Multilab Validation Report for the Verification and Subtyping of Listeria monocytogenes Using qPCR.

Listeria monocytogenes (Lm) is a Gram-positive bacterium that causes invasive listeriosis, an illness with high mortality and hospitalization rates. Due to the severity of illness associated with Lm, rapid identification and characterization of isolates from foods and the food-processing environment are critical to properly identify and track the pathogen and quickly remove adulterated foods from the market. Prior methods can rely on time-consuming biochemical or sera-agglutination assays to perform these tasks. Development of a high-throughput method that would rapidly perform these tasks is critical to improve response to contamination events. Previously, a single laboratory validation of a qPCR-based method was presented that could rapidly verify Lm isolates and characterize them into six molecular serogroups. In the current study, a multi-laboratory validation (MLV) was performed to evaluate the reliability of the qPCR method for identification and serogrouping of Lm isolates. Sixteen collaborating laboratories independently analyzed a panel of 43 blinded isolates plus three control strains using the qPCR method. This panel was comprised of representatives for non-Listeria (n = 7), Listeria sp. (n = 8), and Lm (n = 28) strains. The Lm isolates contained representatives of the six serogroups: 2A, 2B, 2C, 4B, NT, and 4bV/IVb-v1, with five strains for each serogroup except 4bV/IVb-v1 (n = 3). The results generated by 16 laboratories showed high sensitivity, specificity, and accuracy, generally ≥97%, for both the genus-species and serogrouping qPCRs. Results from one laboratory lowered the sensitivity of the non-Listeria group to 93%. These results indicated the method was highly reliable. However, only the previously evaluated serogroups were tested within the MLV panel, though there is the potential for other serogroup results. Sequence Read Archive (SRA) files for Lm isolates were evaluated to determine the frequency of other potential serogroup profiles. This effort identified a low percentage of isolates with atypical qPCR serogroups (0.30%) that are consistent with Lm and were generally associated with lineage II and the natural environment. In summary, the results indicate that the proposed qPCR method is reliable and has a high degree of sensitivity, accuracy, and specificity, while also decreasing hands-on analysis time and increasing throughput of the analysis.

Application of quasimetagenomics methods to define microbial diversity and subtype Listeria monocytogenes in dairy and seafood production facilities.

IMPORTANCE: In developed countries, the human diet is predominated by food commodities, which have been manufactured, processed, and stored in a food production facility. Little is known about the application of metagenomic sequencing approaches for detecting foodborne pathogens, such as L. monocytogenes, and characterizing microbial diversity in food production ecosystems. In this work, we investigated the utility of 16S rRNA amplicon and quasimetagenomic sequencing for the taxonomic and phylogenetic classification of Listeria culture enrichments of environmental swabs collected from dairy and seafood production facilities. We demonstrated that single-nucleotide polymorphism (SNP) analyses of L. monocytogenes metagenome-assembled genomes (MAGs) from quasimetagenomic data sets can achieve similar resolution as culture isolate whole-genome sequencing. To further understand the impact of genome coverage on MAG SNP cluster resolution, an in silico downsampling approach was employed to reduce the percentage of target pathogen sequence reads, providing an initial estimate of required MAG coverage for subtyping resolution of L. monocytogenes.

bettercallsal: better calling of Salmonella serotypes from enrichment cultures using shotgun metagenomic profiling and its application in an outbreak setting.

Most current Salmonella subtyping analyses rely on whole genome sequencing (WGS), which focuses on the high-resolution analysis of single genomes or multiple single genomes from the isolated colonies on microbiological agar plates. In this study, we introduce bioinformatics innovations for a metagenomic outbreak response workflow that accurately identifies multiple Salmonella serovars at the same time. bettercallsal is one of the first analysis tools to identify multiple Salmonella enterica serotypes from metagenomic or quasi-metagenomic datasets with high accuracy, allowing these isolate-independent methods to be incorporated into surveillance and root cause investigations. It was tested on an in silico benchmark dataset comprising 29 unique Salmonella serovars, 46 non-Salmonella bacterial genomes, and 10 viral genomes at varying read depths and on previously well-characterized and sequenced non-selective primary and selective enrichments of papaya and peach samples from separate outbreak investigations that resulted in the identification of multiple Salmonella serovars using traditional isolate culturing and WGS as well as nucleic acid assays. Analyses were also conducted on these datasets using a custom-built k-mer tool, SeqSero2, and Kallisto to compare serotype calling to bettercallsal. The in silico dataset analyzed with bettercallsal achieved the maximum precision, recall, and accuracy of 100, 83, and 94%, respectively. In the papaya outbreak samples, bettercallsal identified the presence of multiple serovars in agreement with the Luminex® xMAP assay results and also identified more serovars per sample, as evidenced by NCBI SNP clustering. In peach outbreak samples, bettercallsal identified two serovars in concordance with k-mer analysis and the Luminex xMAP assay. The genome hit reported by bettercallsal clustered with the chicken isolate genome, as reported by the FDA peach outbreak investigation from sequenced isolates (WGS). Overall, bettercallsal outperformed k-mer, Seqsero2, and Kallisto in identifying multiple serovars from enrichment cultures using shotgun metagenomic sequencing.

