Use of Whole-Genome Sequencing for Food Safety and Public Health in the United States

Galaxy @Sciensano: a comprehensive bioinformatics portal for genomics-based microbial typing, characterization, and outbreak detection

The influx of whole genome sequencing (WGS) data in the public health and clinical diagnostic sectors has created a need for data analysis methods and bioinformatics expertise, which can be a bottleneck for many laboratories. At Sciensano, the Belgian national public health institute, an intuitive and user-friendly bioinformatics tool portal was implemented using Galaxy, an open-source platform for data analysis and workflow creation. The Galaxy @Sciensano instance is available to both internal and external scientists and offers a wide range of tools provided by the community, complemented by over 50 custom tools and pipelines developed in-house. The tool selection is currently focused primarily on the analysis of WGS data generated using Illumina sequencing for microbial pathogen typing, characterization and outbreak detection, but it also addresses specific use cases for other data types. Our Galaxy instance includes several custom-developed 'push-button' pipelines, which are user-friendly and intuitive stand-alone tools that perform complete characterization of bacterial isolates based on WGS data and generate interactive HTML output reports with key findings. These pipelines include quality control, de novo assembly, sequence typing, antimicrobial resistance prediction and several relevant species-specific assays. They are tailored for pathogens with active genomic surveillance programs, and clinical relevance, such as Escherichia coli, Listeria monocytogenes, Salmonella spp. and Mycobacterium tuberculosis. These tools and pipelines utilize internationally recognized databases such as PubMLST, EnteroBase, and the NCBI National Database of Antibiotic Resistant Organisms, which are automatically synchronized on a regular basis to ensure up-to-date results. Many of these pipelines are part of the routine activities of Belgian national reference centers and laboratories, some of which use them under ISO accreditation. This resource is publicly available for noncommercial use at https://galaxy.sciensano.be/ and can help other laboratories establish reliable, traceable and reproducible bioinformatics analyses for pathogens encountered in public health settings.

Comparative evaluation of specimen type and processing conditions for studying oyster microbiomes

Metagenomic sequencing is increasingly being employed to understand the assemblage and dynamics of the oyster microbiome. Specimen collection and processing steps can impact the resultant microbiome composition and introduce bias. To investigate this systematically, a total of 54 farmed oysters were collected from Chesapeake Bay between May and September 2019. Six different specimen types and processing methods were evaluated for microbial community composition using shotgun metagenomics, namely fresh oyster homogenate (FOH), oyster homogenate after simulated temperature abuse (AOH), Luria broth-enriched oyster homogenate (EOH), dissected stomach homogenate (DSH), hemolymph (HLM), and stomach-gut content (SGC). In general, DSH, EOH, and FOH yielded the highest DNA concentration, while EOH had the highest microbial reads, followed by DSH, HLM, and FOH. HLM produced the highest bacterial species alpha diversity, followed by AOH, EOH, and SGC. Although alpha diversities did not differ significantly, beta-diversity measurements showed significant dissimilarity among methods (p < 0.05) indicating that the specimen types and processing steps do play an important role in representing the composition of the bacterial community. Bacterial species that had the highest log mean abundance included Cyanobium sp. PCC 7001 in FOH, Vibrio vulnificus in AOH, EOH, and DSH, and lastly Synechococcus sp. CB0205 in the DSH, HML, and SGC samples. EOH displayed higher bacterial hits, distinct microbial composition, and higher values of bacterial, phages, and antimicrobial resistance gene reads. Therefore, if studying the overall oyster microbial community, prioritizing optimum specimen collection and processing methods that align with the overall goal of the study is recommended.

The European Union One Health 2023 Zoonoses report

This report by the European Food Safety Authority and the European Centre for Disease Prevention and Control presents the results of zoonoses monitoring and surveillance activities carried out in 2023 in 27 Member States (MSs), the United Kingdom (Northern Ireland) and 10 non-MSs. Key statistics on zoonoses and zoonotic agents in humans, food, animals and feed are provided and interpreted historically. In 2023, the first and second most reported zoonoses in humans were campylobacteriosis and salmonellosis, respectively. For both agents, an increase in the absolute number of cases was observed in comparison with 2022. Fifteen MSs and the United Kingdom (Northern Ireland) reached all the established targets in poultry populations with regard to the reduction in Salmonella prevalence for the relevant serovars. Salmonella samples from carcases of various animal species, and samples for Campylobacter quantification from broiler carcases, were more frequently positive when performed by the competent authorities than when own-checks were conducted. Shiga toxin-producing Escherichia coli (STEC) was the third most reported zoonotic agent in humans, followed by Yersinia enterocolitica and Listeria monocytogenes. L. monocytogenes and West Nile virus infections were the most severe zoonotic diseases, with the highest percentage of hospitalisations among cases and the highest case fatality rates. Twenty-seven MSs and the United Kingdom (Northern Ireland) reported a slight decrease in food-borne outbreaks in 2023 overall in comparison with 2022, although the overall number of reported human cases and hospitalisations increased. Salmonella Enteritidis remained the most frequently reported causative agent for reported cases and food-borne outbreaks. Salmonella in 'eggs and egg products' was the agent/food pair of most concern. In 2023 this combination caused the largest number of outbreaks and cases among all agent/food combination and ranked second in number of hospitalisations. Salmonella was also the causative agent associated with the majority of multi-country outbreaks reported in the EU in 2023. This report also provides updates on brucellosis, echinococcosis, Q fever, rabies, toxoplasmosis, trichinellosis, tuberculosis due to Mycobacterium bovis or M. caprae, and tularaemia.

Molecular Epidemiology and AMR Perspective of Diarrhoeagenic Escherichia coli in Africa: A Systematic Review and Meta-analysis

INTRODUCTION

Diarrhoeagenic Escherichia coli (DEC) persistently challenges public health in Africa, contributing substantially to the diarrhoeal disease burden. This systematic review and meta-analysis illuminate the distribution and antimicrobial resistance (AMR) patterns of DEC pathotypes across the continent.

METHODS

The review selectively focused on pathotype-specific studies reporting prevalence and/or AMR of human-derived DEC pathotypes from African nations, excluding data from extra-intestinal, animal, and environmental sources and studies focused on drug and mechanism experiments. Pertinent studies were retrieved from SCOPUS, PubMed, and EBSCOhost, processed with Covidence, and screened in alignment with PRISMA guidelines.

RESULTS

The reviewed studies were predominantly hospital-based (80%) and paediatric-focused (91%), with a meagre 4.4% documenting DEC outbreaks. Seven DEC pathotypes were discerned, with Enteroaggregative E. coli (EAEC) being notably prevalent (43%, 95% CI 30-55%) and Enteroinvasive E. coli (EIEC) least prevalent (24%, 95% CI 17-32%). Identified non-susceptibilities were noted against essential antibiotics including ciprofloxacin, ceftriaxone, and ampicillin, while instances of carbapenem and Extended-Spectrum ß-Lactamase (ESBL) resistance were scarce.

CONCLUSION

Despite sporadic data on DEC prevalence and AMR in Africa, particularly in community settings, a palpable gap remains in real-time outbreak surveillance and comprehensive data documentation. Augmenting surveillance and embracing advancements in molecular/genomic characterisation techniques are crucial to precisely discerning DEC's actual impact and resistance continuum in Africa.

Nanopore Sequencing Allows Recovery of High-Quality Completely Closed Genomes of All Cronobacter Species from Powdered Infant Formula Overnight Enrichments

Precision metagenomic approaches using Oxford Nanopore Technology (ONT) sequencing has been shown to allow recovery of complete genomes of foodborne bacteria from overnight enrichments of agricultural waters. This study tests the applicability of a similar approach for Cronobacter genome recovery from powdered infant formula (PIF) overnight enrichments, where Cronobacter typically dominates the overall microbiome (>90%). This study aimed to test whether using ONT sequencing of overnight PIF enrichments could recover a completely closed Cronobacter genome for further genomic characterization. Ten PIF samples, each inoculated with different Cronobacter strains, covering Cronobacter sakazakii, C. muytjensii, C. dublinensis, C. turicensis, and C. universalis, were processed according to the Bacteriological Analytical Manual (BAM) protocol. Real-time quantitative PCR (qPCR) was used for initial screening (detection and quantification) of the overnight enrichments and confirmed that the inoculated PIF samples after the overnight enrichment had high levels of Cronobacter (107 to 109 CFU/mL). DNA from overnight PIF enrichments was extracted from the enrichment broth and sequenced using ONT. Results showed that ONT sequencing could accurately identify, characterize, and close the genomes of Cronobacter strains from overnight PIF enrichments in 3 days, much faster than the nearly 2 weeks required by the current BAM method. Complete genome recovery and species differentiation were achieved. This suggests that combining qPCR with ONT sequencing provides a rapid, cost-effective alternative for detecting and characterizing Cronobacter in PIF, enabling timely corrective actions during outbreaks.

Genomic perspectives on foodborne illness

Whole-genome sequencing of bacterial pathogens is used by public health agencies to link cases of food poisoning caused by the same source of contamination. The vast majority of these appear to be sporadic cases associated with small contamination episodes and do not trigger investigations. A "contamination episode" refers to one or more contamination events from a single source over a period of time. We examine clusters of sequenced clinical isolates of Salmonella, Escherichia coli, Campylobacter, and Listeria that differ by only a small number of mutations (SNPs) to identify features of the underlying contamination episodes. These analyses provide additional evidence that the youngest age groups have greater susceptibility to infection by Salmonella, E. coli, and Campylobacter than older age groups. This age bias is weaker for the common Salmonella serovar Enteritidis than Salmonella in general. A large fraction of the contamination episodes causing sickness appear to have a long duration. For example, 50% of the Salmonella cases are in clusters that persist for almost 3 y. For all four pathogen species, the majority of the cases were part of genetic clusters with illnesses in multiple states and likely to be caused by contaminated commercially distributed foods. Salmonella infections in infants under 3 mo are predominantly acquired from the same contaminated food, pet food, or environmental sources as older individuals, rather than infant formula contaminated during production.

