Biomedical subjects

Jiri Vohradsky

Publications and source records attributed to Jiri Vohradsky.

5 recordsLinked to original sources

PubMed2006

Nonlinear differential equation model for quantification of transcriptional regulation applied to microarray data of Saccharomyces cerevisiae.

Microarray studies are capable of providing data for temporal gene expression patterns of thousands of genes simultaneously, comprising rich but cryptic information about transcriptional control. However available methods are still not adequate in extraction of useful information about transcriptional regulation from these data. This study presents a dynamic model of gene expression which allows for identification of transcriptional regulators using time series of gene expression. The algorithm was applied for identification of transcriptional regulators controlling 40 cell cycle regulated genes of Saccharomyces cerevisiae. The presented algorithm uses a dynamic model of time continuous gene expression with the assumption that the target gene expression profile results from the action of the upstream regulator. The goal is to apply the model to putative regulators to estimate the transcription pattern of a target gene using a least squares minimization procedure. The procedure iteratively tests all possible transcription factors and selects those that best approximate the target gene expression profile. Results were compared with independently published data and good agreement between the published and identified transcriptional regulators was found.

Algorithms↗

PubMed2006

Systems level analysis of protein synthesis patterns associated with bacterial growth and metabolic transitions.

Gene expression databases, acquired by proteomics and transcriptomics, describe physiological and developmental programs at the systems level. Here we analyze proteosynthetic profiles in a bacterium undergoing defined metabolic changes. Streptomyces coelicolor cultured in a defined liquid medium displays four distinct patterns of gene expression associated with growth on glutamate, diauxic transition, and growth on maltose and ammonia that terminates by starvation for nitrogen and entry into stationary phase. Principal component and fuzzy cluster analyses of the proteome database of 935 protein spot profiles revealed principal kinetic patterns. Online linkage of the proteome database (SWICZ) to a protein-function database (KEGG) revealed limited correlations between expression profiles and metabolic pathway activities. Proteins belonging to principal metabolic pathways defined characteristic kinetic profiles correlated with the physiological state of the culture. These analyses supported the concept that metabolic flux was regulated not by individual enzymes but rather by groups of enzymes whose synthesis responded to changes in nutritional conditions. Higher-level regulation is reflected by the distribution of all kinetic profiles into only nine groups. The observation that enzymes representing principal metabolic pathways displayed their own distinctive average kinetic profiles suggested that expression of a "high-flux backbone" may dominate regulation of metabolic flux.

Adaptation, Physiological↗

PubMed2003

Proteome of Caulobacter crescentus cell cycle publicly accessible on SWICZ server.

Here we present the Swiss-Czech Proteomics Server (SWICZ), which hosts the proteomic database summarizing information about the cell cycle of the aquatic bacterium Caulobacter crescentus. The database provides a searchable tool for easy access of global protein synthesis and protein stability data as examined during the C. crescentus cell cycle. Protein synthesis data collected from five different cell cycle stages were determined for each protein spot as a relative value of the total amount of [(35)S]methionine incorporation. Protein stability of pulse-labeled extracts were measured during a chase period equivalent to one cell cycle unit. Quantitative information for individual proteins together with descriptive data such as protein identities, apparent molecular masses and isoelectric points, were combined with information on protein function, genomic context, and the cell cycle stage, and were then assembled in a relational database with a world wide web interface (http://proteom.biomed.cas.cz), which allows the database records to be searched and displays the recovered information. A total of 1250 protein spots were reproducibly detected on two-dimensional gel electropherograms, 295 of which were identified by mass spectroscopy. The database is accessible either through clickable two-dimensional gel electrophoretic maps or by means of a set of dedicated search engines. Basic characterization of the experimental procedures, data processing, and a comprehensive description of the web site are presented. In its current state, the SWICZ proteome database provides a platform for the incorporation of new data emerging from extended functional studies on the C. crescentus proteome.

Bacterial Proteins↗

PubMed2003

Proteomic studies of diauxic lag in the differentiating prokaryote Streptomyces coelicolor reveal a regulatory network of stress-induced proteins and central metabolic enzymes.

Bacteria typically undergo intermittent periods of starvation and adaptation, emulated as diauxic growth in the laboratory. In association with growth arrest elicited by metabolic stress, the differentiating eubacterium Streptomyces coelicolor not only adapts its primary metabolism, but can also activate developmental programmes leading to morphogenesis and antibiotic biosynthesis. Here, we report combined proteomic and metabolomic data of S. coelicolor used to analyse global changes in gene expression during diauxic growth in a defined liquid medium. Cultures initially grew on glutamate, providing the nitrogen source and feeding carbon (as 2-oxoglutarate) into the TCA cycle, followed by a diauxic delay allowing reorientation of metabolism and a second round of growth supported by NH4+, formed during prediauxic phase, and maltose, a glycolytic substrate. Cultures finally entered stationary phase as a result of nitrogen starvation. These four physiological states had previously been defined statistically by their distinct patterns of protein synthesis and heat shock responses. Together, these data demonstrated that the rates of synthesis of heat shock proteins are determined not only by temperature increase but also by the patterns and rates of metabolic flux in certain pathways. Synthesis profiles for metabolic- and stress-induced proteins can now be interpreted by the identification of 204 spots (SWICZ database presented at http://proteom.biomed.cas.cz). Cluster analysis showed that the activity of central metabolic enzymes involved in glycolysis, the TCA cycle, starvation or proteolysis each displayed identifiable patterns of synthesis that logically underlie the metabolic state of the culture. Diauxic lag was accompanied by a structured regulatory programme involving the sequential activation of heat-, salt-, cold- and bacteriostatic antibiotic (pristinamycin I, PI)-induced stimulons. Although stress stimulons presumably provide protection during environmental- or starvation-induced stress, their identities did not reveal any coherent adaptive or developmental functions. These studies revealed interactive regulation of metabolic and stress response systems including some proteins known to support developmental programmes in S. coelicolor.

Adaptation, Physiological↗

PubMed2002

Genexp--a genetic network simulation environment.

UNLABELLED: An environment for simulation of dynamics of genetic regulatory networks is presented. The model is based on the recurrent neural network principle and allows to interactively simulate various genetic regulatory interactions under different features of the system. The results are displayed graphically. AVAILABILITY: http://proteom.biomed.cas.cz/genexp

Computer Simulation↗