A longitudinal study to examine the influence of farming practices and environmental factors on pathogen prevalence using structural equation modeling.

The contamination of fresh produce with foodborne pathogens has been an on-going concern with outbreaks linked to these commodities. Evaluation of farm practices, such as use of manure, irrigation water source, and other factors that could influence pathogen prevalence in the farming environment could lead to improved mitigation strategies to reduce the potential for contamination events. Soil, water, manure, and compost were sampled from farms in Ohio and Georgia to identify the prevalence of Salmonella, Listeria monocytogenes (Lm), Campylobacter, and Shiga-toxin-producing Escherichia coli (STEC), as well as Arcobacter, an emerging human pathogen. This study investigated agricultural practices to determine which influenced pathogen prevalence, i.e., the percent positive samples. These efforts identified a low prevalence of Salmonella, STEC, and Campylobacter in soil and water (< 10%), preventing statistical modeling of these pathogens. However, Lm and Arcobacter were found in soil (13 and 7%, respectively), manure (49 and 32%, respectively), and water samples (18 and 39%, respectively) at a comparatively higher prevalence, suggesting different dynamics are involved in their survival in the farm environment. Lm and Arcobacter prevalence data, soil chemical characteristics, as well as farm practices and weather, were analyzed using structural equation modeling to identify which factors play a role, directly or indirectly, on the prevalence of these pathogens. These analyses identified an association between pathogen prevalence and weather, as well as biological soil amendments of animal origin. Increasing air temperature increased Arcobacter and decreased Lm. Lm prevalence was found to be inversely correlated with the use of surface water for irrigation, despite a high Lm prevalence in surface water suggesting other factors may play a role. Furthermore, Lm prevalence increased when the microbiome's Simpson's Diversity Index decreased, which occurred as soil fertility increased, leading to an indirect positive effect for soil fertility on Lm prevalence. These results suggest that pathogen, environment, and farm management practices, in addition to produce commodities, all need to be considered when developing mitigation strategies. The prevalence of Arcobacter and Lm versus the other pathogens suggests that multiple mitigation strategies may need to be employed to control these pathogens.

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.

Microbiome Population Dynamics of Cold-Smoked Sockeye Salmon during Refrigerated Storage and after Culture Enrichment.

ABSTRACT: Cold-smoked salmon is a ready-to-eat seafood product of high commercial importance. The processing and storage steps facilitate the introduction, growth, and persistence of foodborne pathogens and spoilage bacteria. The growth of commensal bacteria during storage and once the product is opened also influence the quality and safety of cold-smoked salmon. Here we investigated the microbial community through targeted 16S rRNA gene and shotgun metagenomic sequencing as means to better understand the interactions among bacteria in cold-smoked salmon. Cold-smoked salmon samples were tested over 30 days of aerobic storage at 4°C and cultured at each time point in a buffered Listeria enrichment broth (BLEB) commonly used to detect Listeria in foods. The microbiomes were composed of Firmicutes and Proteobacteria, namely, Carnobacterium, Brochothrix, Pseudomonas, Serratia, and Psychrobacter. Pseudomonas species were the most diverse species, with 181 taxa identified. In addition, we identified potential homologs to 10 classes of bacteriocins in microbiomes of cold-smoked salmon stored at 4°C and corresponding BLEB culture enrichments. The findings presented here contribute to our understanding of microbiome population dynamics in cold-smoked salmon, including changes in bacterial taxa during aerobic cold storage and after culture enrichment. This may facilitate improvements to pathogen detection and quality preservation of this food.

