Submitted on December 1, 2006
Revised on June 25, 2007
Accepted on July 7, 2007
A chemical proteomics approach to pi3k signaling in macrophages
Christian Pasquali, Dominique Bertschy-Meier, Christian Chabert, Marie-Laure Curchod, Christian Arod, Randy Booth, Karl Mechtler, Francis Vilbois, Ioannis Xenoarios, Colin G. Ferguson, Glenn D. Prestwich, Montserrat Camps, and Christian Rommel
Signal Transduction, Molecular Pathophysiology & Pharmacology, Merck Serono International S.A., Geneva, Geneva 1202
Corresponding Author: christian.pasquali{at}merckserono.net
Prior work employing lipid-based affinity matrices has been used to investigate distinct sets of lipid-binding proteins and one series of experiments has proven successful in mammalian cells for their proteome-wide identification. However, most lipid-based proteomics screens require scaled up sample preparation, are often composed of multiple cell types and are not adapted for simultaneous signal transduction studies. Herein, we provide a chemical proteomics strategy that uses cleavable lipid baits with broad applicability to diverse biological samples. The novel baits were designed to avoid preparative steps in order to allow functional proteomics studies when biological source is a limiting factor. This makes this experimental strategy applicable to virtually any primary cell type. Validation of the chemical baits was first confirmed by the selective isolation of several known endogenous PI3K signaling proteins using primary bone marrow-derived macrophages. The use of this technique for cellular proteomics and MS/MS analysis was then demonstrated by the identification of known and potential novel lipid-binding protein, which was confirmed in vitro for several by direct lipid-protein interactions. Further to the identification, the method is also compatible with subsequent signal transduction studies, notably for protein kinase profiling of the isolated lipid-bound protein complexes. Taken together, this integration of minimal scale proteomics, lipid chemistry and activity-based readouts provides a significant advancement in the ability to identify and study the lipid-proteome of single, relevant cell types.