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Toxicogenomic analysis incorporating operon-transcriptional coupling and toxicant concentration-expression response: analysis of MX-treated Salmonella

BACKGROUND: Deficiencies in microarray technology cause unwanted variation in the hybridization signal, obscuring the true measurements of intracellular transcript levels. Here we describe a general method that can improve microarray analysis of toxicant-exposed cells that uses the intrinsic power o...

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Autores principales: Ward, William O, Swartz, Carol D, Porwollik, Steffen, Warren, Sarah H, Hanley, Nancy M, Knapp, Geremy W, McClelland, Michael, DeMarini, David M
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2225428/
https://www.ncbi.nlm.nih.gov/pubmed/17925033
http://dx.doi.org/10.1186/1471-2105-8-378
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author Ward, William O
Swartz, Carol D
Porwollik, Steffen
Warren, Sarah H
Hanley, Nancy M
Knapp, Geremy W
McClelland, Michael
DeMarini, David M
author_facet Ward, William O
Swartz, Carol D
Porwollik, Steffen
Warren, Sarah H
Hanley, Nancy M
Knapp, Geremy W
McClelland, Michael
DeMarini, David M
author_sort Ward, William O
collection PubMed
description BACKGROUND: Deficiencies in microarray technology cause unwanted variation in the hybridization signal, obscuring the true measurements of intracellular transcript levels. Here we describe a general method that can improve microarray analysis of toxicant-exposed cells that uses the intrinsic power of transcriptional coupling and toxicant concentration-expression response data. To illustrate this approach, we characterized changes in global gene expression induced in Salmonella typhimurium TA100 by 3-chloro-4-(dichloromethyl)-5-hydroxy-2(5H)-furanone (MX), the primary mutagen in chlorinated drinking water. We used the co-expression of genes within an operon and the monotonic increases or decreases in gene expression relative to increasing toxicant concentration to augment our identification of differentially expressed genes beyond Bayesian-t analysis. RESULTS: Operon analysis increased the number of altered genes by 95% from the list identified by a Bayesian t-test of control to the highest concentration of MX. Monotonic analysis added 46% more genes. A functional analysis of the resulting 448 differentially expressed genes yielded functional changes beyond what would be expected from only the mutagenic properties of MX. In addition to gene-expression changes in DNA-damage response, MX induced changes in expression of genes involved in membrane transport and porphyrin metabolism, among other biological processes. The disruption of porphyrin metabolism might be attributable to the structural similarity of MX, which is a chlorinated furanone, to ligands indigenous to the porphyrin metabolism pathway. Interestingly, our results indicate that the lexA regulon in Salmonella, which partially mediates the response to DNA damage, may contain only 60% of the genes present in this regulon in E. coli. In addition, nanH was found to be highly induced by MX and contains a putative lexA regulatory motif in its regulatory region, suggesting that it may be regulated by lexA. CONCLUSION: Operon and monotonic analyses improved the determination of differentially expressed genes beyond that of Bayesian-t analysis, showing that MX alters cellular metabolism involving pathways other than DNA damage. Because co-expression of similarly functioning genes also occurs in eukaryotes, this method has general applicability for improving analysis of toxicogenomic data.
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spelling pubmed-22254282008-02-03 Toxicogenomic analysis incorporating operon-transcriptional coupling and toxicant concentration-expression response: analysis of MX-treated Salmonella Ward, William O Swartz, Carol D Porwollik, Steffen Warren, Sarah H Hanley, Nancy M Knapp, Geremy W McClelland, Michael DeMarini, David M BMC Bioinformatics Research Article BACKGROUND: Deficiencies in microarray technology cause unwanted variation in the hybridization signal, obscuring the true measurements of intracellular transcript levels. Here we describe a general method that can improve microarray analysis of toxicant-exposed cells that uses the intrinsic power of transcriptional coupling and toxicant concentration-expression response data. To illustrate this approach, we characterized changes in global gene expression induced in Salmonella typhimurium TA100 by 3-chloro-4-(dichloromethyl)-5-hydroxy-2(5H)-furanone (MX), the primary mutagen in chlorinated drinking water. We used the co-expression of genes within an operon and the monotonic increases or decreases in gene expression relative to increasing toxicant concentration to augment our identification of differentially expressed genes beyond Bayesian-t analysis. RESULTS: Operon analysis increased the number of altered genes by 95% from the list identified by a Bayesian t-test of control to the highest concentration of MX. Monotonic analysis added 46% more genes. A functional analysis of the resulting 448 differentially expressed genes yielded functional changes beyond what would be expected from only the mutagenic properties of MX. In addition to gene-expression changes in DNA-damage response, MX induced changes in expression of genes involved in membrane transport and porphyrin metabolism, among other biological processes. The disruption of porphyrin metabolism might be attributable to the structural similarity of MX, which is a chlorinated furanone, to ligands indigenous to the porphyrin metabolism pathway. Interestingly, our results indicate that the lexA regulon in Salmonella, which partially mediates the response to DNA damage, may contain only 60% of the genes present in this regulon in E. coli. In addition, nanH was found to be highly induced by MX and contains a putative lexA regulatory motif in its regulatory region, suggesting that it may be regulated by lexA. CONCLUSION: Operon and monotonic analyses improved the determination of differentially expressed genes beyond that of Bayesian-t analysis, showing that MX alters cellular metabolism involving pathways other than DNA damage. Because co-expression of similarly functioning genes also occurs in eukaryotes, this method has general applicability for improving analysis of toxicogenomic data. BioMed Central 2007-10-09 /pmc/articles/PMC2225428/ /pubmed/17925033 http://dx.doi.org/10.1186/1471-2105-8-378 Text en Copyright © 2007 Ward 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 Research Article
Ward, William O
Swartz, Carol D
Porwollik, Steffen
Warren, Sarah H
Hanley, Nancy M
Knapp, Geremy W
McClelland, Michael
DeMarini, David M
Toxicogenomic analysis incorporating operon-transcriptional coupling and toxicant concentration-expression response: analysis of MX-treated Salmonella
title Toxicogenomic analysis incorporating operon-transcriptional coupling and toxicant concentration-expression response: analysis of MX-treated Salmonella
title_full Toxicogenomic analysis incorporating operon-transcriptional coupling and toxicant concentration-expression response: analysis of MX-treated Salmonella
title_fullStr Toxicogenomic analysis incorporating operon-transcriptional coupling and toxicant concentration-expression response: analysis of MX-treated Salmonella
title_full_unstemmed Toxicogenomic analysis incorporating operon-transcriptional coupling and toxicant concentration-expression response: analysis of MX-treated Salmonella
title_short Toxicogenomic analysis incorporating operon-transcriptional coupling and toxicant concentration-expression response: analysis of MX-treated Salmonella
title_sort toxicogenomic analysis incorporating operon-transcriptional coupling and toxicant concentration-expression response: analysis of mx-treated salmonella
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2225428/
https://www.ncbi.nlm.nih.gov/pubmed/17925033
http://dx.doi.org/10.1186/1471-2105-8-378
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