Research Note: Effect of butyric acid glycerol esters on ileal and cecal mucosal and luminal microbiota in chickens challenged with Eimeria maxima.

Coccidiosis is one of the most prevalent diseases seen in the poultry industry leading to excessive economic losses. The aim of this study was to investigate the effect of butyric acid glycerol esters (BE) on the ileal and cecal microbiota in birds challenged with Eimeria maxima (EM). Ross 708 male broilers were fed a diet supplemented with 0 (control) or 0.25% BE from day 1. On day 21, half of the birds were infected with 103 EM oocysts. For determing microbiota, ileal and cecal contents and epithelial scrapings were collected at 7 and 10 D postinfection (PI). Alpha diversity of bacterial communities was mostly affected (P < 0.05) by time PI and EM infection. The richness of luminal bacterial populations in the ileum and ceca was affected (P < 0.05) by addition of BE and by time PI × EM × BE interaction, respectively. In the ileal and cecal luminal and mucosal bacterial communities, permutational multivariate analysis of variance (PERMANOVA, unweighted UniFrac) showed significant (P < 0.05) differences because of time PI and interaction between time PI, EM, and BE. Significant (P < 0.05) differences in taxonomic composition at the family level were observed in microbiota of luminal and mucosal populations of the ileum and ceca owing to time PI, EM, BE, and their interactions. The bacterial community present in the cecal lumen was characterized by the lowest number of differential bacteria, whereas the cecal mucosal community was characterized by the highest number of differentially abundant bacteria. In conclusion, our results show that EM infection and time PI has the biggest impact on microbial diversity in the chicken gut. The presence of BE in the diet had a limited effect on gut microbiota.

Cyclization-blocked proguanil as a strategy to improve the antimalarial activity of atovaquone.

Atovaquone-proguanil (Malarone®) is used for malaria prophylaxis and treatment. While the cytochrome bc1-inhibitor atovaquone has potent activity, proguanil's action is attributed to its cyclization-metabolite, cycloguanil. Evidence suggests that proguanil has limited intrinsic activity, associated with mitochondrial-function. Here we demonstrate that proguanil, and cyclization-blocked analogue tBuPG, have potent, but slow-acting, in vitro anti-plasmodial activity. Activity is folate-metabolism and isoprenoid biosynthesis-independent. In yeast dihydroorotate dehydrogenase-expressing parasites, proguanil and tBuPG slow-action remains, while bc1-inhibitor activity switches from comparatively fast to slow-acting. Like proguanil, tBuPG has activity against P. berghei liver-stage parasites. Both analogues act synergistically with bc1-inhibitors against blood-stages in vitro, however cycloguanil antagonizes activity. Together, these data suggest that proguanil is a potent slow-acting anti-plasmodial agent, that bc1 is essential to parasite survival independent of dihydroorotate dehydrogenase-activity, that Malarone® is a triple-drug combination that includes antagonistic partners and that a cyclization-blocked proguanil may be a superior combination partner for bc1-inhibitors in vivo.

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.

High-Resolution Microbiome Profiling for Detection and Tracking of Salmonella enterica.

16S rRNA community profiling continues to be a useful tool to study microbiome composition and dynamics, in part due to advances in next generation sequencing technology that translate into reductions in cost. Reliable taxonomic identification to the species-level, however, remains difficult, especially for short-read sequencing platforms, due to incomplete coverage of the 16S rRNA gene. This is especially true for Salmonella enterica, which is often found as a low abundant member of the microbial community, and is often found in combination with several other closely related enteric species. Here, we report on the evaluation and application of Resphera Insight, an ultra-high resolution taxonomic assignment algorithm for 16S rRNA sequences to the species level. The analytical pipeline achieved 99.7% sensitivity to correctly identify S. enterica from WGS datasets extracted from the FDA GenomeTrakr Bioproject, while demonstrating 99.9% specificity over other Enterobacteriaceae members. From low-diversity and low-complexity samples, namely ice cream, the algorithm achieved 100% specificity and sensitivity for Salmonella detection. As demonstrated using cilantro and chili powder, for highly complex and diverse samples, especially those that contain closely related species, the detection threshold will likely have to be adjusted higher to account for misidentifications. We also demonstrate the utility of this approach to detect Salmonella in the clinical setting, in this case, bloodborne infections.

