H3K4me3 breadth is linked to cell identity and transcriptional consistency.

Trimethylation of histone H3 at lysine 4 (H3K4me3) is a chromatin modification known to mark the transcription start sites of active genes. Here, we show that H3K4me3 domains that spread more broadly over genes in a given cell type preferentially mark genes that are essential for the identity and function of that cell type. Using the broadest H3K4me3 domains as a discovery tool in neural progenitor cells, we identify novel regulators of these cells. Machine learning models reveal that the broadest H3K4me3 domains represent a distinct entity, characterized by increased marks of elongation. The broadest H3K4me3 domains also have more paused polymerase at their promoters, suggesting a unique transcriptional output. Indeed, genes marked by the broadest H3K4me3 domains exhibit enhanced transcriptional consistency and [corrected] increased transcriptional levels, and perturbation of H3K4me3 breadth leads to changes in transcriptional consistency. Thus, H3K4me3 breadth contains information that could ensure transcriptional precision at key cell identity/function genes.

Complex Portal 2022: new curation frontiers.

The Complex Portal (www.ebi.ac.uk/complexportal) is a manually curated, encyclopaedic database of macromolecular complexes with known function from a range of model organisms. It summarizes complex composition, topology and function along with links to a large range of domain-specific resources (i.e. wwPDB, EMDB and Reactome). Since the last update in 2019, we have produced a first draft complexome for Escherichia coli, maintained and updated that of Saccharomyces cerevisiae, added over 40 coronavirus complexes and increased the human complexome to over 1100 complexes that include approximately 200 complexes that act as targets for viral proteins or are part of the immune system. The display of protein features in ComplexViewer has been improved and the participant table is now colour-coordinated with the nodes in ComplexViewer. Community collaboration has expanded, for example by contributing to an analysis of putative transcription cofactors and providing data accessible to semantic web tools through Wikidata which is now populated with manually curated Complex Portal content through a new bot. Our data license is now CC0 to encourage data reuse. Users are encouraged to get in touch, provide us with feedback and send curation requests through the 'Support' link.

Analysing the yeast complexome-the Complex Portal rising to the challenge.

The EMBL-EBI Complex Portal is a knowledgebase of macromolecular complexes providing persistent stable identifiers. Entries are linked to literature evidence and provide details of complex membership, function, structure and complex-specific Gene Ontology annotations. Data are freely available and downloadable in HUPO-PSI community standards and missing entries can be requested for curation. In collaboration with Saccharomyces Genome Database and UniProt, the yeast complexome, a compendium of all known heteromeric assemblies from the model organism Saccharomyces cerevisiae, was curated. This expansion of knowledge and scope has led to a 50% increase in curated complexes compared to the previously published dataset, CYC2008. The yeast complexome is used as a reference resource for the analysis of complexes from large-scale experiments. Our analysis showed that genes coding for proteins in complexes tend to have more genetic interactions, are co-expressed with more genes, are more multifunctional, localize more often in the nucleus, and are more often involved in nucleic acid-related metabolic processes and processes where large machineries are the predominant functional drivers. A comparison to genetic interactions showed that about 40% of expanded co-complex pairs also have genetic interactions, suggesting strong functional links between complex members.

Transcriptome visualization and data availability at the Saccharomyces Genome Database.

The Saccharomyces Genome Database (SGD; www.yeastgenome.org) maintains the official annotation of all genes in the Saccharomyces cerevisiae reference genome and aims to elucidate the function of these genes and their products by integrating manually curated experimental data. Technological advances have allowed researchers to profile RNA expression and identify transcripts at high resolution. These data can be configured in web-based genome browser applications for display to the general public. Accordingly, SGD has incorporated published transcript isoform data in our instance of JBrowse, a genome visualization platform. This resource will help clarify S. cerevisiae biological processes by furthering studies of transcriptional regulation, untranslated regions, genome engineering, and expression quantification in S. cerevisiae.

Complex Portal 2018: extended content and enhanced visualization tools for macromolecular complexes.

