Understanding signaling in yeast: Insights from network analysis

Reconstruction of protein interaction networks that represent groups of proteins contributing to the same cellular function is a key step towards quantitative studies of signal transduction pathways. Here we present a novel approach to reconstruct a highly correlated protein interaction network and to identify previously unknown components of a signaling pathway through integration of protein-protein interaction data, gene expression data, and Gene Ontology annotations. A novel algorithm is designed to reconstruct a highly correlated protein interaction network which is composed of the candidate proteins for signal transduction mechanisms in yeast Saccharomyces cerevisiae. The high efficiency of the reconstruction process is proved by a Receiver Operating Characteristic curve analysis. Identification and scoring of the possible linear pathways enables reconstruction of specific sub-networks for glucose-induction signaling and high osmolarity MAPK signaling in S. cerevisiae. All of the known components of these pathways are identified together with several new "candidate" proteins, indicating the successful reconstructions of two model pathways involved in S. cerevisiae. The integrated approach is hence shown useful for (i) prediction of new signaling pathways, (ii) identification of unknown members of documented pathways, and (iii) identification of network modules consisting of a group of related components that often incorporate the same functional mechanism.     

Does Sertraline Affect Hypothalamic Food Intake Peptides in the Rat Experimental Model of Chronic Mild Stress-Induced Depression?

Neurochemical Research - Depression is a chronic, recurrent and life-threatening disease affecting approximately 15% of the world population. Depression is responsible for neuropathologies like...     

Cybernetic modelling of growth and ethanol production in a recombinant Saccharomyces cerevisiae strain secreting a bifunctional fusion protein

Recombinant Saccharomyces cerevisiae YPB-G strain secreting a fusion protein displaying both BsAAase/GAase activities was grown in 1.5 l YPS media containing single (starch) and mixed carbon sources (glucose+starch) using a 2.5 l New Brunswick BiofloIII fermenter. Ethanol and biomass formation, starch utilisation, secretion of the amylolytic enzymes (-amylase and glucoamylase), accumulation of reducing sugars and glucose were followed during the fermentation of YPB-G under different conditions. Moreover, a model has been developed for the growth of recombinant yeast on substitutable substrates using cybernetic framework principles and incorporating product formation. In the present work, both the biphasic and the diauxic growth patterns observed experimentally in batch culture of recombinant yeast cells were simulated successfully by modifying the cybernetic framework to include ethanol formation and the degradation kinetics of starch which is not directly utilised by yeast. The model can further be expanded to fed-batch systems.     

Actinorhodin production by Streptomyces coelicolor A3(2): kinetic parameters related to growth,substrate uptake and production

The dynamics of an Streptomyces coelicolor A3(2) culture in a 20-l computer-controlled batch bioreactor was investigated both experimentally and theoretically. In defined medium, depending on the initial conditions, the calculated value of some of the kinetic parameters were: maximum specific growth rate, 0.03 h^–1; death rate constant, 1.4–6.3 × 10^–3 h^–1; observed biomass yield, 0.21 g cells g^–1 glucose and the maintenance coefficient for the cells, 0.0448 g glucose g^–1 cells h^–1. According to both experimental observations and the Luedeking-Piret model, actinorhodin production was found to be growth-associated. This paper provides the first published quantitative information on the main kinetic parameters describing the activity of S. coelicolor in batch culture. Correspondence to: F. Mavituna     

Stoichiometric network reconstruction and analysis of yeast sphingolipid metabolism incorporating different states of hydroxylation

The first elaborate metabolic model of Saccharomyces cerevisiae sphingolipid metabolism was reconstructed in silico. The model considers five different states of sphingolipid hydroxylation, rendering it unique among other models. It is aimed to clarify the significance of hydroxylation on sphingolipids and hence to interpret the preferences of the cell between different metabolic pathway branches under different stress conditions. The newly constructed model was validated by single, double and triple gene deletions with experimentally verified phenotypes. Calcium sensitivity and deletion mutations that may suppress calcium sensitivity were examined by CSG1 and CSG2 related deletions. The model enabled the analysis of complex sphingolipid content of the plasma membrane coupled with diacylglycerol and phosphatidic acid biosynthesis and ATP consumption in in silico cell. The flux data belonging to these critically important key metabolites are integrated with the fact of phytoceramide induced cell death to propose novel potential drug targets for cancer therapeutics. In conclusion, we propose that IPT1, GDA1, CSG and AUR1 gene deletions may be novel candidates of drug targets for cancer therapy according to the results of flux balance and variability analyses coupled with robustness analysis.