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Layered functional network analysis of gene expression in human heart failure.

Zhu W, Yang L, Du Z - PLoS ONE (2009)

Bottom Line: The characteristics of the gene expression pattern of the four layers were compared.In the extracellular and plasma membrane layers, there were more proteins encoded by down-regulated genes than by up-regulated genes, but in the other two layers, the opposite trend was found.This study illustrated that by incorporating subcellular localization information into a PPI network based analysis, one can derive greater insights into the mechanisms underlying ICM.

View Article: PubMed Central - PubMed

Affiliation: Institute of Clinical Pharmacology, The Second Affiliated Hospital of Harbin Medical University, The University Key laboratory of Hei Long Jiang Province, Heilongjiang, China.

ABSTRACT

Background: Although dilated cardiomyopathy (DCM) is a leading cause of heart failure (HF), the mechanism underlying DCM is not well understood. Previously, it has been demonstrated that an integrative analysis of gene expression and protein-protein interaction (PPI) networks can provide insights into the molecular mechanisms of various diseases. In this study we develop a systems approach by linking public available gene expression data on ischemic dilated cardiomyopathy (ICM), a main pathological form of DCM, with data from a layered PPI network. We propose that the use of a layered PPI network, as opposed to a traditional PPI network, provides unique insights into the mechanism of DCM.

Methods: Four Cytoscape plugins including BionetBuilder, NetworkAnalyzer, Cerebral and GenePro were used to establish the layered PPI network, which was based upon validated subcellular protein localization data retrieved from the HRPD and Entrez Gene databases. The DAVID function annotation clustering tool was used for gene ontology (GO) analysis.

Results: The assembled layered PPI network was divided into four layers: extracellular, plasma membrane, cytoplasm and nucleus. The characteristics of the gene expression pattern of the four layers were compared. In the extracellular and plasma membrane layers, there were more proteins encoded by down-regulated genes than by up-regulated genes, but in the other two layers, the opposite trend was found. GO analysis established that proteins encoded by up-regulated genes, reflecting significantly over-represented biological processes, were mainly located in the nucleus and cytoplasm layers, while proteins encoded by down-regulated genes were mainly located in the extracellular and plasma membrane layers. The PPI network analysis revealed that the Janus family tyrosine kinase-signal transducer and activator of transcription (Jak-STAT) signaling pathway might play an important role in the development of ICM and could be exploited as a therapeutic target of ICM. In addition, glycogen synthase kinase 3 beta (GSK3B) may also be a potential candidate target, but more evidence is required.

Conclusion: This study illustrated that by incorporating subcellular localization information into a PPI network based analysis, one can derive greater insights into the mechanisms underlying ICM.

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Related in: MedlinePlus

Layered PPI network.Red, green and blue nodes represent up-regulated, down-regulated and unchanged genes, respectively. Purple nodes represent other genes that have no corresponding transcripts in the data set.
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pone-0006288-g001: Layered PPI network.Red, green and blue nodes represent up-regulated, down-regulated and unchanged genes, respectively. Purple nodes represent other genes that have no corresponding transcripts in the data set.

Mentions: In total 1888 significantly differentially expressed genes were identified using the SAM analysis, including 1114 that were up-regulated and 774 that were down-regulated, and 3549 cardiac myocytes proteins were retrieved from the HPA. Some of the proteins did not have corresponding genes in the data set. Single nodes and small components of the PPI network initially assembled were removed and only the largest component was saved as a new PPI network, which was composed of 3316 nodes and 17810 interactions. The network was comprised of 1282 proteins that were encoded by differentially expressed genes,including 776 that were up-regulated and 506 that were down-regulated; only 266 nodes remained representing proteins that were not encoded by significant differentially expressed genes (Table 1). After importing the protein subcellular localization information, the network was re-constructed and divided into four layers: extracellular, plasma membrane, cytoplasm and nucleus (Figure 1, Annex S1). In the extracellular and plasma membrane layers, the sum of proteins encoded by down-regulated genes was greater than that encoded by up-regulated genes, but in the cytoplasm and nucleus layers, this trend was reversed.


