RegenBase: a knowledge base of spinal cord injury biology for translational research.

Spinal cord injury (SCI) research is a data-rich field that aims to identify the biological mechanisms resulting in loss of function and mobility after SCI, as well as develop therapies that promote recovery after injury. SCI experimental methods, data and domain knowledge are locked in the largely unstructured text of scientific publications, making large scale integration with existing bioinformatics resources and subsequent analysis infeasible. The lack of standard reporting for experiment variables and results also makes experiment replicability a significant challenge. To address these challenges, we have developed RegenBase, a knowledge base of SCI biology. RegenBase integrates curated literature-sourced facts and experimental details, raw assay data profiling the effect of compounds on enzyme activity and cell growth, and structured SCI domain knowledge in the form of the first ontology for SCI, using Semantic Web representation languages and frameworks. RegenBase uses consistent identifier schemes and data representations that enable automated linking among RegenBase statements and also to other biological databases and electronic resources. By querying RegenBase, we have identified novel biological hypotheses linking the effects of perturbagens to observed behavioral outcomes after SCI. RegenBase is publicly available for browsing, querying and download.Database URL:http://regenbase.org

Integrated Collection of Stem Cell Bank Data, a Data Portal for Standardized Stem Cell Information

世界中で樹立されたiPS細胞の数や疾患の種類が明らかに. 京都大学プレスリリース. 2021-03-19.The past decade has witnessed an extremely rapid increase in the number of newly established stem cell lines. However, due to the lack of a standardized format, data exchange among stem cell line resources has been challenging, and no system can search all stem cell lines across resources worldwide. To solve this problem, we have developed the Integrated Collection of Stem Cell Bank data (ICSCB) (http://icscb.stemcellinformatics.org/), the largest database search portal for stem cell line information, based on the standardized data items and terms of the MIACARM framework. Currently, ICSCB can retrieve >16, 000 cell lines from four major data resources in Europe, Japan, and the United States. ICSCB is automatically updated to provide the latest cell line information, and its integrative search helps users collect cell line information for over 1, 000 diseases, including many rare diseases worldwide, which has been a formidable task, thereby distinguishing itself from other database search portals

First Proposal of Minimum Information About a Cellular Assay for Regenerative Medicine

国際幹細胞データガイドライン「MIACARM」の開発. 京都大学プレスリリース. 2016-07-14.Advances in stem cell research have triggered scores of studies in regenerative medicine in a large number of institutions and companies around the world. However, reproducibility and data exchange among laboratories or cell banks are constrained by the lack of a standardized format for experiments. To enhance information flow in stem cell and derivative cell research, here we propose a minimum information standard to describe cellular assay data to facilitate practical regenerative medicine. Based on the existing Minimum Information About a Cellular Assay, we developed Minimum Information About a Cellular Assay for Regenerative Medicine (MIACARM), which allows for the description of advanced cellular experiments with defined taxonomy of human cell types. By using controlled terms, such as ontologies, MIACARM will provide a platform for cellular assay data exchange among cell banks or registries that have been established at more than 20 sites in the world

Formalization, annotation and analysis of diverse drug and probe screening assay datasets using the BioAssay Ontology (BAO).

Huge amounts of high-throughput screening (HTS) data for probe and drug development projects are being generated in the pharmaceutical industry and more recently in the public sector. The resulting experimental datasets are increasingly being disseminated via publically accessible repositories. However, existing repositories lack sufficient metadata to describe the experiments and are often difficult to navigate by non-experts. The lack of standardized descriptions and semantics of biological assays and screening results hinder targeted data retrieval, integration, aggregation, and analyses across different HTS datasets, for example to infer mechanisms of action of small molecule perturbagens. To address these limitations, we created the BioAssay Ontology (BAO). BAO has been developed with a focus on data integration and analysis enabling the classification of assays and screening results by concepts that relate to format, assay design, technology, target, and endpoint. Previously, we reported on the higher-level design of BAO and on the semantic querying capabilities offered by the ontology-indexed triple store of HTS data. Here, we report on our detailed design, annotation pipeline, substantially enlarged annotation knowledgebase, and analysis results. We used BAO to annotate assays from the largest public HTS data repository, PubChem, and demonstrate its utility to categorize and analyze diverse HTS results from numerous experiments. BAO is publically available from the NCBO BioPortal at http://bioportal.bioontology.org/ontologies/1533. BAO provides controlled terminology and uniform scope to report probe and drug discovery screening assays and results. BAO leverages description logic to formalize the domain knowledge and facilitate the semantic integration with diverse other resources. As a consequence, BAO offers the potential to infer new knowledge from a corpus of assay results, for example molecular mechanisms of action of perturbagens

Arsinothricin, an arsenic-containing non-proteinogenic amino acid analog of glutamate, is a broad-spectrum antibiotic

Nadar, Chen, Dheeman et al. show that arsinothricin, an arsenic-containing non- proteinogenic amino acid analog of glutamate, is an effective broad-spectrum antibiotic through inhibition of glutamine synthetase. This study suggests a possibility of developing a new class of antimicrobials that thwart microbial resistance to arsinothricin

Long non-coding RNA HOTAIR promotes cell migration by upregulating insulin growth factor–binding protein 2 in renal cell carcinoma

Renal cell carcinoma (RCC) is one of the most lethal urologic cancers. About one-third of RCC patients already have distal metastasis at the time of diagnosis. There is growing evidence that Hox antisense intergenic RNA (HOTAIR) plays essential roles in metastasis in several types of cancers. However, the precise mechanism by which HOTAIR enhances malignancy remains unclear, especially in RCC. Here, we demonstrated that HOTAIR enhances RCC-cell migration by regulating the insulin growth factor-binding protein 2 (IGFBP2) expression. HOTAIR expression in tumors was significantly correlated with nuclear grade, lymph-node metastasis, and lung metastasis. High HOTAIR expression was associated with a poor prognosis in both our dataset and The Cancer Genome Atlas dataset. Migratory capacity was enhanced in RCC cell lines in a HOTAIR-dependent manner. HOTAIR overexpression accelerated tumorigenicity and lung metastasis in immunodeficient mice. Microarray analysis revealed that IGFBP2 expression was upregulated in HOTAIR-overexpressing cells compared with control cells. The enhanced migration activity of HOTAIR-overexpressing cells was attenuated by IGFBP2 knockdown. IGFBP2 and HOTAIR were co-expressed in clinical RCC samples. Our findings suggest that the HOTAIR-IGFBP2 axis plays critical roles in RCC metastasis and may serve as a novel therapeutic target for advanced RCC

Analysis of bio-ontologies to describe chemical biology HTS assays.

<p>Coverage of biomedical concepts/terms to describe HTS assays (shown as rows) by various existing biomedical ontologies (shown as columns) is depicted. The color codes are as follows: green: the concept is well described by the ontology, pink: the concept is partially described, red: no (or little) information is available in the ontology, yellow: the concept is imported from an external reference/ontology, blue: the ontology only includes a placeholder to an external reference of that concept.</p

Generation of a hierarchy-flattened BAO format.

<p>The hierarchy-flattened format of BAO contains only the most specific leaf nodes. Lead node IDs were maintained in this process. The labels/names in the flattened version of BAO reflect the class hierarchy in BAO.</p

Summary of the standardized ‘endpoint’ in PubChem assay annotations.

<p>Summary of the standardized ‘endpoint’ in PubChem assay annotations.</p