Formation of Escherichia coli O157:H7 Persister Cells in the Lettuce Phyllosphere and Application of Differential Equation Models To Predict Their Prevalence on Lettuce Plants in the Field

A stochastic approach for modelling the in-vitro effect of osmotic stress on growth dynamics and persistent cell formation in Listeria monocytogenes

Persistent bacteria (or persisters) can be defined as a microbial subpopulation that, exposed to bactericidal treatment, is killed more slowly than the rest of the population they are part of. They stochastically originate in response to environmental stressors or spontaneously without external signals. When transferred into a fresh medium, persisters can resume active replication although they spend more time adapting to the new conditions remaining in the lag phase longer. They were studied for decades for their ability to survive antibiotic treatments while studies on their formation in food and potential impact on their safety are lacking. The most common food preservation techniques may act as stressors that trigger the formation of persistent bacteria able to survive bactericidal treatments and grow later in foods during storage. This study aimed to investigate a possible relationship between exposure to different salt concentrations (osmotic stress) and the amount of persisters triggered in a strain of Listeria monocytogenes. Furthermore, we described this phenomenon from a mathematical perspective through predictive microbiology models commonly used in the food field. The lag time distribution of a L. monocytogenes ATCC 7644 strain grown in broth with additional 2 %, 4 % and 6 % NaCl was evaluated using the software ScanLag. It uses office scanners to automatically record the colony growth on agar plates and evaluate the frequency distribution of their appearance times (lag phase) by automated image analysis. The same broth cultures were diluted to equalize salt concentration and transferred into a fresh broth to evaluate how the previous salt exposure impacted their growth kinetics. The observed growth curves were reproduced using predictive models in which the mean duration of the lag phase of the whole population took into account the occurrence of persisters with a longer lag phase. The models were solved first using a deterministic approach and then a stochastic one introducing a stochastic term that mimics the variability of lag phase duration due to the persisters occurrence. Results showed that the growth of L. monocytogenes in broth with additional NaCl might trigger the formation of persistent cells whose number increased consistently with salt concentrations. The proposed predictive approach reproduced the observed real curves in strong agreement, especially through the stochastic resolution of the models. Persistence is currently a neglected bacterial defence strategy in the food sector but the persisters' formation during production cannot be excluded; therefore, further insights on the topic are certainly desirable.

Predictive Population Dynamics of Escherichia coli O157:H7 and Salmonella enterica on Plants: a Mechanistic Mathematical Model Based on Weather Parameters and Bacterial State

Weather affects key aspects of bacterial behavior on plants but has not been extensively investigated as a tool to assess risk of crop contamination with human foodborne pathogens. A novel mechanistic model informed by weather factors and bacterial state was developed to predict population dynamics on leafy vegetables and tested against published data tracking Escherichia coli O157:H7 (EcO157) and Salmonella enterica populations on lettuce and cilantro plants. The model utilizes temperature, radiation, and dew point depression to characterize pathogen growth and decay rates. Additionally, the model incorporates the population level effect of bacterial physiological state dynamics in the phyllosphere in terms of the duration and frequency of specific weather parameters. The model accurately predicted EcO157 and S. enterica population sizes on lettuce and cilantro leaves in the laboratory under various conditions of temperature, relative humidity, light intensity, and cycles of leaf wetness and dryness. Importantly, the model successfully predicted EcO157 population dynamics on 4-week-old romaine lettuce plants under variable weather conditions in nearly all field trials. Prediction of initial EcO157 population decay rates after inoculation of 6-week-old romaine plants in the same field study was better than that of long-term survival. This suggests that future augmentation of the model should consider plant age and species morphology by including additional physical parameters. Our results highlight the potential of a comprehensive weather-based model in predicting contamination risk in the field. Such a modeling approach would additionally be valuable for timing field sampling in quality control to ensure the microbial safety of produce. IMPORTANCE Fruits and vegetables are important sources of foodborne disease. Novel approaches to improve the microbial safety of produce are greatly lacking. Given that bacterial behavior on plant surfaces is highly dependent on weather factors, risk assessment informed by meteorological data may be an effective tool to integrate into strategies to prevent crop contamination. A mathematical model was developed to predict the population trends of pathogenic E. coli and S. enterica, two major causal agents of foodborne disease associated with produce, on leaves. Our model is based on weather parameters and rates of switching between the active (growing) and inactive (nongrowing) bacterial state resulting from prevailing environmental conditions on leaf surfaces. We demonstrate that the model has the ability to accurately predict dynamics of enteric pathogens on leaves and, notably, sizes of populations of pathogenic E. coli over time after inoculation onto the leaves of young lettuce plants in the field.

