Editorial: Integrating Whole Genome Sequencing Into Source Attribution and Risk Assessment of Foodborne Bacterial Pathogens

Source attribution and microbial risk assessment have proved to be crucial to identify and prioritize food safety interventions as to effectively control the burden of human illnesses (Cassini et al., 2016; Mughini-Gras et al., 2018a, 2019). By comparing human cases and pathogen occurrences in selected animal, food, and environmental sources, microbial subtyping approaches were successfully applied to pinpoint the most important sources of Salmonella, Campylobacter, Shiga toxin-producing Escherichia coli, and Listeria monocytogenes (Hald et al., 2004; Mullner et al., 2009a,b; Barco et al., 2013; Nielsen et al., 2017; Mughini-Gras et al., 2018b; Cody et al., 2019). Microbial risk assessment has been applied to assess known or potential adverse health effects resulting from human exposure to food-borne hazards. Through a scientific structured approach (FAO and WHO, 2021), microbial risk assessment helps to identify and quantify the risk represented by specific foods and the critical points in these foods' production chains for microbial control (Cassini et al., 2016; FAO and WHO, 2021). For both source attribution and risk assessment, one key challenge has been to define the hazard in question: is the whole foodborne pathogen species a hazard, or only some of its subtypes? In this regard the choice of the subtyping method becomes crucial. In recent years, Whole Genome Sequencing (WGS) has represented a major benefit for more targeted approaches, no longer focused on the species/genus level but at the level of subtypes (Franz et al., 2016; Fritsch et al., 2018; EFSA Panel on Biological Hazards, 2019). Besides WGS, metagenomics showed potentialities in source attribution. In particular, this approach was useful in attributing the source of environmental contamination by comparing the abundances of source-specific genetic markers (i.e., resistome) in different reservoirs (Gupta et al., 2019). Therefore, this special issue focuses on traditional and novel source attribution approaches applied on molecular, WGS, and metagenomic data as well as on a fine-tuning genetic characterization of foodborne pathogens useful for hazard identification and characterization. In particular, one study compares the outputs of a modified Hald model, which was applied to different subtyping input data of S. enterica Typhimurium and its monophasic variant (Arnold et al.) whereas two studies proposed a novel network approach and a method based on the core-genome genetic distance to attribute human infections of S. enterica Typhimurium monophasic variant and S. enterica Derby using WGS as input data (Merlotti et al.; Sévellec et al.). Another study by Duarte et al. included the relative abundance of antimicrobial resistance (AMR) associated genes (resistome) as metagenomic input data in an AMR source attribution study. Finally, two studies were focused on the molecular and genomic characterization of human isolates of Campylobacter jejuni and C. coli from China and of Listeria monocytogenes isolates collected from ready-to-eat meat and processing environment from Poland (Zhang et al.; Kurpas et al.). Arnold et al. performed a source attribution study including the genomes of S. enterica Typhimurium and its monophasic variant of 596 human sources and 327 animal sources from England and Wales between 2014 and 2016. Data from Seven Loci Multi Locus Sequence Typing (7-loci MLST), core-genome MLST (cg-MLST), and SNP calling were compared as input data. By applying a modified Hald model, 60% of human genomes were attributed to pork. Comparing different input data, results highlighted MLST as the method with the lowest fit and the lowest discriminatory power. Merlotti et al. applied a network approach to 351 human and animal genomes of S. enterica Typhimurium and its monophasic variant collected from 2013 to 2014. Three datasets of whole-genome MLST (wgMLST), cgMLST, and SNPs were used as input data. Genomes were clustered based on their genetic similarities. Interestingly, a higher percentage of cluster coherence was reported for animal sources in comparison to country and year of isolation, suggesting animal sources as the major driver of cluster formation. The approach showed to be effective in attributing up to 97.2% of human genomes to animal sources represented in the dataset. Among these genomes, the majority (84%) was attributed to pigs/pork. No significant differences were highlighted by comparing the three different input datasets. Core genome analysis was the approach applied by Sévellec et al. to attribute human sporadic cases of S. enterica Derby that occurred in France in 2014–2015 to non-human reservoirs. The authors analyzed 299 S. enterica Derby genomes corresponding to all S. enterica Derby sporadic human cases registered in the time frame, along with 141 non-human genomes. Within the non-human genomes, three main genomic lineages were detected in France: ST39-ST40 and ST682 associated to pork and ST71 associated to poultry. Within human genomes, 94% of S. enterica Derby clustered within the three genetic groups associated with pork, identifying this animal reservoir as the major contributor of S. enterica Derby to sporadic human cases in France. Relative abundance of antimicrobial resistance genes in shotgun metagenomic data was chosen in an antimicrobial resistance source attribution study by Duarte et al.. Starting from the assumption that fecal resistomes are source related, authors compared the resistomes of pooled fecal samples of pigs, broilers, turkeys, and veal calves with the resistomes of individual fecal samples of humans occupationally exposed to livestock production. Five supervised random forest models were applied on a total of 479 observations. Among the four livestock species, the results indicated that pigs have the resistome composition closest to the composition of the human resistome suggesting that occupational exposure to AMR determinants was higher among workers exposed to pigs than workers of broiler farms. Zhang et al. characterized genetic diversity and antimicrobial resistance of 236 Campylobacter jejuni and C. coli isolates collected from 2,945 individual stool samples of hospitalized patients with diarrhea in Beijing from 2017 to 2018. MLST results confirmed the high genetic diversity among isolates as well as CC21 as the most common clonal complex of C. jejuni in diarrhea patients in China. Clonal complex CC828 was the most frequently identified among C. coli isolates. Regarding antimicrobial resistance, rates higher than 88% were identified for the antimicrobials nalidixic acid, ciprofloxacin, and tetracycline. Last but not least, Kurpas et al. genetically characterized 48 L. monocytogenes isolates of PCR-serogroup IIb and IVb collected from ready-to-eat food and food processing environments. Additionally, the authors compared them with public genomes collected from humans in Poland. Among food isolates, 65% belonged to CC1, CC2, and CC6 already described as hypervirulent strains in humans. The clonal complex CC5 was also identified; mostly collected from food processing environments and belonging to PCR-serogroup IIB. Genomes of this clonal complex showed mutations in the inlA gene and a deletion of 144 bp in the inlB gene suggesting them as hypovirulent. Based on these studies, we conclude that the application of NGS data, in particular source attribution models, shows great potential. The results are improved by becoming more specific and to the point, which is considered very valuable for the decision support process. Integrations with phenotypic tests will continue to be essential for confirmation of NGS predicted outcomes

