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Plant SILAC: Stable-Isotope Labelling with Amino Acids of Arabidopsis Seedlings for Quantitative Proteomics
Stable Isotope Labelling by Amino acids in Cell culture (SILAC) is a powerful technique for comparative quantitative proteomics, which has recently been applied to a number of different eukaryotic organisms. Inefficient incorporation of labelled amino acids in cell cultures of Arabidopsis thaliana h...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3748079/ https://www.ncbi.nlm.nih.gov/pubmed/23977254 http://dx.doi.org/10.1371/journal.pone.0072207 |
Sumario: | Stable Isotope Labelling by Amino acids in Cell culture (SILAC) is a powerful technique for comparative quantitative proteomics, which has recently been applied to a number of different eukaryotic organisms. Inefficient incorporation of labelled amino acids in cell cultures of Arabidopsis thaliana has led to very limited use of SILAC in plant systems. We present a method allowing, for the first time, efficient labelling with stable isotope-containing arginine and lysine of whole Arabidopsis seedlings. To illustrate the utility of this method, we have combined the high labelling efficiency (>95%) with quantitative proteomics analyses of seedlings exposed to increased salt concentration. In plants treated for 7 days with 80 mM NaCl, a relatively mild salt stress, 215 proteins were identified whose expression levels changed significantly compared to untreated seedling controls. The 92 up-regulated proteins included proteins involved in abiotic stress responses and photosynthesis, while the 123 down-regulated proteins were enriched in proteins involved in reduction of oxidative stress and other stress responses, respectively. Efficient labelling of whole Arabidopsis seedlings by this modified SILAC method opens new opportunities to exploit the genetic resources of Arabidopsis and analyse the impact of mutations on quantitative protein dynamics in vivo. |
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