The Complex Portal (www.ebi.ac.uk/complexportal) is a manually curated, encyclopaedic database that collates and summarizes information on stable, macromolecular complexes of known function. It captures complex composition, topology and function and links out to a large range of domain-specific resources that hold more detailed data, such as PDB or Reactome. We have made several significant improvements since our last update, including improving compliance to the FAIR data principles by providing complex-specific, stable identifiers that include versioning. Protein complexes are now available from 20 species for download in standards-compliant formats such as PSI-XML, MI-JSON and ComplexTAB or can be accessed via an improved REST API. A component-based JS front-end framework has been implemented to drive a new website and this has allowed the use of APIs from linked services to import and visualize information such as the 3D structure of protein complexes, its role in reactions and pathways and the co-expression of complex components in the tissues of multi-cellular organisms. A first draft of the complete complexome of Saccharomyces cerevisiae is now available to browse and download.

Saccharomyces genome database informs human biology.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is an expertly curated database of literature-derived functional information for the model organism budding yeast, Saccharomyces cerevisiae. SGD constantly strives to synergize new types of experimental data and bioinformatics predictions with existing data, and to organize them into a comprehensive and up-to-date information resource. The primary mission of SGD is to facilitate research into the biology of yeast and to provide this wealth of information to advance, in many ways, research on other organisms, even those as evolutionarily distant as humans. To build such a bridge between biological kingdoms, SGD is curating data regarding yeast-human complementation, in which a human gene can successfully replace the function of a yeast gene, and/or vice versa. These data are manually curated from published literature, made available for download, and incorporated into a variety of analysis tools provided by SGD.

Development of a 90-Minute Integrated Noninvasive Urinary Assay for Bladder Cancer Detection.

PURPOSE: Despite suboptimal sensitivity urine cytology is often performed as an adjunct to cystoscopy for bladder cancer diagnosis. We aimed to develop a noninvasive, fast molecular diagnostic test for bladder cancer detection with better sensitivity than urine cytology while maintaining adequate specificity. MATERIALS AND METHODS: Urine specimens were collected at 18 multinational sites from subjects prior to cystoscopy or tumor resection, and from healthy and other control subjects without evidence of bladder cancer. The levels of 10 urinary mRNAs were measured in a training cohort of 483 subjects and regression analysis was used to identify a 5-mRNA model to predict cancer status. The performance of the GeneXpert® Bladder Cancer Assay, an assay labeled for investigational use only to detect the 5 mRNAs ABL1, CRH, IGF2, ANXA10 and UPK1B, was evaluated in an independent test cohort of 450 participants. RESULTS: In the independent test cohort the assay ROC curve AUC was 0.87 (95% CI 0.81-0.92). At an example cutoff point of 0.4 overall sensitivity was 73% while specificity was 90% and 77% in the hematuria and surveillance patient populations, respectively. CONCLUSIONS: We developed a 90-minute, urine based test that is simple to perform for the detection of bladder cancer. The test can help guide physician decision making in the management of bladder cancer. Additional evaluation in a prospective study is needed to establish the clinical usefulness of this assay.

The Saccharomyces Genome Database Variant Viewer.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the authoritative community resource for the Saccharomyces cerevisiae reference genome sequence and its annotation. In recent years, we have moved toward increased representation of sequence variation and allelic differences within S. cerevisiae. The publication of numerous additional genomes has motivated the creation of new tools for their annotation and analysis. Here we present the Variant Viewer: a dynamic open-source web application for the visualization of genomic and proteomic differences. Multiple sequence alignments have been constructed across high quality genome sequences from 11 different S. cerevisiae strains and stored in the SGD. The alignments and summaries are encoded in JSON and used to create a two-tiered dynamic view of the budding yeast pan-genome, available at http://www.yeastgenome.org/variant-viewer.

The complex portal--an encyclopaedia of macromolecular complexes.

