The Yeast Resource Center Public Image Repository: A large database of fluorescence microscopy images

<p>Abstract</p> <p>Background</p> <p>There is increasing interest in the development of computational methods to analyze fluorescent microscopy images and enable automated large-scale analysis of the subcellular localization of proteins. Determining the subcellular localization is an integral part of identifying a protein's function, and the application of bioinformatics to this problem provides a valuable tool for the annotation of proteomes. Training and validating algorithms used in image analysis research typically rely on large sets of image data, and would benefit from a large, well-annotated and highly-available database of images and associated metadata.</p> <p>Description</p> <p>The Yeast Resource Center Public Image Repository (YRC PIR) is a large database of images depicting the subcellular localization and colocalization of proteins. Designed especially for computational biologists who need large numbers of images, the YRC PIR contains 532,182 TIFF images from nearly 85,000 separate experiments and their associated experimental data. All images and associated data are searchable, and the results browsable, through an intuitive web interface. Search results, experiments, individual images or the entire dataset may be downloaded as standards-compliant OME-TIFF data.</p> <p>Conclusions</p> <p>The YRC PIR is a powerful resource for researchers to find, view, and download many images and associated metadata depicting the subcellular localization and colocalization of proteins, or classes of proteins, in a standards-compliant format. The YRC PIR is freely available at <url>http://images.yeastrc.org/</url>.</p

Genome wide prediction of protein function via a generic knowledge discovery approach based on evidence integration

BACKGROUND: The automation of many common molecular biology techniques has resulted in the accumulation of vast quantities of experimental data. One of the major challenges now facing researchers is how to process this data to yield useful information about a biological system (e.g. knowledge of genes and their products, and the biological roles of proteins, their molecular functions, localizations and interaction networks). We present a technique called Global Mapping of Unknown Proteins (GMUP) which uses the Gene Ontology Index to relate diverse sources of experimental data by creation of an abstraction layer of evidence data. This abstraction layer is used as input to a neural network which, once trained, can be used to predict function from the evidence data of unannotated proteins. The method allows us to include almost any experimental data set related to protein function, which incorporates the Gene Ontology, to our evidence data in order to seek relationships between the different sets. RESULTS: We have demonstrated the capabilities of this method in two ways. We first collected various experimental datasets associated with yeast (Saccharomyces cerevisiae) and applied the technique to a set of previously annotated open reading frames (ORFs). These ORFs were divided into training and test sets and were used to examine the accuracy of the predictions made by our method. Then we applied GMUP to previously un-annotated ORFs and made 1980, 836 and 1969 predictions corresponding to the GO Biological Process, Molecular Function and Cellular Component sub-categories respectively. We found that GMUP was particularly successful at predicting ORFs with functions associated with the ribonucleoprotein complex, protein metabolism and transportation. CONCLUSION: This study presents a global and generic gene knowledge discovery approach based on evidence integration of various genome-scale data. It can be used to provide insight as to how certain biological processes are implemented by interaction and coordination of proteins, which may serve as a guide for future analysis. New data can be readily incorporated as it becomes available to provide more reliable predictions or further insights into processes and interactions

Localization of Human RNase Z Isoforms: Dual Nuclear/Mitochondrial Targeting of the ELAC2 Gene Product by Alternative Translation Initiation

RNase Z is an endonuclease responsible for the removal of 3′ extensions from tRNA precursors, an essential step in tRNA biogenesis. Human cells contain a long form (RNase ZL) encoded by ELAC2, and a short form (RNase ZS; ELAC1). We studied their subcellular localization by expression of proteins fused to green fluorescent protein. RNase ZS was found in the cytosol, whereas RNase ZL localized to the nucleus and mitochondria. We show that alternative translation initiation is responsible for the dual targeting of RNase ZL. Due to the unfavorable context of the first AUG of ELAC2, translation apparently also starts from the second AUG, whereby the mitochondrial targeting sequence is lost and the protein is instead routed to the nucleus. Our data suggest that RNase ZL is the enzyme involved in both, nuclear and mitochondrial tRNA 3′ end maturation

