Genome-wide identification of geographical segregated genetic markers in Salmonella enterica serovar Typhimurium variant 4,[5],12:i:

Salmonella enterica serovar Braenderup shows clade-specific source associations and a high proportion of molecular epidemiological clustering

Salmonella enterica serovar Braenderup (S. enterica ser. Braenderup) is an important clinical serovar in the United States. This serovar was reported by the CDC in 2017 as the fifth most common Salmonella enterica serovar associated with outbreaks in the United States, which have been linked to both fresh produce and food animal products. The goals of this study were to compare the relatedness of human clinical isolates from southeastern USA (Tennessee (n = 106), Kentucky (n = 48), Virginia (n = 252), South Carolina (n = 109), Georgia (n = 159), Alabama (n = 8), Arkansas (n = 26), and Louisiana (n = 91)) and global clinical (n = 5,153) and nonclinical (n = 1,053) isolates obtained from the NCBI. Additionally, we also examined the population structure of S. enterica ser. Braenderup strains (n = 3,131) on EnteroBase and found that all the strains of this serovar are associated with a single cgMLST eBurst group (ceBG 185), confirming that this serovar is monophyletic. We divided the S. enterica ser. Braenderup population into two clades (Clade I and Clade II) and one clade group (Clade Group III). The composition of distinct environmental isolates in the clades differed: Clade I was significantly associated with produce (90.7%; P < 0.0001) and water, soil, and sediment (76.9%; P < 0.0001), and Clade II was significantly associated with poultry environments (62.8%; P < 0.0001). The clade-specific gene associations (e.g., Clade I-associated competence proteins and cytochrome_c_asm protein and Clade II-associated heme-exporter protein and dimethyl sulfoxide [DMSO] reductase-encoding genes) provide potential insights into possible mechanisms driving environmental adaptation and host-pathogen interaction. Phylogenetic analyses identified 218 molecular epidemiological clusters in the current study, which represented a greater proportion of potentially outbreak-related isolates than previously estimated.

IMPORTANCE

This study provides insights into the genomic diversity of S. enterica ser. Braenderup by revealing distinct clade-specific source attribution patterns and showing that a greater proportion of isolates were associated with epidemiological clusters based on the genomic relatedness than previously estimated. Specifically, we analyzed the diversity of human clinical isolates from southeastern USA and compared them with the global clinical and nonclinical isolates. Our analysis showed different clades of S. enterica ser. Braenderup linked to different environments, providing insights on the potential source of human sporadic infection and outbreaks. These findings can enhance public health surveillance and response strategies targeting S. enterica serovar Braenderup by expanding our understanding of potential transmission pathways and the genomic diversity of clinical and environmental isolates.

Using GWAS and Machine Learning to Identify and Predict Genetic Variants Associated with Foodborne Bacteria Phenotypic Traits

One of the main challenges in food microbiology is to prevent the risk of outbreaks by avoiding the distribution of food contaminated by bacteria. This requires constant monitoring of the circulating strains throughout the food production chain. Bacterial genomes contain signatures of natural evolution and adaptive markers that can be exploited to better understand the behavior of pathogen in the food industry. The monitoring of foodborne strains can therefore be facilitated by the use of these genomic markers capable of rapidly providing essential information on isolated strains, such as the source of contamination, risk of illness, potential for biofilm formation, and tolerance or resistance to biocides. The increasing availability of large genome datasets is enhancing the understanding of the genetic basis of complex traits such as host adaptation, virulence, and persistence. Genome-wide association studies have shown very promising results in the discovery of genomic markers that can be integrated into rapid detection tools. In addition, machine learning has successfully predicted phenotypes and classified important traits. Genome-wide association and machine learning tools have therefore the potential to support decision-making circuits intending at reducing the burden of foodborne diseases. The aim of this chapter review is to provide knowledge on the use of these two methods in food microbiology and to recommend their use in the field.

