improves linking of sporadic cases associated with different food products and geographical regions to a point source outbreak and can facilitate epidemiological investigations, allowing also the use of previously sequenced genomes. Source attribution may be favoured by improved identification of transmission pathways, through the integration of spatial‐temporal factors and the detection of multidirectional transmission and pathogen–host interactions. Metagenomics has potential, especially in relation to the detection and characterisation of non‐culturable, difficult‐to‐culture or slow‐growing microorganisms, for tracking of hazard‐related genetic determinants and the dynamic evaluation of the composition and functionality of complex microbial communities. A SWOT analysis is provided on the use of WGS and metagenomics for Salmonella and Shigatoxin‐producing Escherichia coli (STEC) serotyping and the identification of antimicrobial resistance determinants in bacteria. Close agreement between phenotypic and WGS‐based genotyping data has been observed. WGS provides additional information on the nature and localisation of antimicrobial resistance determinants and on their dissemination potential by horizontal gene transfer, as well as on genes relating to virulence and biological fitness. Interoperable data will play a major role in the future use of WGS and metagenomic data. Capacity building based on harmonised, quality controlled operational systems within European laboratories and worldwide is essential for the investigation of cross‐border outbreaks and for the development of international standardised risk assessments of food‐borne microorganisms.

Prevalence and Genetic Analysis of Salmonella enterica from a Cross-Sectional Survey of the New Zealand Egg Production Environment

Epidemiological evidence suggests that Salmonella on New Zealand eggs is not an important pathway for human salmonellosis. However, robust nationally representative data for Salmonella contamination of eggs is not available to support this. To better understand the exposure of New Zealand commercial eggs to Salmonella, a cross-sectional survey collected data on prevalence and serotypes of Salmonella in the feed, laying sheds (feces, dust, and boot or manure belt swabs), and packhouses (egg contact surfaces) of New Zealand commercial egg layer farms. Salmonella was not detected on 16 of 28 surveyed farms, and 4 farms had only one positive sample. Of the 43 (13.3%) of 323 Salmonella-positive samples, dust samples had the highest prevalence (19 of 67, 28.4%), followed by boot or manure belt swabs (11 of 67, 16.4%), feces (7 of 67, 10.4%), packhouse egg contact surfaces (5 of 87, 5.7%), and feed (1 of 33, 3.0%). A significantly higher prevalence was from caged (33 of 75, 44.0%; P < 0.001) compared with cage-free (4 of 126, 3.2%) systems, yet multiple practices differ between laying systems, which could influence prevalence. Salmonella-positive packhouse samples were only identified on the three farms with the highest laying shed prevalence, and isolates were genetically related (as determined by single nucleotide polymorphism analyses) suggesting cross-contamination between the laying shed and packhouse surfaces. Serotypes isolated included Salmonella Infantis, Salmonella Thompson, Salmonella Typhimurium, Salmonella Anatum, and Salmonella Mbandaka. Importantly, Salmonella Enteritidis, which causes egg-associated outbreaks internationally, was not isolated. Genomic comparisons of isolates supported the presence of a common contamination source in the shed and farm environments rather than multiple sporadic contamination events. This survey establishes a benchmark of Salmonella prevalence and types in the New Zealand egg production environment and provides a reference point for assessing the impact of changes to practices on Salmonella prevalence.

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.

Development of a multi-locus typing scheme for an Enterobacteriaceae linear plasmid that mediates inter-species transfer of flagella

Due to the public health importance of flagellar genes for typing, it is important to understand mechanisms that could alter their expression or presence. Phenotypic novelty in flagellar genes arise predominately through accumulation of mutations but horizontal transfer is known to occur. A linear plasmid termed pBSSB1 previously identified in Salmonella Typhi, was found to encode a flagellar operon that can mediate phase variation, which results in the rare z66 flagella phenotype. The identification and tracking of homologs of pBSSB1 is limited because it falls outside the normal replicon typing schemes for plasmids. Here we report the generation of nine new pBSSB1-family sequences using Illumina and Nanopore sequence data. Homologs of pBSSB1 were identified in 154 genomes representing 25 distinct serotypes from 67,758 Salmonella public genomes. Pangenome analysis of pBSSB1-family contigs was performed using roary and we identified three core genes amenable to a minimal pMLST scheme. Population structure analysis based on the newly developed pMLST scheme identified three major lineages representing 35 sequence types, and the distribution of these sequence types was found to span multiple serovars across the globe. This in silico pMLST scheme has shown utility in tracking and subtyping pBSSB1-family plasmids and it has been incorporated into the plasmid MLST database under the name “pBSSB1-family”.

SeqSero2: Rapid and Improved Salmonella Serotype Determination Using Whole-Genome Sequencing Data

SeqSero, launched in 2015, is a software tool for Salmonella serotype determination from whole-genome sequencing (WGS) data. Despite its routine use in public health and food safety laboratories in the United States and other countries, the original SeqSero pipeline is relatively slow (minutes per genome using sequencing reads), is not optimized for draft genome assemblies, and may assign multiple serotypes for a strain. Here, we present SeqSero2 (github.com/denglab/SeqSero2; denglab.info/SeqSero2), an algorithmic transformation and functional update of the original SeqSero. Major improvements include (i) additional sequence markers for identification of Salmonella species and subspecies and certain serotypes, (ii) a k-mer based algorithm for rapid serotype prediction from raw reads (seconds per genome) and improved serotype prediction from assemblies, and (iii) a targeted assembly approach for specific retrieval of serotype determinants from WGS for serotype prediction, new allele discovery, and prediction troubleshooting. Evaluated using 5,794 genomes representing 364 common U.S. serotypes, including 2,280 human isolates of 117 serotypes from the National Antimicrobial Resistance Monitoring System, SeqSero2 is up to 50 times faster than the original SeqSero while maintaining equivalent accuracy for raw reads and substantially improving accuracy for assemblies. SeqSero2 further suggested that 3% of the tested genomes contained reads from multiple serotypes, indicating a use for contamination detection. In addition to short reads, SeqSero2 demonstrated potential for accurate and rapid serotype prediction directly from long nanopore reads despite base call errors. Testing of 40 nanopore-sequenced genomes of 17 serotypes yielded a single H antigen misidentification.IMPORTANCE Serotyping is the basis of public health surveillance of Salmonella It remains a first-line subtyping method even as surveillance continues to be transformed by whole-genome sequencing. SeqSero allows the integration of Salmonella serotyping into a whole-genome-sequencing-based laboratory workflow while maintaining continuity with the classic serotyping scheme. SeqSero2, informed by extensive testing and application of SeqSero in the United States and other countries, incorporates important improvements and updates that further strengthen its application in routine and large-scale surveillance of Salmonella by whole-genome sequencing.

