Regulation Of Gene Expression In Yeast Research Articles

Ethanol Stress Response in the mRNA Flux ofSaccharomyces cerevisiae

Post-transcriptional regulation as well as transcriptional regulation plays an important role in the expression of genes under stressed conditions in Saccharomyces cerevisiae. Under stressed conditions caused by heat shock or ethanol, yeast cells alter not only their transcriptional patterns but also the types of mRNA to be exported from the nucleus in order to adapt rapidly to the stress. Under heat-shocked conditions at 42 degrees C, bulk poly (A)(+) mRNA accumulates in the nucleus, whereas stress-induced transcripts such as HSP mRNAs are efficiently exported. Ethanol stress also causes nuclear accumulation of bulk poly (A)(+) mRNA, but elicits a different response regarding the transport of HSP mRNAs. Other differences between the heat shock response and the ethanol stress response were observed in the nuclear processing of transcripts and in cytosolic mRNA flux. This review outlines the regulation of yeast gene expression at the mRNA processing and nuclear export steps under ethanol stressed conditions, and discusses how to improve the capabilities of brewer's yeast cells.

A fast and efficient translational control system for conditional expression of yeast genes.

A new artificial regulatory system for essential genes in yeast is described. It prevents translation of target mRNAs upon tetracycline (tc) binding to aptamers introduced into their 5′UTRs. Exploiting direct RNA–ligand interaction renders auxiliary protein factors unnecessary. Therefore, our approach is strain independent and not susceptible to interferences by heterologous expressed regulatory proteins. We use a simple PCR-based strategy, which allows easy tagging of any target gene and the level of gene expression can be adjusted due to various tc aptamer-regulated promoters. As proof of concept, five differently expressed genes were targeted, two of which could not be regulated previously. In all cases, adding tc completely prevented growth and, as shown for Nop14p, rapidly abolished de novo protein synthesis providing a powerful tool for conditional regulation of yeast gene expression.

Post‐transcriptional regulation of gene expression in yeast under ethanol stress

The selective export of mRNA from the nucleus plays an important role in the regulation of yeast gene expression under ethanol-stressed conditions, and it has been clarified that expression of the transcriptionally activated HSP (heat-shock protein) genes are inhibited in the mRNA processing and export steps. In actual alcoholic fermentation, during the late brewing process for wine in which the ethanol concentration has been increased, the export of bulk poly(A)+ (polyadenylated) mRNA is blocked and protein synthesis is considerably repressed. These observations clearly suggest that variation in the mRNA level is not necessarily reflected in the variation of the protein level in yeast cells during the brewing process. The present minireview outlines the regulation of yeast gene expression at the mRNA-processing and nuclear-export steps under ethanol-stressed conditions, highlighting their usefulness in the brewing industry.

Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering.

Organisms simplify the orchestration of gene expression by coregulating genes whose products function together in the cell. Many proteins serve different roles depending on the demands of the organism, and therefore the corresponding genes are often coexpressed with different groups of genes under different situations. This poses a challenge in analyzing whole-genome expression data, because many genes will be similarly expressed to multiple, distinct groups of genes. Because most commonly used analytical methods cannot appropriately represent these relationships, the connections between conditionally coregulated genes are often missed. We used a heuristically modified version of fuzzy k-means clustering to identify overlapping clusters of yeast genes based on published gene-expression data following the response of yeast cells to environmental changes. We have validated the method by identifying groups of functionally related and coregulated genes, and in the process we have uncovered new correlations between yeast genes and between the experimental conditions based on similarities in gene-expression patterns. To investigate the regulation of gene expression, we correlated the clusters with known transcription factor binding sites present in the genes' promoters. These results give insights into the mechanism of the regulation of gene expression in yeast cells responding to environmental changes. Fuzzy k-means clustering is a useful analytical tool for extracting biological insights from gene-expression data. Our analysis presented here suggests that a prevalent theme in the regulation of yeast gene expression is the condition-specific coregulation of overlapping sets of genes.

The regulation of yeast gene expression by multiple control elements.

The effective employment of biological systems for production of commercially useful chemicals often requires a thorough understanding of how the desired system is regulated. In the past we have looked to procaryotic systems for models of how control is exerted; they have served us well. However, it is becoming abundantly clear that the procaryotic paradigm does not extend to eucaryotic systems. For these, new models must be developed and new paradigms constructed. My purpose is the development of such a model in the simple eucaryotic microorganism, Saccharomyces cerevisiae. This yeast is perhaps the oldest commercially cultured organism in existence. It is also one of the most well studied genetic systems available. Our model is the metabolism of two main nitrogen sources, allantoin and arginine. We selected two systems instead of one to gain some insight into the spectrum of regulatory mechanisms that operate in eucaryotic cells. Our choice also presents the added opportunity of assessing the means used to integrate the expression of separately controlled, but functionally related genes.