An Outbreak Investigation of Salmonella Weltevreden Illnesses in the United States Linked to Frozen Precooked Shrimp Imported from India - 2021

In 2021, the U.S. Food and Drug Administration (FDA), Centers for Disease Control and Prevention (CDC), and state partners investigated a multistate sample-initiated retrospective outbreak investigation (SIROI) consisting of a cluster of nine Salmonella Weltevreden illnesses associated with frozen, precooked shrimp imported from India. Import surveillance testing identified Salmonella Weltevreden recovered from a cooked shrimp sample from Supplier B. In total, nine patients with clinical isolates highly related via whole genome sequencing were reported in four states with illness onset dates between February 26 and July 17, 2021. Epidemiologic data were gathered by state partners for seven patients, who all reported exposure to shrimp. Five patients reported consuming shrimp cocktail from the same retailer. A traceback investigation for five of the six patients converged on Supplier B. This evidence demonstrated that the outbreak of Salmonella Weltevreden illnesses was caused by the consumption of cooked, ready-to-eat shrimp manufactured by Supplier B. At the time of the investigation, outbreak and recall information was shared with Indian competent authorities. In March 2022, a follow-up inspection of Supplier B's facility in India was conducted, and insanitary conditions and practices were observed. This outbreak investigation highlighted the importance of multidisciplinary national and international public health partnerships. The lessons learned from this investigation should continue to inform investigational activities and food safety guidance for the industry.

Salmonella enterica virulence databases and bioinformatic analysis tools development

Salmonella enterica, a prominent foodborne pathogen, contributes significantly to global foodborne illnesses annually. This species exhibits significant genetic diversity, potentially impacting its infectivity, disease severity, and antimicrobial resistance. Whole genome sequencing (WGS) offers comprehensive genetic insights that can be utilized for virulence assessment. However, existing bioinformatic tools for studying Salmonella virulence have notable limitations. To address this gap, a Salmonella Virulence Database with a non-redundant, comprehensive list of putative virulence factors was constructed. Two bioinformatic analysis tools, Virulence Factor Profile Assessment and Virulence Factor Profile Comparison tools, were developed. The former provides data on similarity to the reference genes, e-value, and bite score, while the latter assesses the presence/absence of virulence genes in Salmonella isolates and facilitates comparison of virulence profiles across multiple sequences. To validate the database and associated bioinformatic tools, WGS data from 43,853 Salmonella isolates spanning 14 serovars was extracted from GenBank, and WGS data previously generated in our lab was used. Overall, the Salmonella Virulence database and our bioinformatic tools effectively facilitated virulence assessment, enhancing our understanding of virulence profiles among Salmonella isolates and serovars. The public availability of these resources will empower researchers to assess Salmonella virulence comprehensively, which could inform strategies for pathogen control and risk evaluations associated with human illnesses.

Identifying factors that influence the use of pathogen genomics in Australia and New Zealand: a protocol

Introduction

Pathogen genomics, where whole genome sequencing technologies are used to produce complete genomic sequences of pathogens, is being increasingly used for infectious disease surveillance and outbreak response. Although proof-of-concept studies have highlighted the viability of using pathogen genomics in public health, few studies have investigated how end-users utilize pathogen genomics in public health. We describe a protocol for a study that aims to identify key factors that influence the use of pathogen genomics to inform public health responses against infectious diseases in Australia and New Zealand.

Methods

We will use qualitative comparative analysis (QCA), a case-oriented methodology that systematically compares and analyses multiple cases (or 'units of analysis'), to identify multiple pathways leading to the use of pathogen genomics results in public health actions. As part of the process, we will develop a rubric to identify and define the use of pathogen genomics and individual factors affecting this process. Simultaneously, we will identify cases where pathogen genomics has been used in public health across Australia and New Zealand. Data for these cases will be collected from document review of publicly available and confidential documents and semi-structured interviews with technicians and end-users and summarized in a case report. These case reports will form the basis for scoring each case on the extent of the use of pathogen genomics data and the presence or absence of specific factors such as the ease of extracting essential information from pathogen genomics reports and perceptions toward pathogen genomics. Using the scores, cases will be analyzed using QCA techniques to identify pathways leading to the use of pathogen genomics data. These pathways will be interpreted alongside the cases to provide rich explanations of the use of pathogen genomics in public health.

Discussion

This study will improve our understanding of the key factors that facilitate or hinder the use of pathogen genomics to inform public health authorities and end-users. These findings may inform ways to enhance the use of pathogen genomics data in public health.

Use of whole genome sequencing for surveillance and control of foodborne diseases: status quo and quo vadis

Improvements in sequencing quality, availability, speed and costs results in an increased presence of genomics in infectious disease applications. Nevertheless, there are still hurdles in regard to the optimal use of WGS for public health purposes. Here, we discuss the current state ("status quo") and future directions ("quo vadis") based on literature regarding the use of genomics in surveillance, hazard characterization and source attribution of foodborne pathogens. The future directions include the application of new techniques, such as machine learning and network approaches that may overcome the current shortcomings. These include the use of fixed genomic distances in cluster delineation, disentangling similarity or lack thereof in source attribution, and difficulties ascertaining function in hazard characterization. Although, the aforementioned methods can relatively easily be applied technically, an overarching challenge is the inference and biological/epidemiological interpretation of these large amounts of high-resolution data. Understanding the context in terms of bacterial isolate and host diversity allows to assess the level of representativeness in regard to sources and isolates in the dataset, which in turn defines the level of certainty associated with defining clusters, sources and risks. This also marks the importance of metadata (clinical, epidemiological, and biological) when using genomics for public health purposes.

Microbial food spoilage: impact, causative agents and control strategies

Microbial food spoilage is a major contributor to food waste and, hence, to the negative environmental sustainability impacts of food production and processing. Globally, it is estimated that 15-20% of food is wasted, with waste, by definition, occurring after primary production and harvesting (for example, in households and food service establishments). Although the causative agents of food spoilage are diverse, many microorganisms are major contributors across different types of foods. For example, the genus Pseudomonas causes spoilage in various raw and ready-to-eat foods. Aerobic sporeformers (for example, members of the genera Bacillus, Paenibacillus and Alicyclobacillus) cause spoilage across various foods and beverages, whereas anaerobic sporeformers (for example, Clostridiales) cause spoilage in a range of products that present low-oxygen environments. Fungi are also important spoilage microorganisms, including in products that are not susceptible to bacterial spoilage due to their low water activity or low pH. Strategies that can reduce spoilage include improved control of spoilage microorganisms in raw material and environmental sources as well as application of microbicidal or microbiostatic strategies (for example, to products and packaging). Emerging tools (for example, systems models and improved genomic tools) represent an opportunity for rational design of systems, processes and products that minimize microbial food spoilage.

Outbreak detection in Harar town and Kersa district, Ethiopia using phylogenetic analysis and source attribution

BACKGROUND

Foodborne diseases (FBDs) represent a significant risk to public health, with nearly one in ten people falling ill every year globally. The large incidence of foodborne diseases in African low- and middle-income countries (LMIC) shows the immediate need for action, but there is still far to a robust and efficient outbreak detection system. The detection of outbreak heavily relies on clinical diagnosis, which are often delayed or ignored due to resource limitations and inadequate surveillance systems.

METHODS

In total, 68 samples of non-typhoidal Salmonella isolates from human, animal and environmental sources collected between November 2021 and January 2023 were analyzed using sequencing methods to infer phylogenetic relationships between the samples. A source attribution model using a machine-learning logit-boost that predicted the likely source of infection for 20 cases of human salmonellosis was also run and compared with the results of the cluster detection.

RESULTS

Three clusters of samples with close relation (SNP difference < 30) were identified as non-typhoidal Salmonella in Harar town and Kersa district, Ethiopia. These three clusters were comprised of isolates from different sources, including at least two human isolates. The isolates within each cluster showed identical serovar and sequence type (ST), with few exceptions in cluster 3. The close proximity of the samples suggested the occurrence of three potential outbreaks of non-typhoidal Salmonella in the region. The results of the source attribution model found that human cases of salmonellosis could primarily be attributed to bovine meat, which the results of the phylogenetic analysis corroborated.

CONCLUSIONS

The findings of this study suggested the occurrence of three possible outbreaks of non-typhoidal Salmonella in eastern Ethiopia, emphasizing the importance of targeted intervention of food safety protocols in LMICs. It also highlighted the potential of integrated surveillance for detecting outbreak and identifying the most probable source. Source attribution models in combination with other epidemiological methods is recommended as part of a more robust and integrated surveillance system for foodborne diseases.

