High Throughput Sequencing for Detection of Foodborne Pathogens

Diverse patterns of correspondence between protist metabarcodes and protist metagenome-assembled genomes

Two common approaches to study the composition of environmental protist communities are metabarcoding and metagenomics. Raw metabarcoding data are usually processed into Operational Taxonomic Units (OTUs) or amplicon sequence variants (ASVs) through clustering or denoising approaches, respectively. Analogous approaches are used to assemble metagenomic reads into metagenome-assembled genomes (MAGs). Understanding the correspondence between the data produced by these two approaches can help to integrate information between the datasets and to explain how metabarcoding OTUs and MAGs are related with the underlying biological entities they are hypothesised to represent. MAGs do not contain the commonly used barcoding loci, therefore sequence homology approaches cannot be used to match OTUs and MAGs. We made an attempt to match V9 metabarcoding OTUs from the 18S rRNA gene (V9 OTUs) and MAGs from the Tara Oceans expedition based on the correspondence of their relative abundances across the same set of samples. We evaluated several metrics for detecting correspondence between features in these two datasets and developed controls to filter artefacts of data structure and processing. After selecting the best-performing metrics, ranking the V9 OTU/MAG matches by their proportionality/correlation coefficients and applying a set of selection criteria, we identified candidate matches between V9 OTUs and MAGs. In some cases, V9 OTUs and MAGs could be matched with a one-to-one correspondence, implying that they likely represent the same underlying biological entity. More generally, matches we observed could be classified into 4 scenarios: one V9 OTU matches many MAGs; many V9 OTUs match many MAGs; many V9 OTUs match one MAG; one V9 OTU matches one MAG. Notably, we found some instances in which different OTU-MAG matches from the same taxonomic group were not classified in the same scenario, with all four scenarios possible even within the same taxonomic group, illustrating that factors beyond taxonomic lineage influence the relationship between OTUs and MAGs. Overall, each scenario produces a different interpretation of V9 OTUs, MAGs and how they compare in terms of the genomic and ecological diversity they represent.

Benchmarking a targeted 16S ribosomal RNA gene enrichment approach to reconstruct ancient microbial communities

The taxonomic characterization of ancient microbiomes is a key step in the rapidly growing field of paleomicrobiology. While PCR amplification of the 16S ribosomal RNA (rRNA) gene is a widely used technique in modern microbiota studies, this method has systematic biases when applied to ancient microbial DNA. Shotgun metagenomic sequencing has proven to be the most effective method in reconstructing taxonomic profiles of ancient dental calculus samples. Nevertheless, shotgun sequencing approaches come with inherent limitations that could be addressed through hybridization enrichment capture. When employed together, shotgun sequencing and hybridization capture have the potential to enhance the characterization of ancient microbial communities. Here, we develop, test, and apply a hybridization enrichment capture technique to selectively target 16S rRNA gene fragments from the libraries of ancient dental calculus samples generated with shotgun techniques. We simulated data sets generated from hybridization enrichment capture, indicating that taxonomic identification of fragmented and damaged 16S rRNA gene sequences was feasible. Applying this enrichment approach to 15 previously published ancient calculus samples, we observed a 334-fold increase of ancient 16S rRNA gene fragments in the enriched samples when compared to unenriched libraries. Our results suggest that 16S hybridization capture is less prone to the effects of background contamination than 16S rRNA amplification, yielding a higher percentage of on-target recovery. While our enrichment technique detected low abundant and rare taxa within a given sample, these assignments may not achieve the same level of specificity as those achieved by unenriched methods.

Planetary Protection Knowledge Gap Closure Enabling Crewed Missions to Mars

As focus for exploration of Mars transitions from current robotic explorers to development of crewed missions, it remains important to protect the integrity of scientific investigations at Mars, as well as protect the Earth's biosphere from any potential harmful effects from returned martian material. This is the discipline of planetary protection, and the Committee on Space Research (COSPAR) maintains the consensus international policy and guidelines on how this is implemented. Based on National Aeronautics and Space Administration (NASA) and European Space Agency (ESA) studies that began in 2001, COSPAR adopted principles and guidelines for human missions to Mars in 2008. At that point, it was clear that to move from those qualitative provisions, a great deal of work and interaction with spacecraft designers would be necessary to generate meaningful quantitative recommendations that could embody the intent of the Outer Space Treaty (Article IX) in the design of such missions. Beginning in 2016, COSPAR then sponsored a multiyear interdisciplinary meeting series to address planetary protection "knowledge gaps" (KGs) with the intent of adapting and extending the current robotic mission-focused Planetary Protection Policy to support the design and implementation of crewed and hybrid exploration missions. This article describes the outcome of the interdisciplinary COSPAR meeting series, to describe and address these KGs, as well as identify potential paths to gap closure. It includes the background scientific basis for each topic area and knowledge updates since the meeting series ended. In particular, credible solutions for KG closure are described for the three topic areas of (1) microbial monitoring of spacecraft and crew health; (2) natural transport (and survival) of terrestrial microbial contamination at Mars, and (3) the technology and operation of spacecraft systems for contamination control. The article includes a KG data table on these topic areas, which is intended to be a point of departure for making future progress in developing an end-to-end planetary protection requirements implementation solution for a crewed mission to Mars. Overall, the workshop series has provided evidence of the feasibility of planetary protection implementation for a crewed Mars mission, given (1) the establishment of needed zoning, emission, transport, and survival parameters for terrestrial biological contamination and (2) the creation of an accepted risk-based compliance approach for adoption by spacefaring actors including national space agencies and commercial/nongovernment organizations.

Exploring the Microbial Landscape of Neonatal Skin Flora: A Comprehensive Review

This comprehensive review explores the intricate landscape of the neonatal skin microbiome, shedding light on its dynamic composition, developmental nuances, and influential factors. The neonatal period represents a critical window during which microbial colonization significantly impacts local skin health and the foundational development of the immune system. Factors such as mode of delivery and gestational age underscore the vulnerability of neonates to disruptions in microbial establishment. Key findings emphasize the broader systemic implications of the neonatal skin microbiome, extending beyond immediate health outcomes to influence susceptibility to infections, allergies, and immune-related disorders. This review advocates for a paradigm shift in neonatal care, proposing strategies to preserve and promote a healthy skin microbiome for long-term health benefits. The implications of this research extend to public health, where interventions targeting the neonatal skin microbiome could potentially mitigate diseases originating in early life. As we navigate the intersection of research and practical applications, bridging the gap between knowledge and implementation becomes imperative for translating these findings into evidence-based practices and improving neonatal well-being on a broader scale.

