TRIPLES: a database of gene function in Saccharomyces cerevisiae

A method for identifying protein complexes with the features of joint co-localization and joint co-expression in static PPI networks

Identifying protein complexes in static protein-protein interaction (PPI) networks is essential for understanding the underlying mechanism of biological processes. Proteins in a complex are co-localized at the same place and co-expressed at the same time. We propose a novel method to identify protein complexes with the features of joint co-localization and joint co-expression in static PPI networks. To achieve this goal, we define a joint localization vector to construct a joint co-localization criterion of a protein group, and define a joint gene expression to construct a joint co-expression criterion of a gene group. Moreover, the functional similarity of proteins in a complex is an important characteristic. Thus, we use the CC-based, MF-based, and BP-based protein similarities to devise functional similarity criterion to determine whether a protein is functionally similar to a protein cluster. Based on the core-attachment structure and following to seed expanding strategy, we use four types of biological data including PPI data with reliability score, protein localization data, gene expression data, and gene ontology annotations, to identify protein complexes. The experimental results on yeast data show that comparing with existing methods our proposed method can efficiently and exactly identify more protein complexes, especially more protein complexes of sizes from 2 to 6. Furthermore, the enrichment analysis demonstrates that the protein complexes identified by our method have significant biological meaning.

L. F. de Carvalho AC, Jin Y. Reduction strategies for hierarchical multi-label classification in protein function prediction

BACKGROUND

Hierarchical Multi-Label Classification is a classification task where the classes to be predicted are hierarchically organized. Each instance can be assigned to classes belonging to more than one path in the hierarchy. This scenario is typically found in protein function prediction, considering that each protein may perform many functions, which can be further specialized into sub-functions. We present a new hierarchical multi-label classification method based on multiple neural networks for the task of protein function prediction. A set of neural networks are incrementally training, each being responsible for the prediction of the classes belonging to a given level.

RESULTS

The method proposed here is an extension of our previous work. Here we use the neural network output of a level to complement the feature vectors used as input to train the neural network in the next level. We experimentally compare this novel method with several other reduction strategies, showing that it obtains the best predictive performance. Empirical results also show that the proposed method achieves better or comparable predictive performance when compared with state-of-the-art methods for hierarchical multi-label classification in the context of protein function prediction.

CONCLUSIONS

The experiments showed that using the output in one level as input to the next level contributed to better classification results. We believe the method was able to learn the relationships between the protein functions during training, and this information was useful for classification. We also identified in which functional classes our method performed better.

Transcription factors Asg1p and Hal9p regulate pH homeostasis in Candida glabrata

Candida glabrata is an important microorganism used in commercial fermentation to produce pyruvate, but very little is known about its mechanisms for surviving acid stress in culture. In this study, it was shown that transcription factors Asg1p and Hal9p play essential roles in C. glabrata in the tolerance of acid stress, as the deletion of CgASG1 or CgHAL9 resulted in the inability to survive in an acidic environment. Cgasg1Δ and Cghal9Δ mutant strains are unable to maintain pH homeostasis, as evidenced by a decrease in intracellular pH and an increase in reactive oxygen species production, which results in metabolic disorders. The results showed that intracellular acidification was partly due to the diminished activity of the plasma membrane proton pump, CgPma1p. In addition, transcriptome sequencing revealed that Cgasg1Δ and Cghal9Δ mutant strains displayed a variety of changes in gene expression under acidic conditions, including genes in the MAPK signaling pathway, plasma membrane, or cell wall organization, trehalose accumulation, and the RIM101 signaling pathway. Lastly, quantitative reverse-transcribed PCR and cellular localization showed that CgAsg1p and CgHal9p played independent roles in response to acid stress.

A multi-label approach using binary relevance and decision trees applied to functional genomics

Many classification problems, especially in the field of bioinformatics, are associated with more than one class, known as multi-label classification problems. In this study, we propose a new adaptation for the Binary Relevance algorithm taking into account possible relations among labels, focusing on the interpretability of the model, not only on its performance. Experiments were conducted to compare the performance of our approach against others commonly found in the literature and applied to functional genomic datasets. The experimental results show that our proposal has a performance comparable to that of other methods and that, at the same time, it provides an interpretable model from the multi-label problem.

Structures of RNA polymerase II complexes with Bye1, a chromatin-binding PHF3/DIDO homologue

Bypass of Ess1 (Bye1) is a nuclear protein with a domain resembling the central domain in the transcription elongation factor TFIIS. Here we show that Bye1 binds with its TFIIS-like domain (TLD) to RNA polymerase (Pol) II, and report crystal structures of the Bye1 TLD bound to Pol II and three different Pol II-nucleic acid complexes. Like TFIIS, Bye1 binds with its TLD to the Pol II jaw and funnel. In contrast to TFIIS, however, it neither alters the conformation nor the in vitro functions of Pol II. In vivo, Bye1 is recruited to chromatin via its TLD and occupies the 5'-region of active genes. A plant homeo domain (PHD) in Bye1 binds histone H3 tails with trimethylated lysine 4, and this interaction is enhanced by the presence of neighboring posttranslational modifications (PTMs) that mark active transcription and conversely is impaired by repressive PTMs. We identify putative human homologs of Bye1, the proteins PHD finger protein 3 and death-inducer obliterator, which are both implicated in cancer. These results establish Bye1 as the founding member of a unique family of chromatin transcription factors that link histones with active PTMs to transcribing Pol II.

