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Architecture of transcriptional regulatory circuits is knitted over the topology of bio-molecular interaction networks.

Oliveira AP, Patil KR, Nielsen J - BMC Syst Biol (2008)

Bottom Line: Here we introduce a hypothesis-driven method that integrates bio-molecular network topology with transcriptome data, thereby allowing the identification of key biological features (Reporter Features) around which transcriptional changes are significantly concentrated.Reporter Features offer the opportunity to identify regulatory hot-spots in bio-molecular interaction networks that are significantly affected between or across conditions.Results of the Reporter Feature analysis not only provide a snapshot of the transcriptional regulatory program but also are biologically easy to interpret and provide a powerful way to generate new hypotheses.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Microbial Biotechnology, Department of Systems Biology, Technical University of Denmark, Building 223, DK-2800 Kgs, Lyngby, Denmark. apo@bio.dtu.dk

ABSTRACT

Background: Uncovering the operating principles underlying cellular processes by using 'omics' data is often a difficult task due to the high-dimensionality of the solution space that spans all interactions among the bio-molecules under consideration. A rational way to overcome this problem is to use the topology of bio-molecular interaction networks in order to constrain the solution space. Such approaches systematically integrate the existing biological knowledge with the 'omics' data.

Results: Here we introduce a hypothesis-driven method that integrates bio-molecular network topology with transcriptome data, thereby allowing the identification of key biological features (Reporter Features) around which transcriptional changes are significantly concentrated. We have combined transcriptome data with different biological networks in order to identify Reporter Gene Ontologies, Reporter Transcription Factors, Reporter Proteins and Reporter Complexes, and use this to decipher the logic of regulatory circuits playing a key role in yeast glucose repression and human diabetes.

Conclusion: Reporter Features offer the opportunity to identify regulatory hot-spots in bio-molecular interaction networks that are significantly affected between or across conditions. Results of the Reporter Feature analysis not only provide a snapshot of the transcriptional regulatory program but also are biologically easy to interpret and provide a powerful way to generate new hypotheses. Our Reporter Features analyses of yeast glucose repression and human diabetes data brings hints towards the understanding of the principles of transcriptional regulation controlling these two important and potentially closely related systems.

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Comparative ranking analysis. Each column corresponds to the three human GO networks analyzed here: the complete GO network (ALL), the GO network of up-regulated nodes only (UP) and the GO network of down-regulated nodes only (DOWN). The GO terms are colored based on scores (green: p-value < 0.01; yellow: 0.01 <p-value < 0.05; red: p-value > 0.05), and all Reporter GO terms with a p-value < 0.01 in at least one of the networks are displayed. Genes belonging to the GO terms DNA-directed RNA polymerase activity, ceramide metabolism and NADH dehydrogenase (ubiquinone) activity are mostly up-regulated in the diabetic patients, while genes belonging to the GO terms generation of precursor metabolites, mitochondrial inner membrane, TCA cycle and glycolysis are mostly down-regulated in diabetic cases.
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Figure 5: Comparative ranking analysis. Each column corresponds to the three human GO networks analyzed here: the complete GO network (ALL), the GO network of up-regulated nodes only (UP) and the GO network of down-regulated nodes only (DOWN). The GO terms are colored based on scores (green: p-value < 0.01; yellow: 0.01 <p-value < 0.05; red: p-value > 0.05), and all Reporter GO terms with a p-value < 0.01 in at least one of the networks are displayed. Genes belonging to the GO terms DNA-directed RNA polymerase activity, ceramide metabolism and NADH dehydrogenase (ubiquinone) activity are mostly up-regulated in the diabetic patients, while genes belonging to the GO terms generation of precursor metabolites, mitochondrial inner membrane, TCA cycle and glycolysis are mostly down-regulated in diabetic cases.

Mentions: An interesting analysis is to rank GO categories by descendent scores, in both up and down-regulated sub-graphs, and evaluate if there is any dominant direction of regulation (Figure 5). This analysis revealed that the subunits of the NADH-ubiquinone oxidoreductase (part of the Complex I of the mitochondrial electron transport chain) are mostly up-regulated in insulin-resistant subjects compared to the control group. But when comparing DM and FH+ subjects, diabetic patients have lower transcriptional levels of NADH-ubiquinone oxidoreductases genes, while genes encoding for cytochrome-c, ATP-synthesis coupled proton transporters, TCA cycle and glycolysis show an increased expression level relative to non-diatebetic FH+ subjects. Although it is known that in common forms of type 2 diabetes mellitus there is a reduced activity of glycolysis, TCA cycle, β-oxidation, electron transport enzymes and many mitochondrial activities [21,24], Heddi and colleagues showed that, in diabetes subjects with mitochondrial DNA mutations, there is an increase in the transcript levels of many of those genes [25]. Remarkably, Reporter GOs independently point towards the same conclusions. These findings suggest that human skeletal muscle cells attempt to compensate their genomic defects by stimulating transcription of the corresponding genes.


Architecture of transcriptional regulatory circuits is knitted over the topology of bio-molecular interaction networks.