Weather stressors correlate with Escherichia coli and Salmonella enterica persister formation rates in the phyllosphere: a mathematical modeling study

Enteric pathogens can enter a persister state in which they survive exposure to antibiotics and physicochemical stresses. Subpopulations of such phenotypic dormant variants have been detected in vivo and in planta in the laboratory, but their formation in the natural environment remains largely unexplored. We applied a mathematical model predicting the switch rate to persister cell in the phyllosphere to identify weather-related stressors associated with E. coli and S. enterica persister formation on plants based on their population dynamics in published field studies from the USA and Spain. Model outputs accurately depicted the bi-phasic decay of bacterial population sizes measured in the lettuce and spinach phyllosphere in these studies. Predicted E. coli persister switch rate on leaves was positively and negatively correlated with solar radiation intensity and wind velocity, respectively. Likewise, predicted S. enterica persister switch rate correlated positively with solar radiation intensity; however, a negative correlation was observed with air temperature, relative humidity, and dew point, factors involved in water deposition onto the phylloplane. These findings suggest that specific environmental factors may enrich for dormant bacterial cells on plants. Our model quantifiably links persister cell subpopulations in the plant habitat with broader physical conditions, spanning processes at different granular scales.

Seasonality, shelf life and storage atmosphere are main drivers of the microbiome and E. coli O157:H7 colonization of post-harvest lettuce cultivated in a major production area in California

BACKGROUND

Lettuce is linked to recurrent outbreaks of Shiga toxin-producing Escherichia coli (STEC) infections, the seasonality of which remains unresolved. Infections have occurred largely from processed lettuce, which undergoes substantial physiological changes during storage. We investigated the microbiome and STEC O157:H7 (EcO157) colonization of fresh-cut lettuce of two cultivars with long and short shelf life harvested in the spring and fall in California and stored in modified atmosphere packaging (MAP) at cold and warm temperatures.

RESULTS

Inoculated EcO157 declined significantly less on the cold-stored cultivar with short shelf life, while multiplying rapidly at 24 °C independently of cultivar. Metagenomic sequencing of the lettuce microbiome revealed that the pre-storage bacterial community was variable but dominated by species in the Erwiniaceae and Pseudomonadaceae. After cold storage, the microbiome composition differed between cultivars, with a greater relative abundance (RA) of Erwiniaceae and Yersiniaceae on the cultivar with short shelf life. Storage at 24 °C shifted the microbiome to higher RAs of Erwiniaceae and Enterobacteriaceae and lower RA of Pseudomonadaceae compared with 6 °C. Fall harvest followed by lettuce deterioration were identified by recursive partitioning as important factors associated with high EcO157 survival at 6 °C, whereas elevated package CO₂ levels correlated with high EcO157 multiplication at 24 °C. EcO157 population change correlated with the lettuce microbiome during 6 °C storage, with fall microbiomes supporting the greatest EcO157 survival on both cultivars. Fall and spring microbiomes differed before and during storage at both temperatures. High representation of Pantoea agglomerans was a predictor of fall microbiomes, lettuce deterioration, and enhanced EcO157 survival at 6 °C. In contrast, higher RAs of Erwinia persicina, Rahnella aquatilis, and Serratia liquefaciens were biomarkers of spring microbiomes and lower EcO157 survival.

CONCLUSIONS

The microbiome of processed MAP lettuce evolves extensively during storage. Under temperature abuse, high CO₂ promotes a lettuce microbiome enriched in taxa with anaerobic capability and EcO157 multiplication. In cold storage, our results strongly support a role for season and lettuce deterioration in EcO157 survival and microbiome composition, suggesting that the physiology and microbiomes of fall- and spring-harvested lettuce may contribute to the seasonality of STEC outbreaks associated with lettuce grown in coastal California.