Evaluation of Long-Read Sequencing Simulators to Assess Real-World Applications for Food Safety

Shiga toxin-producing Escherichia coli (STEC) and Listeria monocytogenes are routinely responsible for severe foodborne illnesses in the United States. Current identification methods utilized by the U.S. Food Safety Inspection Service require at least four days to identify STEC and six days for L. monocytogenes. Adoption of long-read, whole genome sequencing for food safety testing could significantly reduce the time needed for identification, but method development costs are high. Therefore, the goal of this project was to use NanoSim-H software to simulate Oxford Nanopore sequencing reads to assess the feasibility of sequencing-based foodborne pathogen detection and guide experimental design. Sequencing reads were simulated for STEC, L. monocytogenes, and a 1:1 combination of STEC and Bos taurus genomes using NanoSim-H. At least 2500 simulated reads were needed to identify the seven genes of interest targeted in STEC, and at least 500 reads were needed to detect the gene targeted in L. monocytogenes. Genome coverage of 30x was estimated at 21,521, and 11,802 reads for STEC and L. monocytogenes, respectively. Approximately 5-6% of reads simulated from both bacteria did not align with their respective reference genomes due to the introduction of errors. For the STEC and B. taurus 1:1 genome mixture, all genes of interest were detected with 1,000,000 reads, but less than 1x coverage was obtained. The results suggested sample enrichment would be necessary to detect foodborne pathogens with long-read sequencing, but this would still decrease the time needed from current methods. Additionally, simulation data will be useful for reducing the time and expense associated with laboratory experimentation.

Nucleic Acid Amplification Free-QCM-DNA Biosensor for Burkholderia pseudomallei Detection

Burkholderia pseudomallei is a gram-negative bacterium that causes the infectious disease melioidosis, a disease that can still be fatal despite appropriate treatment. The bacterium contains the gene clusters for the type III secretion system (TTSS), which are essential for its pathogenicity. This gene was often employed for accurate diagnosis through the laborious process of gene amplification. This work intends to develop a quartz crystal microbalance (QCM)-based TTSS gene detection method without gene amplification approaches to simplify the diagnosis process. In this study, it was demonstrated that a 540 bp sequence flanked by BglI restriction sites within the TTSS1 on the B. pseudomallei genome is an effective target for specific detection of the bacteria. After cultivation and genome extraction, the bacteria can be detected by digesting its genome with BglI in which the TTSS1 fragment is detected by a QCM-DNA biosensor, eliminating the need for nucleic acid amplification. A specific probe designed to bind to the TTSSI fragment was utilized as the receptor on the QCM-DNA biosensor which provided the ability to detect the fragment. The limit of detection of the QCM-DNA biosensor was 0.4 µM of the synthetic DNA target oligonucleotide. The system was also capable of specifically detecting the BglI digested-DNA fragment of B. pseudomallei species with significantly higher signal than B. thailandensis. This study provides evidence for an effective QCM-DNA biosensor that can identify B. pseudomallei without the need for nucleic acid amplification.

Microbial trace investigation throughout the entire chicken supply chain based on metagenomic high-throughput sequencing

As poultry possesses a high risk of contamination by various pathogens and has repeatedly been linked to foodborne outbreaks, ensuring microbiological safety throughout the chicken production chain is essential. In this study, bacterial communities in chickens and associated environments (n = 72), including feces, floors, gloves, and worktables, were trace investigated from the broiler farm, slaughterhouse, meat processing plant, and the market by amplicon sequencing of the V4 region of the 16S rRNA. The bacterial composition in live chickens along the production chain significantly changed across the stages, with distinct microbiota noted at each step. Pseudomonas, Shewanella, Acinetobacter, and Psychrobacter were dominant in the final products. Staphylococcus was abundant in live birds originally (36.83 %) but dramatically decreased after slaughter (3.07 %, 0.06 %, and 0.42 % in slaughtered, processed, and market carcasses, respectively), which may be attributed to defeathering. The proportion of Enterobacteriaceae, Acinetobacter, and Pseudomonas increased from 0.95 %, 0.03 %, and 0.04 % before slaughter to 13.57 %, 34.19 %, and 21.90 %, respectively, after slaughter, highlighting the importance of hygiene management in the succeeding steps. Diversity analysis revealed the possibility of bacterial transmission between samples from the processing plant and the market. Source tracking was performed to identify microbial contamination routes in the chicken microbiome; the major bacterial sources in the final products were the samples from the processing plant (such as processed carcasses, gloves, and worktables), accounting for 93.53 % of the total microbial sources. These results suggest that in-depth knowledge of microbial transmission between chickens and their surroundings can facilitate a precise understanding of microbiological concerns across the poultry production system and help establish safety management measures for the poultry industry.

Current and emerging trends in techniques for plant pathogen detection

Plant pathogenic microorganisms cause substantial yield losses in several economically important crops, resulting in economic and social adversity. The spread of such plant pathogens and the emergence of new diseases is facilitated by human practices such as monoculture farming and global trade. Therefore, the early detection and identification of pathogens is of utmost importance to reduce the associated agricultural losses. In this review, techniques that are currently available to detect plant pathogens are discussed, including culture-based, PCR-based, sequencing-based, and immunology-based techniques. Their working principles are explained, followed by an overview of the main advantages and disadvantages, and examples of their use in plant pathogen detection. In addition to the more conventional and commonly used techniques, we also point to some recent evolutions in the field of plant pathogen detection. The potential use of point-of-care devices, including biosensors, have gained in popularity. These devices can provide fast analysis, are easy to use, and most importantly can be used for on-site diagnosis, allowing the farmers to take rapid disease management decisions.

Changes in bacterial diversity, co-occurrence pattern, and potential pathogens following digestate fertilization: Extending pathogen management to field for anaerobic digestion of livestock manure

Digestate can spread pathogens into agroecosystem, posing serious threats to public health. However, the effect of digestate fertilization on digestate- or soil-borne pathogens has not been fully explored. Herein, two settings of microcosm experiment were performed with arable soil and digestate collected at two sites (Beilangzhong or Shunyi) to dissect the succession of the total and potential pathogenic bacterial communities following digestate fertilization. Each experimental setting consisted of three treatments, including digestate aerobically incubated in sterilized soil, and soil amended with sterilized or non-sterilized digestate. Digestate-borne potential pathogenic bacteria were enriched after the aerobic incubation, with Streptococcus sobrinus in the Beilangzhong setting, and Escherichia coli and Enterococcus faecium in the Shunyi setting. Potential soil-borne pathogenic bacteria, such as Acinetobacter lowffii and Pseudomonas fluorescens, were stimulated by the sterilized digestate in the Shunyi setting. Interestingly, S. sobrinus, E. coli, and Ent. faecium did not increase when digestate was amended into the non-sterilized soil, suggesting that soil microorganisms can inhibit the resurgence of these digestate-borne pathogens. A large-scale survey further revealed that organic fertilization exerted a site-dependent effect on different species of potential pathogen, but it did not enrich the total relative abundance of potential pathogenic bacteria in soils. Collectively, these results highlight that pathogen management of anaerobic digestion of livestock manure needs to be extended from anaerobic reactor to field.

