PhosphoGRID: a database of experimentally verified in vivo protein phosphorylation sites from the budding yeast Saccharomyces cerevisiae

Sit4p/PP6 regulates ER-to-Golgi traffic by controlling the dephosphorylation of COPII coat subunits

Previous studies show that the COPII coat is phosphorylated. The phosphorylated coat, however, cannot rebind to the ER to initiate a new round of vesicle budding. The present study shows that Sit4p/PP6, a Ser/Thr phosphatase, dephosphorylates the COPII coat. Consistent with a role in coat recycling, Sit4p/PP6 regulates ER-to-Golgi traffic.

Traffic from the endoplasmic reticulum (ER) to the Golgi complex is initiated when the activated form of the GTPase Sar1p recruits the Sec23p-Sec24p complex to ER membranes. The Sec23p-Sec24p complex, which forms the inner shell of the COPII coat, sorts cargo into ER-derived vesicles. The coat inner shell recruits the Sec13p-Sec31p complex, leading to coat polymerization and vesicle budding. Recent studies revealed that the Sec23p subunit sequentially interacts with three different binding partners to direct a COPII vesicle to the Golgi. One of these binding partners is the serine/threonine kinase Hrr25p. Hrr25p phosphorylates the COPII coat, driving the membrane-bound pool into the cytosol. The phosphorylated coat cannot rebind to the ER to initiate a new round of vesicle budding unless it is dephosphorylated. Here we screen all known protein phosphatases in yeast to identify one whose loss of function alters the cellular distribution of COPII coat subunits. This screen identifies the PP2A-like phosphatase Sit4p as a regulator of COPII coat dephosphorylation. Hyperphosphorylated coat subunits accumulate in the sit4Δ mutant in vivo. In vitro, Sit4p dephosphorylates COPII coat subunits. Consistent with a role in coat recycling, Sit4p and its mammalian orthologue, PP6, regulate traffic from the ER to the Golgi complex.

PhosphoChain: a novel algorithm to predict kinase and phosphatase networks from high-throughput expression data

MOTIVATION

Protein phosphorylation is critical for regulating cellular activities by controlling protein activities, localization and turnover, and by transmitting information within cells through signaling networks. However, predictions of protein phosphorylation and signaling networks remain a significant challenge, lagging behind predictions of transcriptional regulatory networks into which they often feed.

RESULTS

We developed PhosphoChain to predict kinases, phosphatases and chains of phosphorylation events in signaling networks by combining mRNA expression levels of regulators and targets with a motif detection algorithm and optional prior information. PhosphoChain correctly reconstructed ∼78% of the yeast mitogen-activated protein kinase pathway from publicly available data. When tested on yeast phosphoproteomic data from large-scale mass spectrometry experiments, PhosphoChain correctly identified ∼27% more phosphorylation sites than existing motif detection tools (NetPhosYeast and GPS2.0), and predictions of kinase-phosphatase interactions overlapped with ∼59% of known interactions present in yeast databases. PhosphoChain provides a valuable framework for predicting condition-specific phosphorylation events from high-throughput data.

AVAILABILITY

PhosphoChain is implemented in Java and available at http://virgo.csie.ncku.edu.tw/PhosphoChain/ or http://aitchisonlab.com/PhosphoChain

A calcineurin-dependent switch controls the trafficking function of α-arrestin Aly1/Art6

Proper regulation of plasma membrane protein endocytosis by external stimuli is required for cell growth and survival. In yeast, excess levels of certain nutrients induce endocytosis of the cognate permeases to prevent toxic accumulation of metabolites. The α-arrestins, a family of trafficking adaptors, stimulate ubiquitin-dependent and clathrin-mediated endocytosis by interacting with both a client permease and the ubiquitin ligase Rsp5. However, the molecular mechanisms that control α-arrestin function are not well understood. Here, we show that α-arrestin Aly1/Art6 is a phosphoprotein that specifically interacts with and is dephosphorylated by the Ca(2+)- and calmodulin-dependent phosphoprotein phosphatase calcineurin/PP2B. Dephosphorylation of Aly1 by calcineurin at a subset of phospho-sites is required for Aly1-mediated trafficking of the aspartic acid and glutamic acid transporter Dip5 to the vacuole, but it does not alter Rsp5 binding, ubiquitinylation, or stability of Aly1. In addition, dephosphorylation of Aly1 by calcineurin does not regulate the ability of Aly1 to promote the intracellular sorting of the general amino acid permease Gap1. These results suggest that phosphorylation of Aly1 inhibits its vacuolar trafficking function and, conversely, that dephosphorylation of Aly1 by calcineurin serves as a regulatory switch to promote Aly1-mediated trafficking to the vacuole.

