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Bioinformatics analysis of the early inflammatory response in a rat thermal injury model

BACKGROUND: Thermal injury is among the most severe forms of trauma and its effects are both local and systemic. Response to thermal injury includes cellular protection mechanisms, inflammation, hypermetabolism, prolonged catabolism, organ dysfunction and immuno-suppression. It has been hypothesized...

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Autores principales: Yang, Eric, Maguire, Timothy, Yarmush, Martin L, Berthiaume, Francois, Androulakis, Ioannis P
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1797813/
https://www.ncbi.nlm.nih.gov/pubmed/17214898
http://dx.doi.org/10.1186/1471-2105-8-10
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author Yang, Eric
Maguire, Timothy
Yarmush, Martin L
Berthiaume, Francois
Androulakis, Ioannis P
author_facet Yang, Eric
Maguire, Timothy
Yarmush, Martin L
Berthiaume, Francois
Androulakis, Ioannis P
author_sort Yang, Eric
collection PubMed
description BACKGROUND: Thermal injury is among the most severe forms of trauma and its effects are both local and systemic. Response to thermal injury includes cellular protection mechanisms, inflammation, hypermetabolism, prolonged catabolism, organ dysfunction and immuno-suppression. It has been hypothesized that gene expression patterns in the liver will change with severe burns, thus reflecting the role the liver plays in the response to burn injury. Characterizing the molecular fingerprint (i.e., expression profile) of the inflammatory response resulting from burns may help elucidate the activated mechanisms and suggest new therapeutic intervention. In this paper we propose a novel integrated framework for analyzing time-series transcriptional data, with emphasis on the burn-induced response within the context of the rat animal model. Our analysis robustly identifies critical expression motifs, indicative of the dynamic evolution of the inflammatory response and we further propose a putative reconstruction of the associated transcription factor activities. RESULTS: Implementation of our algorithm on data obtained from an animal (rat) burn injury study identified 281 genes corresponding to 4 unique profiles. Enrichment evaluation upon both gene ontologies and transcription factors, verifies the inflammation-specific character of the selections and the rationalization of the burn-induced inflammatory response. Conducting the transcription network reconstruction and analysis, we have identified transcription factors, including AHR, Octamer Binding Proteins, Kruppel-like Factors, and cell cycle regulators as being highly important to an organism's response to burn response. These transcription factors are notable due to their roles in pathways that play a part in the gross physiological response to burn such as changes in the immune response and inflammation. CONCLUSION: Our results indicate that our novel selection/classification algorithm has been successful in selecting out genes with play an important role in thermal injury. Additionally, we have demonstrated the value of an integrative approach in identifying possible points of intervention, namely the activation of certain transcription factors that govern the organism's response.
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spelling pubmed-17978132007-02-16 Bioinformatics analysis of the early inflammatory response in a rat thermal injury model Yang, Eric Maguire, Timothy Yarmush, Martin L Berthiaume, Francois Androulakis, Ioannis P BMC Bioinformatics Methodology Article BACKGROUND: Thermal injury is among the most severe forms of trauma and its effects are both local and systemic. Response to thermal injury includes cellular protection mechanisms, inflammation, hypermetabolism, prolonged catabolism, organ dysfunction and immuno-suppression. It has been hypothesized that gene expression patterns in the liver will change with severe burns, thus reflecting the role the liver plays in the response to burn injury. Characterizing the molecular fingerprint (i.e., expression profile) of the inflammatory response resulting from burns may help elucidate the activated mechanisms and suggest new therapeutic intervention. In this paper we propose a novel integrated framework for analyzing time-series transcriptional data, with emphasis on the burn-induced response within the context of the rat animal model. Our analysis robustly identifies critical expression motifs, indicative of the dynamic evolution of the inflammatory response and we further propose a putative reconstruction of the associated transcription factor activities. RESULTS: Implementation of our algorithm on data obtained from an animal (rat) burn injury study identified 281 genes corresponding to 4 unique profiles. Enrichment evaluation upon both gene ontologies and transcription factors, verifies the inflammation-specific character of the selections and the rationalization of the burn-induced inflammatory response. Conducting the transcription network reconstruction and analysis, we have identified transcription factors, including AHR, Octamer Binding Proteins, Kruppel-like Factors, and cell cycle regulators as being highly important to an organism's response to burn response. These transcription factors are notable due to their roles in pathways that play a part in the gross physiological response to burn such as changes in the immune response and inflammation. CONCLUSION: Our results indicate that our novel selection/classification algorithm has been successful in selecting out genes with play an important role in thermal injury. Additionally, we have demonstrated the value of an integrative approach in identifying possible points of intervention, namely the activation of certain transcription factors that govern the organism's response. BioMed Central 2007-01-10 /pmc/articles/PMC1797813/ /pubmed/17214898 http://dx.doi.org/10.1186/1471-2105-8-10 Text en Copyright © 2007 Yang et al; 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 Methodology Article
Yang, Eric
Maguire, Timothy
Yarmush, Martin L
Berthiaume, Francois
Androulakis, Ioannis P
Bioinformatics analysis of the early inflammatory response in a rat thermal injury model
title Bioinformatics analysis of the early inflammatory response in a rat thermal injury model
title_full Bioinformatics analysis of the early inflammatory response in a rat thermal injury model
title_fullStr Bioinformatics analysis of the early inflammatory response in a rat thermal injury model
title_full_unstemmed Bioinformatics analysis of the early inflammatory response in a rat thermal injury model
title_short Bioinformatics analysis of the early inflammatory response in a rat thermal injury model
title_sort bioinformatics analysis of the early inflammatory response in a rat thermal injury model
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1797813/
https://www.ncbi.nlm.nih.gov/pubmed/17214898
http://dx.doi.org/10.1186/1471-2105-8-10
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