Metagenomic analysis of viruses associated with field-grown and retail lettuce identifies human and animal viruses

Whole-Genome Sequencing-Based Confirmatory Methods on RT-qPCR Results for the Detection of Foodborne Viruses in Frozen Berries

Accurate detection, identification, and subsequent confirmation of pathogens causing foodborne illness are essential for the prevention and investigation of foodborne outbreaks. This is particularly true when the causative agent is an enteric virus that has a very low infectious dose and is likely to be present at or near the limit of detection. In this study, whole-genome sequencing (WGS) was combined with either of two non-targeted pre-amplification methods (SPIA and SISPA) to investigate their utility as a confirmatory method for RT-qPCR positive results of foods contaminated with enteric viruses. Frozen berries (raspberries, strawberries, and blackberries) were chosen as the food matrix of interest due to their association with numerous outbreaks of foodborne illness. The hepatitis A virus (HAV) and human norovirus (HuNoV) were used as the contaminating agents. The non-targeted WGS strategy employed in this study could detect and confirm HuNoV and HAV at genomic copy numbers in the single digit range, and in a few cases, identified viruses present in samples that had been found negative by RT-qPCR analyses. However, some RT-qPCR-positive samples could not be confirmed using the WGS method, and in cases with very high Ct values, only a few viral reads and short sequences were recovered from the samples. WGS techniques show great potential for confirmation and identification of virally contaminated food items. The approaches described here should be further optimized for routine application to confirm the viral contamination in berries.

Virome analysis of irrigation water sources provides extensive insights into the diversity and distribution of plant viruses in agroecosystems

Plant viruses pose a significant threat to agriculture. Several are stable outside their hosts, can enter water bodies and remain infective for prolonged periods of time. Even though the quality of irrigation water is of increasing importance in the context of plant health, the presence of plant viruses in irrigation waters is understudied. In this study, we conducted a large-scale high-throughput sequencing (HTS)-based virome analysis of irrigation and surface water sources to obtain complete information about the abundance and diversity of plant viruses in such waters. We detected nucleic acids of plant viruses from 20 families, discovered several novel plant viruses from economically important taxa, like Tobamovirus and observed the influence of the water source on the present virome. By comparing viromes of water and surrounding plants, we observed presence of plant viruses in both compartments, especially in cases of large-scale outbreaks, such as that of tomato mosaic virus. Moreover, we demonstrated that water virome data can extensively inform us about the distribution and diversity of plant viruses for which only limited information is available from plants. Overall, the results of the study provided extensive insights into the virome of irrigation waters from the perspective of plant health. It also suggested that an HTS-based water virome surveillance system could be used to detect potential plant disease outbreaks and to survey the distribution and diversity of plant viruses in the ecosystem.

Application and Progress of Machine Learning in Pesticide Hazard and Risk Assessment

Long-term exposure to pesticides is associated with the incidence of cancer. With the exponential increase in the number of new pesticides being synthesized, it becomes more and more important to evaluate the toxicity of pesticides by means of simulated calculations. Based on existing data, machine learning methods can train and model the predictions of the effects of novel pesticides, which have limited available data. Combined with other technologies, this can aid the synthesis of new pesticides with specific active structures, detect pesticide residues, and identify their tolerable exposure levels. This article mainly discusses support vector machines, linear discriminant analysis, decision trees, partial least squares, and algorithms based on feedforward neural networks in machine learning. It is envisaged that this article will provide scientists and users with a better understanding of machine learning and its application prospects in pesticide toxicity assessment.

Sample and library preparation approaches for the analysis of the virome of irrigation water

BACKGROUND

The virome (i.e. community of mainly RNA and DNA eukaryotic viruses and bacteriophages) of waters is yet to be extensively explored. In particular, the virome of waters used for irrigation could therefore potentially carry viral pathogens that can contaminate fresh produce. One problem in obtaining viral sequences from irrigation waters is the relatively low amount of virus particles, as well as the presence of human, bacterial and protozoan cells. The present aimed study was to compare different processing, amplification, and sequencing approaches for virome characterization in irrigation waters.

RESULTS

Our analyses considered percentages of viral reads, values for diversity indices and number of families found in sequencing results. The results obtained suggest that enrichment protocols using two (bezonase and microccocal nuclease) or four enzymes at once (bezonase, microccocal nuclease, DNAse and RNase), regardless of an Amicon filtration step, are more appropriate than separated enzymatic treatments for virome characterization in irrigation water. The NetoVIR protocol combined with the ScriptSeq v2 RNA-Seq Library (P0-L20 protocol) showed the highest percentages of RNA viruses and identified the higher number of families.

CONCLUSION

Although virome characterization applied in irrigation waters is an important tool for protecting public health by informing on circulating human and zoonotic infections, optimized and standardized procedures should be followed to reduce the variability of results related to either the sample itself and the downstream bioinformatics analyses. Our results show that virome characterization can be an important tool in the discovery of pathogenic viruses in the environment and can be used to inform and optimize reference-based detection methods provided that appropriate and rigorous controls are included. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Use of a taxon-specific reference database for accurate metagenomics-based pathogen detection of Listeria monocytogenes in turkey deli meat and spinach

BACKGROUND

The reliability of culture-independent pathogen detection in foods using metagenomics is contingent on the quality and composition of the reference database. The inclusion of microbial sequences from a diverse representation of taxonomies in universal reference databases is recommended to maximize classification precision for pathogen detection. However, these sizable databases have high memory requirements that may be out of reach for some users. In this study, we aimed to assess the performance of a foodborne pathogen (FBP)-specific reference database (taxon-specific) relative to a universal reference database (taxon-agnostic). We tested our FBP-specific reference database's performance for detecting Listeria monocytogenes in two complex food matrices-ready-to-eat (RTE) turkey deli meat and prepackaged spinach-using three popular read-based DNA-to-DNA metagenomic classifiers: Centrifuge, Kraken 2 and KrakenUniq.

