A new approach for plant proteomics: characterization of chloroplast proteins of Arabidopsis thaliana by top-down mass spectrometry.

A recently developed methodology for the characterization of complex proteomes, top-down Fourier transform mass spectrometry (FTMS), is applied for the first time to a plant proteome, that of the model plant Arabidopsis thaliana. Of the 3000 proteins predicted by the genome sequence, 97 were recently identified in two separate "bottom-up" mass spectrometry studies in which the proteins were purified and digested and in which the mass spectrometry-measured mass values of the resulting peptides matched against those expected from the DNA-predicted proteins. In the top-down approach applied here, molecular ions from a protein mixture are purified, weighed exactly (+/-1 Da), and fragmented in the FTMS. Of the 22 molecular weight values found in three isolated mixtures, 7 were chosen, and their primary structures were fully characterized; in only one case was the bottom-up structure in full agreement. The top-down technique is not only efficient for identification of the DNA-predicted precursors, such as that of a protein present as a 5% mixture component, but also for characterization of the primary structure of the final protein. For two proteins the previously predicted cleavage site for loss of the signal peptide was found to be incorrect. Two 27-kDa proteins are fully characterized, although they are found to differ by only 12 residues and 6 Da in mass in a 3:1 ratio; the bottom-up studies did not distinguish these proteins. Direct tandem mass spectrometry dissociation of two 15-kDa molecular ions showed >90% sequence similarity, whereas three-stage mass spectrometry traced their +14-Da molecular mass discrepancies to an unusual N-methylation on the N-terminal amino group; the bottom-up approach identified only one precursor protein. The high potential of the top-down FTMS approach for characterization as well as identification of complex plant proteomes should provide a real incentive for its further automation.