Co-enriching microflora associated with culture based methods to detect Salmonella from tomato phyllosphere

Limit of detection of Salmonella ser. Enteritidis using culture-based versus culture-independent diagnostic approaches

To prevent the spread of foodborne illnesses, the presence of pathogens in the food chain is monitored by government agencies and food producers. The culture-based methods currently employed are sensitive but time- and labor-intensive, leading to increasing interest in exploring culture-independent diagnostic tests (CIDTs) for pathogen detection. However, few studies quantify the relative sensitivity and reliability of these CIDTs compared to current approaches. To address this issue, we conducted a comparison of the limit of detection (LOD50) for Salmonella between a culture-based method and three CIDTs: qPCR (targeting invA and stn), metabarcode (16S) sequencing, and shotgun metagenomic sequencing. Samples of chicken feed and chicken caecal contents were spiked with S. serovar Enteritidis and subjected to culture- and DNA-based detection methods. To explore the impact of non-selective enrichment on LOD50, all samples underwent both immediate DNA extraction and overnight enrichment prior to gDNA extraction. In addition to this spike-in experiment, feed and caecal samples acquired from the field were tested with culturing, qPCR, and metabarcoding. In general, LOD50 was comparable between qPCR and shotgun sequencing methods. Overnight microbiological enrichment resulted in an improvement in LOD50 with up to a three-log decrease. However, Salmonella reads were detected in some unspiked feed samples, suggesting false-positive detection of Salmonella. In addition, the LOD50 in feeds was three logs lower than in caecal contents, underscoring the impact of background microbiota on Salmonella detection using all methods.

IMPORTANCE

The appeal of culture-independent diagnostic tests (CIDTs) is increased speed with lowered cost, as well as the potential to detect multiple pathogen species in a single analysis and to monitor other areas of concern such as antimicrobial resistance genes or virulence factors. This study provides quantitative data on the sensitivity of CIDTs relative to current approaches, which is essential for determining the feasibility of implementing these methods in pathogen surveillance programs.

Growth assessment of Salmonella enterica multi-serovar populations in poultry rinsates with commonly used enrichment and plating media

Isolation of Salmonella from enrichment cultures of food or environmental samples is a complicated process. Numerous factors including fitness in various selective enrichment media, relative starting concentrations in pre-enrichment, and competition among multi-serovar populations and associated natural microflora, come together to determine which serovars are identified from a given sample. A recently developed approach for assessing the relative abundance (RA) of multi-serovar Salmonella populations (CRISPR-SeroSeq or Deep Serotyping, DST) is providing new insight into how these factors impact the serovars observed, especially when different selective enrichment methods are used to identify Salmonella from a primary enrichment sample. To illustrate this, we examined Salmonella-positive poultry pre-enrichment samples through the selective enrichment process in Tetrathionate (TT) and Rappaport Vassiliadis (RVS) broths and assessed recovery of serovars with each medium. We observed the RA of serovars detected post selective enrichment varied depending on the medium used, initial concentration, and competitive fitness factors, all which could result in minority serovars in pre-enrichment becoming dominant serovars post selective enrichment. The data presented provide a greater understanding of culture biases and lays the groundwork for investigations into robust enrichment and plating media combinations for detecting Salmonella serovars of greater concern for human health.

Comparison of Phenotype Nutritional Profiles and Phosphate Metabolism Genes in Four Serovars of Salmonella enterica from Water Sources

The surveillance of foods for Salmonella is hindered by bias in common enrichment media where serovars implicated in human illness are outgrown by less virulent serovars. We examined four Salmonella serovars, two common in human illness (Enteritidis and Typhimurium) and two that often dominate enrichments (Give and Kentucky), for factors that might influence culture bias. The four serovars had similar growth kinetics in Tryptic Soy Broth and Buffered Peptone Water. Phenotype microarray analysis with 950 chemical substrates to assess nutrient utilization and stress resistance revealed phenotype differences between serovars. Strains of S. Enteritidis had better utilization of plant-derived sugars such as xylose, mannitol, rhamnose, and fructose, while S. Typhimurium strains were able to metabolize tagatose. Strains of S. Kentucky used more compounds as phosphorus sources and grew better with inorganic phosphate as the sole phosphorus source. The sequences of nine genes involved in phosphate metabolism were compared, and there were differences between serovars in the catalytic ATP-binding domain of the histidine kinase phoR. Analysis of the predicted PhoR amino acid sequences from additional Salmonella genomes indicated a conservation of sequences each within the Typhimurium, Give, and Enteritidis serovars. However, three different PhoR versions were observed in S. Kentucky.

16S microbiome analysis of microbial communities in distribution centers handling fresh produce

Little is known about the microbial communities found in distribution centers (DCs), especially in those storing and handling food. As many foodborne bacteria are known to establish residence in food facilities, it is reasonable to assume that DCs handling foods are also susceptible to pathogen colonization. To investigate the microbial communities within DCs, 16S amplicon sequencing was completed on 317 environmental surface sponge swabs collected in DCs (n = 18) across the United States. An additional 317 swabs were collected in parallel to determine if any viable Listeria species were also present at each sampling site. There were significant differences in median diversity measures (observed, Shannon, and Chao1) across individual DCs, and top genera across all reads were Carnobacterium_A, Psychrobacter, Pseudomonas_E, Leaf454, and Staphylococcus based on taxonomic classifications using the Genome Taxonomy Database. Of the 39 16S samples containing Listeria ASVs, four of these samples had corresponding Listeria positive microbiological samples. Data indicated a predominance of ASVs identified as cold-tolerant bacteria in environmental samples collected in DCs. Differential abundance analysis identified Carnobacterium_A, Psychrobacter, and Pseudomonas_E present at a significantly greater abundance in Listeria positive microbiological compared to those negative for Listeria. Additionally, microbiome composition varied significantly across groupings within variables (e.g., DC, season, general sampling location).

