Development of computational methods for metabolic network analysis based on metabolomics data

The baker';s yeast, Saccharomyces cerevisiae, is a simple eukaryotic organism with approximately 6000 genes. Saccharomyces cerevisiae is an ideal model organism for large-scale functional studies and provides a system in which genes can be systematically inactivated by way of gene-knockout methods. A substantial fraction of the 6000 genes in Saccharomyces cerevisiae encode proteins for which currently we do not know any confirmed or putative function. Prediction of the functional role of these proteins is a challenging problem in systems biology, especially as many of these genes have no overt phenotypes. In our study, we aim at a better understanding of the underlying functional relationships between genes working across diverse metabolic pathways using intracellular metabolite profiling studies. We applied bioinformatics methods and statistical analysis techniques in combination with metabolic profiling to understand the function and the regulatory mechanisms of specific genes involved in central carbon metabolism and amino acid biosynthesis. The experimental work was carried out by the group of Prof. Elmar Heinzle (Biochemical Engineering, Saarland University), our collaboration partner. 13C stable isotope substrates can be used as tracers to generate detailed metabolic profiles of gene knockouts. Detailed and quantitative information on the physiological cellular states is measured by 13C -metabolic profiling of cultures grown on novel high throughput oxygen sensor microtiter plates. In this dissertation, we worked towards developing systematic approaches for study of Saccharomyces cerevisiae genes of unknown function based on the metabolic profiles of knockout mutants under varied environmental conditions. In the first step, we have developed a software tool called CalSpec for automation of Gas Chromatography Mass Spectrometry data acquisition and analysis routine, as this is a bottleneck in the metabolic profiling studies. In the next step, we worked on large scale statistical analysis of metabolic profiling data. We applied various algorithms for finding closely related mutants which show similar metabolic profiles. According to our hypothesis, similarity in the metabolic profiles can be used to find functionally linked genes. Saccharomyces cerevisiae is known to be robust to majority of genetic perturbations. In these cases where the mutants show no overt 4 phenotypes, we developed a sensitive outlier detection method to detect those subsets of metabolic profile features which are most differentiating (outliers) for all mutants. The second part of this dissertation involves developing computational tools for metabolic pathway analysis on the basis of genome scale metabolic models, as well as integration of various newly emerging experimental techniques. In recent years, genome scale metabolic models have been and are continuing to be assembled for various organisms. In the year 2003, first comprehensive genome scale metabolic model for yeast became publicly available. With the emergence of system biology area of research, diverse computational approaches have been developed. In this work, we developed a new webserver called MetaModel, for analysis of genome scale metabolic networks of eukaryotic organisms

Confirmation of human protein interaction data by human expression data

BACKGROUND: With microarray technology the expression of thousands of genes can be measured simultaneously. It is well known that the expression levels of genes of interacting proteins are correlated significantly more strongly in Saccharomyces cerevisiae than those of proteins that are not interacting. The objective of this work is to investigate whether this observation extends to the human genome. RESULTS: We investigated the quantitative relationship between expression levels of genes encoding interacting proteins and genes encoding random protein pairs. Therefore we studied 1369 interacting human protein pairs and human gene expression levels of 155 arrays. We were able to establish a statistically significantly higher correlation between the expression levels of genes whose proteins interact compared to random protein pairs. Additionally we were able to provide evidence that genes encoding proteins belonging to the same GO-class show correlated expression levels. CONCLUSION: This finding is concurrent with the naive hypothesis that the scales of production of interacting proteins are linked because an efficient interaction demands that involved proteins are available to some degree. The goal of further research in this field will be to understand the biological mechanisms behind this observation

PMAP: databases for analyzing proteolytic events and pathways

The Proteolysis MAP (PMAP, http://www.proteolysis.org) is a user-friendly website intended to aid the scientific community in reasoning about proteolytic networks and pathways. PMAP is comprised of five databases, linked together in one environment. The foundation databases, ProteaseDB and SubstrateDB, are driven by an automated annotation pipeline that generates dynamic ‘Molecule Pages’, rich in molecular information. PMAP also contains two community annotated databases focused on function; CutDB has information on more than 5000 proteolytic events, and ProfileDB is dedicated to information of the substrate recognition specificity of proteases. Together, the content within these four databases will ultimately feed PathwayDB, which will be comprised of known pathways whose function can be dynamically modeled in a rule-based manner, and hypothetical pathways suggested by semi-automated culling of the literature. A Protease Toolkit is also available for the analysis of proteases and proteolysis. Here, we describe how the databases of PMAP can be used to foster understanding of proteolytic pathways, and equally as significant, to reason about proteolysis

