Characterization of the Phospho-Adhesome by Mass Spectrometry-Based Proteomics
Integrin adhesion receptors engage with their extracellular matrix (ECM) ligands, initiating intracellular signaling pathways that regulate a range of fundamental cell functions. Protein kinases and phosphatases play an integral role in integrin adhesion-mediated signaling. However, until recently, knowledge of the phosphorylation sites regulated downstream of integrin ligation was limited to candidate-based approaches and did not support a system-level understanding of the molecular mechanisms through which ECM engagement influences cell behavior. Here, we describe a mass spectrometry (MS)-based phosphoproteomic protocol that enables the global characterization of phosphorylation-based signaling networks activated by integrin-mediated adhesion. To analyze specifically integrin-proximal signaling, the phosphoproteomic workflow involves the affinity-based isolation and analysis of integrin-associated complexes (IACs) rather than proteins solubilized from whole-cell lysates , which are typically used for global phosphoproteomic studies. The detection of phosphorylation sites from IAC proteins was optimized at various stages of the workflow, including IAC isolation, proteolytic digestion, and MS-based data acquisition strategies. The protocol permits the identification and quantification of IAC components by both Western blotting and MS. Notably, compared to phosphoproteomic analyses of cell lysates, the workflow described here enables an improved detection of phosphorylation sites from well-defined IAC proteins, including many known components of the signaling pathways activated by adhesion to the ECM.
Key wordsAdhesion complexes Affinity purification Cell adhesion Extracellular matrix Integrins Mass spectrometry Phosphoproteomics Phosphorylation Signaling Ventral membranes
This work was supported by the Wellcome Trust (grant 092015 to M.J.H.), a Wellcome Trust Institutional Strategic Support Fund award (grant 097820 to the University of Manchester) and a Biotechnology and Biological Sciences Research Council studentship (to J.R.). The authors would also like to thank J.N. Selley for bioinformatic support.
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