Osmotic Stress Responses (osmotic + stress_response)

Distribution by Scientific Domains


Selected Abstracts


Novel insights into the osmotic stress response of yeast

FEMS YEAST RESEARCH, Issue 3 2002
Willem H Mager
Abstract Response to hyperosmolarity in the baker's yeast Saccharomyces cerevisiae has attracted a great deal of attention of molecular and cellular biologists in recent years, from both the fundamental scientific and applied viewpoint. Indeed the underlying molecular mechanisms form a clear demonstration of the intricate interplay of (environmental) signalling events, regulation of gene expression and control of metabolism that is pivotal to any living cell. In this article we briefly review the cellular response to conditions of hyperosmolarity, with focus on the high-osmolarity glycerol mitogen-activated protein kinase pathway as the major signalling route governing cellular adaptations. Special attention will be paid to the recent finding that in the yeast cell also major structural changes occur in order to ensure maintenance of cell integrity. The intriguing role of glycerol in growth of yeast under (osmotic) stress conditions is highlighted. [source]


Co-ordination of osmotic stress responses through osmosensing and signal transduction events in fishes

JOURNAL OF FISH BIOLOGY, Issue 8 2010
T. G. Evans
This review centres upon the molecular regulation of osmotic stress responses in fishes, focusing on how osmosensing and signal transduction events co-ordinate changes in the activity and abundance of effector proteins during osmotic stress and how these events integrate into osmotic stress responses of varying magnitude. The concluding sections discuss the relevance of osmosensory signal transduction to the evolution of euryhalinity and present experimental approaches that may best stimulate future research. Iterating the importance of osmosensing and signal transduction during fish osmoregulation may be pertinent amidst the increased use of genomic technologies that typically focus solely on changes in the abundances of gene products, and may limit insight into critical upstream events that occur mainly through post-translational mechanisms. [source]


Computational identification of altered metabolism using gene expression and metabolic pathways

BIOTECHNOLOGY & BIOENGINEERING, Issue 4 2009
Hojung Nam
Abstract Understanding altered metabolism is an important issue because altered metabolism is often revealed as a cause or an effect in pathogenesis. It has also been shown to be an important factor in the manipulation of an organism's metabolism in metabolic engineering. Unfortunately, it is not yet possible to measure the concentration levels of all metabolites in the genome-wide scale of a metabolic network; consequently, a method that infers the alteration of metabolism is beneficial. The present study proposes a computational method that identifies genome-wide altered metabolism by analyzing functional units of KEGG pathways. As control of a metabolic pathway is accomplished by altering the activity of at least one rate-determining step enzyme, not all gene expressions of enzymes in the pathway demonstrate significant changes even if the pathway is altered. Therefore, we measure the alteration levels of a metabolic pathway by selectively observing expression levels of significantly changed genes in a pathway. The proposed method was applied to two strains of Saccharomyces cerevisiae gene expression profiles measured in very high-gravity (VHG) fermentation. The method identified altered metabolic pathways whose properties are related to ethanol and osmotic stress responses which had been known to be observed in VHG fermentation because of the high sugar concentration in growth media and high ethanol concentration in fermentation products. With the identified altered pathways, the proposed method achieved best accuracy and sensitivity rates for the Red Star (RS) strain compared to other three related studies (gene-set enrichment analysis (GSEA), significance analysis of microarray to gene set (SAM-GS), reporter metabolite), and for the CEN.PK 113-7D (CEN) strain, the proposed method and the GSEA method showed comparably similar performances. Biotechnol. Bioeng. 2009;103: 835,843. © 2009 Wiley Periodicals, Inc. [source]