
pmid: 16287169
Abstract With the completion of the sequencing of the Arabidopsis genome and the recent advances in proteomic technology, the identification of proteins from highly complex mixtures is now possible. Rather than using gel electrophoresis and peptide mass fingerprinting, we have used multidimensional protein identification technology (MudPIT) to analyse the ‘tightly‐bound’ proteome for purified cell walls from Arabidospis cell suspension cultures. Using bioinformatics for the prediction of signal peptides for targeting to the secretory pathway and for the absence of ER retention signal, 89 proteins were selected as potential extracellular proteins. Only 33% of these were identified in previous proteomic analyses of Arabidopsis cell walls. A functional classification revealed that a large proportion of the proteins were enzymes, notably carbohydrate active enzymes, peroxidases and proteases. Comparison of all the published proteomic analyses for the Arabidopsis cell wall identified 268 non‐redundant genes encoding wall proteins. Sixty of these (22%) were derived from our analysis of tightly‐bound wall proteins.
Proteome, Arabidopsis Proteins, Cell Wall, Arabidopsis, Computational Biology, Protein Processing, Post-Translational
Proteome, Arabidopsis Proteins, Cell Wall, Arabidopsis, Computational Biology, Protein Processing, Post-Translational
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