The understanding of the molecular basis of yeast resistance to ethanol may guide the design of rational strategies to increase process performance in industrial alcoholic fermentations. In this study, the yeast disruptome was screened for mutants with differential susceptibility to stress induced by high ethanol concentrations in minimal growth medium. Over 250 determinants of resistance to ethanol were identified. The most significant gene ontology terms enriched in this data set are those associated with intracellular organization, biogenesis, and transport, in particular, regarding the vacuole, the peroxisome, the endosome, and the cytoskeleton, and those associated with the transcriptional machinery. Saccharomyces cerevisiae and related yeast species have been extensively used in fermentation, wine making, sake making, and brewing processes. Bioethanol production by yeast is also a growing industry due to energy and environmental demands (38). The successful performance of alcoholic fermentations depends on the ability of the yeast strains used to cope with a number of stress factors occurring during the process (45, 48). These include osmotic pressure imposed by initial high sugar concentration and stress induced by fermentation end products or subproducts such as ethanol and acetate. However, the stress induced by increasing amounts of ethanol, accumulated to toxic concentrations during ethanolic fermentation, is the major factor responsible for reduced ethanol production and, eventually, for stuck fermentations (14). Thus, yeast strains that can endure stress imposed by high ethanol concentrations are highly desired.Throughout the years many efforts to characterize the mechanisms underlying ethanol stress tolerance, aiming to increase ethanol productivity, have been made (3,16,45,53). The successful engineering of yeast transcription machinery for this purpose was recently reported (3). A number of studies based on detailed physiological and molecular analyses have contributed to increasing the understanding of the processes underlying ethanol toxicity and yeast tolerance of stress induced by this metabolite (34)(35)(36)45). These studies indicate that ethanol interferes with membrane lipid organization, affecting its function as a matrix for enzymes, perturbing the conformation and function of membrane transporters, increasing the nonspecific plasma membrane permeability, and leading to the dissipation of transmembrane electrochemical potential (36,45). Concomitantly, yeast responses to ethanol-induced stress include changes in the levels and composition of membrane phospholipids and ergosterol (1,6,53). Through its effect at the level of plasma membrane organization and function, ethanol also produces intracellular acidification (26,(34)(35)(36). In response to this effect, yeast exhibits increased plasma membrane H ϩ -ATPase activity, which is important to maintain the intracellular pH and secondary transport mechanisms, which are dependent on the proton gradient across the plasma membrane (1,29,31,34...
The YEAst Search for Transcriptional Regulators And Consensus Tracking (YEASTRACT) information system (http://www.yeastract.com) was developed to support the analysis of transcription regulatory associations in Saccharomyces cerevisiae. Last updated in June 2010, this database contains over 48 200 regulatory associations between transcription factors (TFs) and target genes, including 298 specific DNA-binding sites for 110 characterized TFs. All regulatory associations stored in the database were revisited and detailed information on the experimental evidences that sustain those associations was added and classified as direct or indirect evidences. The inclusion of this new data, gathered in response to the requests of YEASTRACT users, allows the user to restrict its queries to subsets of the data based on the existence or not of experimental evidences for the direct action of the TFs in the promoter region of their target genes. Another new feature of this release is the availability of all data through a machine readable web-service interface. Users are no longer restricted to the set of available queries made available through the existing web interface, and can use the web service interface to query, retrieve and exploit the YEASTRACT data using their own implementation of additional functionalities. The YEASTRACT information system is further complemented with several computational tools that facilitate the use of the curated data when answering a number of important biological questions. Since its first release in 2006, YEASTRACT has been extensively used by hundreds of researchers from all over the world. We expect that by making the new data and services available, the system will continue to be instrumental for yeast biologists and systems biology researchers.
The Yeast search for transcriptional regulators and consensus tracking (YEASTRACT) information system (www.yeastract.com) was developed to support the analysis of transcription regulatory associations in Saccharomyces cerevisiae. Last updated in September 2007, this database contains over 30 990 regulatory associations between Transcription Factors (TFs) and target genes and includes 284 specific DNA binding sites for 108 characterized TFs. Computational tools are also provided to facilitate the exploitation of the gathered data when solving a number of biological questions, in particular the ones that involve the analysis of global gene expression results. In this new release, YEASTRACT includes DISCOVERER, a set of computational tools that can be used to identify complex motifs over-represented in the promoter regions of co-regulated genes. The motifs identified are then clustered in families, represented by a position weight matrix and are automatically compared with the known transcription factor binding sites described in YEASTRACT. Additionally, in this new release, it is possible to generate graphic depictions of transcriptional regulatory networks for documented or potential regulatory associations between TFs and target genes. The visual display of these networks of interactions is instrumental in functional studies. Tutorials are available on the system to exemplify the use of all the available tools.
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