Time and temperature abuse of milk in conditions representing a school cafeteria share table does not meaningfully reduce microbial quality.

Share tables (ST) are tables or stations in school cafeterias where students can return unopened foods and beverages, providing an opportunity to access these items at no cost. Currently, research suggests that milk is among the most wasted items in breakfast and lunch programs in the United States. Share tables present a simple solution for reducing milk waste, but research is needed to understand the microbial spoilage potential of milk in ST. To this end, uninoculated milk cartons and milk cartons inoculated with 2 to 3 log10(cfu/mL) Pseudomonas poae, a fast-growing psychrotroph, was exposed to ambient temperature during winter (mean temperature = 20.3°C) and summer (23.1°C) for 125 min, repeated over 5 d (the length of a school week). Microbial counts in the inoculated milk cartons increased linearly, exceeding the spoilage threshold of 6.0 log10(cfu/mL) after d 3 and after d 4 in the winter and summer season trials, respectively. In the winter trial, the microbial counts for uninoculated milk cartons never exceeded the lower limit of detection, 2.31 log10(cfu/mL), and in the summer trials, microbial counts never reached the spoilage threshold, indicating that initial contamination is a driving factor of microbial milk spoilage. Regardless of sharing status or seasonality, the greatest changes in counts for inoculated milk cartons occurred during overnight refrigeration, ranging from 0.56 to 1.4 log10(cfu/mL), while during the share table ranged from no observable change up to 0.29 log10(cfu/mL), emphasizing that school nutrition personnel should focus efforts on tightly controlling refrigeration temperatures and returning milk to refrigeration as soon as possible. A previously developed model for school cafeteria share tables was adapted to understand the typical residence time of milk in a simulated cafeteria with an ambient temperature share table for the summer and winter seasons over 1,000 wk. Milk was predicted to have a very short mean residence time (85 min) regardless of sharing status or season, with 99.8% of milk consumed, discarded, or donated within the first 2 d. As a result, only 3 out of 451,410 and 6 out of 451,410 simulated milks spoiled in the winter and summer seasons, respectively. The data generated here can be used to inform science-based decision-making for including milk in share tables, or applied to any system where one might have to accept short-term unrefrigerated storage of milk to meet a waste reduction or food security goal.

Leafy Green Farm-to-Customer Process Model Predicts Product Testing Is Most Effective at Detecting Contamination When Conducted Early in the System before Effective Interventions.

Commercial leafy green supply chains often are required to have test and reject (sampling) plans for specific microbial adulterants at primary production or finished product packing for market access. To better understand the impact of this type of sampling, this study simulated the effect of sampling (from preharvest to consumer) and processing interventions (such as produce wash with antimicrobial chemistry) on the microbial adulterant load reaching the system endpoint (customer). This study simulated seven leafy green systems, an optimal system (all interventions), a suboptimal system (no interventions), and five systems where single interventions were removed to represent single process failures, resulting in 147 total scenarios. The all-interventions scenario resulted in a 3.4 log reduction (95% confidence interval [CI], 3.3 to 3.6) of the total adulterant cells that reached the system endpoint (endpoint TACs). The most effective single interventions were washing, prewashing, and preharvest holding, 1.3 (95% CI, 1.2 to 1.5), 1.3 (95% CI, 1.2 to 1.4), and 0.80 (95% CI, 0.73 to 0.90) log reduction to endpoint TACs, respectively. The factor sensitivity analysis suggests that sampling plans that happen before effective processing interventions (preharvest, harvest, and receiving) were most effective at reducing endpoint TACs, ranging between 0.05 and 0.66 log additional reduction compared to systems with no sampling. In contrast, sampling postprocessing (finished product) did not provide meaningful additional reductions to the endpoint TACs (0 to 0.04 log reduction). The model suggests that sampling used to detect contamination was most effective earlier in the system before effective interventions. Effective interventions reduce undetected contamination levels and prevalence, reducing a sampling plan's ability to detect contamination. IMPORTANCE This study addresses the industry and academic need to understand the effect of test-and-reject sampling within a farm-to-customer food safety system. The model developed looks at product sampling beyond the preharvest stage by assessing sampling at multiple stages. This study shows that individual interventions and combined interventions substantially reduce the total adulterant cells reaching the system endpoint. When effective interventions occur during processing, sampling at earlier stages (preharvest, harvest, receiving) has more power to detect incoming contamination than postprocessing sampling, as prevalence and contamination levels are lower. This study reiterates that effective food safety interventions are crucial for food safety. When product sampling is used to test and reject a lot as a preventive control, it may detect critically high incoming contamination. However, if contamination levels and prevalence are low, typical sampling plans will fail to detect contamination.

