The Gene Ontology (GO) Cellular Component Ontology: integration with SAO (Subcellular Anatomy Ontology) and other recent developments

Dissecting OGT's TPR domain to identify determinants of cellular function

O-GlcNAc transferase (OGT) is an essential mammalian enzyme that glycosylates myriad intracellular proteins and cleaves the transcriptional coregulator Host Cell Factor 1 to regulate cell cycle processes. Via these catalytic activities as well as noncatalytic protein-protein interactions, OGT maintains cell homeostasis. OGT's tetratricopeptide repeat (TPR) domain is important in substrate recognition, but there is little information on how changing the TPR domain impacts its cellular functions. Here, we investigate how altering OGT's TPR domain impacts cell growth after the endogenous enzyme is deleted. We find that disrupting the TPR residues required for OGT dimerization leads to faster cell growth, whereas truncating the TPR domain slows cell growth. We also find that OGT requires eight of its 13 TPRs to sustain cell viability. OGT-8, like the nonviable shorter OGT variants, is mislocalized and has reduced Ser/Thr glycosylation activity; moreover, its interactions with most of wild-type OGT's binding partners are broadly attenuated. Therefore, although OGT's five N-terminal TPRs are not essential for cell viability, they are required for proper subcellular localization and for mediating many of OGT's protein-protein interactions. Because the viable OGT truncation variant we have identified preserves OGT's essential functions, it may facilitate their identification.

Calciprotein Particles Induce Cellular Compartment-Specific Proteome Alterations in Human Arterial Endothelial Cells

Calciprotein particles (CPPs) are indispensable scavengers of excessive Ca2+ and PO43- ions in blood, being internalised and recycled by liver and spleen macrophages, monocytes, and endothelial cells (ECs). Here, we performed a pathway enrichment analysis of cellular compartment-specific proteomes in primary human coronary artery ECs (HCAEC) and human internal thoracic artery ECs (HITAEC) treated with primary (amorphous) or secondary (crystalline) CPPs (CPP-P and CPPs, respectively). Exposure to CPP-P and CPP-S induced notable upregulation of: (1) cytokine- and chemokine-mediated signaling, Ca2+-dependent events, and apoptosis in cytosolic and nuclear proteomes; (2) H+ and Ca2+ transmembrane transport, generation of reactive oxygen species, mitochondrial outer membrane permeabilisation, and intrinsic apoptosis in the mitochondrial proteome; (3) oxidative, calcium, and endoplasmic reticulum (ER) stress, unfolded protein binding, and apoptosis in the ER proteome. In contrast, transcription, post-transcriptional regulation, translation, cell cycle, and cell-cell adhesion pathways were underrepresented in cytosol and nuclear compartments, whilst biosynthesis of amino acids, mitochondrial translation, fatty acid oxidation, pyruvate dehydrogenase activity, and energy generation were downregulated in the mitochondrial proteome of CPP-treated ECs. Differentially expressed organelle-specific pathways were coherent in HCAEC and HITAEC and between ECs treated with CPP-P or CPP-S. Proteomic analysis of mitochondrial and nuclear lysates from CPP-treated ECs confirmed bioinformatic filtration findings.

Structural coverage of the human interactome

Complex biological processes in cells are embedded in the interactome, representing the complete set of protein-protein interactions. Mapping and analyzing the protein structures are essential to fully comprehending these processes' molecular details. Therefore, knowing the structural coverage of the interactome is important to show the current limitations. Structural modeling of protein-protein interactions requires accurate protein structures. In this study, we mapped all experimental structures to the reference human proteome. Later, we found the enrichment in structural coverage when complementary methods such as homology modeling and deep learning (AlphaFold) were included. We then collected the interactions from the literature and databases to form the reference human interactome, resulting in 117 897 non-redundant interactions. When we analyzed the structural coverage of the interactome, we found that the number of experimentally determined protein complex structures is scarce, corresponding to 3.95% of all binary interactions. We also analyzed known and modeled structures to potentially construct the structural interactome with a docking method. Our analysis showed that 12.97% of the interactions from HuRI and 73.62% and 32.94% from the filtered versions of STRING and HIPPIE could potentially be modeled with high structural coverage or accuracy, respectively. Overall, this paper provides an overview of the current state of structural coverage of the human proteome and interactome.

