Activity-based protein profiling (ABPP) has emerged as a powerful proteomic approach to study the active proteins in their native environment by using chemical probes that label active site residues in proteins. Traditionally, ABPP is classified as either comparative or competitive ABPP. In this protocol, we describe a simple method called convolution ABPP, which takes benefit from both the competitive and comparative ABPP. Convolution ABPP allows one to detect if a reduced signal observed during comparative ABPP could be due to the presence of inhibitors. In convolution ABPP, the proteomes are analyzed by comparing labeling intensities in two mixed proteomes that were labeled either before or after mixing. A reduction of labeling in the mix-and-label sample when compared to the label-and-mix sample indicates the presence of an inhibitor excess in one of the proteomes. This method is broadly applicable to detect inhibitors in proteomes against any proteome containing protein activities of interest. As a proof of concept, we applied convolution ABPP to analyze secreted proteomes from Pseudomonas syringae-infected Nicotiana benthamiana leaves to display the presence of a beta-galactosidase inhibitor.
Keywords: Activity-based protein profiling (ABPP); Beta-galactosidase; Convolution ABPP; Cyclophellitol-aziridine; Galactostatin; Nicotiana benthamiana; Pseudomonas syringae; Secreted proteomes.