Pathogenesis and Antifungal Drug Resistance of the Human Fungal Pathogen Candida glabrata

Candida glabrata is a major opportunistic human fungal pathogen causing superficial as well as systemic infections in immunocompromised individuals and several other patient cohorts. C. glabrata represents the second most prevalent cause of candidemia and a better understanding of its virulence and drug resistance mechanisms is thus of high medical relevance. In contrast to the diploid dimorphic pathogen C. albicans, whose ability to undergo filamentation is considered a major virulence trait, C. glabrata has a haploid genome and lacks the ability to switch to filamentous growth. A major impediment for the clinical therapy of C. glabrata infections is its high intrinsic resistance to several antifungal drugs, especially azoles. Further, the development of antifungal resistance, particularly during prolonged and prophylactic therapies is diminishing efficacies of therapeutic interventions. In addition, C. glabrata harbors a large repertoire of adhesins involved in the adherence to host epithelia. Interestingly, genome plasticity, phenotypic switching or the remarkable ability to persist and survive inside host immune cells further contribute to the pathogenicity of C. glabrata. In this comprehensive review, we want to emphasize and discuss the mechanisms underlying virulence and drug resistance of C. glabrata, and discuss its ability to escape from the host immune surveillance or persist inside host cells.

A hub-attachment based method to detect functional modules from confidence-scored protein interactions and expression profiles

Background

Many research results show that the biological systems are composed of functional modules. Members in the same module usually have common functions. This is useful information to understand how biological systems work. Therefore, detecting functional modules is an important research topic in the post-genome era. One of functional module detecting methods is to find dense regions in Protein-Protein Interaction (PPI) networks. Most of current methods neglect confidence-scores of interactions, and pay little attention on using gene expression data to improve their results.

Results

In this paper, we propose a novel hub-attachment based method to detect functional modules from confidence-scored protein interactions and expression profiles, and we name it HUNTER. Our method not only can extract functional modules from a weighted PPI network, but also use gene expression data as optional input to increase the quality of outcomes. Using HUNTER on yeast data, we found it can discover more novel components related with RNA polymerase complex than those existed methods from yeast interactome. And these new components show the close relationship with polymerase after functional analysis on Gene Ontology.

Conclusion

A C++ implementation of our prediction method, dataset and supplementary material are available at http://hub.iis.sinica.edu.tw/Hunter/. Our proposed HUNTER method has been applied on yeast data, and the empirical results show that our method can accurately identify functional modules. Such useful application derived from our algorithm can reconstruct the biological machinery, identify undiscovered components and decipher common sub-modules inside these complexes like RNA polymerases I, II, III.

Prediction and integration of regulatory and protein-protein interactions

Knowledge of transcriptional regulatory interactions (TRIs) is essential for exploring functional genomics and systems biology in any organism. While several results from genome-wide analysis of transcriptional regulatory networks are available, they are limited to model organisms such as yeast ( 1 ) and worm ( 2 ). Beyond these networks, experiments on TRIs study only individual genes and proteins of specific interest. In this chapter, we present a method for the integration of various data sets to predict TRIs for 54 organisms in the Bioverse ( 3 ). We describe how to compile and handle various formats and identifiers of data sets from different sources and how to predict TRIs using a homology-based approach, utilizing the compiled data sets. Integrated data sets include experimentally verified TRIs, binding sites of transcription factors, promoter sequences, protein subcellular localization, and protein families. Predicted TRIs expand the networks of gene regulation for a large number of organisms. The integration of experimentally verified and predicted TRIs with other known protein-protein interactions (PPIs) gives insight into specific pathways, network motifs, and the topological dynamics of an integrated network with gene expression under different conditions, essential for exploring functional genomics and systems biology.

Pdr5-mediated multidrug resistance requires the CPY-vacuolar sorting protein Vps3: are xenobiotic compounds routed from the vacuole to plasma membrane transporters for efflux?

In Saccharomyces cerevisiae several members of the ATP-binding cassette transporter superfamily efflux a broad range of xenobiotic substrates from cells. The vacuole also plays a critical role in multidrug resistance. Mutations in genes such as VPS3 that are essential for vacuolar acidification and carboxypeptidase Y vacuolar protein-sorting are multidrug sensitive. A similar phenotype is also observed with deletions of VPS15, VPS34, and VPS38, which encode essential members of the carboxypeptidase Y vacuolar protein-sorting pathway. Prior to the work described herein, detoxification by transporters and the vacuole were presumed to function independently. We demonstrate that this is not the case. Significantly, Vps3 has an epistatic relationship with Pdr5, a major yeast multidrug transporter. Thus, a double pdr5, vps3 deletion mutant is no more multidrug sensitive than its isogenic single-mutant counterparts. Subcellular fractionation experiments and analysis of purified plasma membrane vesicles indicate, however, that a vps3 mutation does not affect the membrane-localization or ATPase activity of Pdr5 even though rhodamine 6G efflux is reduced significantly. This suggests that Vps3 and probably other members of the carboxypeptidase Y vacuolar protein-sorting pathway are required for relaying xenobiotic compounds to transporters in the membrane.