RNA sequencing analysis revealed differentially expressed genes and their functional annotation in porcine longissimus dorsi muscle affected by dietary lysine restriction

The objective of this study was to investigate the effects of dietary lysine restriction on the global gene expression profile of skeletal muscle in growing pigs. Twelve crossbred (Yorkshire × Landrace) barrows (initial BW 22.6 ± 2.04 kg) were randomly assigned to two dietary treatments (LDD: a lysine-deficient diet; LAD: a lysine-adequate diet) according to a completely randomized experiment design (n = 6). After feeding for 8 weeks, skeletal muscle was sampled from the longissimus dorsi of individual pigs. The muscle total RNA was isolated and cDNA libraries were prepared for RNA sequencing (RNA-Seq) analysis. The RNA-Seq data obtained was then analyzed using the CLC Genomics Workbench to identify differentially expressed genes (DEGs). A total of 80 genes (padj ≤ 0.05) were differentially expressed in the longissimus dorsi muscle of the pigs fed LDD vs. LAD, of which 46 genes were downregulated and 34 genes were upregulated. Gene Ontology (GO) analysis of the DEGs (padj ≤ 0.05) for functional annotation identified those GO terms that are mostly associated with the molecular functions of structural molecules and metabolic enzymes (e.g., oxidoreductase and endopeptidase), biological process of acute-phase response, and amino acid metabolism including synthesis and degradation in the extracellular matrix region. Collectively, the results of this study have provided some novel insight regarding the molecular mechanisms of muscle growth that are associated with dietary lysine supply.

Use of Tandem Mass Spectrometry Quantitative Proteomics to Identify Potential Biomarkers to Follow the Effects of Cold and Frozen Storage of Muscle Tissue of Litopenaeus vannamei

L. vannamei has become one of the most productive species. However, it is susceptible to microbial contamination during fishing, transportation, and storage, which can lead to spoilage and quality deterioration. This study investigates the relationship between changes in the proteome of Litopenaeus vannamei (L. vannamei) muscle and quality characteristics during low-temperature storage using the tandem mass spectrometry technology of quantitative proteomics strategy. The differential expression of proteins under cold storage (4 °C, CS), partial slight freezing (-3 °C, PFS), and frozen storage (-18 °C, FS) conditions was compared with the fresh group (CK), resulting in 1572 proteins identified as differentially expressed. The purpose of this research is to identify potential biochemical markers by analyzing quality changes and relative differential proteins through searches in the UniProt database, Gene Ontology database, and Genome Encyclopedia. Correlation analysis revealed that seven DEPs were significantly related to physical and chemical indicators. Bioinformatics analysis demonstrated that most DEPs are involved in binding proteins, metabolic enzymes, and protein turnover. Additionally, some DEPs were identified as potential biomarkers for muscle decline. These findings contribute to understanding the mechanism of freshness decline in L. vannamei under low-temperature storage and the changes in muscle proteome.

Distinguish the Characteristic Mechanism of 3 Drug Pairs of Corydalis Rhizome in Ameliorating Angina Pectoris: Network Pharmacology and Meta-Analysis