Microbial Antagonism in Food-Enrichment Culture: Inhibition of Shiga Toxin-Producing Escherichia coli and Shigella Species

Bacterial pathogens, such as Shiga toxin-producing Escherichia coli (STEC) and Shigella spp., are important causes of foodborne illness internationally. Recovery of these organisms from foods is critical for food safety investigations to support attribution of illnesses to specific food commodities; however, isolation of bacterial cultures can be challenging. Methods for the isolation of STEC and Shigella spp. from foods typically require enrichment to amplify target organisms to detectable levels. Yet, during enrichment, target organisms can be outcompeted by other bacteria in food matrices due to faster growth rates, or through production of antimicrobial agents such as bacteriocins or bacteriophages. The purpose of this study was to evaluate the occurrence of Shigella and STEC inhibitors produced by food microbiota. The production of antimicrobial compounds in cell-free extracts from 200 bacterial strains and 332 food-enrichment broths was assessed. Cell-free extracts produced by 23 (11.5%) of the strains tested inhibited growth of at least one of the five Shigella and seven STEC indicator strains used in this study. Of the 332 enrichment broths tested, cell-free extracts from 25 (7.5%) samples inhibited growth of at least one of the indicator strains tested. Inhibition was most commonly associated with E. coli recovered from meat products. Most of the inhibiting compounds were determined to be proteinaceous (34 of the 48 positive samples, 71%; including 17 strains, 17 foods) based on inactivation by proteolytic enzymes, indicating presence of bacteriocins. The cell-free extracts from 13 samples (27%, eight strains, five foods) were determined to contain bacteriophages based on the observation of plaques in diluted extracts and/or resistance to proteolytic enzymes. These results indicate that the production of inhibitors by food microbiota may be an important challenge for the recovery of foodborne pathogens, particularly for Shigella sonnei. The performance of enrichment media for recovery of Shigella and STEC could be improved by mitigating the impact of inhibitors produced by food microbiota during the enrichment process.

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

ABSTRACT

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

HIGHLIGHTS

Salmonella Genomics in Public Health and Food Safety

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

Surveillance of Listeria monocytogenes: Early Detection, Population Dynamics, and Quasimetagenomic Sequencing during Selective Enrichment

In this study, we addressed different aspects regarding the implementation of quasimetagenomic sequencing as a hybrid surveillance method in combination with enrichment for early detection of Listeria monocytogenes in the food industry. Different experimental enrichment cultures were used, comprising seven L. monocytogenes strains of different sequence types (STs), with and without a background microbiota community. To assess whether the proportions of the different STs changed over time during enrichment, the growth and population dynamics were assessed using dapE colony sequencing and dapE and 16S rRNA amplicon sequencing. There was a tendency of some STs to have a higher relative abundance during the late stage of enrichment when L. monocytogenes was enriched without background microbiota. When coenriched with background microbiota, the population dynamics of the different STs was more consistent over time. To evaluate the earliest possible time point during enrichment that allows the detection of L. monocytogenes and at the same time the generation of genetic information that enables an estimation regarding the strain diversity in a sample, quasimetagenomic sequencing was performed early during enrichment in the presence of the background microbiota using Oxford Nanopore Technologies Flongle and Illumina MiSeq sequencing. The application of multiple displacement amplification (MDA) enabled detection of L. monocytogenes (and the background microbiota) after only 4 h of enrichment using both applied sequencing approaches. The MiSeq sequencing data additionally enabled the prediction of cooccurring L. monocytogenes strains in the samples.

IMPORTANCE We showed that a combination of a short primary enrichment combined with MDA and Nanopore sequencing can accelerate the traditional process of cultivation and identification of L. monocytogenes. The use of Illumina MiSeq sequencing additionally allowed us to predict the presence of cooccurring L. monocytogenes strains. Our results suggest quasimetagenomic sequencing is a valuable and promising hybrid surveillance tool for the food industry that enables faster identification of L. monocytogenes during early enrichment. Routine application of this approach could lead to more efficient and proactive actions in the food industry that prevent contamination and subsequent product recalls and food destruction, economic and reputational losses, and human listeriosis cases.

Detection of Campylobacter jejuni from Fresh Produce: Comparison of Culture- and PCR-based Techniques, and Metagenomic Approach for Analyses of the Microbiome before and after Enrichment

ABSTRACT

In this study, we compared the efficiency of culture-based methods with or without membrane filtration, real-time PCR, and digital droplet PCR (ddPCR) for the detection of Campylobacter in fresh produce. Alfalfa sprouts, clover sprouts, coleslaw, and lettuce salad spiked with Campylobacter jejuni were enriched in Bolton broth for 48 h, and enrichment cultures were either directly inoculated onto modified charcoal-cefoperazone-deoxycholate agar or applied on membrane filters placed on the surface of plating media. In parallel, 2-mL Bolton broth cultures were taken to extract DNA for real-time PCR and ddPCR assays and bacterial community analysis. A developed primer set for ddPCR and real-time PCR was evaluated for its inclusivity and exclusivity using pure culture of C. jejuni and non-C. jejuni strains, respectively. In pure culture, the primer set reacted only with C. jejuni strains and showed negative reaction to non-C. jejuni strains. There was no significant difference (P > 0.05) in the detection efficiency of positive Campylobacter isolates from coleslaw and lettuce salad using four detection methods. However, for sprout samples, the detection efficiency of the culture method was significantly (P < 0.05) lower than those of the two PCR assays and the filtration method. The analysis also revealed the presence of Pseudomonas and Acinetobacter as the most prevalent competing microbiota in enriched culture and only Acinetobacter on agar plates in the selective culture step.

HIGHLIGHTS

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.

