A genome-wide screen for site-specific DNA-binding proteins

CisMiner: genome-wide in-silico cis-regulatory module prediction by fuzzy itemset mining

Eukaryotic gene control regions are known to be spread throughout non-coding DNA sequences which may appear distant from the gene promoter. Transcription factors are proteins that coordinately bind to these regions at transcription factor binding sites to regulate gene expression. Several tools allow to detect significant co-occurrences of closely located binding sites (cis-regulatory modules, CRMs). However, these tools present at least one of the following limitations: 1) scope limited to promoter or conserved regions of the genome; 2) do not allow to identify combinations involving more than two motifs; 3) require prior information about target motifs. In this work we present CisMiner, a novel methodology to detect putative CRMs by means of a fuzzy itemset mining approach able to operate at genome-wide scale. CisMiner allows to perform a blind search of CRMs without any prior information about target CRMs nor limitation in the number of motifs. CisMiner tackles the combinatorial complexity of genome-wide cis-regulatory module extraction using a natural representation of motif combinations as itemsets and applying the Top-Down Fuzzy Frequent- Pattern Tree algorithm to identify significant itemsets. Fuzzy technology allows CisMiner to better handle the imprecision and noise inherent to regulatory processes. Results obtained for a set of well-known binding sites in the S. cerevisiae genome show that our method yields highly reliable predictions. Furthermore, CisMiner was also applied to putative in-silico predicted transcription factor binding sites to identify significant combinations in S. cerevisiae and D. melanogaster, proving that our approach can be further applied genome-wide to more complex genomes. CisMiner is freely accesible at: http://genome2.ugr.es/cisminer. CisMiner can be queried for the results presented in this work and can also perform a customized cis-regulatory module prediction on a query set of transcription factor binding sites provided by the user.

Natural variation in the yeast glucose-signaling network reveals a new role for the Mig3p transcription factor

The Crabtree effect, in which fermentative metabolism is preferred at the expense of respiration, is a hallmark of budding yeast's glucose response and a model for the Warburg effect in human tumors. While the glucose-responsive transcriptional repressors Mig1p and Mig2p play well-characterized roles in the Crabtree effect, little function for the related Mig3p transcription factor has been uncovered, despite numerous investigations of laboratory yeast strains. Here we studied a wild isolate of Saccharomyces cerevisiae to uncover a critical role for Mig3p that has been lost in S288c-derived laboratory strains. We found that Mig3p affects the expression of hundreds of glucose-responsive genes in the oak strain YPS163, both during growth under standard conditions and upon ethanol treatment. Our results suggest that Mig3p may act as a multifunctional activator/repressor that plays separate roles under standard vs. stress conditions and that this function has been largely lost in the lab strains. Population analysis suggests that the lab strain and several wild strains harbor mutations that diminish Mig3p function. Thus, by expanding our attention to multiple genetic backgrounds, we have uncovered an important missing link in a key metabolic response.

VpWRKY3, a biotic and abiotic stress-related transcription factor from the Chinese wild Vitis pseudoreticulata

Chinese wild grapevine Vitis pseudoreticulata accession 'Baihe-35-1' is identified as the precious resource with multiple resistances to pathogens. A directional cDNA library was constructed from the young leaves inoculated with Erysiphe necator. A total of 3,500 clones were sequenced, yielding 1,727 unigenes. Among them, 762 unigenes were annotated and classified into three classes, respectively, using Gene Ontology, including 22 ESTs related to transcription regulator activity. A novel WRKY transcription factor was isolated from the library, and designated as VpWRKY3 (GenBank Accession No. JF500755). The full-length cDNA is 1,280 bp, encoding a WRKY protein of 320 amino acids. VpWRKY3 is localized to nucleus and functions as a transcriptional activator. QRT-PCR analysis showed that the VpWRKY3 specifically accumulated in response to pathogen, salicylic acid, ethylene and drought stress. Overexpression of VpWRKY3 in tobacco increased the resistance to Ralstonia solanacearum, indicating that VpWRKY3 participates in defense response. Furthermore, VpWRKY3 is also involved in abscisic acid signal pathway and salt stress. This experiment provided an important basis for understanding the defense mechanisms mediated by WRKY genes in China wild grapevine. Generation of the EST collection from the cDNA library provided valuable information for the grapevine breeding. Key message We constructed a cDNA library from Chinese wild grapevine leaves inoculated with powdery mildew. VpWRKY3 was isolated and demonstrated that it was involved in biotic and abiotic stress responses.

