Document Detail


Identification of additional proteins in differential proteomics using protein interaction networks.
MedLine Citation:
PMID:  23386401     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In this study, we developed a novel computational approach based on protein-protein interaction networks to identify a list of proteins that might have remained undetected in differential proteomic profiling experiments. We tested our computational approach on two sets of human smooth muscle cell protein extracts that were affected differently by DNase I treatment. Differential proteomic analysis by saturation DIGE resulted in the identification of 41 human proteins. The application of our approach to these 41 input proteins consisted of four steps: (i) Compilation of a human protein-protein interaction network from public databases; (ii) calculation of interaction scores based on functional similarity; (iii) determination of a set of candidate proteins that are needed to efficiently and confidently connect the 41 input proteins; and (iv) ranking of the resulting 25 candidate proteins. Two of the three highest-ranked proteins, beta-arrestin 1, and beta-arrestin 2, were experimentally tested, revealing that their abundance levels in human smooth muscle cell samples were indeed affected by DNase I treatment. These proteins had not been detected during the experimental proteomic analysis. Our study suggests that our computational approach may represent a simple, universal, and cost-effective means to identify additional proteins that remain elusive for current 2D gel-based proteomic profiling techniques.
Authors:
Frederik Gwinner; Adelina E Acosta-Martin; Ludovic Boytard; Maggy Chwastyniak; Olivia Beseme; Hervé Drobecq; Sophie Duban-Deweer; Francis Juthier; Brigitte Jude; Philippe Amouyel; Florence Pinet; Benno Schwikowski
Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Proteomics     Volume:  13     ISSN:  1615-9861     ISO Abbreviation:  Proteomics     Publication Date:  2013 Apr 
Date Detail:
Created Date:  2013-04-05     Completed Date:  2013-09-20     Revised Date:  2014-04-01    
Medline Journal Info:
Nlm Unique ID:  101092707     Medline TA:  Proteomics     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  1065-76     Citation Subset:  IM    
Copyright Information:
© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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MeSH Terms
Descriptor/Qualifier:
Cell Extracts
Cells, Cultured
Databases, Protein
Electrophoresis, Gel, Two-Dimensional
Humans
Muscle Proteins / metabolism*
Myocytes, Smooth Muscle / cytology,  metabolism
Protein Interaction Maps*
Proteomics / methods*
Reproducibility of Results
Software
Grant Support
ID/Acronym/Agency:
P41 GM103504/GM/NIGMS NIH HHS; P41 GM103504/GM/NIGMS NIH HHS; P41 RR031228/RR/NCRR NIH HHS
Chemical
Reg. No./Substance:
0/Cell Extracts; 0/Muscle Proteins
Comments/Corrections

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


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