Food Safety Surveillance Research Articles

A novel HCR-CRISPR/Cas12a immunosensor for the sensitive detection of pesticide residues in animal-derived foods

Pesticides are widely used in the cultivation and breeding of agricultural products. However, pesticide residue monitoring has focused mainly on fruits and vegetables and has not focused on animal-derived foods. Therefore, a novel approach for determining pesticide residues in animal-derived food products via an immunosensor based on a chain hybridization reaction (HCR) with CRISPR/Cas12a is presented. Triazophos pesticide was used as a research object. This method establishes a competitive immunoreaction system in which OVA-hapten is encapsulated on the surface of the enzyme label plate, competing with pesticide molecules bound to antibodies on the surface of the nanogold composite probe. Integrating the immunoreaction with two signal amplification mechanisms, HCR and CRISPR/Cas12a, ensures heightened method sensitivity while maintaining enhanced convenience and speed. The method's detection range spans from 0.01 to 50 ng/mL, with a remarkably low detection limit of 0.013 ng/mL. Moreover, in practical sample applications, the assay exhibited a robust correlation with GC‒MS. This approach uniquely offers real-time, cost-effective, and onsite data, providing a more comprehensive and timely foundation for establishing standards on pesticide residues in animal-derived foods, bolstering food safety surveillance, and upholding public health. Moreover, the proposed HCR-CRISPR/Cas12a immunosensor effectively improved the sensitivity and accuracy of pesticides detection, offering a promising and versatile platform for food safety detection.

Sequence Types and Antimicrobial Resistance Profiles of Salmonella Typhimurium in the Food Chain in Singapore.

Salmonella remains a significant foodborne pathogen globally with S. Typhimurium presenting as a frequently occurring serovar. This study aimed to characterize 67 S. Typhimurium isolates from humans, food, farms, and slaughterhouses collected in Singapore from 2016 to 2017. Using whole-genome sequencing analysis, the isolates were found to belong to either ST19 (n = 33) or ST36 (n = 34). ST36 predominated in human intestinal and chicken isolates, while human extra-intestinal and non-chicken food isolates belonged to ST19. Plasmids were predicted in 88.1% (n = 59) of the isolates with the most common incompatibility group profiles being IncFIB(S), IncFII(S) and IncQ1. IncFIB(S) (adjusted p-value < 0.05) and IncFII(S) (adjusted p-value < 0.05) were significantly more prevalent in ST19 isolates, while Col156 (adjusted p-value < 0.05) was more significantly found in ST36 isolates. ST36 isolates exhibited higher resistance to multiple antibiotic classes such as penicillins, phenicols, folate pathway inhibitors, aminoglycosides, β-lactam/β-lactamase inhibitor combinations, tetracyclines, and fluoroquinolones. Phylogenetics analysis suggested potential shared routes of transmission among human, chicken, farm and slaughterhouse environments. Taken together, this study offers a cross-sectional epidemiological insight into the genomic epidemiology and antimicrobial landscape of S. Typhimurium isolates in Singapore, informing strategies for future public health and food safety surveillance.

Developing Causality and Severity Assessment Frameworks for Food Safety Signals Using Social Media Reviews: A Technical Report Based on Data From an Urban Indian Suburb.

Social media reviews are a valuable data source, reflecting consumer experiences and interactions with businesses. This study leverages such data to develop a passive surveillance framework for food safety in urban India. By employing a Bidirectional Encoder Representations from Transformers (BERT)-powered Aspect-Based Sentiment Analysis tool, branded as Eat At Right Place (ERP), the study analyses over 100,000 reviews from 93 restaurants to identify and assess food safety signals. The Causality Assessment Index (CAI) and Severity Assessment Score (SAS) are introduced to systematically evaluate potential risks. The CAI uses pattern recognition and temporal relationships to establish causality while the SAS quantifies severity based on sub-aspects such as cleanliness, food handling, and unintended health outcomes. Results indicate that 40% of the restaurants had a CAI above 1, highlighting significant food safety concerns. The framework successfully prioritizes corrective actions by grading the severity of issues, demonstrating its potential for real-time food safety management. This study underscores the importance of integrating innovative data-driven approaches into public health monitoring systems and suggests future improvements in natural language processing algorithms and data source expansion. The findings pave the way for enhanced food safety surveillance and timely regulatory interventions.

