Genomics of foodborne pathogens for microbial food safety

Bioinformatic Pipeline for Profiling Foodborne Bacterial Ecology and Resistome from Short-Read Metagenomics

Next-generation sequencing revolutionized food safety management these last years providing access to a huge quantity of valuable data to identify, characterize, and monitor bacterial pathogens on the food chain. Shotgun metagenomics emerged as a particularly promising approach as it enables in-depth taxonomic profiling and functional investigation of food microbial communities. In this chapter, we provide a comprehensive step-by-step bioinformatical workflow to characterize bacterial ecology and resistome composition from metagenomic short-reads obtained by shotgun sequencing.

Developing the PIP-eco: An integrated genomic pipeline for identification and characterization of Escherichia coli pathotypes encompassing hybrid forms

Pathogenic Escherichia coli (E. coli) strains are distinguished by their diverse virulence factors, which contribute to a wide spectrum of diseases. These pathogens evolve through the horizontal transfer of virulence factors, resulting in the emergence of hybrid pathotypes with complex and heterogeneous characteristics. Recognizing their profound impact on public health, this study introduces the PIP-eco pipeline, a comprehensive analytical tool designed for the precise identification and characterization of E. coli pathotypes. This PIP-eco pipeline advances beyond traditional molecular techniques by facilitating detailed analysis of both single and hybrid pathotypes. It integrates targeted marker gene analysis, virulence factor-based phylogenetic analysis, and pathogenicity islands (PAIs) profiling to elucidate the genetic diversity of E. coli pathotypes and support their accurate classification. This integrative approach enables PIP-eco to uncover connections among various E. coli pathotypes, highlight shared virulence factors, and provide insights into their evolutionary trajectories. By utilizing experimentally validated marker genes, the pipeline ensures robust identification of pathotypes, particularly those of hybrid pathotypes. Additionally, PAI analysis offers comprehensive genetic investigations, revealing strain-specific variations and potential virulence mechanisms. As a result, the PIP-eco pipeline emerges as a useful tool for dissecting the evolutionary dynamics of E. coli and characterizing complex pathotypes, addressing the critical need for accurate detection and understanding of hybrid pathotypes.

Dynamics of microbiome and resistome in a poultry burger processing line

Traditionally, surveillance programs for food products and food processing environments have focused on targeted pathogens and resistance genes. Recent advances in high throughput sequencing allow for more comprehensive and untargeted monitoring. This study assessed the microbiome and resistome in a poultry burger processing line using culturing techniques and whole metagenomic sequencing (WMS). Samples included meat, burgers, and expired burgers, and different work surfaces. Microbiome analysis revealed spoilage microorganisms as the main microbiota, with substantial shifts observed during the shelf-life period. Core microbiota of meat and burgers included Pseudomonas spp., Psychrobacter spp., Shewanella spp. and Brochothrix spp., while expired burgers were dominated by Latilactobacillus spp. and Leuconostoc spp. Cleaning and disinfection (C&D) procedures altered the microbial composition of work surfaces, which still harbored Hafnia spp. and Acinetobacter spp. after C&D. Resistome analysis showed a low overall abundance of resistance genes, suggesting that effective interventions during processing may mitigate their transmission. However, biocide resistance genes were frequently found, indicating potential biofilm formation or inefficient C&D protocols. This study demonstrates the utility of combining culturing techniques and WMS for comprehensive of the microbiome and resistome characterization in food processing lines.

Resilient sustainable current and emerging technologies for foodborne pathogen detection

Foodborne pathogens such as Salmonella, Escherichia coli and Listeria pose significant risks to human health. The World Health Organization estimates that 2.2 million deaths per year are directly caused by foodborne and waterborne bacterial diseases worldwide. Accordingly, detecting pathogens in food is essential to ensure that our food is safe. This review explores the critical role of novel technologies in enhancing food safety practices whilst delving into adopting and integrating innovative, resilient and sustainable approaches in the food supply chain. Further, applying novel, emerging advanced analytical techniques such as Raman spectroscopy and nanotechnology based biosensors in food contamination detection is discussed. These advanced technologies show the promise of real-time monitoring, traceability, and predictive analytics to identify and mitigate potential hazards before they reach consumers. They can provide rapid and accurate results and ensure the integrity of food products. Furthermore, the herein-highlighted synergistic integration of these technologies offers a promising path toward a safer and more transparent food system, thereby addressing the challenges of today's globalised food market and laying the platform for developing multimodal technologies for affordable, sensitive and rapid pathogen detection along the different stages of the food chain, from "farm to fork".

Step-by-Step Metagenomics for Food Microbiome Analysis: A Detailed Review

This review article offers a comprehensive overview of the current understanding of using metagenomic tools in food microbiome research. It covers the scientific foundation and practical application of genetic analysis techniques for microbial material from food, including bioinformatic analysis and data interpretation. The method discussed in the article for analyzing microorganisms in food without traditional culture methods is known as food metagenomics. This approach, along with other omics technologies such as nutrigenomics, proteomics, metabolomics, and transcriptomics, collectively forms the field of foodomics. Food metagenomics allows swift and thorough examination of bacteria and potential metabolic pathways by utilizing foodomic databases. Despite its established scientific basis and available bioinformatics resources, the research approach of food metagenomics outlined in the article is not yet widely implemented in industry. The authors believe that the integration of next-generation sequencing (NGS) with rapidly advancing digital technologies such as artificial intelligence (AI), the Internet of Things (IoT), and big data will facilitate the widespread adoption of this research strategy in microbial analysis for the food industry. This adoption is expected to enhance food safety and product quality in the near future.

Insights into the genomic traits of Yersinia frederiksenii, Yersinia intermedia and Yersinia kristensenii isolated from diverse sources in Brazil

Yersinia is an important genus comprising foodborne, zoonotic and pathogenic bacteria. On the other hand, species of the so-called group Yersinia enterocolitica-like are understudied and mostly characterized as non-pathogenic, despite of some reports of human infections. The present study aimed to provide genomic insights of Yersinia frederiksenii (YF), Yersinia intermedia (YI) and Yersinia kristensenii (YK) isolated worldwide. A total of 22 YF, 20 YI and 14 YK genomes were searched for antimicrobial resistance genes, plasmids, prophages, and virulence factors. Their phylogenomic relatedness was analyzed by Gegenees and core-genome multi-locus sequence typing. Beta-lactam resistance gene blaTEM-116 and five plasmids replicons (pYE854, ColRNAI, ColE10, Col(pHAD28) and IncN3) were detected in less than five genomes. A total of 59 prophages, 106 virulence markers of the Yersinia genus, associated to adherence, antiphagocytosis, exoenzymes, invasion, iron uptake, proteases, secretion systems and the O-antigen, and virulence factors associated to other 20 bacterial genera were detected. Phylogenomic analysis revealed high inter-species distinction and four highly diverse YF clusters. In conclusion, the results obtained through the analyses of YF, YI and YK genomes suggest the virulence potential of these strains due to the broad diversity and high frequency of prophages and virulence factors found. Phylogenetic analyses were able to correctly distinguish these closely related species and show the presence of different genetic subgroups. These data contributed for a better understanding of YF, YI and YK virulence-associated features and global genetic diversity, and reinforced the need for better characterization of these Y. enterocolitica-like species considered non-pathogenic.