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.

Whole Genome DNA Sequence Analysis of Salmonella subspecies enterica serotype Tennessee obtained from related peanut butter foodborne outbreaks.

Establishing an association between possible food sources and clinical isolates requires discriminating the suspected pathogen from an environmental background, and distinguishing it from other closely-related foodborne pathogens. We used whole genome sequencing (WGS) to Salmonella subspecies enterica serotype Tennessee (S. Tennessee) to describe genomic diversity across the serovar as well as among and within outbreak clades of strains associated with contaminated peanut butter. We analyzed 71 isolates of S. Tennessee from disparate food, environmental, and clinical sources and 2 other closely-related Salmonella serovars as outgroups (S. Kentucky and S. Cubana), which were also shot-gun sequenced. A whole genome single nucleotide polymorphism (SNP) analysis was performed using a maximum likelihood approach to infer phylogenetic relationships. Several monophyletic lineages of S. Tennessee with limited SNP variability were identified that recapitulated several food contamination events. S. Tennessee clades were separated from outgroup salmonellae by more than sixteen thousand SNPs. Intra-serovar diversity of S. Tennessee was small compared to the chosen outgroups (1,153 SNPs), suggesting recent divergence of some S. Tennessee clades. Analysis of all 1,153 SNPs structuring an S. Tennessee peanut butter outbreak cluster revealed that isolates from several food, plant, and clinical isolates were very closely related, as they had only a few SNP differences between them. SNP-based cluster analyses linked specific food sources to several clinical S. Tennessee strains isolated in separate contamination events. Environmental and clinical isolates had very similar whole genome sequences; no markers were found that could be used to discriminate between these sources. Finally, we identified SNPs within variable S. Tennessee genes that may be useful markers for the development of rapid surveillance and typing methods, potentially aiding in traceback efforts during future outbreaks. Using WGS can delimit contamination sources for foodborne illnesses across multiple outbreaks and reveal otherwise undetected DNA sequence differences essential to the tracing of bacterial pathogens as they emerge.

Evaluation of corn oil as an additive in the pre-enrichment step to increase recovery of Salmonella enterica from oregano.

Phenolic compounds associated with essential oils of spices and herbs possess a variety of antioxidant and antimicrobial properties that interfere with Salmonella detection from fresh and dried products. Finding a compound to neutralize the effect of these antimicrobial compounds, while allowing Salmonella growth during pre-enrichment, is a crucial step in both traditional pathogen isolation and molecular detection from these foods. This study evaluated the effectiveness of corn oil as a component of the pre-enrichment broth to counteract antimicrobial compounds properties and increase the recovery of Salmonella from spices. Oregano samples artificially contaminated with Salmonella enterica were pre-enriched in modified Buffered Peptone Water (mBPW) supplemented with and without 2% (vol/vol) corn oil respectively. Samples were incubated overnight at 37 °C. The results showed that recovery of Salmonella from oregano samples was increased by ≥50% when pre-enriched with corn oil. Serovars were confirmed using a PCR serotyping method. In addition, shot-gun metagenomics analyses demonstrated bacterial diversity and the effect of corn oil on the relative prevalence of Salmonella in the oregano samples. Modifying pre-enrichment broths with corn oil improved the detection and isolation of Salmonella from oregano, and may provide an alternative method for pathogen detection in dried food matrices such as spices.

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.

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.

Analysis of the cellulose synthase operon genes, bcsA, bcsB, and bcsC in Cronobacter species: Prevalence among species and their roles in biofilm formation and cell-cell aggregation.

Cronobacter species are emerging food-borne pathogens that cause severe sepsis, meningitis, and necrotizing entercolitis in neonates and infants. Bacterial pathogens such as Escherichia coli and Salmonella species produce extracellular cellulose which has been shown to be involved in rugosity, biofilm formation, and host colonization. In this study the distribution and prevalence of cellulose synthase operon genes (bcsABZC) were determined by polymerase chain reaction (PCR) analysis in 231 Cronobacter strains isolated from clinical, food, environmental, and unknown sources. Furthermore, bcsA and bcsB isogenic mutants were constructed in Cronobacter sakazakii BAA894 to determine their roles. In calcofluor binding assays bcsA and bcsB mutants did not produce cellulose, and their colonial morphotypes were different to that of the parent strain. Biofilm formation and bacterial cell-cell aggregation were significantly reduced in bcsA and bcsB mutants compared to the parental strain. bcsA or bcsAB PCR-negative strains of C. sakazakii did not bind calcofluor, and produced less biofilm and cell-cell aggregation compared to strains possessing bcsAB genes. These data indicated that Cronobacter bcsABZC were present in all clinical isolates and most of food and environmental isolates. bcsA and bcsB genes of Cronobacter were necessary to produce cellulose, and were involved in biofilm formation and cell-cell aggregation.

