Miguel C. Teixeira

The YEASTRACT database: a tool for the analysis of transcription regulatory associations in Saccharomyces cerevisiae

We present the YEAst Search for Transcriptional Regulators And Consensus Tracking (YEASTRACT; ) database, a tool for the analysis of transcription regulatory associations in Saccharomyces cerevisiae. This database is a repository of 12 346 regulatory associations between transcription factors and target genes, based on experimental evidence which was spread throughout 861 bibliographic references. It also includes 257 specific DNA-binding sites for more than a hundred characterized transcription factors. Further information about each yeast gene included in the database was obtained from Saccharomyces Genome Database (SGD), Regulatory Sequences Analysis Tools and Gene Ontology (GO) Consortium. Computational tools are also provided to facilitate the exploitation of the gathered data when solving a number of biological questions as exemplified in the Tutorial also available on the system. YEASTRACT allows the identification of documented or potential transcription regulators of a given gene and of documented or potential regulons for each transcription factor. It also renders possible the comparison between DNA motifs, such as those found to be over-represented in the promoter regions of co-regulated genes, and the transcription factor-binding sites described in the literature. The system also provides an useful mechanism for grouping a list of genes (for instance a set of genes with similar expression profiles as revealed by microarray analysis) based on their regulatory associations with known transcription factors.

YEASTRACT: providing a programmatic access to curated transcriptional regulatory associations in Saccharomyces cerevisiae through a web services interface

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 YEASTRACT database: an upgraded information system for the analysis of gene and genomic transcription regulation in Saccharomyces cerevisiae

The YEASTRACT (http://www.yeastract.com) information system is a tool for the analysis and prediction of transcription regulatory associations in Saccharomyces cerevisiae. Last updated in June 2013, this database contains over 200 000 regulatory associations between transcription factors (TFs) and target genes, including 326 DNA binding sites for 113 TFs. All regulatory associations stored in YEASTRACT were revisited and new information was added on the experimental conditions in which those associations take place and on whether the TF is acting on its target genes as activator or repressor. Based on this information, new queries were developed allowing the selection of specific environmental conditions, experimental evidence or positive/negative regulatory effect. This release further offers tools to rank the TFs controlling a gene or genome-wide response by their relative importance, based on (i) the percentage of target genes in the data set; (ii) the enrichment of the TF regulon in the data set when compared with the genome; or (iii) the score computed using the TFRank system, which selects and prioritizes the relevant TFs by walking through the yeast regulatory network. We expect that with the new data and services made available, the system will continue to be instrumental for yeast biologists and systems biology researchers.

YEASTRACT-DISCOVERER: new tools to improve the analysis of transcriptional regulatory associations in Saccharomyces cerevisiae

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.

Genome-Wide Identification of Saccharomyces cerevisiae Genes Required for Maximal Tolerance to Ethanol

ABSTRACT 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. Clustering the proteins encoded by the identified determinants of ethanol resistance by their known physical and genetic interactions highlighted the importance of the vacuolar protein sorting machinery, the vacuolar H+-ATPase complex, and the peroxisome protein import machinery. Evidence showing that vacuolar acidification and increased resistance to the cell wall lytic enzyme β-glucanase occur in response to ethanol-induced stress was obtained. Based on the genome-wide results, the particular role of the FPS1 gene, encoding a plasma membrane aquaglyceroporin which mediates controlled glycerol efflux, in ethanol stress resistance was further investigated. FPS1 expression contributes to decreased [3H]ethanol accumulation in yeast cells, suggesting that Fps1p may also play a role in maintaining the intracellular ethanol level during active fermentation. The increased expression of FPS1 confirmed the important role of this gene in alcoholic fermentation, leading to increased final ethanol concentration under conditions that lead to high ethanol production.

Adaptive Response and Tolerance to Weak Acids in Saccharomyces cerevisiae: A Genome-Wide View

Weak acids are widely used as food preservatives (e.g., acetic, propionic, benzoic, and sorbic acids), herbicides (e.g., 2,4-dichlorophenoxyacetic acid), and as antimalarial (e.g., artesunic and artemisinic acids), anticancer (e.g., artesunic acid), and immunosuppressive (e.g., mycophenolic acid) drugs, among other possible applications. The understanding of the mechanisms underlying the adaptive response and resistance to these weak acids is a prerequisite to develop more effective strategies to control spoilage yeasts, and the emergence of resistant weeds, drug resistant parasites or cancer cells. Furthermore, the identification of toxicity mechanisms and resistance determinants to weak acid-based pharmaceuticals increases current knowledge on their cytotoxic effects and may lead to the identification of new drug targets. This review integrates current knowledge on the mechanisms of toxicity and tolerance to weak acid stress obtained in the model eukaryote Saccharomyces cerevisiae using genome-wide approaches and more detailed gene-by-gene analysis. The major features of the yeast response to weak acids in general, and the more specific responses and resistance mechanisms towards a specific weak acid or a group of weak acids, depending on the chemical nature of the side chain R group (R-COOH), are highlighted. The involvement of several transcriptional regulatory networks in the genomic response to different weak acids is discussed, focusing on the regulatory pathways controlled by the transcription factors Msn2p/Msn4p, War1p, Haa1p, Rim101p, and Pdr1p/Pdr3p, which are known to orchestrate weak acid stress response in yeast. The extrapolation of the knowledge gathered in yeast to other eukaryotes is also attempted.

