Gene Expression In Yeast Research Articles

An Arabidopsis mutation in translation elongation factor 2 causes superinduction of CBF/DREB1 transcription factor genes but blocks the induction of their downstream targets under low temperatures.

Low temperature regulates gene expression in bacteria, yeast, and animals as well as in plants. However, the signal transduction cascades mediating the low temperature responses are not well understood in any organism. To identify components in low temperature signaling genetically, we isolated Arabidopsis thaliana mutants in which cold-responsive genes are no longer induced by low temperatures. One of these mutations, los1-1, specifically blocks low temperature-induced transcription of cold-responsive genes. Surprisingly, cold-induced expression of the early response transcriptional activators, C-repeat/dehydration responsive element binding factors (CBF/DREB1s), is enhanced by the los1-1 mutation. The los1-1 mutation also reduces the capacity of plants to develop freezing tolerance but does not impair the vernalization response. Genetic analysis indicated that los1-1 is a recessive mutation in a single nuclear gene. The LOS1 gene encodes a translation elongation factor 2-like protein. Protein labeling studies show that new protein synthesis is blocked in los1-1 mutant plants specifically in the cold. These results reveal a critical role of new protein synthesis in the proper transduction of low temperature signals. Our results also suggest that cold-induced transcription of CBF/DREB1s is feedback inhibited by their gene products or by products of their downstream target genes.

Polycistronic gene expression in yeast versus cryptic promoter elements

Saccharomyces cerevisiae is a much preferred host for biotechnological applications. However, the expression of entire heterologous pathways, required for some potential products, is technically challenging in yeast. A possible tool would be polycistronic gene expression. Recent studies demonstrated that short 5' untranslated regions (5'UTRs) found upstream of certain genes support cap-independent translation in vitro. In this study 5'UTRs were used as linkers between genes in polycistronic constructs. Expression levels of genes located in the first, second and third position after a promoter were studied by replacing the respective gene by a promoterless green fluorescence protein (GFP) gene. S. cerevisiae transformed with these constructs was grown on different carbon sources and GFP expression was assayed. Our results demonstrate that (i) ribosomal read-through does not suffice for polycistronic gene expression in vivo, (ii) 5'TFIID and 5'HAP4 but not 5'L-A significantly improve the expression of a reporter gene located second in a bicistron, (iii) 5'TFIID, 5'HAP4 and 5'YAP1 but not 5'L-A can drive expression of a promoterless reporter gene, and (iv) expression driven from 5'TFIID, 5'HAP4 and 5'YAP1 is induced in the presence of raffinose or galactose but not in the presence of glucose. This implies that these elements unlike typical internal ribosome entry site-like structures contain small, potentially useful promoters which support carbon source-regulated expression.

Polycistronic gene expression in yeast versus cryptic promoter elements

Saccharomyces cerevisiae is a much preferred host for biotechnological applications. However, the expression of entire heterologous pathways, required for some potential products, is technically challenging in yeast. A possible tool would be polycistronic gene expression. Recent studies demonstrated that short 5′ untranslated regions (5′UTRs) found upstream of certain genes support cap-independent translation in vitro. In this study 5′UTRs were used as linkers between genes in polycistronic constructs. Expression levels of genes located in the first, second and third position after a promoter were studied by replacing the respective gene by a promoterless green fluorescence protein (GFP) gene. S. cerevisiae transformed with these constructs was grown on different carbon sources and GFP expression was assayed. Our results demonstrate that (i) ribosomal read-through does not suffice for polycistronic gene expression in vivo, (ii) 5′TFIID and 5′HAP4 but not 5′L-A significantly improve the expression of a reporter gene located second in a bicistron, (iii) 5′TFIID, 5′HAP4 and 5′YAP1 but not 5′L-A can drive expression of a promoterless reporter gene, and (iv) expression driven from 5′TFIID, 5′HAP4 and 5′YAP1 is induced in the presence of raffinose or galactose but not in the presence of glucose. This implies that these elements unlike typical internal ribosome entry site-like structures contain small, potentially useful promoters which support carbon source-regulated expression.

Wrestling with pleiotropy: Genomic and topological analysis of the yeast gene expression network

The vast majority (>95%) of single-gene mutations in yeast affect not only the expression of the mutant gene, but also the expression of many other genes. These data suggest the presence of a previously uncharacterized "gene expression network"--a set of interactions between genes which dictate gene expression in the native cell environment. Here, we quantitatively analyze the gene expression network revealed by microarray expression data from 273 different yeast gene deletion mutants.(1) We find that gene expression interactions form a robust, error-tolerant "scale-free" network, similar to metabolic pathways(2) and artificial networks such as power grids and the internet.(3-5) Because the connectivity between genes in the gene expression network is unevenly distributed, a scale-free organization helps make organisms resistant to the deleterious effects of mutation, and is thus highly adaptive. The existence of a gene expression network poses practical considerations for the study of gene function, since most mutant phenotypes are the result of changes in the expression of many genes. Using principles of scale-free network topology, we propose that fragmenting the gene expression network via "genome-engineering" may be a viable and practical approach to isolating gene function.

