Document Detail

Network reconstruction and systems analysis of cardiac myocyte hypertrophy signaling.
MedLine Citation:
PMID:  23091058     Owner:  NLM     Status:  MEDLINE    
Cardiac hypertrophy is managed by a dense web of signaling pathways with many pathways influencing myocyte growth. A quantitative understanding of the contributions of individual pathways and their interactions is needed to better understand hypertrophy signaling and to develop more effective therapies for heart failure. We developed a computational model of the cardiac myocyte hypertrophy signaling network to determine how the components and network topology lead to differential regulation of transcription factors, gene expression, and myocyte size. Our computational model of the hypertrophy signaling network contains 106 species and 193 reactions, integrating 14 established pathways regulating cardiac myocyte growth. 109 of 114 model predictions were validated using published experimental data testing the effects of receptor activation on transcription factors and myocyte phenotypic outputs. Network motif analysis revealed an enrichment of bifan and biparallel cross-talk motifs. Sensitivity analysis was used to inform clustering of the network into modules and to identify species with the greatest effects on cell growth. Many species influenced hypertrophy, but only a few nodes had large positive or negative influences. Ras, a network hub, had the greatest effect on cell area and influenced more species than any other protein in the network. We validated this model prediction in cultured cardiac myocytes. With this integrative computational model, we identified the most influential species in the cardiac hypertrophy signaling network and demonstrate how different levels of network organization affect myocyte size, transcription factors, and gene expression.
Karen A Ryall; David O Holland; Kyle A Delaney; Matthew J Kraeutler; Audrey J Parker; Jeffrey J Saucerman
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2012-10-22
Journal Detail:
Title:  The Journal of biological chemistry     Volume:  287     ISSN:  1083-351X     ISO Abbreviation:  J. Biol. Chem.     Publication Date:  2012 Dec 
Date Detail:
Created Date:  2012-12-11     Completed Date:  2013-02-12     Revised Date:  2013-12-12    
Medline Journal Info:
Nlm Unique ID:  2985121R     Medline TA:  J Biol Chem     Country:  United States    
Other Details:
Languages:  eng     Pagination:  42259-68     Citation Subset:  IM    
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MeSH Terms
Cardiomegaly / metabolism*,  physiopathology*
Computer Simulation*
Gene Expression Regulation
Models, Cardiovascular*
Muscle Proteins / metabolism
Myocytes, Cardiac / metabolism*,  pathology
Rats, Sprague-Dawley
Signal Transduction*
Grant Support
Reg. No./Substance:
0/Muscle Proteins

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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