Genomic diversity of Salmonella Typhimurium and its monophasic variant in pig and pork production in France

Salmonella Typhimurium and its monophasic variant (Salmonella 4,[5],12:i:-) are among the most prevalent serovars worldwide. Even though these serovars have been the focus of many studies, their spread has not yet been investigated in French pig herds and slaughterhouses at a regional scale. Here, we characterized the genomic diversity of 188 Salmonella strains belonging to sequence type (ST) 19 and 34. These strains were isolated from pigs in metropolitan France between 2014 and 2019. Samples were collected from 10 regions, three of which together represent 75% of French pig production in 2020. To contextualize the French Salmonella genomes at a worldwide level, 193 ST 34 genomes from three continents and 14 countries were also included. This study revealed little diversity in ST 34 strains circulating in France, suggesting that one or two clones are spreading within pig herds and slaughterhouses. In silico virulence and antimicrobial resistance genes were investigated to understand the prevalence of these strains among farmed pigs and in the slaughterhouse environment. A comparison with ST 34 isolates from other countries highlighted the genomic specificity of the ST 34 monophasic variants in France, with some exceptions concerning isolates from bordering countries. This work provides new insights into the dynamics of S. Typhimurium and its monophasic variant sampled in French pig herds and slaughterhouses.

IMPORTANCE

Salmonellosis is a leading cause of bacterial infection in humans and animals around the world. This study provides a snapshot of the genomic diversity of one of the most prevalent Salmonella serovars (Salmonella Typhimurium and Salmonella 4,[5],12:i:-) circulating on French pig farms between 2013 and 2021. We investigated the link between geographical and genomic diversity. The analyses revealed little diversity of the strains, suggesting that one or two clones are spreading within French pig herds. We also in silico screened genetic elements that could explain the prevalence of these strains among farmed pigs and in the slaughterhouse environment. Finally, the comparison with isolates from other countries highlighted the genomic specificity of these two French sequence type 34 clones. This work provides new insights into the dynamics of S. Typhimurium and S. 4,[5],12:i:- sampled from pig herds and slaughterhouses in France, thus laying the foundations for future analyses.

Diversity of evolution in MDR monophasic S. Typhimurium among food animals and food products in Southern China from 2011 to 2018

The monophasic variant of Salmonella enterica serovar Typhimurium with the antigenic formula 1,4,[5],12:i:- is one of the most common pathogenic bacteria causing global food-borne outbreaks. However, the research on molecular characteristics and evolution of monophasic S. typhimurium in China is still lacking. In the current study, 59 monophasic S. typhimurium strains were isolated from food animals and food products in South China between 2011 and 2018. A total of 87.5 % of monophasic S. typhimurium isolates were grouped into one independent clade with other monophasic S. typhimurium strains in China distinct from other countries by phylogenomic analysis. These isolates possess variable genotypes, including multiple ARGs on plasmid IncHI2, diverse evolutions at the fljAB locus, and virulence factors. Our results suggest that the monophasic S. typhimurium isolates currently circulating in China might be an independent epidemic subtype.

High diversity of Salmonella spp. from children with diarrhea, food, and environmental sources in Kilimanjaro - Tanzania: one health approach

Salmonella is one of the most frequent causes of diarrhea globally. This study used a One Health approach to identify Salmonella species in children admitted with diarrhea and tested samples from the cases' household environment to investigate their genetic similarity using whole genome sequencing. Surveillance of hospitalized diarrhea cases among children under 5 years was conducted in rural and urban Moshi Districts in the Kilimanjaro Region of Tanzania from July 2020 through November 2022. Household visits were conducted for every child case whose parent/caregiver provided consent. Stool samples, water, domestic animal feces, meat, and milk were collected and tested for Salmonella. Isolates were sequenced on the Illumina NextSeq platform. Multilocus Sequence Typing and phylogenetic analyses were performed to map the genetic relatedness of the isolates. Salmonella was isolated from 72 (6.0%) of 1,191 samples. The prevalence of Salmonella in children with diarrhea, domestic animal feces, food, and water was 2.6% (n = 8/306), 4.6% (n = 8/174), 4.2% (n = 16/382), and 17.3% (n = 39/225), respectively. Four (1.3%) of the 306 enrolled children had a Salmonella positive sample taken from their household. The common sequence types (STs) were ST1208, ST309, ST166, and ST473. Salmonella Newport was shared by a case and a raw milk sample taken from the same household. The study revealed a high diversity of Salmonella spp., however, we detected a Salmonella clone of ST1208 isolated at least from all types of samples. These findings contribute to understanding the epidemiology of Salmonella in the region and provide insight into potential control of foodborne diseases through a One Health approach.