Proteome-Scale Analysis of Biochemical Activity

During the last 10 years, there has been a large increase in the number of genome sequences available for study, altering the way that the biology of organisms is studied. In particular, scientific attention has increasingly focused on the proteome, and specifically on the role of all the proteins encoded by the genome. We focus here on several aspects of this problem. We describe several technologies in widespread use to clone genes on a genome-wide scale, and to express and purify the proteins encoded by these genes. We also describe a number of methods that have been developed to analyze various biochemical properties of the proteins, with attention to the methodology and the limitations of the approaches, followed by a look at possible developments in the next decade.

Modern tools for identification of nucleic acid-binding proteins

Numerous biological mechanisms depend on nucleic acid--protein interactions. The first step to the understanding of these mechanisms is to identify interacting molecules. Knowing one partner, the identification of other associated molecular species can be carried out using affinity-based purification procedures. When the nucleic acid-binding protein is known, the nucleic acid can be isolated and identified by sensitive techniques such as polymerase chain reaction followed by DNA sequencing or hybridization on chips. The reverse identification procedure is less straightforward in part because interesting nucleic acid-binding proteins are generally of low abundance and there are no methods to amplify amino acid sequences. In this article, we will review the strategies that have been developed to identify nucleic acid-binding proteins. We will focus on methods permitting the identification of these proteins without a priori knowledge of protein candidates.

Stb3 binds to ribosomal RNA processing element motifs that control transcriptional responses to growth in Saccharomyces cerevisiae

Transfer of quiescent Saccharomyces cerevisiae cells to fresh medium rapidly induces hundreds of genes needed for growth. A large subset of these genes is regulated via a DNA sequence motif known as the ribosomal RNA processing element (RRPE). However, no RRPE-binding proteins have been identified. We screened a panel of 6144 glutathione S-transferase-open reading frame fusions for RRPE-binding proteins and identified Stb3 as a specific RRPE-binding protein, both in vitro and in vivo. Chromatin immunoprecipitation experiments showed that glucose increases Stb3 binding to RRPE-containing promoters. Microarray experiments demonstrated that the loss of Stb3 inhibits the transcriptional response to fresh glucose, especially for genes with RRPE motifs. However, these experiments also showed that not all genes containing RRPEs were dependent on Stb3 for expression. Overall our data support a model in which Stb3 plays an important but not exclusive role in the transcriptional response to growth conditions.

Different signalling pathways mediate glucose induction of SUC2, HXT1 and pyruvate decarboxylase in yeast

The glucose sensors Gpr1, Snf3 and Rgt2 generate the earliest signals produced by glucose in yeast. We showed that a lack of Gpr1 or Snf3/Rgt2 decreased by twofold the glucose induction of SUC2, but had no effect on the induction of pyruvate decarboxylase (Pdc). The induction of HXT1 was not affected by the absence of Gpr1. In an hxk1 hxk2 glk1 strain, high glucose fully induced SUC2, caused partial induction of HXT1 and had no effect on Pdc. In this strain, SUC2 induction was dependent on Gpr1, but HXT1 induction was not. Hxk2, required for the high expression of HXT1, was dispensable for the full induction of SUC2 or Pdc. These results indicate that glucose does not induce transcription through a single signalling pathway, but that several pathways may, in different combinations, regulate the transcription of different genes.

Identification and Characterization of Modification Enzymes by Biochemical Analysis of the Proteome

The use of proteomic libraries designed to express the complete set of proteins from an organism has resulted in the identification of many RNA modification enzymes whose function was previously unknown. Here we describe a generalized procedure for the biochemical analysis of a yeast proteomic library for identification of nucleic acid-modifying enzymes, by use of the yeast MORF (Moveable Open Reading Frame) library (Gelperin et al., 2005) as the source of protein activity, and the known yeast tRNA methyltransferase Trm4 as a test case. The procedures outlined in this chapter can be applied to any proteomic expression library from any organism, many of which will become increasingly available as the number of sequenced genomes increases and as genomic cloning techniques improve.