Examination of gene expression in yeast using microarray technology

Examination of gene expression in yeast using microarray technology

Mitochondrial-nuclear crosstalk is involved in oxygen-regulated gene expression in yeast.

The expression of several oxygen-regulated nuclear genes in the yeast Saccharomyces cerevisiae is affected by the mitochondrion. Recent evidence suggests two levels of mitochondrial involvement. On the one hand, mitochondrial respiratory function is essential for the anoxic induction of some hypoxic genes. On the other hand, the mitochondrial genome itself functions independently of its respiratory function, in the optimal expression of some aerobic genes. These findings suggest that the mitochondrion release at least two types of 'signals' that function in the expression of oxygen-regulated genes.

Linear modes of gene expression determined by independent component analysis.

The expression of genes is controlled by specific combinations of cellular variables. We applied Independent Component Analysis (ICA) to gene expression data, deriving a linear model based on hidden variables, which we term 'expression modes'. The expression of each gene is a linear function of the expression modes, where, according to the ICA model, the linear influences of different modes show a minimal statistical dependence, and their distributions deviate sharply from the normal distribution. Studying cell cycle-related gene expression in yeast, we found that the dominant expression modes could be related to distinct biological functions, such as phases of the cell cycle or the mating response. Analysis of human lymphocytes revealed modes that were related to characteristic differences between cell types. With both data sets, the linear influences of the dominant modes showed distributions with large tails, indicating the existence of specifically up- and downregulated target genes. The expression modes and their influences can be used to visualize the samples and genes in low-dimensional spaces. A projection to expression modes helps to highlight particular biological functions, to reduce noise, and to compress the data in a biologically sensible way.

Drug discovery based on microarray

Gene regulatory networks developed from full genome expression libraries from gene perturbation variant cell lines can be used to quickly and efficiently identify the molecular mechanism of action of drugs or lead compound molecules. We developed an extensive yeast gene expression library consisting of full-genome cDNA array data for over 500 yeast strains each with a single gene disruption. Using this data, combined with dose and time course expression experiments with the oral antifungal agent, we used Boolean network discovery techniques to determine the genes whose expression was most profoundly affected by this drug. Our system identified the gene as the most significantly suppressed target molecule due to exposure to the antifungal agent. This process for network based drug discovery can significantly decrease the time and resources necessary to make rational drug targeting decisions.

Clustering based on conditional distributions in an auxiliary space.

We study the problem of learning groups or categories that are local in the continuous primary space but homogeneous by the distributions of an associated auxiliary random variable over a discrete auxiliary space. Assuming that variation in the auxiliary space is meaningful, categories will emphasize similarly meaningful aspects of the primary space. From a data set consisting of pairs of primary and auxiliary items, the categories are learned by minimizing a Kullback-Leibler divergence-based distortion between (implicitly estimated) distributions of the auxiliary data, conditioned on the primary data. Still, the categories are defined in terms of the primary space. An online algorithm resembling the traditional Hebb-type competitive learning is introduced for learning the categories. Minimizing the distortion criterion turns out to be equivalent to maximizing the mutual information between the categories and the auxiliary data. In addition, connections to density estimation and to the distributional clustering paradigm are outlined. The method is demonstrated by clustering yeast gene expression data from DNA chips, with biological knowledge about the functional classes of the genes as the auxiliary data.

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.

Crosstalk of Prolyl Isomerases, Pin1/Ess1, and Cyclophilin A

Previous studies have indicated that Ess1/Pin1, a gene in the parvulin family of peptidyl-prolyl isomerases (PPIases), plays an important role in regulating the G2/M transition of the cell cycle by binding cell-cycle-regulating proteins in eukaryotic cells. Although the ess1 gene has been considered to be essential in yeast, we have isolated viable ess1 deletion mutants and demonstrated, via analysis of yeast gene expression profiles using microarray techniques, a novel regulatory role for ESS1 in the G1 phase. Although the overall expression profiles in the tested strains (C110-1, W303, S288c, and RAY-3AD) were similar, marked changes were detected for a number of genes involved in the molecular action of ESS1. Among these, the expression levels of a cyclophilin A gene, also a member of the PPIase family, increased in the ess1 null mutant derived from C110-1. Subsequent treatment with cyclosporin A significantly retarded growth, which suggests that ESS1 and cyclophilin A are functionally linked in yeast cells and play important roles at the G1 phase of the cell cycle.