The IntAct molecular interaction database has created a new, free, open-source, manually curated resource, the Complex Portal (www.ebi.ac.uk/intact/complex), through which protein complexes from major model organisms are being collated and made available for search, viewing and download. It has been built in close collaboration with other bioinformatics services and populated with data from ChEMBL, MatrixDB, PDBe, Reactome and UniProtKB. Each entry contains information about the participating molecules (including small molecules and nucleic acids), their stoichiometry, topology and structural assembly. Complexes are annotated with details about their function, properties and complex-specific Gene Ontology (GO) terms. Consistent nomenclature is used throughout the resource with systematic names, recommended names and a list of synonyms all provided. The use of the Evidence Code Ontology allows us to indicate for which entries direct experimental evidence is available or if the complex has been inferred based on homology or orthology. The data are searchable using standard identifiers, such as UniProt, ChEBI and GO IDs, protein, gene and complex names or synonyms. This reference resource will be maintained and grow to encompass an increasing number of organisms. Input from groups and individuals with specific areas of expertise is welcome.

Saccharomyces genome database provides new regulation data.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the community resource for genomic, gene and protein information about the budding yeast Saccharomyces cerevisiae, containing a variety of functional information about each yeast gene and gene product. We have recently added regulatory information to SGD and present it on a new tabbed section of the Locus Summary entitled 'Regulation'. We are compiling transcriptional regulator-target gene relationships, which are curated from the literature at SGD or imported, with permission, from the YEASTRACT database. For nearly every S. cerevisiae gene, the Regulation page displays a table of annotations showing the regulators of that gene, and a graphical visualization of its regulatory network. For genes whose products act as transcription factors, the Regulation page also shows a table of their target genes, accompanied by a Gene Ontology enrichment analysis of the biological processes in which those genes participate. We additionally synthesize information from the literature for each transcription factor in a free-text Regulation Summary, and provide other information relevant to its regulatory function, such as DNA binding site motifs and protein domains. All of the regulation data are available for querying, analysis and download via YeastMine, the InterMine-based data warehouse system in use at SGD.

Saccharomyces Genome Database: the genomics resource of budding yeast.

The Saccharomyces Genome Database (SGD, http://www.yeastgenome.org) is the community resource for the budding yeast Saccharomyces cerevisiae. The SGD project provides the highest-quality manually curated information from peer-reviewed literature. The experimental results reported in the literature are extracted and integrated within a well-developed database. These data are combined with quality high-throughput results and provided through Locus Summary pages, a powerful query engine and rich genome browser. The acquisition, integration and retrieval of these data allow SGD to facilitate experimental design and analysis by providing an encyclopedia of the yeast genome, its chromosomal features, their functions and interactions. Public access to these data is provided to researchers and educators via web pages designed for optimal ease of use.

Subthalamic nucleus deep brain stimulation for Parkinson's disease: evidence for effectiveness and limitations from 12 years' experience.

OBJECTIVE: To present the result and experience of subthalamic nucleus deep brain stimulation for Parkinson's disease. DESIGN: Case series. SETTING: Prince of Wales Hospital, Hong Kong. PATIENTS: A cohort of patients with Parkinson's disease received subthalamic nucleus deep brain stimulation from September 1998 to January 2010. Patient assessment data before and after the operation were collected prospectively. RESULTS: Forty-one patients (21 male and 20 female) with Parkinson's disease underwent bilateral subthalamic nucleus deep brain stimulation and were followed up for a median interval of 12 months. For the whole group, the mean improvements of Unified Parkinson's Disease Rating Scale (UPDRS) parts II and III were 32.5% and 31.5%, respectively (P<0.001). Throughout the years, a multidisciplinary team was gradually built. The deep brain stimulation protocol evolved and was substantiated by updated patient selection criteria and outcome assessment, integrated imaging and neurophysiological targeting, refinement of surgical technique as well as the accumulation of experience in deep brain stimulation programming. Most of the structural improvement occurred before mid-2005. Patients receiving the operation before June 2005 (19 cases) and after (22 cases) were compared; the improvements in UPDRS part III were 13.2% and 55.2%, respectively (P<0.001). There were three operative complications (one lead migration, one cerebral haematoma, and one infection) in the group operated on before 2005. There was no operative mortality. CONCLUSIONS: The functional state of Parkinson's disease patients with motor disabilities refractory to best medical treatment improved significantly after subthalamic nucleus deep brain stimulation. A dedicated multidisciplinary team building, refined protocol for patient selection and assessment, improvement of targeting methods, meticulous surgical technique, and experience in programming are the key factors contributing to the improved outcome.