Machine learning approach as an early warning system to prevent foodborne Salmonella outbreaks in northwestern Italy

Salmonellosis, one of the most common foodborne infections in Europe, is monitored by food safety surveillance programmes, resulting in the generation of extensive databases. By leveraging tree-based machine learning (ML) algorithms, we exploited data from food safety audits to predict spatiotemporal patterns of salmonellosis in northwestern Italy. Data on human cases confirmed in 2015–2018 (n = 1969) and food surveillance data collected in 2014–2018 were used to develop ML algorithms. We integrated the monthly municipal human incidence with 27 potential predictors, including the observed prevalence of Salmonella in food. We applied the tree regression, random forest and gradient boosting algorithms considering different scenarios and evaluated their predictivity in terms of the mean absolute percentage error (MAPE) and R2. Using a similar dataset from the year 2019, spatiotemporal predictions and their relative sensitivities and specificities were obtained. Random forest and gradient boosting (R2 = 0.55, MAPE = 7.5%) outperformed the tree regression algorithm (R2 = 0.42, MAPE = 8.8%). Salmonella prevalence in food; spatial features; and monitoring efforts in ready-to-eat milk, fruits and vegetables, and pig meat products contributed the most to the models’ predictivity, reducing the variance by 90.5%. Conversely, the number of positive samples obtained for specific food matrices minimally influenced the predictions (2.9%). Spatiotemporal predictions for 2019 showed sensitivity and specificity levels of 46.5% (due to the lack of some infection hotspots) and 78.5%, respectively. This study demonstrates the added value of integrating data from human and veterinary health services to develop predictive models of human salmonellosis occurrence, providing early warnings useful for mitigating foodborne disease impacts on public health.

Accelerated and precise identification of antioxidants and pesticides using a smartphone-based colorimetric sensor array

The integration of smartphones with conventional analytical approaches plays a crucial role in enhancing on-site detection platforms for point-of-care testing. Here, we developed a simple, rapid, and efficient three-channel colorimetric sensor array, leveraging the peroxidase (POD)-like activity of polydopamine-decorated FeNi foam (PDFeNi foam), to identify antioxidants using both microplate readers and smartphones for signal readouts. The exceptional catalytic capacity of PDFeNi foam enabled the quick catalytic oxidation of three typical peroxidase substrates (TMB, OPD and 4-AT) within 3 min. Consequently, we constructed a colorimetric sensor array with cross-reactive responses, which was successfully applied to differentiate five antioxidants (i.e., glycine (GLY), glutathione (GSH), citric acid (CA), ascorbic acid (AA), and tannic acid (TAN)) within the concentration range of 0.1–10 μM, quantitatively analyze individual antioxidants (with AA and CA as model analytes), and assess binary mixtures of AA and GSH. The practical application was further validated by discriminating antioxidants in serum samples with a smartphone for signal readout. In addition, since pesticides could be absorbed on the surface of PDFeNi foam through π-π stacking and hydrogen bonding, the active sites were differentially masked, leading to featured modulation on POD-like activity of PDFeNi foam, thereby forming the basis for pesticides discrimination on the sensor array. The nanozyme-based sensor array provides a simple, rapid, visual and high-throughput strategy for precise identification of various analytes with a versatile platform, highlighting its potential application in point-care-of diagnostic, food safety and environmental surveillance.