The risk of transmitting antibiotic resistance through endophytic bacteria

Antibiotic resistance is a global human health threat distributed across humans, animals, plants, and the environment. Under the One-Health concept (humans, animals, and environment), the contamination of water bodies and soil by antibiotic-resistant bacteria cannot be dissociated from its potential transmission to humans. Edible plants can be colonized by a vast diversity of bacteria, representing an important link between the environment and humans in the One-Health triad. Based on multiple examples of bacterial groups that comprise endophytes reported in edible plants, and that have close phylogenetic proximity with human opportunistic pathogens, we argue that plants exposed to human-derived biological contamination may represent a path of transmission of antibiotic resistance to humans.

Environmental Spread of Antibiotic Resistance

Antibiotic resistance represents a global health concern. Soil, water, livestock and plant foods are directly or indirectly exposed to antibiotics due to their agricultural use or contamination. This selective pressure has acted synergistically to bacterial competition in nature to breed antibiotic-resistant (AR) bacteria. Research over the past few decades has focused on the emergence of AR pathogens in food products that can cause disease outbreaks and the spread of antibiotic resistance genes (ARGs), but One Health approaches have lately expanded the focus to include commensal bacteria as ARG donors. Despite the attempts of national and international authorities of developed and developing countries to reduce the over-prescription of antibiotics to humans and the use of antibiotics as livestock growth promoters, the selective flow of antibiotic resistance transmission from the environment to the clinic (and vice-versa) is increasing. This review focuses on the mechanisms of ARG transmission and the hotspots of antibiotic contamination resulting in the subsequent emergence of ARGs. It follows the transmission of ARGs from farm to plant and animal food products and provides examples of the impact of ARG flow to clinical settings. Understudied and emerging antibiotic resistance selection determinants, such as heavy metal and biocide contamination, are also discussed here.

Shaping the leaf microbiota: plant-microbe-microbe interactions

The aerial portion of a plant, namely the leaf, is inhabited by pathogenic and non-pathogenic microbes. The leaf's physical and chemical properties, combined with fluctuating and often challenging environmental factors, create surfaces that require a high degree of adaptation for microbial colonization. As a consequence, specific interactive processes have evolved to establish a plant leaf niche. Little is known about the impact of the host immune system on phyllosphere colonization by non-pathogenic microbes. These organisms can trigger plant basal defenses and benefit the host by priming for enhanced resistance to pathogens. In most disease resistance responses, microbial signals are recognized by extra- or intracellular receptors. The interactions tend to be species specific and it is unclear how they shape leaf microbial communities. In natural habitats, microbe-microbe interactions are also important for shaping leaf communities. To protect resources, plant colonizers have developed direct antagonistic or host manipulation strategies to fight competitors. Phyllosphere-colonizing microbes respond to abiotic and biotic fluctuations and are therefore an important resource for adaptive and protective traits. Understanding the complex regulatory host-microbe-microbe networks is needed to transfer current knowledge to biotechnological applications such as plant-protective probiotics.

The progress of type II persisters of Escherichia coli O157:H7 to a non-culturable state during prolonged exposure to antibiotic stress with revival being aided through acid-shock treatment and provision of methyl pyruvate

Persisters are a form of dormancy in bacteria that provide temporary resistance to antibiotics. The following reports on the formation of Escherichia coli O157:H7 E318 type II persisters from a protracted (8 days) challenge with ampicillin. Escherichia coli O157:H7 followed a multiphasic die-off pattern with an initial rapid decline (Phase I) of susceptible cells that transitioned to a slower rate representing tolerant cells (Phase II). After 24 h post-antibiotic challenge, the E. coli O157:H7 levels remained relatively constant at 2 log CFU/mL (Phase III), but became non-culturable within 8-days (Phase IV). The revival of persisters in Phase III could be achieved by the removal of antibiotic stress, although those in Phase IV required an extended incubation period or application of acid-shock. The carbon utilization profile of persister cells was less diverse compared with non-persisters, with only methyl pyruvate being utilized from the range tested. Inclusion of methyl pyruvate in tryptic soy agar revived non-cultural persisters, presumably by stimulating metabolism. The results suggest that persisters could be subdivided into culturable or non-culturable cells, with the former representing a transition state to the latter. The study provided insights into how to revive cells from dormancy to aid enumeration and control.