Unveiling the persistent threat: recent insights into Listeria monocytogenes adaptation, biofilm formation, and pathogenicity in foodborne infections

Listeriosis is a severe disease caused by the foodborne pathogen Listeria monocytogenes, posing a significant risk to vulnerable populations such as the elderly, pregnant women, and newborns. While relatively uncommon, it has a high global mortality rate of 20-30%. Recent research indicates that smaller outbreaks of the more severe, invasive form of the disease occur more frequently than previously thought, despite the overall stable infection rates of L. monocytogenes over the past 10 years. The ability of L. monocytogenes to form biofilm structures on various surfaces in food production environments contributes to its persistence and challenges in eradication, potentially leading to contamination of food and food production facilities. To address these concerns, this review focuses on recent developments in epidemiology, risk evaluations, and molecular mechanisms of L. monocytogenes survival in adverse conditions and environmental adaptation. Additionally, it covers new insights into strain variability, pathogenicity, mutations, and host vulnerability, emphasizing the important events framework that elucidates the biochemical pathways from ingestion to infection. Understanding the adaptation approaches of L. monocytogenes to environmental stress factors is crucial for the development of effective and affordable pathogen control techniques in the food industry, ensuring the safety of food production.

AMRomics: a scalable workflow to analyze large microbial genome collections

Whole genome analysis for microbial genomics is critical to studying and monitoring antimicrobial resistance strains. The exponential growth of microbial sequencing data necessitates a fast and scalable computational pipeline to generate the desired outputs in a timely and cost-effective manner. Recent methods have been implemented to integrate individual genomes into large collections of specific bacterial populations and are widely employed for systematic genomic surveillance. However, they do not scale well when the population expands and turnaround time remains the main issue for this type of analysis. Here, we introduce AMRomics, an optimized microbial genomics pipeline that can work efficiently with big datasets. We use different bacterial data collections to compare AMRomics against competitive tools and show that our pipeline can generate similar results of interest but with better performance. The software is open source and is publicly available at https://github.com/amromics/amromics under an MIT license.

A Comparative Metagenomic Analysis of Specified Microorganisms in Groundwater for Non-Sterilized Pharmaceutical Products

In pharmaceutical manufacturing, ensuring product safety involves the detection and identification of microorganisms with human pathogenic potential, including Burkholderia cepacia complex (BCC), Escherichia coli, Pseudomonas aeruginosa, Salmonella enterica, Staphylococcus aureus, Clostridium sporogenes, Candida albicans, and Mycoplasma spp., some of which may be missed or not identified by traditional culture-dependent methods. In this study, we employed a metagenomic approach to detect these taxa, avoiding the limitations of conventional cultivation methods. We assessed the groundwater microbiome's taxonomic and functional features from samples collected at two locations in the spring and summer. All datasets comprised 436-557 genera with Proteobacteria, Bacteroidota, Firmicutes, Actinobacteria, and Cyanobacteria accounting for > 95% of microbial DNA sequences. The aforementioned species constituted less than 18.3% of relative abundance. Escherichia and Salmonella were mainly detected in Hot Springs, relative to Jefferson, while Clostridium and Pseudomonas were mainly found in Jefferson relative to Hot Springs. Multidrug resistance efflux pumps and BlaR1 family regulatory sensor-transducer disambiguation dominated in Hot Springs and in Jefferson. These initial results provide insight into the detection of specified microorganisms and could constitute a framework for the establishment of comprehensive metagenomic analysis for the microbiological evaluation of pharmaceutical-grade water and other non-sterile pharmaceutical products, ensuring public safety.

A Comprehensive Methodology for Microbial Strain Typing Using Fourier-Transform Infrared Spectroscopy

Timely and accurate detection and characterization of microbial threats is crucial for effective infection and outbreak management. Additionally, in food production, rapid microbe identification is indispensable for maintaining quality control and hygiene standards. Current methods for typing microbial strains often rely on labor-intensive, time-consuming, and expensive DNA- and sera-serotyping techniques, limiting their applicability in rapid-response scenarios. In this context, the IR Biotyper®, utilizing Fourier-transform infrared (FTIR) spectroscopy, offers a novel approach, providing specific spectra for fast strain typing within 3 h. This methodology article serves as a comprehensive resource for researchers and technicians aiming to utilize FTIR spectroscopy for microbial strain typing. It encompasses detailed guidelines on sample preparation, data acquisition, and analysis techniques, ensuring the generation of reliable and reproducible results. We highlight the IR Biotyper®'s rapid and accurate discrimination capabilities, showcasing its potential for real-time pathogen monitoring and source-tracking to enhance public health and food safety. We propose its integration as an early screening method, followed by more detailed analysis with whole-genome sequencing, to optimize detection accuracy and response efficiency in microbial surveillance systems.

Functional Analysis of Stress Resistance of Bacillus cereus SCL10 Strain Based on Whole-Genome Sequencing

A Gram-positive, rod-shaped, aerobic, motile, and spore-forming bacterium, designated SCL10, was isolated from Acaudina molpadioides exposure to Co-60 radiation. In this study, whole-genome sequencing was performed to identify the strain as Bacillus cereus and functional characterization, with a focus on stress resistance. The genome of the B. cereus SCL10 strain was sequenced and assembled, revealing a size of 4,979,182 bp and 5167 coding genes. The genes involved in biological functions were annotated by using the GO, COG, KEGG, NR, and Swiss-Prot databases. The results showed that genes related to alkyl hydroperoxide reductase (ahpC, ahpF), DNA-binding proteins from starved cells (dps), spore and biofilm formation (spoVG, spo0A, gerP), cold shock-like protein (cspC, cspE), ATP-dependent chaperone (clpB), and photolyase, small, acid-soluble spore protein (SASP) and DNA repair protein (recA, radD) could explain the stress resistance. These findings suggest that antioxidant activity, sporulation, biofilm formation, and DNA protection may be considered as the main resistance mechanisms under exposure to radiation in the B. cereus SCL10 strain.

Assessment of the pathogen genomics landscape highlights disparities and challenges for effective AMR Surveillance and outbreak response in the East African community

The East African Community (EAC) grapples with many challenges in tackling infectious disease threats and antimicrobial resistance (AMR), underscoring the importance of regional and robust pathogen genomics capacities. However, a significant disparity exists among EAC Partner States in harnessing bacterial pathogen sequencing and data analysis capabilities for effective AMR surveillance and outbreak response. This study assesses the current landscape and challenges associated with pathogen next-generation sequencing (NGS) within EAC, explicitly focusing on World Health Organization (WHO) AMR-priority pathogens. The assessment adopts a comprehensive approach, integrating a questionnaire-based survey amongst National Public Health Laboratories (NPHLs) with an analysis of publicly available metadata on bacterial pathogens isolated in the EAC countries. In addition to the heavy reliance on third-party organizations for bacterial NGS, the findings reveal a significant disparity among EAC member States in leveraging bacterial pathogen sequencing and data analysis. Approximately 97% (n = 4,462) of publicly available high-quality bacterial genome assemblies of samples collected in the EAC were processed and analyzed by external organizations, mainly in Europe and North America. Tanzania led in-country sequencing efforts, followed by Kenya and Uganda. The other EAC countries had no publicly available samples or had all their samples sequenced and analyzed outside the region. Insufficient local NGS sequencing facilities, limited bioinformatics expertise, lack of adequate computing resources, and inadequate data-sharing mechanisms are among the most pressing challenges that hinder the EAC's NPHLs from effectively leveraging pathogen genomics data. These insights emphasized the need to strengthen microbial pathogen sequencing and data analysis capabilities within the EAC to empower these laboratories to conduct pathogen sequencing and data analysis independently. Substantial investments in equipment, technology, and capacity-building initiatives are crucial for supporting regional preparedness against infectious disease outbreaks and mitigating the impact of AMR burden. In addition, collaborative efforts should be developed to narrow the gap, remedy regional imbalances, and harmonize NGS data standards. Supporting regional collaboration, strengthening in-country genomics capabilities, and investing in long-term training programs will ultimately improve pathogen data generation and foster a robust NGS-driven AMR surveillance and outbreak response in the EAC, thereby supporting global health initiatives.

A metagenomics-based workflow for the detection and genomic characterization of GBS in raw freshwater fish

The unexpected foodborne outbreak in Singapore in 2015 has accentuated Group B Streptococcus (GBS, Streptococcus agalactiae) sequence type 283 as an emerging foodborne pathogen transmitted via the consumption of contaminated raw freshwater fish. Isolation-based workflows utilizing conventional microbiological and whole-genome sequencing methods are commonly used to support biosurveillance efforts critical for the control management of this emerging foodborne pathogen. However, these isolation-based workflows tend to have relatively long turnaround times that hamper a timely response for implementing risk mitigation. To address this gap, we have developed a metagenomics-based workflow for the simultaneous detection and genomic characterization of GBS in raw freshwater fish. Notably, our validation results showed that this metagenomics-based workflow could achieve comparable accuracy and potentially better detection limits while halving the turnaround time (from 2 weeks to 5 days) relative to an isolation-based workflow. The metagenomics-based workflow was also successfully adapted for use on a portable long-read nanopore sequencer, demonstrating its potential applicability for real-time point-of-need testing. Using GBS in freshwater fish as an example, this work represents a proof-of-concept study that supports the feasibility and validity of metagenomics as a rapid and accurate test methodology for the detection and genomic characterization of foodborne pathogens in complex food matrices.

IMPORTANCE

The need for a rapid and accurate food microbiological testing method is apparent for a timely and effective foodborne outbreak response. This is particularly relevant for emerging foodborne pathogens such as Group B Streptococcus (GBS) whose associated food safety risk might be undercharacterized. By using GBS in raw freshwater fish as a case example, this study describes the development of a metagenomics-based workflow for rapid food microbiological safety testing and surveillance. This study can inform as a working model for various foodborne pathogens in other complex food matrices, paving the way for future methodological development of metagenomics for food microbiological safety testing.