A mini review of mycotoxin’s occurrence in food in South America in the last 5 years: research gaps and challenges in a climate change era

Mycotoxins are natural metabolites produced by species of filamentous fungi belonging mainly to the genera Aspergillus, Fusarium, Penicillium, and Alternaria, which can grow in various crops and foodstuffs. The South American climate is diverse, varying from tropical, temperate, and arid to cold, ideal for the growth of different types of fungi and mycotoxin production. This mini review aimed to describe the natural occurrence of mycotoxin in food in South America from 2018 to 2023, identifying research gaps and challenges in an era of climate change. We analyzed 53 studies, 21 from Brazil. Most of the mycotoxins analyzed in South America were the traditional and regulated mycotoxins, with variable occurrences depending on the region, climatic conditions, and methodology used. Emerging and modified mycotoxins have only been studied in Argentina and Brazil, where some studies have shown high occurrences. Given this, it is essential to strengthen food safety laboratories and surveillance capabilities and establish early warning systems. It is also essential to continue working to raise awareness of mycotoxins as a public health issue and to study and prevent the impact of climate change on soil microbial population, the new prevalence of fungi, and the profile of toxigenic species. An effective connection and collaboration between disciplines and sectors in different countries is needed to meet this research challenge.

Fortified Dual-Spectral Overlap with Enhanced Colorimetric/Fluorescence Dual-Response Immunochromatography for On-Site Bimodal-Type Gentamicin Monitoring.

Immunochromatography (ICA) remains untapped toward enhanced sensitivity and applicability for fulfilling the nuts and bolts of on-site food safety surveillance. Herein, we report a fortified dual-spectral overlap with enhanced colorimetric/fluorescence dual-response ICA for on-site bimodal-type gentamicin (Gen) monitoring by employing polydopamine (PDA)-coated AuNPs (APDA) simultaneously serving as a colorimetric reporter and a fluorescence quencher. Availing of the enhanced colorimetric response that originated from the PDA layer, the resultant APDA exhibits less required antibody and immunoprobes in a single immunoassay, which facilitates improved antibody utilization efficiency and immuno-recognition in APDA-ICA. Further integrated with the advantageous features of fortified excitation and emission dual-spectral overlap for the Arg/ATT-AuNCs, this APDA-ICA with a "turn on/off" pattern achieves the visual limits of detection of 1.0 and 0.5 ng mL-1 for colorimetric and fluorescence patterns (25- and 50-fold lower than standard AuNPs-ICA). Moreover, the excellent self-calibration and satisfactory recovery of 79.03-118.04% were shown in the on-site visual colorimetric-fluorescence analysis for Gen in real environmental media (including real river water, an urban aquaculture water body, an aquatic product, and an animal byproduct). This work provides the feasibility of exploiting fortified dual-spectral overlap with an enhanced colorimetric/fluorescence dual response for safeguarding food safety and public health.

Polycarboxyl ionic liquid functionalized Yb-MOFs nanoballs based dual-wavelength responsive photoelectrochemical aptasensor for the simultaneous determination of AFB1 and OTA

Developing an accurate and precise approach for the simultaneous detection of ochratoxin A (OTA) and aflatoxin B1 (AFB1) is significant for food safety surveillance. Herein, a photoelectrochemical sensing platform was constructed based on polycarboxylic ionic liquid functionalized metal-organic framework integrated with gold nanoparticles (Yb-MOFs@AuNPs). Sulfhydryl functionalized hairpin DNA (hDNA) was immobilized on a Yb-MOFs@AuNPs modified glassy carbon electrode (GCE) surface through Au-S bond. After blocking residual active binding sites with BSA, gold nanoparticles-labeled AFB1 aptamer (AuNPs-Apt 1) and gold nanorods-labeled OTA aptamer (AuNRs-Apt 2) were introduced to construct a photoelectrochemical aptasensor for the simultaneous determination of AFB1 and OTA. Due to the surface plasmon resonance effect and the nanometer size effect of gold nanomaterials, the photoelectrochemical aptasensor can output photocurrent responses as being excited with different wavelengths at 520 nm and 808 nm, respectively. When the AFB1 and OTA concentration in the range of 0.001–50.0 ng mL−1, a good linear relationship between the photocurrent difference (ΔI) before and after recognizing targets and the logarithm of AFB1 or OTA concentration was obtained. The detection limits for AFB1 and OTA were 0.40 pg mL−1 and 0.19 pg mL−1, respectively. AFB1 and OTA in corn samples were detected simultaneously by the photoelectrochemical aptasensor.

