Transmission of Escherichia coli O157:H7 to internal tissues and its survival on flowering heads of wheat

From wheat grain to flour: a review of potential sources of enteric pathogen contamination in wheat milled products

The number of food safety issues linked to wheat milled products have increased in the past decade. These incidents were mainly caused by the contamination of wheat-based products by enteric pathogens. This manuscript is the first of a two-part review on the status of the food safety of wheat-based products. This manuscript focused on reviewing the available information on the potential pre-harvest and post-harvest sources of microbial contamination, and potential foodborne pathogens present in wheat-based products. Potential pre-harvest sources of microbial contamination in wheat included animal activity, water, soil, and manure. Improper grain storage practices, pest activity, and improperly cleaned and sanitized equipment are potential sources of post-harvest microbial contamination for wheat-based foods. Raw wheat flour products and flour-based products are potentially contaminated with enteric pathogens such as Shiga toxin-producing E. coli (STECs), and Salmonella at low concentrations. Wheat grains and their derived products (i.e., flours) are potential vehicles for foodborne illness in humans due to the presence of enteric pathogens. A more holistic approach is needed for assuring the food safety of wheat-based products in the farm-to-table continuum. Future developments in the wheat supply chain should also be aimed at addressing this emerging food safety threat.

Prediction of E. coli Concentrations in Agricultural Pond Waters: Application and Comparison of Machine Learning Algorithms

The microbial quality of irrigation water is an important issue as the use of contaminated waters has been linked to several foodborne outbreaks. To expedite microbial water quality determinations, many researchers estimate concentrations of the microbial contamination indicator Escherichia coli (E. coli) from the concentrations of physiochemical water quality parameters. However, these relationships are often non-linear and exhibit changes above or below certain threshold values. Machine learning (ML) algorithms have been shown to make accurate predictions in datasets with complex relationships. The purpose of this work was to evaluate several ML models for the prediction of E. coli in agricultural pond waters. Two ponds in Maryland were monitored from 2016 to 2018 during the irrigation season. E. coli concentrations along with 12 other water quality parameters were measured in water samples. The resulting datasets were used to predict E. coli using stochastic gradient boosting (SGB) machines, random forest (RF), support vector machines (SVM), and k-nearest neighbor (kNN) algorithms. The RF model provided the lowest RMSE value for predicted E. coli concentrations in both ponds in individual years and over consecutive years in almost all cases. For individual years, the RMSE of the predicted E. coli concentrations (log10 CFU 100 ml-1) ranged from 0.244 to 0.346 and 0.304 to 0.418 for Pond 1 and 2, respectively. For the 3-year datasets, these values were 0.334 and 0.381 for Pond 1 and 2, respectively. In most cases there was no significant difference (P > 0.05) between the RMSE of RF and other ML models when these RMSE were treated as statistics derived from 10-fold cross-validation performed with five repeats. Important E. coli predictors were turbidity, dissolved organic matter content, specific conductance, chlorophyll concentration, and temperature. Model predictive performance did not significantly differ when 5 predictors were used vs. 8 or 12, indicating that more tedious and costly measurements provide no substantial improvement in the predictive accuracy of the evaluated algorithms.

Visible light-activated ZnO nanoparticles for microbial control of wheat crop

Every year 15-50% of cereals all around the world are lost due to fungal contamination and deterioration. In addition, 25% of crops, which are used for human and animal consumption, are contaminated with mycotoxins. It is obvious, that more effective and sustainable technologies for better microbial control of crops are required. For this purpose we evaluated antibacterial and antifungal activity of ZnO nanoparticles (NPs) (10^-3-5 × 10^-3M) activated with visible light (405 nm, 18-30 J/cm²). Obtained data indicated that this treatment can inactivate human pathogen E. coli B by 6 log CFU without any possibility to regrowth after treatment. Wheat pathogen Fusarium oxysporum was inactivated by 51.7%. Results indicated that reactive oxygen species took place in the mechanisms of inactivation. Moreover, visible light activated ZnO NPs reduced the population of mesophiles on the surface of grains by 2.5 log CFU/g, inoculated E. coli- by 2.0 log CFU/g and naturally distributed fungi-by 2.1 log CFU/g. This treatment had no impact on visual quality of grains, did not inhibit grain germination rate and slightly promoted grain seedling growth. Concluding, the use of visible light driven photocatalysis in ZnO nanoparticles has huge potential to control plant pathogens, reduce food-borne diseases and subsequently enhance the sustainability in agriculture, meeting the increasing demands of a growing world population.

Enterobacteriaceae predominate in the endophytic microbiome and contribute to the resistome of strawberry

Antibiotic resistance genes (ARGs) harbored by plant microbiomes have been implicated as a potential risk to public health via food chain, especially directly edible fruits and vegetables. Here, we investigated the microbiome and antibiotic resistome in soil-strawberry ecosystem using shotgun metagenomic sequencing. The results showed that the enterobacterial population dominated the endophytes of strawberry fruits. Moreover, 85 subtypes of ARGs, including several clinically important ARGs, were detected in the strawberry fruit metagenomes. Additionally, host tracking analysis in combination with antibiotic-resistant bacterial isolate screening suggested that fruit-borne ARGs were mainly carried by members of the Enterobacteriaceae family. Unexpectedly, most of fruit-borne isolates were found to be resistant to several clinically important antimicrobials, e.g., erythromycin and cephalexin. Our findings provide broad insights into endophytic antibiotic resistomes of direct edible strawberry fruits and their potential hosts, and highlight the potential exposure risks of plant microbiomes to the human food chain.

