Explore the vast range of titles available.

Various post‐translational modifications (PTMs) fine‐tune the functions of almost all eukaryotic proteins, and co‐regulation of different types of PTMs has been shown within and between a number of proteins. Aiming at a more global view of the interplay between PTM types, we collected modifications for 13 frequent PTM types in 8 eukaryotes, compared their speed of evolution and developed a method for measuring PTM co‐evolution within proteins based on the co‐occurrence of sites across eukaryotes. As many sites are still to be discovered, this is a considerable underestimate, yet, assuming that most co‐evolving PTMs are functionally associated, we found that PTM types are vastly interconnected, forming a global network that comprise in human alone >50 000 residues in about 6000 proteins. We predict substantial PTM type interplay in secreted and membrane‐associated proteins and in the context of particular protein domains and short‐linear motifs. The global network of co‐evolving PTM types implies a complex and intertwined post‐translational regulation landscape that is likely to regulate multiple functional states of many if not all eukaryotic proteins. This study is the first large‐scale comparative analysis of multiple types of post‐translational modifications in different eukaryotic species. The resulting network of co‐evolving and functionally associated modifications reveals the global landscape of post‐translational regulation. Synopsis This study is the first large‐scale comparative analysis of multiple types of post‐translational modifications in different eukaryotic species. The resulting network of co‐evolving and functionally associated modifications reveals the global landscape of post‐translational regulation. In all, 115 149 non‐redundant post‐translational modifications (PTMs) of 13 different types were collected from 8 eukaryotes. Comparison of evolution speed reveals that carboxylation is the most conserved while SUMOylation is the fastest evolving PTM type. Co‐evolution of PTM pairs that co‐occur within proteins reveals a vastly interconnected global network of functionally associated PTM types in eukaryotes. Central to the network of functionally associated PTM types appear phosphorylation, acetylation, ubiquitination and O‐linked glycosylation that control both temporal events and processes that govern protein localization.

Large‐scale siRNA screenings allow linking the function of poorly characterized genes to phenotypic readouts. According to this strategy, genes are associated with a function of interest if the alteration of their expression perturbs the phenotypic readouts. However, given the intricacy of the cell regulatory network, the mapping procedure is low resolution and the resulting models provide little mechanistic insights. We have developed a new strategy that combines multiparametric analysis of cell perturbation with logic modeling to achieve a more detailed functional mapping of human genes onto complex pathways. A literature‐derived optimized model is used to infer the cell activation state following upregulation or downregulation of the model entities. By matching this signature with the experimental profile obtained in the high‐throughput siRNA screening it is possible to infer the target of each protein, thus defining its ‘entry point’ in the network. By this novel approach, 41 phosphatases that affect key growth pathways were identified and mapped onto a human epithelial cell‐specific growth model, thus providing insights into the mechanisms underlying their function. Phosphatases control cell growth by a variety of mechanisms. A novel strategy is presented that combines multiparametric analysis of cell perturbations with logic modeling to achieve a detailed mapping of human phosphatase function on growth pathways. Synopsis Phosphatases control cell growth by a variety of mechanisms. A novel strategy is presented that combines multiparametric analysis of cell perturbations with logic modeling to achieve a detailed mapping of human phosphatase function on growth pathways. siRNA‐mediated downregulation of 298 phosphatase and phosphatase‐related genes coupled to automated microscopy was used to characterize their impact on key growth pathways. In parallel, a literature‐derived signed directed network was derived and optimized by training with experimental data. The resulting logic‐based growth model was used to infer the cell state upon perturbation of each signaling node and compare it with the profiles obtained upon phosphatase perturbation. Mapping of 67% of the protein phosphatase onto the growth model shows that phosphatases are key modulators of growth pathways and affect cell‐cycle progression. This novel approach is general and enables to efficiently map proteins onto complex pathways.