Salmonella Serotyping; Comparison of the Traditional Method to a Microarray-Based Method and an in silico Platform Using Whole Genome Sequencing Data

Salmonella is one of the most common causes of food-borne diseases worldwide. While Salmonella molecular subtyping by Whole Genome Sequencing (WGS) is increasingly used for outbreak and source tracking investigations, serotyping remains as a first-line characterization of Salmonella isolates. The traditional phenotypic method for serotyping is logistically challenging, as it requires the use of more than 150 specific antisera and well trained personnel to interpret the results. Consequently, it is not a routine method for the majority of laboratories. Several rapid molecular methods targeting O and H loci or surrogate genomic markers have been developed as alternative solutions. With the expansion of WGS, in silico Salmonella serotype prediction using WGS data is available. Here, we compared a microarray method using molecular markers, the Check and Trace Salmonella assay (CTS) and a WGS-based serotype prediction tool that targets molecular determinants of serotype (SeqSero) to the traditional phenotypic method using 100 strains representing 45 common and uncommon serotypes. Compared to the traditional method, the CTS assay correctly serotyped 97% of the strains, four strains gave a double serotype prediction. Among the inconclusive data, one strain was not predicted and two strains were incorrectly identified. SeqSero was evaluated with two versions (SeqSero 1 and the alpha test version of SeqSero 2). The correct antigenic formula was predicted by SeqSero 1 for 96 and 95% of strains using raw reads and assembly, respectively. However, 34 and 33% of these predictions included multiple serotypes by raw reads and assembly. With raw reads, one strain was not identified and three strains were discordant with phenotypic serotyping result. With assembly, three strains were not predicted and two strains were incorrectly predicted. While still under development, SeqSero 2 maintained the accuracy of antigenic formula prediction at 98% and reduced multiple serotype prediction rate to 13%. One strain had no prediction and one strain was incorrectly predicted. Our study indicates that the CTS assay is a good alternative for routine laboratories as it is an easy to use method with a short turn-around-time. SeqSero is a reliable replacement for phenotypic serotyping if WGS is routinely implemented.

Genetic and metabolic signatures of Salmonella enterica subsp. enterica associated with animal sources at the pangenomic scale

BACKGROUND

Salmonella enterica subsp. enterica is a public health issue related to food safety, and its adaptation to animal sources remains poorly described at the pangenome scale. Firstly, serovars presenting potential mono- and multi-animal sources were selected from a curated and synthetized subset of Enterobase. The corresponding sequencing reads were downloaded from the European Nucleotide Archive (ENA) providing a balanced dataset of 440 Salmonella genomes in terms of serovars and sources (i). Secondly, the coregenome variants and accessory genes were detected (ii). Thirdly, single nucleotide polymorphisms and small insertions/deletions from the coregenome, as well as the accessory genes were associated to animal sources based on a microbial Genome Wide Association Study (GWAS) integrating an advanced correction of the population structure (iii). Lastly, a Gene Ontology Enrichment Analysis (GOEA) was applied to emphasize metabolic pathways mainly impacted by the pangenomic mutations associated to animal sources (iv).

RESULTS

Based on a genome dataset including Salmonella serovars from mono- and multi-animal sources (i), 19,130 accessory genes and 178,351 coregenome variants were identified (ii). Among these pangenomic mutations, 52 genomic signatures (iii) and 9 over-enriched metabolic signatures (iv) were associated to avian, bovine, swine and fish sources by GWAS and GOEA, respectively.

CONCLUSIONS

Our results suggest that the genetic and metabolic determinants of Salmonella adaptation to animal sources may have been driven by the natural feeding environment of the animal, distinct livestock diets modified by human, environmental stimuli, physiological properties of the animal itself, and work habits for health protection of livestock.

Evaluation of a Bead-Based Salmonella Molecular Serotyping Method for Salmonella Isolated from Food and Environmental Samples

Salmonella is a leading cause of foodborne illness worldwide, and foods containing Salmonella (except raw meat and poultry products) are considered adulterated. Serotyping of Salmonella is an essential part of surveillance and investigation of outbreaks. This study evaluated a bead-based Salmonella molecular serotyping (SMS) method, which included the O-group 1, H-antigen, alternate target, and O-group 2 assays, compared with traditional serotyping. Salmonella was isolated from food, pet food, and environmental samples or were reference strains. A total of 572 isolates were analyzed by using two formats of the SMS method in comparison with traditional methods: 485 were analyzed by using Radix SMS (a custom user-mixed format), 218 were analyzed by using Luminex SMS (a commercial kit format), and 131 of the total isolates were analyzed by both formats for comparison. The SMS method was evaluated on the basis of the successful identification of antigens by the probes included in the method. The method identified 550 (96.2%) isolates as expected, 6 (1.0%) isolates were not identified as initially expected but were shown to be correctly identified by SMS after reanalysis by traditional serotyping, and 16 (2.8%) isolates not identified as expected possessed an antigen that should have been detected by the method but was not. Among the isolates considered correctly identified, 255 (44.6%) were identified to a single serovar, 44 (7.7%) required additional biochemical testing to differentiate variants or subspecies, and 251 (43.9%) were partially serotyped because probes for some antigens were not in the assay or had allelic variation for known serovars. Whole genome sequencing, SeqSero, and the Salmonella In Silico Typing Resource gave added confirmation for three isolates. Addition of the O-group 2 assay enabled the identification of 55 (9.6%) of 572 isolates. The SMS method could fully or partially serotype most isolates within a day. The SMS method should be a valuable tool when faster screening methods are needed, such as outbreaks and screening large numbers of environmental isolates.

