Ligand-induced clustering of type I cytokine receptor subunits leads to trans-phosphorylation and activation of associated cytosolic janus kinases (JAKs). In turn, JAKs phosphorylate tyrosine residues in the receptor tails, leading to recruitment and activation of signalling molecules1. Among these, signal transducers and activators of transcription (STATs) are important in the direct transmission of signals to the nucleus2. Here, we show that incorporation of an interaction trap in a signalling-deficient receptor allows the identification of protein–protein interactions, using a STAT-dependent complementation assay. Mammalian protein–protein interaction trap (MAPPIT) adds to existing yeast two-hybrid procedures, as originally explored by Fields and Song3, and permits the detection of both modification-independent and of phosphorylation-dependent interactions in intact human cells. We also demonstrate that MAPPIT can be used to screen complex complementary DNA libraries, and using this approach, we identify cytokine-inducible SH2-containing protein (CIS) and suppressor of cytokine signalling-2 (SOCS-2) as interaction partners of the phosphotyrosine 402 (Tyr 402)-binding motif in the erythropoietin receptor (EpoR). Importantly, this approach places protein–protein interactions in their normal physiological context, and is especially applicable to the in situ analysis of signal transduction pathways.
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We thank G. Nolan and S. Kinoshita for the pBMN-Z retroviral vector, the mEcoR expression vector pM5Neo and the ΦNX-Eco packaging cell line, N. Nicola for Flag-tagged SOCS vectors, and S. Nordeen for pXP2d2. We are indebted to T. Van den Driessche and M. Chuah Khim for help in setting up the retroviral system, D. Lavens for the construction of the pXP2d2-rPAP1-luci reporter vector, and D. Defeau and M. Goethals for technical assistance. We thank D. Broekaert for critical reading of the manuscript and D. Iserentant and R. Dekeyser for suggestions. S.E. is a fellow with the Vlaams Instituut voor de Bevordering van het Wetenschappelijk-Technologisch Onderzoek in de Industrie (IWT). A.V. was supported by a grant from the Geconcerteerde Onderzoeksacties (GOA 12051296). This work was funded by the Fonds voor Wetenschappelijk Onderzoek Vlaanderen (FWO-V G.014999) and by the Interuniversity Attractions Poles (IUAP P4/23).
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Theoretical Biology and Medical Modelling (2016)