The genomic and epidemiological virulence patterns of Salmonella enterica serovars in the United States

The serovars of Salmonella enterica display dramatic differences in pathogenesis and host preferences. We developed a process (patent pending) for grouping Salmonella isolates and serovars by their public health risk. We collated a curated set of 12,337 S. enterica isolate genomes from human, beef, and bovine sources in the US. After annotating a virulence gene catalog for each isolate, we used unsupervised random forest methods to estimate the proximity (similarity) between isolates based upon the genomic presentation of putative virulence traits We then grouped isolates (virulence clusters) using hierarchical clustering (Ward's method), used non-parametric bootstrapping to assess cluster stability, and externally validated the clusters against epidemiological virulence measures from FoodNet, the National Outbreak Reporting System (NORS), and US federal sampling of beef products. We identified five stable virulence clusters of S. enterica serovars. Cluster 1 (higher virulence) serovars yielded an annual incidence rate of domestically acquired sporadic cases roughly one and a half times higher than the other four clusters combined (Clusters 2-5, lower virulence). Compared to other clusters, cluster 1 also had a higher proportion of infections leading to hospitalization and was implicated in more foodborne and beef-associated outbreaks, despite being isolated at a similar frequency from beef products as other clusters. We also identified subpopulations within 11 serovars. Remarkably, we found S. Infantis and S. Typhimurium subpopulations that significantly differed in genome length and clinical case presentation. Further, we found that the presence of the pESI plasmid accounted for the genome length differences between the S. Infantis subpopulations. Our results show that S. enterica strains associated with highest incidence of human infections share a common virulence repertoire. This work could be updated regularly and used in combination with foodborne surveillance information to prioritize serovars of public health concern.

Tell me if you prefer bovine or poultry sectors and I'll tell you who you are: Characterization of Salmonella enterica subsp. enterica serovar Mbandaka in France

Introduction

In north-western France, Salmonella enterica susp. enterica serovar Mbandaka (S. Mbandaka) is most frequently isolated from bovine and dairy samples. While this serovar most often results in asymptomatic carriage, for a number of years it has caused episodes of abortions, which have serious economic consequences for the sector. Interestingly, this serovar is also isolated from Gallus gallus in the same geographic zone. Despite its prevalence in bovines in north-western France, S. Mbandaka has not been broadly studied at the genomic level, and its prevalence and host adaptation are still not fully understood.

Methods

In this study, we analyzed the genomic diversity of 304 strains of S. Mbandaka isolated from the bovine and poultry sectors in this area over a period of 5 years. A phylogenetic analysis was carried out and two approaches were followed to identify conserved genes and mutations related to host associations. The first approach targeted the genes compiled in the MEGARESv2, Resfinder, VFDB and SPI databases. Plasmid and phage contents were also investigated. The second approach refers to an in-house algorithm developed for this study that computes sensitivity, specificity, and accuracy of accessory genes and core variants according to predefined genomes groups.

Results and discussion

All the analyzed strains belong to the multi-locus sequence type profile ST413, and the phylogenomic analysis revealed main clustering by host (bovine and poultry), emphasizing the circulation of 12 different major clones, of which seven circulate in poultry and five in the bovine sector in France and a likely food production chain adaptation of these clones. All strains present resistance determinants including heavy metals and biocides that could explain the ability of this serovar to survive and persist in the environment, within herds, and in food processing plants. To explore the wild animal contribution to the spread of this serovar in north-western France, we retrieved S. Mbandaka genomes isolated from wild birds from EnteroBase and included them in the phylogenomic analysis together with our collection. Lastly, screening of accessory genes and major variants allowed us to identify conserved specific mutations characteristic of each major cluster. These mutations could be used to design useful probes for food safety surveillance.

Resistome and virulome diversity of foodborne pathogens isolated from artisanal food production chain of animal origin in the Mediterranean region

The aim of the present study was to investigate the resistome and virulome diversity of 43 isolates of Listeria monocytogenes, Salmonella enterica and S. aureus collected from artisanal fermented meat and dairy products and their production environments in Portugal, Spain, Italy and Morocco. After DNA extraction, genomes were sequenced, and de novo assembled. Genetic relationships among genomes were investigated by SNP calling and in silico 7- loci MLST. Genomes of the same species belonged to different ST-types demonstrating the circulation of different clones in in the same artisanal production plant. One specific clone included genomes of S. Paratyphi B belonging to ST43 and repeatedly isolated for more than a year in an artisanal sausage production plant. No genomes but three (belonging to Salmonella enterica), were predicted as multiresistant to different antimicrobials classes. Regarding virulence, genomes of L. monocytogenes belonging to ST1, ST3 and ST489, as well as genomes of S.enterica enterica (ST43, ST33, ST314, ST3667, ST1818, ST198) and ST121 S. aureus were predicted as virulent and hypervirulent. The occurrence of virulent and hypervirulent L. monocytogenes, Salmonella enterica and S. aureus strains in artisanal fermented meat and dairy productions as well as in their finished products suggests the need for a specific focus on prevention and control measures able to reduce the risk of these biological hazards in artisanal food productions.