Distinct Escherichia coli transcriptional profiles in the guts of recurrent UTI sufferers revealed by pangenome hybrid selection

Low-abundance members of microbial communities are difficult to study in their native habitats. This includes Escherichia coli, a minor, but common inhabitant of the gastrointestinal tract and opportunistic pathogen, including of the urinary tract, where it is the primary pathogen. While multi-omic analyses have detailed critical interactions between uropathogenic Escherichia coli (UPEC) and the bladder that mediate UTI outcome, comparatively little is known about UPEC in its pre-infection reservoir, partly due to its low abundance there (<1% relative abundance). To accurately and sensitively explore the genomes and transcriptomes of diverse E. coli in gastrointestinal communities, we developed E. coli PanSelect which uses a set of probes designed to specifically recognize and capture E. coli's broad pangenome from sequencing libraries. We demonstrated the ability of E. coli PanSelect to enrich, by orders of magnitude, sequencing data from diverse E. coli using a mock community and a set of human stool samples collected as part of a cohort study investigating drivers of recurrent urinary tract infections (rUTI). Comparisons of genomes and transcriptomes between E. coli residing in the gastrointestinal tracts of women with and without a history of rUTI suggest that rUTI gut E. coli are responding to increased levels of oxygen and nitrate, suggestive of mucosal inflammation, which may have implications for recurrent disease. E. coli PanSelect is well suited for investigations of native in vivo biology of E. coli in other environments where it is at low relative abundance, and the framework described here has broad applicability to other highly diverse, low abundance organisms.

Comparative genomics reveals high genetic similarity among strains of Salmonella enterica serovar Infantis isolated from multiple sources in Brazil

Background

Salmonella enterica serovar Infantis (Salmonella Infantis) is a zoonotic, ubiquitous and foodborne pathogen of worldwide distribution. Despite Brazil's relevance as a major meat exporter, few studies were conducted to characterize strains of this serovar by genomic analyses in this country. Therefore, this study aimed to assess the diversity of 80 Salmonella Infantis strains isolated from veterinary, food and human sources in Brazil between 2013 and 2018 by comparative genomic analyses. Additional genomes of non-Brazilian countries (n = 18) were included for comparison purposes in some analyses.

Methods

Analyses of whole-genome multi-locus sequence typing (wgMLST), using PGAdb-builder, and of fragmented genomes, using Gegenees, were conducted to compare the 80 Brazilian strains to the 18 non-Brazilian genomes. Pangenome analyses and calculations were performed for all Salmonella Infantis genomes analyzed. The presence of prophages was determined using PHASTER for the 80 Brazilian strains. The genome plasticity using BLAST Ring Image Generator (BRIG) and gene synteny using Mauve were evaluated for 20 selected Salmonella Infantis genomes from Brazil and ten from non-Brazilian countries. Unique orthologous protein clusters were searched in ten selected Salmonella Infantis genomes from Brazil and ten from non-Brazilian countries.

Results

wgMLST and Gegenees showed a high genomic similarity among some Brazilian Salmonella Infantis genomes, and also the correlation of some clusters with non-Brazilian genomes. Gegenees also showed an overall similarity >91% among all Salmonella Infantis genomes. Pangenome calculations revealed an open pangenome for all Salmonella Infantis subsets analyzed and a high gene content in the core genomes. Fifteen types of prophages were detected among 97.5% of the Brazilian strains. BRIG and Mauve demonstrated a high structural similarity among the Brazilian and non-Brazilian isolates. Unique orthologous protein clusters related to biological processes, molecular functions, and cellular components were detected among Brazilian and non-Brazilian genomes.

Conclusion

The results presented using different genomic approaches emphasized the significant genomic similarity among Brazilian Salmonella Infantis genomes analyzed, suggesting wide distribution of closely related genotypes among diverse sources in Brazil. The data generated contributed to novel information regarding the genomic diversity of Brazilian and non-Brazilian Salmonella Infantis in comparison. The different genetically related subtypes of Salmonella Infantis from Brazil can either occur exclusively within the country, or also in other countries, suggesting that some exportation of the Brazilian genotypes may have already occurred.

Approaching pathogenic Clostridia from a One Health perspective

Spore-forming pathogens have a unique capacity to thrive in diverse environments, and with temporal persistence afforded through their ability to sporulate. These behaviors require a One Health approach to identify critical reservoirs and outbreak-associated transmission chains, given their capacity to freely move across soils, waterways, foodstuffs, and as commensals or infecting pathogens in human and veterinary populations. Among anaerobic spore-formers, genomic resources for pathogens including C. botulinum, C. difficile, and C. perfringens enable our capacity to identify common and unique factors that support their persistence in diverse reservoirs and capacity to cause disease. Publicly available genomic resources for spore-forming pathogens at NCBI's Pathogen Detection program aid outbreak investigations and longitudinal monitoring in national and international programs in public health and food safety, as well as for local healthcare systems. These tools also enable research to derive new knowledge regarding disease pathogenesis, and to inform strategies in disease prevention and treatment. As global community resources, the continued sharing of strain genomic data and phenotypes further enhances international resources and means to develop impactful applications. We present examples showing use of these resources in surveillance, including capacity to assess linkages among clinical, environmental, and foodborne reservoirs and to further research investigations into factors promoting their persistence and virulence in different settings.

An Alternative Rapid Confirmation Method for Identifying Listeria monocytogenes from a Variety of 125 g Food Samples Within Two Days of a PCR Presumptive Positive

Cultural confirmation following detection of a Listeria monocytogenespresumptive positive can take 3-7 days to finalize; this uncertainty is a point of frustration for food producers needing to make time-sensitive disposition decisions. To address the demand for shortened time-to-results, an alternative L. monocytogenes confirmation method consisting of two components, (i) a secondary screen using a different rapid method, and (ii) concurrent cultural isolation followed by next-day colony identification was evaluated. For the study, four food matrices (hot dogs, peanut butter, frozen vegetables, and multicomponent frozen meals) were inoculated with low levels (0.36-1.39 MPN/125 g) of L. monocytogenes per the AOAC guidelines for a matrix study. Analyses were performed on 125 g test portions and started with a PCR primary screen (Bio-Rad iQ-Check Listeria monocytogenes II). Next, all enriched food samples underwent a secondary screen by bioMérieux's GENE-UP LMO2 Real-Time PCR and VIDAS LMX ELFA along with streaking onto RAPID'L.mono Agar. Presumptive positive L. monocytogenes colonies were identified utilizing a high throughput rapid identification method (Hygiena's BAX System L. monocytogenes Real-Time PCR assay, Neogen's ANSR isothermal nucleic acid amplification assay, and Bruker's MALDI Biotyper). Importantly, this study evaluated multiple commercially available options for the secondary screen (n = 2) and rapid identification (n = 3) to allow for easy adoption by testing laboratories. Overall, there was no statistically significant difference (p ≤ 0.05) between the number of L. monocytogenes-positive 125 g samples obtained by the cultural reference method and the alternative confirmation methods (regardless of which method combinations were evaluated). Additionally, this study supports that, when both the primary and secondary screen methods yield a positive result, the sample could be considered a confirmed positive for L. monocytogenes.

Relevance of gut microbiome research in food safety assessment

The gut microbiome is indispensable for the host physiological functioning. Yet, the impact of non-nutritious dietary compounds on the human gut microbiota and the role of the gut microbes in their metabolism and potential adverse biological effects have been overlooked. Identifying potential hazards and benefits would contribute to protecting and harnessing the gut microbiome's role in supporting human health. We discuss the evidence on the potential detrimental impact of certain food additives and microplastics on the gut microbiome and human health, with a focus on underlying mechanisms and causality. We provide recommendations for the incorporation of gut microbiome science in food risk assessment and identify the knowledge and tools needed to fill these gaps. The incorporation of gut microbiome endpoints to safety assessments, together with well-established toxicity and mutagenicity studies, might better inform the risk assessment of certain contaminants in food, and/or food additives.