RESULTS

In silico host sequence removal led to substantially fewer false positive (FP) classifications and higher classification precision in RTE turkey deli meat datasets using the FBP-specific reference database. No considerable improvement in classification precision was observed following host filtering for prepackaged spinach datasets and was likely a consequence of a higher microbe-to-host sequence ratio. All datasets classified with Centrifuge using the FBP-specific reference database had the lowest classification precision compared to Kraken 2 or KrakenUniq. When a confidence-scoring threshold was applied, a nearly equivalent precision to the universal reference database was achieved for Kraken 2 and KrakenUniq. Recall was high for both reference databases across all datasets and classifiers. Substantially fewer computational resources were required for metagenomics-based detection of L. monocytogenes using the FBP-specific reference database, especially when combined with Kraken 2.

CONCLUSIONS

A universal (taxon-agnostic) reference database is not essential for accurate and reliable metagenomics-based pathogen detection of L. monocytogenes in complex food matrices. Equivalent classification performance can be achieved using a taxon-specific reference database when the appropriate quality control measures, classification software, and analysis parameters are applied. This approach is less computationally demanding and more attainable for the broader scientific and food safety communities.

Composition and variability of core phyllosphere fungal mycobiota on field-grown broccoli

BACKGROUND

Fresh vegetables harbor an assemblage of different microorganisms on their surfaces. The phyllosphere microbiota is important for maintaining plant health and managing crop quality before and after harvest. However, the diversity and ecology of fungal communities are largely unexplored in fresh vegetables. This study investigated the phyllosphere mycobiota of field-grown broccoli florets (n = 66) collected from 22 farms across four regions in Korea, using culturing, amplicon sequencing of the internal transcribed spacer region, and microbial network analysis.

RESULTS

Microbial network analysis identified core genera (Purpureocillium, Filobasidium, Cystofilobasidium, Papiliotrema, Aureobasidium, and unclassified genera of Capnodiales) specific to the broccoli phyllosphere. The composition and network complexity of core and unique populations varied among farming regions, and was associated with local agro-meteorological conditions. The complexity of microbial associations was higher in mature communities than in immature communities, but complexity was lost upon development of plant pathogenic disease. Broccoli mycobiota were classified according to the dominance of Purpurecillium. While Purpurecillium-type microbiota were prevalent in normal samples, Filobasidium-type microbiota were frequently observed in immature, damaged, or postharvest samples.

CONCLUSIONS

Together, fungal communities were important components of phyllosphere microbiota on fresh vegetables, and have substantial potential for exploitation to enhance and stabilize plant health and growth.

Viral Metagenomics as a Tool to Track Sources of Fecal Contamination: A One Health Approach

The One Health framework recognizes that human, animal, and environmental health are linked and highly interdependent. Fecal contamination of water, soil, foodstuff, and air may impact many aspects of One Health, and culture, PCR-based, and sequencing methods are utilized in the detection of fecal contamination to determine source, load, and risk to inform targeted mitigation strategies. Viruses, particularly, have been considered as fecal contamination indicators given the narrow host range many exhibit and their association with other biological contaminants. Culture- and molecular-based methods are considered the gold-standards for virus detection and for determining specific sources of fecal contamination via viral indicators. However, viral metagenomics is also being considered as a tool for tracking sources of fecal contamination. In the present review, studies tracking potential sources of fecal contamination in freshwaters, marine waters, foodstuff, soil, and air using viral metagenomics are discussed to highlight the potential of viral metagenomics for optimizing fecal source tracking. Limitations of the use of viral metagenomics to track fecal contamination sources, including sample processing, nucleic acid recovery, sequencing depth, and bioinformatics are also discussed. Finally, the present review discusses the potential of viral metagenomics as part of the toolbox of methods in a One Health approach.

Meta-analysis of the prevalence of the main human pathogens in vegetables, with emphasis on lettuce

This meta-analysis aims to summarize the available information on the prevalence of the main human pathogenic microorganisms in vegetables, with emphasis on lettuce (Lactuca sativa). The database searches included scientific papers from 1980 to 2019, without language restrictions. Inclusion criteria were prevalence or incidence studies published in peer-reviewed journals reporting the total number of vegetable samples studied and the number of samples positive for the presence of the studied pathogens. The target pathogens were grouped into the following categories: bacteria, parasites and viruses. Results of different vegetable types, years of sampling, analyzed regions or species of microorganisms reported in the same article were considered as different studies. Therefore, each scientific article may contain several studies. Multilevel random-effect meta-analysis models were fitted to estimate the mean occurrence rate of pathogenic microorganisms and to compare them with different factors potentially associated with the outcome. Overall, the prevalence of bacterial, parasitic and viral pathogens in vegetables was relatively low. The mean prevalence of bacterial hazards was < 0.023, with the exception of S. aureus, whose prevalence was estimated at 0.096. The mean occurrence rates of parasites and viruses were 0.067 (95 % CI: 0.056-0.080) and 0.079 (95 % CI: 0.054-0.113), respectively. The prevalence of pathogenic E. coli and parasites increased as the year of publication of the scientific articles progressed, whereas the prevalence of the other bacterial pathogens and enteric viruses was steady. The types of vegetables evaluated did not affect pathogen prevalence. The prevalence of pathogenic microorganisms differed according to the continent of origin, except for E. coli O157:H7 and parasites. The prevalence of pathogens in vegetables is of public health importance, especially in vegetable types that are eaten raw, without thermal treatment to inactivate pathogens. This meta-analysis results show the need to apply proper sanitation methods to treat raw vegetables in order to avoid foodborne infections.