Oliveira AP, Patil KR, Nielsen J - BMC Syst Biol (2008)

Comparative ranking analysis. Each column corresponds to the three human GO networks analyzed here: the complete GO network (ALL), the GO network of up-regulated nodes only (UP) and the GO network of down-regulated nodes only (DOWN). The GO terms are colored based on scores (green: p-value < 0.01; yellow: 0.01 <p-value < 0.05; red: p-value > 0.05), and all Reporter GO terms with a p-value < 0.01 in at least one of the networks are displayed. Genes belonging to the GO terms DNA-directed RNA polymerase activity, ceramide metabolism and NADH dehydrogenase (ubiquinone) activity are mostly up-regulated in the diabetic patients, while genes belonging to the GO terms generation of precursor metabolites, mitochondrial inner membrane, TCA cycle and glycolysis are mostly down-regulated in diabetic cases.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2268660&req=5

Figure 5: Comparative ranking analysis. Each column corresponds to the three human GO networks analyzed here: the complete GO network (ALL), the GO network of up-regulated nodes only (UP) and the GO network of down-regulated nodes only (DOWN). The GO terms are colored based on scores (green: p-value < 0.01; yellow: 0.01 <p-value < 0.05; red: p-value > 0.05), and all Reporter GO terms with a p-value < 0.01 in at least one of the networks are displayed. Genes belonging to the GO terms DNA-directed RNA polymerase activity, ceramide metabolism and NADH dehydrogenase (ubiquinone) activity are mostly up-regulated in the diabetic patients, while genes belonging to the GO terms generation of precursor metabolites, mitochondrial inner membrane, TCA cycle and glycolysis are mostly down-regulated in diabetic cases.
Mentions: An interesting analysis is to rank GO categories by descendent scores, in both up and down-regulated sub-graphs, and evaluate if there is any dominant direction of regulation (Figure 5). This analysis revealed that the subunits of the NADH-ubiquinone oxidoreductase (part of the Complex I of the mitochondrial electron transport chain) are mostly up-regulated in insulin-resistant subjects compared to the control group. But when comparing DM and FH+ subjects, diabetic patients have lower transcriptional levels of NADH-ubiquinone oxidoreductases genes, while genes encoding for cytochrome-c, ATP-synthesis coupled proton transporters, TCA cycle and glycolysis show an increased expression level relative to non-diatebetic FH+ subjects. Although it is known that in common forms of type 2 diabetes mellitus there is a reduced activity of glycolysis, TCA cycle, β-oxidation, electron transport enzymes and many mitochondrial activities [21,24], Heddi and colleagues showed that, in diabetes subjects with mitochondrial DNA mutations, there is an increase in the transcript levels of many of those genes [25]. Remarkably, Reporter GOs independently point towards the same conclusions. These findings suggest that human skeletal muscle cells attempt to compensate their genomic defects by stimulating transcription of the corresponding genes.

Bottom Line: Here we introduce a hypothesis-driven method that integrates bio-molecular network topology with transcriptome data, thereby allowing the identification of key biological features (Reporter Features) around which transcriptional changes are significantly concentrated.Reporter Features offer the opportunity to identify regulatory hot-spots in bio-molecular interaction networks that are significantly affected between or across conditions.Results of the Reporter Feature analysis not only provide a snapshot of the transcriptional regulatory program but also are biologically easy to interpret and provide a powerful way to generate new hypotheses.

View Article: PubMed Central - HTML - PubMed

Affiliation: Center for Microbial Biotechnology, Department of Systems Biology, Technical University of Denmark, Building 223, DK-2800 Kgs, Lyngby, Denmark. apo@bio.dtu.dk

ABSTRACT

Background: Uncovering the operating principles underlying cellular processes by using 'omics' data is often a difficult task due to the high-dimensionality of the solution space that spans all interactions among the bio-molecules under consideration. A rational way to overcome this problem is to use the topology of bio-molecular interaction networks in order to constrain the solution space. Such approaches systematically integrate the existing biological knowledge with the 'omics' data.

Results: Here we introduce a hypothesis-driven method that integrates bio-molecular network topology with transcriptome data, thereby allowing the identification of key biological features (Reporter Features) around which transcriptional changes are significantly concentrated. We have combined transcriptome data with different biological networks in order to identify Reporter Gene Ontologies, Reporter Transcription Factors, Reporter Proteins and Reporter Complexes, and use this to decipher the logic of regulatory circuits playing a key role in yeast glucose repression and human diabetes.

Conclusion: Reporter Features offer the opportunity to identify regulatory hot-spots in bio-molecular interaction networks that are significantly affected between or across conditions. Results of the Reporter Feature analysis not only provide a snapshot of the transcriptional regulatory program but also are biologically easy to interpret and provide a powerful way to generate new hypotheses. Our Reporter Features analyses of yeast glucose repression and human diabetes data brings hints towards the understanding of the principles of transcriptional regulation controlling these two important and potentially closely related systems.

Show MeSH
Related in: MedlinePlus