Your browser doesn't support javascript.
loading
PIPINO: A Software Package to Facilitate the Identification of Protein-Protein Interactions from Affinity Purification Mass Spectrometry Data.
Kalkhof, Stefan; Schildbach, Stefan; Blumert, Conny; Horn, Friedemann; von Bergen, Martin; Labudde, Dirk.
Affiliation
  • Kalkhof S; 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.
  • Schildbach S; Department of Applied Computer Sciences & Biosciences, University of Applied Sciences Mittweida, 09648 Mittweida, Germany.
  • Blumert C; Institute of Clinical Immunology, Medical Faculty, University of Leipzig, 04103 Leipzig, Germany; Fraunhofer Institute for Cell Therapy and Immunology, 04103 Leipzig, Germany.
  • Horn F; Institute of Clinical Immunology, Medical Faculty, University of Leipzig, 04103 Leipzig, Germany; Fraunhofer Institute for Cell Therapy and Immunology, 04103 Leipzig, Germany.
  • von Bergen M; 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.
  • Labudde D; Department of Applied Computer Sciences & Biosciences, University of Applied Sciences Mittweida, 09648 Mittweida, Germany.
Biomed Res Int ; 2016: 2891918, 2016.
Article in En | MEDLINE | ID: mdl-26966684
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Proteins / Protein Interaction Mapping / STAT1 Transcription Factor Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Biomed Res Int Year: 2016 Document type: Article Affiliation country: Germany Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Proteins / Protein Interaction Mapping / STAT1 Transcription Factor Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Biomed Res Int Year: 2016 Document type: Article Affiliation country: Germany Country of publication: United States