A Validated Preharvest Sampling Simulation Shows that Sampling Plans with a Larger Number of Randomly Located Samples Perform Better than Typical Sampling Plans in Detecting Representative Point-Source and Widespread Hazards in Leafy Green Fields.

Commercial leafy greens customers often require a negative preharvest pathogen test, typically by compositing 60 produce sample grabs of 150 to 375 g total mass from lots of various acreages. This study developed a preharvest sampling Monte Carlo simulation, validated it against literature and experimental trials, and used it to suggest improvements to sampling plans. The simulation was validated by outputting six simulated ranges of positive samples that contained the experimental number of positive samples (range, 2 to 139 positives) recovered from six field trials with point source, systematic, and sporadic contamination. We then evaluated the relative performance between simple random, stratified random, or systematic sampling in a 1-acre field to detect point sources of contamination present at 0.3% to 1.7% prevalence. Randomized sampling was optimal because of lower variability in probability of acceptance. Optimized sampling was applied to detect an industry-relevant point source [3 log(CFU/g) over 0.3% of the field] and widespread contamination [-1 to -4 log(CFU/g) over the whole field] by taking 60 to 1,200 sample grabs of 3 g. More samples increased the power of detecting point source contamination, as the median probability of acceptance decreased from 85% with 60 samples to 5% with 1,200 samples. Sampling plans with larger total composite sample mass increased power to detect low-level, widespread contamination, as the median probability of acceptance with -3 log(CFU/g) contamination decreased from 85% with a 150-g total mass to 30% with a 1,200-g total mass. Therefore, preharvest sampling power increases by taking more, smaller samples with randomization, up to the constraints of total grabs and mass feasible or required for a food safety objective. IMPORTANCE This study addresses a need for improved preharvest sampling plans for pathogen detection in leafy green fields by developing and validating a preharvest sampling simulation model, avoiding the expensive task of physical sampling in many fields. Validated preharvest sampling simulations were used to develop guidance for preharvest sampling protocols. Sampling simulations predicted that sampling plans with randomization are less variable in their power to detect low-prevalence point source contamination in a 1-acre field. Collecting larger total sample masses improved the power of sampling plans in detecting widespread contamination in 1-acre fields. Hence, the power of typical sampling plans that collect 150 to 375 g per composite sample can be improved by taking more, randomized smaller samples for larger total sample mass. The improved sampling plans are subject to feasibility constraints or to meet a particular food safety objective.

Evaluation of the Impact of Skewness, Clustering, and Probe Sampling Plan on Aflatoxin Detection in Corn.

Probe sampling plans for aflatoxin in corn attempt to reliably estimate concentrations in bulk corn given complications like skewed contamination distribution and hotspots. To evaluate and improve sampling plans, three sampling strategies (simple random sampling, stratified random sampling, systematic sampling with U.S. GIPSA sampling schemes), three numbers of probes (5, 10, 100, the last a proxy for autosampling), four clustering levels (1, 10, 100, 1,000 kernels/cluster source), and six aflatoxin concentrations (5, 10, 20, 40, 80, 100 ppb) were assessed by Monte-Carlo simulation. Aflatoxin distribution was approximated by PERT and Gamma distributions of experimental aflatoxin data for uncontaminated and naturally contaminated single kernels. The model was validated against published data repeatedly sampling 18 grain lots contaminated with 5.8-680 ppb aflatoxin. All empirical acceptance probabilities fell within the range of simulated acceptance probabilities. Sensitivity analysis with partial rank correlation coefficients found acceptance probability more sensitive to aflatoxin concentration (-0.87) and clustering level (0.28) than number of probes (-0.09) and sampling strategy (0.04). Comparison of operating characteristic curves indicate all sampling strategies have similar average performance at the 20 ppb threshold (0.8-3.5% absolute marginal change), but systematic sampling has larger variability at clustering levels above 100. Taking extra probes improves detection (1.8% increase in absolute marginal change) when aflatoxin is spatially clustered at 1,000 kernels/cluster, but not when contaminated grains are homogenously distributed. Therefore, taking many small samples, for example, autosampling, may increase sampling plan reliability. The simulation is provided as an R Shiny web app for stakeholder use evaluating grain sampling plans.

Persistent and sporadic Listeria monocytogenes strains do not differ when growing at 37 °C, in planktonic state, under different food associated stresses or energy sources.