Objective: Angina pectoris (AP), affecting over 523 million people, can be alleviated by corydalis rhizome (CR), usually combined with chuanxiong rhizome (CXR), angelica dahuricae radix (ADR), or astragali radix (AR) to enhance the effect. This study aims to distinguish the different mechanisms among 3 drug pairs to treat AP. Methods: The drug pair-disease intersection targets, compound targets, protein–protein interaction (PPI), and herb-compound-target-pathway network were obtained by Cytoscape, STRING, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses ( http://www.kegg.jp/ or http://www.genome.jp/kegg/ ). Importantly, with principal component analysis (PCA), the key point of KEGG and GO were explored and supported, while by meta-analysis, the different mechanisms of the drug pairs on AP were discovered. Results: JUN, SRC, PIK3CA, and MAPK1 as PPI core network of CR-AP, (CR-CXR)-AP, (CR-ADR)-AP, and (CR-AR)-AP. (highest confidence > 0.9). 10, 45, 35, and 21 key compounds, and 68, 123, 117, and 97 core targets were obtained from CR-AP, (CR-CXR)-AP, (CR-ADR)-AP, and (CR-AR)-AP based on more than 2-fold median value for degree and betweenness centrality, more than the median of closeness centrality. The core pathways of (CR-CXR)-AP and (CR-AR)-AP cover “fluid shear stress and atherosclerosis” and the “pathways in cancer”, while (CR-ADR)-AP was found as the “pathways in cancer” by PCA and KEGG ( P < .01). The core biological processes of (BP) (CR-CXR)-AP, (CR-ADR)-AP, and (CR-AR)-AP were all enriched in the “circulatory system process” by PCA and GO ( P < .01). Moreover, meta-analysis indicated the significant differences ( P < .05) of the 3 drug pairs. Conclusion: CR-CXR, CR-ADR, or CR-AR outperformed CR-AP in AP mitigation. Furthermore, meta-analysis revealed, CR-CXR was superior to alleviating AP by affecting “circulatory system process” and “fluid shear stress and atherosclerosis”, particularly the targets PTGS1, PTGS2, ADRB2, ADRA2C, and NOS, when compared with the drug pair of CR-ADR and the CR-AR.

Extending and using anatomical vocabularies in the stimulating peripheral activity to relieve conditions project

The stimulating peripheral activity to relieve conditions (SPARC) program is a US National Institutes of Health-funded effort to improve our understanding of the neural circuitry of the autonomic nervous system (ANS) in support of bioelectronic medicine. As part of this effort, the SPARC project is generating multi-species, multimodal data, models, simulations, and anatomical maps supported by a comprehensive knowledge base of autonomic circuitry. To facilitate the organization of and integration across multi-faceted SPARC data and models, SPARC is implementing the findable, accessible, interoperable, and reusable (FAIR) data principles to ensure that all SPARC products are findable, accessible, interoperable, and reusable. We are therefore annotating and describing all products with a common FAIR vocabulary. The SPARC Vocabulary is built from a set of community ontologies covering major domains relevant to SPARC, including anatomy, physiology, experimental techniques, and molecules. The SPARC Vocabulary is incorporated into tools researchers use to segment and annotate their data, facilitating the application of these ontologies for annotation of research data. However, since investigators perform deep annotations on experimental data, not all terms and relationships are available in community ontologies. We therefore implemented a term management and vocabulary extension pipeline where SPARC researchers may extend the SPARC Vocabulary using InterLex, an online vocabulary management system. To ensure the quality of contributed terms, we have set up a curated term request and review pipeline specifically for anatomical terms involving expert review. Accepted terms are added to the SPARC Vocabulary and, when appropriate, contributed back to community ontologies to enhance ANS coverage. Here, we provide an overview of the SPARC Vocabulary, the infrastructure and process for implementing the term management and review pipeline. In an analysis of >300 anatomical contributed terms, the majority represented composite terms that necessitated combining terms within and across existing ontologies. Although these terms are not good candidates for community ontologies, they can be linked to structures contained within these ontologies. We conclude that the term request pipeline serves as a useful adjunct to community ontologies for annotating experimental data and increases the FAIRness of SPARC data.