Drug:H+ antiporters in chemical stress response in yeast

The emergence of widespread multidrug resistance (MDR) is a serious challenge for therapeutics, food-preservation and crop protection. Frequently, MDR is a result of the action of drug-efflux pumps, which are able to catalyze the extrusion of unrelated chemical compounds. This review summarizes the current knowledge on the Saccharomyces cerevisiae drug:H+ antiporters of the major facilitator superfamily (MFS), a group of MDR transporters that is still characterized poorly in eukaryotes. Particular focus is given here to the physiological role and expression regulation of these transporters, while we provide a unified view of new data emerging from functional genomics approaches. Although traditionally described as drug pumps, evidence reviewed here corroborates the hypothesis that several MFS-MDR transporters might have a natural substrate and that drug transport might occur only fortuitously or opportunistically. Their role in MDR might even result from the transport of endogenous metabolites that affect the partition of cytotoxic compounds indirectly. Finally, the extrapolation of the gathered knowledge on the MDR phenomenon in yeast to pathogenic fungi and higher eukaryotes is discussed.

The Pht1;9 and Pht1;8 transporters mediate inorganic phosphate acquisition by the Arabidopsis thaliana root during phosphorus starvation

• The activation of high-affinity root transport systems is the best-conserved strategy employed by plants to cope with low inorganic phosphate (Pi) availability, a role traditionally assigned to Pi transporters of the Pht1 family, whose respective contributions to Pi acquisition remain unclear. • To characterize the Arabidopsis thaliana Pht1;9 transporter, we combined heterologous functional expression in yeast with expression/subcellular localization studies and reverse genetics approaches in planta. Double Pht1;9/Pht1;8 silencing lines were also generated to gain insight into the role of the closest Pht1;9 homolog. • Pht1;9 encodes a functional plasma membrane-localized transporter that mediates high-affinity Pi/H⁺ symport activity in yeast and is highly induced in Pi-starved Arabidopsis roots. Null pht1;9 alleles exhibit exacerbated responses to prolonged Pi limitation and enhanced tolerance to arsenate exposure, whereas Pht1;9 overexpression induces the opposite phenotypes. Strikingly, Pht1;9/Pht1;8 silencing lines display more pronounced defects than the pht1;9 mutants. • Pi and arsenic plant content analyses confirmed a role of Pht1;9 in Pi acquisition during Pi starvation and arsenate uptake at the root-soil interface. Although not affecting plant internal Pi repartition, Pht1;9 activity influences the overall Arabidopsis Pi status. Finally, our results indicate that both the Pht1;9 and Pht1;8 transporters function in sustaining plant Pi supply on environmental Pi depletion.

A Major Facilitator Superfamily Transporter Plays a Dual Role in Polar Auxin Transport and Drought Stress Tolerance in Arabidopsis

Two plant isoforms, produced by alternative splicing, of a single membrane transporter from the large Major Facilitator Superfamily possess the same transport activity but distinct tissue and subcellular distribution, thereby allowing this transporter to fulfill two very different physiological functions in drought stress tolerance and root hormonal transport. Many key aspects of plant development are regulated by the polarized transport of the phytohormone auxin. Cellular auxin efflux, the rate-limiting step in this process, has been shown to rely on the coordinated action of PIN-formed (PIN) and B-type ATP binding cassette (ABCB) carriers. Here, we report that polar auxin transport in the Arabidopsis thaliana root also requires the action of a Major Facilitator Superfamily (MFS) transporter, Zinc-Induced Facilitator-Like 1 (ZIFL1). Sequencing, promoter-reporter, and fluorescent protein fusion experiments indicate that the full-length ZIFL1.1 protein and a truncated splice isoform, ZIFL1.3, localize to the tonoplast of root cells and the plasma membrane of leaf stomatal guard cells, respectively. Using reverse genetics, we show that the ZIFL1.1 transporter regulates various root auxin-related processes, while the ZIFL1.3 isoform mediates drought tolerance by regulating stomatal closure. Auxin transport and immunolocalization assays demonstrate that ZIFL1.1 indirectly modulates cellular auxin efflux during shootward auxin transport at the root tip, likely by regulating plasma membrane PIN2 abundance. Finally, heterologous expression in yeast revealed that ZIFL1.1 and ZIFL1.3 share H+-coupled K+ transport activity. Thus, by determining the subcellular and tissue distribution of two isoforms, alternative splicing dictates a dual function for the ZIFL1 transporter. We propose that this MFS carrier regulates stomatal movements and polar auxin transport by modulating potassium and proton fluxes in Arabidopsis cells.

Identification of Regulatory Modules in Time Series Gene Expression Data Using a Linear Time Biclustering Algorithm

Although most biclustering formulations are NP-hard, in time series expression data analysis, it is reasonable to restrict the problem to the identification of maximal biclusters with contiguous columns, which correspond to coherent expression patterns shared by a group of genes in consecutive time points. This restriction leads to a tractable problem. We propose an algorithm that finds and reports all maximal contiguous column coherent biclusters in time linear in the size of the expression matrix. The linear time complexity of CCC-Biclustering relies on the use of a discretized matrix and efficient string processing techniques based on suffix trees. We also propose a method for ranking biclusters based on their statistical significance and a methodology for filtering highly overlapping and, therefore, redundant biclusters. We report results in synthetic and real data showing the effectiveness of the approach and its relevance in the discovery of regulatory modules. Results obtained using the transcriptomic expression patterns occurring in Saccharomyces cerevisiae in response to heat stress show not only the ability of the proposed methodology to extract relevant information compatible with documented biological knowledge but also the utility of using this algorithm in the study of other environmental stresses and of regulatory modules in general.