BACKGROUND: The foodborne pathogen Listeria monocytogenes causes the potentially lethal disease listeriosis. Within food-associated environments, L. monocytogenes can persist for long periods and increase the risk of contamination by continued presence in processing facilities or other food-associated environments. Most research on phenotyping of persistent L. monocytogenes' has explored biofilm formation and sanitizer resistance, with less data examining persistent L. monocytogenes' phenotypic responses to extrinsic factors, such as variations in osmotic pressure, pH, and energy source availability. It was hypothesized that isolates of persistent strains are able to grow, and grow faster, under a broader range of intrinsic and extrinsic factors compared to closely related isolates of sporadic strains. RESULTS: To test this hypothesis, 95 isolates (representing 74 isolates of 20 persistent strains and 21 isolates of sporadic strains) from a series of previous studies in retail delis, were grown at 37 °C, in (i) stress conditions: salt (0, 5, and 10% NaCl), pH (5.2, 7.2, and 9.2), and sanitizer (benzalkonium chloride, 0, 2, and 5 µg/mL) and (ii) energy sources: 25 mM glucose, cellobiose, glycogen, fructose, lactose, and sucrose; the original goal was to follow up with low temperature experiments for treatments where significant differences were observed. Growth rate and the ability to grow of 95 isolates were determined using high-throughput, OD600, growth curves. All stress conditions reduced growth rates in isolates compared to control (p < 0.05). In addition, growth varied by the tested energy sources. In chemically defined, minimal media there was a trend toward more isolates showing growth in all replicates using cellobiose (p = 0.052) compared to the control (glucose) and fewer isolates able to grow in glycogen (p = 0.02), lactose (p = 2.2 × 10- 16), and sucrose (p = 2.2 × 10- 16). Still, at least one isolate was able to consistently grow in every replicate for each energy source. CONCLUSIONS: The central hypothesis was rejected, as there was not a significant difference in growth rate or ability to grow for retail deli isolates of persistent strains compared to sporadic strains for any treatments at 37 °C. Therefore, these data suggest that persistence is likely not determined by a phenotype unique to persistent strains grown at 37 °C and exposed to extrinsic stresses or variation in energy sources.

Microbial analysis of commercially available US Queso Fresco.

Queso Fresco (QF), a fresh Hispanic-style cheese, is often associated with Listeria monocytogenes outbreaks and recalls. Queso Fresco's susceptibility to bacterial contamination is partially due to its high pH and moisture content as well as Listeria's tolerance for the salt content typical for QF. Nine different brands of US QF, 2 packages from 4 different lots (to account for temporal variability), were sampled. The pH, salt content, and moisture content were analyzed in addition to microbial testing including yeasts and molds, coliforms, lactic acid bacteria enumeration, and L. monocytogenes counts. The cheeses were also inoculated with a cocktail of 5 food and human isolates of food-borne outbreak-associated Listeria monocytogenes strains to evaluate how the differences between brands influenced Listeria growth. Three of the cheeses underwent additional genus-level microbial analysis using extracted 16S rDNA, allowing for phylogenetic analysis between bacterial taxa including diversity and relative abundance. We found little variation between the sampled QF pH (range = 6.62-6.86), salt content (1.53-2.01%), and moisture content (43.90-54.50%). Yeasts and molds were below the detection limit of enumeration in all of the cheeses and coliforms were below the detection limit across the first 3 lots, but were detected at varying levels in the fourth lot (>3.0 most probable number/g) for 3 of the brands. Listeria monocytogenes was not isolated after enrichment in any of the samples. All cheeses tested positive for the presence of lactic acid bacteria, with only 1 of the cheeses being labeled as produced with added cultures having substantial counts. Fourteen days after inoculation with L. monocytogenes, at least 2.5 log10 cfu/g of growth was found for all QF brands stored at 4°C. Microbial genus analysis showed that, among the 3 brands, the microbial community was more similar within brand than when compared with the other 2 brands. Thermus, Anoxybacillus, and Streptococcus accounted for the dominant genera of brands A, B, and C, respectively. These variations within the microbial community may account for sensory differences and help manufacturers determine quality control consistency more readily than culture-based methods.

Whole-Genome Sequencing Allows for Improved Identification of Persistent Listeria monocytogenes in Food-Associated Environments.