Construction of protein phosphorylation networks by data mining, text mining and ontology integration: analysis of the spindle checkpoint

Knowledge representation of the role of phosphorylation is essential for the meaningful understanding of many biological processes. However, such a representation is challenging because proteins can exist in numerous phosphorylated forms with each one having its own characteristic protein–protein interactions (PPIs), functions and subcellular localization. In this article, we evaluate the current state of phosphorylation event curation and then present a bioinformatics framework for the annotation and representation of phosphorylated proteins and construction of phosphorylation networks that addresses some of the gaps in current curation efforts. The integrated approach involves (i) text mining guided by RLIMS-P, a tool that identifies phosphorylation-related information in scientific literature; (ii) data mining from curated PPI databases; (iii) protein form and complex representation using the Protein Ontology (PRO); (iv) functional annotation using the Gene Ontology (GO); and (v) network visualization and analysis with Cytoscape. We use this framework to study the spindle checkpoint, the process that monitors the assembly of the mitotic spindle and blocks cell cycle progression at metaphase until all chromosomes have made bipolar spindle attachments. The phosphorylation networks we construct, centered on the human checkpoint kinase BUB1B (BubR1) and its yeast counterpart MAD3, offer a unique view of the spindle checkpoint that emphasizes biologically relevant phosphorylated forms, phosphorylation-state–specific PPIs and kinase–substrate relationships. Our approach for constructing protein phosphorylation networks can be applied to any biological process that is affected by phosphorylation.

Database URL:http://www.yeastgenome.org/

The PhosphoGRID Saccharomyces cerevisiae protein phosphorylation site database: version 2.0 update

PhosphoGRID is an online database that curates and houses experimentally verified in vivo phosphorylation sites in the Saccharomyces cerevisiae proteome (www.phosphogrid.org). Phosphosites are annotated with specific protein kinases and/or phosphatases, along with the condition(s) under which the phosphorylation occurs and/or the effects on protein function. We report here an updated data set, including nine additional high-throughput (HTP) mass spectrometry studies. The version 2.0 data set contains information on 20 177 unique phosphorylated residues, representing a 4-fold increase from version 1.0, and includes 1614 unique phosphosites derived from focused low-throughput (LTP) studies. The overlap between HTP and LTP studies represents only ∼3% of the total unique sites, but importantly 45% of sites from LTP studies with defined function were discovered in at least two independent HTP studies. The majority of new phosphosites in this update occur on previously documented proteins, suggesting that coverage of phosphoproteins in the yeast proteome is approaching saturation. We will continue to update the PhosphoGRID data set, with the expectation that the integration of information from LTP and HTP studies will enable the development of predictive models of phosphorylation-based signaling networks.

Database URL:http://www.phosphogrid.org/

Assigning quantitative function to post-translational modifications reveals multiple sites of phosphorylation that tune yeast pheromone signaling output