Understanding the potential role of whole genome sequencing (WGS) in managing patients with gonorrhoea: A systematic review of WGS use on human pathogens in individual patient care

OBJECTIVES

The utility of whole genome sequencing (WGS) to inform sexually transmitted infection (STI) patient management is unclear. Timely WGS data might support clinical management of STIs by characterising epidemiological links and antimicrobial resistance profiles. We conducted a systematic review of clinical application of WGS to any human pathogen that may be transposable to gonorrhoea.

METHODS

We searched six databases for articles published between 01/01/2010-06/02/2023 that reported on real/near real-time human pathogen WGS to inform clinical intervention. All article types from all settings were included. Findings were analysed using narrative synthesis.

RESULTS

We identified 12,179 articles, of which eight reported applications to inform tuberculosis (n = 7) and gonorrhoea (n = 1) clinical patient management. WGS data were successfully used as an adjunct to clinical and epidemiological data to enhance contact-tracing (n = 2), inform antimicrobial therapy (n = 5) and identify cross-contamination (n = 1). WGS identified gonorrhoea transmission chains that were not established via partner notification. Future applications could include insights into pathogen exposure detected within sexual networks for targeted patient management.

CONCLUSIONS

While there was some evidence of WGS use to provide individualised tuberculosis and gonorrhoea treatment, the eight identified studies contained few participants. Future research should focus on testing WGS intervention effectiveness and examining ethical considerations of STI WGS use.

Genomic perspectives on foodborne illness

Whole-genome sequencing of bacterial pathogens is used by public health agencies to link cases of food poisoning caused by the same source of contamination. The vast majority of these appear to be sporadic cases associated with small contamination episodes and do not trigger investigations. We analyzed clusters of sequenced clinical isolates of Salmonella, Escherichia coli, Campylobacter, and Listeria that differ by only a small number of mutations to provide a new understanding of the underlying contamination episodes. These analyses provide new evidence that the youngest age groups have greater susceptibility to infection from Salmonella, Escherichia coli, and Campylobacter than older age groups. This age bias is weaker for the common Salmonella serovar Enteritidis than Salmonella in general. Analysis of these clusters reveals significant regional variations in relative frequencies of Salmonella serovars across the United States. A large fraction of the contamination episodes causing sickness appear to have long duration. For example, 50% of the Salmonella cases are in clusters that persist for almost three years. For all four pathogen species, the majority of the cases were part of genetic clusters with illnesses in multiple states and likely to be caused by contaminated commercially distributed foods. The vast majority of Salmonella cases among infants < 6 months of age appear to be caused by cross-contamination from foods consumed by older age groups or by environmental bacteria rather than infant formula contaminated at production sites.

Rapid and sensitive detection of Salmonella in agro-Food and environmental samples: A review of advances in rapid tests and biosensors

Salmonella is as an intracellular bacterium, causing many human fatalities when the host-specific serotypes reach the host gastrointestinal tract. Nontyphoidal Salmonella are responsible for numerous foodborne outbreaks and product recalls worldwide whereas typhoidal Salmonella are responsible for Typhoid fever cases in developing countries. Yet, Salmonella-related foodborne disease outbreaks through its food and water contaminations have urged the advancement of rapid and sensitive Salmonella-detecting methods for public health protection. While conventional detection methods are time-consuming and ineffective for monitoring foodstuffs with short shelf lives, advances in microbiology, molecular biology and biosensor methods have hastened the detection. Here, the review discusses Salmonella pathogenic mechanisms and its detection technology advancements (fundamental concepts, features, implementations, efficiency, benefits, limitations and prospects). The time-efficiency of each rapid test method is discussed in relation to their limit of detections (LODs) and time required from sample enrichment to final data analysis. Importantly, the matrix effects (LODs and sample enrichments) were compared within the methods to potentially speculate Salmonella detection from environmental, clinical or food matrices using certain techniques. Although biotechnological advancements have led to various time-efficient Salmonella-detecting techniques, one should consider the usage of sophisticated equipment to run the analysis by moderately to highly trained personnel. Ultimately, a fast, accurate Salmonella screening that is readily executed by untrained personnels from various matrices, is desired for public health procurement.

Whole genome enrichment approach for genomic surveillance of Toxoplasma gondii

Pathogenic bacteria, viruses, fungi, and protozoa can cause food and waterborne diseases. Surveillance methods must therefore screen for these pathogens at various stages of water distribution and of food from production to consumption. Detection using nucleic acid amplification methods offer rapid identification, but such methods have limited utility for characterizing populations, variant types or virulence traits of pathogens. Whole genome sequencing (WGS) can be used to determine this information. However, pathogens must be isolated and cultured to yield sufficient DNA for WGS, which is laborious or not feasible for certain stages of parasites like oocysts of Toxoplasma gondii. We previously developed the Circular Nucleic acid Enrichment Reagent (CNER) method to make whole genome enrichment (WGE) baits for difficult-to-grow bacterial pathogens. WGE using CNERs facilitates direct sequencing of pathogens from samples without the need to isolate and grow them. Here, we made WGE-CNERs for T. gondii to demonstrate the use of the CNER method to make baits to enrich the large genomes of water and foodborne protozoan pathogens. By sequencing, we detected as few as 50 parasites spiked in an oyster hemolymph matrix. We discuss the use of WGE-CNERs for genomic surveillance of food and waterborne pathogens.

Genomic characterization of Listeria monocytogenes recovered from dairy facilities in British Columbia, Canada from 2007 to 2017

Listeria monocytogenes is a foodborne pathogen of concern in dairy processing facilities, with the potential to cause human illness and trigger regulatory actions if found in the product. Monitoring for Listeria spp. through environmental sampling is recommended to prevent establishment of these microorganisms in dairy processing environments, thereby reducing the risk of product contamination. To inform on L. monocytogenes diversity and transmission, we analyzed genome sequences of L. monocytogenes strains (n = 88) obtained through the British Columbia Dairy Inspection Program. Strains were recovered from five different dairy processing facilities over a 10 year period (2007-2017). Analysis of whole genome sequences (WGS) grouped the isolates into nine sequence types and 11 cgMLST types (CT). The majority of isolates (93%) belonged to lineage II. Within each CT, single nucleotide polymorphism (SNP) differences ranged from 0 to 237 between isolates. A highly similar (0-16 SNPs) cluster of over 60 isolates, collected over 9 years within one facility (#71), was identified suggesting a possible persistent population. Analyses of genome content revealed a low frequency of genes associated with stress tolerance, with the exception of widely disseminated cadmium resistance genes cadA1 and cadA2. The distribution of virulence genes and mutations within internalin genes varied across the isolates and facilities. Further studies are needed to elucidate their phenotypic effect on pathogenicity and stress response. These findings demonstrate the diversity of L. monocytogenes isolates across dairy facilities in the same region. Findings also showed the utility of using WGS to discern potential persistence events within a single facility over time.

A prospective bacterial whole-genome-sequencing-based surveillance programme for comprehensive early detection of healthcare-associated infection transmission in paediatric oncology patients

BACKGROUND

Bacterial whole-genome sequencing (WGS) and determination of genetic relatedness is an important tool for investigation of epidemiologically suspected outbreaks.

AIM

This prospective cohort study evaluated a comprehensive, prospective bacterial WGS-based surveillance programme for early detection of transmission of most bacterial pathogens among patients at a paediatric oncology hospital.

METHODS

Cultured bacterial isolates from clinical diagnostic specimens collected prospectively from both inpatient and outpatient encounters between January 2019 and December 2021 underwent routine WGS and core genome multi-locus sequence typing to determine isolates' relatedness. Previously collected isolates from January to December 2018 were retrospectively analysed for identification of prior or ongoing transmission. Multi-patient clusters were investigated to identify potential transmission events based on temporal and spatial epidemiological links and interventions were introduced.

FINDINGS

A total of 1497 bacterial isolates from 1025 patients underwent WGS. A total of 259 genetically related clusters were detected, of which 18 (6.9%) multi-patient clusters involving 38 (3.7%) patients were identified. Sixteen clusters involved two patients each, and two clusters involved three patients. Following investigation, epidemiologically plausible transmission links were identified in five (27.8%) multi-patient clusters. None of the multi-patient clusters were suspected by conventional epidemiological surveillance.

CONCLUSION

Bacterial WGS-based surveillance for early detection of hospital transmission detected several limited multi-patient clusters that were unrecognized by conventional epidemiological methods. Genomic surveillance helped efficiently focus interventions while reducing unnecessary investigations.