Glucose signaling in Saccharomyces cerevisiae

Eukaryotic cells possess an exquisitely interwoven and fine-tuned series of signal transduction mechanisms with which to sense and respond to the ubiquitous fermentable carbon source glucose. The budding yeast Saccharomyces cerevisiae has proven to be a fertile model system with which to identify glucose signaling factors, determine the relevant functional and physical interrelationships, and characterize the corresponding metabolic, transcriptomic, and proteomic readouts. The early events in glucose signaling appear to require both extracellular sensing by transmembrane proteins and intracellular sensing by G proteins. Intermediate steps involve cAMP-dependent stimulation of protein kinase A (PKA) as well as one or more redundant PKA-independent pathways. The final steps are mediated by a relatively small collection of transcriptional regulators that collaborate closely to maximize the cellular rates of energy generation and growth. Understanding the nuclear events in this process may necessitate the further elaboration of a new model for eukaryotic gene regulation, called "reverse recruitment." An essential feature of this idea is that fine-structure mapping of nuclear architecture will be required to understand the reception of regulatory signals that emanate from the plasma membrane and cytoplasm. Completion of this task should result in a much improved understanding of eukaryotic growth, differentiation, and carcinogenesis.

Biochemical and genetic analysis of the yeast proteome with a movable ORF collection

Functional analysis of the proteome is an essential part of genomic research. To facilitate different proteomic approaches, a MORF (moveable ORF) library of 5854 yeast expression plasmids was constructed, each expressing a sequence-verified ORF as a C-terminal ORF fusion protein, under regulated control. Analysis of 5573 MORFs demonstrates that nearly all verified ORFs are expressed, suggests the authenticity of 48 ORFs characterized as dubious, and implicates specific processes including cytoskeletal organization and transcriptional control in growth inhibition caused by overexpression. Global analysis of glycosylated proteins identifies 109 new confirmed N-linked and 345 candidate glycoproteins, nearly doubling the known yeast glycome.

SCFGrr1-mediated ubiquitination of Gis4 modulates glucose response in yeast

The F box protein Grr1 is the substrate specificity-determinant of the SCF(Grr1) E3 ubiquitin ligase complex. Genetic analyses of Grr1 mutants have implicated Grr1 in glucose repression, specifically with regard to expression of the SUC2 transcript. To better understand Grr1, we screened for substrates using a mutant version of Grr1 that should not associate with the SCF complex. We identified Gis4 as a novel Grr1 substrate. Gis4 was originally isolated as a multi-copy suppressor of a Gal--phenotype in the triple mutant snf1 mig1 srb8. Here, we show that Gis4 binds Grr1 in vivo and that Grr1 protein levels positively affect the protein levels of Gis4. The Gis4 protein is stable in wild-type cells and in grr1Delta cells; however, Gis4 is ubiquitinated in a Grr1-dependent manner. Furthermore, we show that Gis4 interacts with Snf1 in a Grr1-dependent fashion, and that Gis4 is involved in de-repression of SUC2 and in transcription of other Snf1-dependent transcripts. Gis4 appears to connect the glucose repression and de-repression pathways. We suggest that Gis4 may explain the glucose repression defects in carbon source metabolism for the grr1 mutants.

Elucidation of the role of Grr1p in glucose sensing by Saccharomyces cerevisiae through genome-wide transcription analysis

The role of Grr1p in glucose sensing in Saccharomyces cerevisiae was elucidated through genome-wide transcription analysis. From triplicate analysis of a strain with deletion of the GRR1-gene from the genome and an isogenic reference strain, 68 genes were identified to have significantly altered expression using a Student's t-test with Bonferroni correction. These 68 genes were widely distributed across different parts of the cellular metabolism and GRR1-deletion is therefore concluded to result in polytrophic effects, indicating multiple roles for Grr1p. Using a less conservative statistical test, namely the SAM test, 232 genes were identified as having significantly altered expression, and also these genes were widely distributed across different parts of the cellular metabolism. Promoter analyses on a genome-wide scale and on the genes with significant changes revealed an over-representation of DNA-binding motifs for the transcriptional regulators Mig1p and Rgt1p in the promoter region of the significantly altered genes, indicating that Grr1p plays an important role in the regulatory pathways that ultimately lead to transcriptional regulation by each of the components Mig1p and Rgt1p.

Charting gene regulatory networks: strategies, challenges and perspectives

One of the foremost challenges in the post-genomic era will be to chart the gene regulatory networks of cells, including aspects such as genome annotation, identification of cis-regulatory elements and transcription factors, information on protein-DNA and protein-protein interactions, and data mining and integration. Some of these broad sets of data have already been assembled for building networks of gene regulation. Even though these datasets are still far from comprehensive, and the approach faces many important and difficult challenges, some strategies have begun to make connections between disparate regulatory events and to foster new hypotheses. In this article we review several different genomics and proteomics technologies, and present bioinformatics methods for exploring these data in order to make novel discoveries.

Identifying combinatorial regulation of transcription factors and binding motifs

A novel method that integrates chromatin immunoprecipitation data with microarray expression data and combinatorial TF-motif analysis was used to systematically identify combinations of transcription factors and of motifs and to reconstruct a new combinatorial regulatory map of the yeast cell cycle.

