Using quantitative proteomics of Arabidopsis roots and leaves to predict metabolic activity

Abstract

Proteins isolated from developing roots and leaves of Arabidopsis thaliana were separated by high-resolution two-dimensional (2-D) electrophoresis. The resulting 2-D proteome maps are markedly different. Quantitative analysis of root and leaf protein spot pairs revealed that in most instances there was at least a 1.5-fold differential. Peptide mass fingerprint analysis of the 288 most abundant 2-D spots from each organ allowed 156 and 126 protein assignments for roots and leaves, respectively, 54 of which were common. Metabolism-related proteins accounted for 20% of assignments in samples from both organs, whereas energy-related proteins comprised 25 and 18% of leaf and root samples, respectively. Proteins involved in disease resistance and defense encompass 13% of root proteins, but only 7% of leaf proteins. Comparison of protein abundance with transcript abundance, using previously reported microarray data, yielded a correlation coefficient of approximately 0.6, suggesting that it is inappropriate to make protein level or metabolic conclusions based solely upon data from transcript profiling. A comparative model of root and leaf metabolism was developed, based upon protein rather than transcript abundance. The model indicates elevated one-carbon and tricarboxylic acid metabolism in roots relative to leaves. Copyright © Physiologia Plantarum 2006.