Cell signaling systems transmit information by post-translationally modifying signaling proteins, often via phosphorylation. While thousands of sites of phosphorylation have been identified in proteomic studies, the vast majority of sites have no known function. Assigning functional roles to the catalog of uncharacterized phosphorylation sites is a key research challenge. Here we present a general approach to address this challenge and apply it to a prototypical signaling pathway, the pheromone response pathway in Saccharomyces cerevisiae. The pheromone pathway includes a mitogen activated protein kinase (MAPK) cascade activated by a G-protein coupled receptor (GPCR). We used published mass spectrometry-based proteomics data to identify putative sites of phosphorylation on pheromone pathway components, and we used evolutionary conservation to assign priority to a list of candidate MAPK regulatory sites. We made targeted alterations in those sites, and measured the effects of the mutations on pheromone pathway output in single cells. Our work identified six new sites that quantitatively tuned system output. We developed simple computational models to find system architectures that recapitulated the quantitative phenotypes of the mutants. Our results identify a number of putative phosphorylation events that contribute to adjust the input-output relationship of this model eukaryotic signaling system. We believe this combined approach constitutes a general means not only to reveal modification sites required to turn a pathway on and off, but also those required for more subtle quantitative effects that tune pathway output. Our results suggest that relatively small quantitative influences from individual phosphorylation events endow signaling systems with plasticity that evolution may exploit to quantitatively tailor signaling outcomes.

Computational phosphorylation site prediction in plants using random forests and organism-specific instance weights

MOTIVATION

Phosphorylation is the most important post-translational modification in eukaryotes. Although many computational phosphorylation site prediction tools exist for mammals, and a few were created specifically for Arabidopsis thaliana, none are currently available for other plants.

RESULTS

In this article, we propose a novel random forest-based method called PHOSFER (PHOsphorylation Site FindER) for applying phosphorylation data from other organisms to enhance the accuracy of predictions in a target organism. As a test case, PHOSFER is applied to phosphorylation sites in soybean, and we show that it more accurately predicts soybean sites than both the existing Arabidopsis-specific predictors, and a simpler machine-learning scheme that uses only known phosphorylation sites and non-phosphorylation sites from soybean. In addition to soybean, PHOSFER will be extended to other organisms in the near future.

Yeast protein phosphatase 2A-Cdc55 regulates the transcriptional response to hyperosmolarity stress by regulating Msn2 and Msn4 chromatin recruitment

We have identified Cdc55, a regulatory B subunit of protein phosphatase 2A (PP2A), as an essential activating factor for stress gene transcription in Saccharomyces cerevisiae. The presence of PP2A-Cdc55 is required for full activation of the environmental stress response mediated by the transcription factors Msn2 and Msn4. We show that PP2A-Cdc55 contributes to sustained nuclear accumulation of Msn2 and Msn4 during hyperosmolarity stress. PP2A-Cdc55 also enhances Msn2-dependent transactivation, required for extended chromatin recruitment of the transcription factor. We analyzed a possible direct regulatory role for PP2A-Cdc55 on the phosphorylation status of Msn2. Detailed mass spectrometric and genetic analysis of Msn2 showed that stress exposure causes immediate transient dephosphorylation of Msn2 which is not dependent on PP2A-Cdc55 activity. Furthermore, the Hog1 mitogen-activated protein kinase pathway activity is not influenced by PP2A-Cdc55. We therefore propose that the PP2A-Cdc55 phosphatase is not involved in cytosolic stress signal perception but is involved in a specific intranuclear mechanism to regulate Msn2 and Msn4 nuclear accumulation and chromatin association under stress conditions.

Yeast RNA polymerase III transcription factors and effectors

Recent data indicate that the well-defined transcription machinery of RNA polymerase III (Pol III) is probably more complex than commonly thought. In this review, we describe the yeast basal transcription factors of Pol III and their involvements in the transcription cycle. We also present a list of proteins detected on genes transcribed by Pol III (class III genes) that might participate in the transcription process. Surprisingly, several of these proteins are involved in RNA polymerase II transcription. Defining the role of these potential new effectors in Pol III transcription in vivo will be the challenge of the next few years. This article is part of a Special Issue entitled: Transcription by Odd Pols.

