Dataset Information

Characterization and Prediction of Protein Phosphorylation Hotspots in Arabidopsis thaliana.

ABSTRACT: The regulation of protein function by modulating the surface charge status via sequence-locally enriched phosphorylation sites (P-sites) in so called phosphorylation "hotspots" has gained increased attention in recent years. We set out to identify P-hotspots in the model plant Arabidopsis thaliana. We analyzed the spacing of experimentally detected P-sites within peptide-covered regions along Arabidopsis protein sequences as available from the PhosPhAt database. Confirming earlier reports (Schweiger and Linial, 2010), we found that, indeed, P-sites tend to cluster and that distributions between serine and threonine P-sites to their respected closest next P-site differ significantly from those for tyrosine P-sites. The ability to predict P-hotspots by applying available computational P-site prediction programs that focus on identifying single P-sites was observed to be severely compromised by the inevitable interference of nearby P-sites. We devised a new approach, named HotSPotter, for the prediction of phosphorylation hotspots. HotSPotter is based primarily on local amino acid compositional preferences rather than sequence position-specific motifs and uses support vector machines as the underlying classification engine. HotSPotter correctly identified experimentally determined phosphorylation hotspots in A. thaliana with high accuracy. Applied to the Arabidopsis proteome, HotSPotter-predicted 13,677 candidate P-hotspots in 9,599 proteins corresponding to 7,847 unique genes. Hotspot containing proteins are involved predominantly in signaling processes confirming the surmised modulating role of hotspots in signaling and interaction events. Our study provides new bioinformatics means to identify phosphorylation hotspots and lays the basis for further investigating novel candidate P-hotspots. All phosphorylation hotspot annotations and predictions have been made available as part of the PhosPhAt database at http://phosphat.mpimp-golm.mpg.de.

SUBMITTER: Christian JO

PROVIDER: S-EPMC3433687 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Characterization and Prediction of Protein Phosphorylation Hotspots in Arabidopsis thaliana.

Christian Jan-Ole JO Braginets Rostyslav R Schulze Waltraud X WX Walther Dirk D

Frontiers in plant science 20120905

The regulation of protein function by modulating the surface charge status via sequence-locally enriched phosphorylation sites (P-sites) in so called phosphorylation "hotspots" has gained increased attention in recent years. We set out to identify P-hotspots in the model plant Arabidopsis thaliana. We analyzed the spacing of experimentally detected P-sites within peptide-covered regions along Arabidopsis protein sequences as available from the PhosPhAt database. Confirming earlier reports (Schwe ...[more]

PMID: 22973286

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Project description:BACKGROUND: In plants, proline synthesis occurs by two enzymatic steps starting from glutamate as a precursor. Some bacteria, including bacteria such as Agrobacterium rhizogenes have an Ornithine Cyclodeaminase (OCD) which can synthesize proline in a single step by deamination of ornithine. In A. rhizogenes, OCD is one of the genes transferred to the plant genome during the transformation process and plants expressing A. rhizogenes OCD have developmental phenotypes. One nuclear encoded gene of Arabidopsis thaliana has recently been annotated as an OCD (OCD-like; referred to here as AtOCD) but nothing is known of its function. As proline metabolism contributes to tolerance of low water potential during drought, it is of interest to determine if AtOCD affects proline accumulation or low water potential tolerance. RESULTS: Expression of AtOCD was induced by low water potential stress and by exogenous proline, but not by the putative substrate ornithine. The AtOCD protein was plastid localized. T-DNA mutants of atocd and AtOCD RNAi plants had approximately 15% higher proline accumulation at low water potential while p5cs1-4/atocd double mutants had 40% higher proline than p5cs1 at low water potential but no change in proline metabolism gene expression which could directly explain the higher proline level. AtOCD overexpression did not affect proline accumulation. Enzymatic assays with bacterially expressed AtOCD or AtOCD purified from AtOCD:Flag transgenic plants did not detect any activity using ornithine, proline or several other amino acids as substrates. Moreover, AtOCD mutant or over-expression lines had normal morphology and no difference in root elongation or flowering time, in contrast to previous report of transgenic plants expressing A. rhizogenes OCD. Metabolite analysis found few differences between AtOCD mutants and overexpression lines. CONCLUSIONS: The Arabidopsis OCD-like protein (AtOCD) may not catalyze ornithine to proline conversion and this is consistent with observation that three residues critical for activity of bacterial OCDs are not conserved in AtOCD. AtOCD was, however, stress and proline induced and lack of AtOCD expression increased proline accumulation by an unknown mechanism which did not require expression of P5CS1, the main enzyme responsible for stress-induced proline synthesis from glutamate. The results suggest that AtOCD may have function distinct from bacterial OCDs.

Dataset Information

Characterization and Prediction of Protein Phosphorylation Hotspots in Arabidopsis thaliana.

Publications

Characterization and Prediction of Protein Phosphorylation Hotspots in Arabidopsis thaliana.

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