Signal and noise in metabarcoding data

Metabarcoding is a powerful molecular tool for simultaneously surveying hundreds to thousands of species from a single sample, underpinning microbiome and environmental DNA (eDNA) methods. Deriving quantitative estimates of underlying biological communities from metabarcoding is critical for enhancing the utility of such approaches for health and conservation. Recent work has demonstrated that correcting for amplification biases in genetic metabarcoding data can yield quantitative estimates of template DNA concentrations. However, a major source of uncertainty in metabarcoding data stems from non-detections across technical PCR replicates where one replicate fails to detect a species observed in other replicates. Such non-detections are a special case of variability among technical replicates in metabarcoding data. While many sampling and amplification processes underlie observed variation in metabarcoding data, understanding the causes of non-detections is an important step in distinguishing signal from noise in metabarcoding studies. Here, we use both simulated and empirical data to 1) suggest how non-detections may arise in metabarcoding data, 2) outline steps to recognize uninformative data in practice, and 3) identify the conditions under which amplicon sequence data can reliably detect underlying biological signals. We show with both simulations and empirical data that, for a given species, the rate of non-detections among technical replicates is a function of both the template DNA concentration and species-specific amplification efficiency. Consequently, we conclude metabarcoding datasets are strongly affected by (1) deterministic amplification biases during PCR and (2) stochastic sampling of amplicons during sequencing-both of which we can model-but also by (3) stochastic sampling of rare molecules prior to PCR, which remains a frontier for quantitative metabarcoding. Our results highlight the importance of estimating species-specific amplification efficiencies and critically evaluating patterns of non-detection in metabarcoding datasets to better distinguish environmental signal from the noise inherent in molecular detections of rare targets.

Current Status and Future Trends in Removal, Control, and Mitigation of Algae Food Safety Risks for Human Consumption

With the rapid development of the economy and productivity, an increasing number of citizens are not only concerned about the nutritional value of algae as a potential new food resource but are also, in particular, paying more attention to the safety of its consumption. Many studies and reports pointed out that analyzing and solving seaweed food safety issues requires holistic and systematic consideration. The three main factors that have been found to affect the food safety of algal are physical, chemical, and microbiological hazards. At the same time, although food safety awareness among food producers and consumers has increased, foodborne diseases caused by algal food safety incidents occur frequently. It threatens the health and lives of consumers and may cause irreversible harm if treatment is not done promptly. A series of studies have also proved the idea that microbial contamination of algae is the main cause of this problem. Therefore, the rapid and efficient detection of toxic and pathogenic microbial contamination in algal products is an urgent issue that needs to be addressed. At the same time, two other factors, such as physical and chemical hazards, cannot be ignored. Nowadays, the detection techniques are mainly focused on three major hazards in traditional methods. However, especially for food microorganisms, the use of traditional microbiological control techniques is time-consuming and has limitations in terms of accuracy. In recent years, these two evaluations of microbial foodborne pathogens monitoring in the farm-to-table chain have shown more importance, especially during the COVID-19 pandemic. Meanwhile, there are also many new developments in the monitoring of heavy metals, algal toxins, and other pollutants. In the future, algal food safety risk assessment will not only focus on convenient, rapid, low-cost and high-accuracy detection but also be connected with some novel technologies, such as the Internet of Things (artificial intelligence, machine learning), biosensor, and molecular biology, to reach the purpose of simultaneous detection.

Tracking the Transmission of Antimicrobial-Resistant Non-O157 Escherichia coli and Salmonella Isolates at the Interface of Food Animals and Fresh Produce from Agriculture Operations Using Whole-Genome Sequencing

An increasing number of outbreaks are caused by foodborne pathogens such as Escherichia coli and Salmonella, which often harbor antimicrobial resistance (AMR) genes. We previously demonstrated the transmission of pathogens from animal operations to produce fields on sustainable farms, which illustrated an urgent need to develop and implement novel prevention methods and remediation practices such as the vegetative buffer zone (VBZ) to prevent this movement. The focus of this study was to use whole-genome sequencing (WGS) to characterize the AMR, virulence, and single-nucleotide polymorphism profile of 15 Salmonella and 128 E. coli isolates collected from small-scale dairy and poultry farms on a research station in North Carolina. Phenotypically, seven E. coli and three Salmonella isolates displayed resistance to antibiotics such as tetracycline (n = 4), ampicillin (n = 4), nalidixic acid (n = 3), chloramphenicol (n = 2), sulfisoxazole (n = 1), and streptomycin (n = 1). A single E. coli isolate was found to be resistant to five different antibiotic class types and possessed the bla_TEM-150 resistance gene. Virulence genes that facilitate toxin production and cell invasion were identified. Mauve analysis of the E. coli isolates identified seven clusters (dairy-six and poultry-one) indicating that transmission is occurring from animal operations to fresh produce fields and the surrounding environment when the VBZ is denudated. This suggests that the VBZ is a useful barrier to reducing the transmission of enteric pathogens in agricultural systems. Our study demonstrates the prevalence of AMR and virulence genes on small-scale sustainable farms and highlights the advantage of using WGS to assess the impact of the VBZ to reduce the transmission of E. coli and Salmonella.

Present and pioneer methods of early detection of food borne pathogens

Food-borne pathogens are a severe threat to human illness and death world-wide. Researchers have reported more than 250 food-borne diseases. Most of these are infections caused by a wide variety of bacteria, viruses, and parasites. It has a significant economic impact also. Detection of pathogenic microbes is thus essential for food safety. Such identification techniques could meet the following parameters viz., the accuracy of detection techniques that are quick, efficient, economical, highly sensitive, specific, and non-labor intensive. The various available methods for detecting food pathogens are classified into different groups, each having its advantages and disadvantages. The conventional methods are usually the first choice of detection even though they are laborious. Modern techniques such as biosensors, immunological assays, and macromolecule-based (nucleic acid) methods are being developed and refined to overcome traditional methods' limitations. Early detection of pathogens and secure food safety at each stage of food processing to storage, utilizing improved methodologies are mandatory. This review summarizes the deadly food pathogens leading to significant outbreaks and discusses the importance of early detection methods and advanced detection methods in comparison.