Systematic Two-Hybrid and Comparative Proteomic Analyses Reveal Novel Yeast Pre-mRNA Splicing Factors Connected to Prp19

Prp19 is the founding member of the NineTeen Complex, or NTC, which is a spliceosomal subcomplex essential for spliceosome activation. To define Prp19 connectivity and dynamic protein interactions within the spliceosome, we systematically queried the Saccharomyces cerevisiae proteome for Prp19 WD40 domain interaction partners by two-hybrid analysis. We report that in addition to S. cerevisiae Cwc2, the splicing factor Prp17 binds directly to the Prp19 WD40 domain in a 1∶1 ratio. Prp17 binds simultaneously with Cwc2 indicating that it is part of the core NTC complex. We also find that the previously uncharacterized protein Urn1 (Dre4 in Schizosaccharomyces pombe) directly interacts with Prp19, and that Dre4 is conditionally required for pre-mRNA splicing in S. pombe. S. pombe Dre4 and S. cerevisiae Urn1 co-purify U2, U5, and U6 snRNAs and multiple splicing factors, and dre4Δ and urn1Δ strains display numerous negative genetic interactions with known splicing mutants. The S. pombe Prp19-containing Dre4 complex co-purifies three previously uncharacterized proteins that participate in pre-mRNA splicing, likely before spliceosome activation. Our multi-faceted approach has revealed new low abundance splicing factors connected to NTC function, provides evidence for distinct Prp19 containing complexes, and underscores the role of the Prp19 WD40 domain as a splicing scaffold

False positive reduction in protein-protein interaction predictions using gene ontology annotations

<p>Abstract</p> <p>Background</p> <p>Many crucial cellular operations such as metabolism, signalling, and regulations are based on protein-protein interactions. However, the lack of robust protein-protein interaction information is a challenge. One reason for the lack of solid protein-protein interaction information is poor agreement between experimental findings and computational sets that, in turn, comes from huge false positive predictions in computational approaches. Reduction of false positive predictions and enhancing true positive fraction of computationally predicted protein-protein interaction datasets based on highly confident experimental results has not been adequately investigated.</p> <p>Results</p> <p>Gene Ontology (GO) annotations were used to reduce false positive protein-protein interactions (PPI) pairs resulting from computational predictions. Using experimentally obtained PPI pairs as a training dataset, eight top-ranking keywords were extracted from GO molecular function annotations. The sensitivity of these keywords is 64.21% in the yeast experimental dataset and 80.83% in the worm experimental dataset. The specificities, a measure of recovery power, of these keywords applied to four predicted PPI datasets for each studied organisms, are 48.32% and 46.49% (by average of four datasets) in yeast and worm, respectively. Based on eight top-ranking keywords and co-localization of interacting proteins a set of two knowledge rules were deduced and applied to remove false positive protein pairs. The '<it>strength</it>', a measure of improvement provided by the rules was defined based on the signal-to-noise ratio and implemented to measure the applicability of knowledge rules applying to the predicted PPI datasets. Depending on the employed PPI-predicting methods, the <it>strength </it>varies between two and ten-fold of randomly removing protein pairs from the datasets.</p> <p>Conclusion</p> <p>Gene Ontology annotations along with the deduced knowledge rules could be implemented to partially remove false predicted PPI pairs. Removal of false positives from predicted datasets increases the true positive fractions of the datasets and improves the robustness of predicted pairs as compared to random protein pairing, and eventually results in better overlap with experimental results.</p

Moonlighting Proteins Hal3 and Vhs3 Form a Heteromeric PPCDC with Ykl088w in Yeast CoA Biosynthesis