Role of Whole Genome Sequencing in Assessing Resident and Transient Listeria monocytogenes in a Produce Packinghouse

Whole genome sequencing (WGS) is a powerful tool that may be used to assist in identifying Listeria contamination sources and movement within environments, and to assess persistence. This study investigated sites in a produce packinghouse where Listeria had been historically isolated; and aimed to characterize dispersal patterns and identify cases of transient and resident Listeria. Environmental swab samples (n = 402) were collected from 67 sites at two time-points on three separate visits. Each sample was tested for Listeria, and Listeria isolates were characterized by partial sigB sequencing to determine species and allelic type (AT). Representative isolates from the three most common L. monocytogenes ATs (n = 79) were further characterized by WGS. Of the 144 Listeria species positive samples (35.8%), L. monocytogenes was the most prevalent species. L. monocytogenes was often coisolated with another species of Listeria. WGS identified cases of sporadic and continued reintroduction of L. monocytogenes from the cold storages into the packinghouse and demonstrated cases of L. monocytogenes persistence over 2 years in cold storages, drains, and on a forklift. Nine distinct clusters were found in this study. Two clusters showed evidence of persistence. Isolates in these two clusters (N = 11, with one historical isolate) were obtained predominantly and over multiple samplings from cold storages, with sporadic movement to sites in the packing area, suggesting residence in cold storages with opportunistic dispersal within the packinghouse. The other seven clusters demonstrated evidence of transient Listeria, as isolation was sporadic over time and space during the packing season. Our data provide important insights into likely L. monocytogenes harborage points and transfer in a packinghouse, which is key to root cause analysis. While results support Listeria spp. as a suitable indicator organism for environmental monitoring surveys, findings were unable to establish a specific species as an index organism for L. monocytogenes. Findings also suggest long-term persistence with substantial SNP diversification, which may assist in identifying potential contamination sources and implementing control measures.

A preliminary study of the use of MinION sequencing to specifically detect Shiga toxin-producing Escherichia coli in culture swipes containing multiple serovars of this species

An important challenge relating to clinical diagnostics of the foodborne pathogen Shiga toxin-producing E. coli (STEC), is that PCR-detection of the shiga-toxin gene (stx) in DNA from stool samples can be accompanied by a failure to identify an STEC isolate in pure culture on agar. In this study, we have explored the use of MinION long-read sequencing of DNA from bacterial culture swipes to detect the presence of STEC, and bioinformatic tools to characterize the STEC virulence factors. The online workflow "What's in my pot" (WIMP) in the Epi2me cloud service, rapidly identified STEC also when it was present in culture swipes together with multiple other E. coli serovars, given sufficient abundance. These preliminary results provide useful information about the sensitivity of the method, which has potential to be used in clinical diagnostic of STEC, particularly in cases where a pure culture of the STEC isolate is not obtained due to the 'STEC lost Shiga toxin' phenomenon.

Rapid geographical source attribution of Salmonella enterica serovar Enteritidis genomes using hierarchical machine learning

Salmonella enterica serovar Enteritidis is one of the most frequent causes of Salmonellosis globally and is commonly transmitted from animals to humans by the consumption of contaminated foodstuffs. In the UK and many other countries in the Global North, a significant proportion of cases are caused by the consumption of imported food products or contracted during foreign travel, therefore, making the rapid identification of the geographical source of new infections a requirement for robust public health outbreak investigations. Herein, we detail the development and application of a hierarchical machine learning model to rapidly identify and trace the geographical source of S. Enteritidis infections from whole genome sequencing data. 2313 S. Enteritidis genomes, collected by the UKHSA between 2014-2019, were used to train a 'local classifier per node' hierarchical classifier to attribute isolates to four continents, 11 sub-regions, and 38 countries (53 classes). The highest classification accuracy was achieved at the continental level followed by the sub-regional and country levels (macro F1: 0.954, 0.718, 0.661, respectively). A number of countries commonly visited by UK travelers were predicted with high accuracy (hF1: >0.9). Longitudinal analysis and validation with publicly accessible international samples indicated that predictions were robust to prospective external datasets. The hierarchical machine learning framework provided granular geographical source prediction directly from sequencing reads in <4 min per sample, facilitating rapid outbreak resolution and real-time genomic epidemiology. The results suggest additional application to a broader range of pathogens and other geographically structured problems, such as antimicrobial resistance prediction, is warranted.

Hybridization chain reaction-assisted enzyme cascade genosensor for the detection of Listeria monocytogenes

Foodborne diseases caused by pathogens may threaten public health and the social economy. We demonstrated a method for identifying pathogenic Listeria monocytogenes using DNA logic operations. To achieve accurate species distinguishing, three specific sequences of Listeria monocytogenes genomic DNA were screened out and used as the feature sequences. Three complementary probes with tag modification were designed as sensing elements and exert affinity for magnetic beads, glucose oxidase (GOx), and horseradish peroxidase (HRP). To obtain a digital output (YES/NO answer) for rapid determination, a Boolean logic function was employed. Three sensing probes enabled the recognition of the target sequence (input) and the formation of a target DNA/probe hybrid. Through magnetic separation and affinity binding events, the target DNA/probes hybrid led to the construction of GOx/HRP enzyme cascade, which produced a visualized color signal (output) in the presence of substrates, glucose, and 3, 3', 5, 5'-tetramethylbenzidine (TMB). A hybridization chain reaction (HCR) was coupled with this sensing scaffold to increase the binding of the enzyme cascade and amplify the output signal. The logical functional biosensor showed high selectivity of Listeria monocytogenes over other Listeria species. This sensing platform provides a simple, sensitive, and highly specific method for detecting Listeria monocytogenes.

Microbiological analysis and characterization of Salmonella and ciprofloxacin-resistant Escherichia coli isolates recovered from retail fresh vegetables in Shaanxi Province, China

Fresh vegetables are closely associated with foodborne disease outbreaks; however, systematic analysis of the microbiological quality of fresh vegetables and molecular information on foodborne pathogens in fresh produce are poorly reported in China. Here, we evaluated the epidemiological prevalence of coliforms via the most probable number method and characterized Salmonella and ciprofloxacin-resistant (CIP^R) Escherichia coli isolates recovered from retail fresh vegetables in Shaanxi Province, China. Antimicrobial susceptibility testing, serotype determination, multilocus sequence typing (MLST), core genome multilocus sequence typing (cgMLST), antibiotic resistance encoding gene (ARG) annotation, virulence factor prediction, and functional classification were performed. Between October 2020 and September 2021, 576 samples (i.e., tomatoes, lettuces, spinaches, and cabbages) were found to be positive for coliforms, and the prevalence of coliforms showed a seasonal trend. Coliform counts of vegetables in supermarkets in Xi'an were significantly lower (P < 0.01) than that in other cities. The detection rates of Salmonella and CIP^RE. coli-positive vegetables were 1 % (6/576) and 0.7 % (4/576), respectively. All isolates exhibited resistance to ≥1 antibiotics, and 92.9 % (13/14) were multidrug-resistant. One extended spectrum β-lactamase (ESBL)-producing CIP^RE. coli isolate in spinach was resistant to not only three third-generation cephalosporins but also to two polymyxins. Among nine Salmonella isolates, five different serovars (S. Enteritidis, S. Indiana, monophasic variant of S. Typhimurium, S. Agona, and S. Gallinarum), four sequence types (STs; ST11, ST13, ST17, and ST34), and seven core genome STs (cgSTs) were identified. Five CIP^RE. coli strains were assigned to three serovars (O101:H4, O8:H18, and O11:H25), three STs (ST44, ST48, and ST457), and four cgSTs. Coexisting amino acid mutations of Thr57Ser/Ser80Arg in ParC and Ser83Phe/Asp87Gly in GyrA in quinolone resistance-determining regions (QRDRs) might be causes for nalidixic acid resistance. Eight definite virulence profiles in eight serovars were identified. Notably, cdtB and pltA only encoded typhoid toxins and were just detected from S. Typhoid isolates were also detected from S. Indiana and monophasic S. Typhimurium, which are closely associated with swine food chain were first detected in fresh vegetables. In conclusion, our findings suggest that coliform contamination on fresh vegetables is prevalent in this province. Most Salmonella and CIP^RE. coli isolates were phenotypically and genetically diverse and could resist multiple antibiotics by carrying multiple ARGs and virulence genes.

