Selected reaction monitoring to determine protein abundance in Arabidopsis using the Arabidopsis proteotypic predictor.

In reverse genetic knockout (KO) studies that aim to assign function to specific genes, confirming the reduction in abundance of the encoded protein will often aid the link between genotype and phenotype. However, measuring specific protein abundance is particularly difficult in plant research, where only a limited number of antibodies are available. This problem is enhanced when studying gene families or different proteins derived from the same gene (isoforms), as many antibodies cross react with more than one protein. We show that utilizing selected reaction monitoring (SRM) mass spectrometry allows researchers to confirm protein abundance in mutant lines, even when discrimination between very similar proteins is needed. Selecting the best peptides for SRM analysis to ensure that protein- or gene-specific information can be obtained requires a series of steps, aids, and interpretation. To enable this process in Arabidopsis (Arabidopsis thaliana), we have built a Web-based tool, the Arabidopsis Proteotypic Predictor, to select candidate SRM transitions when no previous mass spectrometry evidence exists. We also provide an in-depth analysis of the theoretical Arabidopsis proteome and its use in selecting candidate SRM peptides to establish assays for use in determining protein abundance. To test the effectiveness of SRM mass spectrometry in determining protein abundance in mutant lines, we selected two enzymes with multiple isoforms, aconitase and malate dehydrogenase. Selected peptides were quantified to estimate the abundance of each of the two mitochondrial isoforms in wild-type, KO, double KO, and complemented plant lines. We show that SRM protein analysis is a sensitive and rapid approach to quantify protein abundance differences in Arabidopsis for specific and highly related enzyme isoforms.