Functional dissection of IME1 transcription using quantitative promoter-reporter screening.

Transcriptional regulation is a key mechanism that controls the fate and response of cells to diverse signals. Therefore, the identification of the DNA-binding proteins, which mediate these signals, is a crucial step in elucidating how cell fate is regulated. In this report, we applied both bioinformatics and functional genomic approaches to scrutinize the unusually large promoter of the IME1 gene in budding yeast. Using a recently described fluorescent protein-based reporter screen, reporter-synthetic genetic array (R-SGA), we assessed the effect of viable deletion mutants on transcription of various IME1 promoter-reporter genes. We discovered potential transcription factors, many of which have no perfect consensus site within the IME1 promoter. Moreover, most of the cis-regulatory sequences with perfect homology to known transcription factor (TF) consensus were found to be nonfunctional in the R-SGA analysis. In addition, our results suggest that lack of conservation may not discriminate against a TF regulatory role at a specific promoter. We demonstrate that Sum1 and Sok2, which regulate IME1, bind to nonperfect consensuses within nonconserved regions in the sensu stricto Saccharomyces strains. Our analysis supports the view that although comparative analysis can provide a useful guide, functional assays are required for accurate identification of TF-binding site interactions in complex promoters.

Deciphering protein kinase specificity through large-scale analysis of yeast phosphorylation site motifs.

Phosphorylation is a universal mechanism for regulating cell behavior in eukaryotes. Although protein kinases target short linear sequence motifs on their substrates, the rules for kinase substrate recognition are not completely understood. We used a rapid peptide screening approach to determine consensus phosphorylation site motifs targeted by 61 of the 122 kinases in Saccharomyces cerevisiae. By correlating these motifs with kinase primary sequence, we uncovered previously unappreciated rules for determining specificity within the kinase family, including a residue determining P-3 arginine specificity among members of the CMGC [CDK (cyclin-dependent kinase), MAPK (mitogen-activated protein kinase), GSK (glycogen synthase kinase), and CDK-like] group of kinases. Furthermore, computational scanning of the yeast proteome enabled the prediction of thousands of new kinase-substrate relationships. We experimentally verified several candidate substrates of the Prk1 family of kinases in vitro and in vivo and identified a protein substrate of the kinase Vhs1. Together, these results elucidate how kinase catalytic domains recognize their phosphorylation targets and suggest general avenues for the identification of previously unknown kinase substrates across eukaryotes.

Dual regulation by pairs of cyclin-dependent protein kinases and histone deacetylases controls G1 transcription in budding yeast.

START-dependent transcription in Saccharomyces cerevisiae is regulated by two transcription factors SBF and MBF, whose activity is controlled by the binding of the repressor Whi5. Phosphorylation and removal of Whi5 by the cyclin-dependent kinase (CDK) Cln3-Cdc28 alleviates the Whi5-dependent repression on SBF and MBF, initiating entry into a new cell cycle. This Whi5-SBF/MBF transcriptional circuit is analogous to the regulatory pathway in mammalian cells that features the E2F family of G1 transcription factors and the retinoblastoma tumor suppressor protein (Rb). Here we describe genetic and biochemical evidence for the involvement of another CDK, Pcl-Pho85, in regulating G1 transcription, via phosphorylation and inhibition of Whi5. We show that a strain deleted for both PHO85 and CLN3 has a slow growth phenotype, a G1 delay, and is severely compromised for SBF-dependent reporter gene expression, yet all of these defects are alleviated by deletion of WHI5. Our biochemical and genetic tests suggest Whi5 mediates repression in part through interaction with two histone deacetylases (HDACs), Hos3 and Rpd3. In a manner analogous to cyclin D/CDK4/6, which phosphorylates Rb in mammalian cells disrupting its association with HDACs, phosphorylation by the early G1 CDKs Cln3-Cdc28 and Pcl9-Pho85 inhibits association of Whi5 with the HDACs. Contributions from multiple CDKs may provide the precision and accuracy necessary to activate G1 transcription when both internal and external cues are optimal.

Reporter-based synthetic genetic array analysis: a functional genomics approach for investigating the cell cycle in Saccharomyces cerevisiae.

