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Biomed Res Int. 2016;2016:2891918. doi: 10.1155/2016/2891918. Epub 2016 Feb 7.

PIPINO: A Software Package to Facilitate the Identification of Protein-Protein Interactions from Affinity Purification Mass Spectrometry Data.

Author information

1
Department of Proteomics, Helmholtz Centre for Environmental Research-UFZ, 04318 Leipzig, Germany; Department of Bioanalytics, University of Applied Sciences and Arts of Coburg, 96450 Coburg, Germany.
2
Department of Applied Computer Sciences & Biosciences, University of Applied Sciences Mittweida, 09648 Mittweida, Germany.
3
Institute of Clinical Immunology, Medical Faculty, University of Leipzig, 04103 Leipzig, Germany; Fraunhofer Institute for Cell Therapy and Immunology, 04103 Leipzig, Germany.
4
Department of Proteomics, Helmholtz Centre for Environmental Research-UFZ, 04318 Leipzig, Germany; Department of Metabolomics, Helmholtz Centre for Environmental Research-UFZ, 04318 Leipzig, Germany; Department of Chemistry and Bioscience, Aalborg University, 9220 Aalborg, Denmark.

Abstract

The functionality of most proteins is regulated by protein-protein interactions. Hence, the comprehensive characterization of the interactome is the next milestone on the path to understand the biochemistry of the cell. A powerful method to detect protein-protein interactions is a combination of coimmunoprecipitation or affinity purification with quantitative mass spectrometry. Nevertheless, both methods tend to precipitate a high number of background proteins due to nonspecific interactions. To address this challenge the software Protein-Protein-Interaction-Optimizer (PIPINO) was developed to perform an automated data analysis, to facilitate the selection of bona fide binding partners, and to compare the dynamic of interaction networks. In this study we investigated the STAT1 interaction network and its activation dependent dynamics. Stable isotope labeling by amino acids in cell culture (SILAC) was applied to analyze the STAT1 interactome after streptavidin pull-down of biotagged STAT1 from human embryonic kidney 293T cells with and without activation. Starting from more than 2,000 captured proteins 30 potential STAT1 interaction partners were extracted. Interestingly, more than 50% of these were already reported or predicted to bind STAT1. Furthermore, 16 proteins were found to affect the binding behavior depending on STAT1 phosphorylation such as STAT3 or the importin subunits alpha 1 and alpha 6.

PMID:
26966684
PMCID:
PMC4761381
DOI:
10.1155/2016/2891918
[Indexed for MEDLINE]
Free PMC Article

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