Genome-Wide Identification and Expression Profiling of KCS Gene Family in Passion Fruit (Passiflora edulis) Under Fusarium kyushuense and Drought Stress Conditions

Plant and fruit surfaces are covered with cuticle wax and provide a protective barrier against biotic and abiotic stresses. Cuticle wax consists of very-long-chain fatty acids (VLCFAs) and their derivatives. β-Ketoacyl-CoA synthase (KCS) is a key enzyme in the synthesis of VLCFAs and provides a precursor for the synthesis of cuticle wax, but the KCS gene family was yet to be reported in the passion fruit (Passiflora edulis). In this study, thirty-two KCS genes were identified in the passion fruit genome and phylogenetically grouped as KCS1-like, FAE1-like, FDH-like, and CER6-like. Furthermore, thirty-one PeKCS genes were positioned on seven chromosomes, while one PeKCS was localized to the unassembled genomic scaffold. The cis-element analysis provides insight into the possible role of PeKCS genes in phytohormones and stress responses. Syntenic analysis revealed that gene duplication played a crucial role in the expansion of the PeKCS gene family and underwent a strong purifying selection. All PeKCS proteins shared similar 3D structures, and a protein-protein interaction network was predicted with known Arabidopsis proteins. There were twenty putative ped-miRNAs which were also predicted that belong to nine families targeting thirteen PeKCS genes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation results were highly associated with fatty acid synthase and elongase activity, lipid metabolism, stress responses, and plant-pathogen interaction. The highly enriched transcription factors (TFs) including ERF, MYB, Dof, C2H2, TCP, LBD, NAC, and bHLH were predicted in PeKCS genes. qRT-PCR expression analysis revealed that most PeKCS genes were highly upregulated in leaves including PeKCS2, PeKCS4, PeKCS8, PeKCS13, and PeKCS9 but not in stem and roots tissues under drought stress conditions compared with controls. Notably, most PeKCS genes were upregulated at 9th dpi under Fusarium kyushuense biotic stress condition compared to controls. This study provides a basis for further understanding the functions of KCS genes, improving wax and VLCFA biosynthesis, and improvement of passion fruit resistance.

Elephant seal muscle cells adapt to sustained glucocorticoid exposure by shifting their metabolic phenotype

Elephant seals experience natural periods of prolonged food deprivation while breeding, molting, and undergoing postnatal development. Prolonged food deprivation in elephant seals increases circulating glucocorticoids without inducing muscle atrophy, but the cellular mechanisms that allow elephant seals to cope with such conditions remain elusive. We generated a cellular model and conducted transcriptomic, metabolic, and morphological analyses to study how seal cells adapt to sustained glucocorticoid exposure. Seal muscle progenitor cells differentiate into contractile myotubes with a distinctive morphology, gene expression profile, and metabolic phenotype. Exposure to dexamethasone at three ascending concentrations for 48 h modulated the expression of six clusters of genes related to structural constituents of muscle and pathways associated with energy metabolism and cell survival. Knockdown of the glucocorticoid receptor (GR) and downstream expression analyses corroborated that GR mediates the observed effects. Dexamethasone also decreased cellular respiration, shifted the metabolic phenotype toward glycolysis, and induced mitochondrial fission and dissociation of mitochondria-endoplasmic reticulum (ER) interactions without decreasing cell viability. Knockdown of DNA damage-inducible transcript 4 (DDIT4), a GR target involved in the dissociation of mitochondria-ER membranes, recovered respiration and modulated antioxidant gene expression in myotubes treated with dexamethasone. These results show that adaptation to sustained glucocorticoid exposure in elephant seal myotubes involves a metabolic shift toward glycolysis, which is supported by alterations in mitochondrial morphology and a reduction in mitochondria-ER interactions, resulting in decreased respiration without compromising cell survival.