Evaluation of Antimicrobial Resistance in Salmonella Strains Isolated from Food, Animal and Human Samples between 2017 and 2021 in Southern Italy

Salmonella enterica is one of the most common causes of foodborne infection in the world, and the most common one in Italy. Italy collaborates with the other EU member states to survey the antimicrobial resistance of Salmonella on a large scale. This study on the situation in Apulia and Basilicata provides a more focused point of view on the territory, and anticipates the data reported in future Italian reports. Antimicrobial resistance was detected using the MIC detection method, with EUVSEC® plates, on the strains collected between 2017 and 2021. The results of serotyping showed that Salmonella Infantis is the serovar that has increased the most over time in veterinary samples, while Salmonella Tyhimurium and its monophasic variant are the most isolated in human samples. The results of the antimicrobial resistance study comply with European data, showing high resistance to quinolones, tetracyclines, ampicillin and trimethoprim, and low resistance to colistin and cephems. The significant exception was that all strains were resistant to sulphametoxazole. The presence of MDRs, which was 85% in veterinary and 77.4% in human strains, often included critically important antibiotics, which is a sign that more study and action is needed to manage the use of antibiotics.

Relationship and distribution of Salmonella enterica serovar I 4,[5],12:i:- strain sequences in the NCBI Pathogen Detection database

Background

Of the > 2600 Salmonella serovars, Salmonella enterica serovar I 4,[5],12:i:- (serovar I 4,[5],12:i:-) has emerged as one of the most common causes of human salmonellosis and the most frequent multidrug-resistant (MDR; resistance to ≥3 antimicrobial classes) nontyphoidal Salmonella serovar in the U.S. Serovar I 4,[5],12:i:- isolates have been described globally with resistance to ampicillin, streptomycin, sulfisoxazole, and tetracycline (R-type ASSuT) and an integrative and conjugative element with multi-metal tolerance named Salmonella Genomic Island 4 (SGI-4).

Results

We analyzed 13,612 serovar I 4,[5],12:i:- strain sequences available in the NCBI Pathogen Detection database to determine global distribution, animal sources, presence of SGI-4, occurrence of R-type ASSuT, frequency of antimicrobial resistance (AMR), and potential transmission clusters. Genome sequences for serovar I 4,[5],12:i:- strains represented 30 countries from 5 continents (North America, Europe, Asia, Oceania, and South America), but sequences from the United States (59%) and the United Kingdom (28%) were dominant. The metal tolerance island SGI-4 and the R-type ASSuT were present in 71 and 55% of serovar I 4,[5],12:i:- strain sequences, respectively. Sixty-five percent of strain sequences were MDR which correlates to serovar I 4,[5],12:i:- being the most frequent MDR serovar. The distribution of serovar I 4,[5],12:i:- strain sequences in the NCBI Pathogen Detection database suggests that swine-associated strain sequences were the most frequent food-animal source and were significantly more likely to contain the metal tolerance island SGI-4 and genes for MDR compared to all other animal-associated isolate sequences.

Conclusions

Our study illustrates how analysis of genomic sequences from the NCBI Pathogen Detection database can be utilized to identify the prevalence of genetic features such as antimicrobial resistance, metal tolerance, and virulence genes that may be responsible for the successful emergence of bacterial foodborne pathogens.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08458-z.

Genomic Characterization of Endemic and Ecdemic Non-typhoidal Salmonella enterica Lineages Circulating Among Animals and Animal Products in South Africa