While the food-borne pathogen Listeria monocytogenes can persist in food associated environments, there are no whole-genome sequence (WGS) based methods to differentiate persistent from sporadic strains. Whole-genome sequencing of 188 isolates from a longitudinal study of L. monocytogenes in retail delis was used to (i) apply single-nucleotide polymorphism (SNP)-based phylogenetics for subtyping of L. monocytogenes, (ii) use SNP counts to differentiate persistent from repeatedly reintroduced strains, and (iii) identify genetic determinants of L. monocytogenes persistence. WGS analysis revealed three prophage regions that explained differences between three pairs of phylogenetically similar populations with pulsed-field gel electrophoresis types that differed by ≤3 bands. WGS-SNP-based phylogenetics found that putatively persistent L. monocytogenes represent SNP patterns (i) unique to a single retail deli, supporting persistence within the deli (11 clades), (ii) unique to a single state, supporting clonal spread within a state (7 clades), or (iii) spanning multiple states (5 clades). Isolates that formed one of 11 deli-specific clades differed by a median of 10 SNPs or fewer. Isolates from 12 putative persistence events had significantly fewer SNPs (median, 2 to 22 SNPs) than between isolates of the same subtype from other delis (median up to 77 SNPs), supporting persistence of the strain. In 13 events, nearly indistinguishable isolates (0 to 1 SNP) were found across multiple delis. No individual genes were enriched among persistent isolates compared to sporadic isolates. Our data show that WGS analysis improves food-borne pathogen subtyping and identification of persistent bacterial pathogens in food associated environments.

Listeria floridensis sp. nov., Listeria aquatica sp. nov., Listeria cornellensis sp. nov., Listeria riparia sp. nov. and Listeria grandensis sp. nov., from agricultural and natural environments.

Sampling of agricultural and natural environments in two US states (Colorado and Florida) yielded 18 Listeria-like isolates that could not be assigned to previously described species using traditional methods. Using whole-genome sequencing and traditional phenotypic methods, we identified five novel species, each with a genome-wide average BLAST nucleotide identity (ANIb) of less than 85% to currently described species. Phylogenetic analysis based on 16S rRNA gene sequences and amino acid sequences of 31 conserved loci showed the existence of four well-supported clades within the genus Listeria; (i) a clade representing Listeria monocytogenes, L. marthii, L. innocua, L. welshimeri, L. seeligeri and L. ivanovii, which we refer to as Listeria sensu stricto, (ii) a clade consisting of Listeria fleischmannii and two newly described species, Listeria aquatica sp. nov. (type strain FSL S10-1188(T) = DSM 26686(T) = LMG 28120(T) = BEI NR-42633(T)) and Listeria floridensis sp. nov. (type strain FSL S10-1187(T) = DSM 26687(T) = LMG 28121(T) = BEI NR-42632(T)), (iii) a clade consisting of Listeria rocourtiae, L. weihenstephanensis and three novel species, Listeria cornellensis sp. nov. (type strain TTU A1-0210(T) = FSL F6-0969(T) = DSM 26689(T) = LMG 28123(T) = BEI NR-42630(T)), Listeria grandensis sp. nov. (type strain TTU A1-0212(T) = FSL F6-0971(T) = DSM 26688(T) = LMG 28122(T) = BEI NR-42631(T)) and Listeria riparia sp. nov. (type strain FSL S10-1204(T) = DSM 26685(T) = LMG 28119(T) = BEI NR- 42634(T)) and (iv) a clade containing Listeria grayi. Genomic and phenotypic data suggest that the novel species are non-pathogenic.

Risk Assessment Predicts Most of the Salmonellosis Risk in Raw Chicken Parts is Concentrated in Those Few Products with High Levels of High-Virulence Serotypes of Salmonella.

Salmonella prevalence declined in U.S. raw poultry products since adopting prevalence-based Salmonella performance standards, but human illnesses did not reduce proportionally. We used Quantitative Microbial Risk Assessment (QMRA) to evaluate public health risks of raw chicken parts contaminated with different levels of all Salmonella and specific high- and low-virulence serotypes. Lognormal Salmonella level distributions were fitted to 2012 USDA-FSIS Baseline parts survey and 2023 USDA-FSIS HACCP verification sampling data. Three different Dose-Response (DR) approaches included (i) a single DR for all serotypes, (ii) DR that reduces Salmonella Kentucky ST152 virulence, and (iii) multiple serotype-specific DR models. All scenarios found risk concentrated in the few products with high Salmonella levels. Using a single DR model with Baseline data (µ = -3.19, σ = 1.29 Log CFU/g), 68% and 37% of illnesses were attributed to the 0.7% and 0.06% of products with >1 and >10 CFU/g Salmonella, respectively. Using distributions from 2023 HACCP data (µ = -5.53, σ = 2.45), 99.8% and 99.0% of illnesses were attributed to the 1.3% and 0.4% of products with >1 and >10 CFU/g Salmonella, respectively. Scenarios with serotype-specific DR models showed more concentrated risk at higher levels. Baseline data showed 92% and 67% and HACCP data showed >99.99% and 99.96% of illnesses attributed to products with >1 and >10 CFU/g Salmonella, respectively. Regarding serotypes using Baseline or HACCP input data, 0.002% and 0.1% of illnesses were attributed to the 0.2% and 0.4% of products with >1 CFU/g of Kentucky ST152, respectively, while 69% and 83% of illnesses were attributed to the 0.3% and 0.6% of products with >1 CFU/g of Enteritidis, Infantis, or Typhimurium, respectively. Therefore, public health risk in chicken parts is concentrated in finished products with high levels and specifically high levels of high-virulence serotypes. Low-virulence serotypes like Kentucky contribute few human cases.