Genome Analysis and Multiplex PCR Method for the Molecular Detection of Coresistance to Cephalosporins and Fosfomycin in Salmonella enterica Serovar Heidelberg

Heidelberg is among the top three Salmonella enterica serovars associated with human foodborne illness in Canada. Traditional culture and antimicrobial susceptibility testing techniques can be time-consuming to identify Salmonella Heidelberg resistant to cephalosporins and fosfomycin. Rapid and accurate detection of such antibiotic-resistant Salmonella Heidelberg isolates is essential to adopt appropriate control measures. In this study, 15 Salmonella Heidelberg strains isolated from feces of Canadian broiler chickens were characterized by whole genome sequencing. Salmonella Heidelberg genomes had an average coverage of greater than 80-fold, an average of 4,761 protein-coding genes, and all belonged to multilocus sequence type ST15. Genome sequences were compared with genomes in the National Center for Biotechnology Information Pathogen Detection database ( www.ncbi.nlm.nih.gov/pathogens/ ), including human outbreak isolates. The Canadian broiler isolates clustered with chicken isolates from the United States and an equine clinical isolate from Ontario, Canada. In agreement with their antimicrobial resistance phenotypes, several chromosomally encoded specific antimicrobial resistance genes including fosA7 and multidrug resistance efflux pump determinants were detected. An AmpC-like β-lactamase gene, bla_CMY-2, linked with a quaternary ammonium compound resistance gene, sugE, on a replicon type IncI1 plasmid was detected in all 15 broiler Salmonella Heidelberg isolates. Of the 205,031 published Salmonella genomes screened in silico, 4,954 (2.4%) contained bla_CMY-2, 8,143 (4.0%) contained fosA7, and 919 (0.4%) contained both resistance genes. The combination of both resistance genes (fosA7 and bla_CMY-2) was detected in 64% of the Heidelberg genomes and in a small proportion of various other serovars. A PCR method was developed to detect Salmonella Heidelberg in pure culture and chicken feces based on specific primers targeting genes conferring fosfomycin (fosA7) and third-generation cephalosporin (bla_CMY-2) resistance as well as the Salmonella-specific invA gene and the universal 16S rRNA genes. The PCR assay was specific and sensitive for bla_CMY-2 and fosA7 harboring Salmonella Heidelberg. However, some other Salmonella serovars containing these two resistance genes could also be detected by the developed PCR method.

First complete genome sequence and comparative analysis of Salmonella enterica subsp. diarizonae serovar 61:k:1,5,(7) indicates host adaptation traits to sheep

Background

The Salmonella enterica subsp. diarizonae serovar 61:k:1,5,(7) (SASd) has been found to be host-adapted to sheep, with a high prevalence in sheep herds worldwide. Infections are usually sub-clinical, however the serovar has the potential to cause diarrhea, abortions and chronic proliferative rhinitis. Although occurrence and significance of SASd infections in sheep have been extensively studied, the genetic mechanism underlying this unusual host-adaptation have remained unknown, due to a lack of (a) available high-quality genome sequence(s).

Results

We utilized Nanopore and Illumina sequencing technologies to generate a de novo assembly of the 4.88-Mbp complete genome sequence of the SASd strain 16-SA00356, isolated from the organs of a deceased sheep in 2016. We annotated and analyzed the genome sequence with the aim to gain a deeper understanding of the genome characteristics associated with its pathogenicity and host adaptation to sheep. Overall, we found a number of interesting genomic features such as several prophage regions, a VirB4/D4 plasmid and novel genomic islands. By comparing the genome of 16-SA00356 to other S. enterica serovars we found that SASd features an increased number of pseudogenes as well as a high level of genomic rearrangements, both known indicators of host-adaptation.

Conclusions

With this sequence, we provide the first complete and closed genome sequence of a SASd strain. With this study, we provide an important basis for an understanding of the genetic mechanism that underlie pathogenicity and host adaptation of SASd to sheep.

Identification of Primary Antimicrobial Resistance Drivers in Agricultural Nontyphoidal Salmonella enterica Serovars by Using Machine Learning

Nontyphoidal Salmonella (NTS) is a leading global cause of bacterial foodborne morbidity and mortality. Our ability to treat severe NTS infections has been impaired by increasing antimicrobial resistance (AMR). To understand and mitigate the global health crisis AMR represents, we need to link the observed resistance phenotypes with their underlying genomic mechanisms. Broiler chickens represent a key reservoir and vector for NTS infections, but isolates from this setting have been characterized in only very low numbers relative to clinical isolates. In this study, we sequenced and assembled 97 genomes encompassing 7 serotypes isolated from broiler chicken in farms in British Columbia between 2005 and 2008. Through application of machine learning (ML) models to predict the observed AMR phenotype from this genomic data, we were able to generate highly (0.92 to 0.99) precise logistic regression models using known AMR gene annotations as features for 7 antibiotics (amoxicillin-clavulanic acid, ampicillin, cefoxitin, ceftiofur, ceftriaxone, streptomycin, and tetracycline). Similarly, we also trained "reference-free" k-mer-based set-covering machine phenotypic prediction models (0.91 to 1.0 precision) for these antibiotics. By combining the inferred k-mers and logistic regression weights, we identified the primary drivers of AMR for the 7 studied antibiotics in these isolates. With our research representing one of the largest studies of a diverse set of NTS isolates from broiler chicken, we can thus confirm that the AmpC-like CMY-2 β-lactamase is a primary driver of β-lactam resistance and that the phosphotransferases APH(6)-Id and APH(3″-Ib) are the principal drivers of streptomycin resistance in this important ecosystem.IMPORTANCE Antimicrobial resistance (AMR) represents an existential threat to the function of modern medicine. Genomics and machine learning methods are being increasingly used to analyze and predict AMR. This type of surveillance is very important to try to reduce the impact of AMR. Machine learning models are typically trained using genomic data, but the aspects of the genomes that they use to make predictions are rarely analyzed. In this work, we showed how, by using different types of machine learning models and performing this analysis, it is possible to identify the key genes underlying AMR in nontyphoidal Salmonella (NTS). NTS is among the leading cause of foodborne illness globally; however, AMR in NTS has not been heavily studied within the food chain itself. Therefore, in this work we performed a broad-scale analysis of the AMR in NTS isolates from commercial chicken farms and identified some priority AMR genes for surveillance.