Genomic and proteomic analysis of Salmonella Enteritidis isolated from a patient with foodborne diarrhea

Salmonella is a major cause of foodborne diseases and clinical infections worldwide. This study aimed to investigate the drug resistance, genomic characteristics, and protein expression of foodborne Salmonella in Shanxi Province. We isolated a strain of Salmonella Enteritidis from patient feces and designated it 31A. The drug resistance of 31A against 14 antibiotics was determined using an antimicrobial susceptibility test. Whole-genome sequencing and quantitative proteomic analysis were performed on the 31A strain. Functional annotation of drug resistance genes/proteins and virulence genes/proteins was conducted using various databases, such as VFDB, ARDB, CAZY, COG, KOG, CARD, GO, and KEGG. The focus of this study was understanding the mechanisms related to food poisoning, and the genetic evolution of 31A was analyzed through comparative genomics. The 31A strain belonged to ST11 Salmonella Enteritidis and showed resistance to β-lactam and quinolone antibiotics. The genome of 31A had 70 drug resistance genes, 321 virulence genes, 12 SPIs, and 3 plasmid replicons. Functional annotation of these drug resistance and virulence genes revealed that drug resistance genes were mainly involved in defense mechanisms to confer resistance to antibiotics, while virulence genes were mainly associated with cellular motility. There were extensive interactions among the virulence genes, which included SPI-1, SPI-2, flagella, fimbriae, capsules and so on. The 31A strain had a close relationship with ASM2413794v1 and ASM130523v1, which were also ST11 Salmonella Enteritidis strains from Asia and originated from clinical patients, animals, and food. These results suggested minimal genomic differences among strains from different sources and the potential for interhost transmission. Differential analysis of the virulence and drug resistance-related proteins revealed their involvement in pathways related to human diseases, indicating that these proteins mediated bacterial invasion and infection. The integration of genomic and proteomic information led to the discovery that Salmonella can survive in a strong acid environment through various acid resistance mechanisms after entering the intestine with food and then invade intestinal epithelial cells to exert its effects. In this study, we comprehensively analyzed the drug resistance and virulence characteristics of Salmonella Enteritidis 31A using a combination of genomic and proteomic approaches, focusing on the pathogenic mechanism of Salmonella Enteritidis in food poisoning. We found significant fluctuations in various virulence factors during the survival, invasion, and infection of Salmonella Enteritidis, which collectively contributed to its pathogenicity. These results provide important information for the source tracing, prevention, and treatment of clinical infections caused by Salmonella Enteritidis.

A Single-Laboratory Performance Evaluation of MALDI-TOF MS in Rapid Identification of Staphylococcus aureus, Cronobacter sakazakii, Vibrio parahaemolyticus, and Some Closely Related Bacterial Species of Public Health Importance

BACKGROUND

Staphylococcus is a genus of Gram-positive bacteria, known to cause food poisoning and gastrointestinal illness in humans. Additionally, the emergence of methicillin-resistant S. aureus (MRSA) strains has caused a major health care burden worldwide. Cronobacter is a group of Gram-negative bacteria that can survive in extreme dry conditions. Cronobacter sakazakii is known to contaminate powdered infant formula and cause life-threatening infections in neonates. Vibrio is a genus of human-pathogenic Gram-negative bacteria that can cause foodborne illness by consuming undercooked or raw seafood. Vibrio parahaemolyticus can cause serious gastrointestinal disease in humans. Thus, rapid identification of Staphylococcus spp., Cronobacter spp., and Vibrio spp. is crucial for the source tracking of contaminated food, as well as to measure the transmission dynamics of these bacterial pathogens causing foodborne diseases and outbreaks.

OBJECTIVE

This single-laboratory performance evaluation study used the VITEK MS system to evaluate the potential of MALDI-TOF MS technology for rapid identification of S. aureus-like, C. sakazakii-like, and V. parahaemolyticus-like isolates of public health importance.

METHOD

A total of 226 isolates recovered from various food, environmental surveillance samples, and other sources were identified by bioMérieux VITEK 2 and VITEK MS systems as Staphylococcus spp., Cronobacter spp., and Vibrio spp. Five American Type Culture Collection (ATCC) reference Gram-positive and Gram-negative bacterial isolates were also tested to complete the study. In addition, for some Staphylococcus spp. isolates, whole genome sequencing (WGS) and DNA sequencing of 16S rRNA partial region were also performed for species identification.

RESULTS

The VITEK MS system was able to provide species identification to all 96 isolates of Staphylococcus spp. and to all 29 isolates of Vibrio spp. examined with a high confidence value (99.9%). Similarly, species identification was observed for the majority of spots (245 of 303) for the 101 Cronobacter spp. isolates (∼82.0%) with a high confidence value (99.9%), and genus level identification was noticed for the rest of the Cronobacter spp. isolates (18.0%; 58 of the 303 spots) analyzed. Species identification data generated by VITEK 2 system were comparable to data obtained by the VITEK MS system.

CONCLUSIONS

The VITEK MS system is a reliable high-throughput platform that can rapidly identify Staphylococcus, Vibrio, and Cronobacter to the genus level, as well as S. aureus, C. sakazakii, V. parahaemolyticus, and other closely related foodborne isolates and bacterial isolates from additional sources, in most cases.

HIGHLIGHTS

The VITEK MS system can be used in the rapid genus and species identification of human-pathogenic Staphylococcus spp., Cronobacter spp., and Vibrio spp. isolates.

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

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

Evaluation of whole and core genome multilocus sequence typing allele schemes for Salmonella enterica outbreak detection in a national surveillance network, PulseNet USA

Salmonella enterica is a leading cause of bacterial foodborne and zoonotic illnesses in the United States. For this study, we applied four different whole genome sequencing (WGS)-based subtyping methods: high quality single-nucleotide polymorphism (hqSNP) analysis, whole genome multilocus sequence typing using either all loci [wgMLST (all loci)] and only chromosome-associated loci [wgMLST (chrom)], and core genome multilocus sequence typing (cgMLST) to a dataset of isolate sequences from 9 well-characterized Salmonella outbreaks. For each outbreak, we evaluated the genomic and epidemiologic concordance between hqSNP and allele-based methods. We first compared pairwise genomic differences using all four methods. We observed discrepancies in allele difference ranges when using wgMLST (all loci), likely caused by inflated genetic variation due to loci found on plasmids and/or other mobile genetic elements in the accessory genome. Therefore, we excluded wgMLST (all loci) results from any further comparisons in the study. Then, we created linear regression models and phylogenetic tanglegrams using the remaining three methods. K-means analysis using the silhouette method was applied to compare the ability of the three methods to partition outbreak and sporadic isolate sequences. Our results showed that pairwise hqSNP differences had high concordance with cgMLST and wgMLST (chrom) allele differences. The slopes of the regressions for hqSNP vs. allele pairwise differences were 0.58 (cgMLST) and 0.74 [wgMLST (chrom)], and the slope of the regression was 0.77 for cgMLST vs. wgMLST (chrom) pairwise differences. Tanglegrams showed high clustering concordance between methods using two statistical measures, the Baker's gamma index (BGI) and cophenetic correlation coefficient (CCC), where 9/9 (100%) of outbreaks yielded BGI values ≥ 0.60 and CCCs were ≥ 0.97 across all nine outbreaks and all three methods. K-means analysis showed separation of outbreak and sporadic isolate groups with average silhouette widths ≥ 0.87 for outbreak groups and ≥ 0.16 for sporadic groups. This study demonstrates that Salmonella isolates clustered in concordance with epidemiologic data using three WGS-based subtyping methods and supports using cgMLST as the primary method for national surveillance of Salmonella outbreak clusters.

Genetic diversity of Salmonella enterica isolated over 13 years from raw California almonds and from an almond orchard

A comparative genomic analysis was conducted for 171 Salmonella isolates recovered from raw inshell almonds and raw almond kernels between 2001 and 2013 and for 30 Salmonella Enteritidis phage type (PT) 30 isolates recovered between 2001 and 2006 from a 2001 salmonellosis outbreak-associated almond orchard. Whole genome sequencing was used to measure the genetic distance among isolates by single nucleotide polymorphism (SNP) analyses and to predict the presence of plasmid DNA and of antimicrobial resistance (AMR) and virulence genes. Isolates were classified by serovars with Parsnp, a fast core-genome multi aligner, before being analyzed with the CFSAN SNP Pipeline (U.S. Food and Drug Administration Center for Food Safety and Applied Nutrition). Genetically similar (≤18 SNPs) Salmonella isolates were identified among several serovars isolated years apart. Almond isolates of Salmonella Montevideo (2001 to 2013) and Salmonella Newport (2003 to 2010) differed by ≤9 SNPs. Salmonella Enteritidis PT 30 isolated between 2001 and 2013 from survey, orchard, outbreak, and clinical samples differed by ≤18 SNPs. One to seven plasmids were found in 106 (62%) of the Salmonella isolates. Of the 27 plasmid families that were identified, IncFII and IncFIB plasmids were the most predominant. AMR genes were identified in 16 (9%) of the survey isolates and were plasmid encoded in 11 of 16 cases; 12 isolates (7%) had putative resistance to at least one antibiotic in three or more drug classes. A total of 303 virulence genes were detected among the assembled genomes; a plasmid that harbored a combination of pef, rck, and spv virulence genes was identified in 23% of the isolates. These data provide evidence of long-term survival (years) of Salmonella in agricultural environments.

Precision metagenomics sequencing for food safety: hybrid assembly of Shiga toxin-producing Escherichia coli in enriched agricultural water

Culture-independent metagenomic sequencing of enriched agricultural water could expedite the detection and virulotyping of Shiga toxin-producing Escherichia coli (STEC). We previously determined the limits of a complete, closed metagenome-assembled genome (MAG) assembly and of a complete, fragmented MAG assembly for O157:H7 in enriched agricultural water using long reads (Oxford Nanopore Technologies, Oxford), which were 107 and 105 CFU/ml, respectively. However, the nanopore assemblies did not have enough accuracy to be used in Single Nucleotide Polymorphism (SNP) phylogenies and cannot be used for the precise identification of an outbreak STEC strain. The present study aimed to determine the limits of detection and assembly for STECs in enriched agricultural water by Illumina MiSeq sequencing technology alone, followed by establishing the limit of hybrid assembly with nanopore long-read sequencing using three different hybrid assemblers (SPAdes, Unicycler, and OPERA-MS). We also aimed to generate a genome with enough accuracy to be used in a SNP phylogeny. The classification of MiSeq and nanopore sequencing identified the same highly abundant species. Using the totality of the MiSeq output and a precision metagenomics approach in which the E. coli reads are binned before assembly, the limit of detection and assembly of STECs by MiSeq were determined to be 105 and 107 CFU/ml, respectively. While a complete, closed MAG could not be generated at any concentration, a complete, fragmented MAG was produced using the SPAdes assembler with an STEC concentration of at least 107 CFU/ml. At this concentration, hybrid assembled contigs aligned to the nanopore-assembled genome could be accurately placed in a neighbor-joining tree. The MiSeq limit of detection and assembly was less sensitive than nanopore sequencing, which was likely due to factors including the small starting material (50 vs. 1 μg) and the dilution of the library loaded on the cartridge. This pilot study demonstrates that MiSeq sequencing requires higher coverage in precision metagenomic samples; however, with sufficient concentration, STECs can be characterized and phylogeny can be accurately determined.