Is SARS-CoV-2 a Concern for Food Safety? A Very Low Prevalence from a Food Survey during the COVID-19 Pandemic in Northern Italy

In 2019, SARS-CoV-2 was identified as the cause of an easily transmissible disease that was declared as a world pandemic. Foodborne transmission was never reported. However, early studies suggested that food could be involved in SARS-CoV-2 entry in the human gastrointestinal tract leading to possible infection, and highlighting the importance of further studies to inspect possible issues linked to food consumption. In this perspective, this work aimed at monitoring SARS-CoV-2 presence in some food and mains water samples in Northern Italy during the COVID-19 pandemic (2020–2022). A total of 1806 foods, 112 mains water samples, and 580 swabs on meat and dairy product surfaces were analyzed for SARS-CoV-2 RNA detection by Real-time PCR. All the analyzed samples were negative to viral RNA detection with the exception of one vegetable sample. Even if data on foodborne coronavirus transmission suggested a limited importance of this pathway, the impact of the current pandemic in Northern Italy deserved a rigorous investigation to rule out such possibility. Indeed, gaining insight on all SARS-CoV-2 possible transmission pathways, including the foodborne route, seemed of interest to maintain consumers’ confidence and trust in food safety, and for the effective management of the current, and future, possible pandemics.

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

Next-Generation Food Research: Use of Meta-Omic Approaches for Characterizing Microbial Communities Along the Food Chain

Microorganisms exist along the food chain and impact the quality and safety of foods in both positive and negative ways. Identifying and understanding the behavior of these microbial communities enable the implementation of preventative or corrective measures in public health and food industry settings. Current culture-dependent microbial analyses are time-consuming and target only specific subsets of microbes. However, the greater use of culture-independent meta-omic approaches has the potential to facilitate a thorough characterization of the microbial communities along the food chain. Indeed, these methods have shown potential in contributing to outbreak investigation, ensuring food authenticity, assessing the spread of antimicrobial resistance, tracking microbial dynamics during fermentation and processing, and uncovering the factors along the food chain that impact food quality and safety. This review examines the community-based approaches, and particularly the application of sequencing-based meta-omics strategies, for characterizing microbial communities along the food chain. Expected final online publication date for the Annual Review of Food Science and Technology, Volume 13 is March 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

NGS Techniques Reveal a High Diversity of RNA Viral Pathogens and Papillomaviruses in Fresh Produce and Irrigation Water

Fresh fruits and vegetables are susceptible to microbial contamination at every stage of the food production chain, and as a potential source of pathogens, irrigation water quality is a critical factor. Next-generation sequencing (NGS) techniques have been flourishing and expanding to a wide variety of fields. However, their application in food safety remains insufficiently explored, and their sensitivity requires improvement. In this study, quantitative polymerase chain reaction (qPCR) assays showed low but frequent contamination of common circulating viral pathogens, which were found in 46.9% of samples of fresh produce: 6/12 lettuce samples, 4/12 strawberries samples, and 5/8 parsley samples. Furthermore, the application of two different NGS approaches, target enrichment sequencing (TES) for detecting viruses that infect vertebrates and amplicon deep sequencing (ADS), revealed a high diversity of viral pathogens, especially Norovirus (NoV) and Human Papillomavirus (HPV), in fresh produce and irrigation water. All NoV and HPV types found in fresh fruit and vegetable samples were also detected in irrigation water sources, indicating that these viruses are common circulating pathogens in the population and that irrigation water may be the most probable source of viral pathogens in food samples.

Radiosensitivity of Feline Calicivirus F9 on Iceberg Lettuce Surface after Combined Treatments with γ-Radiation

ABSTRACT

The surface of iceberg lettuce (Lactuca sativa L.) is favorable to the survival of pathogens such as bacteria, parasites, and viruses such as norovirus. The present study was conducted to investigate the antiviral properties of treatment with cranberry juice (CJ), ozone (O3), and γ-radiation alone or in combination against feline calicivirus (FCV) F9 present on the surface of iceberg lettuce. The lettuce leaves were inoculated with virus suspensions at ∼6 log TCID50 (50% tissue culture infective dose)/mL and treated with CJ, O3, and γ-radiation alone and in combination during storage at 4°C. The D10-values of 1.21 kGy, 2.23% CJ, and 14.93 ppm of O3 were obtained when samples were treated with various radiation doses, CJ, and O3, respectively. Relative radiosensitization of FCV-F9 virus on lettuce was 1.20, 1.50, 1.09, and 1.00 after combined CJ treatments of 0.1, 0.25, 0.50, and 1.50%, respectively. Optimum treatments were 5 ppm for 7.5 min for O3, 0.25% CJ, and γ-radiation at 1.5 kGy when each treatment was used alone. The combination of the three treatments produced the highest reduction of 2.15 log TCID50/mL (from initial inoculation of ∼7 log TCID50/mL) during 10 days of storage at 4°C. Antibacterial properties of treatments and physicochemical quality of lettuce were investigated during 13 days of storage at 4°C. The treatment of lettuce with γ-radiation alone (1.5 kGy) reduced the total flora by 3 log CFU/g; however, the combination of CJ (0.25%) with irradiation (1.5 kGy) reduced it by ∼5 log CFU/g after 13 days of storage at 4°C. The texture and color of the lettuce treated with the combined treatments changed slightly during storage, and chlorophyll increased by 3.81 μg/mL after 10 days of storage at 4°C. Significant differences in taste and color were observed in lettuce without treatments after 5 days of storage, whereas no difference was observed after the 0.25% CJ or the combined treatments.

HIGHLIGHTS

Metagenomics-Based Proficiency Test of Smoked Salmon Spiked with a Mock Community

An inter-laboratory proficiency test was organized to assess the ability of participants to perform shotgun metagenomic sequencing of cold smoked salmon, experimentally spiked with a mock community composed of six bacteria, one parasite, one yeast, one DNA, and two RNA viruses. Each participant applied its in-house wet-lab workflow(s) to obtain the metagenomic dataset(s), which were then collected and analyzed using MG-RAST. A total of 27 datasets were analyzed. Sample pre-processing, DNA extraction protocol, library preparation kit, and sequencing platform, influenced the abundance of specific microorganisms of the mock community. Our results highlight that despite differences in wet-lab protocols, the reads corresponding to the mock community members spiked in the cold smoked salmon, were both detected and quantified in terms of relative abundance, in the metagenomic datasets, proving the suitability of shotgun metagenomic sequencing as a genomic tool to detect microorganisms belonging to different domains in the same food matrix. The implementation of standardized wet-lab protocols would highly facilitate the comparability of shotgun metagenomic sequencing dataset across laboratories and sectors. Moreover, there is a need for clearly defining a sequencing reads threshold, to consider pathogens as detected or undetected in a food sample.