Systematic functional prioritization of protein posttranslational modifications

Protein function is often regulated by posttranslational modifications (PTMs), and recent advances in mass spectrometry have resulted in an exponential increase in PTM identification. However, the functional significance of the vast majority of these modifications remains unknown. To address this problem, we compiled nearly 200,000 phosphorylation, acetylation, and ubiquitination sites from 11 eukaryotic species, including 2,500 newly identified ubiquitylation sites for Saccharomyces cerevisiae. We developed methods to prioritize the functional relevance of these PTMs by predicting those that likely participate in cross-regulatory events, regulate domain activity, or mediate protein-protein interactions. PTM conservation within domain families identifies regulatory "hot spots" that overlap with functionally important regions, a concept that we experimentally validated on the HSP70 domain family. Finally, our analysis of the evolution of PTM regulation highlights potential routes for neutral drift in regulatory interactions and suggests that only a fraction of modification sites are likely to have a significant biological role.

Dissecting the gene network of dietary restriction to identify evolutionarily conserved pathways and new functional genes

Dietary restriction (DR), limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR–essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/). To dissect the interactions of DR–essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR–essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR–essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2) had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR–induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of multiple organisms led us to suggest that DR commonly suppresses translation, while stimulating an ancient reproduction-related process.

Dietary restriction has been shown to extend lifespan in diverse, evolutionarily distant species, yet its underlying mechanisms remain unknown. We first constructed a database of genes essential for the life-extending effects of dietary restriction in various model organisms and then studied their interactions using a variety of network and systems biology approaches. This enabled us to predict novel genes related to dietary restriction, which we validated experimentally in yeast. By comparing large-scale data compilations (interactomes and transcriptomes) from multiple organisms, we were able to condense this -omics information to the most conserved essential elements, eliminating species-specific adaptive responses. These results lead us to the rather surprising conclusion that lifespan extension by a restricted diet commonly may exploit an ancient rejuvenation process derived from gametogenesis.

Network evolution: rewiring and signatures of conservation in signaling

The analysis of network evolution has been hampered by limited availability of protein interaction data for different organisms. In this study, we investigate evolutionary mechanisms in Src Homology 3 (SH3) domain and kinase interaction networks using high-resolution specificity profiles. We constructed and examined networks for 23 fungal species ranging from Saccharomyces cerevisiae to Schizosaccharomyces pombe. We quantify rates of different rewiring mechanisms and show that interaction change through binding site evolution is faster than through gene gain or loss. We found that SH3 interactions evolve swiftly, at rates similar to those found in phosphoregulation evolution. Importantly, we show that interaction changes are sufficiently rapid to exhibit saturation phenomena at the observed timescales. Finally, focusing on the SH3 interaction network, we observe extensive clustering of binding sites on target proteins by SH3 domains and a strong correlation between the number of domains that bind a target protein (target in-degree) and interaction conservation. The relationship between in-degree and interaction conservation is driven by two different effects, namely the number of clusters that correspond to interaction interfaces and the number of domains that bind to each cluster leads to sequence specific conservation, which in turn results in interaction conservation. In summary, we uncover several network evolution mechanisms likely to generalize across peptide recognition modules.

Protein interaction networks control virtually all cellular processes. The rules governing their evolution have remained elusive, as comprehensive protein interaction data is available for only a small number of very distant species, making evolutionary network studies difficult. Here we attempt to overcome this limitation by computationally constructing protein interaction networks for 23 relatively tightly spaced yeast species. We focus on networks consisting of kinase and peptide binding domain interactions, which play central roles in signaling pathways. These networks enable us to investigate evolutionary network mechanisms. We are able, for the first time, to accurately quantify the contribution of different rewiring mechanisms. Interaction change appears to be mainly accomplished through binding site evolution rather than through gene gain or loss. This is in contrast to other evolutionary processes, where gene duplication or deletion is a major driving factor. Moreover, our analysis reveals that interaction changes are very fast – fast enough that the number of changes saturates, i.e., the actual rate of change has been strongly underestimated in previous studies. Our analysis also reveals different mechanisms by which certain interactions are conserved throughout evolution. Our results likely transfer to other species and networks, and will benefit future evolutionary studies of signaling pathways.

Predicting kinase substrates using conservation of local motif density

MOTIVATION

Protein kinases represent critical links in cell signaling. A central problem in computational biology is to systematically identify their substrates.