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.

Next-Generation Sequencing for Confronting Virus Pandemics

Virus pandemics have happened, are happening and will happen again. In recent decades, the rate of zoonotic viral spillover into humans has accelerated, mirroring the expansion of our global footprint and travel network, including the expansion of viral vectors and the destruction of natural spaces, bringing humans closer to wild animals. Once viral cross-species transmission to humans occurs, transmission cannot be stopped by cement walls but by developing barriers based on knowledge that can prevent or reduce the effects of any pandemic. Controlling a local transmission affecting few individuals is more efficient that confronting a community outbreak in which infections cannot be traced. Genetic detection, identification, and characterization of infectious agents using next-generation sequencing (NGS) has been proven to be a powerful tool allowing for the development of fast PCR-based molecular assays, the rapid development of vaccines based on mRNA and DNA, the identification of outbreaks, transmission dynamics and spill-over events, the detection of new variants and treatment of vaccine resistance mutations, the development of direct-acting antiviral drugs, the discovery of relevant minority variants to improve knowledge of the viral life cycle, strengths and weaknesses, the potential for becoming dominant to take appropriate preventive measures, and the discovery of new routes of viral transmission.

Metagenomics Approaches for Improving Food Safety: A Review

ABSTRACT

Advancements in next-generation sequencing technology have dramatically reduced the cost and increased the ease of microbial whole genome sequencing. This approach is revolutionizing the identification and analysis of foodborne microbial pathogens, facilitating expedited detection and mitigation of foodborne outbreaks, improving public health outcomes, and limiting costly recalls. However, next-generation sequencing is still anchored in the traditional laboratory practice of the selection and culture of a single isolate. Metagenomic-based approaches, including metabarcoding and shotgun and long-read metagenomics, are part of the next disruptive revolution in food safety diagnostics and offer the potential to directly identify entire microbial communities in a single food, ingredient, or environmental sample. In this review, metagenomic-based approaches are introduced and placed within the context of conventional detection and diagnostic techniques, and essential considerations for undertaking metagenomic assays and data analysis are described. Recent applications of the use of metagenomics for food safety are discussed alongside current limitations and knowledge gaps and new opportunities arising from the use of this technology.

HIGHLIGHTS

Characterization of Genetically Modified Microorganisms Using Short- and Long-Read Whole-Genome Sequencing Reveals Contaminations of Related Origin in Multiple Commercial Food Enzyme Products

Despite their presence being unauthorized on the European market, contaminations with genetically modified (GM) microorganisms have repeatedly been reported in diverse commercial microbial fermentation produce types. Several of these contaminations are related to a GM Bacillus velezensis used to synthesize a food enzyme protease, for which genomic characterization remains currently incomplete, and it is unknown whether these contaminations have a common origin. In this study, GM B. velezensis isolates from multiple food enzyme products were characterized by short- and long-read whole-genome sequencing (WGS), demonstrating that they harbor a free recombinant pUB110-derived plasmid carrying antimicrobial resistance genes. Additionally, single-nucleotide polymorphism (SNP) and whole-genome based comparative analyses showed that the isolates likely originate from the same parental GM strain. This study highlights the added value of a hybrid WGS approach for accurate genomic characterization of GMM (e.g., genomic location of the transgenic construct), and of SNP-based phylogenomic analysis for source-tracking of GMM.

Analysis of Bacterial Communities by 16S rRNA Gene Sequencing in a Melon-Producing Agro-environment

Cantaloupe melons, which have been responsible of an increasing number of foodborne disease outbreaks, may become contaminated with microbial pathogens during production. However, little information is available on the microbial populations in the cantaloupe farm environment. The purpose of this work was to characterize the bacterial communities present on cantaloupe farms. Fruit, soil, and harvester hand rinsates were collected from two Mexican cantaloupe farms, each visited three times. Microbiome analysis was performed by sequencing 16sRNA and analyzed using qiime2 software. Correlations were determined between sample type and microbial populations. The α and β diversity analysis identified 2777 sequences across all samples. The soil samples had the highest number and diversity of unique species (from 130 to 1329 OTUs); cantaloupe (from 112 to 205 OTUs), and hands (from 67 to 151 OTUs) had similar diversity. Collectively, Proteobacteria was the most abundant phyla (from 42 to 95%), followed by Firmicutes (1-47%), Actinobacteria (< 1 to 23%), and Bacteroidetes (< 1 to 4.8%). The most abundant genera were Acinetobacter (20-58%), Pseudomonas (14.5%), Erwinia (13%), and Exiguobacterium (6.3%). Genera with potential to be pathogenic included Bacillus (4%), Salmonella (0.85%), Escherichia-Shigella (0.38%), Staphylococcus (0.32%), Listeria (0.29%), Clostridium (0.28%), and Cronobacter (0.27%), which were found at lower frequencies. This study provides information on the cantaloupe production microbiome, which can inform future research into critical food safety issues such as antimicrobial resistance, virulence, and genomic epidemiology.

Improved Microbial Community Characterization of 16S rRNA via Metagenome Hybridization Capture Enrichment

Environmental microbial diversity is often investigated from a molecular perspective using 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics. While amplicon methods are fast, low-cost, and have curated reference databases, they can suffer from amplification bias and are limited in genomic scope. In contrast, shotgun metagenomic methods sample more genomic regions with fewer sequence acquisition biases, but are much more expensive (even with moderate sequencing depth) and computationally challenging. Here, we develop a set of 16S rRNA sequence capture baits that offer a potential middle ground with the advantages from both approaches for investigating microbial communities. These baits cover the diversity of all 16S rRNA sequences available in the Greengenes (v. 13.5) database, with no sequence having <78% sequence identity to at least one bait for all segments of 16S. The use of our baits provide comparable results to 16S amplicon libraries and shotgun metagenomic libraries when assigning taxonomic units from 16S sequences within the metagenomic reads. We demonstrate that 16S rRNA capture baits can be used on a range of microbial samples (i.e., mock communities and rodent fecal samples) to increase the proportion of 16S rRNA sequences (average > 400-fold) and decrease analysis time to obtain consistent community assessments. Furthermore, our study reveals that bioinformatic methods used to analyze sequencing data may have a greater influence on estimates of community composition than library preparation method used, likely due in part to the extent and curation of the reference databases considered. Thus, enriching existing aliquots of shotgun metagenomic libraries and obtaining modest numbers of reads from them offers an efficient orthogonal method for assessment of bacterial community composition.

