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Intelligent mixing of proteomes for elimination of false positives in affinity purification-mass spectrometry

Sven Eyckerman (UGent) , Francis Impens (UGent) , Emmy Van Quickelberghe (UGent) , Noortje Samyn (UGent) , Giel Vandemoortele (UGent) , Delphine De Sutter (UGent) , Jan Tavernier (UGent) and Kris Gevaert (UGent)
(2016) JOURNAL OF PROTEOME RESEARCH. 15(10). p.3929-3937
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Abstract
Protein complexes are essential in all organizational and functional aspects of the cell. Different strategies currently exist for analyzing such protein complexes by mass spectrometry, including affinity purification (AP-MS) and proximal labeling-based strategies. However, the high sensitivity of current mass spectrometers typically results in extensive protein lists mainly consisting of nonspecifically copurified proteins. Finding the true positive interactors in these lists remains highly challenging. Here, we report a powerful design based on differential labeling with stable isotopes combined with nonequal mixing of control and experimental samples to discover bona fide interaction partners in AP-MS experiments. We apply this intelligent mixing of proteomes (iMixPro) concept to overexpression experiments for RAF1, RNF41, and TANK and also to engineered cell lines expressing epitope-tagged endogenous PTPN14, JIP3, and IQGAP1. For all baits, we confirmed known interactions and found a number of novel interactions. The results for RNF41 and TANK were compared to a classical affinity purification experiment, which demonstrated the efficiency and specificity of the iMixPro approach.
Keywords
SYSTEM, DESIGN, KINASE, ORGANIZATION, COMPLEXES, IDENTIFICATION, HUMAN INTERACTOME, PROTEIN-INTERACTION, SILAC, protein complex, affinity purification-mass spectrometry, RECEPTOR, NETWORK

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Chicago
Eyckerman, Sven, Francis Impens, Emmy Van Quickelberghe, Noortje Samyn, Giel Vandemoortele, Delphine De Sutter, Jan Tavernier, and Kris Gevaert. 2016. “Intelligent Mixing of Proteomes for Elimination of False Positives in Affinity Purification-mass Spectrometry.” Journal of Proteome Research 15 (10): 3929–3937.
APA
Eyckerman, S., Impens, F., Van Quickelberghe, E., Samyn, N., Vandemoortele, G., De Sutter, D., Tavernier, J., et al. (2016). Intelligent mixing of proteomes for elimination of false positives in affinity purification-mass spectrometry. JOURNAL OF PROTEOME RESEARCH, 15(10), 3929–3937.
Vancouver
1.
Eyckerman S, Impens F, Van Quickelberghe E, Samyn N, Vandemoortele G, De Sutter D, et al. Intelligent mixing of proteomes for elimination of false positives in affinity purification-mass spectrometry. JOURNAL OF PROTEOME RESEARCH. 2016;15(10):3929–37.
MLA
Eyckerman, Sven, Francis Impens, Emmy Van Quickelberghe, et al. “Intelligent Mixing of Proteomes for Elimination of False Positives in Affinity Purification-mass Spectrometry.” JOURNAL OF PROTEOME RESEARCH 15.10 (2016): 3929–3937. Print.
@article{8173314,
  abstract     = {Protein complexes are essential in all organizational and functional aspects of the cell. Different strategies currently exist for analyzing such protein complexes by mass spectrometry, including affinity purification (AP-MS) and proximal labeling-based strategies. However, the high sensitivity of current mass spectrometers typically results in extensive protein lists mainly consisting of nonspecifically copurified proteins. Finding the true positive interactors in these lists remains highly challenging. Here, we report a powerful design based on differential labeling with stable isotopes combined with nonequal mixing of control and experimental samples to discover bona fide interaction partners in AP-MS experiments. We apply this intelligent mixing of proteomes (iMixPro) concept to overexpression experiments for RAF1, RNF41, and TANK and also to engineered cell lines expressing epitope-tagged endogenous PTPN14, JIP3, and IQGAP1. For all baits, we confirmed known interactions and found a number of novel interactions. The results for RNF41 and TANK were compared to a classical affinity purification experiment, which demonstrated the efficiency and specificity of the iMixPro approach.},
  author       = {Eyckerman, Sven and Impens, Francis and Van Quickelberghe, Emmy and Samyn, Noortje and Vandemoortele, Giel and De Sutter, Delphine and Tavernier, Jan and Gevaert, Kris},
  issn         = {1535-3893},
  journal      = {JOURNAL OF PROTEOME RESEARCH},
  keyword      = {SYSTEM,DESIGN,KINASE,ORGANIZATION,COMPLEXES,IDENTIFICATION,HUMAN INTERACTOME,PROTEIN-INTERACTION,SILAC,protein complex,affinity purification-mass spectrometry,RECEPTOR,NETWORK},
  language     = {eng},
  number       = {10},
  pages        = {3929--3937},
  title        = {Intelligent mixing of proteomes for elimination of false positives in affinity purification-mass spectrometry},
  url          = {http://dx.doi.org/10.1021/acs.jproteome.6b00517},
  volume       = {15},
  year         = {2016},
}

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