A quantitative method for measuring protein phosphorylation

Ubiquitination of human AP-endonuclease 1 (APE1) enhanced by T233E substitution and by CDK5

Apurinic/apyrimidinic endonuclease-1 (APE1) is a multifunctional DNA repair/gene regulatory protein in mammalian cells, and was recently reported to be phosphorylated at Thr233 by CDK5. We here report that ubiquitination of T233E APE1, a mimicry of phospho-T233 APE1, was markedly increased in multiple cell lines. Expression of CDK5 enhanced monoubiquitination of endogenous APE1. Polyubiquitinated APE1 was decreased when K48R ubiquitin was expressed, suggesting that polyubiquitination was mediated mainly through Lys48 of ubiquitin. The ubiquitination activity of MDM2, consistent in its role for APE1 ubiquitination, was increased for T233E APE1 compared to the wild-type APE1. In mouse embryonic fibroblasts lacking the MDM2 gene, ubiquitination of T233E APE1 was still observed probably because of the decreased degradation activity for monoubiquitinated APE1 and because of backup E3 ligases in the cells. Monoubiquitinated APE1 was present in the nucleus, and analyzing global gene expression profiles with or without induction of a ubiquitin-APE1 fusion gene suggested that monoubiquitination enhanced the gene suppression activity of APE1. These data reveal a delicate balance of ubiquitination and phosphorylation activities that alter the gene regulatory function of APE1.

Posttranslational modification of mammalian AP endonuclease (APE1)

A key issue in studying mammalian DNA base excision repair is how its component proteins respond to a plethora of cell-signaling mediators invoked by DNA damage and stress-inducing agents such as reactive oxygen species, and how the actions of individual BER proteins are attributed to cell survival or apoptotic/necrotic death. This article reviews the past and recent progress on posttranslational modification (PTM) of mammalian apurinic/apyrimidinic (AP) endonuclease 1 (APE1).

Chinese hamster apurinic/apyrimidinic endonuclease (chAPE1) expressed in sf9 cells reveals that its endonuclease activity is regulated by phosphorylation

Apurinic/apyrimidinic endonuclease (APE), an essential DNA repair enzyme, initiates the base excision repair pathway by creating a nick 5' to an abasic site in double-stranded DNA. Although the Chinese hamster ovary cells remain an important model for DNA repair studies, the Chinese hamster APE (chAPE1) has not been studied in vitro in respect to its kinetic characteristics. Here we report the results of a kinetic study performed on cloned and overexpressed enzyme in sf9 cells. The kinetic parameters were fully compatible with the broad range of kinetic parameters reported for the human enzyme. However, the activity measures depended on the time point of the culture. We applied inductivity coupled plasma spectrometry to measure the phosphorylation level of chAPE1. Our data showed that a higher phosphorylation of chAPE1 in the expression host was correlated to a lower endonuclease activity. The phosphorylation of a higher activity batch of chAPE1 by casein kinase II decreased the endonuclease activity, and the dephosphorylation of chAPE1 by lambda phosphatase increased the endonuclease activity. The exonuclease activity of chAPE1 was not observed in our kinetic analysis. The results suggest that noticeable divergence in reported activity levels for the human APE1 endonuclease might be caused by unaccounted phosphorylation. Our data also demonstrate that only selected kinases and phosphatases exert regulatory effects on chAPE1 endonuclease activity, suggesting further that this regulatory mechanism may function in vivo to turn on and off the function of this important enzyme in different organisms.

Sgt1 dimerization is negatively regulated by protein kinase CK2-mediated phosphorylation at Ser361

The kinetochore, which consists of centromere DNA and structural proteins, is essential for proper chromosome segregation in eukaryotes. In budding yeast, Sgt1 and Hsp90 are required for the binding of Skp1 to Ctf13 (a component of the core kinetochore complex CBF3) and therefore for the assembly of CBF3. We have previously shown that Sgt1 dimerization is important for this kinetochore assembly mechanism. In this study, we report that protein kinase CK2 phosphorylates Ser(361) on Sgt1, and this phosphorylation inhibits Sgt1 dimerization.