Viruses in fermented foods: are they good or bad? Two sides of the same coin

The emergence of Coronavirus disease 2019 as a global pandemic has increased popular concerns about diseases caused by viruses. Fermented foods containing high loads of viable fungi and bacteria are potential sources for virus contamination. The most common include viruses that infect bacteria (bacteriophage) and yeasts reported in fermented milks, sausages, vegetables, wine, sourdough, and cocoa beans. Recent molecular studies have also associated fermented foods as vehicles for pathogenic human viruses. Human noroviruses, rotavirus, and hepatitis virus have been identified in different fermented foods through multiple routes. No severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) virus or close members were found in fermented foods to date. However, the occurrence/persistence of other pathogenic viruses reveals a potential vulnerability of fermented foods to SARS-CoV-2 contamination. On the other side of the coin, some bacteriophages are being suggested for improving the fermentation process and food safety, as well as owing potential probiotic properties in modern fermented foods. This review will address the diversity and characteristics of viruses associated with fermented foods and what has been changed after a short introduction to the most common next-generation sequencing platforms. Also, the risk of SARS-CoV-2 transmission via fermented foods and preventive measures will be discussed.

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.

The Role of Peridomestic Rodents as Reservoirs for Zoonotic Foodborne Pathogens

Although rodents are well-known reservoirs and vectors for a number of zoonoses, the functional role that peridomestic rodents serve in the amplification and transmission of foodborne pathogens is likely underappreciated. Clear links have been identified between commensal rodents and outbreaks of foodborne pathogens throughout Europe and Asia; however, comparatively little research has been devoted to studying this relationship in the United States. In particular, regional studies focused on specific rodent species and their foodborne pathogen reservoir status across the diverse agricultural landscapes of the United States are lacking. We posit that both native and invasive species of rodents associated with food-production pipelines are likely sources of seasonal outbreaks of foodborne pathogens throughout the United States. In this study, we review the evidence that identifies peridomestic rodents as reservoirs for foodborne pathogens, and we call for novel research focused on the metagenomic communities residing at the rodent-agriculture interface. Such data will likely result in the identification of new reservoirs for foodborne pathogens and species-specific demographic traits that might underlie seasonal enteric disease outbreaks. Moreover, we anticipate that a One Health metagenomic research approach will result in the discovery of new strains of zoonotic pathogens circulating in peridomestic rodents. Data resulting from such research efforts would directly inform and improve upon biosecurity efforts, ultimately serving to protect our food supply.

Precision long-read metagenomics sequencing for food safety by detection and assembly of Shiga toxin-producing Escherichia coli in irrigation water

Shiga toxin-producing Escherichia coli (STEC) contamination of agricultural water might be an important factor to recent foodborne illness and outbreaks involving leafy greens. Closed bacterial genomes from whole genome sequencing play an important role in source tracking. We aimed to determine the limits of detection and classification of STECs by qPCR and nanopore sequencing using 24 hour enriched irrigation water artificially contaminated with E. coli O157:H7 (EDL933). We determined the limit of STEC detection by qPCR to be 30 CFU/reaction, which is equivalent to 105 CFU/ml in the enrichment. By using Oxford Nanopore's EPI2ME WIMP workflow and de novo assembly with Flye followed by taxon classification with a k-mer analysis software (Kraken2), E. coli O157:H7 could be detected at 103 CFU/ml (68 reads) and a complete fragmented E. coli O157:H7 metagenome-assembled genome (MAG) was obtained at 105-108 CFU/ml. Using a custom script to extract the E. coli reads, a completely closed MAG was obtained at 107-108 CFU/ml and a complete, fragmented MAG was obtained at 105-106 CFU/ml. In silico virulence detection for E. coli MAGs for 105-108 CFU/ml showed that the virulotype was indistinguishable from the spiked E. coli O157:H7 strain. We further identified the bacterial species in the un-spiked enrichment, including antimicrobial resistance genes, which could have important implications to food safety. We propose this workflow provides proof of concept for faster detection and complete genomic characterization of STECs from a complex microbial sample compared to current reporting protocols and could be applied to determine the limit of detection and assembly of other foodborne bacterial pathogens.

Diversity of the microbial community and antioxidant activity during fermentation of red raspberry Enzymes

The diversity and succession of microbial community and antioxidant activity present during the preparation of red raspberry Enzymes with and without starter cultures were investigated by high-throughput sequencing of 16S rRNA and ITS1 genes and correlation analysis of the microbial diversity and antioxidant activity. The results showed that the sample inoculated with mixed fermentation had higher antioxidant activity than the sample without inoculated fermentation. The antioxidant capacity of red raspberry Enzymes increased significantly as the fermentation time increased. Firmicutes and Ascomycota were the predominant phyla of bacteria and fungi in all samples. At the genus level, Rhodococcus and Lactobacillus were the predominating bacteria throughout the fermentation process. The genus Kodamaea dominated the fungal community of early-fermentation samples with microbial inoculated fermentation. Candida spp. grew rapidly in the late stage of fermentation in the samples with spontaneous fermentation. Unweighted pair-group and PCA analysis revealed that the microbiota structures differed between the two groups. RDA and CCA showed that Rhodococcus and Kodamaea had positive effects on the DPPH scavenging ability and other antioxidant indicators, and the total phenol content had a significant and positive correlation coefficient with Gluconobacter. The results indicated that the fermentation by microorganisms significantly improves the oxidation resistance and helps to improve the quality of the red raspberry Enzymes.

Strain-Level Metagenomic Data Analysis of Enriched In Vitro and In Silico Spiked Food Samples: Paving the Way towards a Culture-Free Foodborne Outbreak Investigation Using STEC as a Case Study

Culture-independent diagnostics, such as metagenomic shotgun sequencing of food samples, could not only reduce the turnaround time of samples in an outbreak investigation, but also allow the detection of multi-species and multi-strain outbreaks. For successful foodborne outbreak investigation using a metagenomic approach, it is, however, necessary to bioinformatically separate the genomes of individual strains, including strains belonging to the same species, present in a microbial community, which has up until now not been demonstrated for this application. The current work shows the feasibility of strain-level metagenomics of enriched food matrix samples making use of data analysis tools that classify reads against a sequence database. It includes a brief comparison of two database-based read classification tools, Sigma and Sparse, using a mock community obtained by in vitro spiking minced meat with a Shiga toxin-producing Escherichia coli (STEC) isolate originating from a described outbreak. The more optimal tool Sigma was further evaluated using in silico simulated metagenomic data to explore the possibilities and limitations of this data analysis approach. The performed analysis allowed us to link the pathogenic strains from food samples to human isolates previously collected during the same outbreak, demonstrating that the metagenomic approach could be applied for the rapid source tracking of foodborne outbreaks. To our knowledge, this is the first study demonstrating a data analysis approach for detailed characterization and phylogenetic placement of multiple bacterial strains of one species from shotgun metagenomic WGS data of an enriched food sample.