Innovative breeding technologies in lettuce for improved post-harvest quality

Societal awareness of healthy eating is increasing alongside the market for processed bagged salads, which remain as one of the strongest growing food sectors internationally, including most recently from indoor growing systems. Lettuce represents a significant proportion of this ready-to-eat salad market. However, such products typically have a short shelf life, with decay of post-harvest quality occurring through complex biochemical and physiological changes in leaves and resulting in spoilage, food waste and risks to health. We review the functional and quantitative genetic understanding of lettuce post-harvest quality, revealing that few findings have translated into improved cultivar development. We identify (i) phytonutrient status (for enhanced antioxidant and vitamin status, aroma and flavour) (ii) leaf biophysical, cell wall and water relations traits (for longer shelf life) (iii) leaf surface traits (for enhanced food safety and reduced spoilage) and (iv) chlorophyll, other pigments and developmental senescence traits (for appearance and colour), as key targets for future post-harvest breeding. Lettuce is well-placed for rapid future exploitation to address postharvest quality traits with extensive genomic resources including the recent release of the lettuce genome and the development of innovative breeding technologies. Although technologies such as CRISPR/Cas genome editing are paving the way for accelerated crop improvement, other equally important resources available for lettuce include extensive germplasm collections, bi-parental mapping and wide populations with genotyping for genomic selection strategies and extensive multiomic datasets for candidate gene discovery. We discuss current progress towards post-harvest quality breeding for lettuce and how such resources may be utilised for future crop improvement.

Effect of Weather on the Die-Off of Escherichia coli and Attenuated Salmonella enterica Serovar Typhimurium on Preharvest Leafy Greens following Irrigation with Contaminated Water

The Food Safety Modernization Act (FSMA) includes a time-to-harvest interval following the application of noncompliant water to preharvest produce to allow for microbial die-off. However, additional scientific evidence is needed to support this rule. This study aimed to determine the impact of weather on the die-off rate of Escherichia coli and Salmonella on spinach and lettuce under field conditions. Standardized, replicated field trials were conducted in California, New York, and Spain over 2 years. Baby spinach and lettuce were grown and inoculated with an ∼104-CFU/ml cocktail of E. coli and attenuated Salmonella Leaf samples were collected at 7 time points (0 to 96 h) following inoculation; E. coli and Salmonella were enumerated. The associations of die-off with study design factors (location, produce type, and bacteria) and weather were assessed using log-linear and biphasic segmented log-linear regression. A segmented log-linear model best fit die-off on inoculated leaves in most cases, with a greater variation in the segment 1 die-off rate across trials (-0.46 [95% confidence interval {95% CI}, -0.52, -0.41] to -6.99 [95% CI, -7.38, -6.59] log10 die-off/day) than in the segment 2 die-off rate (0.28 [95% CI, -0.20, 0.77] to -1.00 [95% CI, -1.16, -0.85] log10 die-off/day). A lower relative humidity was associated with a faster segment 1 die-off and an earlier breakpoint (the time when segment 1 die-off rate switches to the segment 2 rate). Relative humidity was also found to be associated with whether die-off would comply with FSMA's specified die-off rate of -0.5 log10 die-off/day.IMPORTANCE The log-linear die-off rate proposed by FSMA is not always appropriate, as the die-off rates of foodborne bacterial pathogens and specified agricultural water quality indicator organisms appear to commonly follow a biphasic pattern with an initial rapid decline followed by a period of tailing. While we observed substantial variation in the net culturable population levels of Salmonella and E. coli at each time point, die-off rate and FSMA compliance (i.e., at least a 2 log10 die-off over 4 days) appear to be impacted by produce type, bacteria, and weather; die-off on lettuce tended to be faster than that on spinach, die-off of E. coli tended to be faster than that of attenuated Salmonella, and die-off tended to become faster as relative humidity decreased. Thus, the use of a single die-off rate for estimating time-to-harvest intervals across different weather conditions, produce types, and bacteria should be revised.