The Basis of Peracetic Acid Inactivation Mechanisms for Rotavirus and Tulane Virus under Conditions Relevant for Vegetable Sanitation

We determined the disinfection efficacy and inactivation mechanisms of peracetic acid (PAA)-based sanitizer using pH values relevant for vegetable sanitation against rotavirus (RV) and Tulane virus (TV; a human norovirus surrogate). TV was significantly more resistant to PAA disinfection than RV: for a 2-log10 reduction of virus titer, RV required 1 mg/liter PAA for 3.5 min of exposure, while TV required 10 mg/liter PAA for 30 min. The higher resistance of TV can be explained, in part, by significantly more aggregation of TV in PAA solutions. The PAA mechanisms of virus inactivation were explored by quantifying (i) viral genome integrity and replication using reverse transcription-quantitative PCR (RT-qPCR) and (ii) virus-host receptor interactions using a cell-free binding assay with porcine gastric mucin conjugated with magnetic beads (PGM-MBs). We observed that PAA induced damage to both RV and TV genomes and also decreased virus-receptor interactions, with the latter suggesting that PAA damages viral proteins important for binding its host cell receptors. Importantly, the levels of genome-versus-protein damage induced by PAA were different for each virus. PAA inactivation correlated with higher levels of RV genome damage than of RV-receptor interactions. For PAA-treated TV, the opposite trends were observed. Thus, PAA inactivates each of these viruses via different molecular mechanisms. The findings presented here potentially contribute to the design of a robust sanitation strategy for RV and TV using PAA to prevent foodborne disease.IMPORTANCE In this study, we examined the inactivation mechanisms of peracetic acid (PAA), a sanitizer commonly used for postharvest vegetable washing, for two enteric viruses: Tulane virus (TV) as a human norovirus surrogate and rotavirus (RV). PAA disinfection mechanisms for RV were mainly due to genome damage. In contrast, PAA disinfection in TV was due to damage of the proteins important for binding to its host receptor. We also observed that PAA triggered aggregation of TV to a much greater extent than RV. These studies demonstrate that different viruses are inactivated via different PAA mechanisms. This information is important for designing an optimal sanitation practice for postharvest vegetable washing to minimize foodborne viral diseases.

Novel opportunities for NGS-based one health surveillance of foodborne viruses

Foodborne viral infections rank among the top 5 causes of disease, with noroviruses and hepatitis A causing the greatest burden globally. Contamination of foods by infected food handlers or through environmental pollution are the main sources of foodborne illness, with a lesser role for consumption of products from infected animals. Viral partial genomic sequencing has been used for more than two decades to track foodborne outbreaks and whole genome or metagenomics next-generation-sequencing (NGS) are new additions to the toolbox of food microbiology laboratories. We discuss developments in the field of targeted and metagenomic NGS, with an emphasis on application in food virology, the challenges and possible solutions towards future routine application.

Roles of Vegetable Surface Properties and Sanitizer Type on Annual Disease Burden of Rotavirus Illness by Consumption of Rotavirus-Contaminated Fresh Vegetables: A Quantitative Microbial Risk Assessment

Enteric viruses are often detected in water used for crop irrigation. One concern is foodborne viral disease via the consumption of fresh produce irrigated with virus-contaminated water. Although the food industry routinely uses chemical sanitizers to disinfect post-harvest fresh produce, it remains unknown how sanitizer and fresh produce properties affect the risk of viral illness through fresh produce consumption. A quantitative microbial risk assessment model was conducted to estimate (i) the health risks associated with consumption of rotavirus (RV)-contaminated fresh produce with different surface properties (endive and kale) and (ii) how risks changed when using peracetic acid (PAA) or a surfactant-based sanitizer. The modeling results showed that the annual disease burden depended on the combination of sanitizer and vegetable type when vegetables were irrigated with RV-contaminated water. Global sensitivity analyses revealed that the most influential factors in the disease burden were RV concentration in irrigation water and postharvest disinfection efficacy. A postharvest disinfection efficacy of higher than 99% (2-log₁₀ ) was needed to decrease the disease burden below the World Health Organization (WHO) threshold, even in scenarios with low RV concentrations in irrigation water (i.e., river water). All scenarios tested here with at least 99.9% (3-log₁₀ ) disinfection efficacy had a disease burden lower than the WHO threshold, except for the endive treated with PAA. The disinfection efficacy for the endive treated with PAA was only about 80%, leading to a disease burden 100 times higher than the WHO threshold. These findings should be considered and incorporated into future models for estimating foodborne viral illness risks.

Next-generation sequencing as a screening tool for foodborne pathogens in fresh produce

Next generation sequencing (NGS) approaches are increasingly applied to tracing microbial contaminants entering the food chain due to NGS' untargeted nature and ability to investigate non-culturable (and/or difficult to culture) organisms while yielding genomic information about the microbiota. So far, a plethora of microbes has been shown to be associated with fresh produce, but few studies have utilised NGS to identify contamination with human pathogens. This study aims to establish the limit of detection (LoD) for Salmonella and phage MS2 (a Norovirus surrogate) contamination of fresh produce employing NGS approaches on the Illumina MiSeq: 16S amplicon-sequencing, and RNA-seq, using ScriptSeq (Illumina) and NEBNext (New England BioLabs) kits. ScriptSeq proved the most sensitive approach; delivering an LoD of 10⁴ CFU reaction^-1 (Colony Forming Units) for Salmonella and 10⁵ PFU reaction^-1 (Plaque Forming Units) for phage MS2. Use of the NEBNext kit resulted in detection of Salmonella at 10⁶ CFU reaction^-1 and phage MS2 at 10⁷ PFU reaction^-1. 16S amplicon-sequencing yielded a similar LoD of 10⁵ CFU reaction^-1 for Salmonella but could not detect MS2. The tested NGS methodologies, in combination with bioinformatics approaches applied, proved less sensitive than conventional microbial detection approaches.