In Africa, the burden of illness caused by non-typhoidal Salmonella enterica is disproportionally high; however, whole-genome sequencing (WGS) efforts are overwhelmingly concentrated in world regions with lower burdens. While WGS is being increasingly employed in South Africa to characterize Salmonella enterica, the bulk of these efforts have centered on characterizing human clinical strains. Thus, very little is known about lineages circulating among animals in the country on a genomic scale. Here, we used WGS to characterize 63 Salmonella enterica strains isolated from livestock, companion animals, wildlife, and animal products in South Africa over a 60-year period. Genomes were assigned to serotypes Dublin, Hadar, Enteritidis, and Typhimurium (n = 18, 8, 13, and 24 strains, respectively) and sequence types (STs) ST10 (all S. Dublin), ST33 (all S. Hadar), ST11/ST366 (n = 12 and 1 S. Enteritidis, respectively), and ST19/ST34 (n = 23 and 1 S. Typhimurium, respectively; via seven-gene multi-locus sequence typing). Within-ST phylogenies were constructed using genomes sequenced in this study, plus publicly available genomes representative of each ST's (i) global (n = 2,802 and 1,569 S. Dublin and Hadar genomes, respectively) and (ii) African (n = 716 and 343 S. Enteritidis and Typhimurium genomes, respectively) population. For S. Dublin ST10, a largely antimicrobial-susceptible, endemic lineage circulating among humans, animals, and food in South Africa was identified, as well as a lineage that was likely recently introduced from the United States. For S. Hadar ST33, multiple South African lineages harboring streptomycin and tetracycline resistance-conferring genes were identified. African S. Enteritidis ST11 could be primarily partitioned into one largely antimicrobial-susceptible and one largely multidrug-resistant (MDR) clade, with South African isolates confined to the largely antimicrobial-susceptible clade. S. Typhimurium ST19/ST34 strains sequenced here were distributed across the African S. Typhimurium ST19/ST34 phylogeny, representing a diverse range of lineages, including numerous MDR lineages. Overall, this study provides critical insights into endemic and ecdemic non-typhoidal Salmonella enterica lineages circulating among animals, foods, and humans in South Africa and showcases the utility of WGS in characterizing animal-associated strains from a world region with a high salmonellosis burden.

Monitoring the Microevolution of Salmonella enterica in Healthy Dairy Cattle Populations at the Individual Farm Level Using Whole-Genome Sequencing

Livestock represent a possible reservoir for facilitating the transmission of the zoonotic foodborne pathogen Salmonella enterica to humans; there is also concern that strains can acquire resistance to antimicrobials in the farm environment. Here, whole-genome sequencing (WGS) was used to characterize Salmonella strains (n = 128) isolated from healthy dairy cattle and their associated environments on 13 New York State farms to assess the diversity and microevolution of this important pathogen at the level of the individual herd. Additionally, the accuracy and concordance of multiple in silico tools are assessed, including: (i) two in silico serotyping tools, (ii) combinations of five antimicrobial resistance (AMR) determinant detection tools and one to five AMR determinant databases, and (iii) one antimicrobial minimum inhibitory concentration (MIC) prediction tool. For the isolates sequenced here, in silico serotyping methods outperformed traditional serotyping and resolved all un-typable and/or ambiguous serotype assignments. Serotypes assigned in silico showed greater congruency with the Salmonella whole-genome phylogeny than traditional serotype assignments, and in silico methods showed high concordance (99% agreement). In silico AMR determinant detection methods additionally showed a high degree of concordance, regardless of the pipeline or database used (≥98% agreement among susceptible/resistant assignments for all pipeline/database combinations). For AMR detection methods that relied exclusively on nucleotide BLAST, accuracy could be maximized by using a range of minimum nucleotide identity and coverage thresholds, with thresholds of 75% nucleotide identity and 50-60% coverage adequate for most pipeline/database combinations. In silico characterization of the microevolution and AMR dynamics of each of six serotype groups (S. Anatum, Cerro, Kentucky, Meleagridis, Newport, Typhimurium/Typhimurium variant Copenhagen) revealed that some lineages were strongly associated with individual farms, while others were distributed across multiple farms. Numerous AMR determinant acquisition and loss events were identified, including the recent acquisition of cephalosporin resistance-conferring bla CMY- and bla CTX-M-type beta-lactamases. The results presented here provide high-resolution insight into the temporal dynamics of AMR Salmonella at the scale of the individual farm and highlight both the strengths and limitations of WGS in tracking zoonotic pathogens and their associated AMR determinants at the livestock-human interface.

