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Construction of predictive promoter models on the example of antibacterial response of human epithelial cells

BACKGROUND: Binding of a bacteria to a eukaryotic cell triggers a complex network of interactions in and between both cells. P. aeruginosa is a pathogen that causes acute and chronic lung infections by interacting with the pulmonary epithelial cells. We use this example for examining the ways of tri...

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Detalles Bibliográficos
Autores principales: Shelest, Ekaterina, Wingender, Edgar
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC546226/
https://www.ncbi.nlm.nih.gov/pubmed/15647113
http://dx.doi.org/10.1186/1742-4682-2-2
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author Shelest, Ekaterina
Wingender, Edgar
author_facet Shelest, Ekaterina
Wingender, Edgar
author_sort Shelest, Ekaterina
collection PubMed
description BACKGROUND: Binding of a bacteria to a eukaryotic cell triggers a complex network of interactions in and between both cells. P. aeruginosa is a pathogen that causes acute and chronic lung infections by interacting with the pulmonary epithelial cells. We use this example for examining the ways of triggering the response of the eukaryotic cell(s), leading us to a better understanding of the details of the inflammatory process in general. RESULTS: Considering a set of genes co-expressed during the antibacterial response of human lung epithelial cells, we constructed a promoter model for the search of additional target genes potentially involved in the same cell response. The model construction is based on the consideration of pair-wise combinations of transcription factor binding sites (TFBS). It has been shown that the antibacterial response of human epithelial cells is triggered by at least two distinct pathways. We therefore supposed that there are two subsets of promoters activated by each of them. Optimally, they should be "complementary" in the sense of appearing in complementary subsets of the (+)-training set. We developed the concept of complementary pairs, i.e., two mutually exclusive pairs of TFBS, each of which should be found in one of the two complementary subsets. CONCLUSIONS: We suggest a simple, but exhaustive method for searching for TFBS pairs which characterize the whole (+)-training set, as well as for complementary pairs. Applying this method, we came up with a promoter model of antibacterial response genes that consists of one TFBS pair which should be found in the whole training set and four complementary pairs. We applied this model to screening of 13,000 upstream regions of human genes and identified 430 new target genes which are potentially involved in antibacterial defense mechanisms.
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spelling pubmed-5462262005-01-30 Construction of predictive promoter models on the example of antibacterial response of human epithelial cells Shelest, Ekaterina Wingender, Edgar Theor Biol Med Model Research BACKGROUND: Binding of a bacteria to a eukaryotic cell triggers a complex network of interactions in and between both cells. P. aeruginosa is a pathogen that causes acute and chronic lung infections by interacting with the pulmonary epithelial cells. We use this example for examining the ways of triggering the response of the eukaryotic cell(s), leading us to a better understanding of the details of the inflammatory process in general. RESULTS: Considering a set of genes co-expressed during the antibacterial response of human lung epithelial cells, we constructed a promoter model for the search of additional target genes potentially involved in the same cell response. The model construction is based on the consideration of pair-wise combinations of transcription factor binding sites (TFBS). It has been shown that the antibacterial response of human epithelial cells is triggered by at least two distinct pathways. We therefore supposed that there are two subsets of promoters activated by each of them. Optimally, they should be "complementary" in the sense of appearing in complementary subsets of the (+)-training set. We developed the concept of complementary pairs, i.e., two mutually exclusive pairs of TFBS, each of which should be found in one of the two complementary subsets. CONCLUSIONS: We suggest a simple, but exhaustive method for searching for TFBS pairs which characterize the whole (+)-training set, as well as for complementary pairs. Applying this method, we came up with a promoter model of antibacterial response genes that consists of one TFBS pair which should be found in the whole training set and four complementary pairs. We applied this model to screening of 13,000 upstream regions of human genes and identified 430 new target genes which are potentially involved in antibacterial defense mechanisms. BioMed Central 2005-01-12 /pmc/articles/PMC546226/ /pubmed/15647113 http://dx.doi.org/10.1186/1742-4682-2-2 Text en Copyright © 2005 Shelest and Wingender; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Shelest, Ekaterina
Wingender, Edgar
Construction of predictive promoter models on the example of antibacterial response of human epithelial cells
title Construction of predictive promoter models on the example of antibacterial response of human epithelial cells
title_full Construction of predictive promoter models on the example of antibacterial response of human epithelial cells
title_fullStr Construction of predictive promoter models on the example of antibacterial response of human epithelial cells
title_full_unstemmed Construction of predictive promoter models on the example of antibacterial response of human epithelial cells
title_short Construction of predictive promoter models on the example of antibacterial response of human epithelial cells
title_sort construction of predictive promoter models on the example of antibacterial response of human epithelial cells
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC546226/
https://www.ncbi.nlm.nih.gov/pubmed/15647113
http://dx.doi.org/10.1186/1742-4682-2-2
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