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. 2012 Jun 19;3:132.
doi: 10.3389/fpls.2012.00132. eCollection 2012.

Current Status of the Plant Phosphorylation Site Database PhosPhAt and Its Use as a Resource for Molecular Plant Physiology

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Free PMC article

Current Status of the Plant Phosphorylation Site Database PhosPhAt and Its Use as a Resource for Molecular Plant Physiology

Borjana Arsova et al. Front Plant Sci. .
Free PMC article

Abstract

As the most studied post-translational modification, protein phosphorylation is analyzed in a growing number of proteomic experiments. These high-throughput approaches generate large datasets, from which specific spectrum-based information can be hard to find. In 2007, the PhosPhAt database was launched to collect and present Arabidopsis phosphorylation sites identified by mass spectrometry from and for the scientific community. At present, PhosPhAt 3.0 consolidates phosphoproteomics data from 19 published proteomic studies. Out of 5460 listed unique phosphoproteins, about 25% have been identified in at least two independent experimental setups. This is especially important when considering issues of false positive and false negative identification rates and data quality (Durek etal., 2010). This valuable data set encompasses over 13205 unique phosphopeptides, with unambiguous mapping to serine (77%), threonine (17%), and tyrosine (6%). Sorting the functional annotations of experimentally found phosphorylated proteins in PhosPhAt using Gene Ontology terms shows an over-representation of proteins in regulatory pathways and signaling processes. A similar distribution is found when the PhosPhAt predictor, trained on experimentally obtained plant phosphorylation sites, is used to predict phosphorylation sites for the Arabidopsis genome. Finally, the possibility to insert a protein sequence into the PhosPhAt predictor allows species independent use of the prediction resource. In practice, PhosPhAt also allows easy exploitation of proteomic data for design of further targeted experiments.

Keywords: Arabidopsis; PhosPhAt; database; protein phosphorylation; proteomics.

Figures

FIGURE 1
FIGURE 1
Distribution of experimental and predicted phosphorylation sites to functional categories of MapMan. The bins which group encoded proteins in their functional categories are: photosynthesis (PS)-1; major carbohydrate (CHO) metabolism-2; minor CHO metabolism-3; glycolysis-4; fermentation-5; gluconeogenese/glyoxylate cycle-6; OPP-7; TCA/org. transformation- 8; mitochondrial electron transport/ATP synthesis -9; cell wall-10; lipid metabolism-11; N-metabolism-12; amino acid metabolism-13; S-assimilation-14; metal handling-15; secondary metabolism-16; hormone metabolism-17; co-factor and vitamin metabolism-18: tetrapyrrole synthesis-19; stress-20; redox-21; polyamine metabolism-22; nucleotide metabolism-23; biodegradation of xenobiotics-24; C1-metabolism-25; misc-26; RNA-27; DNA-28; protein-29; signaling-30; cell-31; microRNA, natural antisense etc-32; development-33; transport-34; not assigned-35.
FIGURE 2
FIGURE 2
Example spectra from PhosPhAt and selected transitions for quantification in targeted SRM analyses for NIA2.

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