The Silent Threat: Antimicrobial-Resistant Pathogens in Food-Producing Animals and Their Impact on Public Health

The emergence of antimicrobial resistance (AMR) is a global health problem without geographic boundaries. This increases the risk of complications and, thus, makes it harder to treat infections, which can result in higher healthcare costs and a greater number of deaths. Antimicrobials are often used to treat infections from pathogens in food-producing animals, making them a potential source of AMR. Overuse and misuse of these drugs in animal agriculture can lead to the development of AMR bacteria, which can then be transmitted to humans through contaminated food or direct contact. It is therefore essential to take multifaceted, comprehensive, and integrated measures, following the One Health approach. To address this issue, many countries have implemented regulations to limit antimicrobial use. To our knowledge, there are previous studies based on AMR in food-producing animals; however, this paper adds novelty related to the AMR pathogens in livestock, as we include the recent publications of this field worldwide. In this work, we aim to describe the most critical and high-risk AMR pathogens among food-producing animals, as a worldwide health problem. We also focus on the dissemination of AMR genes in livestock, as well as its consequences in animals and humans, and future strategies to tackle this threat.

CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter

BACKGROUND

The rapid expansion of Whole-Genome Sequencing has revolutionized the fields of clinical and food microbiology. However, its implementation as a routine laboratory technique remains challenging due to the growth of data at a faster rate than can be effectively analyzed and critical gaps in bioinformatics knowledge.

RESULTS

To address both issues, CamPype was developed as a new bioinformatics workflow for the genomics analysis of sequencing data of bacteria, especially Campylobacter, which is the main cause of gastroenteritis worldwide making a negative impact on the economy of the public health systems. CamPype allows fully customization of stages to run and tools to use, including read quality control filtering, read contamination, reads extension and assembly, bacterial typing, genome annotation, searching for antibiotic resistance genes, virulence genes and plasmids, pangenome construction and identification of nucleotide variants. All results are processed and resumed in an interactive HTML report for best data visualization and interpretation.

CONCLUSIONS

The minimal user intervention of CamPype makes of this workflow an attractive resource for microbiology laboratories with no expertise in bioinformatics as a first line method for bacterial typing and epidemiological analyses, that would help to reduce the costs of disease outbreaks, or for comparative genomic analyses. CamPype is publicly available at https://github.com/JoseBarbero/CamPype .

Genus-wide genomic characterization of Macrococcus: insights into evolution, population structure, and functional potential

Introduction

Macrococcus species have been isolated from a range of mammals and mammal-derived food products. While they are largely considered to be animal commensals, Macrococcus spp. can be opportunistic pathogens in both veterinary and human clinical settings. This study aimed to provide insight into the evolution, population structure, and functional potential of the Macrococcus genus, with an emphasis on antimicrobial resistance (AMR) and virulence potential.

Methods

All high-quality, publicly available Macrococcus genomes (n = 104, accessed 27 August 2022), plus six South African genomes sequenced here (two strains from bovine clinical mastitis cases and four strains from beef products), underwent taxonomic assignment (using four different approaches), AMR determinant detection (via AMRFinderPlus), and virulence factor detection (using DIAMOND and the core Virulence Factor Database).

Results

Overall, the 110 Macrococcus genomes were of animal commensal, veterinary clinical, food-associated (including food spoilage), and environmental origins; five genomes (4.5%) originated from human clinical cases. Notably, none of the taxonomic assignment methods produced identical results, highlighting the potential for Macrococcus species misidentifications. The most common predicted antimicrobial classes associated with AMR determinants identified across Macrococcus included macrolides, beta-lactams, and aminoglycosides (n = 81, 61, and 44 of 110 genomes; 73.6, 55.5, and 40.0%, respectively). Genes showing homology to Staphylococcus aureus exoenzyme aureolysin were detected across multiple species (using 90% coverage, n = 40 and 77 genomes harboring aureolysin-like genes at 60 and 40% amino acid [AA] identity, respectively). S. aureus Panton-Valentine leucocidin toxin-associated lukF-PV and lukS-PV homologs were identified in eight M. canis genomes (≥40% AA identity, >85% coverage). Using a method that delineates populations using recent gene flow (PopCOGenT), two species (M. caseolyticus and M. armenti) were composed of multiple within-species populations. Notably, M. armenti was partitioned into two populations, which differed in functional potential (e.g., one harbored beta-lactamase family, type II toxin-antitoxin system, and stress response proteins, while the other possessed a Type VII secretion system; PopCOGenT p < 0.05).

Discussion

Overall, this study leverages all publicly available Macrococcus genomes in addition to newly sequenced genomes from South Africa to identify genomic elements associated with AMR or virulence potential, which can be queried in future experiments.

Comparison of genetic variations between high- and low-risk Listeria monocytogenes isolates using whole-genome de novo sequencing

In this study, genetic variations and characteristics of Listeria monocytogenes isolates from enoki mushrooms (23), smoked ducks (7), and processed ground meat products (30) were examined with respect to hemolysis, virulence genes, growth patterns, and heat resistance. The isolates that showed the highest pathogenicity and the lowest pathogenicity were analyzed to obtain the whole-genome sequence, and the sequences were further analyzed to identify genetic variations in virulence, low-temperature growth-related, and heat resistance-related factors. All isolates had β-hemolysis and virulence genes (actA, hlyA, inlA, inlB, and plcB). At low temperatures, isolates with high growth (L. monocytogenes strains SMFM 201803 SD 1-1, SMFM 201803 SD 4-2, and SMFM 201804 SD 5-3) and low growth (L. monocytogenes strains SMFM 2019-FV43, SMFM 2019-FV42, and SMFM 2020-BT30) were selected. Among them, L. monocytogenes SMFM 201804 SD 5-3 showed the highest resistance at 60°C and 70°C. The strains SMFM 201804 SD 5-3 (high-risk) and SMFM 2019-FV43 (low-risk) harbored 45 virulence genes; 41 single nucleotide variants (SNVs) were identified between these two isolates. A comparison of 26 genes related to low-temperature growth revealed 18 SNVs between these two isolates; a comparison of the 21 genes related to heat resistance revealed 16 SNVs. These results indicate that the differences in the pathogenicity of L. monocytogenes SMFM 201804 SD 5-3 and L. monocytogenes SMFM 2019-FV43 are associated with the SNVs identified in virulence genes, low-temperature growth-related genes, and heat resistance-related genes.

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

Introduction

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.

Methods

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.

Results

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.

Discussion

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.

An Overview of Foodborne Sample-Initiated Retrospective Outbreak Investigations and Interagency Collaboration in the United States

Foodborne outbreak investigations have traditionally included the detection of a cluster of illnesses first, followed by an epidemiologic investigation to identify a food of interest. The increasing use of whole genome sequencing (WGS) subtyping technology for clinical, environmental, and food isolates of foodborne pathogens, and the ability to share and compare the data on public platforms, present new opportunities to identify earlier links between illnesses and their potential sources. We describe a process called sample-initiated retrospective outbreak investigations (SIROI) used by federal public health and regulatory partners in the United States. SIROIs begin with an evaluation of the genomic similarity between bacterial isolates recovered from food or environmental samples and clusters of clinical isolates while subsequent and parallel epidemiologic and traceback investigations are initiated to corroborate their connection. SIROIs allow for earlier hypothesis generation, followed by targeted collection of information about food exposures and the foods and manufacturer of interest, to confirm a link between the illnesses and their source. This often leads to earlier action that could reduce the breadth and burden of foodborne illness outbreaks. We describe two case studies of recent SIROIs and present the benefits and challenges. Benefits include insight into foodborne illness attribution, international collaboration, and opportunities for enhanced food safety efforts in the food industry. Challenges include resource intensiveness, variability of epidemiologic and traceback data, and an increasingly complex food supply chain. SIROIs are valuable in identifying connections among small numbers of illnesses that may span significant time periods; detecting early signals for larger outbreaks or food safety issues associated with manufacturers; improving our understanding of the scope of contamination of foods; and identifying novel pathogen/commodity pairs.

Prevalence of extended-spectrum β-lactamase producing Enterobacterales in Africa's water-plant-food interface: A meta-analysis (2010–2022)

Background

Multidrug-resistant extended-spectrum β-lactamase (ESBL)-producing Enterobacterales is regarded as a critical health issue, yet, surveillance in the water-plant-food interface remains low, especially in Africa.

Objectives

The objective of the study was to elucidate the distribution and prevalence of antimicrobial resistance in clinically significant members of the Enterobacterales order isolated from the water-plant-food interface in Africa.

