[Histone-like protein H-NS as a negative regulator of quorum sensing systems in gram-negative bacteria].

The effects of histone-like protein H-NS on transcription of promoters of the Quorum Sensing regulated operons from marine luminescent mesophilic bacterium Aliivibrio fischeri and psychrophilic Aliivibrio logei, as well as from pathogenic Pseudomonas aeruginosa, are studied. In the present work, the plasmids carrying DNA fragments with the promoters Pr1f (upstream of the luxICDABEG operon from A. fischeri), Pr1l (upstream of the luxCDABEG operon from A. logei), Pr2l (upstream of luxI gene from A. logei), PluxCf (upstream of luxC gene from A. fischeri), and PlasI (upstream of lasI gene from P. aerugenosa) are used. In these plasmids, promoter-operator regions are transcriptionally fused to the reporter genes cassette luxCDABE from Photorhabdus luminescens. Here we have shown that the transcription of the QS-regulated promoters in E. coli hns::kan cells increases 100 to 1000 times. Furthermore, transcription of the QS-regulated promoters in E. coli hns + cells increases 10 to 100 times in the cells transformed with the plasmid carrying gene ardA ColIb-P9 encoding DNA mimic antirestriction protein ArdA, inhibitor of the type I restriction-modification systems.

Trigger factor assists the refolding of heterodimeric but not monomeric luciferases.

The refolding of thermally inactivated protein by ATP-independent trigger factor (TF) and ATP-dependent DnaKJE chaperones was comparatively analyzed. Heterodimeric (αß) bacterial luciferases of Aliivibrio fischeri, Photobacterium leiognathi, and Vibrio harveyi as well as monomeric luciferases of Vibrio harveyi and Luciola mingrelica (firefly) were used as substrates. In the presence of TF, thermally inactivated heterodimeric bacterial luciferases refold, while monomeric luciferases do not refold. These observations were made both in vivo (Escherichia coli ΔdnaKJ containing plasmids with tig gene) and in vitro (purified TF). Unlike TF, the DnaKJE chaperone system refolds both monomeric and heterodimeric luciferases with equal efficiency.

Kinetic model of imidazologlycerol-phosphate synthetase from Escherichia coli.

Based on the available experimental data, we developed a kinetic model of the catalytic cycle of imidazologlycerol-phosphate synthetase from Escherichia coli accounting for the synthetase and glutaminase activities of the enzyme. The rate equations describing synthetase and glutaminase activities of imidazologlycerol-phosphate synthetase were derived from this catalytic cycle. Using the literature data, we evaluated all kinetic parameters of the rate equations characterizing individually synthetase and glutaminase activities as well as the contribution of each activity depending on concentration of the substrates, products, and effectors. As shown, in the presence of 5 -phosphoribosylformimino-5-aminoimidazolo-4-carboxamideribonucleotide (ProFAR) and imidazologlycerol phosphate (IGP) glutaminase activity dominates over synthetase activity at sufficiently low concentrations of 5 -phosphoribulosylformimino-5-aminoimidazolo-4-carboxamideribonucleotide (PRFAR). Increased PRFAR concentrations resulted in decreased contribution of glutaminase activity and, consequently, increased the contribution of synthetase activity in the enzyme functioning.

The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models.

MOTIVATION: Molecular biotechnology now makes it possible to build elaborate systems models, but the systems biology community needs information standards if models are to be shared, evaluated and developed cooperatively. RESULTS: We summarize the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks. SBML is a software-independent language for describing models common to research in many areas of computational biology, including cell signaling pathways, metabolic pathways, gene regulation, and others. AVAILABILITY: The specification of SBML Level 1 is freely available from http://www.sbml.org/

Metabolic modeling of microbial strains in silico.

The large volume of genome-scale data that is being produced and made available in databases on the World Wide Web is demanding the development of integrated mathematical models of cellular processes. The analysis of reconstructed metabolic networks as systems leads to the development of an in silico or computer representation of collections of cellular metabolic constituents, their interactions and their integrated function as a whole. The use of quantitative analysis methods to generate testable hypotheses and drive experimentation at a whole-genome level signals the advent of a systemic modeling approach to cellular and molecular biology.

Regulation of pyruvate dehydrogenase complex activity in Ehrlich ascites carcinoma cells by Ca2+ and pyruvate.

The dependence of pyruvate dehydrogenase complex (PDC) activity on [Ca2+] was determined in Ehrlich ascites carcinoma cells at different pyruvate concentrations. The resulting family of curves had the following characteristics: a) bell-shaped appearance of all curves with maximum activity at 600 nM Ca2+; b) unchanged position of maxima with changes in pyruvate concentration; c) nonmonotonous changes in PDC activity with increasing pyruvate concentration at fixed [Ca2+]. Feasible mechanisms involving Ca2+-dependent phosphatase and kinase which are consistent with the experimental findings are discussed. To determine the steps in the chain of PDC reactions which determine the observed phenomena, a mathematical model is suggested which is based on the known data on the structural--functional relationships between the complex components--pyruvate dehydrogenase (E1), dihydrolipoyl acetyl transferase (E2), dihydrolipoyl dehydrogenase (E3), protein X, kinase, and phosphatase. To adequately describe the non-trivial dependence of PDC activity on [Ca2+] at different pyruvate concentrations, it was also necessary to consider the interdependence of some steps in the general chain of PDC reactions. Phenomenon (a) is shown to be due only to the involvement of protein X in the PDC reactions, phenomenon (b) to be due to changes in the activity of kinase, and phenomenon (c) to be due to dependence of acetylation and transacetylation rates on pyruvate concentration.