Geography Shapes the Population Genomics of Salmonella enterica Dublin

Salmonella enterica serotype Dublin (S. Dublin) is a bovine-adapted serotype that can cause serious systemic infections in humans. Despite the increasing prevalence of human infections and the negative impact on agricultural processes, little is known about the population structure of the serotype. To this end, we compiled a manually curated data set comprising of 880 S. Dublin genomes. Core genome phylogeny and ancestral state reconstruction revealed that region-specific clades dominate the global population structure of S. Dublin. Strains of S. Dublin in the UK are genomically distinct from US, Brazilian, and African strains. The geographical partitioning impacts the composition of the core genome as well as the ancillary genome. Antibiotic resistance genes are almost exclusively found in US genomes and are mediated by an IncA/C2 plasmid. Phage content and the S. Dublin virulence plasmid were strongly conserved in the serotype. Comparison of S. Dublin to a closely related serotype, S. enterica serotype Enteritidis, revealed that S. Dublin contains 82 serotype specific genes that are not found in S. Enteritidis. Said genes encode metabolic functions involved in the uptake and catabolism of carbohydrates and virulence genes associated with type VI secretion systems and fimbria assembly respectively.

Changes detected in the genome sequences of Escherichia coli, Listeria monocytogenes, Vibrio parahaemolyticus, and Salmonella enterica after serial subculturing

Whole genome sequencing (WGS) is rapidly replacing other molecular techniques for identifying and subtyping bacterial isolates. The resolution or discrimination offered by WGS is significantly higher than that offered by other molecular techniques, and WGS readily allows infrequent differences that occur between 2 closely related strains to be found. In this investigation, WGS was used to identify the changes that occurred in the genomes of 13 strains of bacterial foodborne pathogens after 100 serial subcultures. Pure cultures of Shiga-toxin-producing Escherichia coli, Salmonella enterica, Listeria monocytogenes, and Vibrio parahaemolyticus were subcultured daily for 100 successive days. The 1st and 100th subcultures were whole-genome sequenced using short-read sequencing. Single nucleotide polymorphisms (SNPs) were identified between the 1st and final culture using 2 different approaches, and multilocus sequence typing of the whole genome was also performed to detect any changes at the allelic level. The number of observed genomic changes varied by strain, species, and the SNP caller used. This study provides insight into the genomic variation that can be detected using next-generation sequencing and analysis methods after repeated subculturing of 4 important bacterial pathogens.

The ADP-Ribosylating Toxins of Salmonella

A number of pathogenic bacteria utilize toxins to mediate disease in a susceptible host. The foodborne pathogen Salmonella is one of the most important and well-studied bacterial pathogens. Recently, whole genome sequence characterizations revealed the presence of multiple novel ADP-ribosylating toxins encoded by a variety of Salmonella serovars. In this review, we discuss both the classical (SpvB) and novel (typhoid toxin, ArtAB, and SboC/SeoC) ADP-ribosylating toxins of Salmonella, including the structure and function of these toxins and our current understanding of their contributions to virulence.

Assessment and Comparison of Molecular Subtyping and Characterization Methods for Salmonella

The food industry is facing a major transition regarding methods for confirmation, characterization, and subtyping of Salmonella. Whole-genome sequencing (WGS) is rapidly becoming both the method of choice and the gold standard for Salmonella subtyping; however, routine use of WGS by the food industry is often not feasible due to cost constraints or the need for rapid results. To facilitate selection of subtyping methods by the food industry, we present: (i) a comparison between classical serotyping and selected widely used molecular-based subtyping methods including pulsed-field gel electrophoresis, multilocus sequence typing, and WGS (including WGS-based serovar prediction) and (ii) a scoring system to evaluate and compare Salmonella subtyping assays. This literature-based assessment supports the superior discriminatory power of WGS for source tracking and root cause elimination in food safety incident; however, circumstances in which use of other subtyping methods may be warranted were also identified. This review provides practical guidance for the food industry and presents a starting point for further comparative evaluation of Salmonella characterization and subtyping methods.

Embracing Diversity: Differences in Virulence Mechanisms, Disease Severity, and Host Adaptations Contribute to the Success of Nontyphoidal Salmonella as a Foodborne Pathogen

Not all Salmonella enterica serovars cause the same disease. S. enterica represents an incredibly diverse species comprising >2,600 unique serovars. While some S. enterica serovars are host-restricted, others infect a wide range of hosts. The diseases that nontyphoidal Salmonella (NTS) serovars cause vary considerably, with some serovars being significantly more likely to cause invasive disease in humans than others. Furthermore, while genomic analyses have advanced our understanding of the genetic diversity of these serovars, they have not been able to fully account for the observed clinical differences. One overarching challenge is that much of what is known about Salmonella's general biology and virulence strategies is concluded from studies examining a select few serovars, especially serovar Typhimurium. As targeted control strategies have been implemented to control select serovars, an increasing number of foodborne outbreaks involving serovars that are less frequently associated with human clinical illness are being detected. Harnessing what is known about the diversity of NTS serovars represents an important factor in achieving the ultimate goal of reducing salmonellosis-associated morbidity and mortality worldwide. In this review we summarize the current understanding of the differences and similarities among NTS serovars, highlighting the virulence mechanisms, genetic differences, and sources that characterize S. enterica diversity and contribute to its success as a foodborne pathogen.