RESULTS

This study introduces a new method to predict kinase substrates by extracting evolutionary information from multiple sequence alignments in a manner that is tolerant to degenerate motif positioning. Given a known consensus, the new method (ConDens) compares the observed density of matches to a null model of evolution and does not require labeled training data. We confirmed that ConDens has improved performance compared with several existing methods in the field. Further, we show that it is generalizable and can predict interesting substrates for several important eukaryotic kinases where training data is not available.

AVAILABILITY AND IMPLEMENTATION

ConDens can be found at http://www.moseslab.csb.utoronto.ca/andyl/.

CONTACT

alan.moses@utoronto.ca

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Evaluation and properties of the budding yeast phosphoproteome

We have assembled a reliable phosphoproteomic data set for budding yeast Saccharomyces cerevisiae and have investigated its properties. Twelve publicly available phosphoproteome data sets were triaged to obtain a subset of high-confidence phosphorylation sites (p-sites), free of “noisy” phosphorylations. Analysis of this combined data set suggests that the inventory of phosphoproteins in yeast is close to completion, but that these proteins may have many undiscovered p-sites. Proteins involved in budding and protein kinase activity have high numbers of p-sites and are highly over-represented in the vast majority of the yeast phosphoproteome data sets. The yeast phosphoproteome is characterized by a few proteins with many p-sites and many proteins with a few p-sites. We confirm a tendency for p-sites to cluster together and find evidence that kinases may phosphorylate off-target amino acids that are within one or two residues of their cognate target. This suggests that the precise position of the phosphorylated amino acid is not a stringent requirement for regulatory fidelity. Compared with nonphosphorylated proteins, phosphoproteins are more ancient, more abundant, have longer unstructured regions, have more genetic interactions, more protein interactions, and are under tighter post-translational regulation. It appears that phosphoproteins constitute the raw material for pathway rewiring and adaptation at various evolutionary rates.

Functional wiring of the yeast kinome revealed by global analysis of genetic network motifs

A combinatorial genetic perturbation strategy was applied to interrogate the yeast kinome on a genome-wide scale. We assessed the global effects of gene overexpression or gene deletion to map an integrated genetic interaction network of synthetic dosage lethal (SDL) and loss-of-function genetic interactions (GIs) for 92 kinases, producing a meta-network of 8700 GIs enriched for pathways known to be regulated by cognate kinases. Kinases most sensitive to dosage perturbations had constitutive cell cycle or cell polarity functions under standard growth conditions. Condition-specific screens confirmed that the spectrum of kinase dosage interactions can be expanded substantially in activating conditions. An integrated network composed of systematic SDL, negative and positive loss-of-function GIs, and literature-curated kinase-substrate interactions revealed kinase-dependent regulatory motifs predictive of novel gene-specific phenotypes. Our study provides a valuable resource to unravel novel functional relationships and pathways regulated by kinases and outlines a general strategy for deciphering mutant phenotypes from large-scale GI networks.

Transparent mediation-based access to multiple yeast data sources using an ontology driven interface

BACKGROUND

Saccharomyces cerevisiae is recognized as a model system representing a simple eukaryote whose genome can be easily manipulated. Information solicited by scientists on its biological entities (Proteins, Genes, RNAs...) is scattered within several data sources like SGD, Yeastract, CYGD-MIPS, BioGrid, PhosphoGrid, etc. Because of the heterogeneity of these sources, querying them separately and then manually combining the returned results is a complex and time-consuming task for biologists most of whom are not bioinformatics expert. It also reduces and limits the use that can be made on the available data.

RESULTS

To provide transparent and simultaneous access to yeast sources, we have developed YeastMed: an XML and mediator-based system. In this paper, we present our approach in developing this system which takes advantage of SB-KOM to perform the query transformation needed and a set of Data Services to reach the integrated data sources. The system is composed of a set of modules that depend heavily on XML and Semantic Web technologies. User queries are expressed in terms of a domain ontology through a simple form-based web interface.

CONCLUSIONS

YeastMed is the first mediation-based system specific for integrating yeast data sources. It was conceived mainly to help biologists to find simultaneously relevant data from multiple data sources. It has a biologist-friendly interface easy to use. The system is available at http://www.khaos.uma.es/yeastmed/.