An investigation into the anaerobic spoilage microbiota of beef carcass and rump steak cuts using high- throughput sequencing

The presence of anaerobic microflora on fresh beef carcass and rump steaks, which may contribute to meat spoilage, was explored in this study. A total of 120 carcass and 120 rump steak swabs were collected immediately after slaughtering and boning, respectively from five meat plants, anaerobically incubated and enriched at 4°C for 3 weeks. This was followed by DNA extraction and 16S rRNA amplicon sequencing using the Illumina MiSeq, with subsequent bioinformatics analysis. The enriched microbiota of the samples was classified and grouped into 149 operational taxonomic units (OTUs). The microbiota recovered from both sample types consisted mainly of Carnobacterium, with an average relative abundance of 28.4% and 32.8% in beef carcasses and beef rump steaks, respectively. This was followed by Streptococcus, Serratia, Lactococcus, Enterococcus, Escherichia-Shigella, Raoultella and Aeromonas ranging from 1.5 to 20% and 0.1 to 29.8% in enriched carcasses and rump steak swabs, respectively. Trichococcus, Bacteroides, Dysgomonas, Providencia, Paraclostridium and Proteus were also present ranging from 0 to 0.8% on carcass and 0 to 1.8% on rump steak swabs, respectively. Alpha and beta diversity measurements showed limited diversity between the two sample types, but some differences between samples from the beef plants investigated were evident. This study highlights the presence of potential spoilage bacteria, mainly anaerobic genera on and between carcass and rump steaks, as an indication of contamination on and between these samples.

Evaluating the accuracy of Listeria monocytogenes assemblies from quasimetagenomic samples using long and short reads

BACKGROUND

Whole genome sequencing of cultured pathogens is the state of the art public health response for the bioinformatic source tracking of illness outbreaks. Quasimetagenomics can substantially reduce the amount of culturing needed before a high quality genome can be recovered. Highly accurate short read data is analyzed for single nucleotide polymorphisms and multi-locus sequence types to differentiate strains but cannot span many genomic repeats, resulting in highly fragmented assemblies. Long reads can span repeats, resulting in much more contiguous assemblies, but have lower accuracy than short reads.

RESULTS

We evaluated the accuracy of Listeria monocytogenes assemblies from enrichments (quasimetagenomes) of naturally-contaminated ice cream using long read (Oxford Nanopore) and short read (Illumina) sequencing data. Accuracy of ten assembly approaches, over a range of sequencing depths, was evaluated by comparing sequence similarity of genes in assemblies to a complete reference genome. Long read assemblies reconstructed a circularized genome as well as a 71 kbp plasmid after 24 h of enrichment; however, high error rates prevented high fidelity gene assembly, even at 150X depth of coverage. Short read assemblies accurately reconstructed the core genes after 28 h of enrichment but produced highly fragmented genomes. Hybrid approaches demonstrated promising results but had biases based upon the initial assembly strategy. Short read assemblies scaffolded with long reads accurately assembled the core genes after just 24 h of enrichment, but were highly fragmented. Long read assemblies polished with short reads reconstructed a circularized genome and plasmid and assembled all the genes after 24 h enrichment but with less fidelity for the core genes than the short read assemblies.

CONCLUSION

The integration of long and short read sequencing of quasimetagenomes expedited the reconstruction of a high quality pathogen genome compared to either platform alone. A new and more complete level of information about genome structure, gene order and mobile elements can be added to the public health response by incorporating long read analyses with the standard short read WGS outbreak response.

Direct identification and molecular characterization of zoonotic hazards in raw milk by metagenomics using Brucella as a model pathogen

Metagenomics is a valuable diagnostic tool for enhancing microbial food safety because (i) it enables the untargeted detection of pathogens, (ii) it is fast since primary isolation of micro-organisms is not required, and (iii) it has high discriminatory power allowing for a detailed molecular characterization of pathogens. For shotgun metagenomics, total nucleic acids (NAs) are isolated from complex samples such as foodstuff. Along with microbial NAs, high amounts of matrix NAs are extracted that might outcompete microbial NAs during next-generation sequencing and compromise sensitivity for the detection of low abundance micro-organisms. Sensitive laboratory methods are indispensable for detecting highly pathogenic foodborne bacteria like Brucella spp., because a low infectious dose is sufficient to cause human disease through the consumption of contaminated dairy or meat products. In our study, we applied shotgun metagenomic sequencing for the identification and characterization of Brucella spp. in artificially and naturally contaminated raw milk from various ruminant species. With the depletion of eukaryotic cells prior to DNA extraction, Brucella was detectable at 10 bacterial cells ml⁻¹, while at the same time microbiological culture and isolation of the fastidious bacteria commonly failed. Moreover, we were able to retrieve the genotype of a Brucella isolate from a metagenomic dataset, indicating the potential of metagenomics for outbreak investigations using SNPs and core-genome multilocus sequence typing (cgMLST). To improve diagnostic applications, we developed a new bioinformatics approach for strain prediction based on SNPs to identify the correct species and define a certain strain with only low numbers of genus-specific reads per sample. This pipeline turned out to be more sensitive and specific than Mash Screen. In raw milk samples, we simultaneously detected numerous other zoonotic pathogens, antimicrobial resistance genes and virulence factors. Our study showed that metagenomics is a highly sensitive tool for biological risk assessment of foodstuffs, particularly when pathogen isolation is hazardous or challenging.

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.

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.

Microbiomes Associated With Foods From Plant and Animal Sources

Food microbiome composition impacts food safety and quality. The resident microbiota of many food products is influenced throughout the farm to fork continuum by farming practices, environmental factors, and food manufacturing and processing procedures. Currently, most food microbiology studies rely on culture-dependent methods to identify bacteria. However, advances in high-throughput DNA sequencing technologies have enabled the use of targeted 16S rRNA gene sequencing to profile complex microbial communities including non-culturable members. In this study we used 16S rRNA gene sequencing to assess the microbiome profiles of plant and animal derived foods collected at two points in the manufacturing process; post-harvest/pre-retail (cilantro) and retail (cilantro, masala spice mixes, cucumbers, mung bean sprouts, and smoked salmon). Our findings revealed microbiome profiles, unique to each food, that were influenced by the moisture content (dry spices, fresh produce), packaging methods, such as modified atmospheric packaging (mung bean sprouts and smoked salmon), and manufacturing stage (cilantro prior to retail and at retail). The masala spice mixes and cucumbers were comprised mainly of Proteobacteria, Firmicutes, and Actinobacteria. Cilantro microbiome profiles consisted mainly of Proteobacteria, followed by Bacteroidetes, and low levels of Firmicutes and Actinobacteria. The two brands of mung bean sprouts and the three smoked salmon samples differed from one another in their microbiome composition, each predominated by either by Firmicutes or Proteobacteria. These data demonstrate diverse and highly variable resident microbial communities across food products, which is informative in the context of food safety, and spoilage where indigenous bacteria could hamper pathogen detection, and limit shelf life.