Layered functional network analysis of gene expression in human heart failure.

Zhu W, Yang L, Du Z - PLoS ONE (2009)

Layered PPI network.Red, green and blue nodes represent up-regulated, down-regulated and unchanged genes, respectively. Purple nodes represent other genes that have no corresponding transcripts in the data set.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2712681&req=5

pone-0006288-g001: Layered PPI network.Red, green and blue nodes represent up-regulated, down-regulated and unchanged genes, respectively. Purple nodes represent other genes that have no corresponding transcripts in the data set.
Mentions: In total 1888 significantly differentially expressed genes were identified using the SAM analysis, including 1114 that were up-regulated and 774 that were down-regulated, and 3549 cardiac myocytes proteins were retrieved from the HPA. Some of the proteins did not have corresponding genes in the data set. Single nodes and small components of the PPI network initially assembled were removed and only the largest component was saved as a new PPI network, which was composed of 3316 nodes and 17810 interactions. The network was comprised of 1282 proteins that were encoded by differentially expressed genes,including 776 that were up-regulated and 506 that were down-regulated; only 266 nodes remained representing proteins that were not encoded by significant differentially expressed genes (Table 1). After importing the protein subcellular localization information, the network was re-constructed and divided into four layers: extracellular, plasma membrane, cytoplasm and nucleus (Figure 1, Annex S1). In the extracellular and plasma membrane layers, the sum of proteins encoded by down-regulated genes was greater than that encoded by up-regulated genes, but in the cytoplasm and nucleus layers, this trend was reversed.

Bottom Line: The characteristics of the gene expression pattern of the four layers were compared.In the extracellular and plasma membrane layers, there were more proteins encoded by down-regulated genes than by up-regulated genes, but in the other two layers, the opposite trend was found.This study illustrated that by incorporating subcellular localization information into a PPI network based analysis, one can derive greater insights into the mechanisms underlying ICM.

View Article: PubMed Central - PubMed

Affiliation: Institute of Clinical Pharmacology, The Second Affiliated Hospital of Harbin Medical University, The University Key laboratory of Hei Long Jiang Province, Heilongjiang, China.

ABSTRACT

Background: Although dilated cardiomyopathy (DCM) is a leading cause of heart failure (HF), the mechanism underlying DCM is not well understood. Previously, it has been demonstrated that an integrative analysis of gene expression and protein-protein interaction (PPI) networks can provide insights into the molecular mechanisms of various diseases. In this study we develop a systems approach by linking public available gene expression data on ischemic dilated cardiomyopathy (ICM), a main pathological form of DCM, with data from a layered PPI network. We propose that the use of a layered PPI network, as opposed to a traditional PPI network, provides unique insights into the mechanism of DCM.

Methods: Four Cytoscape plugins including BionetBuilder, NetworkAnalyzer, Cerebral and GenePro were used to establish the layered PPI network, which was based upon validated subcellular protein localization data retrieved from the HRPD and Entrez Gene databases. The DAVID function annotation clustering tool was used for gene ontology (GO) analysis.

Results: The assembled layered PPI network was divided into four layers: extracellular, plasma membrane, cytoplasm and nucleus. The characteristics of the gene expression pattern of the four layers were compared. In the extracellular and plasma membrane layers, there were more proteins encoded by down-regulated genes than by up-regulated genes, but in the other two layers, the opposite trend was found. GO analysis established that proteins encoded by up-regulated genes, reflecting significantly over-represented biological processes, were mainly located in the nucleus and cytoplasm layers, while proteins encoded by down-regulated genes were mainly located in the extracellular and plasma membrane layers. The PPI network analysis revealed that the Janus family tyrosine kinase-signal transducer and activator of transcription (Jak-STAT) signaling pathway might play an important role in the development of ICM and could be exploited as a therapeutic target of ICM. In addition, glycogen synthase kinase 3 beta (GSK3B) may also be a potential candidate target, but more evidence is required.

Conclusion: This study illustrated that by incorporating subcellular localization information into a PPI network based analysis, one can derive greater insights into the mechanisms underlying ICM.

Show MeSH
Related in: MedlinePlus