Global Transcriptional Regulation in Yeast

Nine transcriptional regulators--MBP1, Swi6, Swi4, Mcm1, Fkh1, Fkh2, Ndd1, Swi5, and Ace2--are responsible for mediating cell cycle-dependent gene expression in yeast. Although much is known about the expression and regulation of each of these transcription factors individually, it would be helpful to know how the transcription factors function together to begin to coordinate complex processes like the cell division cycle. By using epitope-tagged transcription factors, DNA immunoprecipitation, and ligation-mediated polymerase chain reaction, Simon et al. arrayed the expression of hundreds of cell cycle-regulated genes and determined, with high probabilty, which transcription factors were required for the expression of those genes. Additionally, Simon et al. have begun to map out the profiles of transcription factors required for the expression of subsequent transcription factors during the cell cycle. Thus, this work helps to collate molecular observations into the better understanding of cellwide control networks.I. Simon, J. Barnett, N. Hannett, C. T. Harbison, N. J. Rinaldi, T. L. Volkert, J. J. Wyrick, J. Zeitlinger, D. K. Gifford, T. S. Jaakkola, R. A. Young, Serial regulation of transcriptional regulators in the yeast cell cycle. Cell 106, 697-708 (2001). [Online Journal]

Global Transcriptional Regulation in Yeast

Nine transcriptional regulators--MBP1, Swi6, Swi4, Mcm1, Fkh1, Fkh2, Ndd1, Swi5, and Ace2--are responsible for mediating cell cycle-dependent gene expression in yeast. Although much is known about the expression and regulation of each of these transcription factors individually, it would be helpful to know how the transcription factors function together to begin to coordinate complex processes like the cell division cycle. By using epitope-tagged transcription factors, DNA immunoprecipitation, and ligation-mediated polymerase chain reaction, Simon et al. arrayed the expression of hundreds of cell cycle-regulated genes and determined, with high probabilty, which transcription factors were required for the expression of those genes. Additionally, Simon et al. have begun to map out the profiles of transcription factors required for the expression of subsequent transcription factors during the cell cycle. Thus, this work helps to collate molecular observations into the better understanding of cellwide control networks. I. Simon, J. Barnett, N. Hannett, C. T. Harbison, N. J. Rinaldi, T. L. Volkert, J. J. Wyrick, J. Zeitlinger, D. K. Gifford, T. S. Jaakkola, R. A. Young, Serial regulation of transcriptional regulators in the yeast cell cycle. Cell 106 , 697-708 (2001). [Online Journal]

Upc2p and Ecm22p, dual regulators of sterol biosynthesis in Saccharomyces cerevisiae.

Sterol levels affect the expression of many genes in yeast and humans. We found that the paralogous transcription factors Upc2p and Ecm22p of yeast were sterol regulatory element (SRE) binding proteins (SREBPs) responsible for regulating transcription of the sterol biosynthetic genes ERG2 and ERG3. We defined a 7-bp SRE common to these and other genes, including many genes involved in sterol biosynthesis. Upc2p and Ecm22p activated ERG2 expression by binding directly to this element in the ERG2 promoter. Upc2p and Ecm22p may thereby coordinately regulate genes involved in sterol homeostasis in yeast. Ecm22p and Upc2p are members of the fungus-specific Zn[2]-Cys[6] binuclear cluster family of transcription factors and share no homology to the analogous proteins, SREBPs, that are responsible for transcriptional regulation by sterols in humans. These results suggest that Saccharomyces cerevisiae and human cells regulate sterol synthesis by different mechanisms.

Inhibition of acetyl coenzyme A carboxylase activity restores expression of the INO1 gene in a snf1 mutant strain of Saccharomyces cerevisiae.

