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Topological data analysis of Escherichia coli O157:H7 and non-O157 survival in soils

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 soils are limited due to the complexity in datasets generated from different environmental variables and...

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Autores principales: Ibekwe, Abasiofiok M., Ma, Jincai, Crowley, David E., Yang, Ching-Hong, Johnson, Alexis M., Petrossian, Tanya C., Lum, Pek Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4155871/
https://www.ncbi.nlm.nih.gov/pubmed/25250242
http://dx.doi.org/10.3389/fcimb.2014.00122
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author Ibekwe, Abasiofiok M.
Ma, Jincai
Crowley, David E.
Yang, Ching-Hong
Johnson, Alexis M.
Petrossian, Tanya C.
Lum, Pek Y.
author_facet Ibekwe, Abasiofiok M.
Ma, Jincai
Crowley, David E.
Yang, Ching-Hong
Johnson, Alexis M.
Petrossian, Tanya C.
Lum, Pek Y.
author_sort Ibekwe, Abasiofiok M.
collection PubMed
description 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 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 an approach called Topological Data Analysis (TDA); 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. In our study, we took a community approach based on total soil microbiome to study community level survival and examining the network of the community as a whole and the relationship between its topology and biological processes. TDA produces a geometric representation of complex data sets. Network analysis showed that Shiga toxin negative strain E. coli O157:H7 4554 survived significantly longer in comparison to E. coli O157:H7 EDL 933, while the survival time of E. coli O157:NM was comparable to that of E. coli O157:H7 EDL 933 in all of the tested soils. Two non-O157 strains, E. coli O26:H11 and E. coli O103:H2 survived much longer than E. coli O91:H21 and the three strains of E. coli O157. We show that there are complex interactions between E. coli strain survival, microbial community structures, and soil parameters.
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spelling pubmed-41558712014-09-23 Topological data analysis of Escherichia coli O157:H7 and non-O157 survival in soils Ibekwe, Abasiofiok M. Ma, Jincai Crowley, David E. Yang, Ching-Hong Johnson, Alexis M. Petrossian, Tanya C. Lum, Pek Y. Front Cell Infect Microbiol Microbiology 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 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 an approach called Topological Data Analysis (TDA); 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. In our study, we took a community approach based on total soil microbiome to study community level survival and examining the network of the community as a whole and the relationship between its topology and biological processes. TDA produces a geometric representation of complex data sets. Network analysis showed that Shiga toxin negative strain E. coli O157:H7 4554 survived significantly longer in comparison to E. coli O157:H7 EDL 933, while the survival time of E. coli O157:NM was comparable to that of E. coli O157:H7 EDL 933 in all of the tested soils. Two non-O157 strains, E. coli O26:H11 and E. coli O103:H2 survived much longer than E. coli O91:H21 and the three strains of E. coli O157. We show that there are complex interactions between E. coli strain survival, microbial community structures, and soil parameters. Frontiers Media S.A. 2014-09-05 /pmc/articles/PMC4155871/ /pubmed/25250242 http://dx.doi.org/10.3389/fcimb.2014.00122 Text en Copyright © 2014 Ibekwe, Ma, Crowley, Yang, Johnson, Petrossian and Lum. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Ibekwe, Abasiofiok M.
Ma, Jincai
Crowley, David E.
Yang, Ching-Hong
Johnson, Alexis M.
Petrossian, Tanya C.
Lum, Pek Y.
Topological data analysis of Escherichia coli O157:H7 and non-O157 survival in soils
title Topological data analysis of Escherichia coli O157:H7 and non-O157 survival in soils
title_full Topological data analysis of Escherichia coli O157:H7 and non-O157 survival in soils
title_fullStr Topological data analysis of Escherichia coli O157:H7 and non-O157 survival in soils
title_full_unstemmed Topological data analysis of Escherichia coli O157:H7 and non-O157 survival in soils
title_short Topological data analysis of Escherichia coli O157:H7 and non-O157 survival in soils
title_sort topological data analysis of escherichia coli o157:h7 and non-o157 survival in soils
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4155871/
https://www.ncbi.nlm.nih.gov/pubmed/25250242
http://dx.doi.org/10.3389/fcimb.2014.00122
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