The risks of using molecular biodiversity data for incidental detection of species of concern

Incidental detection of species of concern (e.g., invasive species, pathogens, threatened and endangered species) during biodiversity assessments based on high-throughput DNA sequencing holds significant risks in the absence of rigorous, fit-for-purpose data quality and reporting standards. Molecular biodiversity data are predominantly collected for ecological studies and thus are generated to common quality assurance standards. However, the detection of certain species of concern in these data would likely elicit interest from end users working in biosecurity or other surveillance contexts (e.g., pathogen detection in health-related fields), for which more stringent quality control standards are essential to ensure that data are suitable for informing decision-making and can withstand legal or political challenges. We suggest here that data quality and reporting criteria are urgently needed to enable clear identification of those studies that may be appropriately applied to surveillance contexts. In the interim, more pointed disclaimers on uncertainties associated with the detection and identification of species of concern may be warranted in published studies. This is not only to ensure the utility of molecular biodiversity data for consumers, but also to protect data generators from uncritical and potentially ill-advised application of their science in decision-making.

TORMES: an automated pipeline for whole bacterial genome analysis

MOTIVATION

The progress of High Throughput Sequencing (HTS) technologies and the reduction in the sequencing costs are such that Whole Genome Sequencing (WGS) could replace many traditional laboratory assays and procedures. Exploiting the volume of data produced by HTS platforms requires substantial computing skills and this is the main bottleneck in the implementation of WGS as a routine laboratory technique. The way in which the vast amount of results are presented to researchers and clinicians with no specialist knowledge of genome sequencing is also a significant issue.

RESULTS

Here we present TORMES, a user-friendly pipeline for WGS analysis of bacteria from any origin generated by HTS on Illumina platforms. TORMES is designed for non-bioinformatician users, and automates the steps required for WGS analysis directly from the raw sequence data: sequence quality filtering, de novo assembly, draft genome ordering against a reference, genome annotation, multi-locus sequence typing (MLST), searching for antibiotic resistance and virulence genes, and pangenome comparisons. Once the analysis is finished, TORMES generates and interactive web-like report that can be opened in any web browser and shared and revised by researchers in a simple manner. TORMES can be run by using very simple commands and represent a quick an easy way to perform WGS analysis.

AVAILABILITY AND IMPLEMENTATION

TORMES is free available at https://github.com/nmquijada/tormes.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A Recombinase Polymerase Amplification and Lateral Flow Strip Combined Method That Detects Salmonella enterica Serotype Typhimurium With No Worry of Primer-Dependent Artifacts

On-site detection demands are quickly increasing to control foodborne pathogenic bacteria along with the long food supply chains. Combining the isothermal recombinase polymerase amplification (RPA) with lateral flow strips (LFSs) is a promising molecular detection approach for the short reaction time, low isothermal condition, and simple and "instrument-free" procedure. However, the method comes with a non-negligible intrinsic risk of the primer-dependent artifacts. In this study, with an important foodborne pathogenic bacterium Salmonella enterica serotype Typhimurium (S. Typhimurium) as the model, system measures including the careful selection of primers targeting unique virulence genes, use of a probe in the RPA reaction, introducing base substitutions with specific guidelines in the primer and probe sequences, and analyzing and screening the primer-probe complex formation were taken to eliminate the primer-dependent artifacts. The measures were strictly tested for the efficacy, and the standardized method was able to specifically detect S. typhimurium within 30 min at 42°C without any interference of probe-primer signals. The established RPA-LFS method shared high sensitivity with the detection limit of 1 CFU/μl of unpurified culture. Our study provided practical measures for the prevention of false positive signals from primer-dimers or primer-probe complexes when using the RPA-LFS method in pathogen detections, and also established a readily applicable method for S. Typhimurium detection.

Occurrence and species diversity of human-pathogenic Mucorales in commercial food-stuffs purchased in Paris area

Mucormycoses are life-threatening fungal diseases that affect a variety of patients including those with diabetes mellitus or hematological malignancies. The responsible agents, the Mucorales, are opportunistic pathogens originating from the environment such as soil or decaying organic matter. The aim of the present study was to assess the prevalence and diversity of human-pathogenic species of Mucorales in commercially available foodstuffs in France. All food samples were purchased from January 2014 to May 2015 in France. A total of 159 dried food samples including spices and herbs (n = 68), herbal tea (n = 19), cereals (n = 19), vegetables (n = 14), and other foodstuffs (n = 39) were analyzed. Each strain of Mucorales was identified phenotypically, and molecular identification was performed by ITS sequencing. From the 28 (17.6%) samples that were culture-positive for Mucorales, 30 isolates were recovered. Among the isolates, 13 were identified as Rhizopus arrhizus var. arrhizus, 10 R. arrhizus var. delemar, two Rhizopus microsporus, one Lichtheimia corymbifera, three Lichtheimia ramosa, and one Syncephalastrum racemosum. Culture-positive samples originated from different countries (Europe, Asia) and brands. The samples most frequently contaminated by Mucorales were spices and herbs (19/68, 27.9%), followed by herbal tea (2/19, 10.5%), cereals (2/19, 10.5%), other food products (5/39, 12.8%). The present study showed that human-pathogenic Mucorales were frequently recovered from commercially available foodstuffs in France with a large diversity of species. The potential danger represented by Mucorales present in food for immunocompromised patients should be further analyzed.

Prospective Salmonella Enteritidis surveillance and outbreak detection using whole genome sequencing, Minnesota 2015-2017

Clusters of Salmonella Enteritidis cases were identified by the Minnesota Department of Health using both pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) single nucleotide polymorphism analysis from 1 January 2015 through 31 December 2017. The median turnaround time for obtaining WGS results was 11 days longer than for PFGE (12 vs. 1 day). WGS analysis more than doubled the number of clusters compared to PFGE analysis, but reduced the total number of cases included in clusters by 34%. The median cluster size was two cases for WGS compared to four for PFGE, and the median duration of WGS clusters was 27 days shorter than PFGE clusters. While the percentage of PFGE clusters with a confirmed source (46%) was higher than WGS clusters (32%), a higher percentage of cases in clusters that were confirmed as outbreaks reported the vehicle or exposure of interest for WGS (78%) than PFGE (46%). WGS cluster size was a significant predictor of an outbreak source being confirmed. WGS data have enhanced S. Enteritidis cluster investigations in Minnesota by improving the specificity of cluster case definitions and has become an integral part of the S. Enteritidis surveillance process.