Surface Plasmon Resonance Application for Bacteria Pathogen Detection: A Minireview

Detection of pathogenic bacteria requires a fast and accurate process so technological developments related to the sensitivity and selectivity of a sensor are very concerned. Surface Plasmon Resonance (SPR) technology has great potential to detect pathogenic bacteria that are not only used for medical diagnostics, but food safety surveillance and environmental monitoring are also applications of SPR. The success of SPR has proven the advantages of real-time detection without the need for fluorescent markers or additional dyes. The development of sensor surface systems of SPR with nanomaterials is one of the discussions in this paper. The recent development of SPR in recent years is summarized by linking future prospective applications.

Centrifugal microfluidic system for colorimetric sample-to-answer detection of viral pathogens.

We describe a microfluidic system for conducting thermal lysis, polymerase chain reaction (PCR) amplification, hybridization, and colorimetric detection of foodborne viral organisms in a sample-to-answer format. The on-chip protocol entails 24 steps which are conducted by a centrifugal platform that allows for actuating liquids pneumatically during rotation and so facilitates automation of the workflow. The microfluidic cartridge is fabricated from transparent thermoplastic polymers and accommodates assay components along with an embedded micropillar array for detection and read-out. A panel of oligonucleotide primers and probes has been developed to perform PCR and hybridization assays that allows for identification of five different viruses, including pathogens such as norovirus and hepatitis A virus (HAV) in a multiplexed format using digoxigenin-labelled amplicons and immunoenzymatic conversion of a chromogenic substrate. Using endpoint detection, we demonstrate that the system can accurately and repetitively (n = 3) discriminate positive and negative signals for HAV at 350 genome copies per μL. As part of the characterization and optimization process, we show that the implementation of multiple (e.g., seven) micropillar arrays in a narrow fluidic pathway can lead to variation (up to 50% or more) in the distribution of colorimetric signal deriving from the assay. Numerical modeling of flow behaviour was used to substantiate these findings. The technology-by virtue of automation-can provide a pathway toward rapid detection of viral pathogens, shortening response time in food safety surveillance, compliance, and enforcement as well as outbreak investigations.

Occurrence of aflatoxigenic fungi and aflatoxins in maize grains and associated awareness and handling practices among farmers and traders in South Sudan

Maize is a popular staple food among the urban population of South Sudan. However, due to inadequate food safety surveillance and enforcement systems, there is limited information on the aflatoxin safety of maize grains at farm and market levels. Therefore, this study aimed at assessing aflatoxins awareness and handling practices of maize grains among randomly selected farmers (n=30) and traders (n=30) as well as determining the moisture content, Aspergillus species counts and aflatoxins contamination. A cross-sectional descriptive study was carried out in Magwi maize producing areas, Juba retail/wholesale markets and Nimule border points of South Sudan. Moisture content, fungal and aflatoxins contamination in maize grain samples were determined using dry air oven method, dilution plating technique, and High-Performance Liquid Chromatography (HPLC), respectively. The respondent results showed that farmers (97%) and traders (83%) were unaware of aflatoxins. About 83% of the farmers dried their maize grains on tarpaulins, for 4 - 5 days (77%). In addition, most farmers (77%) stored their maize grain bags on raised platforms, whereas most traders (73%) stored grains on bare ground. All the maize grains met the required moisture content limit (below 13.5%). Maize from Nimule main park had the highest levels of contamination with Aspergillus flavus (9 log CFU/g), Aspergillus parasiticus (12 log CFU/g), aflatoxin B1 (505.56 µg/kg) and total aflatoxins (1,032.19 µg/kg). Maize from Gudele market was contaminated with Aspergillus parasiticus (12 log CFU/g), and aflatoxin B1 (76.55 µg/kg), and had a total aflatoxin content of 94.09 µg/kg. Omeo farmers’ maize grains had the least levels of contamination of Aspergillus parasiticus (6 log CFU/g), aflatoxin B1 (4.39 µg/kg), and total aflatoxins (7.83 µg/kg). In addition, Aspergillus flavus was not detected from Omeo farmers’ maize grains and no aflatoxins were detected from Agoro and Paluonganyi farmers’ grains. This study recommends wider aflatoxins awareness and regular aflatoxin screening of maize grains by the relevant stakeholders in South Sudan. Key words: aflatoxins, aflatoxigenic fungi, awareness, farmers, handling practices, maize, South Sudan, traders