Fluorescent Probe Combined with Photoelectric Analysis Technology for Detection of Escherichia coli

Food safety is facing great challenges in preventing foodborne diseases caused by pathogenic pollution, especially in resource-limited areas. The rapid detection technique of microorganisms, such as immunological methods and molecular biological methods, plays a crucial key in timely bioanalysis and disease treatment strategies. However, it is difficult for these methods to simultaneously meet the criteria of simple operation, high specificity, and sensitivity, as well as low cost. Coconut water is known as the "water of life" in Hainan. It is a refreshing and nutritious beverage which is widely consumed due to its beneficial properties to health. Coconut water processing is an important pillar industry in Hainan. The detection of pathogenic microorganisms, such as Escherichia coli, in coconut water has become an important factor which has restricted the upgrading and development of this industry. Based on the needs of industrial development, we developed a microbial photoelectric detection system which was composed of a fluorescent probe detection reagent and a photoelectric sensor detection device. This system combined microbial enzyme targets, selective fluorescent substrate metabolism characteristics, and a photoelectric sensor signal transduction mechanism, which produce a strong signal with a high signal-to-noise ratio. The microbial detection system developed here has a simple structure, simple and convenient operation, short detecting time (≥2 h), and high sensitivity (1 CFU/mL). This system may also enable early warning and monitoring programs for other pathogenic microorganisms in order to promote the overall competitiveness of the Hainan coconut water industry.

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.

Prevalence of efflux pump and heavy metal tolerance encoding genes among Salmonella enterica serovar Infantis strains from diverse sources in Brazil

Salmonella enterica subspecies enterica serovar Infantis (S. Infantis) is a non-typhoid, zoonotic and foodborne serovar with worldwide distribution, and often associated with increasing antimicrobial resistance. Efflux pumps are antimicrobial resistance mechanisms able to promote and increase resistance levels to multiple distinct drug classes. Heavy metal tolerance genes have been demonstrated to promote resistance against these compounds and act in the co-selection of antimicrobial resistant strains. Despite the relevance of S. Infantis in clinical and non-clinical fields, few studies worldwide have investigated the occurrence of such genes in strains from diverse sources. Therefore, the present study aimed at determining the prevalence of antimicrobial efflux pump and heavy metal tolerance genes and their genomic relatedness through core-genome multi-locus sequence typing (cgMLST) of 80 S. Infantis strains isolated from food, environmental, human and animal sources from 2013 to 2018 in Brazil. Twenty efflux pump encoding genes were detected, with 17 of these (acrA, acrB, baeR, crp, emrB, emrR, hns, kdpE, kpnF, marA, marR, mdtK, msbA, rsmA, sdiA, soxR and soxS) detected in all strains studied, golS in 98.75%, mdfA in 58.75% and tet(A) in 37.5%. Tolerance genes to arsenic (arsR) were detected in 100% of the strains, gold (golS and golT) in 98.75%, silver (silABCDEFPRS) in 36.25% and mercury (merR and merT) in 1.25%. cgMLST demonstrated a closer genetic relationship among strains harboring similar profiles of heavy metal and efflux pump encoding genes, despite their origin. In conclusion, the high prevalence of some efflux pump and heavy metal tolerance encoding genes alert us about the importance of strong surveillance measures to monitor resistance and the transmission of S. Infantis among diverse sources in Brazil.

Metataxonomic sequencing to assess microbial safety of Turkish white cheeses

High-throughput sequencing has provided a way to monitor the large diversity of microorganisms in fermented foods that have complex microbiota. Up to date, many kinds of cheese have been characterized with the metataxonomic approach, but the safety of unpacked Turkish white cheeses, which are widely consumed in Turkey, has not been assessed. In this study, fifteen unpacked white cheeses sold in public bazaars in Ankara province have been collected and subjected to microbial enumeration as well as physicochemical analysis. Five white cheeses, which have relatively the highest foodborne pathogens, out of fifteen white cheeses, have been analyzed by next-generation sequencing and metataxonomic analysis. According to the results, abundant families were Lactobacillaceae, Oceanospirillaceae, Enterococcaceae, Pseudomonadaceae, and Vibrionaceae. Staphylococcus aureus, E. coli, and Salmonella, which are indicators of bad hygiene and sanitation conditions, were found in cheeses. In conclusion, culture-independent methods such as metataxonomic can be important to evaluate the safety of foods.

Curation of the AMRFinderPlus databases: applications, functionality and impact

Antimicrobial resistance (AMR) is a significant public health threat. Low-cost whole-genome sequencing, which is often used in surveillance programmes, provides an opportunity to assess AMR gene content in these genomes using in silico approaches. A variety of bioinformatic tools have been developed to identify these genomic elements. Most of those tools rely on reference databases of nucleotide or protein sequences and collections of models and rules for analysis. While the tools are critical for the identification of AMR genes, the databases themselves also provide significant utility for researchers, for applications ranging from sequence analysis to information about AMR phenotypes. Additionally, these databases can be evaluated by domain experts and others to ensure their accuracy. Here we describe how we curate the genes, point mutations and blast rules, and hidden Markov models used in NCBI’s AMRFinderPlus, along with the quality-control steps we take to ensure database quality. We also describe the web interfaces that display the full structure of the database and their newly developed cross-browser relationships. Then, using the Reference Gene Catalog as an example, we detail how the databases, rules and models are made publicly available, as well as how to access the software. In addition, as part of the Pathogen Detection system, we have analysed over 1 million publicly available genomes using AMRFinderPlus and its databases. We discuss how the computed analyses generated by those tools can be accessed through a web interface. Finally, we conclude with NCBI’s plans to make these databases accessible over the long-term.

Frozen Vegetable Processing Plants Can Harbour Diverse Listeria monocytogenes Populations: Identification of Critical Operations by WGS

Frozen vegetables have emerged as a concern due to their association with foodborne outbreaks such as the multi-country outbreak of Listeria monocytogenes serogroup IVb linked to frozen corn. The capacity of L. monocytogenes to colonize food-processing environments is well-known, making the bacteria a real problem for consumers. However, the significance of the processing environment in the contamination of frozen foods is not well established. This study aimed to identify potential contamination niches of L. monocytogenes in a frozen processing plant and characterize the recovered isolates. A frozen vegetable processing plant was monitored before cleaning activities. A total of 78 points were sampled, including frozen vegetables. Environmental samples belonged to food-contact surfaces (FCS); and non-food-contact surfaces (n-FCS). Positive L. monocytogenes samples were found in FCS (n = 4), n-FCS (n = 9), and the final product (n = 1). A whole-genome sequencing (WGS) analysis revealed two clusters belonging to serotypes 1/2a-3a and 1/2b-3b). The genetic characterization revealed the presence of four different sequence types previously detected in the food industry. The isolate obtained from the final product was the same as one isolate found in n-FCS. A multi-virulence-locus sequence typing (MVLST) analysis showed four different virulence types (VT). The results obtained highlight the relevant role that n-FCS such as floors and drains can play in spreading L. monocytogenes contamination to the final product.