Metagenomic analysis of viruses, bacteria and protozoa in irrigation water

Viruses (e.g., noroviruses and hepatitis A and E virus), bacteria (e.g., Salmonella spp. and pathogenic Escherichia coli) and protozoa (e.g., Cryptosporidium parvum and Giardia intestinalis) are well-known contributors to food-borne illnesses linked to contaminated fresh produce. As agricultural irrigation increases the total amount of water used annually, reclaimed water is a good alternative to reduce dependency on conventional irrigation water sources. European guidelines have established acceptable concentrations of certain pathogens and/or indicators in irrigation water, depending on the irrigation system used and the irrigated crop. However, the incidences of food-borne infections are known to be underestimated and all the different pathogens contributing to these infections are not known. Next-generation sequencing (NGS) enables the determination of the viral, bacterial and protozoan populations present in a water sample, providing an opportunity to detect emerging pathogens and develop improved tools for monitoring the quality of irrigation water. This is a descriptive study of the virome, bacteriome and parasitome present in different irrigation water sources. We applied the same concentration method for all the studied samples and specific metagenomic approaches to characterize both DNA and RNA viruses, bacteria and protozoa. In general, most of the known viral species corresponded to plant viruses and bacteriophages. Viral diversity in river water varied over the year, with higher bacteriophage prevalences during the autumn and winter. Reservoir water contained Enterobacter cloacae, an opportunistic human pathogen and an indicator of fecal contamination, as well as Naegleria australiensis and Naegleria clarki. Hepatitis E virus and Naegleria fowleri, emerging human pathogens, were detected in groundwater. Reclaimed water produced in a constructed wetland system presented a virome and bacteriome that resembled those of freshwater samples (river and reservoir water). Viral, bacterial and protozoan pathogens were occasionally detected in the different irrigation water sources included in this study, justifying the use of improved NGS techniques to get a comprehensive evaluation of microbial species and potential environmental health hazards associated to irrigation water.

Application of shotgun metagenomics to smoked salmon experimentally spiked: Comparison between sequencing and microbiological data using different bioinformatic approaches

The aims of this study were i) to evaluate the possibility to detect and possibly quantify microorganisms belonging to different domains experimentally spiked in smoked salmon at known concentrations using shotgun metagenomics; ii) to compare the sequencing results using four bioinformatic tools. The salmon was spiked with six species of bacteria, including potential foodborne pathogens, as well as Cryptosporidium parvum, Saccharomyces cerevisiae and Bovine alphaherpesvirus 1. After spiking, the salmon was kept refrigerated before DNA extraction, library preparation and sequencing at 7 Gbp in paired ends at 150 bp. The bioinformatic tools named MG-RAST, OneCodex, CosmosID and MgMapper were used for the sequence analysis and the data provided were compared using STAMP. All bacteria spiked in the salmon were identified using all bioinformatic tools. Such tools were also able to assign the higher abundances to the species Propionibacterium freudenreichii spiked at the highest concentration in comparison to the other bacteria. Nevertheless, different abundances were quantified for bacteria spiked in the salmon at the same cell concentration. Cryptosporidium parvum was detected by all bioinformatics tools, while Saccharomyces cerevisiae by MG-RAST only. Finally, the DNA virus was detected by CosmosID and OneCodex only. Overall, the results of this study showed that shotgun metagenomics can be applied to detect microorganisms belonging to different domains in the same food sample. Nevertheless, a direct correlation between cell concentration of each spiked microorganism and number of corresponding reads cannot be established yet.

Free Chlorine Disinfection Mechanisms of Rotaviruses and Human Norovirus Surrogate Tulane Virus Attached to Fresh Produce Surfaces

To fill the knowledge gap on how effective free chlorine is against viral-contaminated produce, we inoculated the surfaces of outdoor- or greenhouse-grown kale and mustard with Rotavirus (RV) or a human norovirus surrogate (Tulane virus, TV) and then disinfected the leaves with free chlorine. Disinfection efficacies for RV strain OSU and Wa were approximately 1-log10 higher when attached to mustard than to kale. Similar disinfection efficacies were observed for TV attached to mustard or kale. When examining TV and RV OSU in suspension (not attached to leaf surfaces), TV was more resistant to free chlorine than RV OSU. Inactivation efficacies were higher for these viruses in suspension versus viruses attached to produce the surface. We also found that free chlorine damaged viral capsids, allowing free chlorine access to viral RNA to damage viral genomes. Exposure to free chlorine at 1.7 ppm over 1 min caused VP8* of RV OSU to lose its ability to bind to its host receptors. TV lost its ability to bind to its receptor only after exposure to free chlorine at 29 ppm over 1 min. Thus, to reduce foodborne viral infections, it is important to consider the differences in virus' reactivity and inactivation mechanisms with free chlorine.

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.