Establishment of real-time fluorescence and visual LAMP for rapid detection of Escherichia coli O157: H7 and kits construction.

E. coli O157: H7 is a common pathogenic bacterium in food and water that can pose a threat to human health. The aim of this study was to develop LAMP method for the detection of E. coli O157: H7 in food based on the specific gene Ecs_2840, and to construct rapid detection kits based on the established methods. Specifically, we established two methods of Real-time fluorescent LAMP (RT-LAMP) and visual LAMP with calcein as indicator. In pure bacterial culture, the cell sensitivity and genomic sensitivity of the RT-LAMP kit were 8.8×10°CFU·mL-1 and 4.61 fg·µL-1 respectively. The sensitivity of the visual LAMP kit were 2.35×10°CFU·mL-1 and 4.61 fg·µL-1. Both kits had excellent specificity and anti-interference performance. In addition, milk inoculated with 2.26×10°CFU·mL-1 E. coli O157: H7 could be detected within the reaction time after enrichment for 3 hours. The results showed that the LAMP kits were rapid, sensitive and specific for the detection of E. coli O157: H7 in food and had good application prospects in food safety surveillance.

A foodborne outbreak linked to Bacillus cereus at two middle schools in a rural area of Chongqing, China, 2021.

Bacillus cereus (B. cereus) is a common cause of foodborne illness. An outbreak of acute gastrointestinal illness occurred at two middle schools in a rural region of Chongqing, China, in 2021. This study aimed to elucidate the outbreak's characteristics, identify risk factors, and determine the source of contamination. A retrospective cohort study and an environmental investigation were conducted. Vomit samples, anal swabs, and food samples were collected and tested by RT-PCR for 18 species of bacteria and viruses, including B. cereus. Positive samples of B. cereus underwent biochemical experiments and bacterial quantification. A total of 198 cases were reported in this outbreak, with an attack rate of 24.63%. The main symptoms were vomiting (100%), bellyache (83.33%), and dizziness (62.63%). The retrospective cohort study showed a significant association between the outbreak and rice noodles provided by a nearby food manufacturer (RR = 39.63, p < 0.001). B. cereus was detected in 20 vomit samples, three anal swabs, and seven rice noodles samples, with a count exceeding 103 CFU/g. These findings strongly suggested that the outbreak was linked to B. cereus-contaminated rice noodles. Enhancing food safety surveillance and promoting health measures among schools and food manufacturers in rural areas is crucial to prevent similar incidents in the future in Chongqing, China.