Phosphoinositide 5-phosphatase Fig 4p is required for both acute rise and subsequent fall in stress-induced phosphatidylinositol 3,5-bisphosphate levels

Phosphoinositide lipids regulate complex events via the recruitment of proteins to a specialized region of the membrane at a specific time. Precise control of both the synthesis and turnover of phosphoinositide lipids is integral to membrane trafficking, signal transduction, and cytoskeletal rearrangements. Little is known about the acute regulation of the levels of these signaling lipids. When Saccharomyces cerevisiae cells are treated with hyperosmotic medium the levels of phosphatidylinositol 3,5-bisphosphate (PI3,5P(2)) increase 20-fold. Here we show that this 20-fold increase is rapid and occurs within 5 min. Surprisingly, these elevated levels are transient. Fifteen minutes following hyperosmotic shock they decrease at a rapid rate, even though the cells remain in hyperosmotic medium. In parallel with the rapid increase in the levels of PI3,5P(2), vacuole volume decreases rapidly. Furthermore, concomitant with a return to basal levels of PI3,5P(2) vacuole volume is restored. We show that Fig 4p, consistent with its proposed role as a PI3,5P(2) 5-phosphatase, is required in vivo for this rapid return to basal levels of PI3,5P(2). Surprisingly, we find that Fig 4p is also required for the hyperosmotic shock-induced increase in PI3,5P(2) levels. These findings demonstrate that following hyperosmotic shock, large, transient changes occur in the levels of PI3,5P(2) and further suggest that Fig 4p is important in regulating both the acute rise and subsequent fall in PI3,5P(2) levels.

Automated interpretation of subcellular patterns in fluorescence microscope images for location proteomics

Proteomics, the large scale identification and characterization of many or all proteins expressed in a given cell type, has become a major area of biological research. In addition to information on protein sequence, structure and expression levels, knowledge of a protein's subcellular location is essential to a complete understanding of its functions. Currently, subcellular location patterns are routinely determined by visual inspection of fluorescence microscope images. We review here research aimed at creating systems for automated, systematic determination of location. These employ numerical feature extraction from images, feature reduction to identify the most useful features, and various supervised learning (classification) and unsupervised learning (clustering) methods. These methods have been shown to perform significantly better than human interpretation of the same images. When coupled with technologies for tagging large numbers of proteins and high-throughput microscope systems, the computational methods reviewed here enable the new subfield of location proteomics. This subfield will make critical contributions in two related areas. First, it will provide structured, high-resolution information on location to enable Systems Biology efforts to simulate cell behavior from the gene level on up. Second, it will provide tools for Cytomics projects aimed at characterizing the behaviors of all cell types before, during, and after the onset of various diseases.

Systems biology of AGC kinases in fungi

Sch9 appears to be the Saccharomyces cerevisiae homolog of protein kinase B and is involved in the control of numerous nutrient-sensitive processes, including regulation of cell size, cell cycle progression, and stress resistance. Sch9 has also been implicated in the regulation of replicative and chronological life span. Systematic comparison of the phenotypes of sch9 and other AGC kinase mutants in fungal species with their counterparts in model eukaryotic organisms provides insight into the functions of AGC kinases. The availability of data from global studies of protein-protein interactions now makes it possible to predict and validate functional connections between Sch9, its putative substrates, and other proteins. This review highlights several emerging paradigms of AGC kinase signaling that are relevant for growth, development, and aging.

Automated Interpretation of Protein Subcellular Location Patterns

Proteomics is a major current focus of biomedical research, and location proteomics is the important branch of proteomics that systematically studies the subcellular distributions for all proteins expressed in a given cell type. Fluorescence microscopy of labeled proteins is currently the main methodology to obtain location information. Traditionally, microscope images are analyzed by visual inspection, which suffers from inefficiency and inconsistency. Automated and objective interpretation approaches are therefore needed for location proteomics. In this article, we briefly review recent advances in automated imaging interpretation tools, including supervised classification (which assigns location pattern labels to previously unseen images), unsupervised clustering (which groups proteins based on the similarity among their subcellular distributions), and additional statistical tools that can aid cell and molecular biologists who use microscopy in their work.

Identification and characterization of Elf1, a conserved transcription elongation factor in Saccharomyces cerevisiae

In order to identify previously unknown transcription elongation factors, a genetic screen was carried out to identify mutations that cause lethality when combined with mutations in the genes encoding the elongation factors TFIIS and Spt6. This screen identified a mutation in YKL160W, hereafter named ELF1 (elongation factor 1). Further analysis identified synthetic lethality between an elf1Delta mutation and mutations in genes encoding several known elongation factors, including Spt4, Spt5, Spt6, and members of the Paf1 complex. Genome-wide synthetic lethality studies confirmed that elf1Delta specifically interacts with mutations in genes affecting transcription elongation. Chromatin immunoprecipitation experiments show that Elf1 is cotranscriptionally recruited over actively transcribed regions and that this association is partially dependent on Spt4 and Spt6. Analysis of elf1Delta mutants suggests a role for this factor in maintaining proper chromatin structure in regions of active transcription. Finally, purification of Elf1 suggests an association with casein kinase II, previously implicated in roles in transcription. Together, these results suggest an important role for Elf1 in the regulation of transcription elongation.

Association of ribosomal proteins with nascent transcripts in S. cerevisiae

Although it is generally accepted that transcription and translation are spatially separated in eukaryotes, a number of recent observations have called this belief into question. In particular, several studies have shown that parts of the translation machinery, including ribosomal proteins, can be found associated with sites of active transcription in metazoans. Here we describe results of chromatin immunoprecipitation (ChIP) experiments designed to determine whether ribosomal proteins associate with nascent transcripts in Saccharomyces cerevisiae and whether this association reflects a functional engagement of the translation machinery. We find that HAT-tagged ribosomal proteins can be detected in association with nascent RNAs in budding yeast. However, our data clearly indicate that this binding is independent of transcript translatability, so is therefore not indicative of nuclear translation.

Analyzing and mining image databases

Image mining is the application of computer-based techniques that extract and exploit information from large image sets to support human users in generating knowledge from these sources. This review focuses on biomedical applications, in particular automated imaging at the cellular level. An image database is an interactive software application that combines data management, image analysis and visual data mining. The main characteristic of such a system is a layer that represents objects within an image, and that represents a large spectrum of quantitative and semantic object features. The image analysis needs to be adapted to each particular experiment, so 'end-user programming' will be desirable to make the technology more widely applicable.