BRENDA, the ELIXIR core data resource in 2021: new developments and updates

The BRENDA enzyme database (https://www.brenda-enzymes.org), established in 1987, has evolved into the main collection of functional enzyme and metabolism data. In 2018, BRENDA was selected as an ELIXIR Core Data Resource. BRENDA provides reliable data, continuous curation and updates of classified enzymes, and the integration of newly discovered enzymes. The main part contains >5 million data for ∼90 000 enzymes from ∼13 000 organisms, manually extracted from ∼157 000 primary literature references, combined with information of text and data mining, data integration, and prediction algorithms. Supplements comprise disease-related data, protein sequences, 3D structures, genome annotations, ligand information, taxonomic, bibliographic, and kinetic data. BRENDA offers an easy access to enzyme information from quick to advanced searches, text- and structured-based queries for enzyme-ligand interactions, word maps, and visualization of enzyme data. The BRENDA Pathway Maps are completely revised and updated for an enhanced interactive and intuitive usability. The new design of the Enzyme Summary Page provides an improved access to each individual enzyme. A new protein structure 3D viewer was integrated. The prediction of the intracellular localization of eukaryotic enzymes has been implemented. The new EnzymeDetector combines BRENDA enzyme annotations with protein and genome databases for the detection of eukaryotic and prokaryotic enzymes.

Bioinformatic Prediction of Gene Ontology Terms of Uncharacterized Proteins from Chromosome 11

In chromosome 11, 71 out of its 1254 proteins remain functionally uncharacterized on the basis of their existence evidence (uPE1s) following the latest version of neXtProt (release 2020-01-17). Because in vivo and in vitro experimental strategies are often time-consuming and labor-intensive, there is a need for a bioinformatics tool to predict the function annotation. Here, we used I-TASSER/COFACTOR provided on the neXtProt web site, which predicts gene ontology (GO) terms based on the 3D structure of the protein. I-TASSER/COFACTOR predicted 2413 GO terms with a benchmark dataset of the 22 proteins belonging to PE1 of chromosome 11. In this study, we developed a filtering algorithm in order to select specific GO terms using the GO map generated by I-TASSER/COFACTOR. As a result, 187 specific GO terms showed a higher average precision-recall score at the least cellular component term compared to 2413 predicted GO terms. Next, we applied 65 proteins belonging to uPE1s of chromosome 11, and then 409 out of 6684 GO terms survived, where 103 and 142 GO terms of molecular function and biological process, respectively, were included. Representatively, the cellular component GO terms of CCDC90B, C11orf52, and the SMAP were predicted and validated using the overexpression system into 293T cells and immunofluorescence staining. We will further study their biological and molecular functions toward the goal of the neXt-CP50 project as a part of C-HPP. We shared all results and programs in Github (https://github.com/heeyounh/I-TASSER-COFACTOR-filtering.git).

Unveiling the transcriptome alteration of POMC neuron in diet-induced obesity

Loss of neuron homeostasis in the arcuate nucleus (ARC) is responsible for diet-induced-obesity (DIO). We previously reported that loss of Rb1 gene compromised the homeostasis of anorexigenic POMC neurons in ARC and induced obesity in mice. To evaluate the development of DIO, we propose to analyze the transcriptomic alteration of POMC neurons in mice following high fat diet (HFD) feeding. We isolated these neurons from established DIO mice and performed transcriptomic profiling using RNA-seq. In total, 1066 genes (628 upregulated and 438 downregulated) were identified as differentially expressed genes (DEGs). Pathway enrichment analysis with these DEGs further revealed that "cell cycle," "apoptosis," "chemokine signaling," and "sphingolipid metabolism" pathways were correlated with DIO development. Moreover, we validated that the pRb protein, a key regulator of "cell cycle pathway," was inactivated by phosphorylation in POMC neurons by HFD feeding. Importantly, the reversal of deregulated cell cycle by stereotaxic delivering of the unphosphorylated pRbΔP in ARC significantly meliorated the DIO. Collectively, our study provides insights into the mechanisms related to the loss of homeostasis of POMC neurons in DIO, and suggests pRb phosphorylation as a potential intervention target to treat DIO.