The Challenges of Analysing Highly Diverse Picobirnavirus Sequence Data

The reliable identification and classification of infectious diseases is critical for understanding their biology and controlling their impact. Recent advances in sequencing technology have allowed insight into the remarkable diversity of the virosphere, of which a large component remains undiscovered. For these emerging or undescribed viruses, the process of classifying unknown sequences is heavily reliant on existing nucleotide sequence information in public databases. However, due to the enormous diversity of viruses, and past focus on the most prevalent and impactful virus types, databases are often incomplete. Picobirnaviridae is a dsRNA virus family with broad host and geographic range, but with relatively little sequence information in public databases. The family contains one genus, Picobirnavirus, which may be associated with gastric illness in humans and animals. Little further information is available due in part to difficulties in identification. Here, we investigate diversity both within the genus Picobirnavirus and among other dsRNA virus types using a combined phylogenetic and functional (protein structure homology-modelling) approach. Our results show that diversity within picobirnavirus exceeds that seen between many other dsRNA genera. Furthermore, we find that commonly used practices employed to classify picobirnavirus, such as analysis of short fragments and trimming of sequences, can influence phylogenetic conclusions. The degree of phylogenetic and functional divergence among picobirnavirus sequences in our study suggests an enormous undiscovered diversity, which contributes to the undescribed “viral dark matter” component of metagenomic studies.

Analysis of frozen strawberries involved in a large norovirus gastroenteritis outbreak using next generation sequencing and digital PCR

Virus-contaminated frozen berries have been frequently identified as cause of foodborne disease outbreaks. To provide new tools for virus detection and characterization in berries, next generation sequencing (NGS) and reverse transcription-digital PCR (RT-dPCR) techniques were tested here with strawberries previously involved in a large-scale norovirus (NoV) gastroenteritis outbreak in Germany. By NGS, about 29 million sequence reads were generated, which mainly showed identities to sequences from the plant matrix and from the bacterial flora. Most abundant virus sequences originated from plant-specific viruses, whereas sequences with high identity to human viruses were rare. Only two sequence reads showed homologies to human NoV. They were identical to GII.P16/GII.13 NoV sequences from patients and a strawberry sample independently analyzed during the outbreak. Quantification of the GII NoV RNA of the berries using RT-dPCR confirmed a low mean virus amount of 185 copies/25 g, which is similar to independently assessed RT-qPCR results (257 copies/25 g). The study shows that identification of human-pathogenic viruses in naturally contaminated frozen berries is possible using NGS technologies. However, the method needs to be further optimized in order to enable convenient and reproducible detection of a low amount of human-pathogenic virus sequences in a background of highly abundant nucleic acids of other sources.

Inactivation Mechanisms of Human and Animal Rotaviruses by Solar UVA and Visible Light

Two rotavirus (RV) strains (sialidase-resistant Wa and sialidase-sensitive OSU) were irradiated with simulated solar UVA and visible light in sensitizer-free phosphate buffered solution (PBS) (lacking exogenous reactive oxygen species (ROS)) or secondary effluent wastewater (producing ROS). Although light attenuated for up to 15% through the secondary effluent wastewater (SEW), the inactivation efficacies increased by 0.7 log₁₀ for Wa and 2 log₁₀ for OSU compared to those in sensitizer-free phosphate buffered solution (PBS) after 4 h of irradiation. A binding assay using magnetic beads coated with porcine gastric mucin containing receptors for rotaviruses (PGM-MB) was developed to determine if inactivation influenced RV binding to its receptors. The linear correlation between the reduction in infectivity and the reduction in binding after irradiation in sensitizer-free solution suggests that the main mechanism of RV inactivation in the absence of exogenous ROS was due to damage to VP8*, the RV protein that binds to host cell receptors. For a given reduction in infectivity, greater damage in VP8* was observed with sialidase-resistant Wa compared to sialidase-sensitive OSU. The lack of correlation between the reduction in infectivity and the reduction in binding, in SEW, led us to include RNase treatment before the binding step to quantify virions with intact protein capsids and exclude virions that can bind to the receptors but have their capsid permeable after irradiation. This assay showed a linear correlation between the reduction in RV infectivity and RV-receptor interactions, suggesting that RV inactivation in SEW was due to compromised capsid proteins other than the VP8* protein. Thus, rotavirus inactivation by UVA and visible light irradiation depends on both the formation of ROS and the stability of viral proteins.

Impact of Unit Operations From Farm to Fork on Microbial Safety and Quality of Foods

Unit operations modify material properties aiming to produce uniform and high-quality food products with greater acceptance by the increasingly demanding consumers or with longer shelf life and better possibilities of storage and transport. Microorganisms, including bacteria, molds, viruses, and parasites, may have different susceptibilities to unit operations employed during food processing. On-farm (cleaning, selection and classification, cooling, storage, and transport) and on-factory unit operations (heating, refrigeration/freezing, dehydration, modification of atmosphere, irradiation, and physical, chemical, and microbial-based operations) are commonly employed throughout food production chain. The intensity and combination of unit operations along with food composition, packaging, and storage conditions will influence on the dominance of specific microorganisms, which can be pathogenic or responsible for spoilage. Thus, in the context of food safety objective (FSO), the knowledge and the quantification of the effects caused by each step of processing can enable to control and ensure the quality and safety of manufactured products.

Selected Viruses Detected on and in our Food

PURPOSE OF REVIEW

The purpose of this review is to provide an update on recent literature and findings concerning selected foodborne viruses. Two groups of viruses were selected: (a) the most important viruses contaminating food, based on numbers of publications in the last 5 years and (b) viruses infecting sources of food that might have an impact on human health.

RECENT FINDINGS

Important foodborne viruses such as norovirus, hepatitis A and rotavirus are usually "only" contaminating food and are detected on the surface of foodstuffs. However, they are threats to human public health and make up for the majority of cases. In contrast, the meaning of viruses born from within the food such as natural animal and plant viruses is still in many cases unknown. An exception is Hepatitis E virus that is endemic in pigs, transmitted via pork meat and is recognised as an emerging zoonosis in industrialised countries.

SUMMARY

Even though the clinical meaning of "new" foodborne viruses, often detected by next generation sequencing, still needs clarification, the method has great potential to enhance surveillance and detection particularly in view of an increasingly globalised food trade.