From quantitative microscopy to automated image understanding

Quantitative microscopy has been extensively used in biomedical research and has provided significant insights into structure and dynamics at the cell and tissue level. The entire procedure of quantitative microscopy is comprised of specimen preparation, light absorption/reflection/emission from the specimen, microscope optical processing, optical/electrical conversion by a camera or detector, and computational processing of digitized images. Although many of the latest digital signal processing techniques have been successfully applied to compress, restore, and register digital microscope images, automated approaches for recognition and understanding of complex subcellular patterns in light microscope images have been far less widely used. We describe a systematic approach for interpreting protein subcellular distributions using various sets of subcellular location features (SLF), in combination with supervised classification and unsupervised clustering methods. These methods can handle complex patterns in digital microscope images, and the features can be applied for other purposes such as objectively choosing a representative image from a collection and performing statistical comparisons of image sets.

Saccharomyces cerevisiae ubiquitin-like protein Rub1 conjugates to cullin proteins Rtt101 and Cul3 in vivo

In Saccharomyces cerevisiae, the ubiquitin-like protein Rub1p (related to ubiquitin 1 protein) covalently attaches to the cullin protein Cdc53p (cell division cycle 53 protein), a subunit of a class of ubiquitin E3 ligases named SCF (Skp1-Cdc53-F-box protein) complex. We identified Rtt101p (regulator of Ty transposition 101 protein, where Ty stands for transposon of yeast), initially found during a screen for proteins to confer retrotransposition suppression, and Cul3p (cullin 3 protein), a protein encoded by the previously uncharacterized open reading frame YGR003w, as two new in vivo targets for Rub1p conjugation. These proteins show significant identity with Cdc53p and, therefore, are cullin proteins. Modification of Cul3p is eliminated by deletion of the Rub1p pathway through disruption of either RUB1 or its activating enzyme ENR2 / ULA1. The same disruptions in the Rub pathway decreased the percentage of total Rtt101p that is modified from approx. 60 to 30%. This suggests that Rtt101p has an additional RUB1 - and ENR2 -independent modification. All modified forms of Rtt101p and Cul3p were lost when a single lysine residue in a conserved region near the C-terminus was replaced by an arginine residue. These results suggest that this lysine residue is the site of Rub1p-dependent and -independent modifications in Rtt101p and of Rub1p-dependent modification in Cul3p. An rtt101 Delta strain was hypersensitive to thiabendazole, isopropyl ( N -3-chlorophenyl) carbamate and methyl methanesulphonate, but rub1 Delta strains were not. Whereas rtt101 Delta strains exhibited a 14-fold increase in Ty1 transposition, isogenic rub1 Delta strains did not show statistically significant increases. Rtt101K791Rp, which cannot be modified, complemented for Rtt101p function in a transposition assay. Altogether, these results suggest that neither the RUB1 -dependent nor the RUB1 -independent form of Rtt101p is required for Rtt101p function. The identification of additional Rub1p targets in S. cerevisiae suggests an expanded role for Rub in this organism.

Flytrap, a database documenting a GFP protein-trap insertion screen in Drosophila melanogaster

Flytrap is a web-enabled relational database of transposable element insertions in Drosophila melanogaster. A green fluorescent protein (GFP) artificial exon carried by a transposable P-element is mobilized and inserted into a host gene intron creating a GFP fusion protein. The sequence of the tagged gene is determined by sequencing inverse-PCR products derived from genomic DNA. Flytrap contains two principle data types: micrographs of protein localization and a cellular component ontology, based on rules derived from the Gene Ontology consortium (http://www.geneontology.org), describing protein localization. Flytrap also has links to gene information contained in Flybase (http:// flybase.bio.indiana.edu). The system is designed to accept submissions of micrographs and descriptions from any type of tissue (e.g. wing imaginal disk, ovary) and at any stage of development. Insertion lines can be searched using a number of queries, including Berkeley Drosophila Genome Project (BDGP) numbers and protein localization. In addition, Flytrap provides online order forms linked to each insertion line so that users may request any line generated from this project. Flytrap may be accessed from the homepage at http://flytrap.med. yale.edu.

LIFEdb: a database for functional genomics experiments integrating information from external sources, and serving as a sample tracking system

We have implemented LIFEdb (http://www.dkfz.de/LIFEdb) to link information regarding novel human full-length cDNAs generated and sequenced by the German cDNA Consortium with functional information on the encoded proteins produced in functional genomics and proteomics approaches. The database also serves as a sample-tracking system to manage the process from cDNA to experimental read-out and data interpretation. A web interface enables the scientific community to explore and visualize features of the annotated cDNAs and ORFs combined with experimental results, and thus helps to unravel new features of proteins with as yet unknown functions.