Persistent Listeria monocytogenes subtypes isolated from a smoked fish processing facility included both phage susceptible and resistant isolates.

Contamination of Ready-To-Eat foods with Listeria monocytogenes can typically be traced back to post-processing contamination from environmental sources; contamination is often linked to subtypes that persist in food associated environments. Although phage-based biocontrol strategies have been proposed for controlling this pathogen, information on the efficacy of phage treatment against diverse L. monocytogenes subtypes from food associated environments is still limited. We identified subtypes that were repeatedly found ("persistent") in a smoked fish processing facility by using EcoRI ribotyping data for isolates obtained in 1998-2009. PFGE analysis of 141 isolates (9 ribotypes) supported persistence for up to 11 years. Characterization of selected isolates, representing persistent subtypes, against a panel of 28 listeriaphages showed a wide range of likelihood of phage susceptibility, ranging from 4.6% (for 7 ribotype DUP-1043A isolates) to 95.4% (for 7 ribotype DUP-1044A isolates). In challenge studies with 10(5) and 10(6) CFU/ml L. monocytogenes, using phage cocktails and a commercial phage product at different phage-host ratios, one isolate (ribotype DUP-1043A) was not affected by any treatment. A reduction in L. monocytogenes counts of up to 4 log units was observed, after 8 h of treatment, in isolates of two ribotypes, but subsequent re-growth occurred. Survivor isolates obtained after 24 h of treatment showed decreased susceptibility to individual phages included in the phage cocktail, suggesting rapid emergence of resistant subtypes.

Modeling Preharvest Cyclospora cayetanensis Sampling and Testing for Various Water and Produce Sampling Plans.

As of August 2023, the two U.S. Food and Drug Administration (FDA) official detection methods for C. cayetanensis are outlined in the FDA Bacteriological Analytical Manual (BAM) Chapters 19b (produce testing) and 19c (agricultural water testing). These newly developed detection methods have been shown to not always detect contamination when present at low levels. Yet, industry and regulators may choose to use these methods as part of their monitoring and verification activities while detection methods continue to be improved. This study uses simulation to better understand the performance of these methods for various produce and water sampling plans. To do so, we used published FDA test validation data to fit a logistic regression model that predicts the methods' detection rate given the number of oocysts present in a 10-L agricultural water or 25 g produce sample. By doing so, we were able to determine contamination thresholds at which different numbers of samples (n = 1, 2, 4, 8, 16, and 32) would be adequate for detecting contamination. Furthermore, to evaluate sampling plans in use cases, a simulation was developed to represent C. cayetanensis contamination in agricultural water and on cilantro throughout a 45-day growth cycle. The model included uncertainty around the contamination sources, including scenarios of unintentionally contaminated irrigation water or in-field contamination. The results demonstrate that in cases where irrigation water was the contamination source, frequent water testing proved to be more powerful than produce testing. In scenarios where contamination occurred in-field, conducting frequent produce testing or testing produce toward the end of the season more reliably detected contamination. This study models the power of C. cayetanensis detection methods to understand the sampling plan performance and how these methods can be better used to monitor this emerging food safety hazard.

Simulation Evaluation of Power of Sampling Plans to Detect Cronobacter in Powdered Infant Formula Production.