Methods

A literature search was conducted using six online databases according to the PRISMA guidelines. All available published studies involving phenotypic and genotypic characterization of ESBL-producing Enterobacterales from water, fresh produce or soil in Africa were considered eligible. Identification and characterization methods used as well as a network analysis according to the isolation source and publication year were summarized. Analysis of Escherichia coli, Salmonella spp. and Klebsiella pneumoniae included the calculation of the multiple antibiotic resistance (MAR) index according to isolation sources and statistical analysis was performed using RStudio.

Results

Overall, 51 studies were included for further investigation. Twelve African countries were represented, with environmental AMR surveillance studies predominantly conducted in South Africa. In 76.47% of the studies, occurrence of antimicrobial resistant bacteria was investigated in irrigation water samples, while 50.98% of the studies included fresh produce samples. Analysis of bacterial phenotypic antimicrobial resistance profiles were reported in 94.12% of the studies, with the disk diffusion method predominantly used. When investigating the MAR indexes of the characterized Escherichia coli, Klebsiella pneumoniae and Salmonella spp., from different sources (water, fresh produce or soil), no significant differences were seen across the countries. The only genetic determinant identified using PCR detection in all the studies was the blaCTX − M resistance gene. Only four studies used whole genome sequence analysis for molecular isolate characterization.

Discussion

Globally, AMR surveillance programmes recognize ESBL- and carbapenemase-producing Enterobacterales as vectors of great importance in AMR gene dissemination. However, in low- and middle-income countries, such as those in Africa, challenges to implementing effective and sustainable AMR surveillance programmes remain. This review emphasizes the need for improved surveillance, standardized methods and documentation of resistance gene dissemination across the farm-to-fork continuum in Africa.

Characterization and Antibiotic Resistance of Listeria monocytogenes Strains Isolated from Greek Myzithra Soft Whey Cheese and Related Food Processing Surfaces over Two-and-a-Half Years of Safety Monitoring in a Cheese Processing Facility

Listeriosis is a serious infectious disease with one of the highest case fatality rates (ca. 20%) among the diseases manifested from bacterial foodborne pathogens in humans, while dairy products are often implicated as sources of human infection with Listeria monocytogenes. In this study, we characterized phenotypically and genetically by whole-genome sequencing (WGS) 54 L. monocytogenes strains isolated from Myzithra, a traditional Greek soft whey cheese (48 isolates), and swabs collected from surfaces of a cheese processing plant (six isolates) in the Epirus region of Greece. All but one strain of L. monocytogenes belonged to the polymerase chain reaction (PCR) serogroups IIa (16.7%) and IIb (81.5%), corresponding to serotypes 1/2a, 3a and 1/2b, 3b, 7, respectively. The latter was identified as a PCR-serogroup IVb strain (1.8%) of serotypes 4b, 4d, 4e. Bioinformatics analysis revealed the presence of five sequence types (STs) and clonal complexes (CCs); ST1, ST3, ST121, ST 155, ST398 and CC1, CC3, CC121, CC155, CC398 were thus detected in 1.9, 83.3, 11.0, 1.9, and 1.9% of the L. monocytogenes isolates, respectively. Antibiograms of the pathogen against a panel of seven selected antibiotics (erythromycin, tetracycline, benzylpenicillin, trimethoprim-sulfamethoxazole, ampicillin, ciprofloxacin, and meropenem) showed that 50 strains (92.6%), the six surface isolates also included, were intermediately resistant to ciprofloxacin and susceptible to the rest of the six antimicrobial agents tested, whereas strong resistance against the use of a single from three implicated antibiotics was recorded to four strains (7.4%) of the pathogen isolated from Myzithra cheese samples. Thence, the minimum inhibitory concentrations (MICs) were determined for erythromycin (MIC = 0.19 μg/mL), ciprofloxacin (MIC ≥ 0.19 μg/mL), and meropenem (MIC = 0.64 μg/mL), and finally, just one strain was deemed resistant to the latter antibiotic. The phylogenetic positions of the L. monocytogenes strains and their genetic variability were determined through WGS, whilst also stress response and virulence gene analysis for the isolates was conducted. Findings of this work should be useful as they could be utilized for epidemiological investigations of L. monocytogenes in the food processing environment, revealing possible contamination scenarios, and acquired antimicrobial resistance along the food production chain.

Genetic Characterization of Listeria from Food of Non-Animal Origin Products and from Producing and Processing Companies in Bavaria, Germany

Reported cases of listeriosis from food of non-animal origin (FNAO) are increasing. In order to assess the risk of exposure to Listeria monocytogenes from FNAO, the genetic characterization of the pathogen in FNAO products and in primary production and processing plants needs to be investigated. For this, 123 samples of fresh and frozen soft fruit and 407 samples of 39 plants in Bavaria, Germany that produce and process FNAO were investigated for Listeria contamination. As a result, 64 Listeria spp. isolates were detected using ISO 11290-1:2017. Environmental swabs and water and food samples were investigated. L. seeligeri (36/64, 56.25%) was the most frequently identified species, followed by L. monocytogenes (8/64, 12.50%), L. innocua (8/64, 12.50%), L. ivanovii (6/64, 9.38%), L. newyorkensis (5/64, 7.81%), and L. grayi (1/64, 1.56%). Those isolates were subsequently sequenced by whole-genome sequencing and subjected to pangenome analysis to retrieve data on the genotype, serotype, antimicrobial resistance (AMR), and virulence markers. Eight out of sixty-four Listeria spp. isolates were identified as L. monocytogenes. The serogroup analysis detected that 62.5% of the L. monocytogenes isolates belonged to serogroup IIa (1/2a and 3a) and 37.5% to serogroup IVb (4b, 4d, and 4e). Furthermore, the MLST (multilocus sequence typing) analysis of the eight detected L. monocytogenes isolates identified seven different sequence types (STs) and clonal complexes (CCs), i.e., ST1/CC1, ST2/CC2, ST6/CC6, ST7/CC7, ST21/CC21, ST504/CC475, and ST1413/CC739. The core genome MLST analysis also showed high allelic differences and suggests plant-specific isolates. Regarding the AMR, we detected phenotypic resistance against benzylpenicillin, fosfomycin, and moxifloxacin in all eight L. monocytogenes isolates. Moreover, virulence factors, such as prfA, hly, plcA, plcB, hpt, actA, inlA, inlB, and mpl, were identified in pathogenic and nonpathogenic Listeria species. The significance of L. monocytogenes in FNAO is growing and should receive increasing levels of attention.

Overview of methodologies for the culturing, recovery and detection of Campylobacter

Campylobacter species are responsible for human gastroenteritis with diverse clinical spectra, ranging from acute watery or bloody diarrhea to life-threatening autoimmune disorders. Given the importance of Campylobacter in causing human illness, this article has reviewed the transmission and attribution sources as well as methodologies for the detection and virulence characterization of campylobacteria. The recovery and detection of Campylobacter from clinical, food and environmental samples has been achieved by the combinatorial use of selective enrichment and culturing methods. Biochemical, immunological, and nucleic acid-based methodologies have enabled the detection and differentiation of closely related Campylobacter isolates in foodborne outbreak investigations and have assessed the diversity and phylogenetic relationships of these bacterial pathogens. Analyses of motility, adherence, and invasiveness in host cells have assessed the pathogenic potential of campylobacteria. Further examination of determinants conferring antimicrobial resistance in Campylobacter have supported the growing need to closely monitor antimicrobials use in clinical and agricultural sectors.

Listeria monocytogenes Illness and Deaths Associated With Ongoing Contamination of a Multiregional Brand of Ice Cream Products, United States, 2010-2015

BACKGROUND

Frozen foods have rarely been linked to Listeria monocytogenes illness. We describe an outbreak investigation prompted by both hospital clustering of illnesses and product testing.

METHODS

We identified outbreak-associated listeriosis cases using whole-genome sequencing (WGS), product testing results, and epidemiologic linkage to cases in the same Kansas hospital. We reviewed hospital medical and dietary records, product invoices, and molecular subtyping results. Federal and state officials tested product and environmental samples for L. monocytogenes.

RESULTS

Kansas officials were investigating 5 cases of listeriosis at a single hospital when, simultaneously, unrelated sampling for a study in South Carolina identified L. monocytogenes in Company A ice cream products made in Texas. Isolates from 4 patients and Company A products were closely related by WGS, and the 4 patients with known exposures had consumed milkshakes made with Company A ice cream while hospitalized. Further testing identified L. monocytogenes in ice cream produced in a second Company A production facility in Oklahoma; these isolates were closely related by WGS to those from 5 patients in 3 other states. These 10 illnesses, involving 3 deaths, occurred from 2010 through 2015. Company A ultimately recalled all products.

CONCLUSIONS

In this US outbreak of listeriosis linked to a widely distributed brand of ice cream, WGS and product sampling helped link cases spanning 5 years to 2 production facilities, indicating longstanding contamination. Comprehensive sanitation controls and environmental and product testing for L. monocytogenes with regulatory oversight should be implemented for ice cream production.

Wholegenome sequencing as the gold standard approach for control of Listeria monocytogenes in the food chain

Listeria monocytogenes has been implicated in numerous outbreaks and related deaths of listeriosis. In food production, L. monocytogenes occurs in raw food material and above all, through postprocessing contamination. The use of next-generation sequencing technologies such as whole-genome sequencing (WGS) facilitates foodborne outbreak investigations, pathogen source tracking and tracing geographic distributions of different clonal complexes, routine microbiological/epidemiological surveillance of listeriosis, and quantitative microbial risk assessment. WGS can also be used to predict various genetic traits related to virulence, stress, or antimicrobial resistance, which can be of great benefit for improving food safety management as well as public health.

