Phosphoproteomics involves identification of phosphoproteins, precise mapping, and quantification of phosphorylation sites, and eventually, revealing their biological function. In plants, several systematic phosphoproteomic analyses have recently been performed to optimize in vitro and in vivo technologies to reveal components of the phosphoproteome. The discovery of novel substrates for specific protein kinases is also an important issue. Development of a new tool has enabled rapid identification of potential kinase substrates such as kinase assays using plant protein microarrays. Progress has also been made in quantitative and dynamic analysis of mapped phosphorylation sites. Increased quantity of experimentally verified phosphorylation sites in plants has prompted the creation of dedicated web-resources for plant-specific phosphoproteomics data. This resulted in development of computational prediction methods yielding significantly improved sensitivity and specificity for the detection of phosphorylation sites in plants when compared to methods trained on less plant-specific data. In this review, we present an update on phosphoproteomic studies in plants and summarize the recent progress in the computational prediction of plant phosphorylation sites. The application of the experimental and computed results in understanding the phosphoproteomic networks of cellular and metabolic processes in plants is discussed. This is a continuation of our comprehensive review series on plant phosphoproteomics.

Background: Haplotype inference based on unphased SNP markers is an important task in population genetics. Although there are different approaches to the inference of haplotypes in diploid species, the existing software is not suitable for inferring haplotypes from unphased SNP data in polyploid species, such as the cultivated potato (Solanum tuberosum). Potato species are tetraploid and highly heterozygous.

BackgroundProtein phosphorylation is an important post-translational modification influencing many aspects of dynamic cellular behavior. Site-specific phosphorylation of amino acid residues serine, threonine, and tyrosine can have profound effects on protein structure, activity, stability, and interaction with other biomolecules. Phosphorylation sites can be affected in diverse ways in members of any species, one such way is through single nucleotide polymorphisms (SNPs). The availability of large numbers of experimentally identified phosphorylation sites, and of natural variation datasets in Arabidopsis thaliana prompted us to analyze the effect of non-synonymous SNPs (nsSNPs) onto phosphorylation sites.ResultsFrom the analyses of 7,178 experimentally identified phosphorylation sites we found that: (i) Proteins with multiple phosphorylation sites occur more often than expected by chance. (ii) Phosphorylation hotspots show a preference to be located outside conserved domains. (iii) nsSNPs affected experimental phosphorylation sites as much as the corresponding non-phosphorylated amino acid residues. (iv) Losses of experimental phosphorylation sites by nsSNPs were identified in 86 A. thaliana proteins, among them receptor proteins were overrepresented.These results were confirmed by similar analyses of predicted phosphorylation sites in A. thaliana. In addition, predicted threonine phosphorylation sites showed a significant enrichment of nsSNPs towards asparagines and a significant depletion of the synonymous substitution. Proteins in which predicted phosphorylation sites were affected by nsSNPs (loss and gain), were determined to be mainly receptor proteins, stress response proteins and proteins involved in nucleotide and protein binding. Proteins involved in metabolism, catalytic activity and biosynthesis were less affected.ConclusionsWe analyzed more than 7,100 experimentally identified phosphorylation sites in almost 4,300 protein-coding loci in silico, thus constituting the largest phosphoproteomics dataset for A. thaliana available to date. Our findings suggest a relatively high variability in the presence or absence of phosphorylation sites between different natural accessions in receptor and other proteins involved in signal transduction. Elucidating the effect of phosphorylation sites affected by nsSNPs on adaptive responses represents an exciting research goal for the future.

Maintenance of functionality of complex cellular networks and entire organisms exposed to environmental perturbations often depends on concentration robustness of the underlying components. Yet, the reasons and consequences of concentration robustness in large-scale cellular networks remain largely unknown. Here, we derive a necessary condition for concentration robustness based only on the structure of networks endowed with mass action kinetics. The structural condition can be used to design targeted experiments to study concentration robustness. We show that metabolites satisfying the necessary condition are present in metabolic networks from diverse species, suggesting prevalence of this property across kingdoms of life. We also demonstrate that our predictions about concentration robustness of energy-related metabolites are in line with experimental evidence from Escherichia coli. The necessary condition is applicable to mass action biological systems of arbitrary size, and will enable understanding the implications of concentration robustness in genetic engineering strategies and medical applications.