Cronobacteris a hazard in Powdered Infant Formula (PIF) products that is hard to detect due to localized and low-level contamination. We adapted a previously published sampling simulation to PIF sampling and benchmarked industry-relevant sampling plans across different numbers of grabs, total sample mass, and sampling patterns. We evaluated performance to detect published Cronobacter contamination profiles for a recalled PIF batch [42% prevalence, -1.8 ± 0.7 log(CFU/g)] and a reference, nonrecalled, PIF batch [1% prevalence, -2.4 ± 0.8 log(CFU/g)]. Simulating a range of numbers of grabs [n = 1-22,000 (representing testing every finished package)] with 300 g total composite mass showed that taking 30 or more grabs detected contamination reliably (<1% median probability to accept the recalled batch). Benchmarking representative sampling plans ([n = 30, mass grab = 10g], [n = 30, m = 25g], [n = 60, m = 25g], [n = 180, m = 25g]) showed that all plans would reject the recalled batch (<1% median probability to accept) but would rarely reject the reference batch (>50% median probability of acceptance, all plans). Overall, (i) systematic or stratified random sampling patterns are equal to or more powerful than random sampling of the same sample size and total sampled mass, and, (ii) taking more samples, even if smaller, can increase the power to detect contamination.

Use of Doehlert Matrix as a Tool for High-Throughput Screening of Organic Acids and Essential Oils on Miniaturized Pork Loins, Followed by Lab-Scale Validation That Confirmed Tested Compounds Do Not Show Synergistic Effects against Salmonella Typhimurium.

The many possible treatments and continuously changing consumer trends present a challenge when selecting antimicrobial interventions during pork processing. Thirty-five potential antimicrobials were screened at commercial working concentrations by individually adding them to miniaturized (69 cm3) disks of pork loin ends, followed by inoculation with Salmonella Typhimurium ATCC 19585. Two organic acids and nine essential oils significantly inhibited Salmonella counts on pork (p < 0.05). However, six compounds that represent different levels of significance (p < 0.05-p < 0.0001) were selected as independent variables to build a Response Surface Methodology model based on a Doehlert matrix (Doehlert Matrix-RSM): lactic acid 1.25%, formic acid 0.25%, cumin 0.25%, clove 0.25%, peppermint 0.5%, and spearmint 0.5%. The goal of the Doehlert Matrix-RSM was to study single and paired effects of these antimicrobials on the change in Salmonella over 24 h. The Doehlert Matrix-RSM model predicted that lactic acid, formic acid, cumin, peppermint, and spearmint significantly reduced Salmonella when added alone, while no significant interactions between these antimicrobials were found. A laboratory-scale validation was carried out on pork loin end slices, which confirmed the results predicted by the model. While this screening did not identify novel synergistic combinations, our approach to screening a variety of chemical compounds by implementing a miniaturized pork loin disk model allowed us to identify the most promising antimicrobial candidates to then formally design experiments to study potential interactions with other antimicrobials.

Aggregative Soil Sampling Using Boot Covers Compared to Soil Grabs From Commercial Romaine Fields Shows Similar Indicator Organism and Microbial Community Recoveries.

Aggregative boot cover sampling may be a more representative, practical, and powerful method for preharvest produce soil testing than grab sampling because boot covers aggregate soil from larger areas. Our study tests if boot cover sampling results reflect quality and safety indicator organisms and community diversity of grab sampling. We collected soil samples from commercial romaine lettuce fields spanning 5060 m2 using boot covers (n = 28, m = 1.1 ± 0.4 g; wearing boot covers and walking along the path), composite grabs (n = 28, m = 231 ± 24 g; consisting of 60 grabs of 3-5 g each), and high-resolution grabs (n = 72, m = 56 ± 4 g; taking one sample per stratum). Means and standard deviations of log-transformed aerobic plate counts (APCs) were 7.0 ± 0.3, 7.1 ± 0.2, and 7.3 ± 0.2 log(CFU/g) for boot covers, composite grabs, and high-resolution grabs, respectively. APCs did not show biologically meaningful differences between sample types. Boot covers recovered on average 0.6 log(CFU/g) more total coliforms than both grabs (p < 0.001) where means and standard deviations of log-transformed counts were 3.2 ± 1.0, 2.6 ± 0.6, and 2.6 ± 1.0 log(CFU/g) for boot covers, composite grabs, and high-resolution grabs, respectively. There were no generic E. coli detected in any sample by enumeration methods with LODs of 1.3-2.1 log(CFU/g) for boot covers and 0.5 log(CFU/g) for both grabs. By 16S rRNA sequencing, community species diversity (alpha diversity) was not significantly different within collection methods. While communities differed (p < 0.001) between soil sampling methods (beta diversity), variance in microbial communities was not significantly different. Of the 28 phyla and 297 genera detected, 25 phyla (89%) and 258 genera (87%) were found by all methods. Overall, aggregative boot cover sampling is similar to both grab methods for recovering quality and safety indicator organisms and representative microbiomes. This justifies future work testing aggregative soil sampling for foodborne pathogen detection.