A dynamic view of domain-motif interactions

Many protein-protein interactions are mediated by domain-motif interaction, where a domain in one protein binds a short linear motif in its interacting partner. Such interactions are often involved in key cellular processes, necessitating their tight regulation. A common strategy of the cell to control protein function and interaction is by post-translational modifications of specific residues, especially phosphorylation. Indeed, there are motifs, such as SH2-binding motifs, in which motif phosphorylation is required for the domain-motif interaction. On the contrary, there are other examples where motif phosphorylation prevents the domain-motif interaction. Here we present a large-scale integrative analysis of experimental human data of domain-motif interactions and phosphorylation events, demonstrating an intriguing coupling between the two. We report such coupling for SH3, PDZ, SH2 and WW domains, where residue phosphorylation within or next to the motif is implied to be associated with switching on or off domain binding. For domains that require motif phosphorylation for binding, such as SH2 domains, we found coupled phosphorylation events other than the ones required for domain binding. Furthermore, we show that phosphorylation might function as a double switch, concurrently enabling interaction of the motif with one domain and disabling interaction with another domain. Evolutionary analysis shows that co-evolution of the motif and the proximal residues capable of phosphorylation predominates over other evolutionary scenarios, in which the motif appeared before the potentially phosphorylated residue, or vice versa. Our findings provide strengthening evidence for coupled interaction-regulation units, defined by a domain-binding motif and a phosphorylated residue.

Domain-motif interactions are instrumental for many central cellular processes, and are therefore tightly regulated. Phosphorylation events are known modulators of protein-protein interactions in general, including domain-motif interactions. Here, we addressed the association of phosphorylation and domain-motif interaction taking a motif-centred view. We integrated human domain-motif interaction and phosphorylation data for four representative domains (SH2, WW, SH3 and PDZ), and showed that the adjacency between phosphorylation and domain-motif interactions is extensive, suggesting interesting functional links between them that extend the classical and widely studied phospho-regulation of SH2 or WW domain-motif interactions. Furthermore, we show that such interaction-regulation units may function as double switches, concurrently enabling interaction of the motif with one domain and disabling interaction with another domain. These latter interaction-regulation units are more conserved in evolution than the individual units comprising them. Assuming that the four analyzed domain-motif interaction types are reliable representatives of such interactions, our results support the existence of units comprising motifs and associated phosphorylation sites, in which the regulation of domain-motif interaction is inherent.

Benchmarking of the 2010 BioCreative Challenge III text-mining competition by the BioGRID and MINT interaction databases

Background

The vast amount of data published in the primary biomedical literature represents a challenge for the automated extraction and codification of individual data elements. Biological databases that rely solely on manual extraction by expert curators are unable to comprehensively annotate the information dispersed across the entire biomedical literature. The development of efficient tools based on natural language processing (NLP) systems is essential for the selection of relevant publications, identification of data attributes and partially automated annotation. One of the tasks of the Biocreative 2010 Challenge III was devoted to the evaluation of NLP systems developed to identify articles for curation and extraction of protein-protein interaction (PPI) data.

Results

The Biocreative 2010 competition addressed three tasks: gene normalization, article classification and interaction method identification. The BioGRID and MINT protein interaction databases both participated in the generation of the test publication set for gene normalization, annotated the development and test sets for article classification, and curated the test set for interaction method classification. These test datasets served as a gold standard for the evaluation of data extraction algorithms.

Conclusion

The development of efficient tools for extraction of PPI data is a necessary step to achieve full curation of the biomedical literature. NLP systems can in the first instance facilitate expert curation by refining the list of candidate publications that contain PPI data; more ambitiously, NLP approaches may be able to directly extract relevant information from full-text articles for rapid inspection by expert curators. Close collaboration between biological databases and NLP systems developers will continue to facilitate the long-term objectives of both disciplines.