Novel monoclonal antibodies against Pdx1 reveal feedback regulation of Pdx1 protein levels

The aim of this study was to characterize two monoclonal antibodies (F6A11 and F109-D12) generated against Pdx1 (pancreatic and duodenal homeobox-1), a homeodomain transcription factor, which is critical for pancreas formation as well as for normal pancreatic beta cell function. For production of monoclonal antibodies, we immunized Robertsonian POSF (RBF)mice with a GST-Pdx1 fusion protein containing a 68-amino acid C-terminal fragment of rat Pdx1. These monoclonal antibodies detect Pdx1 by western blotting and allow immunohistochemical detection of Pdx1 in both mouse and rat tissue. F6A11 and F109-D12 produce IHC staining patterns indistinguishable from that obtained with highly specific polyclonal Pdx1 antisera raised in rabbits and goats, when applied to embryonic or adult mouse pancreatic tissue. In contrast to previously generated polyclonal anti-Pdx1 antisera, we also demonstrate that F6A11 works for intracellular fluorescence activated cell sorting (FACS) staining of Pdx1. By using F6A11, we characterize the induction of Pdx1 in the Doxycycline (DOX) inducible insulinoma cell line INSrαβ-Pdx1 and follow the reduction of Pdx1 after removing Dox. Finally, we show that induction of exogenous Pdx1 leads to a reduction in endogenous Pdx1 levels, which suggests that a negative feedback loop is involved in maintaining correct levels of Pdx1 in the cell