Occupational health and safety activities undertaken by physiotherapy students: A retrospective review of industry placement reports.

BACKGROUND: The University of South Australia's Bachelor of Physiotherapy course, 'Work Health and Safety (WHS) Practice', provides students with introductory practical WHS experience. Students undertake 80-hour effort WHS projects for industry, culminating in a report for hosts. OBJECTIVE: To establish the types of industry that host WHS undergraduate physiotherapy placements and the nature of activities that students conduct. METHODS: Reports were retrospectively, systematically classified using a descriptive, document content analysis approach. Demographic data were collected: report and student numbers, placement locations and industry types. Selected reports were used as a subset for further analysis with definitions created to classify the nature of placement activities. RESULTS: Most reports were written by a pair of students (88%, n = 269), with placements based in metropolitan Adelaide (91%, n = 284). Various industries hosted students, including healthcare and social assistance (40%, n = 117) and manufacturing (30%, n = 89). Reports primarily included risk management activities as required by WHS legislation (97%, n = 229). CONCLUSION: Physiotherapy student WHS activities maintain close links with industry, involving stakeholders (workforce, students, University of South Australia and academics). At an entry-level standard, the student WHS activities align well with some criteria set as key competencies for Australian Occupational Health physiotherapy practitioners.

Saccharomyces genome database update: server architecture, pan-genome nomenclature, and external resources.

As one of the first model organism knowledgebases, Saccharomyces Genome Database (SGD) has been supporting the scientific research community since 1993. As technologies and research evolve, so does SGD: from updates in software architecture, to curation of novel data types, to incorporation of data from, and collaboration with, other knowledgebases. We are continuing to make steps toward providing the community with an S. cerevisiae pan-genome. Here, we describe software upgrades, a new nomenclature system for genes not found in the reference strain, and additions to gene pages. With these improvements, we aim to remain a leading resource for students, researchers, and the broader scientific community.

Saccharomyces Genome Database provides mutant phenotype data.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is a scientific database for the molecular biology and genetics of the yeast Saccharomyces cerevisiae, which is commonly known as baker's or budding yeast. The information in SGD includes functional annotations, mapping and sequence information, protein domains and structure, expression data, mutant phenotypes, physical and genetic interactions and the primary literature from which these data are derived. Here we describe how published phenotypes and genetic interaction data are annotated and displayed in SGD.

New data and collaborations at the Saccharomyces Genome Database: updated reference genome, alleles, and the Alliance of Genome Resources.

Saccharomyces cerevisiae is used to provide fundamental understanding of eukaryotic genetics, gene product function, and cellular biological processes. Saccharomyces Genome Database (SGD) has been supporting the yeast research community since 1993, serving as its de facto hub. Over the years, SGD has maintained the genetic nomenclature, chromosome maps, and functional annotation, and developed various tools and methods for analysis and curation of a variety of emerging data types. More recently, SGD and six other model organism focused knowledgebases have come together to create the Alliance of Genome Resources to develop sustainable genome information resources that promote and support the use of various model organisms to understand the genetic and genomic bases of human biology and disease. Here we describe recent activities at SGD, including the latest reference genome annotation update, the development of a curation system for mutant alleles, and new pages addressing homology across model organisms as well as the use of yeast to study human disease.

Comparison of strain typing results for Clostridium difficile isolates from North America.