Using the Saccharomyces Genome Database (SGD) for analysis of genomic information

Analysis of genomic data requires access to software tools that place the sequence-derived information in the context of biology. The Saccharomyces Genome Database (SGD) integrates functional information about budding yeast genes and their products with a set of analysis tools that facilitate exploring their biological details. This unit describes how the various types of functional data available at SGD can be searched, retrieved, and analyzed. Starting with the guided tour of the SGD Home page and Locus Summary page, this unit highlights how to retrieve data using YeastMine, how to visualize genomic information with GBrowse, how to explore gene expression patterns with SPELL, and how to use Gene Ontology tools to characterize large-scale datasets.

Sch9 regulates ribosome biogenesis via Stb3, Dot6 and Tod6 and the histone deacetylase complex RPD3L

TORC1 is a conserved multisubunit kinase complex that regulates many aspects of eukaryotic growth including the biosynthesis of ribosomes. The TOR protein kinase resident in TORC1 is responsive to environmental cues and is potently inhibited by the natural product rapamycin. Recent characterization of the rapamycin-sensitive phosphoproteome in yeast has yielded insights into how TORC1 regulates growth. Here, we show that Sch9, an AGC family kinase and direct substrate of TORC1, promotes ribosome biogenesis (Ribi) and ribosomal protein (RP) gene expression via direct inhibitory phosphorylation of the transcriptional repressors Stb3, Dot6 and Tod6. Deletion of STB3, DOT6 and TOD6 partially bypasses the growth and cell size defects of an sch9 strain and reveals interdependent regulation of both Ribi and RP gene expression, and other aspects of Ribi. Dephosphorylation of Stb3, Dot6 and Tod6 enables recruitment of the RPD3L histone deacetylase complex to repress Ribi/RP gene promoters. Taken together with previous studies, these results suggest that Sch9 is a master regulator of ribosome biogenesis through the control of Ribi, RP, ribosomal RNA and tRNA gene transcription.

Diverse protein kinase interactions identified by protein microarrays reveal novel connections between cellular processes

Protein kinases are key regulators of cellular processes. In spite of considerable effort, a full understanding of the pathways they participate in remains elusive. We globally investigated the proteins that interact with the majority of yeast protein kinases using protein microarrays. Eighty-five kinases were purified and used to probe yeast proteome microarrays. One-thousand-twenty-three interactions were identified, and the vast majority were novel. Coimmunoprecipitation experiments indicate that many of these interactions occurred in vivo. Many novel links of kinases to previously distinct cellular pathways were discovered. For example, the well-studied Kss1 filamentous pathway was found to bind components of diverse cellular pathways, such as those of the stress response pathway and the Ccr4-Not transcriptional/translational regulatory complex; genetic tests revealed that these different components operate in the filamentation pathway in vivo. Overall, our results indicate that kinases operate in a highly interconnected network that coordinates many activities of the proteome. Our results further demonstrate that protein microarrays uncover a diverse set of interactions not observed previously.

Expression of the human atypical kinase ADCK3 rescues coenzyme Q biosynthesis and phosphorylation of Coq polypeptides in yeast coq8 mutants

Coenzyme Q (ubiquinone or Q) is a lipid electron and proton carrier in the electron transport chain. In yeast Saccharomyces cerevisiae eleven genes, designated COQ1 through COQ9, YAH1 and ARH1, have been identified as being required for Q biosynthesis. One of these genes, COQ8 (ABC1), encodes an atypical protein kinase, containing six (I, II, III, VIB, VII, and VIII) of the twelve motifs characteristically present in canonical protein kinases. Here we characterize seven distinct Q-less coq8 yeast mutants and show that unlike the coq8 null mutant, each maintained normal steady-state levels of the Coq8 polypeptide. The phosphorylation states of Coq polypeptides were determined with two-dimensional gel analyses. Coq3p, Coq5p, and Coq7p were phosphorylated in a Coq8p-dependent manner. Expression of a human homolog of Coq8p, ADCK3(CABC1) bearing an amino-terminal yeast mitochondrial leader sequence, rescued growth of yeast coq8 mutants on medium containing a nonfermentable carbon source and partially restored biosynthesis of Q(6). The phosphorylation state of several of the yeast Coq polypeptides was also rescued, indicating a profound conservation of yeast Coq8p and human ADCK3 protein kinase function in Q biosynthesis.