The GABI Primary Database, GabiPD (http://www.gabipd.org/), was established in the frame of the German initiative for Genome Analysis of the Plant Biological System (GABI). The goal of GabiPD is to collect, integrate, analyze and visualize primary information from GABI projects. GabiPD constitutes a repository and analysis platform for a wide array of heterogeneous data from high-throughput experiments in several plant species. Data from different ‘omics’ fronts are incorporated (i.e. genomics, transcriptomics, proteomics and metabolomics), originating from 14 different model or crop species. We have developed the concept of GreenCards for text-based retrieval of all data types in GabiPD (e.g. clones, genes, mutant lines). All data types point to a central Gene GreenCard, where gene information is integrated from genome projects or NCBI UniGene sets. The centralized Gene GreenCard allows visualizing ESTs aligned to annotated transcripts as well as displaying identified protein domains and gene structure. Moreover, GabiPD makes available interactive genetic maps from potato and barley, and protein 2DE gels from Arabidopsis thaliana and Brassica napus. Gene expression and metabolic-profiling data can be visualized through MapManWeb. By the integration of complex data in a framework of existing knowledge, GabiPD provides new insights and allows for new interpretations of the data.

The GABI Primary Database, GabiPD (http://www.gabipd.org/), was established in the frame of the German initiative for Genome Analysis of the Plant Biological System (GABI). The goal of GabiPD is to collect, integrate, analyse and visualise primary information from GABI projects. GabiPD constitutes a repository and analysis platform for a wide array of heterogeneous data from high-throughput experiments in several plant species. Data from different ‘omics’ fronts are incorporated (i.e., genomics, transcriptomics, proteomics and metabolomics), originating from 14 different model or crop species. We have developed the concept of GreenCards for text based retrieval of all data types in GabiPD (e.g., clones, genes, mutant lines). All data types point to a central Gene GreenCard, where gene information is integrated from genome projects or NCBI UniGene sets. The centralised Gene GreenCard allows visualising ESTs aligned to annotated transcripts as well as displaying identified protein domains and gene structure. Moreover GabiPD makes available interactive genetic maps from potato and barley, and 2DE-gels from Arabidopsis thaliana and Brassica napus. Gene expression and metabolic profiling data can be visualised through MapManWeb. By the integration of complex data in a framework of existing knowledge, GabiPD provides new insights and allows for new interpretations of the data.

The GABI Primary Database, GabiPD, was established eight years ago in the frame of the German initiative for Genome Analysis of the Plant Biological System (Genomanalyse im biologischen System Pflanze, GABI), funded by the German Federal Ministry of Education, Research and Technology (BMBF) as well as a number of private enterprise companies. The main goal of GabiPD is to collect, integrate, visualize and link primary information from GABI projects. GabiPD, in contrast to other plant databases constitutes a repository and analysis platform for a wide array of heterogeneous data arising from high-throughput experiments in several plant species. Currently, data from different 'omics' fronts are incorporated in GabiPD (i.e., genomics, transcriptomics, metabolomics, proteomics), originating from 14 different model or crop species. We have developed the concept of GreenCards for text based retrieval of all data types in GabiPD (e.g., clones, genes, mutant plant lines, markers). All data types are pointing to the central Gene’s GreenCard, where gene information is integrated from genome annotation projects. Within the Gene’s GreenCards links to all GabiPD data related to the corresponding genes as well as cross references to large UniGene sets from NCBI and to useful gene-based external data bases are displayed. A collection of ~400000 ESTs from different species, generated in different GABI projects, is made publicly available though GabiPD. These ESTs have been cross referenced to UniGene sets from NCBI and to sequences from different plant genome projects, in an effort to ease the transfer of functional information. The centralized Gene's GreenCard also allows visualizing ESTs aligned to annotated transcripts as well as identified protein domains and gene structure. Moreover GabiPD makes available interactive genetic maps from Solanum tuberosum (potato) and Hordeum vulgare (barley). Gene expression data in GabiPD can be visualized through MapManWeb, the web interface of MapMan. Access to the data in GabiPD is provided via either the web interface (http://www.gabipd.org) or webservices that are currently available for Arabidopsis-related information. GabiPD was accessed by more than 30000 unique visitors last year from around the world.

Robustness of biochemical systems has become one of the central questions in systems biology although it is notoriously difficult to formally capture its multifaceted nature. Maintenance of normal system function depends not only on the stoichiometry of the underlying interrelated components, but also on the multitude of kinetic parameters. Invariant flux ratios, obtained within flux coupling analysis, as well as invariant complex ratios, derived within chemical reaction network theory, can characterize robust properties of a system at steady state. However, the existing formalisms for the description of these invariants do not provide full characterization as they either only focus on the flux-centric or the concentration-centric view. Here we develop a novel mathematical framework which combines both views and thereby overcomes the limitations of the classical methodologies. Our unified framework will be helpful in analyzing biologically important system properties.