|Ibekwe, Abasiofiok - Mark
|MA, JINCAI - University Of California
|CROWLEY, DAVID - University Of California
|YANG, CHING-HONG - University Of Wisconsin
|JOHNSON, ALEXIS - Ayasdi, Inc
|PETROSSIAN, TANYA - Ayasdi, Inc
|LUM, PEK - Ayasdi, Inc
Submitted to: Frontiers in Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/4/2016
Publication Date: 9/4/2016
Citation: Ibekwe, A.M., Ma, J., Crowley, D.E., Yang, C., Johnson, A.M., Petrossian, T.C., Lum, P.Y. 2016. Topological data analysis of Escherichia coli O157:H7 and non-O157 survival in soils. Frontiers in Microbiology. 1-11. doi: 10.3389/fcimb.2014.00122.
Interpretive Summary: Shiga toxin producing Escherichia coli are pathogens that are known to cause many outbreaks of foodborne infections in human. Hundreds of Shiga toxin producing strains have been isolated from healthy animals, infected humans, and contaminated foods. Although E. coli O157:H7 is reported to be the most predominant Shiga toxin producing E. coli in the United States, more than 200 non-O157 serotypes have been identified in animals or foods. In this study, we applied topological methods to study complex high dimensional data sets by extracting shapes (patterns) and obtaining the relationship structure of E. coli O157 and non-O157 survival in 32 soils (16 organic and 16 conventionally managed soils) from California (CA) and Arizona (AZ) with a multi-resolution output. Our method permits the analysis of individual data sets as well as the analysis of relationships between related data sets obtained using different methodologies. Using six E. coli O157 and non-O157, the analysis method reconstructed how different strains persist in soils at different rates and revealed a complex interaction between E. coli strains, survival, microbial communities, and soil parameters. This information will be of interest to growers, shippers, packers, as well as food and feed processors and researchers.
Technical Abstract: Shiga toxin-producing E. coli O157:H7 and non-O157 have been implicated in many foodborne illnesses caused by the consumption of contaminated fresh produce. However, data on their persistence in major fresh produce-growing soils are limited due to the complexity in datasets generated from different environmental variables and bacterial taxa. There is a continuing need to distinguish the various environmental variables and different bacterial groups to understand the relationships among these factors and the pathogen survival. Using the Ayasdi Iris platform, which employs Topological Data Analysis (TDA) methods, we reconstructed the relationship structure of E. coli O157 and non-O157 survival in 32 soils (16 organic and 16 conventionally managed soils) from California (CA) and Arizona (AZ) with a multi-resolution output. The statistical method combines principal component and cluster analyses to produce a geometric representation of complex data sets. Kolmogorov-Smirnov test provided correlation analysis between soil properties and survival time. Network analysis showed that Shiga toxin negative strain E. coli O157:H7 4554 survived significantly longer in comparison to E. coli O157:H7 EDL933, while the survival time of E. coli O157:NM was comparable to that of E. coli O157:H7 strain 933in all soil tested. Two non-O157 strains, E. coli O26:H11 and E. coli O103:H2 survived much longer than E. coli O91:H21 and the three E. coli O157. Different strains persist in soils at different rates as the Kolmogorov-Smirnov test of survival time and soil properties revealed a complex interaction between E. coli strains, survival, microbial communities, and soil parameters.