The Spatiotemporal Dynamics and Microevolution Events That Favored the Success of the Highly Clonal Multidrug-Resistant Monophasic Salmonella Typhimurium Circulating in Europe

The European epidemic monophasic variant of Salmonella enterica serovar Typhimurium (S. 1,4,[5],12:i:-) characterized by the multi locus sequence type ST34 and the antimicrobial resistance ASSuT profile has become one of the most common serovars in Europe (EU) and the United States (US). In this study, we reconstructed the time-scaled phylogeny and evolution of this Salmonella in Europe. The epidemic S. 1,4,[5],12:i:- ST34 emerged in the 1980s by an acquisition of the Salmonella Genomic Island (SGI)-4 at the 3' end of the phenylalanine phe tRNA locus conferring resistance to copper and arsenic toxicity. Subsequent integration of the Tn21 transposon into the fljAB locus gave resistance to mercury toxicity and several classes of antibiotics used in food-producing animals (ASSuT profile). The second step of the evolution occurred in the 1990s, with the integration of mTmV and mTmV-like prophages carrying the perC and/or sopE genes involved in the ability to reduce nitrates in intestinal contents and facilitate the disruption of the junctions of the host intestinal epithelial cells. Heavy metals are largely used as food supplements or pesticide for cultivation of seeds intended for animal feed so the expansion of the epidemic S. 1,4,[5],12:i:- ST34 was strongly related to the multiple-heavy metal resistance acquired by transposons, integrative and conjugative elements and facilitated by the escape until 2011 from the regulatory actions applied in the control of S. Typhimurium in Europe. The genomic plasticity of the epidemic S. 1,4,[5],12:i:- was demonstrated in our study by the analysis of the plasmidome. We were able to identify plasmids harboring genes mediating resistance to phenicols, colistin, and fluoroquinolone and also describe for the first time in six of the analyzed genomes the presence of two plasmids (pERR1744967-1 and pERR2174855-2) previously described only in strains of enterotoxigenic Escherichia coli and E. fergusonii.

Population structure, case clusters, and genetic lesions associated with Canadian Salmonella 4,[5],12:i:- isolates

Monophasic Salmonella 4,[5]:12:i:- are a major public health problem because they are one of the top five Salmonella serotypes isolated from clinical cases globally and because they can carry resistance to multiple antibiotics. A total of 811 Salmonella 4,[5]:12:i:- and S. Typhimurium whole genome sequences (WGS) were generated. The various genetic lesions causing the Salmonella 4,[5]:12:i:- genotype were identified and assessed with regards to their distribution in the population of 811 Salmonella 4,[5]:12:i:- and S. Typhimurium isolates, their geographical and temporal distribution, and their association with non-human sources. Several clades were identified in the population structure, and the largest two were associated almost exclusively with a short prophage insertion and insertion of a mobile element carrying loci encoding antibiotic and mercury resistance. IS26-mediated deletions and fljB point mutants appeared to spread clonally. 'Inconsistent' Salmonella 4,[5]:12:i:- isolates associated with specific, single amino acid changes in fljA and hin were found in a single clade composed of water, shellfish, and avian isolates. Inclusion of isolates from different case clusters identified previously by PFGE validated some of the clusters and invalidated others. Some wgMLST clusters of clinical isolates composed of very closely related isolates contained an isolate(s) with a different genetic lesion, suggesting continuing mobility of the implicated element responsible. Such cases may need to be left out of epidemiological investigations until sufficient numbers of isolates are included that statistical significance of association with sources is not impaired. Non-human sources were frequently found in or near clinical case clusters. Prospective surveillance and WGS of non-human sources and retrospective analysis by WGS of isolates from existing culture collections provides data critical for epidemiological investigations of food- and waterborne outbreaks.

Whole-genome epidemiology links phage-mediated acquisition of a virulence gene to the clonal expansion of a pandemic Salmonella enterica serovar Typhimurium clone

Epidemic and pandemic clones of bacterial pathogens with distinct characteristics continually emerge, replacing those previously dominant through mechanisms that remain poorly characterized. Here, whole-genome-sequencing-powered epidemiology linked horizontal transfer of a virulence gene, sopE, to the emergence and clonal expansion of a new epidemic Salmonella enterica serovar Typhimurium (S. Typhimurium) clone. The sopE gene is sporadically distributed within the genus Salmonella and rare in S. enterica Typhimurium lineages, but was acquired multiple times during clonal expansion of the currently dominant pandemic monophasic S. Typhimurium sequence type (ST) 34 clone. Ancestral state reconstruction and time-scaled phylogenetic analysis indicated that sopE was not present in the common ancestor of the epidemic clade, but later acquisition resulted in increased clonal expansion of sopE-containing clones that was temporally associated with emergence of the epidemic, consistent with increased fitness. The sopE gene was mainly associated with a temperate bacteriophage mTmV, but recombination with other bacteriophage and apparent horizontal gene transfer of the sopE gene cassette resulted in distribution among at least four mobile genetic elements within the monophasic S. enterica Typhimurium ST34 epidemic clade. The mTmV prophage lysogenic transfer to other S. enterica serovars in vitro was limited, but included the common pig-associated S. enterica Derby (S. Derby). This may explain mTmV in S. Derby co-circulating on farms with monophasic S. Typhimurium ST34, highlighting the potential for further transfer of the sopE virulence gene in nature. We conclude that whole-genome epidemiology pinpoints potential drivers of evolutionary and epidemiological dynamics during pathogen emergence, and identifies targets for subsequent research in epidemiology and bacterial pathogenesis.