Rapid Multilateral and Integrated Public Health Response to a Cross-City Outbreak of Salmonella Enteritidis Infections Combining Analytical, Molecular, and Genomic Epidemiological Analysis

On September 21, 2019, the Shenzhen and Dongguan Centers for Disease Control and Prevention received notification of a large cluster of suspected gastroenteritis involving primarily children who sought medical care at hospitals throughout two adjacent cities in China, Shenzhen, and Dongguan. A joint outbreak response was promptly initiated across jurisdictions in a concerted effort between clinical microbiologists, epidemiologists, and public health scientists. Concurrently, multiplex PCRs were used for rapid laboratory diagnosis of suspected cases; epidemiological investigations were conducted to identify the outbreak source, complemented by near real-time multicenter whole-genome analyses completed within 34 h. Epidemiological evidence indicated that all patients had consumed egg sandwiches served on September 20 as snacks to children and staff at a nursery in Dongguan, located near Shenzhen. Salmonella Enteritidis was isolated from case-patients, food handlers, kitchenware, and sandwiches with kitchen-made mayonnaise. Whole-genome single-nucleotide polymorphism (SNP)-based phylogenetic analysis demonstrated a well-supported cluster with pairwise distances of ≤1 SNP between genomes for outbreak-associated isolates, providing the definitive link between all samples. In comparison with historical isolates from the same geographical region, the minimum pairwise distance was >14 SNPs, suggesting a non-local outbreak source. Genomic source tracing revealed the possible transmission dynamics of a S. Enteritidis clone throughout a multi-provincial egg distribution network. The efficiency and scale with which multidisciplinary and integrated approaches were coordinated in this foodborne disease outbreak response was unprecedented in China, leading to the timely intervention of a large cross-jurisdiction Salmonella outbreak.

Application of Nanopore Sequencing in the Detection of Foodborne Microorganisms

Foodborne pathogens have become the subject of intense interest because of their high incidence and mortality worldwide. In the past few decades, people have developed many methods to solve this challenge. At present, methods such as traditional microbial culture methods, nucleic acid or protein-based pathogen detection methods, and whole-genome analysis are widely used in the detection of pathogenic microorganisms in food. However, these methods are limited by time-consuming, cumbersome operations or high costs. The development of nanopore sequencing technology offers the possibility to address these shortcomings. Nanopore sequencing, a third-generation technology, has the advantages of simple operation, high sensitivity, real-time sequencing, and low turnaround time. It can be widely used in the rapid detection and serotyping of foodborne pathogens. This review article discusses foodborne diseases, the principle of nanopore sequencing technology, the application of nanopore sequencing technology in foodborne pathogens detection, as well as its development prospects.

Use of Whole Genome Sequencing by the Federal Interagency Collaboration for Genomics for Food and Feed Safety in the United States

ABSTRACT

This multiagency report developed by the Interagency Collaboration for Genomics for Food and Feed Safety provides an overview of the use of and transition to whole genome sequencing (WGS) technology for detection and characterization of pathogens transmitted commonly by food and for identification of their sources. We describe foodborne pathogen analysis, investigation, and harmonization efforts among the following federal agencies: National Institutes of Health; Department of Health and Human Services, Centers for Disease Control and Prevention (CDC) and U.S. Food and Drug Administration (FDA); and the U.S. Department of Agriculture, Food Safety and Inspection Service, Agricultural Research Service, and Animal and Plant Health Inspection Service. We describe single nucleotide polymorphism, core-genome, and whole genome multilocus sequence typing data analysis methods as used in the PulseNet (CDC) and GenomeTrakr (FDA) networks, underscoring the complementary nature of the results for linking genetically related foodborne pathogens during outbreak investigations while allowing flexibility to meet the specific needs of Interagency Collaboration partners. We highlight how we apply WGS to pathogen characterization (virulence and antimicrobial resistance profiles) and source attribution efforts and increase transparency by making the sequences and other data publicly available through the National Center for Biotechnology Information. We also highlight the impact of current trends in the use of culture-independent diagnostic tests for human diagnostic testing on analytical approaches related to food safety and what is next for the use of WGS in the area of food safety.

HIGHLIGHTS

Antibiogram signatures of Vibrio species recovered from surface waters in South Western districts of Uganda: Implications for environmental pollution and infection control

Reports of vibriosis and other related gastrointestinal infections have remained a recurring concern in the diverse global continent. The safety of drinking surface water and associated environmental pollution has remained a public health concern in limited resource sittings. Seen in this light, we report the antibiogram signatures of Vibrio species recovered from surface waters in the South-Western districts of Uganda. Surface water samples were collected for four months for Vibrio species isolation in four districts (Bushenyi-B, Mitooma-M, Rubirizi-R, and Sheema-S) using bacteria culture procedures, disc diffusion and Polymerase Chain Reaction (PCR) technique. Isolates were characterised, and the antibiotic fingerprints were determined using PCR and nine selected antibiotics in routine use. A total of 392 Vibrio species were confirmed from the various districts (B: 172, M: 79. R: 60, S: 81), with 163 (94.77%) resistant to colistin (polymixin), 145 (84.3%) resistant to cefotaxime, 127 (73.84%) resistant to azithromycin, and 33 (19.19%) resistant to chloramphenicol among Bushenyi isolates. A similar high resistance to fluoroquinolones and carbapenem antibiotics were also recorded in other districts of the study area. A complete multiple antibiotic resistance phenotype ((M)ARPs) to the applied antibiotics (A-CTX-CXM-MEM-ATH-K-TM-C-PB-NI-CIP-NA) were also recorded among some isolates, which produced multiple antibiotic resistance indexes of 1, suggesting a high-risk source of contamination due to the usage of several antibiotics. The PCR reports also confirm ampC gene {20 (10.9%)}, beta-lactamase TEM gene (blaTEM2), {30 (10%)} and dihydropteroate synthase type-1 and 11 gene (sul 1 & 11) {16 (8%)}. The results present an implicated environmental pollution problem and a potential concern to public health, therefore there is the need for control of such infectious bacteria and environmental pollution monitoring. Hence, it is recommended various approaches crucial to monitoring of emerging trends in drug resistance at the local and international levels.

Salmonella Genomics in Public Health and Food Safety

The species Salmonella enterica comprises over 2,600 serovars, many of which are known to be intracellular pathogens of mammals, birds, and reptiles. It is now apparent that Salmonella is a highly adapted environmental microbe and can readily persist in a number of environmental niches, including water, soil, and various plant (including produce) species. Much of what is known about the evolution and diversity of nontyphoidal Salmonella serovars (NTS) in the environment is the result of the rise of the genomics era in enteric microbiology. There are over 340,000 Salmonella genomes available in public databases. This extraordinary breadth of genomic diversity now available for the species, coupled with widespread availability and affordability of whole-genome sequencing (WGS) instrumentation, has transformed the way in which we detect, differentiate, and characterize Salmonella enterica strains in a timely way. Not only have WGS data afforded a detailed and global examination of the molecular epidemiological movement of Salmonella from diverse environmental reservoirs into human and animal hosts, but they have also allowed considerable consolidation of the diagnostic effort required to test for various phenotypes important to the characterization of Salmonella. For example, drug resistance, serovar, virulence determinants, and other genome-based attributes can all be discerned using a genome sequence. Finally, genomic analysis, in conjunction with functional and phenotypic approaches, is beginning to provide new insights into the precise adaptive changes that permit persistence of NTS in so many diverse and challenging environmental niches.

Evaluation of WGS performance for bacterial pathogen characterization with the Illumina technology optimized for time-critical situations

Whole genome sequencing (WGS) has become the reference standard for bacterial outbreak investigation and pathogen typing, providing a resolution unattainable with conventional molecular methods. Data generated with Illumina sequencers can however only be analysed after the sequencing run has finished, thereby losing valuable time during emergency situations. We evaluated both the effect of decreasing overall run time, and also a protocol to transfer and convert intermediary files generated by Illumina sequencers enabling real-time data analysis for multiple samples part of the same ongoing sequencing run, as soon as the forward reads have been sequenced. To facilitate implementation for laboratories operating under strict quality systems, extensive validation of several bioinformatics assays (16S rRNA species confirmation, gene detection against virulence factor and antimicrobial resistance databases, SNP-based antimicrobial resistance detection, serotype determination, and core genome multilocus sequence typing) for three bacterial pathogens (Mycobacterium tuberculosis , Neisseria meningitidis , and Shiga-toxin producing Escherichia coli ) was performed by evaluating performance in function of the two most critical sequencing parameters, i.e. read length and coverage. For the majority of evaluated bioinformatics assays, actionable results could be obtained between 14 and 22 h of sequencing, decreasing the overall sequencing-to-results time by more than half. This study aids in reducing the turn-around time of WGS analysis by facilitating a faster response in time-critical scenarios and provides recommendations for time-optimized WGS with respect to required read length and coverage to achieve a minimum level of performance for the considered bioinformatics assay(s), which can also be used to maximize the cost-effectiveness of routine surveillance sequencing when response time is not essential.