Performance of neural network basecalling tools for Oxford Nanopore sequencing

Background

Basecalling, the computational process of translating raw electrical signal to nucleotide sequence, is of critical importance to the sequencing platforms produced by Oxford Nanopore Technologies (ONT). Here, we examine the performance of different basecalling tools, looking at accuracy at the level of bases within individual reads and at majority-rule consensus basecalls in an assembly. We also investigate some additional aspects of basecalling: training using a taxon-specific dataset, using a larger neural network model and improving consensus basecalls in an assembly by additional signal-level analysis with Nanopolish.

Results

Training basecallers on taxon-specific data results in a significant boost in consensus accuracy, mostly due to the reduction of errors in methylation motifs. A larger neural network is able to improve both read and consensus accuracy, but at a cost to speed. Improving consensus sequences (‘polishing’) with Nanopolish somewhat negates the accuracy differences in basecallers, but pre-polish accuracy does have an effect on post-polish accuracy.

Conclusions

Basecalling accuracy has seen significant improvements over the last 2 years. The current version of ONT’s Guppy basecaller performs well overall, with good accuracy and fast performance. If higher accuracy is required, users should consider producing a custom model using a larger neural network and/or training data from the same species.

Electronic supplementary material

The online version of this article (10.1186/s13059-019-1727-y) contains supplementary material, which is available to authorized users.

Performance of neural network basecalling tools for Oxford Nanopore sequencing

BACKGROUND

Basecalling, the computational process of translating raw electrical signal to nucleotide sequence, is of critical importance to the sequencing platforms produced by Oxford Nanopore Technologies (ONT). Here, we examine the performance of different basecalling tools, looking at accuracy at the level of bases within individual reads and at majority-rule consensus basecalls in an assembly. We also investigate some additional aspects of basecalling: training using a taxon-specific dataset, using a larger neural network model and improving consensus basecalls in an assembly by additional signal-level analysis with Nanopolish.

RESULTS

Training basecallers on taxon-specific data results in a significant boost in consensus accuracy, mostly due to the reduction of errors in methylation motifs. A larger neural network is able to improve both read and consensus accuracy, but at a cost to speed. Improving consensus sequences ('polishing') with Nanopolish somewhat negates the accuracy differences in basecallers, but pre-polish accuracy does have an effect on post-polish accuracy.

CONCLUSIONS

Basecalling accuracy has seen significant improvements over the last 2 years. The current version of ONT's Guppy basecaller performs well overall, with good accuracy and fast performance. If higher accuracy is required, users should consider producing a custom model using a larger neural network and/or training data from the same species.

Phylogenomic Investigation of IncI1-Iγ Plasmids Harboring bla CMY-2 and bla SHV-12 in Salmonella enterica and Escherichia coli in Multiple Countries

The objective of this study was to elucidate the genetic and evolutionary relatedness of bla _CMY-2- and bla _SHV-12-carrying IncI1-Iγ plasmids. Phylogenomic analysis based on core genome alignments and gene presence/absence was performed for different IncI1-Iγ sequence types (STs). Most IncI1-Iγ/ST12 and IncI1-Iγ/ST231 plasmids had near-identical core genomes. The data suggest that widely occurring bla _CMY-2-carrying IncI1-Iγ/ST12 plasmids originate from a common ancestor. In contrast, bla _SHV-12 was inserted independently into different IncI1-Iγ/ST231-related plasmids.

The diversity, evolution and ecology of Salmonella in venomous snakes

BACKGROUND

Reptile-associated Salmonella bacteria are a major, but often neglected cause of both gastrointestinal and bloodstream infection in humans globally. The diversity of Salmonella enterica has not yet been determined in venomous snakes, however other ectothermic animals have been reported to carry a broad range of Salmonella bacteria. We investigated the prevalence and diversity of Salmonella in a collection of venomous snakes and non-venomous reptiles.

METHODOLOGY/PRINCIPLE FINDINGS

We used a combination of selective enrichment techniques to establish a unique dataset of reptilian isolates to study Salmonella enterica species-level evolution and ecology and used whole-genome sequencing to investigate the relatedness of phylogenetic groups. We observed that 91% of venomous snakes carried Salmonella, and found that a diverse range of serovars (n = 58) were carried by reptiles. The Salmonella serovars belonged to four of the six Salmonella enterica subspecies: diarizonae, enterica, houtanae and salamae. Subspecies enterica isolates were distributed among two distinct phylogenetic clusters, previously described as clade A (52%) and clade B (48%). We identified metabolic differences between S. diarizonae, S. enterica clade A and clade B involving growth on lactose, tartaric acid, dulcitol, myo-inositol and allantoin.

SIGNIFICANCE

We present the first whole genome-based comparative study of the Salmonella bacteria that colonise venomous and non-venomous reptiles and shed new light on Salmonella evolution. Venomous snakes examined in this study carried a broad range of Salmonella, including serovars which have been associated with disease in humans such as S. Enteritidis. The findings raise the possibility that venomous snakes could be a reservoir for Salmonella serovars associated with human salmonellosis.

Genomic Investigation of the Emergence of Invasive Multidrug-Resistant Salmonella enterica Serovar Dublin in Humans and Animals in Canada

Salmonella enterica subsp. enterica serovar Dublin is a zoonotic pathogen that often leads to invasive bloodstream infections in humans that are multidrug resistant. Described here are the results of Canadian national surveillance of S Dublin from 2003 to 2015 in humans and bovines, principally collected through the Canadian Integrated Program for Antibiotic Resistance Surveillance (CIPARS). An increase in human infections due to multidrug-resistant (MDR) S Dublin was observed in 2010, many of which were bloodstream infections. Phylogenomic analysis of human and bovine isolates revealed a closely related network that differed by only 0 to 17 single nucleotide variants (SNVs), suggesting some potential transmission between humans and bovines. Phylogenomic comparison of global publicly available sequences of S Dublin showed that Canadian isolates clustered closely with those from the United States. A high correlation between phenotypic and genotypic antimicrobial susceptibility was observed in Canadian isolates. IS26 replication was widespread among U.S. and Canadian isolates and caused the truncation and inactivation of the resistance genes strA and blaTEM-1B A hybrid virulence and MDR plasmid (pN13-01125) isolated from a Canadian S Dublin isolate was searched against NCBI SRA data of bacteria. The pN13-01125 coding sequences were found in 13 Salmonella serovars, but S Dublin appears to be a specific reservoir. In summary, we have observed the rise of invasive MDR S Dublin in humans in Canada and found that they are closely related to bovine isolates and to American isolates in their mobile and chromosomal contents.