A metagenomic assessment of viral contamination on fresh parsley plants irrigated with fecally tainted river water

Microbial food-borne diseases are still frequently reported despite the implementation of microbial quality legislation to improve food safety. Among all the microbial agents, viruses are the most important causative agents of food-borne outbreaks. The development and application of a new generation of sequencing techniques to test for viral contaminants in fresh produce is an unexplored field that allows for the study of the viral populations that might be transmitted by the fecal-oral route through the consumption of contaminated food. To advance this promising field, parsley was planted and grown under controlled conditions and irrigated using contaminated river water. Viruses polluting the irrigation water and the parsley leaves were studied by using metagenomics. To address possible contamination due to sample manipulation, library preparation, and other sources, parsley plants irrigated with nutritive solution were used as a negative control. In parallel, viruses present in the river water used for plant irrigation were analyzed using the same methodology. It was possible to assign viral taxons from 2.4 to 74.88% of the total reads sequenced depending on the sample. Most of the viral reads detected in the river water were related to the plant viral families Tymoviridae (66.13%) and Virgaviridae (14.45%) and the phage viral families Myoviridae (5.70%), Siphoviridae (5.06%), and Microviridae (2.89%). Less than 1% of the viral reads were related to viral families that infect humans, including members of the Adenoviridae, Reoviridae, Picornaviridae and Astroviridae families. On the surface of the parsley plants, most of the viral reads that were detected were assigned to the Dicistroviridae family (41.52%). Sequences related to important viral pathogens, such as the hepatitis E virus, several picornaviruses from species A and B as well as human sapoviruses and GIV noroviruses were detected. The high diversity of viral sequences found in the parsley plants suggests that irrigation on fecally-tainted food may have a role in the transmission of a wide diversity of viral families. This finding reinforces the idea that the best way to avoid food-borne viral diseases is to introduce good field irrigation and production practices. New strains have been identified that are related to the Picornaviridae and distantly related to the Hepeviridae family. However, the detection of a viral genome alone does not necessarily indicate there is a risk of infection or disease development. Thus, further investigation is crucial for correlating the detection of viral metagenomes in samples with the risk of infection. There is also an urgent need to develop new methods to improve the sensitivity of current Next Generation Sequencing (NGS) techniques in the food safety area.

High Throughput Sequencing for Detection of Foodborne Pathogens

High-throughput sequencing (HTS) is becoming the state-of-the-art technology for typing of microbial isolates, especially in clinical samples. Yet, its application is still in its infancy for monitoring and outbreak investigations of foods. Here we review the published literature, covering not only bacterial but also viral and Eukaryote food pathogens, to assess the status and potential of HTS implementation to inform stakeholders, improve food safety and reduce outbreak impacts. The developments in sequencing technology and bioinformatics have outpaced the capacity to analyze and interpret the sequence data. The influence of sample processing, nucleic acid extraction and purification, harmonized protocols for generation and interpretation of data, and properly annotated and curated reference databases including non-pathogenic "natural" strains are other major obstacles to the realization of the full potential of HTS in analytical food surveillance, epidemiological and outbreak investigations, and in complementing preventive approaches for the control and management of foodborne pathogens. Despite significant obstacles, the achieved progress in capacity and broadening of the application range over the last decade is impressive and unprecedented, as illustrated with the chosen examples from the literature. Large consortia, often with broad international participation, are making coordinated efforts to cope with many of the mentioned obstacles. Further rapid progress can therefore be prospected for the next decade.

Bovine leukaemia virus DNA in fresh milk and raw beef for human consumption

Bovine leukaemia virus (BLV) is the causative agent of enzootic bovine leucosis, which has been reported worldwide. BLV has been found recently in human tissue and it could have a significant impact on human health. A possible hypothesis regarding viral entry to humans is through the consumption of infected foodstuffs. This study was aimed at detecting the presence of BLV DNA in raw beef and fresh milk for human consumption. Nested PCR directed at the BLV gag gene (272 bp) was used as a diagnostic test. PCR products were confirmed by Sanger sequencing. Forty-nine per cent of the samples proved positive for the presence of proviral DNA. This is the first study highlighting the presence of the BLV gag gene in meat products for human consumption and confirms the presence of the viral DNA in raw milk, as in previous reports. The presence of viral DNA in food products could suggest that viral particles may also be found. Further studies are needed to confirm the presence of infected viral particles, even though the present findings could represent a first approach to BLV transmission to humans through foodstuff consumption.

A Review on the Applications of Next Generation Sequencing Technologies as Applied to Food-Related Microbiome Studies

The development of next generation sequencing (NGS) techniques has enabled researchers to study and understand the world of microorganisms from broader and deeper perspectives. The contemporary advances in DNA sequencing technologies have not only enabled finer characterization of bacterial genomes but also provided deeper taxonomic identification of complex microbiomes which in its genomic essence is the combined genetic material of the microorganisms inhabiting an environment, whether the environment be a particular body econiche (e.g., human intestinal contents) or a food manufacturing facility econiche (e.g., floor drain). To date, 16S rDNA sequencing, metagenomics and metatranscriptomics are the three basic sequencing strategies used in the taxonomic identification and characterization of food-related microbiomes. These sequencing strategies have used different NGS platforms for DNA and RNA sequence identification. Traditionally, 16S rDNA sequencing has played a key role in understanding the taxonomic composition of a food-related microbiome. Recently, metagenomic approaches have resulted in improved understanding of a microbiome by providing a species-level/strain-level characterization. Further, metatranscriptomic approaches have contributed to the functional characterization of the complex interactions between different microbial communities within a single microbiome. Many studies have highlighted the use of NGS techniques in investigating the microbiome of fermented foods. However, the utilization of NGS techniques in studying the microbiome of non-fermented foods are limited. This review provides a brief overview of the advances in DNA sequencing chemistries as the technology progressed from first, next and third generations and highlights how NGS provided a deeper understanding of food-related microbiomes with special focus on non-fermented foods.