Optimized conditions for Listeria, Salmonella and Escherichia whole genome sequencing using the Illumina iSeq100 platform with point-and-click bioinformatic analysis

Whole-genome sequencing (WGS) data have become an integral component of public health investigations and clinical diagnostics. Still, many veterinary diagnostic laboratories cannot afford to implement next generation sequencing (NGS) due to its high cost and the lack of bioinformatic knowledge of the personnel to analyze NGS data. Trying to overcome these problems, and make NGS accessible to every diagnostic laboratory, thirteen veterinary diagnostic laboratories across the United States (US) initiated the assessment of Illumina iSeq100 sequencing platform for whole genome sequencing of important zoonotic foodborne pathogens Escherichia coli, Listeria monocytogenes, and Salmonella enterica. The work presented in this manuscript is a continuation of this multi-laboratory effort. Here, seven AAVLD accredited diagnostic laboratories explored a further reduction in sequencing costs and the usage of user-friendly platforms for genomic data analysis. Our investigation showed that the same genomic library quality could be achieved by using a quarter of the recommended reagent volume and, therefore a fraction of the actual price, and confirmed that Illumina iSeq100 is the most affordable sequencing technology for laboratories with low WGS demand. Furthermore, we prepared step-by-step protocols for genomic data analysis in three popular user-friendly software (BaseSpace, Geneious, and GalaxyTrakr), and we compared the outcomes in terms of genome assembly quality, and species and antimicrobial resistance gene (AMR) identification. No significant differences were found in assembly quality, and the three analysis methods could identify the target bacteria species. However, antimicrobial resistance genes were only identified using BaseSpace and GalaxyTrakr; and GalaxyTrakr was the best tool for this task.

A Practical Bioinformatics Workflow for Routine Analysis of Bacterial WGS Data

The use of whole-genome sequencing (WGS) for bacterial characterisation has increased substantially in the last decade. Its high throughput and decreasing cost have led to significant changes in outbreak investigations and surveillance of a wide variety of microbial pathogens. Despite the innumerable advantages of WGS, several drawbacks concerning data analysis and management, as well as a general lack of standardisation, hinder its integration in routine use. In this work, a bioinformatics workflow for (Illumina) WGS data is presented for bacterial characterisation including genome annotation, species identification, serotype prediction, antimicrobial resistance prediction, virulence-related genes and plasmid replicon detection, core-genome-based or single nucleotide polymorphism (SNP)-based phylogenetic clustering and sequence typing. Workflow was tested using a collection of 22 in-house sequences of Salmonella enterica isolates belonging to a local outbreak, coupled with a collection of 182 Salmonella genomes publicly available. No errors were reported during the execution period, and all genomes were analysed. The bioinformatics workflow can be tailored to other pathogens of interest and is freely available for academic and non-profit use as an uploadable file to the Galaxy platform.

Genomic diversity, virulence and source of Campylobacter jejuni contamination in Irish poultry slaughterhouses by whole genome sequencing

AIMS

The aim was to exploit whole genome sequencing (WGS) to assess genomic diversity, identify virulence genes and deduce the proportion of Campylobacter colonized broilers that directly contaminate their carcasses.

METHODS AND RESULTS

Campylobacter jejuni isolates (107) from caeca and carcass neck skin samples (50 pairs from the same batch plus 7 individual caeca) sampled at three poultry slaughterhouses over a one-year period were selected for sequencing (MiSeq; Illumina). FastQ files were submitted to BioNumerics for analysis using the wgMLST scheme for allele calling. Campylobacter cgMLST and hierarchical clustering was performed by applying the single linkage algorithm. Sequence types (STs) were determined in silico from the WGS data and isolates were assigned into clonal complexes (CCs) using the Campylobacter PubMLST.org database. Virulence genes were determined by downloading core sequences from the virulence factor database (VFDB) and the National Center for Biotechnology Information (NCBI). A high degree of diversity was observed with 23 different STs identified. ST257 and CC-21 were the most common STs and CCs, respectively. cgMLST analysis suggested that 56% of carcass contamination was a direct result of contamination from caeca from the same batch. Virulence genes known to play a role in human C. jejuni infection were identified such as the wlaN gene and the genes associated with lipooligosaccharide synthesis, which were identified in 30% of isolates.

CONCLUSIONS

Caecal colonization was the more plausible occurring source of C. jejuni contamination of broiler carcasses, compared with cross-contamination from another batch or the environment. The high rate of genetic diversity observed amongst caecal isolates is consistent with a wide variety of Campylobacter strains circulating in poultry flocks in Ireland.

SIGNIFICANCE AND IMPACT OF STUDY

The results will further inform broiler processors and regulators about the influence and importance of on-farm colonization versus slaughterhouse cross-contamination and the relationship between C. jejuni in caeca and carcasses during processing.

Using genetic markers for detection and subtyping of the emerging Salmonella enterica subspecies enterica serotype Muenchen

Non-typhoidal Salmonella (NTS) poses a global threat to public health. Poultry, one of the main reservoirs of NTS, is usually not clinically affected by most NTS, yet the economic losses to the poultry industry due to control and mitigation efforts, and due to negative publicity can be tremendous.

NTS strains are routinely characterized into serotypes in a time-consuming, labor-intensive multistep process that requires skilled personnel. Moreover, the discriminatory power of serotyping is limited compared to other subtyping methods. Whole-genome sequence data enable the identification of genetic variation within serotypes. However, sequencing is often limited by available resources, and analyzing and interpreting the genetic data may be time-consuming. Source tracing during epidemiological outbreak investigations requires rapid and efficient characterization of strains to control pathogen spread. Here we designed a multiplex polymerase chain reaction (PCR) assay for the detection of genetic variants of Salmonella Muenchen, a serotype that has emerged in Israel in the last 3 yr in both clinical human cases and different hosts. Test sensitivity of 99.21% and specificity of 94 to 100% were determined using in-silico PCR with a dataset of 18,282 NTS assemblies from 37 NTS serotypes. Similarly, test sensitivity of 100% and specificity of 96.2 to 100% were determined in-vitro with 120 NTS isolates of 52 serotypes. Moreover, the test enabled differentiation between the common sequence types of serotype Muenchen using both approaches. As opposed to traditional serotyping and other subtyping methods, the designed test allows for rapid and cost-efficient detection of the emerging S. Muenchen serotype and its variants in a single step. Future development of similar assays for other dominant serotypes may help reduce the time and cost required for detection and initial characterization of dominant NTS strains. Overall, these tests will be beneficial to both public health and for reducing of the economic losses to the poultry industry due to NTS infections.

Genomic Analysis of Shiga Toxin-Producing E. coli O157 Cattle and Clinical Isolates from Alberta, Canada

Shiga toxin (stx) is the principal virulence factor of the foodborne pathogen, Shiga toxin-producing Escherichia coli (STEC) O157:H7 and is associated with various lambdoid bacterio (phages). A comparative genomic analysis was performed on STEC O157 isolates from cattle (n = 125) and clinical (n = 127) samples to characterize virulence genes, stx-phage insertion sites and antimicrobial resistance genes that may segregate strains circulating in the same geographic region. In silico analyses revealed that O157 isolates harboured the toxin subtypes stx1a and stx2a. Most cattle (76.0%) and clinical (76.4%) isolates carried the virulence gene combination of stx1, stx2, eae and hlyA. Characterization of stx1 and stx2-carrying phages in assembled contigs revealed that they were associated with mlrA and wrbA insertion sites, respectively. In cattle isolates, mlrA and wrbA insertion sites were occupied more often (77% and 79% isolates respectively) than in clinical isolates (38% and 1.6% isolates, respectively). Profiling of antimicrobial resistance genes (ARGs) in the assembled contigs revealed that 8.8% of cattle (11/125) and 8.7% of clinical (11/127) isolates harboured ARGs. Eight antimicrobial resistance genes cassettes (ARCs) were identified in 14 isolates (cattle, n = 8 and clinical, n = 6) with streptomycin (aadA1, aadA2, ant(3'')-Ia and aph(3'')-Ib) being the most prevalent gene in ARCs. The profound disparity between the cattle and clinical strains in occupancy of the wrbA locus suggests that this trait may serve to differentiate cattle from human clinical STEC O157:H7. These findings are important for stx screening and stx-phage insertion site genotyping as well as monitoring ARGs in isolates from cattle and clinical samples.

The power, potential, benefits, and challenges of implementing high-throughput sequencing in food safety systems

The development and application of modern sequencing technologies have led to many new improvements in food safety and public health. With unprecedented resolution and big data, high-throughput sequencing (HTS) has enabled food safety specialists to sequence marker genes, whole genomes, and transcriptomes of microorganisms almost in real-time. These data reveal not only the identity of a pathogen or an organism of interest in the food supply but its virulence potential and functional characteristics. HTS of amplicons, allow better characterization of the microbial communities associated with food and the environment. New and powerful bioinformatics tools, algorithms, and machine learning allow for development of new models to predict and tackle important events such as foodborne disease outbreaks. Despite its potential, the integration of HTS into current food safety systems is far from complete. Government agencies have embraced this new technology, and use it for disease diagnostics, food safety inspections, and outbreak investigations. However, adoption and application of HTS by the food industry have been comparatively slow, sporadic, and fragmented. Incorporation of HTS by food manufacturers in their food safety programs could reinforce the design and verification of effectiveness of control measures by providing greater insight into the characteristics, origin, relatedness, and evolution of microorganisms in our foods and environment. Here, we discuss this new technology, its power, and potential. A brief history of implementation by public health agencies is presented, as are the benefits and challenges for the food industry, and its future in the context of food safety.