Impact of Biotic and Abiotic Factors on Listeria monocytogenes, Salmonella enterica, and Enterohemorrhagic Escherichia coli in Agricultural Soil Extracts

被引:0
作者
Sharma, Dimple [1 ]
Kraft, Autumn L. [2 ]
Owade, Joshua O. [1 ,3 ]
Milicevic, Mateja [3 ]
Yi, Jiyoon [3 ]
Bergholz, Teresa M. [1 ]
机构
[1] Michigan State Univ, Dept Food Sci & Human Nutr, E Lansing, MI 48824 USA
[2] North Dakota State Univ, Dept Microbiol Sci, Fargo, ND 58105 USA
[3] Michigan State Univ, Dept Biosyst & Agr Engn, E Lansing, MI 48824 USA
基金
美国食品与农业研究所;
关键词
soil extracts; Listeria monocytogenes; Salmonella enterica; enterohemorrhagic Escherichia coli; native microbiome; SURVIVAL; O157/H7; WATER; SPP;
D O I
10.3390/microorganisms12071498
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Outbreaks of Enterohemorrhagic Escherichia coli (EHEC), Salmonella enterica, and Listeria monocytogenes linked to fresh produce consumption pose significant food safety concerns. These pathogens can contaminate pre-harvest produce through various routes, including contaminated water. Soil physicochemical properties and flooding can influence pathogen survival in soils. We investigated survival of EHEC, S. enterica, and L. monocytogenes in soil extracts designed to represent soils with stagnant water. We hypothesized pathogen survival would be influenced by soil extract nutrient levels and the presence of native microbes. A chemical analysis revealed higher levels of total nitrogen, phosphorus, and carbon in high-nutrient soil extracts compared to low-nutrient extracts. Pathogen survival was enhanced in high-nutrient, sterile soil extracts, while the presence of native microbes reduced pathogen numbers. A microbiome analysis showed greater diversity in low-nutrient soil extracts, with distinct microbial compositions between extract types. Our findings highlight the importance of soil nutrient composition and microbial dynamics in influencing pathogen behavior. Given key soil parameters, a long short-term memory model (LSTM) effectively predicted pathogen survival. Integrating these factors can aid in developing predictive models for pathogen persistence in agricultural systems. Overall, our study contributes to understanding the complex interplay in agricultural ecosystems, facilitating informed decision-making for crop production and food safety enhancement.
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页数:16
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