Temporal control of gene expression is a widespread feature of cell cycles, with clear transcriptional programs in bacteria, yeast, and metazoans. In budding yeast, approximately 1,000 genes are transcribed during a specific interval of the cell cycle. Although a number of factors that contribute to this periodic pattern of gene expression have been studied in Saccharomyces cerevisiae, pathways of cell cycle-regulated transcription remain largely undefined. To identify regulators of genes exhibiting cell cycle periodicity, we have developed a functional genomics approach termed reporter-based synthetic genetic array (R-SGA) analysis. Based on synthetic genetic array (SGA) analysis, R-SGA allows rapid and easily automated incorporation of a cell cycle reporter gene into the array of viable haploid yeast gene-deletion mutants. Scoring of reporter activity in mutant strains compared to wild type identifies candidate regulators of the cell cycle gene of interest. In contrast to microarrays, which generally provide information about the expression of all genes under a particular condition (for example, a single gene deletion), R-SGA analysis facilitates the study of the expression of a single gene in all deletion mutants. Our system can be adapted to examine the expression of any gene not only in the context of haploid deletion mutants but also using other array-based strain collections available to the yeast community.

Comprehensive genetic analysis of transcription factor pathways using a dual reporter gene system in budding yeast.

The development and application of genomic reagents and techniques has fuelled progress in our understanding of regulatory networks that control gene expression in eukaryotic cells. However, a full description of the network of regulator-gene interactions that determine global gene expression programs remains elusive and will require systematic genetic as well as biochemical assays. Here, we describe a functional genomics approach that combines reporter technology, genome-wide array-based reagents and high-throughput imaging to discover new regulators controlling gene expression patterns in Saccharomyces cerevisiae. Our strategy utilizes the synthetic genetic array (SGA) method to systematically introduce promoter-GFP (green fluorescent protein) reporter constructs along with a control promoter-RFP (red fluorescent protein) gene into the array of approximately 4500 viable yeast deletion mutants. Fluorescence intensities from each reporter are assayed from individual colonies arrayed on solid agar plates using a scanning fluorimager and the ratio of GFP to RFP intensity reveals deletion mutants that cause differential GFP expression. We are exploiting this screening approach to construct a detailed map describing the interplay of regulators controlling the eukaryotic cell cycle. The method is extensible to any transcription factor or signalling pathway for which an appropriate reporter gene can be devised.

Gene CATCHR--gene cloning and tagging for Caenorhabditis elegans using yeast homologous recombination: a novel approach for the analysis of gene expression.

Expression patterns of gene products provide important insights into gene function. Reporter constructs are frequently used to analyze gene expression in Caenorhabditis elegans, but the sequence context of a given gene is inevitably altered in such constructs. As a result, these transgenes may lack regulatory elements required for proper gene expression. We developed Gene Catchr, a novel method of generating reporter constructs that exploits yeast homologous recombination (YHR) to subclone and tag worm genes while preserving their local sequence context. YHR facilitates the cloning of large genomic regions, allowing the isolation of regulatory sequences in promoters, introns, untranslated regions and flanking DNA. The endogenous regulatory context of a given gene is thus preserved, producing expression patterns that are as accurate as possible. Gene Catchr is flexible: any tag can be inserted at any position without introducing extra sequence. Each step is simple and can be adapted to process multiple genes in parallel. We show that expression patterns derived from Gene Catchr transgenes are consistent with previous reports and also describe novel expression data. Mutant rescue assays demonstrate that Gene Catchr-generated transgenes are functional. Our results validate the use of Gene Catchr as a valuable tool to study spatiotemporal gene expression.

Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry.

The recent abundance of genome sequence data has brought an urgent need for systematic proteomics to decipher the encoded protein networks that dictate cellular function. To date, generation of large-scale protein-protein interaction maps has relied on the yeast two-hybrid system, which detects binary interactions through activation of reporter gene expression. With the advent of ultrasensitive mass spectrometric protein identification methods, it is feasible to identify directly protein complexes on a proteome-wide scale. Here we report, using the budding yeast Saccharomyces cerevisiae as a test case, an example of this approach, which we term high-throughput mass spectrometric protein complex identification (HMS-PCI). Beginning with 10% of predicted yeast proteins as baits, we detected 3,617 associated proteins covering 25% of the yeast proteome. Numerous protein complexes were identified, including many new interactions in various signalling pathways and in the DNA damage response. Comparison of the HMS-PCI data set with interactions reported in the literature revealed an average threefold higher success rate in detection of known complexes compared with large-scale two-hybrid studies. Given the high degree of connectivity observed in this study, even partial HMS-PCI coverage of complex proteomes, including that of humans, should allow comprehensive identification of cellular networks.