Quantitative assessment of the sources of human salmonellosis attributable to pork

Salmonellosis is the main cause of food-borne human gastroenteritis in Denmark. The annual incidence of registered cases increased throughout the 1980\u27ies reaching a maximum of 67.2 cases per 100,000 inhabitants in 1988 (Figure 1) (1). At that time, the most prevalent serotype encountered among humans was S. Typhimurium, which also occurred frequently in the broiler production, where 80-90% of the flocks was infected. As a consequence, a voluntary Salmonella control programme was implemented in the broiler production in 1989 (2). Further, the Danish food authority carried out a campaign informing the consumers about the correct handling and preparation of poultry and poultry products. These actions led to a decrease in the annual incidence of human salmonellosis

Source Attribution of Human Campylobacteriosis Using Whole-Genome Sequencing Data and Network Analysis

Campylobacter spp. are a leading and increasing cause of gastrointestinal infections world-wide. Source attribution, which apportions human infection cases to different animal species and food reservoirs, has been instrumental in control-and evidence-based intervention efforts. The rapid increase in whole-genome sequencing data provides an opportunity for higher-resolution source attribution models. Important challenges, including the high dimension and complex structure of WGS data, have inspired concerted research efforts to develop new models. We propose network analysis models as an accurate, high-resolution source attribution approach for the sources of human campylobacteriosis. A weighted network analysis approach was used in this study for source attribution comparing different WGS data inputs. The compared model inputs consisted of cgMLST and wgMLST distance matrices from 717 human and 717 animal isolates from cattle, chickens, dogs, ducks, pigs and turkeys. SNP distance matrices from 720 human and 720 animal isolates were also used. The data were collected from 2015 to 2017 in Denmark, with the animal sources consisting of domestic and imports from 7 European countries. Clusters consisted of network nodes representing respective genomes and links representing distances between genomes. Based on the results, animal sources were the main driving factor for cluster formation, followed by type of species and sampling year. The coherence source clustering (CSC) values based on animal sources were 78%, 81% and 78% for cgMLST, wgMLST and SNP, respectively. The CSC values based on Campylobacter species were 78%, 79% and 69% for cgMLST, wgMLST and SNP, respectively. Including human isolates in the network resulted in 88%, 77% and 88% of the total human isolates being clustered with the different animal sources for cgMLST, wgMLST and SNP, respectively. Between 12% and 23% of human isolates were not attributed to any animal source. Most of the human genomes were attributed to chickens from Denmark, with an average attribution percentage of 52.8%, 52.2% and 51.2% for cgMLST, wgMLST and SNP distance matrices respectively, while ducks from Denmark showed the least attribution of 0% for all three distance matrices. The best-performing model was the one using wgMLST distance matrix as input data, which had a CSC value of 81%. Results from our study show that the weighted network-based approach for source attribution is reliable and can be used as an alternative method for source attribution considering the high performance of the model. The model is also robust across the different Campylobacter species, animal sources and WGS data types used as input

Outbreak of Salmonella manhattan associated with a ready-to-eat pork product in Denmark in 1998

Salmonella Manhattan is rarely found in Denmark. Since 1980, only 0-3 human cases have been registered annually. However, in the first 4 weeks of 1998, 19 cases of this serotype were registered suggesting an outbreak. S. Manhattan isolates from 18 human cases were typed using pulsedfield gel electrophoresis. Twelve of these isolates were identical and 3 were closely related, whereas the remaining isolates from humans in 1997 were clearly different. This indicated an outbreak with a common source. Further typing of S. Manhattan isolates collected as a part of the routine surveillance of domestic animals and food suggested a link to pork. Of 17 isolates from broilers, pigs and imported poultry, 6 isolates from breeder pigs imported from an internationally operating pig-production company were indistinguishable from the outbreak strain, whereas the remaining were different. A matched case-control study of 16 cases and 45 controls was carried out. The results suggested that cured and smoked ready-to-eat fillet of pork was the most likely source. Ten of 16 cases had consumed this product within three days before onset of disease, compared with 4 of 45 matched controls (OR 17,