Title
A generic approach for shotgun analysis of the soluble proteome of plant cell suspension cultures A generic approach for shotgun analysis of the soluble proteome of plant cell suspension cultures
Author
Faculty/Department
Faculty of Sciences. Biology
Faculty of Sciences. Chemistry
Faculty of Sciences. Mathematics and Computer Science
Publication type
article
Publication
Amsterdam ,
Subject
Chemistry
Biology
Source (journal)
Journal of chromatography : B: analytical technologies in the biomedical and life sciences. - Amsterdam, 2002, currens
Volume/pages
974(2015) , p. 48-56
ISSN
1570-0232
ISI
000346540800007
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Cell suspension cultures from different plant species act as important model systems for studying cellular processes in plant biology and are often used as green factories for the production of valuable secondary metabolites and recombinant proteins. While mass spectrometry based proteome analysis techniques are ideally suited to study plant cell metabolism and other fundamental cellular processes from a birds eye perspective, they remain underused in plant studies. We describe a comprehensive sample preparation and multidimensional shotgun proteomics strategy that can be generically applied to plant cell suspension cultures. This strategy was optimized and tested on an Arabidopsis thaliana ecotype Landsberg erecta culture. Furthermore, the implementation of strong cation exchange chromatography as a peptide fractionation step is elaborately tested. Its utility in mass spectrometry based proteome analysis is discussed. Using the presented analytical platform, over 13,000 unique peptides and 2640 proteins could be identified from a single plant cell suspension sample. Finally, the experimental setup is validated using Nicotiana tabacum cv. Bright Yellow-2 (BY-2) plant cell suspension cultures, thereby demonstrating that the presented analytical platform can also be valuable tool in proteome analysis of non-genomic model systems.
Full text (open access)
https://repository.uantwerpen.be/docman/irua/18fa71/31974b89.pdf
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