BRENDA in 2019: a European ELIXIR core data resource

The BRENDA enzyme database (www.brenda-enzymes.org), recently appointed ELIXIR Core Data Resource, is the main enzyme and enzyme-ligand information system. The core database provides a comprehensive overview on enzymes. A collection of 4.3 million data for ∼84 000 enzymes manually evaluated and extracted from ∼140 000 primary literature references is combined with information obtained by text and data mining, data integration and prediction algorithms. Supplements comprise disease-related data, protein sequences, 3D structures, predicted enzyme locations and genome annotations. Major developments are a revised ligand summary page and the structure search now including a similarity and isomer search. BKMS-react, an integrated database containing known enzyme-catalyzed reactions, is supplemented with further reactions and improved access to pathway connections. In addition to existing enzyme word maps with graphical information of enzyme specific terms, plant word maps have been developed. They show a graphical overview of terms, e.g. enzyme or plant pathogen information, connected to specific plants. An organism summary page showing all relevant information, e.g. taxonomy and synonyms linked to enzyme data, was implemented. Based on a decision by the IUBMB enzyme task force the enzyme class EC 7 has been established for 'translocases', enzymes that catalyze a transport of ions or metabolites across cellular membranes.

Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach

Background

Our understanding of the molecular mechanisms underlying Alzheimer’s disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease.

Method

In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm.

Results

We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules—neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module—indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified.

Conclusion

By means of network and pathway-based methodology, we explored the pathogenetic mechanism underlying AD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular mechanism underlying AD. In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13195-017-0252-z) contains supplementary material, which is available to authorized users.

A secretome analysis reveals that PPARα is upregulated by fractionated-dose γ-irradiation in three-dimensional keratinocyte cultures

Studies have shown that γ-irradiation induces various biological responses, including oxidative stress and apoptosis, as well as cellular repair and immune system responses. However, most such studies have been performed using traditional two-dimensional cell culture systems, which are limited in their ability to faithfully represent in vivo conditions. A three-dimensional (3D) environment composed of properly interconnected and differentiated cells that allow communication and cooperation among cells via secreted molecules would be expected to more accurately reflect cellular responses. Here, we investigated γ-irradiation-induced changes in the secretome of 3D-cultured keratinocytes. An analysis of keratinocyte secretome profiles following fractionated-dose γ-irradiation revealed changes in genes involved in cell adhesion, angiogenesis, and the immune system. Notably, peroxisome proliferator-activated receptor-α (PPARα) was upregulated in response to fractionated-dose γ-irradiation. This upregulation was associated with an increase in the transcription of known PPARα target genes in secretome, including angiopoietin-like protein 4, dermokine and kallikrein-related peptide 12, which were differentially regulated by fractionated-dose γ-irradiation. Collectively, our data imply a mechanism linking γ-irradiation and secretome changes, and suggest that these changes could play a significant role in the coordinated cellular responses to harmful ionizing radiation, such as those associated with radiation therapy. This extension of our understanding of γ-irradiation-induced secretome changes has the potential to improve radiation therapy strategies.

BRENDA in 2017: new perspectives and new tools in BRENDA

The BRENDA enzyme database (www.brenda-enzymes.org) has developed into the main enzyme and enzyme-ligand information system in its 30 years of existence. The information is manually extracted from primary literature and extended by text mining procedures, integration of external data and prediction algorithms. Approximately 3 million data from 83 000 enzymes and 137 000 literature references constitute the manually annotated core. Text mining procedures extend these data with information on occurrence, enzyme-disease relationships and kinetic data. Prediction algorithms contribute locations and genome annotations. External data and links complete the data with sequences and 3D structures. A total of 206 000 enzyme ligands provide functional and structural data. BRENDA offers a complex query tool engine allowing the users an efficient access to the data via different search methods and explorers. The new design of the BRENDA entry page and the enzyme summary pages improves the user access and the performance. New interactive and intuitive BRENDA pathway maps give an overview on biochemical processes and facilitate the visualization of enzyme, ligand and organism information in the biochemical context. SCOPe and CATH, databases for protein structure classification, are included. New online and video tutorials provide online training for the users. BRENDA is freely available for academic users.