Sensitive and rapid detection of Salmonella enterica serovar Indiana by cross-priming amplification

Salmonella enterica serovar Indiana (S. Indiana) was the most frequently reported foodborne pathogen, which has a broad host range including poultry, swine, and humans. Traditional methods used for the detection of S. Indiana from contaminated food products are time-consuming and labor-intensive. Therefore, rapid detection methods with high sensitivity and specificity are vitally important to prevent the spread of S. Indiana. In this study, we developed a nearly instrument-free, simple molecular method which incorporates cross-priming amplification (CPA) combined with a nucleic acid detection strip (NADS) for sensitive detection of S. Indiana. A set of CPA primers was designed based on S. Indiana specific nucleotide sequences and the specificity of CPA-NADS was tested against 42 bacterial strains. The results showed that this method was highly specific for detection of S. Indiana. The sensitivity of CPA-NADS was evaluated and compared with that of the serovar-specific PCR method and the real-time PCR method. The limit of detection of the CPA method was 8.997 fg/μL for genomic DNA and 6.2 × 10¹ CFU/mL for bacteria in pure culture. An application of the CPA assay was conducted with 90 inoculated specimens by S. Indiana. The accuracy of CPA-NADS was consistent with the results of the traditional culture-based methods in inoculated specimens. This method showed a higher sensitivity than the serovar-specific PCR method did and was more convenient to perform. In conclusion, we demonstrated that the CPA-NADS system offers high specificity, sensitivity, rapidity, and a simple detection tool for screening S. Indiana.

Presence and Persistence of Salmonella in Water: The Impact on Microbial Quality of Water and Food Safety

Salmonella ranks high among the pathogens causing foodborne disease outbreaks. According to the Centers for Disease Control and Prevention, Salmonella contributed to about 53.4% of all foodborne disease outbreaks from 2006 to 2017, and approximately 32.7% of these foodborne Salmonella outbreaks were associated with consumption of produce. Trace-back investigations have suggested that irrigation water may be a source of Salmonella contamination of produce and a vehicle for transmission. Presence and persistence of Salmonella have been reported in surface waters such as rivers, lakes, and ponds, while ground water in general offers better microbial quality for irrigation. To date, culture methods are still the gold standard for detection, isolation and identification of Salmonella in foods and water. In addition to culture, other methods for the detection of Salmonella in water include most probable number, immunoassay, and PCR. The U.S. Food and Drug Administration (FDA) issued the Produce Safety Rule (PSR) in January 2013 based on the Food Safety Modernization Act (FSMA), which calls for more efforts toward enhancing and improving approaches for the prevention of foodborne outbreaks. In the PSR, agricultural water is defined as water used for in a way that is intended to, or likely to, contact covered produce, such as spray, wash, or irrigation. In summary, Salmonella is frequently present in surface water, an important source of water for irrigation. An increasing evidence indicates irrigation water as a source (or a vehicle) for transmission of Salmonella. This pathogen can survive in aquatic environments by a number of mechanisms, including entry into the viable but nonculturable (VBNC) state and/or residing within free-living protozoa. As such, assurance of microbial quality of irrigation water is critical to curtail the produce-related foodborne outbreaks and thus enhance the food safety. In this review, we will discuss the presence and persistence of Salmonella in water and the mechanisms Salmonella uses to persist in the aquatic environment, particularly irrigation water, to better understand the impact on the microbial quality of water and food safety due to the presence of Salmonella in the water environment.

The Present and Future of Whole Genome Sequencing (WGS) and Whole Metagenome Sequencing (WMS) for Surveillance of Antimicrobial Resistant Microorganisms and Antimicrobial Resistance Genes across the Food Chain

Antimicrobial resistance (AMR) surveillance is a critical step within risk assessment schemes, as it is the basis for informing global strategies, monitoring the effectiveness of public health interventions, and detecting new trends and emerging threats linked to food. Surveillance of AMR is currently based on the isolation of indicator microorganisms and the phenotypic characterization of clinical, environmental and food strains isolated. However, this approach provides very limited information on the mechanisms driving AMR or on the presence or spread of AMR genes throughout the food chain. Whole-genome sequencing (WGS) of bacterial pathogens has shown potential for epidemiological surveillance, outbreak detection, and infection control. In addition, whole metagenome sequencing (WMS) allows for the culture-independent analysis of complex microbial communities, providing useful information on AMR genes occurrence. Both technologies can assist the tracking of AMR genes and mobile genetic elements, providing the necessary information for the implementation of quantitative risk assessments and allowing for the identification of hotspots and routes of transmission of AMR across the food chain. This review article summarizes the information currently available on the use of WGS and WMS for surveillance of AMR in foodborne pathogenic bacteria and food-related samples and discusses future needs that will have to be considered for the routine implementation of these next-generation sequencing methodologies with this aim. In particular, methodological constraints that impede the use at a global scale of these high-throughput sequencing (HTS) technologies are identified, and the standardization of methods and protocols is suggested as a measure to upgrade HTS-based AMR surveillance schemes.