Identification of an unauthorized genetically modified bacteria in food enzyme through whole-genome sequencing

Recently, the unexpected presence of a viable unauthorized genetically modified bacterium in a commercialized food enzyme (protease) product originating from a microbial fermentation process has been notified at the European level (RASFF 2019.3332). This finding was made possible thanks to the use of the next-generation sequencing technology, as reported in this study. Whole-genome sequencing was used to characterize the genetic modification comprising a sequence from the pUB110 shuttle vector (GenBank: M19465.1), harbouring antimicrobial resistance genes conferring a resistance to kanamycine, neomycin and bleomycin, flanked on each side by a sequence coding for a protease (GenBank: WP_032874795.1). In addition, based on these data, two real-time PCR methods, that can be used by enforcement laboratories, specific to this unauthorized genetically modified bacterium were developed and validated. The present study emphasizes the key role that whole-genome sequencing can take for detection of unknown and unauthorized genetically modified microorganisms in commercialized microbial fermentation products intended for the food and feed chain. Moreover, current issues encountered by the Competent Authorities and enforcement laboratories with such unexpected contaminations and the importance of performing official controls were highlighted.

Whole Genome Sequencing and Characteristics of mcr-1-Harboring Plasmids of Porcine Escherichia coli Isolates Belonging to the High-Risk Clone O25b:H4-ST131 Clade B

Porcine Escherichia coli ST131 isolates are scarcely documented. Here, whole genome sequencing and core genome (CG) and plasmidome analysis of seven isolates collected from diarrheic piglets and four from pork meat were performed. All of the 11 ST131 isolates belonged to serotype O25b:H4 and clade B and showed fimH22 allele or mutational derivatives. The 11 porcine isolates possessed virulence traits that classified the isolates as avian pathogenic, uropathogenic, and extraintestinal pathogenic E. coli–like (APEC-, UPEC-, and ExPEC-like) and constituted virotype D. The CG was performed for all porcine isolates in addition to 73 ST131 reference isolates from different origins. Within clade B, the CG showed nine subclusters, allowing us to describe five new subclades (B6, B6-like, B7, B8, and B9). There was an association between subclade B6, PST43, virotype D2, and food origin, whereas subclade B7 included PST9 isolates with virotype D5 from diarrheic piglets (p = 0.007). The distance between human and porcine isolates from subclades B6 and B7 had an average of 20 and 15 SNP/Mb, respectively. [F2:A-:B1]-IncF, ColE1-like, and IncX plasmids were the most prevalent. Besides, IncF plasmids harbored a ColV region frequent among APEC isolates. Antimicrobial resistance genes conferring resistance to penicillin, tetracycline, quinolones, and colistin were the most common. The mcr-1.1 gene was detected in 5 of 11 porcine isolates, integrated into the chromosome of one isolate and into plasmids in the remainder isolates (two MOB_H11/IncHI2-ST4, one MOB_P3/IncX4, and one MOB_F12/IncF [F2:A-:B1] supposedly cointegrated with an IncHI2). The surrounding environments of the mcr-1 cassette showed variability. However, there were conserved structures within the same plasmid family. In conclusion, CG analysis defined five new subclades. The ST131 porcine isolates belonged to new subclades B6 and B7. Moreover, porcine and clinical human isolates were strongly related. The 11 porcine ST131 isolates harbored a wide variety of plasmids, virulence, and resistance genes. Furthermore, epidemic plasmids IncX4 and IncHI2 are responsible for the acquisition of mcr-1.1 gene. We hypothesize that the APEC-IncF plasmid acquired the mcr-1.1 gene via cointegrating an IncHI2 plasmid, which is worrying due to combination of virulence and resistance attributes in a single mobile genetic element.

Application of aptamers as molecular recognition elements in lateral flow assays

Owing to their ease in operation and fast turnaround time, lateral flow assays (LFAs) are increasingly being used as point-of-care diagnostic tests for variety of analytes. In a majority of these LFAs, antibodies are used as a molecular recognition element. Antibodies have a number of limitations such as high batch-to-batch variation, poor stability, long development time, difficulty in functionalization and need for ethical approval and cold chain. All these factors pose a great challenge to scale up the antibody-based tests. In recent years, the advent of aptamer technology has made a paradigm shift in the point-of-care diagnostics owing to the various advantages of aptamers over antibodies that favour their adaptability on a variety of sensing platforms including the lateral flow. In this review, we have highlighted the advantages of aptamers over antibodies, suitability of aptamers for lateral flow platforms, different types of aptamer-based LFAs and various labels for aptamer-based LFAs. We have also provided a summary of the applications of aptamer technology in LFAs for analytical applications.

Food Security: Microbiological and Chemical Risks

Food Security within a health security context relates to systems dealing with the prevention and control of not only acute but also sporadic and chronic foodborne diseases. The description of food security and safety systems in this chapter will hence include oversight of both microbiological and chemical hazards, which both can cause acute as well as chronic disease events.

The Chapter includes a description of existing national and international surveillance systems for foodborne diseases and regulatory systems enabling risk mitigation action for both chemical and microbiological hazards, with specific inclusion of the concerning increase in antimicrobial resistance (AMR) of foodborne microorganisms also related to the animal production systems.

The Chapter also includes descriptions of methodology for the quantitative assessment of sustainability of food production systems.

Resistome metagenomics from plate to farm: The resistome and microbial composition during food waste feeding and composting on a Vermont poultry farm

Food waste diversion and composting, either mandated or voluntary, are growing alternatives to traditional waste disposal. An acceptable source of agricultural feed and composting material, methane-emitting food residuals, including post-consumer food scraps, are diverted from landfills allowing recapture of nutrients that would otherwise be lost. However, risk associated with the transfer of antimicrobial resistant bacteria (ARB), antibiotic resistance genes (ARGs), or pathogens from food waste is not well characterized. Using shotgun metagenomic sequencing, ARGs, microbial content, and associated virulence factors were successfully identified across samples from an integrated poultry farm that feeds post-consumer food waste. A total of 495 distinct bacterial species or sub-species, 50 ARGs, and 54 virulence gene sequences were found. ARG sequences related to aminoglycoside, tetracycline, and macrolide resistance were most prominent, while most virulence gene sequences were related to transposon or integron activity. Microbiome content was distinct between on-farm samples and off-farm food waste collection sites, with a reduction in pathogens throughout the composting process. While most samples contained some level of resistance, only 3 resistance gene sequences occurred in both on- and off-farm samples and no multidrug resistance (MDR) gene sequences persisted once on the farm. The risk of incorporating novel or multi-drug resistance from human sources appears to be minimal and the practice of utilizing post-consumer food scraps as feed for poultry and composting material may not present a significant risk for human or animal health. Pearson correlation and co-inertia analysis identified a significant interaction between resistance and virulence genes (P = 0.05, RV = 0.67), indicating that ability to undergo gene transfer may be a better marker for ARG risk than presence of specific bacterial species. This work expands the knowledge of ARG fate during food scrap animal feeding and composting and provides a methodology for reproducible analysis.