Mutations in the Saccharomyces cerevisiae SNF1 gene affect a number of cellular processes, including the expression of genes involved in carbon source utilization and phospholipid biosynthesis. To identify targets of the Snf1 kinase that modulate expression of INO1, a gene required for an early, rate-limiting step in phospholipid biosynthesis, we performed a genetic selection for suppressors of the inositol auxotrophy of snf1Delta strains. We identified mutations in ACC1 and FAS1, two genes important for fatty acid biosynthesis in yeast; ACC1 encodes acetyl coenzyme A carboxylase (Acc1), and FAS1 encodes the beta subunit of fatty acid synthase. Acc1 was shown previously to be phosphorylated and inactivated by Snf1. Here we show that snf1Delta strains with increased Acc1 activity exhibit decreased INO1 transcription. Strains carrying the ACC1 suppressor mutation have reduced Acc1 activity in vitro and in vivo, as revealed by enzymatic assays and increased sensitivity to the Acc1-specific inhibitor soraphen A. Moreover, a reduction in Acc1 activity, caused by addition of soraphen A, provision of exogenous fatty acid, or conditional expression of ACC1, suppresses the inositol auxotrophy of snf1Delta strains. Together, these findings indicate that the inositol auxotrophy of snf1Delta strains arises in part from elevated Acc1 activity and that a reduction in this activity restores INO1 expression in these strains. These results reveal a Snf1-dependent connection between fatty acid production and phospholipid biosynthesis, identify Acc1 as a Snf1 target important for INO1 transcription, and suggest models in which metabolites that are generated or utilized during fatty acid biosynthesis can significantly influence gene expression in yeast.

Plant Tps1 proteins: what do we learn by expression of plant TPS1 genes in yeast?

Plant Tps1 proteins: what do we learn by expression of plant TPS1 genes in yeast?

Multiple Mechanisms Regulate Expression of Low Temperature Responsive (LOT) Genes in Saccharomyces cerevisiae

Using cDNA subtraction screening, we identified five Saccharomyces cerevisiae genes whose expressions is up-regulated when culture temperature was down-shifted from 30 to 10°C. Among these LOT (low temperature-responsive) genes, three (LOT1, LOT2, and LOT3) were identical to FBA1, RPL2B, and NOP1, encoding a fructose biphosphate aldolase, a ribosomal protein L2B, and a nucleolar protein for rRNA processing, respectively. No functions were assigned for LOT5 and LOT6, which are identical to YKL183w and YLR011w, respectively. Northern hybridization analysis revealed that these genes are not uniformly regulated in response to the change of growth temperature. In addition, all the LOT genes, except for LOT1/FBA1, were induced by a low concentration of cycloheximide. The data indicate that multiple mechanisms, including translational functionality may be involved in the regulation of LOT gene expression in yeast.

Transcription elongation: the 'Foggy' is liftingellipsis.

Transcription can be controlled by regulating either the initiation or elongation of RNA chains. Recent studies highlight the importance of an elongation regulator, Spt5, in controlling gene expression in yeast, fruit fly and zebrafish; Spt5 may provide a link between transcriptional elongation and cell fate.

BR22, a novel protein, interacts with thyroid transcription factor-1 and activates the human surfactant protein B promoter.

Surfactant protein (SP)-B expression is restricted to type II pneumocytes and Clara cells in the lung. Previously, a promoter region of human SP-B gene from -64 to -118 has been identified as critical for the tissue-specific expression of this gene. Two cis-elements for thyroid transcription factor (TTF)-1 and hepatocyte nuclear factor (HNF)-3alpha binding were found within this area. Using an oligonucleotide fragment, we incorporated this region sequence into the promoter of a HIS3 reporter gene in yeast. With this modified yeast a human lung complementary DNA (cDNA) library was screened for DNA-binding proteins, other than TTF-1 and HNF-3alpha, that interacted with this promoter segment. A cDNA clone encoding a novel polypeptide, BR22, was identified that activated the reporter gene expression in yeast. This gene is expressed in many tissues and encodes a protein with bipartite nuclear localization signals. Studies using in vivo yeast two-hybrid analysis, in vitro protein-protein interactions, and coimmunoprecipitation analyses demonstrated that BR22 formed a protein complex with TTF-1. In vivo cotransfection studies further indicated that BR22 could act with TTF-1 to synergistically activate the SP-B promoter in mammalian cells. Our data suggest that BR22 is a TTF-1-associated protein. Through a protein-protein interaction with TTF-1, BR22 can form a complex and activate the human SP-B promoter in vivo.

Numerical methods for handling uncertainty in microarray data: An example analyzing perturbed mitochondrial function in yeast

Publisher Summary This chapter discusses methodological issues related to the processing and evaluation of numerical results from microarray experiments. It illustrates the application of microarray technology to the study of how perturbations of mitochondrial function affect gene expression in yeast. The “wet” steps in spotted DNA microarray methodology including slide washing and coating, polymerase chain reaction (PCR) product manipulation and printing, and mRNA labeling and hybridization are well described. These procedures give excellent results and can be followed essentially without modification. A unique exception to this rule concerns the interval between coating slides and printing. The optimal results can be obtained using slides as soon as possible after coating with poly-L-lysine. The current procedure is to coat slides immediately prior to printing and to steam treat and UV irradiate them immediately after printing. Succinic anhydride treatment may be done shortly before the arrays are used and should be done using materials that are as fresh as possible.