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

Ptc6 is required for proper rapamycin-induced down-regulation of the genes coding for ribosomal and rRNA processing proteins in S. cerevisiae

Ptc6 is one of the seven components (Ptc1-Ptc7) of the protein phosphatase 2C family in the yeast Saccharomyces cerevisiae. In contrast to other type 2C phosphatases, the cellular role of this isoform is poorly understood. We present here a comprehensive characterization of this gene product. Cells lacking Ptc6 are sensitive to zinc ions, and somewhat tolerant to cell-wall damaging agents and to Li+. Ptc6 mutants are sensitive to rapamycin, albeit to lesser extent than ptc1 cells. This phenotype is not rescued by overexpression of PTC1 and mutation of ptc6 does not reproduce the characteristic geneti

MHO1, an Evolutionarily Conserved Gene, Is Synthetic Lethal with PLC1; Mho1p Has a Role in Invasive Growth

The novel protein Memo (Mediator of ErbB2 driven cell motility) was identified in a screen for ErbB2 interacting proteins and found to have an essential function in cell motility. Memo is evolutionarily conserved with homologs found in all branches of life; the human and yeast proteins have a similarity of >50%. In the present study we used the model organism S. cerevisiae to characterize the Memo-homologue Mho1 (Yjr008wp) and to investigate its function in yeast. In a synthetic lethal screen we found MHO1 as a novel synthetic lethal partner of PLC1, which encodes the single phospholipase C in yeast. Double-deleted cells lacking MHO1 and PLC1, proliferate for up to ten generations. Introduction of human Memo into the memoΔplc1Δ strain rescued the synthetic lethal phenotype suggesting that yeast and human proteins have similar functions. Mho1 is present in the cytoplasm and the nucleus of yeast cells; the same distribution of Memo was found in mammalian cells. None of the Memo homologues have a characteristic nuclear localization sequence, however, a conserved nuclear export sequence is found in all. In mammalian cells, blocking nuclear export with Leptomycin B led to nuclear Memo accumulation, suggesting that it is actively exported from the nucleus. In yeast MHO1 expression is induced by stress conditions. Since invasive growth in S. cerevisiea is also stress-induced, we tested Mho1's role in this response. MHO1 deletion had no effect on invasion induced by nutrient deprivation, however, Mho1 overexpression blocked the invasive ability of yeast cells, suggesting that Mho1 might be acting in a dominant negative manner. Taken together, our results show that MHO1 is a novel synthetic lethal interactor with PLC1, and that both gene products are required for proliferation. Moreover, a role for Memo in cell motility/invasion appears to be conserved across species

Identification of novel targets for breast cancer by exploring gene switches on a genome scale

<p>Abstract</p> <p>Background</p> <p>An important feature that emerges from analyzing gene regulatory networks is the "switch-like behavior" or "bistability", a dynamic feature of a particular gene to preferentially toggle between two steady-states. The state of gene switches plays pivotal roles in cell fate decision, but identifying switches has been difficult. Therefore a challenge confronting the field is to be able to systematically identify gene switches.</p> <p>Results</p> <p>We propose a top-down mining approach to exploring gene switches on a genome-scale level. Theoretical analysis, proof-of-concept examples, and experimental studies demonstrate the ability of our mining approach to identify bistable genes by sampling across a variety of different conditions. Applying the approach to human breast cancer data identified genes that show bimodality within the cancer samples, such as estrogen receptor (ER) and ERBB2, as well as genes that show bimodality between cancer and non-cancer samples, where tumor-associated calcium signal transducer 2 (TACSTD2) is uncovered. We further suggest a likely transcription factor that regulates TACSTD2.</p> <p>Conclusions</p> <p>Our mining approach demonstrates that one can capitalize on genome-wide expression profiling to capture dynamic properties of a complex network. To the best of our knowledge, this is the first attempt in applying mining approaches to explore gene switches on a genome-scale, and the identification of TACSTD2 demonstrates that single cell-level bistability can be predicted from microarray data. Experimental confirmation of the computational results suggest TACSTD2 could be a potential biomarker and attractive candidate for drug therapy against both ER+ and ER- subtypes of breast cancer, including the triple negative subtype.</p

Genome-wide single-cell-level screen for protein abundance and localization changes in response to DNA damage in S. cerevisiae

An effective response to DNA damaging agents involves modulating numerous facets of cellular homeostasis in addition to DNA repair and cell-cycle checkpoint pathways. Fluorescence microscopy-based imaging offers the opportunity to simultaneously interrogate changes in both protein level and subcellular localization in response to DNA damaging agents at the single-cell level. We report here results from screening the yeast Green Fluorescent Protein (GFP)-fusion library to investigate global cellular protein reorganization on exposure to the alkylating agent methyl methanesulfonate (MMS). Broad groups of induced, repressed, nucleus- and cytoplasm-enriched proteins were identified. Gene Ontology and interactome analyses revealed the underlying cellular processes. Transcription factor (TF) analysis identified principal regulators of the response, and targets of all major stress-responsive TFs were enriched amongst the induced proteins. An unexpected partitioning of biological function according to the number of TFs targeting individual genes was revealed. Finally, differential modulation of ribosomal proteins depending on methyl methanesulfonate dose was shown to correlate with cell growth and with the translocation of the Sfp1 TF. We conclude that cellular responses can navigate different routes according to the extent of damage, relying on both expression and localization changes of specific proteins.National Cancer Institute (U.S.) (R01-CA055042 (now NIEHS R01-ES022872))Massachusetts Institute of Technology. Center for Environmental Health Sciences (Grant NIEHS P30-ES002109)National Cancer Institute (U.S.) (KI Center Grant U54-CA112967)National Cancer Institute (U.S.) (Cancer Center Support Grant P30-CA14051)National Institute of Environmental Health Sciences (R01-ES022872)MIT Faculty Start-up FundMassachusetts Institute of Technology. Computational and Systems Biology Initiative (Merck & Co. Postdoctoral Fellowship