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Plant phosphoproteomics: An update

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.

GabiPD: the GABI primary database—a plant integrative ‘omics’ database

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.

Haplotype inference from unphased SNP data in heterozygous polyploids based on SAT

BackgroundHaplotype 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.ResultsHere we present the software SATlotyper which is able to handle polyploid and polyallelic data. SATlo-typer uses the Boolean satisfiability problem to formulate Haplotype Inference by Pure Parsimony. The software excludes existing haplotype inferences, thus allowing for calculation of alternative inferences. As it is not known which of the multiple haplotype inferences are best supported by the given unphased data set, we use a bootstrapping procedure that allows for scoring of alternative inferences. Finally, by means of the bootstrapping scores, it is possible to optimise the phased genotypes belonging to a given haplotype inference. The program is evaluated with simulated and experimental SNP data generated for heterozygous tetraploid populations of potato. We show that, instead of taking the first haplotype inference reported by the program, we can significantly improve the quality of the final result by applying additional methods that include scoring of the alternative haplotype inferences and genotype optimisation. For a sub-population of nineteen individuals, the predicted results computed by SATlotyper were directly compared with results obtained by experimental haplotype inference via sequencing of cloned amplicons. Prediction and experiment gave similar results regarding the inferred haplotypes and phased genotypes.ConclusionOur results suggest that Haplotype Inference by Pure Parsimony can be solved efficiently by the SAT approach, even for data sets of unphased SNP from heterozygous polyploids. SATlotyper is freeware and is distributed as a Java JAR file. The software can be downloaded from the webpage of the GABI Primary Database at http://www.gabipd.org/projects/satlotyper/. The application of SATlotyper will provide haplotype information, which can be used in haplotype association mapping studies of polyploid plants.

Proteome-wide survey of phosphorylation patterns affected by nuclear DNA polymorphisms in Arabidopsis thaliana

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.

On the relation between reactions and complexes of (bio)chemical reaction networks.

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.

A network property necessary for concentration robustness

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.