Association of Salmonella virulence factor alleles with intestinal and invasive serovars

BACKGROUND

The role of Salmonella virulence factor (VF) allelic variation in modulating pathogenesis or host specificity has only been demonstrated in a few cases, mostly through serendipitous findings. Virulence factor (VF) alleles from Salmonella enterica subsp. enterica genomes were compared to identify potential associations with the host-adapted invasive serovars Typhi, Dublin, Choleraesuis, and Gallinarum, and with the broad host-range intestinal serovars Typhimurium, Enteritidis, and Newport.

RESULTS

Through a bioinformatics analysis of 500 Salmonella genomes, we have identified allelic variants of 70 VFs, many of which are associated with either one of the four host-adapted invasive Salmonella serovars or one of the three broad host-range intestinal serovars. In addition, associations between specific VF alleles and intra-serovar clusters, sequence types (STs) and/or host-adapted FimH adhesins were identified. Moreover, new allelic VF associations with non-typhoidal S. Enteritidis and S. Typhimurium (NTS) or invasive NTS (iNTS) were detected.

CONCLUSIONS

By analogy to the previously shown association of specific FimH adhesin alleles with optimal binding by host adapted Salmonella serovars, lineages or strains, we predict that some of the identified association of other VF alleles with host-adapted serovars, lineages or strains will reflect specific contributions to host adaptation and/or pathogenesis. The identification of these allelic associations will support investigations of the biological impact of VF alleles and better characterize the role of allelic variation in Salmonella pathogenesis. Most relevant functional experiments will test the potential causal contribution of the detected FimH-associated VF variants in host adapted virulence.

Integrating Whole-Genome Sequencing Data Into Quantitative Risk Assessment of Foodborne Antimicrobial Resistance: A Review of Opportunities and Challenges

Whole-genome sequencing (WGS) will soon replace traditional phenotypic methods for routine testing of foodborne antimicrobial resistance (AMR). WGS is expected to improve AMR surveillance by providing a greater understanding of the transmission of resistant bacteria and AMR genes throughout the food chain, and therefore support risk assessment activities. At this stage, it is unclear how WGS data can be integrated into quantitative microbial risk assessment (QMRA) models and whether their integration will impact final risk estimates or the assessment of risk mitigation measures. This review explores opportunities and challenges of integrating WGS data into QMRA models that follow the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR. We describe how WGS offers an opportunity to enhance the next-generation of foodborne AMR QMRA modeling. Instead of considering all hazard strains as equally likely to cause disease, WGS data can improve hazard identification by focusing on those strains of highest public health relevance. WGS results can be used to stratify hazards into strains with similar genetic profiles that are expected to behave similarly, e.g., in terms of growth, survival, virulence or response to antimicrobial treatment. The QMRA input distributions can be tailored to each strain accordingly, making it possible to capture the variability in the strains of interest while decreasing the uncertainty in the model. WGS also allows for a more meaningful approach to explore genetic similarity among bacterial populations found at successive stages of the food chain, improving the estimation of the probability and magnitude of exposure to AMR hazards at point of consumption. WGS therefore has the potential to substantially improve the utility of foodborne AMR QMRA models. However, some degree of uncertainty remains in relation to the thresholds of genetic similarity to be used, as well as the degree of correlation between genotypic and phenotypic profiles. The latter could be improved using a functional approach based on prediction of microbial behavior from a combination of 'omics' techniques (e.g., transcriptomics, proteomics and metabolomics). We strongly recommend that methodologies to incorporate WGS data in risk assessment be included in any future revision of the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR.

Enhancing the one health initiative by using whole genome sequencing to monitor antimicrobial resistance of animal pathogens: Vet-LIRN collaborative project with veterinary diagnostic laboratories in United States and Canada

BACKGROUND

Antimicrobial resistance (AMR) of bacterial pathogens is an emerging public health threat. This threat extends to pets as it also compromises our ability to treat their infections. Surveillance programs in the United States have traditionally focused on collecting data from food animals, foods, and people. The Veterinary Laboratory Investigation and Response Network (Vet-LIRN), a national network of 45 veterinary diagnostic laboratories, tested the antimicrobial susceptibility of clinically relevant bacterial isolates from animals, with companion animal species represented for the first time in a monitoring program. During 2017, we systematically collected and tested 1968 isolates. To identify genetic determinants associated with AMR and the potential genetic relatedness of animal and human strains, whole genome sequencing (WGS) was performed on 192 isolates: 69 Salmonella enterica (all animal sources), 63 Escherichia coli (dogs), and 60 Staphylococcus pseudintermedius (dogs).

RESULTS

We found that most Salmonella isolates (46/69, 67%) had no known resistance genes. Several isolates from both food and companion animals, however, showed genetic relatedness to isolates from humans. For pathogenic E. coli, no resistance genes were identified in 60% (38/63) of the isolates. Diverse resistance patterns were observed, and one of the isolates had predicted resistance to fluoroquinolones and cephalosporins, important antibiotics in human and veterinary medicine. For S. pseudintermedius, we observed a bimodal distribution of resistance genes, with some isolates having a diverse array of resistance mechanisms, including the mecA gene (19/60, 32%).

CONCLUSION

The findings from this study highlight the critical importance of veterinary diagnostic laboratory data as part of any national antimicrobial resistance surveillance program. The finding of some highly resistant bacteria from companion animals, and the observation of isolates related to those isolated from humans demonstrates the public health significance of incorporating companion animal data into surveillance systems. Vet-LIRN will continue to build the infrastructure to collect the data necessary to perform surveillance of resistant bacteria as part of fulfilling its mission to advance human and animal health. A One Health approach to AMR surveillance programs is crucial and must include data from humans, animals, and environmental sources to be effective.

