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

Food Science and Technology

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

M. T. Brandl, R. Ivanek, et al.

This fascinating study explores how enteric pathogens like *E. coli* and *S. enterica* can enter a persister state amid varying environmental conditions. Using a mathematical model, researchers predicted how these pathogens survive and thrive on leafy greens, revealing intriguing correlations with solar radiation and other weather factors. Discover the groundbreaking findings from experts like Maria T. Brandl and others!

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Playback language: English
Introduction
Bacterial populations in the phyllosphere face diverse conditions, including solar radiation, water scarcity, temperature fluctuations, nutrient limitations, and antimicrobials, all of which influence their survival. Human enteric pathogens on crops often exhibit biphasic decay: an initial rapid decline followed by a stable, smaller population. These surviving cells are crucial because they may serve as a reservoir for future pathogen amplification, increasing foodborne illness risk. The heterogeneous nature of plant surfaces means clonal bacterial populations may form subpopulations with differing physiologies; some cells may enter a persister state—a phenotypic dormancy—surviving stress without genetic changes. This dormancy is thought to be a survival strategy triggered by environmental cues such as nutritional, acidic, oxidative, osmotic, and antimicrobial stresses. While persisters and viable-but-non-culturable (VBNC) cells might represent a dormancy continuum, the persister state is transient, allowing cells to revert to a replicating state under favorable conditions. Previous research has shown the presence of *E. coli* O157:H7 persister cells on spinach and lettuce, with higher persister fractions under dry conditions. A mathematical model accurately described *E. coli* O157:H7 survival in several field studies, showcasing biphasic decay. Given the significant public health threat of enteric pathogen contamination on edible crops, particularly leafy greens, understanding the influence of environmental stressors on pathogen behavior is crucial for developing crop safety strategies. This study utilizes mathematical modeling and data on *E. coli* and *Salmonella enterica* survival on spinach and lettuce under varying weather conditions to estimate persister cell switch rates and explore the relationship between weather factors and persister formation.
Literature Review
The introduction extensively reviews existing literature on the phyllosphere microbiology, biphasic decay of enteric pathogens on plants, persister cell formation in bacteria, and the public health implications of contaminated produce. It cites numerous studies demonstrating biphasic decay patterns of *E. coli* and *Salmonella* on leafy greens, highlighting the significance of understanding the survival mechanisms of these pathogens in the plant environment. The review also covers the role of phenotypic heterogeneity in bacterial populations, the characteristics of persister cells, and the environmental factors that can induce persister formation. Previous work by the authors on *E. coli* O157:H7 persister formation on lettuce and the development of a mathematical model to describe persister switch rates are also discussed.
Methodology
This study employed a mathematical model and data from a previously published field study on *E. coli* and *Salmonella* survival on spinach and lettuce under various weather conditions. The field study involved spray-inoculating plants with rifampin-resistant *E. coli* and attenuated *S. enterica* serovar Typhimurium at three locations (California, New York, and Spain). Bacterial populations were quantified via plate counts at various time points (0, 4, 8, 24, 48, 72, and 96 h post-inoculation), and concurrent hourly weather data (temperature, relative humidity (RH), solar radiation intensity, and wind velocity) were recorded. The model, based on previous laboratory work, assumes the total pathogen population comprises normal cells (fast and slow decay) and persister cells. A simplified model, derived from a more complex system, focused on the switch rate (α) from normal to persister cells. This simplified model was fit to the field study data using a least squares approach, with the parameter α representing the maximum switch rate. Spearman and partial Spearman correlation analyses were then used to assess the relationship between α and various weather factors (8-h averages, minimums, and ranges) while controlling for other factors and produce type. The model fitting procedure involved minimizing the sum of squared errors (log-transformed) between observed and predicted bacterial populations. The initial persister population was assumed to be minimal, to obtain the largest possible (and most conservative) switch rate.
Key Findings
The mathematical model accurately captured the biphasic decay patterns observed in the field study data for both *E. coli* and *Salmonella* on lettuce and spinach. For *E. coli*, the persister switch rate (α) was positively correlated with solar radiation intensity and negatively correlated with wind speed (based on partial Spearman correlation). For *Salmonella*, α showed a strong positive correlation with solar radiation and negative correlations with relative humidity, temperature, and dew point (based on partial Spearman correlation). The negative correlations with temperature for *Salmonella* were explained by the strong negative correlation between temperature and dew point. Analyzing minimum values and ranges of weather parameters further strengthened these findings. The root mean square errors from the model fits were low, indicating good agreement between the model and the data. The maximum persister population was predicted to occur within 10 hours post-inoculation, justifying the focus on 8-hour average weather data in the correlation analysis.
Discussion
The positive correlation between persister formation and solar radiation for both pathogens aligns with the known induction of persistence by the SOS response in *E. coli* and likely in *Salmonella*, due to the high similarity in their DNA repair response networks. The negative correlation of *Salmonella* persister formation with factors promoting leaf wetness (RH, temperature, dew point) is consistent with evidence suggesting osmotic stress and starvation (associated with low water availability) can induce persister cell formation. The negative correlation between *E. coli* persister formation and wind speed might be due to reduced leaf temperatures and potential shading effects from leaf movement. The findings highlight the importance of using partial correlation analyses to reveal significant correlations that might be masked by direct correlations and interdependencies among various weather factors. The similar persister response in both spinach and lettuce might be because of the young growth stage of the plants during the experiment, resulting in similar leaf structures and environments. These results provide valuable insights into the environmental factors influencing persister cell formation in enteric pathogens on plants and the potential implications for food safety.
Conclusion
This study demonstrates that weather conditions significantly influence the formation of persister cells in *E. coli* and *Salmonella* on leafy greens. Solar radiation was a major driver of persister formation in both pathogens, while other factors, such as wind speed for *E. coli* and humidity-related parameters for *Salmonella*, played species-specific roles. These findings have important implications for food safety strategies, suggesting that environmental conditions can significantly affect the survival and persistence of these pathogens on produce. Future research could focus on investigating the underlying molecular mechanisms of persistence under different environmental conditions and explore the effectiveness of interventions targeting persister cell formation.
Limitations
The study relies on data from a previous field study, limiting the control over experimental conditions. The model simplifies complex interactions between pathogens and their environment, neglecting potential interactions between weather factors and other variables. The focus on 8-hour average weather data might not fully capture short-term fluctuations in environmental conditions. While the study suggests distinct pathways for persister formation in different bacteria, further research at a molecular level is needed to fully elucidate these mechanisms. Finally, the study focuses on specific plant varieties at a particular growth stage, and results may not be generalizable to all plant types and growth stages.
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