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Streamlined Analysis Schema for High-Throughput Identification of Endogenous Protein Complexes
Anna Malovannaya, Yehua Li, Yaroslava Bulynko, Sung Yun Jung, Yi Wang, Rainer B. Lanz, Bert W. O'Malley and Jun Qin
Proceedings of the National Academy of Sciences of the United States of America
Vol. 107, No. 6 (Feb. 9, 2010), pp. 2431-2436
Published by: National Academy of Sciences
Stable URL: http://www.jstor.org/stable/40536602
Page Count: 6
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Immunoprecipitation followed by mass spectrometry (IP/MS) has recently emerged as a preferred method in the analysis of protein complex components and cellular protein networks. Targeting endogenous protein complexes of higher eukaryotes, particularly in large-scale efforts, has been challenging due to cellular heterogeneity, high proteome complexity, and, compared to lower organisms, lack of efficient in-locus epitope-tagging techniques. It is further complicated by variability in nonspecific identifications and cross-reactivity of primary antibodies. Still, the study of endogenous human protein networks is highly desired despite its challenges. Here we describe a streamlined IP/MS protocol for the purification and identification of extended endogenous protein complexes. We investigate the sources of nonspecific protein binding and develop semiquantitative specificity filters that are based on peptide spectral count measurements. We also outline logical constraints for the derivation of accurate complex composition from IP/MS data and demonstrate the effectiveness of this approach by presenting our analyses of different transcriptional coregulator complexes. We show consistent purification of novel components for the Integrator complex, analyze the composition of the Mediator complex solely from our data to demonstrate the wide usability of spectral counts, and deconvolute heterogeneous HDAC1/2 networks into core complex modules and several novel subcomplex interactions.
Proceedings of the National Academy of Sciences of the United States of America © 2010 National Academy of Sciences