Microbiological profile of chicken carcasses: A comparative analysis using shotgun metagenomic sequencing

In the last few years metagenomic and 16S rRNA sequencing have completly changed the microbiological investigations of food products. In this preliminary study, the microbiological profile of chicken carcasses collected from animals fed with different diets were tested by using shotgun metagenomic sequencing. A total of 15 carcasses have been collected at the slaughetrhouse at the end of the refrigeration tunnel from chickens reared for 35 days and fed with a control diet (n=5), a diet supplemented with 1500 FTU/kg of commercial phytase (n=5) and a diet supplemented with 1500 FTU/kg of commercial phytase and 3g/kg of inositol (n=5). Ten grams of neck and breast skin were obtained from each carcass and submited to total DNA extraction by using the DNeasy Blood & Tissue Kit (Qiagen). Sequencing libraries have been prepared by using the Nextera XT DNA Library Preparation Kit (Illumina) and sequenced in a HiScanSQ (Illumina) at 100 bp in paired ends. A number of sequences ranging between 5 and 9 million was obtained for each sample. Sequence analysis showed that Proteobacteria and Firmicutes represented more than 98% of whole bacterial populations associated to carcass skin in all groups but their abundances were different between groups. Moraxellaceae and other degradative bacteria showed a significantly higher abundance in the control compared to the treated groups. Furthermore, Clostridium perfringens showed a relative frequency of abundance significantly higher in the group fed with phytase and Salmonella enterica in the group fed with phytase plus inositol. The results of this preliminary study showed that metagenome sequencing is suitable to investigate and monitor carcass microbiota in order to detect specific pathogenic and/or degradative populations.

Quasimetagenomics-Based and Real-Time-Sequencing-Aided Detection and Subtyping of Salmonella enterica from Food Samples

Metagenomics analysis of food samples promises isolation-independent detection and subtyping of foodborne bacterial pathogens in a single workflow. The selective concentration of Salmonella genomic DNA by immunomagnetic separation (IMS) and multiple displacement amplification (MDA) shortened the time for culture enrichment of Salmonella-spiked raw chicken breast samples by over 12 h while permitting serotyping and high-fidelity single nucleotide polymorphism (SNP) typing of the pathogen using short shotgun sequencing reads. The herein-termed quasimetagenomics approach was evaluated on Salmonella-spiked lettuce and black peppercorn samples as well as retail chicken parts naturally contaminated with different serotypes of Salmonella Culture enrichment of between 8 and 24 h was required for detecting and subtyping naturally occurring Salmonella from unspiked chicken parts compared with 4- to 12-h culture enrichment when Salmonella-spiked food samples were analyzed, indicating the likely need for longer culture enrichment to revive low levels of stressed or injured Salmonella cells in food. A further acceleration of the workflow was achieved by real-time nanopore sequencing. After 1.5 h of analysis on a potable sequencer, sufficient data were generated from sequencing the IMS-MDA products of a cultured-enriched lettuce sample to enable serotyping and robust phylogenetic placement of the inoculated isolate.IMPORTANCE Both culture enrichment and next-generation sequencing remain time-consuming processes for food testing, whereas rapid methods for pathogen detection are widely available. Our study demonstrated a substantial acceleration of these processes by the use of immunomagnetic separation (IMS) with multiple displacement amplification (MDA) and real-time nanopore sequencing. In one example, the combined use of the two methods delivered a less than 24-h turnaround time from the collection of a Salmonella-contaminated lettuce sample to the phylogenetic identification of the pathogen. An improved efficiency such as this is important for further expanding the use of whole-genome and metagenomics sequencing in the microbial analysis of food. Our results suggest the potential of the quasimetagenomics approach in areas where rapid detection and subtyping of foodborne pathogens are important, such as for foodborne outbreak response and the precision tracking and monitoring of foodborne pathogens in production environments and supply chains.

Next generation microbiological risk assessment meta-omics: The next need for integration

The development of a multi-omics approach has provided a new approach to the investigation of microbial communities allowing an integration of data, which can be used to better understand the behaviour of and interactions between community members. Metagenomics, metatranscriptomics, metaproteomics and metabolomics have the potential of producing a large amount of data in a very short time, however an important challenge is how to exploit and interpret these data to assist risk managers in food safety and quality decisions. This can be achieved by integrating multi-omics data in microbiological risk assessment. In this paper we identify limitations and challenges of the multi-omics approach, underlining promising potentials, but also identifying gaps, which should be addressed for its full exploitation. A view on how this new way of investigation will impact the traditional microbiology schemes in the food industry is also presented.

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.

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.

Early Recovery of Salmonella from Food Using a 6-Hour Non-selective Pre-enrichment and Reformulation of Tetrathionate Broth

Culture based methods are commonly employed to detect pathogens in food and environmental samples. These methods are time consuming and complex, requiring multiple non-selective and selective enrichment broths, and usually take at least 1 week to recover and identify pathogens. Improving pathogen detection in foods is a primary goal for regulatory agencies and industry. Salmonella detection in food relies on a series of culture steps in broth formulations optimized to resuscitate Salmonella and reduce the abundance of competitive bacteria. Examples of non-selective pre-enrichment broths used to isolate Salmonella from food include Lactose, Universal Pre-enrichment, BPW, and Trypticase Soy broths. Tetrathionate (TT) and Rappaport-Vassiliadis (RV) broths are employed after a 24-h non-selective enrichment to select for Salmonella and hamper the growth of competitive bacteria. In this study, we tested a new formulation of TT broth that lacks brilliant green dye and has lower levels of TT . We employed this TT broth formulation in conjunction with a 6-h non-selective pre-enrichment period and determined that Salmonella recovery was possible one day earlier than standard food culture methods. We tested the shortened culture method in different non-selective enrichment broths, enumerated Salmonella in the non-selective enrichments, and used 16S rRNA gene sequencing to determine the proportional abundances of Salmonella in the TT and RV selective enrichments. Together these data revealed that a 6-h non-selective pre-enrichment reduces the levels of competitive bacteria inoculated into the selective TT and RV broths, enabling the recovery of Salmonella 1 day earlier than standard culture enrichment methods.