Whole-genome sequencing analysis and CRISPR genotyping of rare antibiotic-resistant Salmonella enterica serovars isolated from food and related sources

For decades, Salmonella Typhimurium and Salmonella Enteritidis have prevailed in several countries as agents of salmonellosis outbreaks. In Brazil, the largest exporter of poultry meat, relatively little attention has been paid to infrequent serovars. Here, we report the emergence and characterization of rare serovars isolated from food and related sources collected between 2014 and 2016 in Brazil. Twenty-two Salmonella enterica isolates were analyzed through the use of whole-genome sequencing (WGS) and clustered regularly interspaced short palindromic repeats (CRISPR) genotyping. These isolates were classified into 10 infrequent serovars, including S. Abony, S. Isangi, S. Rochdale, S. Saphra, S. Orion, S. Ouakam, S. Grumpensis, S. Carrau, S. Abaetetuba, and S. Idikan. The presence of six antimicrobial resistance (AMR) genes, qnrB19, bla_CMY-2, tetA, aac(6')-Iaa, sul2 and fosA7, which encode resistance to quinolones, third-generation cephalosporin, tetracycline, aminoglycoside, sulfonamide and fosfomycin, respectively, were confirmed by WGS. All S. Isangi harbored qnrB19 with conserved genomic context across strains, while S. Abony harbored bla_CMY-2. Twelve (54.5%) strains displayed chromosomal mutations in parC (Thr57→Ser). Most serovars were classified as independent lineages, except S. Abony and S. Abaetetuba, which phylogenetically nested with Salmonella strains from different countries. CRISPR analysis revealed that the spacer content was strongly correlated with serovar and multi-locus sequence type for all strains, independently confirming the observed phylogenetic patterns, and highlighting the value of CRISPR-based genotyping for Salmonella. These findings add valuable information to the epidemiology of S. enterica in Brazil, where the emergency of antibiotic-resistant Salmonella continues to evolve.

AB_SA: Accessory genes-Based Source Attribution - tracing the source of Salmonella enterica Typhimurium environmental strains

The partitioning of pathogenic strains isolated in environmental or human cases to their sources is challenging. The pathogens usually colonize multiple animal hosts, including livestock, which contaminate the food-production chain and the environment (e.g. soil and water), posing an additional public-health burden and major challenges in the identification of the source. Genomic data opens up new opportunities for the development of statistical models aiming to indicate the likely source of pathogen contamination. Here, we propose a computationally fast and efficient multinomial logistic regression source-attribution classifier to predict the animal source of bacterial isolates based on 'source-enriched' loci extracted from the accessory-genome profiles of a pangenomic dataset. Depending on the accuracy of the model's self-attribution step, the modeller selects the number of candidate accessory genes that best fit the model for calculating the likelihood of (source) category membership. The Accessory genes-Based Source Attribution (AB_SA) method was applied to a dataset of strains of Salmonella enterica Typhimurium and its monophasic variant (S. enterica 1,4,[5],12:i:-). The model was trained on 69 strains with known animal-source categories (i.e. poultry, ruminant and pig). The AB_SA method helped to identify 8 genes as predictors among the 2802 accessory genes. The self-attribution accuracy was 80 %. The AB_SA model was then able to classify 25 of the 29 S. enterica Typhimurium and S. enterica 1,4,[5],12:i:- isolates collected from the environment (considered to be of unknown source) into a specific category (i.e. animal source), with more than 85 % of probability. The AB_SA method herein described provides a user-friendly and valuable tool for performing source-attribution studies in only a few steps. AB_SA is written in R and freely available at https://github.com/lguillier/AB_SA.