Multispectral Sorting Based on Visibly High-Risk Kernels Sourced from Another Country Reduces Fumonisin and Toxigenic Fusarium on Maize Kernels.

Fusarium species infect maize crops leading to the production of fumonisin by their toxigenic members. Elimination of microbes is critical in mitigating further postharvest spoilage and toxin accumulation. The current study investigates the efficacy of a previously described multispectral sorting technique to analyze the reduction of fumonisin and toxigenic Fusarium species found contaminating maize kernels in Kenya. Maize samples (n = 99) were collected from six mycotoxin hotspot counties in Kenya (Embu, Meru, Tharaka Nithi, Machakos, Makueni, and Kitui County) and analyzed for aflatoxin and fumonisin using commercial ELISA kits. Aflatoxin levels in majority (91%) of the samples were below the 10 ng/g threshold set by the Kenya Bureau of Standards and therefore not studied further. The 23/99 samples that had >2,000 ng/g of fumonisin were selected for sorting. The sorter was calibrated using kernels sourced from Ghana to reject visibly high-risk kernels for fumonisin contamination using reflectance at nine distinct wavelengths (470-1,550 nm). Accepted and rejected streams were tested for fumonisin using ELISA, and the presence of toxigenic Fusarium using qPCR. After sorting, there was a significant (p < 0.001) reduction of fumonisin, by an average of 1.8 log ng/g (98%) and ranging between 0.14 and 2.7 log ng/g reduction (28-99.8%) with a median mass rejection rate of 1.9% (ranged 0% to 48%). The fumonisin rejection rate ranged between 0 and 99.8% with a median of 77%. There was also a significant reduction (p = 0.005) in the proportion of DNA represented by toxigenic Fusarium, from a mean of 30-1.4%. This study demonstrates the use of multispectral sorting as a potential postharvest intervention tool for the reduction of Fusarium species and preformed fumonisin. The spectral sorting approach of this study suggests that classification algorithms based on high-risk visual features associated with mycotoxin can be applied across different sources of maize to reduce fumonisin.

Tomato Plant Microbiota under Conventional and Organic Fertilization Regimes in a Soilless Culture System.

Tomato is the main vegetable cultivated under soilless culture systems (SCSs); production of organic tomato under SCSs has increased due to consumer demands for healthier and environmentally friendly vegetables. However, organic tomato production under SCSs has been associated with low crop performance and fruit quality defects. These agricultural deficiencies could be linked to alterations in tomato plant microbiota; nonetheless, this issue has not been sufficiently addressed. Thus, the main goal of the present study was to characterize the rhizosphere and phyllosphere of tomato plants cultivated under conventional and organic SCSs. To accomplish this goal, tomato plants grown in commercial greenhouses under conventional or organic SCSs were tested at 8, 26, and 44 weeks after seedling transplantation. Substrate (n = 24), root (n = 24), and fruit (n = 24) composite samples were subjected to DNA extraction and high-throughput 16S rRNA gene sequencing. The present study revealed that the tomato core microbiota was predominantly constituted by Proteobacteria, Actinobacteria, and Firmicutes. Remarkably, six bacterial families, Bacillaceae, Microbacteriaceae, Nocardioidaceae, Pseudomonadaceae, Rhodobacteraceae, and Sphingomonadaceae, were shared among all substrate, rhizosphere, and fruit samples. Importantly, it was shown that plants under organic SCSs undergo a dysbiosis characterized by significant changes in the relative abundance of Bradyrhizobiaceae, Caulobacteraceae, Chitinophagaceae, Enterobacteriaceae, Erythrobacteraceae, Flavobacteriaceae, Nocardioidaceae, Rhodobacteraceae, and Streptomycetaceae. These results suggest that microbial alterations in substrates, roots, and fruits could be potential factors in contributing to the crop performance and fruit quality deficiencies observed in organic SCSs.

Efficacy of electron beam irradiation in reduction of mycotoxin-producing fungi, aflatoxin, and fumonisin, in naturally contaminated maize slurry.