TheESS1Prolyl Isomerase and Its SuppressorBYE1Interact With RNA Pol II to Inhibit Transcription Elongation inSaccharomyces cerevisiae

Transcription by RNA polymerase II (pol II) requires the ordered binding of distinct protein complexes to catalyze initiation, elongation, termination, and coupled mRNA processing events. One or more proteins from each complex are known to bind pol II via the carboxy-terminal domain (CTD) of the largest subunit, Rpb1. How binding is coordinated is not known, but it might involve conformational changes in the CTD induced by the Ess1 peptidyl-prolyl cis/trans isomerase. Here, we examined the role of ESS1 in transcription by studying one of its multicopy suppressors, BYE1. We found that Bye1 is a negative regulator of transcription elongation. This led to the finding that Ess1 also inhibits elongation; Ess1 opposes elongation factors Dst1 and Spt4/5, and overexpression of ESS1 makes cells more sensitive to the elongation inhibitor 6-AU. In reporter gene assays, ess1 mutations reduce the ability of elongation-arrest sites to stall polymerase. We also show that Ess1 acts positively in transcription termination, independent of its role in elongation. We propose that Ess1-induced conformational changes attenuate pol II elongation and help coordinate the ordered assembly of protein complexes on the CTD. In this way, Ess1 might regulate the transition between multiple steps of transcription.

Evolution in Saccharomyces cerevisiae: Identification of Mutations Increasing Fitness in Laboratory Populations

Since the publication of the complete sequence of the genome of Saccharomyces cerevisiae, a number of comprehensive investigations have been initiated to gain insight into cellular function. The focus of these studies has been to identify genes essential for survival in specific environments or those that when mutated cause gross phenotypic defects in growth. Here we describe Ty1-based mutational approaches designed to identify genes, which when mutated generate evolutionarily significant phenotypes causing small but positive increments on fitness. As expected, Ty1 mutations with a positive fitness effect were in the minority. However, mutations in two loci, one inactivating FAR3 and one upstream of CYR1, identified in evolving populations, were shown to have small but significantly positive fitness effects.

Characterization of mutations that are synthetic lethal with pol3-13, a mutated allele of DNA polymerase delta in Saccharomyces cerevisiae

The pol3-13 mutation is located in the C-terminal end of POL3, the gene encoding the catalytic subunit of polymerase delta, and confers thermosensitivity onto the Saccharomyces cerevisiae mutant strain. To get insight about DNA replication control, we performed a genetic screen to identify genes that are synthetic lethal with pol3-13. Mutations in genes encoding the two other subunits of DNA polymerase delta (HYS2, POL32) were identified. Mutations in two recombination genes (RAD50, RAD51) were also identified, confirming that homologous recombination is necessary for pol3-13 mutant strain survival. Other mutations were identified in genes involved in repair and genome stability (MET18/ MMS19), in the control of origin-firing and/or transcription (ABF1, SRB7), in the S/G2 checkpoint (RAD53), in the Ras-cAMP signal transduction pathway (MKS1), in nuclear pore metabolism (SEH1), in protein degradation (DOC1) and in folding (YDJ1). Finally, mutations in three genes of unknown function were isolated (NBP35, DRE2, TAH18). Synthetic lethality between pol3-13 and each of the three mutants pol32, mms19 and doc1 could be suppressed by a rad18 deletion, suggesting an important role of ubiquitination in DNA replication control. We propose that the pol3-13 mutant generates replicative problems that need both homologous recombination and an intact checkpoint machinery to be overcome.

Classification schemes for protein structure and function

We examine the structural and functional classifications of the protein universe, providing an overview of the existing classification schemes, their features and inter-relationships. We argue that a unified scheme should be based on a natural classification approach and that more comparative analyses of the present schemes are required both to understand their limitations and to help delimit the number of known protein folds and their corresponding functional roles in cells.

DNA replication: telling time with microarrays

A long-standing hypothesis about eukaryotic DNA replication is that the late-replicating regions are transcriptionally inert and that repressing transcription delays replication initiation. But do contrasting results from yeast and a recent study in Drosophila imply that replication timing and transcriptional activity are differentially regulated in yeast and higher eukaryotes?

FunSpec: a web-based cluster interpreter for yeast

BACKGROUND

For effective exposition of biological information, especially with regard to analysis of large-scale data types, researchers need immediate access to multiple categorical knowledge bases and need summary information presented to them on collections of genes, as opposed to the typical one gene at a time.

RESULTS

We present here a web-based tool (FunSpec) for statistical evaluation of groups of genes and proteins (e.g. co-regulated genes, protein complexes, genetic interactors) with respect to existing annotations (e.g. functional roles, biochemical properties, localization). FunSpec is available online at http://funspec.med.utoronto.ca

CONCLUSION

FunSpec is helpful for interpretation of any data type that generates groups of related genes and proteins, such as gene expression clustering and protein complexes, and is useful for predictive methods employing "guilt-by-association."

The plant disease resistance gene Asc-1 prevents disruption of sphingolipid metabolism during AAL-toxin-induced programmed cell death

The nectrotrophic fungus Alternaria alternata f.sp. lycopersici infects tomato plants of the genotype asc/asc by utilizing a host-selective toxin, AAL-toxin, that kills the host cells by inducing programmed cell death. Asc-1 is homologous to genes found in most eukaryotes from yeast to humans, suggesting a conserved function. A yeast strain with deletions in the homologous genes LAG1 and LAC1 was functionally complemented by Asc-1, indicating that Asc-1 functions in an analogous manner to the yeast homologues. Examination of the yeast sphingolipids, which are almost absent in the lag1Deltalac1Delta mutant, showed that Asc-1 was able to restore the synthesis of sphingolipids. We therefore examined the biosynthesis of sphingolipids in tomato by labeling leaf discs with l-[3-3H]serine. In the absence of AAL-toxin, there was no detectable difference in sphingolipid labeling between leaf discs from Asc/Asc or asc/asc leaves. In the presence of pathologically significant concentrations of AAL-toxin however, asc/asc leaf discs showed severely reduced labeling of sphingolipids and increased label in dihydrosphingosine (DHS) and 3-ketodihydrosphingosine (3-KDHS). Leaf discs from Asc/Asc leaves responded to AAL-toxin treatment by incorporating label into different sphingolipid species. The effects of AAL-toxin on asc/asc leaflets could be partially blocked by the simultaneous application of AAL-toxin and myriocin. Leaf discs simultaneously treated with AAL-toxin and myriocin showed no incorporation of label into sphingolipids or long-chain bases as expected. These results indicate that the presence of Asc-1 is able to relieve an AAL-toxin-induced block on sphingolipid synthesis that would otherwise lead to programmed cell death.