Crystal structure of a novel prokaryotic Ser/Thr kinase and its implication in the Cpx stress response pathway

The Cpx signalling system of Escherichia coli and Salmonella enterica senses extracytoplasmic stress and controls expression of factors that allow the bacterium to adapt to these stressors and thereby enhance survival. Many of the Cpx-responsive genes products are of unknown function. We determined the crystal structure of one of these gene products, called YihE in E. coli, which exhibits a eukaryotic kinase fold. Functional assays established that both YihE and the S. enterica YihE homologue, RdoA, undergo autophosphorylation and phosphorylate protein substrates at Ser/Thr residues in vitro, demonstrating that YihE/RdoA is a novel Ser/Thr protein kinase in prokaryotic cells. Phenotypic analysis of yihE/rdoA null strains indicates that this kinase is most abundant in stationary phase, and is important for long-term cell survival and for expression of surface appendages in both a Cpx-independent and -dependent manner. YihE/RdoA is therefore a previously unknown kinase component of a new type of bacterial phosphorelay mechanism, adding kinase activity as another response to the Cpx sensing system that functions to maintain cellular homeostasis.

Reconstructing biochemical pathways from time course data

Time series data on biochemical reactions reveal transient behavior, away from chemical equilibrium, and contain information on the dynamic interactions among reacting components. However, this information can be difficult to extract using conventional analysis techniques. We present a new method to infer biochemical pathway mechanisms from time course data using a global nonlinear modeling technique to identify the elementary reaction steps which constitute the pathway. The method involves the generation of a complete dictionary of polynomial basis functions based on the law of mass action. Using these basis functions, there are two approaches to model construction, namely the general to specific and the specific to general approach. We demonstrate that our new methodology reconstructs the chemical reaction steps and connectivity of the glycolytic pathway of Lactococcus lactis from time course experimental data.

A unified view of base excision repair: lesion-dependent protein complexes regulated by post-translational modification

Base excision repair (BER) proteins act upon a significantly broad spectrum of DNA lesions that result from endogenous and exogenous sources. Multiple sub-pathways of BER (short-path or long-patch) and newly designated DNA repair pathways (e.g., SSBR and NIR) that utilize BER proteins complicate any comprehensive understanding of BER and its role in genome maintenance, chemotherapeutic response, neuro-degeneration, cancer or aging. Herein, we propose a unified model of BER, comprised of three functional processes: Lesion Recognition/Strand Scission, Gap Tailoring and DNA Synthesis/Ligation, each represented by one or more multi-protein complexes and coordinated via the XRCC1/DNA Ligase III and PARP1 scaffold proteins. BER therefore may be represented by a series of repair complexes that assemble at the site of the DNA lesion and mediates repair in a coordinated fashion involving protein-protein interactions that dictate subsequent steps or sub-pathway choice. Complex formation is influenced by post-translational protein modifications that arise from the cellular state or the DNA damage response, providing an increase in specificity and efficiency to the BER pathway. In this review, we have summarized the reported BER protein-protein interactions and protein post-translational modifications and discuss the impact on DNA repair capacity and complex formation.

An automated procedure for the extraction of metabolic network information from time series data

Novel high-throughput measurement techniques in vivo are beginning to produce dense high-quality time series which can be used to investigate the structure and regulation of biochemical networks. We propose an automated information extraction procedure which takes advantage of the unique S-system structure and supports model building from time traces, curve fitting, model selection, and structure identification based on parameter estimation. The procedure comprises of three modules: model Generation, parameter estimation or model Fitting, and model Selection (GFS algorithm). The GFS algorithm has been implemented in MATLAB and returns a list of candidate S-systems which adequately explain the data and guides the search to the most plausible model for the time series under study. By combining two strategies (namely decoupling and limiting connectivity) with methods of data smoothing, the proposed algorithm is scalable up to realistic situations of moderate size. We illustrate the proposed methodology with a didactic example.

Priming nonlinear searches for pathway identification

BACKGROUND

Dense time series of metabolite concentrations or of the expression patterns of proteins may be available in the near future as a result of the rapid development of novel, high-throughput experimental techniques. Such time series implicitly contain valuable information about the connectivity and regulatory structure of the underlying metabolic or proteomic networks. The extraction of this information is a challenging task because it usually requires nonlinear estimation methods that involve iterative search algorithms. Priming these algorithms with high-quality initial guesses can greatly accelerate the search process. In this article, we propose to obtain such guesses by preprocessing the temporal profile data and fitting them preliminarily by multivariate linear regression.

RESULTS

The results of a small-scale analysis indicate that the regression coefficients reflect the connectivity of the network quite well. Using the mathematical modeling framework of Biochemical Systems Theory (BST), we also show that the regression coefficients may be translated into constraints on the parameter values of the nonlinear BST model, thereby reducing the parameter search space considerably.

CONCLUSION

The proposed method provides a good approach for obtaining a preliminary network structure from dense time series. This will be more valuable as the systems become larger, because preprocessing and effective priming can significantly limit the search space of parameters defining the network connectivity, thereby facilitating the nonlinear estimation task.