RapamycinFungusV1, Main, Exploration, bibRecord, 000C99

Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

Identifieur interne : 000C99 ( Main/Exploration ); précédent : 000C98; suivant : 000D00

Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

Auteurs : Bader Al-Anzi [États-Unis] ; Patrick Arpp [États-Unis] ; Sherif Gerges [États-Unis] ; Christopher Ormerod [États-Unis] ; Noah Olsman [États-Unis] ; Kai Zinn [États-Unis]

Source :

PLoS computational biology [ 1553-7358 ] ; 2015.

RBID : pubmed:26020510

Descripteurs français

English descriptors

KwdEn :
- Algorithms (MeSH), Cluster Analysis (MeSH), Computational Biology (MeSH), Computer Simulation (MeSH), Fatty Acids (chemistry), Gene Deletion (MeSH), MAP Kinase Signaling System (MeSH), Models, Genetic (MeSH), Models, Theoretical (MeSH), Mutation (MeSH), Phenotype (MeSH), Proteins (chemistry), Proteome (MeSH), Reproducibility of Results (MeSH), Saccharomyces cerevisiae (chemistry), Sirolimus (chemistry), Software (MeSH), Systems Biology (MeSH).
MESH :
- chemical , chemistry : Fatty Acids, Proteins, Sirolimus.
- chemistry : Saccharomyces cerevisiae.
- Algorithms, Cluster Analysis, Computational Biology, Computer Simulation, Gene Deletion, MAP Kinase Signaling System, Models, Genetic, Models, Theoretical, Mutation, Phenotype, Proteome, Reproducibility of Results, Software, Systems Biology.

Abstract

An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae). A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates "small-world" networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein's position within a module and to the module's relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model.

DOI: 10.1371/journal.pcbi.1004264
PubMed: 26020510
PubMed Central: PMC4447291

Affiliations:

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Le document en format XML

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<front><div type="abstract" xml:lang="en">An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae). A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates "small-world" networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein's position within a module and to the module's relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model. </div>
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	Serveur d'exploration sur la rapamycine et les champignons
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Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

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