Strain-Level Discrimination of Shiga Toxin-Producing Escherichia coli in Spinach Using Metagenomic Sequencing

Consumption of fresh bagged spinach contaminated with Shiga toxin-producing Escherichia coli (STEC) has led to severe illness and death; however current culture-based methods to detect foodborne STEC are time consuming. Since not all STEC strains are considered pathogenic to humans, it is crucial to incorporate virulence characterization of STEC in the detection method. In this study, we assess the comprehensiveness of utilizing a shotgun metagenomics approach for detection and strain-level identification by spiking spinach with a variety of genomically disparate STEC strains at a low contamination level of 0.1 CFU/g. Molecular serotyping, virulence gene characterization, microbial community analysis, and E. coli core gene single nucleotide polymorphism (SNP) analysis were performed on metagenomic sequence data from enriched samples. It was determined from bacterial community analysis that E. coli, which was classified at the phylogroup level, was a major component of the population in most samples. However, in over half the samples, molecular serotyping revealed the presence of indigenous E. coli which also contributed to the percent abundance of E. coli. Despite the presence of additional E. coli strains, the serotype and virulence genes of the spiked STEC, including correct Shiga toxin subtype, were detected in 94% of the samples with a total number of reads per sample averaging 2.4 million. Variation in STEC abundance and/or detection was observed in replicate spiked samples, indicating an effect from the indigenous microbiota during enrichment. SNP analysis of the metagenomic data correctly placed the spiked STEC in a phylogeny of related strains in cases where the indigenous E. coli did not predominate in the enriched sample. Also, for these samples, our analysis demonstrates that strain-level phylogenetic resolution is possible using shotgun metagenomic data for determining the genomic relatedness of a contaminating STEC strain to other closely related E. coli.

Enrichment dynamics of Listeria monocytogenes and the associated microbiome from naturally contaminated ice cream linked to a listeriosis outbreak

Background

Microbiota that co-enrich during efforts to recover pathogens from foodborne outbreaks interfere with efficient detection and recovery. Here, dynamics of co-enriching microbiota during recovery of Listeria monocytogenes from naturally contaminated ice cream samples linked to an outbreak are described for three different initial enrichment formulations used by the Food and Drug Administration (FDA), the International Organization of Standardization (ISO), and the United States Department of Agriculture (USDA). Enrichment cultures were analyzed using DNA extraction and sequencing from samples taken every 4 h throughout 48 h of enrichment. Resphera Insight and CosmosID analysis tools were employed for high-resolution profiling of 16S rRNA amplicons and whole genome shotgun data, respectively.

Results

During enrichment, other bacterial taxa were identified, including Anoxybacillus, Geobacillus, Serratia, Pseudomonas, Erwinia, and Streptococcus spp. Surprisingly, incidence of L. monocytogenes was proportionally greater at hour 0 than when tested 4, 8, and 12 h later with all three enrichment schemes. The corresponding increase in Anoxybacillus and Geobacillus spp.indicated these taxa co-enriched in competition with L. monocytogenes during early enrichment hours. L. monocytogenes became dominant after 24 h in all three enrichments. DNA sequences obtained from shotgun metagenomic data of Listeria monocytogenes at 48 h were assembled to produce a consensus draft genome which appeared to have a similar tracking utility to pure culture isolates of L. monocytogenes.

Conclusions

All three methods performed equally well for enrichment of Listeria monocytogenes. The observation of potential competitive exclusion of L. mono by Anoxybacillus and Geobacillus in early enrichment hours provided novel information that may be used to further optimize enrichment formulations. Application of Resphera Insight for high-resolution analysis of 16S amplicon sequences accurately identified L. monocytogenes. Both shotgun and 16S rRNA data supported the presence of three slightly variable genomes of L. monocytogenes. Moreover, the draft assembly of a consensus genome of L. monocytogenes from shotgun metagenomic data demonstrated the potential utility of this approach to expedite trace-back of outbreak-associated strains, although further validation will be needed to confirm this utility.

Electronic supplementary material

The online version of this article (doi:10.1186/s12866-016-0894-1) contains supplementary material, which is available to authorized users.

Mungo bean sprout microbiome and changes associated with culture based enrichment protocols used in detection of Gram-negative foodborne pathogens

BACKGROUND

Fresh sprouted seeds have been associated with a number of large outbreaks caused by Salmonella and Shiga toxin-producing E. coli. However, the high number of commensal bacteria found on sprouted seeds hampers the detection of these pathogens. Knowledge about the composition of the sprout microbiome is limited. In this study, the microbiome of mungo bean sprouts and the impact of buffered peptone water (BPW) and Enterobacteriaceae enrichment broth (EE-broth)-based enrichment protocols on this microbiome were investigated.

RESULTS

Assessments based on aerobic mesophilic colony counts showed similar increases in mungo bean sprout background flora levels independent of the enrichment protocol used. 16S rRNA sequencing revealed a mungo bean sprout microbiome dominated by Proteobacteria and Bacteroidetes. EE-broth enrichment of such samples preserved and increased Proteobacteria dominance while reducing Bacteroidetes and Firmicutes relative abundances. BPW enrichment, however, increased Firmicutes relative abundance while decreasing Proteobacteria and Bacteroidetes levels. Both enrichments also lead to various genus level changes within the Protobacteria and Firmicutes phyla.

CONCLUSIONS

New insights into the microbiome associated with mungo bean sprout and how it is influenced through BPW and EE-broth-based enrichment strategies used for detecting Gram-negative pathogens were generated. BPW enrichment leads to Firmicutes and Proteobacteria dominance, whereas EE-broth enrichment preserves Proteobacteria dominance in the mungo bean sprout samples. By increasing the relative abundance of Firmicutes, BPW also increases the abundance of Gram-positive organisms including some that might inhibit recovery of Gram-negative pathogens. The use of EE-broth, although preserving and increasing the dominance of Proteobacteria, can also hamper the detection of lowly abundant Gram-negative target pathogens due to outgrowth of such organisms by the highly abundant non-target Proteobacteria genera comprising the mungo bean sprout associated background flora.