Rapid, multiplexed, whole genome and plasmid sequencing of foodborne pathogens using long-read nanopore technology

U.S. public health agencies have employed next-generation sequencing (NGS) as a tool to quickly identify foodborne pathogens during outbreaks. Although established short-read NGS technologies are known to provide highly accurate data, long-read sequencing is still needed to resolve highly-repetitive genomic regions and genomic arrangement, and to close the sequences of bacterial chromosomes and plasmids. Here, we report the use of long-read nanopore sequencing to simultaneously sequence the entire chromosome and plasmid of Salmonella enterica subsp. enterica serovar Bareilly and Escherichia coli O157:H7. We developed a rapid and random sequencing approach coupled with de novo genome assembly within a customized data analysis workflow that uses publicly-available tools. In sequencing runs as short as four hours, using the MinION instrument, we obtained full-length genomes with an average identity of 99.87% for Salmonella Bareilly and 99.89% for E. coli in comparison to the respective MiSeq references. These nanopore-only assemblies provided readily available information on serotype, virulence factors, and antimicrobial resistance genes. We also demonstrate the potential of nanopore sequencing assemblies for rapid preliminary phylogenetic inference. Nanopore sequencing provides additional advantages as very low capital investment and footprint, and shorter (10 hours library preparation and sequencing) turnaround time compared to other NGS technologies.

Machine Learning Approaches for Epidemiological Investigations of Food-Borne Disease Outbreaks

Foodborne diseases (FBDs) are infections of the gastrointestinal tract caused by foodborne pathogens (FBPs) such as bacteria [Salmonella, Listeria monocytogenes and Shiga toxin-producing E. coli (STEC)] and several viruses, but also parasites and some fungi. Artificial intelligence (AI) and its sub-discipline machine learning (ML) are re-emerging and gaining an ever increasing popularity in the scientific community and industry, and could lead to actionable knowledge in diverse ranges of sectors including epidemiological investigations of FBD outbreaks and antimicrobial resistance (AMR). As genotyping using whole-genome sequencing (WGS) is becoming more accessible and affordable, it is increasingly used as a routine tool for the detection of pathogens, and has the potential to differentiate between outbreak strains that are closely related, identify virulence/resistance genes and provide improved understanding of transmission events within hours to days. In most cases, the computational pipeline of WGS data analysis can be divided into four (though, not necessarily consecutive) major steps: de novo genome assembly, genome characterization, comparative genomics, and inference of phylogeny or phylogenomics. In each step, ML could be used to increase the speed and potentially the accuracy (provided increasing amounts of high-quality input data) of identification of the source of ongoing outbreaks, leading to more efficient treatment and prevention of additional cases. In this review, we explore whether ML or any other form of AI algorithms have already been proposed for the respective tasks and compare those with mechanistic model-based approaches.

The use of next generation sequencing for improving food safety: Translation into practice

Next Generation Sequencing (NGS) combined with powerful bioinformatic approaches are revolutionising food microbiology. Whole genome sequencing (WGS) of single isolates allows the most detailed comparison possible hitherto of individual strains. The two principle approaches for strain discrimination, single nucleotide polymorphism (SNP) analysis and genomic multi-locus sequence typing (MLST) are showing concordant results for phylogenetic clustering and are complementary to each other. Metabarcoding and metagenomics, applied to total DNA isolated from either food materials or the production environment, allows the identification of complete microbial populations. Metagenomics identifies the entire gene content and when coupled to transcriptomics or proteomics, allows the identification of functional capacity and biochemical activity of microbial populations. The focus of this review is on the recent use and future potential of NGS in food microbiology and on current challenges. Guidance is provided for new users, such as public health departments and the food industry, on the implementation of NGS and how to critically interpret results and place them in a broader context. The review aims to promote the broader application of NGS technologies within the food industry as well as highlight knowledge gaps and novel applications of NGS with the aim of driving future research and increasing food safety outputs from its wider use.

Toward multiomics-based next-generation diagnostics for precision medicine

Our healthcare system is experiencing a paradigm shift to precision medicine, aiming at an early prediction of individual disease risks and targeted interventions. Whole-genome sequencing is currently gaining momentum, as it has the potential to capture all classes of genetic variation, thus providing a more complete picture of the individual's genetic makeup, which could be utilized in genetic testing; however, this will also lead to difficulties in interpreting the test results, necessitating careful integration of genomic data with other layers of information, both molecular multiomics measurements of epigenome, transcriptome, proteome, metabolome and even microbiome, as well as comprehensive information on diet, lifestyle and environment. Overall, the translation of patient-specific data into actionable diagnostic tools will be a challenging task, requiring expertise from multiple disciplines, secure data sharing in large reference databases and a strong computational infrastructure.

Developments in Rapid Detection Methods for the Detection of Foodborne Campylobacter in the United States

The accurate and rapid detection of Campylobacter spp. is critical for optimal surveillance throughout poultry processing in the United States. The further development of highly specific and sensitive assays to detect Campylobacter in poultry matrices has tremendous utility and potential for aiding the reduction of foodborne illness. The introduction and development of molecular methods such as polymerase chain reaction (PCR) have enhanced the diagnostic capabilities of the food industry to identify the presence of foodborne pathogens throughout poultry production. Further innovations in various methodologies, such as immune-based typing and detection as well as high throughput analyses, will provide important epidemiological data such as the identification of unique or region-specific Campylobacter. Comparable to traditional microbiology and enrichment techniques, molecular techniques/methods have the potential to have improved sensitivity and specificity, as well as speed of data acquisition. This review will focus on the development and application of rapid molecular methods for identifying and quantifying Campylobacter in U.S. poultry and the emergence of novel methods that are faster and more precise than traditional microbiological techniques.

Exploring Foodborne Pathogen Ecology and Antimicrobial Resistance in the Light of Shotgun Metagenomics

In this chapter, applications of shotgun metagenomics for taxonomic profiling and functional investigation of food microbial communities with a focus on antimicrobial resistance (AMR) were overviewed in the light of last data in the field. Potentialities of metagenomic approach, along with the challenges encountered for a wider and routinely use in food safety was discussed.