Application of next generation sequencing toward sensitive detection of enteric viruses isolated from celery samples as an example of produce

Next generation sequencing (NGS) holds promise as a single application for both detection and sequence identification of foodborne viruses; however, technical challenges remain due to anticipated low quantities of virus in contaminated food. In this study, with a focus on data analysis using several bioinformatics tools, we applied NGS toward amplification-independent detection and identification of norovirus at low copy (<10³ copies) or within multiple strains from produce. Celery samples were inoculated with human norovirus (stool suspension) either as a single norovirus strain, a mixture of strains (GII.4 and GII.6), or a mixture of different species (hepatitis A virus and norovirus). Viral RNA isolation and recovery was confirmed by RT-qPCR, and optimized for library generation and sequencing without amplification using the Illumina MiSeq platform. Extracts containing either a single virus or a two-virus mixture were analyzed using two different analytic approaches to achieve virus detection and identification. First an overall assessment of viral genome coverage for samples varying in copy numbers (1.1×10³ to 1.7×10⁷) and genomic content (single or multiple strains in various ratios) was completed by reference-guided mapping. Not unexpectedly, this targeted approach to identification was successful in correctly mapping reads, thus identifying each virus contained in the inoculums even at low copy (estimated at 12 copies). For the second (metagenomic) approach, samples were treated as "unknowns" for data analyses using (i) a sequence-based alignment with a local database, (ii) an "in-house" k-mer tool, (iii) a commercially available metagenomics bioinformatic analysis platform cosmosID, and (iv) an open-source program Kraken. Of the four metagenomics tools applied in this study, only the local database alignment and in-house k-mer tool were successful in detecting norovirus (as well as HAV) at low copy (down to <10³ copies) and within a mixture of virus strains or species. The results of this investigation provide support for continued investigation into the development and integration of these analytical tools for identification and detection of foodborne viruses.

Metagenomics: The Next Culture-Independent Game Changer

A trend towards the abandonment of obtaining pure culture isolates in frontline laboratories is at a crossroads with the ability of public health agencies to perform their basic mandate of foodborne disease surveillance and response. The implementation of culture-independent diagnostic tests (CIDTs) including nucleic acid and antigen-based assays for acute gastroenteritis is leaving public health agencies without laboratory evidence to link clinical cases to each other and to food or environmental substances. This limits the efficacy of public health epidemiology and surveillance as well as outbreak detection and investigation. Foodborne outbreaks have the potential to remain undetected or have insufficient evidence to support source attribution and may inadvertently increase the incidence of foodborne diseases. Next-generation sequencing of pure culture isolates in clinical microbiology laboratories has the potential to revolutionize the fields of food safety and public health. Metagenomics and other 'omics' disciplines could provide the solution to a cultureless future in clinical microbiology, food safety and public health. Data mining of information obtained from metagenomics assays can be particularly useful for the identification of clinical causative agents or foodborne contamination, detection of AMR and/or virulence factors, in addition to providing high-resolution subtyping data. Thus, metagenomics assays may provide a universal test for clinical diagnostics, foodborne pathogen detection, subtyping and investigation. This information has the potential to reform the field of enteric disease diagnostics and surveillance and also infectious diseases as a whole. The aim of this review will be to present the current state of CIDTs in diagnostic and public health laboratories as they relate to foodborne illness and food safety. Moreover, we will also discuss the diagnostic and subtyping utility and concomitant bias limitations of metagenomics and comparable detection techniques in clinical microbiology, food and public health laboratories. Early advances in the discipline of metagenomics, however, have indicated noteworthy challenges. Through forthcoming improvements in sequencing technology and analytical pipelines among others, we anticipate that within the next decade, detection and characterization of pathogens via metagenomics-based workflows will be implemented in routine usage in diagnostic and public health laboratories.

Effect of Leaf Surface Chemical Properties on Efficacy of Sanitizer for Rotavirus Inactivation

The use of sanitizers is essential for produce safety. However, little is known about how sanitizer efficacy varies with respect to the chemical surface properties of produce. To answer this question, the disinfection efficacies of an oxidant-based sanitizer and a new surfactant-based sanitizer for porcine rotavirus (PRV) strain OSU were examined. PRV was attached to the leaf surfaces of two kale cultivars with high epicuticular wax contents and one cultivar of endive with a low epicuticular wax content and then treated with each sanitizer. The efficacy of the oxidant-based sanitizer correlated with leaf wax content as evidenced by the 1-log10 PRV disinfection on endive surfaces (low wax content) and 3-log10 disinfection of the cultivars with higher wax contents. In contrast, the surfactant-based sanitizer showed similar PRV disinfection efficacies (up to 3 log10) that were independent of leaf wax content. A statistical difference was observed with the disinfection efficacies of the oxidant-based sanitizer for suspended and attached PRV, while the surfactant-based sanitizer showed similar PRV disinfection efficacies. Significant reductions in the entry and replication of PRV were observed after treatment with either disinfectant. Moreover, the oxidant-based-sanitizer-treated PRV showed sialic acid-specific binding to the host cells, whereas the surfactant-based sanitizer increased the nonspecific binding of PRV to the host cells. These findings suggest that the surface properties of fresh produce may affect the efficacy of virus disinfection, implying that food sanitizers should be carefully selected for the different surface characteristics of fresh produce.

IMPORTANCE

Food sanitizer efficacies are affected by the surface properties of vegetables. This study evaluated the disinfection efficacies of two food sanitizers, an oxidant-based sanitizer and a surfactant-based sanitizer, on porcine rotavirus strain OSU adhering to the leaf epicuticular surfaces of high- and low-wax-content cultivars. The disinfection efficacy of the oxidant-based sanitizer was affected by the surface properties of the vegetables, while the surfactant-based sanitizer was effective for both high- and low-wax leafy vegetable cultivars. This study suggests that the surface properties of vegetables may be an important factor that interacts with disinfection with food sanitizers of rotaviruses adhering to fresh produce.