Avoiding Pandemic Fears in the Subway and Conquering the Platypus

Metagenomics is increasingly used not just to show patterns of microbial diversity but also as a culture-independent method to detect individual organisms of intense clinical, epidemiological, conservation, forensic, or regulatory interest. A widely reported metagenomic study of the New York subway suggested that the pathogens Yersinia pestis and Bacillus anthracis were part of the "normal subway microbiome." In their article in mSystems, Hsu and collaborators (mSystems 1(3):e00018-16, 2016, http://dx.doi.org/10.1128/mSystems.00018-16) showed that microbial communities on transit surfaces in the Boston subway system are maintained from a metapopulation of human skin commensals and environmental generalists and that reanalysis of the New York subway data with appropriate methods did not detect the pathogens. We note that commonly used software pipelines can produce results that lack prima facie validity (e.g., reporting widespread distribution of notorious endemic species such as the platypus or the presence of pathogens) but that appropriate use of inclusion and exclusion sets can avoid this issue.

Functional Responses of Salt Marsh Microbial Communities to Long-Term Nutrient Enrichment

Environmental nutrient enrichment from human agricultural and waste runoff could cause changes to microbial communities that allow them to capitalize on newly available resources. Currently, the response of microbial communities to nutrient enrichment remains poorly understood, and, while some studies have shown no clear changes in community composition in response to heavy nutrient loading, others targeting specific genes have demonstrated clear impacts. In this study, we compared functional metagenomic profiles from sediment samples taken along two salt marsh creeks, one of which was exposed for more than 40 years to treated sewage effluent at its head. We identified strong and consistent increases in the relative abundance of microbial genes related to each of the biochemical steps in the denitrification pathway at enriched sites. Despite fine-scale local increases in the abundance of denitrification-related genes, the overall community structures based on broadly defined functional groups and taxonomic annotations were similar and varied with other environmental factors, such as salinity, which were common to both creeks. Homology-based taxonomic assignments of nitrous oxide reductase sequences in our data show that increases are spread over a broad taxonomic range, thus limiting detection from taxonomic data alone. Together, these results illustrate a functionally targeted yet taxonomically broad response of microbial communities to anthropogenic nutrient loading, indicating some resolution to the apparently conflicting results of existing studies on the impacts of nutrient loading in sediment communities.

IMPORTANCE In this study, we used environmental metagenomics to assess the response of microbial communities in estuarine sediments to long-term, nutrient-rich sewage effluent exposure. Unlike previous studies, which have mainly characterized communities based on taxonomic data or primer-based amplification of specific target genes, our whole-genome metagenomics approach allowed an unbiased assessment of the abundance of denitrification-related genes across the entire community. We identified strong and consistent increases in the relative abundance of gene sequences related to denitrification pathways across a broad phylogenetic range at sites exposed to long-term nutrient addition. While further work is needed to determine the consequences of these community responses in regulating environmental nutrient cycles, the increased abundance of bacteria harboring denitrification genes suggests that such processes may be locally upregulated. In addition, our results illustrate how whole-genome metagenomics combined with targeted hypothesis testing can reveal fine-scale responses of microbial communities to environmental disturbance.

Recent and emerging innovations in Salmonella detection: a food and environmental perspective

Salmonella is a diverse genus of Gram‐negative bacilli and a major foodborne pathogen responsible for more than a million illnesses annually in the United States alone. Rapid, reliable detection and identification of this pathogen in food and environmental sources is key to safeguarding the food supply. Traditional microbiological culture techniques have been the ‘gold standard’ for State and Federal regulators. Unfortunately, the time to result is too long to effectively monitor foodstuffs, especially those with very short shelf lives. Advances in traditional microbiology and molecular biology over the past 25 years have greatly improved the speed at which this pathogen is detected. Nonetheless, food and environmental samples possess a distinctive set of challenges for these newer, more rapid methodologies. Furthermore, more detailed identification and subtyping strategies still rely heavily on the availability of a pure isolate. However, major shifts in DNA sequencing technologies are meeting this challenge by advancing the detection, identification and subtyping of Salmonella towards a culture‐independent diagnostic framework. This review will focus on current approaches and state‐of‐the‐art next‐generation advances in the detection, identification and subtyping of Salmonella from food and environmental sources.

Evaluation of Rapid Molecular Detection Assays for Salmonella in Challenging Food Matrices at Low Inoculation Levels and Using Difficult-to-Detect Strains

Assays for detection of foodborne pathogens are generally initially evaluated for performance in validation studies carried out according to guidelines provided by validation schemes (e.g., AOAC International or the International Organization for Standardization). End users often perform additional validation studies to evaluate the performance of assays in specific matrices (e.g., specific foods or raw material streams of interest) and with specific pathogen strains. However, these types of end-user validations are typically not well defined. This study was conducted to evaluate a secondary end user validation of four AOAC-validated commercial rapid detection assays (an isothermal nucleic acid amplification, an immunoassay, and two PCR-based assays) for their ability to detect Salmonella in two challenging matrices (dry pet food and dark chocolate). Inclusivity was evaluated with 68 diverse Salmonella strains at low population levels representing the limit of detection (LOD) for each assay. One assay detected all strains at the LOD, two assays detected multiple strains only at 10 times the LOD, and the fourth assay failed to detect two strains (Salmonella bongori and S. enterica subsp. houtenae) even at 1,000 times the LOD; this assay was not further evaluated. The three remaining assays were subsequently evaluated for their ability to detect five selected Salmonella strains in food samples contaminated at fractional levels. Unpaired comparisons revealed no significant difference between the results for each given assay and the results obtained with the reference assay. However, analysis of paired culture-confirmed results revealed assay false-negative rates of 4 to 26% for dry pet food and 12 to 16% for dark chocolate. Overall, our data indicate that rapid assays may have high false-negative rates when performance is evaluated under challenging conditions, including low-moisture matrices, strains that are difficult to detect, injured cells, and low inoculum levels.