Phagotrophic protists preserve antibiotic-resistant opportunistic human pathogens in the vegetable phyllosphere

Food safety of leafy greens is an emerging public health issue as they can harbor opportunistic human pathogens (OHPs) and expose OHPs to consumers. Protists are an integral part of phyllosphere microbial ecosystems. However, our understanding of protist-pathogen associations in the phyllosphere and their consequences on public health remains poor. Here, we examined phyllosphere protists, human pathogen marker genes (HPMGs), and protist endosymbionts from four species of leafy greens from major supermarkets in Xiamen, China. Our results showed that Staphylococcus aureus and Klebsiella pneumoniae were the dominant human pathogens in the vegetable phyllosphere. The distribution of HPMGs and protistan communities differed between vegetable species, of which Chinese chive possessed the most diverse protists and highest abundance of HPMGs. HPMGs abundance positively correlated with the diversity and relative abundance of phagotrophic protists. Whole genome sequencing further uncovered that most isolated phyllosphere protists harbored multiple OHPs which carried antibiotic resistance genes, virulence factors, and metal resistance genes and had the potential to HGT. Colpoda were identified as key phagotrophic protists which positively linked to OHPs and carried diverse resistance and virulence potential endosymbiont OHPs including Pseudomonas nitroreducens, Achromobacter xylosoxidans, and Stenotrophomonas maltophilia. We highlight that phyllosphere protists contribute to the transmission of resistant OHPs through internalization and thus pose risks to the food safety of leafy greens and human health. Our study provides insights into the protist-OHP interactions in the phyllosphere, which will help in food safety surveillance and human health.

Assessing the Prevalence and Potential Risks of Salmonella Infection Associated with Fresh Salad Vegetable Consumption in the United Arab Emirates.

This study aimed to investigate the occurrence and characteristics of Salmonella isolates in salad vegetables in the United Arab Emirates (UAE). Out of 400 samples tested from retail, only 1.25% (95% confidence interval, 0.41-2.89) were found to be positive for Salmonella, all of which were from conventional local produce, presented at ambient temperature, and featured as loose items. The five Salmonella-positive samples were arugula (n = 3), dill (n = 1), and spinach (n = 1). The Salmonella isolates from the five samples were found to be pan-susceptible to a panel of 12 antimicrobials tested using a disc diffusion assay. Based on whole-genome sequencing (WGS) analysis, only two antimicrobial resistance genes were detected-one conferring resistance to aminoglycosides (aac(6')-Iaa) and the other to fosfomycin (fosA7). WGS enabled the analysis of virulence determinants of the recovered Salmonella isolates from salad vegetables, revealing a range from 152 to 165 genes, collectively grouped under five categories, including secretion system, fimbrial adherence determinants, macrophage-inducible genes, magnesium uptake, and non-fimbrial adherence determinants. All isolates were found to possess genes associated with the type III secretion system (TTSS), encoded by Salmonella pathogenicity island-1 (SPI-1), but various genes associated with the second type III secretion system (TTSS-2), encoded by SPI-2, were absent in all isolates. Combining the mean prevalence of Salmonella with information regarding consumption in the UAE, an exposure of 0.0131 salmonellae consumed per person per day through transmission via salad vegetables was calculated. This exposure was used as an input in a beta-Poisson dose-response model, which estimated that there would be 10,584 cases of the Salmonella infection annually for the entire UAE population. In conclusion, salad vegetables sold in the UAE are generally safe for consumption regarding Salmonella occurrence, but occasional contamination is possible. The results of this study may be used for the future development of risk-based food safety surveillance systems in the UAE and to elaborate on the importance for producers, retailers, and consumers to follow good hygiene practices, particularly for raw food items such as leafy salad greens.

Transforming Shiga toxin-producing Escherichia coli surveillance through whole genome sequencing in food safety practices.