The Persistence of Bacterial Pathogens in Surface Water and Its Impact on Global Food Safety

Water is vital to agriculture. It is essential that the water used for the production of fresh produce commodities be safe. Microbial pathogens are able to survive for extended periods of time in water. It is critical to understand their biology and ecology in this ecosystem in order to develop better mitigation strategies for farmers who grow these food crops. In this review the prevalence, persistence and ecology of four major foodborne pathogens, Shiga toxin-producing Escherichia coli (STEC), Salmonella, Campylobacter and closely related Arcobacter, and Listeria monocytogenes, in water are discussed. These pathogens have been linked to fresh produce outbreaks, some with devastating consequences, where, in a few cases, the contamination event has been traced to water used for crop production or post-harvest activities. In addition, antimicrobial resistance, methods improvements, including the role of genomics in aiding in the understanding of these pathogens, are discussed. Finally, global initiatives to improve our knowledge base of these pathogens around the world are touched upon.

Microbial colonization and resistome dynamics in food processing environments of a newly opened pork cutting industry during 1.5 years of activity

BACKGROUND

The microorganisms that inhabit food processing environments (FPE) can strongly influence the associated food quality and safety. In particular, the possibility that FPE may act as a reservoir of antibiotic-resistant microorganisms, and a hotspot for the transmission of antibiotic resistance genes (ARGs) is a concern in meat processing plants. Here, we monitor microbial succession and resistome dynamics relating to FPE through a detailed analysis of a newly opened pork cutting plant over 1.5 years of activity.

RESULTS

We identified a relatively restricted principal microbiota dominated by Pseudomonas during the first 2 months, while a higher taxonomic diversity, an increased representation of other taxa (e.g., Acinetobacter, Psychrobacter), and a certain degree of microbiome specialization on different surfaces was recorded later on. An increase in total abundance, alpha diversity, and β-dispersion of ARGs, which were predominantly assigned to Acinetobacter and associated with resistance to certain antimicrobials frequently used on pig farms of the region, was detected over time. Moreover, a sharp increase in the occurrence of extended-spectrum β-lactamase-producing Enterobacteriaceae and vancomycin-resistant Enterococcaceae was observed when cutting activities started. ARGs associated with resistance to β-lactams, tetracyclines, aminoglycosides, and sulphonamides frequently co-occurred, and mobile genetic elements (i.e., plasmids, integrons) and lateral gene transfer events were mainly detected at the later sampling times in drains.

CONCLUSIONS

The observations made suggest that pig carcasses were a source of resistant bacteria that then colonized FPE and that drains, together with some food-contact surfaces, such as equipment and table surfaces, represented a reservoir for the spread of ARGs in the meat processing facility. Video Abstract.

Heuristic and Hierarchical-Based Population Mining of Salmonella enterica Lineage I Pan-Genomes as a Platform to Enhance Food Safety

The recent incorporation of bacterial whole-genome sequencing (WGS) into Public Health laboratories has enhanced foodborne outbreak detection and source attribution. As a result, large volumes of publicly available datasets can be used to study the biology of foodborne pathogen populations at an unprecedented scale. To demonstrate the application of a heuristic and agnostic hierarchical population structure guided pan-genome enrichment analysis (PANGEA), we used populations of S. enterica lineage I to achieve two main objectives: (i) show how hierarchical population inquiry at different scales of resolution can enhance ecological and epidemiological inquiries; and (ii) identify population-specific inferable traits that could provide selective advantages in food production environments. Publicly available WGS data were obtained from NCBI database for three serovars of Salmonella enterica subsp. enterica lineage I (S. Typhimurium, S. Newport, and S. Infantis). Using the hierarchical genotypic classifications (Serovar, BAPS1, ST, cgMLST), datasets from each of the three serovars showed varying degrees of clonal structuring. When the accessory genome (PANGEA) was mapped onto these hierarchical structures, accessory loci could be linked with specific genotypes. A large heavy-metal resistance mobile element was found in the Monophasic ST34 lineage of S. Typhimurium, and laboratory testing showed that Monophasic isolates have on average a higher degree of copper resistance than the Biphasic ones. In S. Newport, an extra sugE gene copy was found among most isolates of the ST45 lineage, and laboratory testing of multiple isolates confirmed that isolates of S. Newport ST45 were on average less sensitive to the disinfectant cetylpyridimium chloride than non-ST45 isolates. Lastly, data-mining of the accessory genomic content of S. Infantis revealed two cryptic Ecotypes with distinct accessory genomic content and distinct ecological patterns. Poultry appears to be the major reservoir for Ecotype 1, and temporal analysis further suggested a recent ecological succession, with Ecotype 2 apparently being displaced by Ecotype 1. Altogether, the use of a heuristic hierarchical-based population structure analysis that includes bacterial pan-genomes (core and accessory genomes) can (1) improve genomic resolution for mapping populations and accessing epidemiological patterns; and (2) define lineage-specific informative loci that may be associated with survival in the food chain.

Analysis of the antimicrobial resistance gene frequency in whole-genome sequenced Vibrio from Latin American countries

Vibrio species are important environmental-related bacteria responsible for diverse infections in humans due to consumption of contaminated water and seafood in underdeveloped areas of the world. This study aimed to investigate the frequency of antimicrobial resistance genes in 577 sequenced Vibrio cholerae, Vibrio parahaemolyticus and Vibrio vulnificus strains isolated in Latin American countries available at the NCBI Pathogen Detection database and to determine the sequence type (ST) of the strains. Almost all strains studied (99.8%) carried at least one antimicrobial resistance gene, while 54.2 % presented a multidrug-resistance profile. The Vibrio strains exhibited genotypic resistance to 11 antimicrobial classes and almG, varG, and catB9, which confer resistance to antibiotic peptides, β-lactams and amphenicols, respectively, were the most detected genes. Vibrio parahaemolyticus and V. vulnificus showed a broad diversity of STs. Vibrio cholerae strains isolated in Haiti after 2010's earthquake presented the highest diversity and amount of resistance genes in the set of strains analysed and mostly belonged to ST69. In conclusion, the detection of resistance genes from 11 antimicrobial classes and the high number of multidrug-resistant Vibrio species strains emphasize that Latin American public health authorities should employ more efficient control measures and that special attention should be given for the rational use of antimicrobials in human therapy and aquaculture, since the consumption of contaminated water and seafood with resistant Vibrio may result in human infections difficult to be treated.

SAUTE: sequence assembly using target enrichment

Background

Illumina is the dominant sequencing technology at this time. Short length, short insert size, some systematic biases, and low-level carryover contamination in Illumina reads continue to make assembly of repeated regions a challenging problem. Some applications also require finding multiple well supported variants for assembled regions.

Results

To facilitate assembly of repeat regions and to report multiple well supported variants when a user can provide target sequences to assist the assembly, we propose SAUTE and SAUTE_PROT assemblers. Both assemblers use de Bruijn graph on reads. Targets can be transcripts or proteins for RNA-seq reads and transcripts, proteins, or genomic regions for genomic reads. Target sequences are nucleotide and protein sequences for SAUTE and SAUTE_PROT, respectively.