Maize is a staple food in Kenya. However, maize is prone to fungal infestation, which may result in production of harmful aflatoxins and fumonisins. Electron beam (eBeam) food processing is a proven post-harvest technology, but published literature is rare on the ability of eBeam to reduce mycotoxins in naturally contaminated maize samples. This study evaluated the efficacy of eBeam doses in reducing viable fungal populations and the destruction of aflatoxins and fumonisins in naturally highly contaminated maize samples from eastern Kenya. Ninety-seven maize samples were analyzed for total aflatoxins and fumonisins using commercial ELISA kits. Then, 24 samples with >100 ng/g of total aflatoxins and >1000 ng/g of total fumonisins were chosen for eBeam toxin degradation studies. Prior to eBeam exposure studies, the samples were made into a slurry using sterile de-ionized water. These slurry samples were exposed to target doses of 5 kGy, 10 kGy, and 20 kGy, with 0 kGy (untreated) samples as controls. Samples were analyzed for total fungal load using culture methods, the quantity of total aflatoxins and fumonisins using ELISA, and the presence of Aspergillus and Fusarium spp. nucleic acids using qPCR for just control samples. There was a significant positive correlation in the control samples between total Aspergillus and aflatoxin levels (r = 0.54; p = 0.007) and total Fusarium and fumonisin levels (r = 0.68; p < 0.001). Exposure to eBeam doses 5 kGy and greater reduced fungal loads to below limits of detection by plating (<1.9 log(CFU/g)). There was also a significant (p = 0.03) average reduction of 0.3 log (ng/g) in aflatoxin at 20 kGy (range from -0.9 to 1.4 log (ng/g)). There was no significant reduction in fumonisin even at 20 kGy. eBeam doses below 20 kGy did not reduce mycotoxins. These results confirm the sensitivity of fungi to eBeam doses in a naturally contaminated maize slurry and that 20 kGy is effective at degrading some pre-formed aflatoxin in such maize preparations.

The transcriptional response of Listeria monocytogenes during adaptation to growth on lactate and diacetate includes synergistic changes that increase fermentative acetoin production.

The organic acids lactate and diacetate are commonly used in combination in ready-to-eat foods because they show synergistic ability to inhibit the growth of Listeria monocytogenes. Full-genome microarrays were used to investigate the synergistic transcriptomic responses of two L. monocytogenes strains, H7858 (serotype 4b) and F6854 (serotype 1/2a), to these two organic acids under conditions representing osmotic and cold stress encountered in foods. Strains were exposed to brain heart infusion (BHI) broth at 7°C with 4.65% water-phase (w.p.) NaCl at pH 6.1 with (i) 2% w.p. potassium lactate, (ii) 0.14% w.p. sodium diacetate, (iii) the combination of both at the same levels, or (iv) no organic acids as a control. RNA was extracted 8 h after exposure, during lag phase, to capture gene transcription changes during adaptation to the organic acid stress. Significant differential transcription of 1,041 genes in H7858 and 640 genes in F6854 was observed in at least one pair of the 4 different treatments. The effects of combined treatment with lactate and diacetate included (i) synergistic transcription differences for 474 and 209 genes in H7858 and F6854, respectively, (ii) differential transcription of genes encoding cation transporters and ABC transporters of metals, and (iii) altered metabolism, including induction of a nutrient-limiting stress response, reduction of menaquinone biosynthesis, and a shift from fermentative production of acetate and lactate to energetically less favorable, neutral acetoin. These data suggest that additional treatments that interfere with cellular energy generation processes could more efficiently inhibit the growth of L. monocytogenes.

Genomic Analysis of Prophages Recovered from Listeria monocytogenes Lysogens Found in Seafood and Seafood-Related Environment.

A prophage is a phage-related sequence that is integrated into a bacterial chromosome. Prophages play an important role in bacterial evolution, survival, and persistence. To understand the impact of Listeria prophages on their host genome organizations, this work sequenced two L. monocytogenes strains (134LM and 036LM), previously identified as lysogens by mitomycin C induction. Draft genomes were generated with assembly sizes of 2,953,877 bp and 3,000,399 bp. One intact prophage (39,532 bp) was inserted into the comK gene of the 134LM genome. Two intact prophages (48,684 bp and 39,488 bp) were inserted in tRNA-Lys and elongation-factor genes of the 036LM genome. The findings confirmed the presence of three corresponding induced phages previously obtained by mitomycin C induction. Comparative genomic analysis of three prophages obtained in the newly sequenced lysogens with 61 prophages found in L. monocytogenes genomes, available in public databases, identified six major clusters using whole genome-based phylogenetic analysis. The results of the comparative genomic analysis of the prophage sequences provides knowledge about the diversity of Listeria prophages and their distribution among Listeria genomes in diverse environments, including different sources or geographical regions. In addition, the prophage sequences and their insertion sites contribute to the genomic diversity of L. monocytogenes genomes. These data of prophage sequences, prophage insertion sites, and prophage sequence comparisons, together with ANIb confirmation, could be useful for L. monocytogenes classification by prophages. One potential development could be refinement of prophage typing tools for monitoring or surveillance of L. monocytogenes contamination and transmission.