Subcellular localization of the yeast proteome

Protein localization data are a valuable information resource helpful in elucidating eukaryotic protein function. Here, we report the first proteome-scale analysis of protein localization within any eukaryote. Using directed topoisomerase I-mediated cloning strategies and genome-wide transposon mutagenesis, we have epitope-tagged 60% of the Saccharomyces cerevisiae proteome. By high-throughput immunolocalization of tagged gene products, we have determined the subcellular localization of 2744 yeast proteins. Extrapolating these data through a computational algorithm employing Bayesian formalism, we define the yeast localizome (the subcellular distribution of all 6100 yeast proteins). We estimate the yeast proteome to encompass approximately 5100 soluble proteins and >1000 transmembrane proteins. Our results indicate that 47% of yeast proteins are cytoplasmic, 13% mitochondrial, 13% exocytic (including proteins of the endoplasmic reticulum and secretory vesicles), and 27% nuclear/nucleolar. A subset of nuclear proteins was further analyzed by immunolocalization using surface-spread preparations of meiotic chromosomes. Of these proteins, 38% were found associated with chromosomal DNA. As determined from phenotypic analyses of nuclear proteins, 34% are essential for spore viability--a percentage nearly twice as great as that observed for the proteome as a whole. In total, this study presents experimentally derived localization data for 955 proteins of previously unknown function: nearly half of all functionally uncharacterized proteins in yeast. To facilitate access to these data, we provide a searchable database featuring 2900 fluorescent micrographs at http://ygac.med.yale.edu.

The Sur7p family defines novel cortical domains in Saccharomyces cerevisiae, affects sphingolipid metabolism, and is involved in sporulation

We have discovered a novel cortical patch structure in Saccharomyces cerevisiae defined by a family of integral plasma membrane proteins, including Sur7p, Ynl194p, and Ydl222p. Sur7p-family patches localized as cortical patches that were immobile and stable. These patches were polarized to regions of the cell with a mature cell wall; they were absent from small buds and the tips of many medium-sized buds. These patches were distinct from other known cortical structures. Digestion of the cell wall caused Sur7p patches to disassemble, indicating that Sur7p requires cell wall-dependent extracellular interactions for its localization as patches. sur7Delta, ydl222Delta, and ynl194Delta mutants had reduced sporulation efficiencies. SUR7 was originally described as a multicopy suppressor of rvs167, whose product is an actin patch component. This suppression is probably mediated by sphingolipids, since deletion of SUR7, YDL222, and YNL194 altered the sphingolipid content of the yeast plasma membrane, and other SUR genes suppress rvs167 via effects on sphingolipid synthesis. In particular, the sphingoid base length and number of hydroxyl groups in inositol phosphorylceramides were altered in sur7Delta, ydl222Delta, and yne194Delta strains.

The TRIPLES database: a community resource for yeast molecular biology

TRIPLES is a web-accessible database of TRansposon-Insertion Phenotypes, Localization and Expression in Saccharomyces cerevisiae-a relational database housing nearly half a million data points generated from an ongoing study using large-scale transposon mutagenesis to characterize gene function in yeast. At present, TRIPLES contains three principal data sets (i.e. phenotypic data, protein localization data and expression data) for over 3500 annotated yeast genes as well as several hundred non-annotated open reading frames. In addition, the TRIPLES web site provides online order forms linked to each data set so that users may request any strain or reagent generated from this project free of charge. In response to user requests, the TRIPLES web site has undergone several recent modifications. Our localization data have been supplemented with approximately 500 fluorescent micrographs depicting actual staining patterns observed upon indirect immunofluorescence analysis of indicated epitope-tagged proteins. These localization data, as well as all other data sets within TRIPLES, are now available in full as tab-delimited text. To accommodate increased reagent requests, all orders are now cataloged in a separate database, and users are notified immediately of order receipt and shipment. Also, TRIPLES is one of five sites incorporated into the new functional analysis tool Function Junction provided by the Saccharomyces Genome Database. TRIPLES may be accessed from the Yale Genome Analysis Center (YGAC) homepage at http://ygac.med.yale.edu.

Absence of Dbp2p alters both nonsense-mediated mRNA decay and rRNA processing

Dbp2p, a member of the large family of DEAD-box proteins and a yeast homolog of human p68, was shown to interact with Upf1p, an essential component of the nonsense-mediated mRNA decay pathway. Dbp2p:Upf1p interaction occurs within a large conserved region in the middle of Upf1p that is largely distinct from its Nmd2p and Sup35/45p interaction domains. Deletion of DBP2, or point mutations within its highly conserved DEAD-box motifs, increased the abundance of nonsense-containing transcripts, leading us to conclude that Dbp2p also functions in the nonsense-mediated mRNA decay pathway. Dbp2p, like Upf1p, acts before or at decapping, is predominantly cytoplasmic, and associates with polyribosomes. Interestingly, Dbp2p also plays an important role in rRNA processing. In dbp2Delta cells, polyribosome profiles are deficient in free 60S subunits and the mature 25S rRNA is greatly reduced. The ribosome biogenesis phenotype, but not the mRNA decay function, of dbp2Delta cells can be complemented by the human p68 gene. We propose a unifying model in which Dbp2p affects both nonsense-mediated mRNA decay and rRNA processing by altering rRNA structure, allowing specific processing events in one instance and facilitating dissociation of the translation termination complex in the other.

