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  A Human Interactome in Three Quantitative Dimensions Organized by Stoichiometries and Abundances

Hein, M. Y., Hubner, N. C., Poser, I., Cox, J., Nagaraj, N., Toyoda, Y., et al. (2015). A Human Interactome in Three Quantitative Dimensions Organized by Stoichiometries and Abundances. CELL, 163(3), 712-723. doi:10.1016/j.cell.2015.09.053.

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 Creators:
Hein, Marco Y.1, Author           
Hubner, Nina C.1, Author           
Poser, Ina2, Author
Cox, Jürgen3, Author           
Nagaraj, Nagarjuna1, Author           
Toyoda, Yusuke2, Author
Gak, Igor A.2, Author
Weisswange, Ina2, Author
Mansfeld, Jörg2, Author
Buchholz, Frank2, Author
Hyman, Anthony A.2, Author
Mann, Matthias1, Author           
Affiliations:
1Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565159              
2external, ou_persistent22              
3Cox, Jürgen / Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society, ou_2063284              

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Free keywords: PROTEIN INTERACTION NETWORK; MASS-SPECTROMETRY; SACCHAROMYCES-CEREVISIAE; BAC TRANSGENEOMICS; COPY-NUMBER; SCALE MAP; COMPLEXES; REVEALS; YEAST; ACCURATE
 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 measure 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.

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Language(s): eng - English
 Dates: 2015
 Publication Status: Issued
 Pages: 12
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Degree: -

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Title: CELL
Source Genre: Journal
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Publ. Info: 600 TECHNOLOGY SQUARE, 5TH FLOOR, CAMBRIDGE, MA 02139 USA : CELL PRESS
Pages: - Volume / Issue: 163 (3) Sequence Number: - Start / End Page: 712 - 723 Identifier: ISSN: 0092-8674