Proteomics

Dataset Information

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A human interactome in three quantitative dimensions organized by stoichiometries and abundances


ABSTRACT: The organization of a cell emerges from the interactions in protein networks. The interactome is critically dependent on the strengths of interactions and the cellular abundances of the connected proteins, both of which span orders of magnitude. However, these aspects have not yet been analyzed globally. Here, we have generated a library of HeLa cell lines expressing 1,125 GFP-tagged proteins under near-endogenous control, which we used as input for a next-generation interaction survey. Using quantitative proteomics, we detect specific interactions, estimate interaction stoichiometries and measures cellular abundances of interacting proteins. These three quantitative dimensions reveal that the protein network is dominated by weak, substoichiometric interactions that play a pivotal role in defining network topology. The minority of stable complexes can be identified by their unique stoichiometry signature. This study provides a rich interaction dataset connecting thousands of proteins, and introduces a framework for quantitative network analysis.

INSTRUMENT(S): LTQ Orbitrap, Q Exactive

ORGANISM(S): Homo Sapiens (human) Mus Musculus (mouse)

SUBMITTER: Mario Oroshi  

LAB HEAD: Matthias Mann

PROVIDER: PXD002815 | Pride | 2015-10-23

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
MCP_ky_0000136_0167_38_JBA.RAW Raw
MCP_ky_0000136_0168_01_JBA.RAW Raw
MCP_ky_0000136_0172_20_JBA.RAW Raw
MCP_ky_0000155_0167_12_JBA.RAW Raw
MCP_ky_0000155_0168_03_JBA.RAW Raw
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Publications


The organization of a cell emerges from the interactions in protein networks. The interactome is critically dependent on the strengths of interactions and the cellular abundances of the connected proteins, both of which span orders of magnitude. However, these aspects have not yet been analyzed globally. Here, we have generated a library of HeLa cell lines expressing 1,125 GFP-tagged proteins under near-endogenous control, which we used as input for a next-generation interaction survey. Using qu  ...[more]

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