Cilantro microbiome before and after nonselective pre-enrichment for Salmonella using 16S rRNA and metagenomic sequencing

BACKGROUND

Salmonella enterica is a common cause of foodborne gastroenteritis in the United States and is associated with outbreaks in fresh produce such as cilantro. Salmonella culture-based detection methods are complex and time consuming, and improvments to increase detection sensitivity will benefit consumers. In this study, we used 16S rRNA sequencing to determine the microbiome of cilantro. We also investigated changes to the microbial community prior to and after a 24-hour nonselective pre-enrichment culture step commonly used by laboratory analysts to resuscitate microorganisms in foods suspected of contamination with pathogens. Cilantro samples were processed for Salmonella detection according to the method in the United States Food and Drug Administration Bacteriological Analytical Manual. Genomic DNA was extracted from culture supernatants prior to and after a 24-hour nonselective pre-enrichment step and 454 pyrosequencing was performed on 16S rRNA amplicon libraries. A database of Enterobacteriaceae 16S rRNA sequences was created, and used to screen the libraries for Salmonella, as some samples were known to be culture positive. Additionally, culture positive cilantro samples were examined for the presence of Salmonella using shotgun metagenomics on the Illumina MiSeq.

RESULTS

Time zero uncultured samples had an abundance of Proteobacteria while the 24-hour enriched samples were composed mostly of Gram-positive Firmicutes. Shotgun metagenomic sequencing of Salmonella culture positive cilantro samples revealed variable degrees of Salmonella contamination among the sequenced samples.

CONCLUSIONS

Our cilantro study demonstrates the use of high-throughput sequencing to reveal the microbiome of cilantro, and how the microbiome changes during the culture-based protocols employed by food safety laboratories to detect foodborne pathogens. Finding that culturing the cilantro shifts the microbiome to a predominance of Firmicutes suggests that changing our culture-based methods will improve detection sensitivity for foodborne enteric pathogens.

The impact of systemic and copper pesticide applications on the phyllosphere microflora of tomatoes

BACKGROUND

Contamination of tomatoes by Salmonella can occur in agricultural settings. Little is currently understood about how agricultural inputs such as pesticide applications may impact epiphytic crop microflora and potentially play a role in contamination events. We examined the impact of two materials commonly used in Virginia tomato agriculture: acibenzolar-S-methyl (crop protectant) and copper oxychloride (pesticide) to identify the effects these materials may exert on baseline tomato microflora and on the incidence of three specific genera; Salmonella, Xanthomonas and Paenibacillus.

RESULTS

Approximately 186 441 16S rRNA gene and 39 381 18S rRNA gene sequences per independent replicate were used to analyze the impact of the pesticide applications on tomato microflora. An average of 3 346 677 (634 892 974 bases) shotgun sequences per replicate were used for metagenomic analyses.

CONCLUSION

A significant decrease in the presence of Gammaproteobacteria was observed between controls and copper-treated plants, suggesting that copper is effective at suppressing growth of certain taxa in this class. A higher mean abundance of Salmonella and Paenibacillus in control samples compared to treatments may suggest that both systemic and copper applications diminish the presence of these genera in the phyllosphere; however, owing to the lack of statistical significance, this could also be due to other factors. The most distinctive separation of shared membership was observed in shotgun data between the two different sampling time-points (not between treatments), potentially supporting the hypothesis that environmental pressures may exert more selective pressures on epiphytic microflora than do certain agricultural management practices.

Salmonella serotype determination utilizing high-throughput genome sequencing data

Serotyping forms the basis of national and international surveillance networks for Salmonella, one of the most prevalent foodborne pathogens worldwide (1-3). Public health microbiology is currently being transformed by whole-genome sequencing (WGS), which opens the door to serotype determination using WGS data. SeqSero (www.denglab.info/SeqSero) is a novel Web-based tool for determining Salmonella serotypes using high-throughput genome sequencing data. SeqSero is based on curated databases of Salmonella serotype determinants (rfb gene cluster, fliC and fljB alleles) and is predicted to determine serotype rapidly and accurately for nearly the full spectrum of Salmonella serotypes (more than 2,300 serotypes), from both raw sequencing reads and genome assemblies. The performance of SeqSero was evaluated by testing (i) raw reads from genomes of 308 Salmonella isolates of known serotype; (ii) raw reads from genomes of 3,306 Salmonella isolates sequenced and made publicly available by GenomeTrakr, a U.S. national monitoring network operated by the Food and Drug Administration; and (iii) 354 other publicly available draft or complete Salmonella genomes. We also demonstrated Salmonella serotype determination from raw sequencing reads of fecal metagenomes from mice orally infected with this pathogen. SeqSero can help to maintain the well-established utility of Salmonella serotyping when integrated into a platform of WGS-based pathogen subtyping and characterization.

Analysis of plant microbe interactions in the era of next generation sequencing technologies

Next generation sequencing (NGS) technologies have impressively accelerated research in biological science during the last years by enabling the production of large volumes of sequence data to a drastically lower price per base, compared to traditional sequencing methods. The recent and ongoing developments in the field allow addressing research questions in plant-microbe biology that were not conceivable just a few years ago. The present review provides an overview of NGS technologies and their usefulness for the analysis of microorganisms that live in association with plants. Possible limitations of the different sequencing systems, in particular sources of errors and bias, are critically discussed and methods are disclosed that help to overcome these shortcomings. A focus will be on the application of NGS methods in metagenomic studies, including the analysis of microbial communities by amplicon sequencing, which can be considered as a targeted metagenomic approach. Different applications of NGS technologies are exemplified by selected research articles that address the biology of the plant associated microbiota to demonstrate the worth of the new methods.

Omics approaches in food safety: fulfilling the promise?

Genomics, transcriptomics, and proteomics are rapidly transforming our approaches to the detection, prevention, and treatment of foodborne pathogens. Microbial genome sequencing in particular has evolved from a research tool into an approach that can be used to characterize foodborne pathogen isolates as part of routine surveillance systems. Genome sequencing efforts will not only improve outbreak detection and source tracking, but will also create large amounts of foodborne pathogen genome sequence data, which will be available for data-mining efforts that could facilitate better source attribution and provide new insights into foodborne pathogen biology and transmission. Although practical uses and application of metagenomics, transcriptomics, and proteomics data and associated tools are less prominent, these tools are also starting to yield practical food safety solutions.