Reduction in pathogenic load of wheat by tempering with saline organic acid solutions at different seasonal temperatures

As a raw agricultural commodity, wheat is exposed to microbial contamination; therefore, enteric pathogens may be among its microbiota creating a food safety risk in milled products. This research evaluates (1) the effectiveness of organic acids dissolved in saline solutions to reduce the counts of pathogenic microorganisms in soft and hard wheat, and also investigates the effect of seasonal temperature on (2) survivability of pathogens in wheat kernels and on (3) pathogen inactivation during tempering with saline organic acid solutions. Wheat samples were inoculated with cocktails of either 5 serovars of Salmonella enterica, 5 E. coli O157:H7 or 6 non-O157 Shiga toxin-producing E. coli (STEC) strains to achieve a concentration of ~7 log CFU/g. Inoculated samples were allowed to stand for 7-days at temperatures (2.0, 10.8, 24.2, 32 °C) corresponding to those experienced during winter, spring/fall, and summer (average and maximum) in the main wheat growing regions in the state of Nebraska, USA. Besides water, solutions containing acid (acetic or lactic 2.5% or 5.0% v/v) and NaCl (~26% w/v) were used for tempering the wheat to 15.0% (soft) and 15.5% (hard) moisture at the different seasonal temperatures. The survival of pathogenic microorganisms throughout the resting period, and before and after tempering was analyzed by plating samples on injury-recovery media. The survival rate of pathogenic microorganisms on wheat kernels was higher at temperatures experienced during the winter (2.0 °C) and spring/fall (10.8 °C) months. Regardless of tempering temperature, the initial pathogen load was reduced significantly by all solutions when compared to the control tempered with water (P ≤ .05). The combination of lactic acid (5.0%) and NaCl was the most effective treatment against Salmonella enterica, E. coli O157:H7 and non-O157 STEC, with average reduction values of 1.8, 1.8 and 1.6 log CFU/g for soft wheat and 2.6, 2.4 and 2.4 log CFU/g for hard wheat, respectively. Implementation of organic acids and NaCl in tempering water may have the potential to reduce the risk of pathogen contamination in milled products.

Differences in internalization and growth of Escherichia coli O157:H7 within the apoplast of edible plants, spinach and lettuce, compared with the model species Nicotiana benthamiana

Internalization of food-borne bacteria into edible parts of fresh produce plants represents a serious health risk. Therefore, internalization of verocytotoxigenic E. coli O157:H7 isolate Sakai was assessed in two species associated with outbreaks, spinach (Spinacia oleracea) and lettuce (Lactuca sativa) and compared to the model species Nicotiana benthamiana. Internalization occurred in the leaves and roots of spinach and lettuce throughout a 10 day time-course. The plant species, tissue type and inoculum dose all impacted the outcome. A combination of low inoculum dose (~102 CFU) together with light microscopy imaging highlighted marked differences in the fate of endophytic E. coli O157:H7 Sakai. In the fresh produce species, bacterial growth was restricted but viable cells persisted over 20 days, whereas there was > 400-fold (~2.5 Log10 ) increase in growth in N. benthamiana. Colony formation occurred adjacent to epidermal cells and mesophyll cells or close to vascular bundles of N. benthamiana and contained components of a biofilm matrix, including curli expression and elicitation, extracellular DNA and a limited presence of cellulose. Together the data show that internalization is a relevant issue in crop production and that crop species and tissue need to be considered as food safety risk parameters.

Long-term survival of the Shiga toxin-producing Escherichia coli O104:H4 outbreak strain on fenugreek seeds

A major outbreak of Shiga toxin-producing Escherichia coli (STEC) O104:H4 occurred in Germany in 2011. The epidemiological investigation revealed that a contaminated batch of fenugreek seeds (Trigonella foenum-graecum) was the most probable source of the pathogen. It was suggested that the most probable point of contamination was prior to leaving the importer, meaning that the seed contamination with STEC O104:H4 should have happened more than one year before the seeds were used for sprout production. Here, we investigated the capacity of STEC O104:H4 and closely related pathogenic as well as non-pathogenic Escherichia coli strains for long-term survival on dry fenugreek seeds. We did not observe a superior survival capacity of STEC O104:H4 on dry seeds. For none of the strains tested cultivatable cells were found without enrichment on contaminated seeds after more than 24 weeks of storage. Our findings suggest that contamination previous to the distribution from the importer may be less likely than previously assumed. We show that seeds contaminated with E. coli in extremely high numbers can be completely sterilized by a short treatment with bleach. This simple and cheap procedure does not affect the germination capacity of the seeds and could significantly improve safety in sprout production.

Antibiotics and Antibiotic Resistance in Agroecosystems: State of the Science

We propose a simple causal model depicting relationships involved in dissemination of antibiotics and antibiotic resistance in agroecosystems and potential effects on human health, functioning of natural ecosystems, and agricultural productivity. Available evidence for each causal link is briefly summarized, and key knowledge gaps are highlighted. A lack of quantitative estimates of human exposure to environmental bacteria, in general, and antibiotic-resistant bacteria, specifically, is a significant data gap hindering the assessment of effects on human health. The contribution of horizontal gene transfer to resistance in the environment and conditions that might foster the horizontal transfer of antibiotic resistance genes into human pathogens also need further research. Existing research has focused heavily on human health effects, with relatively little known about the effects of antibiotics and antibiotic resistance on natural and agricultural ecosystems. The proposed causal model is used to elucidate gaps in knowledge that must be addressed by the research community and may provide a useful starting point for the design and analysis of future research efforts.