Naturwissenschaftlich-Technischen Fakultät I der Universität des Saarlandes

The baker’s yeast, Saccharomyces cerevisiae, is a simple eukaryotic organism with approximately 6000 genes. Saccharomyces cerevisiae is an ideal model organism for large-scale functional studies and provides a system in which genes can be systematically inactivated by way of gene-knockout methods. A substantial fraction of the 6000 genes in Saccharomyces cerevisiae encode proteins for which currently we do not know any confirmed or putative function. Prediction of the functional role of these proteins is a challenging problem in systems biology, especially as many of these genes have no overt phenotypes. In our study, we aim at a better understanding of the underlying functional relationships between genes working across diverse metabolic pathways using intracellular metabolite profiling studies. We applied bioinformatics methods and statistical analysis techniques in combination with metabolic profiling to understand the function and the regulatory mechanisms of specific genes involved in central carbon metabolism and amino acid biosynthesis. The experimental work was carried out by the group of Prof. Elmar Heinzle (Biochemical Engineering, Saarland University), our collaboration partner. 13 C stable isotope substrates can be used as tracers to generat

DESIGN AND DEVELOPMENT OF PULSIN-CAP CHRONOMODULATED DRUG DELIVERY OF SELECTIVE ANTI-ANGINAL DRUG: AN IN-VITRO AND IN-VIVO EVALUATION

Objective: In the current work, an attempt was made to formulate the chrono pharmaceutical drug delivery of Ivabradine HCl to the colon. A time delayed capsule was prepared by sealing the micro particles inside a gelatin capsule made up of erodible hydrogel plug. Methods: The microparticles were formulated by counter-ion elicited aggregation methodology. A natural polymer such as chitosan was chosen as polycation and smaller molecular electrolytes like sodium citrate, sodium sulphate and sodium tripolyphosphate were chosen as poly-anions. The formulated aggregate microparticles were tested for surface morphology, size distribution, in-vitro un-harness and drug excipient interaction. Optimized microparticles formulations were carefully chosen on the basis on dissolution studies. The whole device was enteric coated and hydrogel plug was placed in the capsule opening. Results: The pulsatile capsule was found to be acceptable to delay the drug release in small intestinal fluid and eject out the plugin colonic fluid, thus releasing the microparticles into colonic fluid after a lag time criterion of 5 hours. To mimic the pH changes along the GI tract, three dissolution media with pH 1.2, 6.8 and 7.4 were sequentially used. FT-IR study established that there was no interaction between the drug and polymer. Among all the formulations Ivabradine HCl prepared with sodium tripolyphosphate showed prolonged release for a period of 12 hours. Conclusion:  The obtained results revealed the system's capability to defer the drug release for a programmable period and prevent a sharp increase in blood pressure during the early morning hours when the risk of heart attack is the greatest

Method Development: A non-stereotactic device based method for CSF extraction from cisterna magna in rats.

Biomarker discovery has traditionally been done from serum. However, the problem with serum is that we get high abundance proteins like albumin in large quantities. These high abundance biomarkers mask the presence of biomarkers which are present in minute quantity. The aim of biomarker discovery from CSF is that it would give us rather clear repertoire of biomarkers which are of neurological importance and specific to the CNS. In this work, we propose to standardize a lab protocol for extraction of CSF from Rat brain (cisterna magna). There are two different procedures for extraction of CSF. One by lumber puncture method without sacrificing the rat and the other method is serial extraction from the cisterna magna region. The cisterna magna is located in the lowermost portion of brain from where the spinal cord starts. Our aim was to adapt the second protocol to extract the CSF from in house Rat repository. In the first step we had tried our method on dead experimented albino Wistar rats. In the next step we tested it on 12 live albino Wistar rats