Clinically Unreported Salmonellosis Outbreak Detected via Comparative Genomic Analysis of Municipal Wastewater Salmonella Isolates

Municipal wastewater includes human waste that contains both commensal and pathogenic enteric microorganisms, and this collective community microbiome can be monitored for community diseases. In a previous study, we assessed the salmonellosis disease burden using municipal wastewater from Honolulu, Hawaii, which was monitored over a 54-week period. During that time, a strain of Salmonella enterica serovar Paratyphi B variant L(+) tartrate(+) (also known as Salmonella enterica serovar Paratyphi B variant Java) was identified; this strain was detected simultaneously with a clinically reported outbreak, and pulsed-field gel electrophoresis patterns were identical for clinical and municipal wastewater isolates. Months after the outbreak subsided, the same pulsotype was detected as the dominant pulsotype in municipal wastewater samples, with no corresponding clinical cases reported. Using genomic characterization (including core single-nucleotide polymorphism alignment, core genome multilocus sequence typing, and screening for virulence and antibiotic resistance genes), all S Java municipal wastewater isolates were determined to be clonal, indicating a resurgence of the original outbreak strain. This demonstrates the feasibility and utility of municipal wastewater surveillance for determining enteric disease outbreaks that may be missed by traditional clinical surveillance methods.IMPORTANCE Underdetection of microbial infectious disease outbreaks in human communities carries enormous health costs and is an ongoing problem in public health monitoring (which relies almost exclusively on data from health clinics). Surveillance of municipal wastewater for community-level monitoring of infectious disease burdens has the potential to fill this information gap, due to its easy access to the mixed community microbiome. In the present study, the genomes of 21 S Java isolates (collected from municipal wastewater in Honolulu) were analyzed; results showed that the same Salmonella strain that caused a known salmonellosis clinical outbreak in spring 2010 remerged as the most dominant strain in municipal wastewater in spring 2011, indicating a new outbreak that was not detected by health clinics. Our results show that wastewater monitoring holds great promise to inform the field of public health regarding outbreak status within communities.

Operational models and criteria for incorporating microbial whole genome sequencing in hospital microbiology - A systematic literature review

BACKGROUND

Microbial whole genome sequencing (WGS) has many advantages over standard microbiological methods. However, it is not yet widely implemented in routine hospital diagnostics due to notable challenges.

OBJECTIVES

The aim was to extract managerial, financial and clinical criteria supporting the decision to implement WGS in routine diagnostic microbiology, across different operational models of implementation in the hospital setting.

METHODS

This was a systematic review of literature identified through PubMed and Web of Science. English literature studies discussing the applications of microbial WGS without limitation on publication date were eligible. A narrative approach for categorization and synthesis of the sources identified was adopted.

RESULTS

A total of 98 sources were included. Four main alternative operational models for incorporating WGS in clinical microbiology laboratories were identified: full in-house sequencing and analysis, full outsourcing of sequencing and analysis and two hybrid models combining in-house/outsourcing of the sequencing and analysis components. Six main criteria (and multiple related sub-criteria) for WGS implementation emerged from our review and included cost (e.g. the availability of resources for capital and operational investment); manpower (e.g. the ability to provide training programmes or recruit trained personnel), laboratory infrastructure (e.g. the availability of supplies and consumables or sequencing platforms), bioinformatics requirements (e.g. the availability of valid analysis tools); computational infrastructure (e.g. the availability of storage space or data safety arrangements); and quality control (e.g. the existence of standardized procedures).

CONCLUSIONS

The decision to incorporate WGS in routine diagnostics involves multiple, sometimes competing, criteria and sub-criteria. Mapping these criteria systematically is an essential stage in developing policies for adoption of this technology, e.g. using a multicriteria decision tool. Future research that will prioritize criteria and sub-criteria that were identified in our review in the context of operational models will inform decision-making at clinical and managerial levels with respect to effective implementation of WGS for routine use. Beyond WGS, similar decision-making challenges are expected with respect to future integration of clinical metagenomics.

Draft Genome Sequences of Four Salmonella enterica subsp. enterica Serovar Gallinarum Strains Isolated from Layer Breeder Flocks in an Outbreak of Fowl Typhoid in Colombia

This report describes the genome sequences of four Salmonella enterica subsp. enterica serovar Gallinarum (Salmonella Gallinarum) strains isolated in Colombia in 2017 from layer breeders of different ages. The layer breeder flocks were presenting with an elevated mortality with lesions typical of fowl typhoid (FT).

This report describes the genome sequences of four Salmonella enterica subsp. enterica serovar Gallinarum (Salmonella Gallinarum) strains isolated in Colombia in 2017 from layer breeders of different ages. The layer breeder flocks were presenting with an elevated mortality with lesions typical of fowl typhoid (FT). These draft genome sequences revealed a highly conserved genome of Salmonella Gallinarum strains circulating in Colombia.