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 Complete Mitochondrial Genome of the Foodborne Parasitic Pathogen Cyclospora cayetanensis.

Cyclospora cayetanensis is a human-specific coccidian parasite responsible for several food and water-related outbreaks around the world, including the most recent ones involving over 900 persons in 2013 and 2014 outbreaks in the USA. Multicopy organellar DNA such as mitochondrion genomes have been particularly informative for detection and genetic traceback analysis in other parasites. We sequenced the C. cayetanensis genomic DNA obtained from stool samples from patients infected with Cyclospora in Nepal using the Illumina MiSeq platform. By bioinformatically filtering out the metagenomic reads of non-coccidian origin sequences and concentrating the reads by targeted alignment, we were able to obtain contigs containing Eimeria-like mitochondrial, apicoplastic and some chromosomal genomic fragments. A mitochondrial genomic sequence was assembled and confirmed by cloning and sequencing targeted PCR products amplified from Cyclospora DNA using primers based on our draft assembly sequence. The results show that the C. cayetanensis mitochondrion genome is 6274 bp in length, with 33% GC content, and likely exists in concatemeric arrays as in Eimeria mitochondrial genomes. Phylogenetic analysis of the C. cayetanensis mitochondrial genome places this organism in a tight cluster with Eimeria species. The mitochondrial genome of C. cayetanensis contains three protein coding genes, cytochrome (cytb), cytochrome C oxidase subunit 1 (cox1), and cytochrome C oxidase subunit 3 (cox3), in addition to 14 large subunit (LSU) and nine small subunit (SSU) fragmented rRNA genes.

Genome Sequence of Cronobacter sakazakii Serogroup O:4, Sequence Type 4 Strain CDC 2009-03746, Isolated from a Fatal Case of Infantile Meningitis.

We report the draft genome sequence of a Cronobacter sakazakii serogroup O:4, sequence type 4 strain, CDC 2009-03746 (=NM1240=2009-06-01), isolated from a fatal case of infantile meningitis. The draft genome has a size of 4,492,904 bp and a G+C% content of 56.7.

A proposed harmonized LPS molecular-subtyping scheme for Cronobacter species.

Cronobacter are opportunistic pathogens, which cause infections in all age groups. To aid the characterization of Cronobacter in foods and environments a harmonized LPS identification scheme for molecular serotyping is needed. To this end, we studied 409 Cronobacter isolates representing the seven Cronobacter species using two previously reported molecular serotyping schemes, described here as Mullane-Jarvis (M-J) and Sun schemes. PCR analysis revealed many overlapping results that were obtained when independently applying the two serotyping schemes. There were complete agreements between the two PCR schemes for Cronobacter sakazakii (Csak) O:1, Csak O:3, and Csak O:7 serotypes. However, only thirty-five of 41 Csak O:4 strains, identified using the M-J scheme, were PCR-positive with the Sun scheme primers. Also the Sun scheme Csak O:5 primers failed to identify this serotype in any of the C. sakazakii strains tested, but did recognize seven Cronobacter turicensis strains, which were identified as Ctur O:3 using the M-J scheme. Similarly, the Sun scheme Csak O:6 primers recognized 30 Cronobacter malonaticus O:2 strains identified with the M-J scheme, but failed to identify this serotype in any C. sakazakii strain investigated. In this report, these findings are summarized and a harmonized molecular-serotyping scheme is proposed which is predicated on the correct identification of Cronobacter species, prior to serotype determination. In summary, fourteen serotypes were identified using the combined protocol, which consists of Csak O:1-O:4, and Csak O:7; Cmal O:1-O:2; Cdub O:1-O:2, Cmuy O:1-O:2, Cuni O:1, as well as Ctur O:1 and Ctur O:3.