TY - JOUR A1 - Riaño-Pachón, Diego Mauricio A1 - Kleessen, Sabrina A1 - Neigenfind, Jost A1 - Durek, Pawel A1 - Weber, Elke A1 - Engelsberger, Wolfgang R. A1 - Walther, Dirk A1 - Selbig, Joachim A1 - Schulze, Waltraud X. A1 - Kersten, Birgit T1 - Proteome-wide survey of phosphorylation patterns affected by nuclear DNA polymorphisms in Arabidopsis thaliana JF - BMC Genomics N2 - Background: Protein 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. Results: From 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. Conclusions: We 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. KW - Gene Ontology KW - Phosphorylation Site KW - phosphorylated amino acid KW - slim term KW - single nucleotide polymorphism mapping Y1 - 2010 U6 - https://doi.org/10.1186/1471-2164-11-411 SN - 1471-2164 VL - 11 PB - Biomed Central CY - London ER - TY - JOUR A1 - Neigenfind, Jost A1 - Grimbs, Sergio A1 - Nikoloski, Zoran T1 - On the relation between reactions and complexes of (bio)chemical reaction networks JF - Journal of theoretical biology N2 - 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. KW - Metabolic network KW - Mass action system KW - Flux coupling analysis KW - Chemical reaction network theory Y1 - 2013 U6 - https://doi.org/10.1016/j.jtbi.2012.10.016 SN - 0022-5193 VL - 317 IS - 2 SP - 359 EP - 365 PB - Elsevier CY - London ER -