Conclusions

For RNA-seq, comparisons with Trinity, rnaSPAdes, SPAligner, and SPAdes assembly of reads aligned to target proteins by DIAMOND show that SAUTE_PROT finds more coding sequences that translate to benchmark proteins. Using AMRFinderPlus calls, we find SAUTE has higher sensitivity and precision than SPAdes, plasmidSPAdes, SPAligner, and SPAdes assembly of reads aligned to target regions by HISAT2. It also has better sensitivity than SKESA but worse precision.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04174-9.

Microbial Food Safety in China: Past, Present, and Future

Food safety is a major public health issue worldwide, especially in heavily populated countries such as China. As in other countries, the predominant food safety issues in China are foodborne diseases caused by microbial pathogens. Hence, this review provides a systematic overview on microbial food safety in the past, present, and future in China. Management of microbial food safety in China is generally divided into three stages: Stage I before 2000, Stage II from 2000 to 2009, and Stage III from 2010 to present. At Stage I, China's main food concern gradually shifted from food security to food safety. At Stage II, foodborne pathogen surveillance was initiated and gradually became a focus of microbial food safety marked by the establishment of national food contamination monitoring system in 2000 and the promulgation of China Food Safety Law in 2009, although chemical food safety was considered a priority issue during this stage. At Stage III, microbial food safety was recognized as a high priority supported by many national food safety policies such as the launch of a national foodborne disease molecular tracing network in 2013 and the revision of China Food Safety Law in 2015. Advancement in food safety education and research support by central and local governments has also made significant contributions to tackling and solving microbial food safety problems. Management in the future should be focused on active involvement of food industries in mitigating microbial risks by introducing ISO 22000, regulatory enforcement to oversee compliances to standards and rules, and application of molecular tools for fast detection and source tracking to support decision-making. Future research efforts may include, but are not limited to, exploitation of interaction mechanisms among pathogenic bacteria, food and gut microbiota, smart traceability of microbial hazards, and development of novel antimicrobial strategies.

AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence

Antimicrobial resistance (AMR) is a significant public health threat. With the rise of affordable whole genome sequencing, in silico approaches to assessing AMR gene content can be used to detect known resistance mechanisms and potentially identify novel mechanisms. To enable accurate assessment of AMR gene content, as part of a multi-agency collaboration, NCBI developed a comprehensive AMR gene database, the Bacterial Antimicrobial Resistance Reference Gene Database and the AMR gene detection tool AMRFinder. Here, we describe the expansion of the Reference Gene Database, now called the Reference Gene Catalog, to include putative acid, biocide, metal, stress resistance genes, in addition to virulence genes and species-specific point mutations. Genes and point mutations are classified by broad functions, as well as more detailed functions. As we have expanded both the functional repertoire of identified genes and functionality, NCBI released a new version of AMRFinder, known as AMRFinderPlus. This new tool allows users the option to utilize only the core set of AMR elements, or include stress response and virulence genes, too. AMRFinderPlus can detect acquired genes and point mutations in both protein and nucleotide sequence. In addition, the evidence used to identify the gene has been expanded to include whether nucleotide or protein sequence was used, its location in the contig, and presence of an internal stop codon. These database improvements and functional expansions will enable increased precision in identifying AMR genes, linking AMR genotypes and phenotypes, and determining possible relationships between AMR, virulence, and stress response.

How Broad Is Enough: The Host Range of Bacteriophages and Its Impact on the Agri-Food Sector

Novel bacteriophages (phages) possessing a broad host range are consistently and routinely reported, yet there is presently no consensus on the definition of "broad host range." As phages are increasingly being used in the development of methods for the detection and biocontrol of human pathogens, it is important to address the limitations associated with the host range. For instance, unanticipated host range breadth may result in the detection of nonpathogenic targets, thereby increasing the false-positive rate. Moreover, a broad host range is generally favored in biocontrol applications despite the risk of undesirable ancillary effects against nontarget species. Here, we discuss the research progress, applications, and implications of broad host range phages with a focus on tailed broad host range phages infecting human pathogens of concern in the Agri-Food sector.

A Bioinformatics Whole-Genome Sequencing Workflow for Clinical Mycobacterium tuberculosis Complex Isolate Analysis, Validated Using a Reference Collection Extensively Characterized with Conventional Methods and In Silico Approaches

The use of whole-genome sequencing (WGS) for routine typing of bacterial isolates has increased substantially in recent years. For Mycobacterium tuberculosis (MTB), in particular, WGS has the benefit of drastically reducing the time required to generate results compared to most conventional phenotypic methods. Consequently, a multitude of solutions for analyzing WGS MTB data have been developed, but their successful integration in clinical and national reference laboratories is hindered by the requirement for their validation, for which a consensus framework is still largely absent. We developed a bioinformatics workflow for (Illumina) WGS-based routine typing of MTB complex (MTBC) member isolates allowing complete characterization, including (sub)species confirmation and identification (16S, csb/RD, hsp65), single nucleotide polymorphism (SNP)-based antimicrobial resistance (AMR) prediction, and pathogen typing (spoligotyping, SNP barcoding, and core genome multilocus sequence typing). Workflow performance was validated on a per-assay basis using a collection of 238 in-house-sequenced MTBC isolates, extensively characterized with conventional molecular biology-based approaches supplemented with public data. For SNP-based AMR prediction, results from molecular genotyping methods were supplemented with in silico modified data sets, allowing us to greatly increase the set of evaluated mutations. The workflow demonstrated very high performance with performance metrics of >99% for all assays, except for spoligotyping, where sensitivity dropped to ∼90%. The validation framework for our WGS-based bioinformatics workflow can aid in the standardization of bioinformatics tools by the MTB community and other SNP-based applications regardless of the targeted pathogen(s). The bioinformatics workflow is available for academic and nonprofit use through the Galaxy instance of our institute at https://galaxy.sciensano.be.

Perspective on Clinically-Relevant Antimicrobial Resistant Enterobacterales in Food: Closing the Gaps Using Genomics

Antimicrobial resistance is one of the most important public health concerns—it causes 700,000 deaths annually according to the World Health Organization (WHO). Enterobacterales such as E. coli and Klebsiella pneumoniae, have become resistant to many relevant antimicrobials including carbapenems and extended spectrum cephalosporins. These clinically relevant resistant Enterobacterales (CRRE) members are now globally distributed in the environment including different food types (meats, produce, dairy). Unlike known foodborne pathogens, CRRE are not usually part of most food surveillance systems. However, numerous reports of CRRE highlight the importance of these bacteria in food and have been shown to contribute to the overall crisis of antimicrobial resistance. This is especially important in the context of carriage of these pathogens by immuno-compromised individuals. CRRE infections upon consumption of contaminated food could colonize the human gastrointestinal tract and eventually be a source of systemic infections such as urinary tract infections or septicemia. While different aspects need to be considered to elucidate this, whole genome sequencing along with metadata could be used to understand genomic relationships of CRRE obtained from foods and humans, including isolates from clinical infections. Once robust scientific data is available on the role of CRRE in food, countries could move forward to better survey and control CRRE in food.