Premi a l'excel·lència investigadora. 2010Unlike most other organisms, the essential five-step Coenzyme A biosynthetic pathway has not been fully resolved in yeast. Specifically, the gene(s) encoding the phosphopantothenoylcysteine decarboxylase (PPCDC) activity still remains unidentified. Sequence homology analyses suggest three candidates, namely Ykl088w, Hal3 and Vhs3, as putative PPCDC enzymes in Saccharomyces cerevisiae. Interestingly, Hal3 and Vhs3 have been characterized as negative regulatory subunits of the Ppz1 protein phosphatase. Here we show that YKL088w does not encode a third Ppz1 regulatory subunit, and that the essential roles of Ykl088w and the Hal3/Vhs3 pair are complementary, cannot be interchanged and can be attributed to PPCDC-related functions. We demonstrate that while known eukaryotic PPCDCs are homotrimers, the active yeast enzyme is a heterotrimer which consists of Ykl088w and Hal3/Vhs3 monomers that separately provides two essential catalytic residues. Our results unveil Hal3/Vhs3 as moonlighting proteins, involved in both CoA biosynthesis and protein phosphatase regulation

The Smc5–Smc6 Complex Is Required to Remove Chromosome Junctions in Meiosis

Meiosis, a specialized cell division with a single cycle of DNA replication round and two consecutive rounds of nuclear segregation, allows for the exchange of genetic material between parental chromosomes and the formation of haploid gametes. The structural maintenance of chromosome (SMC) proteins aid manipulation of chromosome structures inside cells. Eukaryotic SMC complexes include cohesin, condensin and the Smc5–Smc6 complex. Meiotic roles have been discovered for cohesin and condensin. However, although Smc5–Smc6 is known to be required for successful meiotic divisions, the meiotic functions of the complex are not well understood. Here we show that the Smc5–Smc6 complex localizes to specific chromosome regions during meiotic prophase I. We report that meiotic cells lacking Smc5–Smc6 undergo catastrophic meiotic divisions as a consequence of unresolved linkages between chromosomes. Surprisingly, meiotic segregation defects are not rescued by abrogation of Spo11-induced meiotic recombination, indicating that at least some chromosome linkages in smc5–smc6 mutants originate from other cellular processes. These results demonstrate that, as in mitosis, Smc5-Smc6 is required to ensure proper chromosome segregation during meiosis by preventing aberrant recombination intermediates between homologous chromosomes

Specialized interfaces of Smc5/6 control hinge stability and DNA association

The Structural Maintenance of Chromosomes (SMC) complexes: cohesin, condensin and Smc5/6 are involved in the organization of higher-order chromosome structure—which is essential for accurate chromosome duplication and segregation. Each complex is scaffolded by a specific SMC protein dimer (heterodimer in eukaryotes) held together via their hinge domains. Here we show that the Smc5/6-hinge, like those of cohesin and condensin, also forms a toroidal structure but with distinctive subunit interfaces absent from the other SMC complexes; an unusual ‘molecular latch’ and a functional ‘hub’. Defined mutations in these interfaces cause severe phenotypic effects with sensitivity to DNA-damaging agents in fission yeast and reduced viability in human cells. We show that the Smc5/6-hinge complex binds preferentially to ssDNA and that this interaction is affected by both ‘latch’ and ‘hub’ mutations, suggesting a key role for these unique features in controlling DNA association by the Smc5/6 complex

Towards Establishment of a Rice Stress Response Interactome

Rice (Oryza sativa) is a staple food for more than half the world and a model for studies of monocotyledonous species, which include cereal crops and candidate bioenergy grasses. A major limitation of crop production is imposed by a suite of abiotic and biotic stresses resulting in 30%–60% yield losses globally each year. To elucidate stress response signaling networks, we constructed an interactome of 100 proteins by yeast two-hybrid (Y2H) assays around key regulators of the rice biotic and abiotic stress responses. We validated the interactome using protein–protein interaction (PPI) assays, co-expression of transcripts, and phenotypic analyses. Using this interactome-guided prediction and phenotype validation, we identified ten novel regulators of stress tolerance, including two from protein classes not previously known to function in stress responses. Several lines of evidence support cross-talk between biotic and abiotic stress responses. The combination of focused interactome and systems analyses described here represents significant progress toward elucidating the molecular basis of traits of agronomic importance