Weather factors, soil microbiome, and bacteria-fungi interactions as drivers of the epiphytic phyllosphere communities of romaine lettuce

Differential microbiota shift on whole romaine lettuce subjected to source or forward processing and on fresh-cut products during cold storage

Romaine lettuce in the U.S. is primarily grown in California or Arizona and either processed near the growing regions (source processing) or transported long distance for processing in facilities serving distant markets (forward processing). Recurring outbreaks of Escherichia coli O157:H7 implicating romaine lettuce in recent years, which sometimes exhibited patterns of case clustering in Northeast and Midwest, have raised industry concerns over the potential impact of forward processing on romaine lettuce food safety and quality. In this study, freshly harvested romaine lettuce from a commercial field destined for both forward and source processing channels was tracked from farm to processing facility in two separate trials. Whole-head romaine lettuce and packaged fresh-cut products were collected from both forward and source facilities for microbiological and product quality analyses. High-throughput amplicon sequencing targeting16S rRNA gene was performed to describe shifts in lettuce microbiota. Total aerobic bacteria and coliform counts on whole-head lettuce and on fresh-cut lettuce at different storage times were significantly (p < 0.05) higher for those from the forward processing facility than those from the source processing facility. Microbiota on whole-head lettuce and on fresh-cut lettuce showed differential shifting after lettuce being subjected to source or forward processing, and after product storage. Consistent with the length of pre-processing delays between harvest and processing, the lettuce quality scores of source-processed romaine lettuce, especially at late stages of 2-week storage, was significantly higher than of forward-processed product (p < 0.05).

Growth assessment of Salmonella enterica multi-serovar populations in poultry rinsates with commonly used enrichment and plating media

Isolation of Salmonella from enrichment cultures of food or environmental samples is a complicated process. Numerous factors including fitness in various selective enrichment media, relative starting concentrations in pre-enrichment, and competition among multi-serovar populations and associated natural microflora, come together to determine which serovars are identified from a given sample. A recently developed approach for assessing the relative abundance (RA) of multi-serovar Salmonella populations (CRISPR-SeroSeq or Deep Serotyping, DST) is providing new insight into how these factors impact the serovars observed, especially when different selective enrichment methods are used to identify Salmonella from a primary enrichment sample. To illustrate this, we examined Salmonella-positive poultry pre-enrichment samples through the selective enrichment process in Tetrathionate (TT) and Rappaport Vassiliadis (RVS) broths and assessed recovery of serovars with each medium. We observed the RA of serovars detected post selective enrichment varied depending on the medium used, initial concentration, and competitive fitness factors, all which could result in minority serovars in pre-enrichment becoming dominant serovars post selective enrichment. The data presented provide a greater understanding of culture biases and lays the groundwork for investigations into robust enrichment and plating media combinations for detecting Salmonella serovars of greater concern for human health.

Applied microbiology of the phyllosphere

The phyllosphere, or plant leaf surface, represents a microbial ecosystem of considerable size, holding extraordinary biodiversity and enormous potential for the discovery of new products, tools, and applications in biotechnology, agriculture, medicine, and elsewhere. This mini-review highlights the applied microbiology of the phyllosphere as an original field of study concerning itself with the genes, gene products, natural compounds, and traits that underlie phyllosphere-specific adaptations and services that have commercial and economic value for current or future innovation. Examples include plant-growth-promoting and disease-suppressive phyllobacteria, probiotics and fermented foods that support human health, as well as microbials that remedy foliar contamination with airborne pollutants, residual pesticides, or plastics. Phyllosphere microbes promote plant biomass conversion into compost, renewable energy, animal feed, or fiber. They produce foodstuffs such as thickening agents and sugar substitutes, industrial-grade biosurfactants, novel antibiotics and cancer drugs, as well as enzymes used as food additives or freezing agents. Furthermore, new developments in DNA sequence-based profiling of leaf-associated microbial communities allow for surveillance approaches in the context of food safety and security, for example, to detect enteric human pathogens on leafy greens, predict plant disease outbreaks, and intercept plant pathogens and pests on internationally traded goods. KEY POINTS: • Applied phyllosphere microbiology concerns leaf-specific adaptations for economic value • Phyllobioprospecting searches the phyllosphere microbiome for product development • Phyllobiomonitoring tracks phyllosphere microbial profiles for early risk detection.

Light Intensity Modulates the Functional Composition of Leaf Metabolite Groups and Phyllosphere Prokaryotic Community in Garden Lettuce (Lactuca sativa L.) Plants at the Vegetative Stage

Light intensity primarily drives plant growth and morphogenesis, whereas the ecological impact of light intensity on the phyllosphere (leaf surface and endosphere) microbiome is poorly understood. In this study, garden lettuce (Lactuca sativa L.) plants were grown under low, medium, and high light intensities. High light intensity remarkably induced the leaf contents of soluble proteins and chlorophylls, whereas it reduced the contents of leaf nitrate. In comparison, medium light intensity exhibited the highest contents of soluble sugar, cellulose, and free amino acids. Meanwhile, light intensity resulted in significant changes in the composition of functional genes but not in the taxonomic compositions of the prokaryotic community (bacteria and archaea) in the phyllosphere. Notably, garden lettuce plants under high light intensity treatment harbored more sulfur-cycling mdh and carbon-cycling glyA genes than under low light intensity, both of which were among the 20 most abundant prokaryotic genes in the leaf phyllosphere. Furthermore, the correlations between prokaryotic functional genes and lettuce leaf metabolite groups were examined to disclose their interactions under varying light intensities. The relative abundance of the mdh gene was positively correlated with leaf total chlorophyll content but negatively correlated with leaf nitrate content. In comparison, the relative abundance of the glyA gene was positively correlated with leaf total chlorophyll and carotenoids. Overall, this study revealed that the functional composition of the phyllosphere prokaryotic community and leaf metabolite groups were tightly linked in response to changing light intensities. These findings provided novel insights into the interactions between plants and prokaryotic microbes in indoor farming systems, which will help optimize environmental management in indoor farms and harness beneficial plant-microbe relationships for crop production.

Comparison of Phenotype Nutritional Profiles and Phosphate Metabolism Genes in Four Serovars of Salmonella enterica from Water Sources

The surveillance of foods for Salmonella is hindered by bias in common enrichment media where serovars implicated in human illness are outgrown by less virulent serovars. We examined four Salmonella serovars, two common in human illness (Enteritidis and Typhimurium) and two that often dominate enrichments (Give and Kentucky), for factors that might influence culture bias. The four serovars had similar growth kinetics in Tryptic Soy Broth and Buffered Peptone Water. Phenotype microarray analysis with 950 chemical substrates to assess nutrient utilization and stress resistance revealed phenotype differences between serovars. Strains of S. Enteritidis had better utilization of plant-derived sugars such as xylose, mannitol, rhamnose, and fructose, while S. Typhimurium strains were able to metabolize tagatose. Strains of S. Kentucky used more compounds as phosphorus sources and grew better with inorganic phosphate as the sole phosphorus source. The sequences of nine genes involved in phosphate metabolism were compared, and there were differences between serovars in the catalytic ATP-binding domain of the histidine kinase phoR. Analysis of the predicted PhoR amino acid sequences from additional Salmonella genomes indicated a conservation of sequences each within the Typhimurium, Give, and Enteritidis serovars. However, three different PhoR versions were observed in S. Kentucky.

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.