The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability

BACKGROUND

The Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies.

CONSTRUCTION AND CONTENT

Recent work on the CL has focused on extending the representation of various cell types, and developing new modules in the CL itself, and in related ontologies in coordination with the CL. For example, the Kidney and Urinary Pathway Ontology was used as a template to populate the CL with additional cell types. In addition, subtypes of the class 'cell in vitro' have received improved definitions and labels to provide for modularity with the representation of cells in the Cell Line Ontology and Reagent Ontology. Recent changes in the ontology development methodology for CL include a switch from OBO to OWL for the primary encoding of the ontology, and an increasing reliance on logical definitions for improved reasoning.

UTILITY AND DISCUSSION

The CL is now mandated as a metadata standard for large functional genomics and transcriptomics projects, and is used extensively for annotation, querying, and analyses of cell type specific data in sequencing consortia such as FANTOM5 and ENCODE, as well as for the NIAID ImmPort database and the Cell Image Library. The CL is also a vital component used in the modular construction of other biomedical ontologies-for example, the Gene Ontology and the cross-species anatomy ontology, Uberon, use CL to support the consistent representation of cell types across different levels of anatomical granularity, such as tissues and organs.

CONCLUSIONS

The ongoing improvements to the CL make it a valuable resource to both the OBO Foundry community and the wider scientific community, and we continue to experience increased interest in the CL both among developers and within the user community.

Dynamic software design for clinical exome and genome analyses: insights from bioinformaticians, clinical geneticists, and genetic counselors

BACKGROUND

The transition of whole-exome and whole-genome sequencing (WES/WGS) from the research setting to routine clinical practice remains challenging.

OBJECTIVES

With almost no previous research specifically assessing interface designs and functionalities of WES and WGS software tools, the authors set out to ascertain perspectives from healthcare professionals in distinct domains on optimal clinical genomics user interfaces.

METHODS

A series of semi-scripted focus groups, structured around professional challenges encountered in clinical WES and WGS, were conducted with bioinformaticians (n = 8), clinical geneticists (n = 9), genetic counselors (n = 5), and general physicians (n = 4).

RESULTS

Contrary to popular existing system designs, bioinformaticians preferred command line over graphical user interfaces for better software compatibility and customization flexibility. Clinical geneticists and genetic counselors desired an overarching interactive graphical layout to prioritize candidate variants--a "tiered" system where only functionalities relevant to the user domain are made accessible. They favored a system capable of retrieving consistent representations of external genetic information from third-party sources. To streamline collaboration and patient exchanges, the authors identified user requirements toward an automated reporting system capable of summarizing key evidence-based clinical findings among the vast array of technical details.

CONCLUSIONS

Successful adoption of a clinical WES/WGS system is heavily dependent on its ability to address the diverse necessities and predilections among specialists in distinct healthcare domains. Tailored software interfaces suitable for each group is likely more appropriate than the current popular "one size fits all" generic framework. This study provides interfaces for future intervention studies and software engineering opportunities.

Small RNA deep sequencing reveals the important role of microRNAs in the halophyte Halostachys caspica