Genomics of Environmental Salmonella: Engaging Students in the Microbiology and Bioinformatics of Foodborne Pathogens

We have developed and implemented an undergraduate microbiology course in which students isolate, characterize, and perform whole genome assembly and analysis of Salmonella enterica from stream sediments and poultry litter. In the development of the course and over three semesters, successive teams of undergraduate students collected field samples and performed enrichment and isolation techniques specific for the detection of S. enterica. Eighty-eight strains were confirmed using standard microbiological methods and PCR of the invA gene. The isolates' genomes were Illumina-sequenced by the Center for Food Safety and Applied Nutrition at the FDA and the Virginia state Division of Consolidated Laboratory Services as part of the GenomeTrakr program. Students used GalaxyTrakr and other web- and non-web-based platforms and tools to perform quality control on raw and assembled sequence data, assemble, and annotate genomes, identify antimicrobial resistance and virulence genes, putative plasmids, and other mobile genetic elements. Strains with putative plasmid-borne antimicrobial resistance genes were further sequenced by students in our research lab using the Oxford Nanopore MinIONTM platform. Strains of Salmonella that were isolated include human infectious serotypes such as Typhimurium and Infantis. Over 31 of the isolates possessed antibiotic resistance genes, some of which were located on large, multidrug resistance plasmids. Plasmid pHJ-38, identified in a Typhimurium isolate, is an apparently self-transmissible 183 kb IncA/C2 plasmid that possesses multiple antimicrobial resistance and heavy-metal resistance genes. Plasmid pFHS-02, identified in an Infantis isolate, is an apparently self-transmissible 303 kb IncF1B plasmid that also possesses numerous heavy-metal and antimicrobial resistance genes. Using direct and indirect measures to assess student outcomes, results indicate that course participation contributed to cognitive gains in relevant content knowledge and research skills such as field sampling, molecular techniques, and computational analysis. Furthermore, participants self-reported a deeper interest in scientific research and careers as well as psychosocial outcomes (e.g., sense of belonging and self-efficacy) commonly associated with student success and persistence in STEM. Overall, this course provided a powerful combination of field, wet lab, and computational biology experiences for students, while also providing data potentially useful in pathogen surveillance, epidemiological tracking, and for the further study of environmental reservoirs of S. enterica.

Rapid Open-Source SNP-Based Clustering Offers an Alternative to Core Genome MLST for Outbreak Tracing in a Hospital Setting

Traditional genotyping methods for infection control of antimicrobial-resistant bacteria in healthcare settings have been supplemented by whole-genome sequencing (WGS), often relying on a gene-based approach, e.g., core genome multilocus sequence typing (cgMLST), to cluster-related samples. In this study, we compared clusters of methicillin-resistant Staphylococcus aureus (MRSA) and Enterococcus faecium analyzed with the commercial cgMLST software Ridom SeqSphere+ and with an open-source single-nucleotide polymorphism (SNP)-based phylogenetic analysis pipeline (PAPABAC). A total of 5,655 MRSA and 2,572 E. faecium patient isolates, collected between 2013 and 2018, were processed. Clusters of 1,844 MRSA and 1,355 E. faecium isolates were compared to cgMLST results, and epidemiological data were included when available. The phylogenies inferred by the two different technologies were highly concordant, and the MRSA SNP tree re-captured known hospital-related outbreaks and epidemiologically linked samples. PAPABAC has the advantage over Ridom SeqSphere+ to generate stable, referable clusters without the need for sequence assembly, and it is a free-of-charge, open-source alternative to the commercial software.

Choice of library preparation affects sequence quality, genome assembly, and precise in silico prediction of virulence genes in shiga toxin-producing Escherichia coli

Whole genome sequencing (WGS) provides essential public health information and is used worldwide for pathogen surveillance, epidemiology, and source tracking. Foodborne pathogens are often sequenced using rapid library preparation chemistries based on transposon technology; however, this method may miss random segments of genomes that can be important for accurate downstream analyses. As new technologies become available, it may become possible to achieve better overall coverage. Here we compare the sequence quality obtained using libraries prepared from the Nextera XT and Nextera DNA Prep (Illumina, San Diego, CA) chemistries for 31 Shiga toxin-producing Escherichia coli (STEC) O121:H19 strains, which had been isolated from flour during a 2016 outbreak. The Nextera DNA Prep gave superior performance metrics including sequence quality, assembly quality, uniformity of genome coverage, and virulence gene identification, among other metrics. Comprehensive detection of virulence genes is essential for making educated assessments of STECs virulence potential. The phylogenetic SNP analysis did not show any differences in the variants detected by either library preparation method which allows isolates prepared from either library method to be analysed together. Our comprehensive comparison of these chemistries should assist researchers wishing to improve their sequencing workflow for STECs and other genomic risk assessments.

Cost of whole genome sequencing for non-typhoidal Salmonella enterica

Background

While whole genome sequencing (WGS) may be more expensive than traditional testing and polymerase chain reaction (PCR), simple cost comparisons ignore the potential for WGS to reduce the societal costs of non-typhoidal Salmonella enterica through public health action to prevent illness.

Methods

We determined how many cases the use of WGS data would need to prevent to be cost-equal to serotyping and MLVA, or culture independent testing based on PCR in Australia. We then examined the costs and cost-savings of current typing methods compared with WGS in outbreak scenarios.

Results

A median of 275 (90% CrI -55-775) or 1.9% (90% CrI -0.4%-5.4%) of notified serotyped Salmonella cases would need to be prevented for WGS to be cost-equal to current typing methods and 1,550 (90% CrI 820–2,725) or 9.6% of all notified Salmonella cases would need to be prevented to be cost-equal to PCR. WGS is likely to result in cost savings in prolonged outbreaks, where data can support earlier public health action.

Conclusions

Despite currently having a higher cost per isolate, routine WGS of Salmonella was no more expensive than existing typing methods or PCR where >2% of illness was averted.

Complete Whole Genome Sequences of Escherichia coli Surrogate Strains and Comparison of Sequence Methods with Application to the Food Industry

In 2013, the U.S. Department of Agriculture Food Safety and Inspection Service (USDA-FSIS) began transitioning to whole genome sequencing (WGS) for foodborne disease outbreak- and recall-associated isolate identification of select bacterial species. While WGS offers greater precision, certain hurdles must be overcome before widespread application within the food industry is plausible. Challenges include diversity of sequencing platform outputs and lack of standardized bioinformatics workflows for data analyses. We sequenced DNA from USDA-FSIS approved, non-pathogenic E. coli surrogates and a derivative group of rifampicin-resistant mutants (rif^R) via both Oxford Nanopore MinION and Illumina MiSeq platforms to generate and annotate complete genomes. Genome sequences from each clone were assembled separately so long-read, short-read, and combined sequence assemblies could be directly compared. The combined sequence data approach provides more accurate completed genomes. The genomes from these isolates were verified to lack functional key E. coli elements commonly associated with pathogenesis. Genetic alterations known to confer rif^R were also identified. As the food industry adopts WGS within its food safety programs, these data provide completed genomes for commonly used surrogate strains, with a direct comparison of sequence platforms and assembly strategies relevant to research/testing workflows applicable for both processors and regulators.

Comparison of MiSeq, MinION, and hybrid genome sequencing for analysis of Campylobacter jejuni

The sequencing, assembly, and analysis of bacterial genomes is central to tracking and characterizing foodborne pathogens. The bulk of bacterial genome sequencing at the US Food and Drug Administration is performed using short-read Illumina MiSeq technology, resulting in highly accurate but fragmented genomic sequences. The MinION sequencer from Oxford Nanopore is an evolving technology that produces long-read sequencing data with low equipment cost. The goal of this study was to compare Campylobacter genome assemblies generated from MiSeq and MinION data independently, as well as hybrid genome assemblies combining both data types. Two reference strains and two field isolates of C. jejuni were sequenced using MiSeq and MinION, and the sequence data were assembled using the software programs SPAdes and Canu, respectively. Hybrid genome assembly was performed using the program Unicycler. Comparison of the C. jejuni 81-176 and RM1221 genome assemblies to the PacBio reference genomes revealed that the SPAdes assemblies had the most accurate nucleotide identity, while the hybrid assemblies were the most contiguous. Assemblies generated only from MinION data using Canu were the least accurate, containing many indels and substitutions that affected downstream analyses. The hybrid sequencing approach was the most useful for detecting plasmids, large genome rearrangements, and repetitive elements such as rRNA and tRNA genes. The full genomes of both C. jejuni field isolates were completed and circularized using hybrid sequencing, and a plasmid was detected in one isolate. Continued development of nanopore sequencing technologies will likely enhance the accuracy of hybrid genome assemblies and enable public health laboratories to routinely generate complete circularized bacterial genome sequences.