Multiple cis-regulatory elements and the yeast sulphur regulatory network are required for the regulation of the yeast glutathione transporter, Hgt1p.
ABSTRACT HGT1 encodes a high-affinity glutathione transporter in the yeast Saccharomyces cerevisiae that is induced under sulphur limitation. The present work demonstrates that repression by organic sulphur sources is under the control of the classic sulphur regulatory network, as seen by the absence of expression in a met4delta background. Cysteine appeared to be the principal regulatory molecule, since elevated levels were seen in str4delta strains (deficient in cysteine biosynthesis) that could be repressed by elevated levels of cysteine, but not by methionine or glutathione. Investigations into cis-regulatory elements revealed that the previously described motif, a 9-bp cis element, CCGCCACAC, located at the -356 to -364 region of the promoter could in fact be refined to a 7-bp CGCCACA motif that is also repeated at -333 to -340. The second copy of this motif was essential for activity, since mutations in the core region of the second copy completely abolished activity and regulation by sulphur sources. Activity, but not regulation, could be restored by reintroducing an additional copy upstream of the first copy. A third region, GCCGTCTGCAAGGCA, conserved in the HGT1 promoters of the different Saccharomyces spp, was observed at -300 to -285 but, while mutations in this region did not lead to any loss in repression, the basal and induced levels were significantly increased. In contrast to a previous report, no evidence was found for regulation by the VDE endonuclease. The strong repression at the transport level by glutathione seen in strains overexpressing HGT1 was due to a glutathione-dependent toxicity in these cells.
Article: Identification of eukaryotic promoter regulatory elements using nonhomologous random recombination.[show abstract] [hide abstract]
ABSTRACT: Understanding the regulatory logic of a eukaryotic promoter requires the elucidation of the regulatory elements within that promoter. Current experimental or computational methods to discover regulatory motifs within a promoter can be labor intensive and may miss redundant, unprecedented or weakly activating elements. We have developed an unbiased combinatorial approach to rapidly identify new upstream activating sequences (UASs) in a promoter. This approach couples nonhomologous random recombination with an in vivo screen to efficiently identify UASs and does not rely on preconceived hypotheses about promoter regulation or on similarity to known activating sequences. We validated this method using the unfolded protein response (UPR) in yeast and were able to identify both known and potentially novel UASs involved in the UPR. One of the new UASs discovered using this approach implicates Crz1 as a possible activator of Hac1, a transcription factor involved in the UPR. This method has several advantages over existing methods for UAS discovery including its speed, potential generality, sensitivity and lack of false positives and negatives.Nucleic Acids Research 02/2007; 35(17):5851-60. · 8.03 Impact Factor
Article: ScerTF: a comprehensive database of benchmarked position weight matrices for Saccharomyces species.[show abstract] [hide abstract]
ABSTRACT: Saccharomyces cerevisiae is a primary model for studies of transcriptional control, and the specificities of most yeast transcription factors (TFs) have been determined by multiple methods. However, it is unclear which position weight matrices (PWMs) are most useful; for the roughly 200 TFs in yeast, there are over 1200 PWMs in the literature. To address this issue, we created ScerTF, a comprehensive database of 1226 motifs from 11 different sources. We identified a single matrix for each TF that best predicts in vivo data by benchmarking matrices against chromatin immunoprecipitation and TF deletion experiments. We also used in vivo data to optimize thresholds for identifying regulatory sites with each matrix. To correct for biases from different methods, we developed a strategy to combine matrices. These aligned matrices outperform the best available matrix for several TFs. We used the matrices to predict co-occurring regulatory elements in the genome and identified many known TF combinations. In addition, we predict new combinations and provide evidence of combinatorial regulation from gene expression data. The database is available through a web interface at http://ural.wustl.edu/ScerTF. The site allows users to search the database with a regulatory site or matrix to identify the TFs most likely to bind the input sequence.Nucleic Acids Research 12/2011; 40(Database issue):D162-8. · 8.03 Impact Factor