In silico Identification of Serovar-Specific Genes for Salmonella Serotyping

Salmonella enterica subspecies enterica is a highly diverse subspecies with more than 1500 serovars and the ability to distinguish serovars within this group is vital for surveillance. With the development of whole-genome sequencing technology, serovar prediction by traditional serotyping is being replaced by molecular serotyping. Existing in silico serovar prediction approaches utilize surface antigen encoding genes, core genome MLST and serovar-specific gene markers or DNA fragments for serotyping. However, these serovar-specific gene markers or DNA fragments only distinguished a small number of serovars. In this study, we compared 2258 Salmonella accessory genomes to identify 414 candidate serovar-specific or lineage-specific gene markers for 106 serovars which includes 24 polyphyletic serovars and the paraphyletic serovar Enteritidis. A combination of several lineage-specific gene markers can be used for the clear identification of the polyphyletic serovars and the paraphyletic serovar. We designed and evaluated an in silico serovar prediction approach by screening 1089 genomes representing 106 serovars against a set of 131 serovar-specific gene markers. The presence or absence of one or more serovar-specific gene markers was used to predict the serovar of an isolate from genomic data. We show that serovar-specific gene markers have comparable accuracy to other in silico serotyping methods with 84.8% of isolates assigned to the correct serovar with no false positives (FP) and false negatives (FN) and 10.5% of isolates assigned to a small subset of serovars containing the correct serovar with varied FP. Combined, 95.3% of genomes were correctly assigned to a serovar. This approach would be useful as diagnosis moves to culture-independent and metagenomic methods as well as providing a third alternative to confirm other genome-based analyses. The identification of a set of gene markers may also be useful in the development of more cost-effective molecular assays designed to detect specific gene markers of the all major serovars in a region. These assays would be useful in serotyping isolates where cultures are no longer obtained and traditional serotyping is therefore impossible.

Loss and Gain in the Evolution of the Salmonella enterica Serovar Gallinarum Biovar Pullorum Genome

Pullorum disease, an acute poultry septicemia caused by Salmonella Gallinarum biovar Pullorum, is fatal for young chickens and is a heavy burden on poultry industry. The pathogen is rare in most developed countries but still extremely difficult to eliminate in China. Efficient epidemiological surveillance necessitates clarifying the origin of the isolates from different regions and their phylogenic relationships. Genomic epidemiological analysis of 97 S. Pullorum strains was carried out to reconstruct the phylogeny and transmission history of S. Pullorum. Further analysis demonstrated that functional gene loss and acquisition occurred simultaneously throughout the evolution of S. Pullorum, both of which reflected adaptation to the changing environment. The result of our study will be helpful in surveillance and prevention of pullorum disease.

Salmonella enterica subspecies enterica serovar Gallinarum biovar Pullorum (S. Pullorum) is the etiological agent of pullorum disease, causing white diarrhea with high mortality in chickens. There are many unsolved issues surrounding the epidemiology of S. Pullorum, including its origin and transmission history as well as the discordance between its phenotypic heterogeneity and genetic monomorphism. In this paper, we report the results of whole-genome sequencing of a panel of 97 S. Pullorum strains isolated between 1962 and 2014 from four countries across three continents. We utilized 6,795 core genome single nucleotide polymorphisms (SNPs) to reconstruct a phylogenetic tree within a spatiotemporal Bayesian framework, estimating that the most recent common ancestor of S. Pullorum emerged in ∼914 CE (95% confidence interval [95%CI], 565 to 1273 CE). The extant S. Pullorum strains can be divided into four distinct lineages, each of which is significantly associated with geographical distribution. The intercontinental transmissions of lineages III and IV can be traced to the mid-19th century and are probably related to the “Hen Fever” prevalent at that time. Further genomic analysis indicated that the loss or pseudogenization of functional genes involved in metabolism and virulence in S. Pullorum has been ongoing since before and after divergence from the ancestor. In contrast, multiple prophages and plasmids have been acquired by S. Pullorum, and these have endowed it with new characteristics, especially the multidrug resistance conferred by two large plasmids in lineage I. The results of this study provide insight into the evolution of S. Pullorum and prove the efficiency of whole-genome sequencing in epidemiological surveillance of pullorum disease.

IMPORTANCE Pullorum disease, an acute poultry septicemia caused by Salmonella Gallinarum biovar Pullorum, is fatal for young chickens and is a heavy burden on poultry industry. The pathogen is rare in most developed countries but still extremely difficult to eliminate in China. Efficient epidemiological surveillance necessitates clarifying the origin of the isolates from different regions and their phylogenic relationships. Genomic epidemiological analysis of 97 S. Pullorum strains was carried out to reconstruct the phylogeny and transmission history of S. Pullorum. Further analysis demonstrated that functional gene loss and acquisition occurred simultaneously throughout the evolution of S. Pullorum, both of which reflected adaptation to the changing environment. The result of our study will be helpful in surveillance and prevention of pullorum disease.

Circulation of Plasmids Harboring Resistance Genes to Quinolones and/or Extended-Spectrum Cephalosporins in Multiple Salmonella enterica Serotypes from Swine in the United States

Nontyphoidal Salmonella enterica (NTS) poses a major public health risk worldwide that is amplified by the existence of antimicrobial-resistant strains, especially those resistant to quinolones and extended-spectrum cephalosporins (ESC). Little is known on the dissemination of plasmids harboring the acquired genetic determinants that confer resistance to these antimicrobials across NTS serotypes from livestock in the United States. NTS isolates (n = 183) from U.S. swine clinical cases retrieved during 2014 to 2016 were selected for sequencing based on their phenotypic resistance to enrofloxacin (quinolone) or ceftiofur (3rd-generation cephalosporin). De novo assemblies were used to identify chromosomal mutations and acquired antimicrobial resistance genes (AARGs). In addition, plasmids harboring AARGs were identified using short-read assemblies and characterized using a multistep approach that was validated by long-read sequencing. AARGs to quinolones [qnrB15, qnrB19, qnrB2, qnrD, qnrS1, qnrS2, and aac(6')Ib-cr] and ESC (bla _CMY-2, bla _CTX-M-1, bla _CTX-M-27, and bla _SHV-12) were distributed across serotypes and were harbored by several plasmids. In addition, chromosomal mutations associated with resistance to quinolones were identified in the target enzyme and efflux pump regulation genes. The predominant plasmid harboring the prevalent qnrB19 gene was distributed across serotypes. It was identical to a plasmid previously reported in S. enterica serovar Anatum from swine in the United States (GenBank accession number KY991369.1) and similar to Escherichia coli plasmids from humans in South America (GenBank accession numbers GQ374157.1 and JN979787.1). Our findings suggest that plasmids harboring AARGs encoding mechanisms of resistance to critically important antimicrobials are present in multiple NTS serotypes circulating in swine in the United States and can contribute to resistance expansion through horizontal transmission.