Accurate strain typing is critical for understanding the changing epidemiology of Clostridium difficile infections. We typed 350 isolates of toxigenic C. difficile from 2008 to 2009 from seven laboratories in the United States and Canada. Typing was performed by PCR-ribotyping, pulsed-field gel electrophoresis (PFGE), and restriction endonuclease analysis (REA) of whole-cell DNA. The Cepheid Xpert C. difficile test for presumptive identification of 027/NAP1/BI isolates was also tested directly on original stool samples. Of 350 isolates, 244 (70%) were known PCR ribotypes, 224 (68%) were 1 of 8 common REA groups, and 187 (54%) were known PFGE types. Eighty-four isolates typed as 027, NAP1, and BI, and 83 of these were identified as presumptive 027/NAP1/BI by Xpert C. difficile. Eight additional isolates were called presumptive 027/NAP1/BI by Xpert C. difficile, of which three were ribotype 027. Five PCR ribotypes contained multiple REA groups, and three North American pulsed-field (NAP) profiles contained both multiple REA groups and PCR ribotypes. There was modest concordance of results among the three methods for C. difficile strains, including the J strain (ribotype 001 and PFGE NAP2), the toxin A-negative 017 strain (PFGE NAP9 and REA type CF), the 078 animal strain (PFGE NAP7 and REA type BK), and type 106 (PFGE NAP11 and REA type DH). PCR-ribotyping, REA, and PFGE provide different but overlapping patterns of strain clustering. Unlike the other methods, the Xpert C. difficile 027/NAP1/BI assay gave results directly from stool specimens, required only 45 min to complete, but was limited to detection of a single strain type.

Impact of strain type on detection of toxigenic Clostridium difficile: comparison of molecular diagnostic and enzyme immunoassay approaches.

A multicenter clinical trial assessed the performance of the Cepheid Xpert C. difficile assay on stool specimens collected from patients suspected of having Clostridium difficile infection (CDI). A total of 2,296 unformed stool specimens, collected from seven study sites, were tested by Xpert C. difficile enrichment culture followed by cell culture cytotoxicity testing of the isolates (i.e., toxigenic culture with enrichment) and the study sites' standard C. difficile test methods. The methods included enzyme immunoassay (EIA), direct cytotoxin testing, and two- and three-step algorithms using glutamate dehydrogenase (GDH) screening followed by either EIA or EIA and an in-house PCR assay. All C. difficile strains were typed by PCR-ribotyping. Compared to results for toxigenic culture with enrichment, the sensitivity, specificity, and positive and negative predictive values of the Xpert assay were 93.5, 94.0, 73.0, and 98.8%, respectively. The overall sensitivity of the EIAs compared to that of enrichment culture was 60.0%, and the sensitivity of combined GDH algorithms was 72.9%; both were significantly lower than that of Xpert C. difficile (P < 0.001 and P = 0.03, respectively). The sensitivity of the EIA was significantly lower than that of the Xpert C. difficile assay for detection of ribotypes 002, 027, and 106 (P < 0.0001, P < 0.0001, and P = 0.004, respectively, Fisher's exact test), and the sensitivity of GDH algorithms for ribotypes other than 027 was lower than that for Xpert C. difficile (P < 0.001). The Xpert C. difficile assay is a simple, rapid, and accurate method for detection of toxigenic C. difficile in unformed stool specimens and is minimally affected by strain type compared to EIA and GDH-based methods.

Gene Ontology annotations at SGD: new data sources and annotation methods.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) collects and organizes biological information about the chromosomal features and gene products of the budding yeast Saccharomyces cerevisiae. Although published data from traditional experimental methods are the primary sources of evidence supporting Gene Ontology (GO) annotations for a gene product, high-throughput experiments and computational predictions can also provide valuable insights in the absence of an extensive body of literature. Therefore, GO annotations available at SGD now include high-throughput data as well as computational predictions provided by the GO Annotation Project (GOA UniProt; http://www.ebi.ac.uk/GOA/). Because the annotation method used to assign GO annotations varies by data source, GO resources at SGD have been modified to distinguish data sources and annotation methods. In addition to providing information for genes that have not been experimentally characterized, GO annotations from independent sources can be compared to those made by SGD to help keep the literature-based GO annotations current.