Quantitative target display: a method to screen yeast mutants conferring quantitative phenotypes by 'mutant DNA fingerprints'

Whole genome sequencing of several microbes has revealed thousands of genes of unknown function. A large proportion of these genes seem to confer subtle quantitative phenotypes or phenotypes that do not have a plate screen. We report a novel method to monitor such phenotypes, where the fitness of mutants is assessed in mixed cultures under competitive growth conditions, and the abundance of any individual mutant in the pool is followed by means of its unique feature, namely the mutation itself. A mixed population of yeast mutants, obtained through transposon mutagenesis, was subjected to selection. The DNA regions (targets) flanking the transposon, until nearby restriction sites, are then quantitatively amplified by means of a ligation-mediated PCR method, using transposon-specific and adapter-specific primers. The amplified PCR products correspond to mutated regions of the genome and serve as 'mutant DNA fingerprints' that can be displayed on a sequencing gel. The relative intensity of the amplified DNA fragments before and after selection match with the relative abundance of corresponding mutants, thereby revealing the fate of the mutants during selection. Using this method we demonstrate that UBI4, YDJ1 and HSP26 are essential for stress tolerance of yeast during ethanol production. We anticipate that this method will be useful for functional analysis of genes of any microbe amenable to insertional mutagenesis.

Why multiple small subunits (Y2 and Y4) for yeast ribonucleotide reductase? Toward understanding the role of Y4

Ribonucleotide reductases (RNRs) catalyze the conversion of nucleotides to deoxynucleotides. Class I RNRs are composed of two homodimeric subunits: R1 and R2. R1 is directly involved in the reduction, and R2 contains the diferric-tyrosyl radical (Y*) cofactor essential for the initiation of reduction. Saccharomyces cerevisiae has two RNRs; Y1 and Y3 correspond to R1, whereas Y2 and Y4 correspond to R2. Y4 is essential for diferric-Y* formation in Y2 from apoY2, Fe(2+), and O(2). The actual function of Y4 is controversial. Y2 and Y4 have been further characterized in an effort to understand their respective roles in nucleotide reduction. (His)(6)-Y2, Y4, and (His)(6)-Y4 are homodimers, isolated largely in apo form. Their CD spectra reveal that they are predominantly helical. The concentrations of Y2 and Y4 in vivo are 0.5-2.3 microM, as determined by Western analysis. Incubation of Y2 and Y4 under physiological conditions generates apo Y2Y4 heterodimer, which can form a diferric-Y small middle dot when incubated with Fe(2+) and O(2). Holo Y2Y4 heterodimer contains 0.6-0.8 Y* and has a specific activity of 0.8-1.3 micromol.min.mg. Titration of Y2 with Y4 in the presence of Fe(2+) and O(2) gives maximal activity with one equivalent of Y4 per Y2. Models for the function of Y4 based on these data and the accompanying structure will be discussed.

Structure of the yeast ribonucleotide reductase Y2Y4 heterodimer

The R2 subunits of class I ribonucleotide reductases (RNRs) house a diferric-tyrosyl radical (Y*) cofactor essential for DNA synthesis. In yeast, there are two R2 proteins, Y2 and Y4. Although both Y2 and Y4 are homologous to R2s from other organisms, Y4 lacks three conserved iron-binding residues, and its exact function is unclear. Y4 is required for assembly of the diferric-Y* cofactor in Y2, and the two proteins can form both homodimeric and heterodimeric complexes. The Y2Y4 heterodimer was crystallized from a mixture of the two proteins, and its structure was determined to 2.8 A resolution. Both Y2 and Y4 are completely alpha helical and resemble the mouse and Escherichia coli R2s in overall fold. Three alpha helices not observed in the mouse R2 structure are present at the Y2 N terminus, and one extra N-terminal helix is observed in Y4. In addition, one of the eight principal helices in both Y2 and Y4, alphaD, is shifted significantly from its position in mouse R2. The heterodimer interface is similar to the mouse R2 homodimer interface in size and interacting residues, but loop regions at the interface edges differ. A single metal ion, assigned as Zn(II), occupies the Fe2 position in the Y2 active site. Treatment of the crystals with Fe(II) results in difference electron density consistent with formation of a diiron center. No metal-binding site is observed in Y4. Instead, the residues in the active site region form a hydrogen-bonding network involving an arginine, two glutamic acids, and a water molecule.

THEGENETICS OFFATTYACIDMETABOLISM INSACCHAROMYCESCEREVISIAE

Long-chain fatty acids are a vital metabolic energy source and are building blocks of membrane lipids. The yeast Saccharomyces cerevisiae is a valuable model system for elucidation of gene-function relationships in such eukaryotic processes as fatty acid metabolism. Yeast degrades fatty acids only in the peroxisome, and recently, genes encoding core and auxiliary enzymes of peroxisomal beta-oxidation have been identified. Mechanisms involved in fatty acid induction of gene expression have been described, and novel fatty acid-responsive genes have been discovered via yeast genome analysis. In addition, a number of genes essential for synthesis of the variety of fatty acids in yeast have been cloned. Advances in understanding such processes in S. cerevisiae will provide helpful insights to functional genomics approaches in more complex organisms.

