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Published in

American Chemical Society, Journal of Proteome Research, 10(15), p. 3929-3937, 2016

DOI: 10.1021/acs.jproteome.6b00517

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

This paper was not found in any repository; the policy of its publisher is unknown or unclear.
This paper was not found in any repository; the policy of its publisher is unknown or unclear.

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Data provided by SHERPA/RoMEO

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.