gamma-Glutamylcyclotransferase: inhibition by D-beta-aminoglutaryl-L-alanine and analysis of the solvent kinetic isotope effect

A Novel Prodrug of a γ-Glutamylcyclotransferase Inhibitor Suppresses Cancer Cell Proliferation in vitro and Inhibits Tumor Growth in a Xenograft Mouse Model of Prostate Cancer

γ-Glutamylcyclotransferase (GGCT) depletion inhibits cancer cell proliferation. However, whether the enzymatic activity of GGCT is critical for the regulation of cancer cell growth remains unclear. In this study, a novel diester-type cell-permeable prodrug, pro-GA, was developed based on the structure of N-glutaryl-l-alanine (GA), by structure optimization using temporary fluorophore-tagged prodrug candidates. The antiproliferative activity of pro-GA was demonstrated using GGCT-overexpressing NIH-3T3 cells and human cancer cells including MCF7, HL-60, and PC3 cells. By contrast, normal cells were not significantly affected by pro-GA treatment. Moreover, pro-GA administration exhibited anticancer effects in a xenograft model using immunocompromised mice inoculated with PC3 cells. These results indicate that the enzymatic activity of GGCT accelerates tumor growth and that GGCT inhibition is a promising therapeutic strategy for the treatment of GGCT-overexpressing tumors.

Reconstruction of metabolic pathways for the cattle genome

Background

Metabolic reconstruction of microbial, plant and animal genomes is a necessary step toward understanding the evolutionary origins of metabolism and species-specific adaptive traits. The aims of this study were to reconstruct conserved metabolic pathways in the cattle genome and to identify metabolic pathways with missing genes and proteins. The MetaCyc database and PathwayTools software suite were chosen for this work because they are widely used and easy to implement.

Results

An amalgamated cattle genome database was created using the NCBI and Ensembl cattle genome databases (based on build 3.1) as data sources. PathwayTools was used to create a cattle-specific pathway genome database, which was followed by comprehensive manual curation for the reconstruction of metabolic pathways. The curated database, CattleCyc 1.0, consists of 217 metabolic pathways. A total of 64 mammalian-specific metabolic pathways were modified from the reference pathways in MetaCyc, and two pathways previously identified but missing from MetaCyc were added. Comparative analysis of metabolic pathways revealed the absence of mammalian genes for 22 metabolic enzymes whose activity was reported in the literature. We also identified six human metabolic protein-coding genes for which the cattle ortholog is missing from the sequence assembly.

Conclusion

CattleCyc is a powerful tool for understanding the biology of ruminants and other cetartiodactyl species. In addition, the approach used to develop CattleCyc provides a framework for the metabolic reconstruction of other newly sequenced mammalian genomes. It is clear that metabolic pathway analysis strongly reflects the quality of the underlying genome annotations. Thus, having well-annotated genomes from many mammalian species hosted in BioCyc will facilitate the comparative analysis of metabolic pathways among different species and a systems approach to comparative physiology.

Current status and challenges in connecting models of erythrocyte metabolism to experimental reality

Detailed kinetic models of human erythrocyte metabolism have served to summarize the vast literature and to predict outcomes from laboratory and "Nature's" experiments on this simple cell. Mathematical methods for handling the large array of nonlinear ordinary differential equations that describe the time dependence of this system are well developed, but experimental methods that can guide the evolution of the models are in short supply. NMR spectroscopy is one method that is non-selective with respect to analyte detection but is highly specific with respect to their identification and quantification. Thus time courses of metabolism are readily recorded for easily changed experimental conditions. While the data can be simulated, the systems of equations are too complex to allow solutions of the inverse problem, namely parameter-value estimation for the large number of enzyme and membrane-transport reactions operating in situ as opposed to in vitro. Other complications with the modelling include the dependence of cell volume on time, and the rates of membrane transport processes are often dependent on the membrane potential. These matters are discussed in the light of new modelling strategies.