Network Approach to Source Attribution of Salmonella enterica Serovar Typhimurium and Its Monophasic Variant

Salmonella enterica subspecies enterica serovar Typhimurium and its monophasic variant are among the most common Salmonella serovars associated with human salmonellosis each year. Related infections are often due to consumption of contaminated meat of pig, cattle, and poultry origin. In order to evaluate novel microbial subtyping methods for source attribution, an approach based on weighted networks was applied on 141 human and 210 food and animal isolates of pigs, broilers, layers, ducks, and cattle collected in Denmark from 2013 to 2014. A whole-genome SNP calling was performed along with cgMLST and wgMLST. Based on these genomic input data, pairwise distance matrices were built and used as input for construction of a weighted network where nodes represent genomes and links to distances. Analyzing food and animal Typhimurium genomes, the coherence of source clustering ranged from 89 to 90% for animal source, from 84 to 85% for country, and from 63 to 65% for year of isolation and was equal to 82% for serotype, suggesting animal source as the first driver of clustering formation. Adding human isolate genomes to the network, a percentage between 93.6 and 97.2% clustered with the existing component and only a percentage between 2.8 and 6.4% appeared as not attributed to any animal sources. The majority of human genomes were attributed to pigs with probabilities ranging from 83.9 to 84.5%, followed by broilers, ducks, cattle, and layers in descending order. In conclusion, a weighted network approach based on pairwise SNPs, cgMLST, and wgMLST matrices showed promising results for source attribution studies.

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.

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.

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.

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.

Raw meat-based diets for companion animals: a potential source of transmission of pathogenic and antimicrobial-resistant Enterobacteriaceae

Feeding pets raw meat-based diets (RMBDs) has become increasingly popular but may constitute a risk due to the contamination with pathogenic and antimicrobial-resistant (AMR) bacteria. The aim of this study was to evaluate commercially available RMBDs with regard to microbiological quality and occurrence of AMR Enterobacteriaceae. Of 51 RMBD samples, 72.5% did not meet the microbiological standards for Enterobacteriaceae set out by EU regulations for animal by-products intended for pet food. Furthermore, Salmonella was detected in 3.9% of the samples. AMR bacteria were found in 62.7% of the samples, the majority thereof were resistant to third-generation cephalosporins due to the production of extended-spectrum β-lactamases (ESBLs) including CTX-M-1, which is widespread in livestock, and CTX-M-15, which is the most common ESBL variant worldwide. Colistin- and aminoglycoside-resistant isolates, producing MCR-1 and RMTB, were identified in 3.9 and 2% of the samples, respectively. The majority of the AMR Escherichia coli belonged to commensal groups A or B1 and were associated with clonal complexes CC155 and CC10. Two belonged to the emerging extraintestinal pathogenic CC648, and one to the globally disseminated uropathogenic E. coli sequence type ST69, suggesting zoonotic potential. The microbiological quality and the high prevalence of AMR producing Enterobacteriaceae in RMBDs raise concerns for animal and public health.

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.

Current strategy for local- to global-level molecular epidemiological characterisation of global antimicrobial resistance surveillance system pathogens

The prime goal of molecular epidemiology is to identify the origin and evolution of pathogens, which can potentially influence the public health worldwide. Traditional methods provide limited information which is not sufficient for outbreak investigation and studying transmission dynamics. The recent advancement of next-generation sequencing had a major impact on molecular epidemiological studies. Currently, whole-genome sequencing (WGS) has become the gold standard typing method, especially for clinically significant pathogens. Here, we aimed to describe the application of appropriate molecular typing methods for global antimicrobial resistance surveillance system pathogens based on the level of discrimination and epidemiological settings. This shows that sequence-based methods such as multi-locus sequence typing (MLST) are widely used due to cost-effectiveness and database accessibility. However, WGS is the only method of choice for studying Escherichia coli and Shigella spp. WGS is shown to have higher discrimination than other methods in typing Klebsiella pneumoniae, Acinetobacter baumannii and Salmonella spp. due to its changing accessory genome content. For Gram positives such as Streptococcus pneumoniae, WGS would be preferable to understand the evolution of the strains. Similarly, for Staphylococcus aureus, combination of MLST, staphylococcal protein A or SCCmec typing along with WGS could be the choice for epidemiological typing of hospital- and community-acquired strains. This review highlights that combinations of different typing methods should be used to get complete information since no one standalone method is sufficient to study the varying genome diversity.