Shiga toxin-producing Escherichia coli (STEC) is a gastrointestinal pathogen causing foodborne outbreaks. Whole Genome Sequencing (WGS) in STEC surveillance holds promise in outbreak prevention and confinement, in broadening STEC epidemiology and in contributing to risk assessment and source attribution. However, despite international recommendations, WGS is often restricted to assist outbreak investigation and is not yet fully implemented in food safety surveillance across all European countries, in contrast to for example in the United States. In this study, WGS was retrospectively applied to isolates collected within the context of Belgian food safety surveillance and combined with data from clinical isolates to evaluate its benefits. A cross-sector WGS-based collection of 754 strains from 1998 to 2020 was analyzed. We confirmed that WGS in food safety surveillance allows accurate detection of genomic relationships between human cases and strains isolated from food samples, including those dispersed over time and geographical locations. Identifying these links can reveal new insights into outbreaks and direct epidemiological investigations to facilitate outbreak management. Complete WGS-based isolate characterization enabled expanding epidemiological insights related to circulating serotypes, virulence genes and antimicrobial resistance across different reservoirs. Moreover, associations between virulence genes and severe disease were determined by incorporating human metadata into the data analysis. Gaps in the surveillance system were identified and suggestions for optimization related to sample centralization, harmonizing isolation methods, and expanding sampling strategies were formulated. This study contributes to developing a representative WGS-based collection of circulating STEC strains and by illustrating its benefits, it aims to incite policymakers to support WGS uptake in food safety surveillance.

P19-018-23 Social Media Mining for Food Safety Surveillance in Italy

P19-018-23 Social Media Mining for Food Safety Surveillance in Italy

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.

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. 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. 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.

Virulence and antimicrobial resistance profiles of Salmonella enterica isolated from foods, humans, and the environment in Mexico

Salmonella enterica genotypic and phenotypic characteristics play an important role in its pathogenesis, which could be influenced by its origin. This study evaluated the association among the antimicrobial resistance, virulence, and origin of circulating S. enterica strains in Mexico, isolated from foods, humans, and the environment. The antimicrobial susceptibility to fourteen antibiotics by the Kirby-Bauer method (n = 117), and the presence of thirteen virulence genes by multiplex PCR (n = 153) and by sequence alignments (n = 2963) were evaluated. In addition, a set of S. enterica isolates from Mexico (n = 344) previously characterized according to their genotypic and phenotypic print was included to increase the coverage of the association analysis. Strains with the presence of sopE and strains with the absence of sspH1 were significantly associated with multidrug-resistant (MDR) phenotypes (p < 0.05). The origin of the strains had significant associations with the antimicrobial profiles and some virulence genes (hilA, orgA, sifA, ssaQ, sseL, sspH1, pefA, and spvC) (p < 0.05). Animal-origin food isolates showed the highest frequency of MDR (57.2 %), followed by human isolates (30.0 %). Also, sspH1, pefA, and spvC were found in major frequency in human (32.4 %, 31.0 %, 31.7 %) and animal-origin foods (41.6 %, 10.6 %, 10.6 %) isolates. The findings highlighted that antimicrobial profiles and specific virulence genes of S. enterica strains are related to their origin. Similar genotypic and phenotypic characteristics between human and animal-origin foods isolates were found, suggesting that animal-origin foods isolates are the most responsible for human cases. The revealed associations can be used to improve risk estimation assessments in national food safety surveillance programs.

A research framework for passive surveillance for food safety from social media: Identification and evaluation of customer reviews for regulatory use and case study of 30 restaurants

The primary objective of this paper is to develop a framework for continuous monitoring of the safety of food business operators without overburdening established regulatory systems through social media for food safety. A phase-wise methodology was adopted, wherein Phase 1 was dedicated to identifying available literature on Adverse Drugs Reactions (ADR) reporting using Social Media data. Phase 2 used the data from google maps review of the restaurants to replicate a similar methodology for Food Safety Surveillance. We identified 5 themes for a complete Surveillance framework, theme 1 involves data collection from social media, theme 2 involves pre-processing of data for analysis, theme 3 involves data annotations, theme 4 involves Identifying the relationship between regulatory violation and event, and theme 5 involves evaluation of the model. We were able to demonstrate the ADR reporting methodology could be adopted till theme 3, whereas theme 4 requires the development of an algorithm to assess the causality of an event with the Food Safety Code. According to our research, it is possible to develop a passive surveillance system for food safety that adheres to the principle of ADR reporting; however, the main obstacle is the absence of a causality assessment algorithm that can link an event to the food safety code and help regulators take immediate action.