A quantitative literature-curated gold standard for kinase-substrate pairs

We describe the Yeast Kinase Interaction Database (KID, http://www.moseslab.csb.utoronto.ca/KID/), which contains high- and low-throughput data relevant to phosphorylation events. KID includes 6,225 low-throughput and 21,990 high-throughput interactions, from greater than 35,000 experiments. By quantitatively integrating these data, we identified 517 high-confidence kinase-substrate pairs that we consider a gold standard. We show that this gold standard can be used to assess published high-throughput datasets, suggesting that it will enable similar rigorous assessments in the future.

Phosphoproteomic analysis reveals interconnected system-wide responses to perturbations of kinases and phosphatases in yeast

The phosphorylation and dephosphorylation of proteins by kinases and phosphatases constitute an essential regulatory network in eukaryotic cells. This network supports the flow of information from sensors through signaling systems to effector molecules and ultimately drives the phenotype and function of cells, tissues, and organisms. Dysregulation of this process has severe consequences and is one of the main factors in the emergence and progression of diseases, including cancer. Thus, major efforts have been invested in developing specific inhibitors that modulate the activity of individual kinases or phosphatases; however, it has been difficult to assess how such pharmacological interventions would affect the cellular signaling network as a whole. Here, we used label-free, quantitative phosphoproteomics in a systematically perturbed model organism (Saccharomyces cerevisiae) to determine the relationships between 97 kinases, 27 phosphatases, and more than 1000 phosphoproteins. We identified 8814 regulated phosphorylation events, describing the first system-wide protein phosphorylation network in vivo. Our results show that, at steady state, inactivation of most kinases and phosphatases affected large parts of the phosphorylation-modulated signal transduction machinery-and not only the immediate downstream targets. The observed cellular growth phenotype was often well maintained despite the perturbations, arguing for considerable robustness in the system. Our results serve to constrain future models of cellular signaling and reinforce the idea that simple linear representations of signaling pathways might be insufficient for drug development and for describing organismal homeostasis.

The BioGRID Interaction Database: 2011 update

The Biological General Repository for Interaction Datasets (BioGRID) is a public database that archives and disseminates genetic and protein interaction data from model organisms and humans (http://www.thebiogrid.org). BioGRID currently holds 347 966 interactions (170 162 genetic, 177 804 protein) curated from both high-throughput data sets and individual focused studies, as derived from over 23 000 publications in the primary literature. Complete coverage of the entire literature is maintained for budding yeast (Saccharomyces cerevisiae), fission yeast (Schizosaccharomyces pombe) and thale cress (Arabidopsis thaliana), and efforts to expand curation across multiple metazoan species are underway. The BioGRID houses 48 831 human protein interactions that have been curated from 10 247 publications. Current curation drives are focused on particular areas of biology to enable insights into conserved networks and pathways that are relevant to human health. The BioGRID 3.0 web interface contains new search and display features that enable rapid queries across multiple data types and sources. An automated Interaction Management System (IMS) is used to prioritize, coordinate and track curation across international sites and projects. BioGRID provides interaction data to several model organism databases, resources such as Entrez-Gene and other interaction meta-databases. The entire BioGRID 3.0 data collection may be downloaded in multiple file formats, including PSI MI XML. Source code for BioGRID 3.0 is freely available without any restrictions.

Phospho.ELM: a database of phosphorylation sites--update 2011

The Phospho.ELM resource (http://phospho.elm.eu.org) is a relational database designed to store in vivo and in vitro phosphorylation data extracted from the scientific literature and phosphoproteomic analyses. The resource has been actively developed for more than 7 years and currently comprises 42 574 serine, threonine and tyrosine non-redundant phosphorylation sites. Several new features have been implemented, such as structural disorder/order and accessibility information and a conservation score. Additionally, the conservation of the phosphosites can now be visualized directly on the multiple sequence alignment used for the score calculation. Finally, special emphasis has been put on linking to external resources such as interaction networks and other databases.