MicroRNAs (miRNAs), an extensive class of small regulatory RNAs, play versatile roles in plant growth and development as well as stress responses. However, the regulatory mechanism is unclear on miRNA-mediated response to abiotic stress in plants. Halostachys caspica is a halophytic plant species and a great model for investigating plant response to salinity stress. However, no research has been performed on miRNAs in H. caspica. In this study, we employed deep sequencing to identify both conserved and novel miRNAs from salinity-exposed H. caspica and its untreated control. Among the 13-19 million sequences generated from both treatments, a total of 170 conserved miRNAs, belonging to 151 miRNA families, were identified; among these miRNAs, 31 were significantly up-regulated and 48 were significantly down-regulated by salinity stress. We also identified 102 novel miRNAs from H. caspica; among them, 12 miRNAs were significantly up-regulated and 13 were significantly down-regulated by salinity. qRT-PCR expression analysis validated the deep sequencing results and also demonstrated that miRNAs and their targeted genes were responsive to high salt stress and existed a negative expression correlation between miRNAs and their targets. miRNA-target prediction, GO and KEGG analysis showed that miRNAs were involved in salt stress-related biological pathway, including calcium signalling pathway, MAPK signalling pathway, plant hormone signal transduction and flavonoid biosynthesis, etc. This suggests that miRNAs play an important role in plant salt stress tolerance in H. caspica. This result could be used to improve salt tolerance in crops and woods.

Gene Ontology Consortium: going forward

The Gene Ontology (GO; http://www.geneontology.org) is a community-based bioinformatics resource that supplies information about gene product function using ontologies to represent biological knowledge. Here we describe improvements and expansions to several branches of the ontology, as well as updates that have allowed us to more efficiently disseminate the GO and capture feedback from the research community. The Gene Ontology Consortium (GOC) has expanded areas of the ontology such as cilia-related terms, cell-cycle terms and multicellular organism processes. We have also implemented new tools for generating ontology terms based on a set of logical rules making use of templates, and we have made efforts to increase our use of logical definitions. The GOC has a new and improved web site summarizing new developments and documentation, serving as a portal to GO data. Users can perform GO enrichment analysis, and search the GO for terms, annotations to gene products, and associated metadata across multiple species using the all-new AmiGO 2 browser. We encourage and welcome the input of the research community in all biological areas in our continued effort to improve the Gene Ontology.

BRENDA in 2015: exciting developments in its 25th year of existence

The BRENDA enzyme information system (http://www.brenda-enzymes.org/) has developed into an elaborate system of enzyme and enzyme-ligand information obtained from different sources, combined with flexible query systems and evaluation tools. The information is obtained by manual extraction from primary literature, text and data mining, data integration, and prediction algorithms. Approximately 300 million data include enzyme function and molecular data from more than 30 000 organisms. The manually derived core contains 3 million data from 77 000 enzymes annotated from 135 000 literature references. Each entry is connected to the literature reference and the source organism. They are complemented by information on occurrence, enzyme/disease relationships from text mining, sequences and 3D structures from other databases, and predicted enzyme location and genome annotation. Functional and structural data of more than 190 000 enzyme ligands are stored in BRENDA. New features improving the functionality and analysis tools were implemented. The human anatomy atlas CAVEman is linked to the BRENDA Tissue Ontology terms providing a connection between anatomical and functional enzyme data. Word Maps for enzymes obtained from PubMed abstracts highlight application and scientific relevance of enzymes. The EnzymeDetector genome annotation tool and the reaction database BKM-react including reactions from BRENDA, KEGG and MetaCyc were improved. The website was redesigned providing new query options.

Protein Ontology: a controlled structured network of protein entities

The Protein Ontology (PRO; http://proconsortium.org) formally defines protein entities and explicitly represents their major forms and interrelations. Protein entities represented in PRO corresponding to single amino acid chains are categorized by level of specificity into family, gene, sequence and modification metaclasses, and there is a separate metaclass for protein complexes. All metaclasses also have organism-specific derivatives. PRO complements established sequence databases such as UniProtKB, and interoperates with other biomedical and biological ontologies such as the Gene Ontology (GO). PRO relates to UniProtKB in that PRO’s organism-specific classes of proteins encoded by a specific gene correspond to entities documented in UniProtKB entries. PRO relates to the GO in that PRO’s representations of organism-specific protein complexes are subclasses of the organism-agnostic protein complex terms in the GO Cellular Component Ontology. The past few years have seen growth and changes to the PRO, as well as new points of access to the data and new applications of PRO in immunology and proteomics. Here we describe some of these developments.