Phenotypic analysis of genes encoding yeast zinc cluster proteins

Zinc cluster proteins (or binuclear cluster proteins) possess zinc fingers of the Zn(II)2Cys6-type involved in DNA recognition as exemplified by the well-characterized protein Gal4p. These fungal proteins are transcriptional regulators of genes involved in a wide variety of cellular processes including metabolism of compounds such as amino acids and sugars, as well as control of meiosis, multi-drug resistance etc. The yeast (Saccharomyces cerevisiae) sequencing project has allowed the identification of additional zinc cluster proteins for a total of 54. However, the role of many of these putative zinc cluster proteins is unknown. We have performed phenotypic analysis of 33 genes encoding (putative) zinc cluster proteins. Only two members of the GAL4 family are essential genes. Our results show that deletion of eight different zinc cluster genes impairs growth on non-fermentable carbon sources. The same strains are also hypersensitive to the antifungal calcofluor white suggesting a role for these genes in cell wall integrity. In addition, one of these strains (YFL052W) is also heat sensitive on rich (but not minimal) plates. Thus, deletion of YFL052W results in sensitivity to a combination of low osmolarity and high temperature. In addition, six strains are hypersensitive to caffeine, an inhibitor of the MAP kinase pathway and phosphodiesterase of the cAMP pathway. In conclusion, our analysis assigns phenotypes to a number of genes and provides a basis to better understand the role of these transcriptional regulators.

Transcript expression in Saccharomyces cerevisiae at high salinity

Transcript expression of Saccharomyces cerevisiae at high salinity was determined by microarray analysis of 6144 open reading frames (ORFs). From cells grown in 1 m NaCl for 10, 30, and 90 min, changes in transcript abundance >2-fold were classified. Salinity-induced ORFs increased over time: 107 (10 min), 243 (30 min), and 354 (90 min). Up-regulated, functionally unknown ORFs increased from 17 to 149 over this period. Expression patterns were similar early, with 67% of up-regulated transcripts after 10 min identical to those at 30 min. The expression profile after 90 min revealed different up-regulated transcripts (identities of 13% and 22%, respectively). Nucleotide and amino acid metabolism exemplified the earliest responses to salinity, followed by ORFs related to intracellular transport, protein synthesis, and destination. Transcripts related to energy production were up-regulated throughout the time course with respiration-associated transcripts strongly induced at 30 min. Highly expressed at 90 min were known salinity stress-induced genes, detoxification-related responses, transporters of the major facilitator superfamily, metabolism of energy reserves, nitrogen and sulfur compounds, and lipid, fatty acid/isoprenoid biosynthesis. We chose severe stress conditions to monitor responses in essential biochemical mechanisms. In the mutant, Deltagpd1/gpd2, lacking glycerol biosynthesis, the stress response was magnified with a partially different set of up-regulated ORFs.

Genome-wide transposon mutagenesis in yeast

This unit provides comprehensive protocols for the use of insertional libraries generated by shuttle mutagenesis. From the basic protocol, a small aliquot of insertional library DNA may be used to mutagenize yeast, producing strains containing a single transposon insertion within a transcribed and translated region of the genome. This transposon-mutagenized bank of yeast strains may be screened for any desired mutant phenotype. Alternatively, since the transposon contains a reporter gene lacking its start codon and promoter, transposon-tagged strains may also be screened for specific patterns of gene expression. Strains of interest may be characterized by vectorette PCR (protocol provided) in order to locate the precise genomic site of transposon insertion within each mutant. A method by which Cre/lox recombination may be used to reduce the transposon in yeast to a small insertion element encoding an epitope tag is described. This tag serves as a tool by which transposon-mutagenized gene products may be analyzed further (e.g., localized to a discrete subcellular site).

Emerging technologies in yeast genomics

The genomic revolution is undeniable: in the past year alone, the term 'genomics' was found in nearly 500 research articles, and at least 6 journals are devoted solely to genomic biology. More than just a buzzword, molecular biology has genuinely embraced genomics (the systematic, large-scale study of genomes and their functions). With its facile genetics, the budding yeast Saccharomyces cerevisiae has emerged as an important model organism in the development of many current genomic methodologies. These techniques have greatly influenced the manner in which biology is studied in yeast and in other organisms. In this review, we summarize the most promising technologies in yeast genomics.

Large-scale mutagenesis: yeast genetics in the genome era

The completion of the DNA sequence of the budding yeast Saccharomyces cerevisiae resulted in the identification of a large number of genes. However, the function of most of these genes is not known. One of the best ways to determine gene function is to carry out mutational and phenotypic analysis. In recent years, several approaches have been developed for the mutational analysis of yeast genes on a large scale. These include transposon-based insertional mutagenesis, and systematic deletions using PCR-based approaches. These projects have produced collections of yeast strains and plasmid alleles that can be screened using novel approaches. Analysis of these collections by the scientific community promises to reveal a great deal of biological information about this organism.

Protein localisation approaches for understanding yeast cell wall biogenesis

Yeast cells are surrounded by the cell wall, a rigid but dynamic structure that is essential for their viability. The complexity and functionality of this structure suggest that a high number of proteins must be involved in the biogenesis of the cell wall architecture and, as a consequence, in the maintenance of cell integrity. Among them, a high percentage is assumed to be located at the cell surface, mostly as structural or enzymatic components of the cell wall. Therefore, the presence of a protein in the cell wall is suggestive of its cell wall-related function. Different techniques can be used to specifically detect the cell wall localisation of a given protein or to identify cell wall proteins in large-scale analyses. These include the detection of proteins in whole cells or specific cell wall fractions by immunological, biochemical, microscopic, or genetic approaches, as well as the emerging proteomic technology. The advantages, limitations, and usefulness of these techniques are discussed and illustrated with some examples.