Background

Combinatorial interaction of transcription factors (TFs) is important for gene regulation. Although various genomic datasets are relevant to this issue, each dataset provides relatively weak evidence on its own. Developing methods that can integrate different sequence, expression and localization data have become important.

Results

Here we use a novel method that integrates chromatin immunoprecipitation (ChIP) data with microarray expression data and with combinatorial TF-motif analysis. We systematically identify combinations of transcription factors and of motifs. The various combinations of TFs involved multiple binding mechanisms. We reconstruct a new combinatorial regulatory map of the yeast cell cycle in which cell-cycle regulation can be drawn as a chain of extended TF modules. We find that the pairwise combination of a TF for an early cell-cycle phase and a TF for a later phase is often used to control gene expression at intermediate times. Thus the number of distinct times of gene expression is greater than the number of transcription factors. We also see that some TF modules control branch points (cell-cycle entry and exit), and in the presence of appropriate signals they can allow progress along alternative pathways.

Conclusions

Combining different data sources can increase statistical power as demonstrated by detecting TF interactions and composite TF-binding motifs. The original picture of a chain of simple cell-cycle regulators can be extended to a chain of composite regulatory modules: different modules may share a common TF component in the same pathway or a TF component cross-talking to other pathways.

Zinc finger transcriptional activators of yeasts

Transcriptional transactivators are important proteins which in addition to controlling the cell regulatory circuitries, can be manipulated for various biotechnological processes. The latter is of great interest for non-conventional yeasts used for industrial purposes. To facilitate the identification of these transactivators, we have reanalyzed the "Génolevures" data (FEBS Lett. 487 (2000); http://cbi.labri.u-bordeaux.fr/Genolevures/) for the presence of zinc finger (Zf) proteins. After analysis of 239 RST ("random sequence tag") sequences, we describe in this paper 161 homologs of the Saccharomyces cerevisiae Zf proteins present in one or several of 13 different hemiascomyceteous yeasts. These partial sequences have been evaluated on different criteria such as percentage of identity of the proteins, synteny, detailed analysis of the Zf motif and flanking regions, and iterative BLASTs. They can be used to fetch the corresponding gene.

Identification of the yeast gene encoding the tRNA m1G methyltransferase responsible for modification at position 9

Methylation of tRNA at the N-1 position of guanosine to form m(1)G occurs widely in nature. It occurs at position 37 in tRNAs from all three kingdoms, and the methyltransferase that catalyzes this reaction is known from previous work of others to be critically important for cell growth in Escherichia coli and the yeast Saccharomyces cerevisiae. m(1)G is also widely found at position 9 in eukaryotic tRNAs, but the corresponding methyltransferase was unknown. We have used a biochemical genomics approach with a collection of purified yeast GST-ORF fusion proteins to show that m(1)G(9) formation of yeast tRNA(Gly) is associated with ORF YOL093w, named TRM10. Extracts lacking Trm10p have undetectable levels of m(1)G(9) methyltransferase activity but retain normal m(1)G(37) methyltransferase activity. Yeast Trm10p purified from E. coli quantitatively modifies the G(9) position of tRNA(Gly) in an S-adenosylmethionine-dependent fashion. Trm10p is responsible in vivo for most if not all m(1)G(9) modification of tRNAs, based on two results: tRNA(Gly) purified from a trm10-Delta/trm10-Delta strain is lacking detectable m(1)G; and a primer extension block occurring at m(1)G(9) is removed in trm10-Delta/trm10-Delta-derived tRNAs for all 9 m(1)G(9)-containing species that were testable by this method. There is no obvious growth defect of trm10-Delta/trm10-Delta strains. Trm10p bears no detectable resemblance to the yeast m(1)G(37) methyltransferase, Trm5p, or its orthologs. Trm10p homologs are found widely in eukaryotes and many archaea, with multiple homologs in several metazoans, including at least three in humans.

Protein analysis on a proteomic scale

The long-term challenge of proteomics is enormous: to define the identities, quantities, structures and functions of complete complements of proteins, and to characterize how these properties vary in different cellular contexts. One critical step in tackling this goal is the generation of sets of clones that express a representative of each protein of a proteome in a useful format, followed by the analysis of these sets on a genome-wide basis. Such studies enable genetic, biochemical and cell biological technologies to be applied on a systematic level, leading to the assignment of biochemical activities, the construction of protein arrays, the identification of interactions, and the localization of proteins within cellular compartments.