GlyGen growth and evolution into a central resource for glycans and glycoconjugates

GlyGen 生长并进化为聚糖和复合糖的核心资源

• 批准号: 10710220
• 负责人: Raja Mazumder
• 金额: $ 107.37万
• 依托单位: UNIVERSITY OF GEORGIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-27 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10710220
• 关键词: 5 year old; Anabolism; Binding; Binding Proteins; Biology; Biomedical Research; Cells; Communities; Complex; Computer software; Consumption; Coupled; Data; Data Analyses; Data Set; Databases; Development; Discipline; Disease; Education; Education and Outreach; Educational Curriculum; Educational process of instructing; Ensure; Event; Evolution; Feedback; Funding; Future; Gene Expression; Generations; Genes; Genetic Transcription; Genome; Genomics; Glycobiology; Glycoconjugates; Glycoproteins; Growth; Health; Heterogeneity; Individual; International; Intuition; Investigation; Isomerism; Knowledge; Licensing; Link; Lipids; Malignant Neoplasms; Manuals; Maps; Mediating; Metadata; MicroRNAs; Mission; Modeling; Mutation; Neurosciences; Pathway interactions; Pattern; Persons; Polysaccharides; Procedures; Process; Professional Organizations; Prokaryotic Cells; Proteins; Quality Control; Regulatory Pathway; Research Personnel; Resource Informatics; Resources; Science; Site; Societies; Specificity; Structure; System; Testing; Tissues; Training; Translations; Visualization; base; cell type; complex data; data communication; data format; data harmonization; data integration; data modeling; data portal; data visualization; design; disease phenotype; experience; genome resource; glycosylation; glycosyltransferase; improved; knowledgebase; lipidomics; machine learning algorithm; meetings; metabolomics; next generation; novel; outreach; permissiveness; preference; protein expression; social media; specific biomarkers; text searching; tool; training opportunity; transcription factor; transcriptome sequencing; transcriptomics; undergraduate student; web portal; webinar

ABSTRACT GlyGen is a maturing (five years old) knowledgebase that accumulates data in the glycobiology domain and connects it with other data types. GlyGen is unique; no other present or prior informatic resource has undertaken such an integrative mission. In part, the lagging growth of accessible knowledge in the glycobiology domain, compared to other -omics or biomedical research fields, reflects the inherent complexity of glycan structures, which, unlike genes and proteins, exist in branched and isomeric forms whose biosynthesis is not attributable to well-characterized, template-driven processes such as transcription or translation. Rather, glycan biosynthesis is mediated by the regulated expression of ensembles of glycosyltransferases, substrate transporters, and secretory pathway regulatory mechanisms that together generate dynamic cell- and tissue-specific patterns of protein and lipid glycosylation. In addition, each glycosylation site on a glycoprotein may routinely be modified by one of an ensemble of glycan structures, a glycoprotein feature called microheterogeneity. Importantly, microheterogeneity is not random, but reflects the intrinsic biosynthetic capacity of specific cells and tissues and may be modified by disease. These structural and biosynthetic complexities are essential contributors to the tissue- and disease-specific functions of glycans and glycosylation, and, therefore, need to be captured and represented in knowledgebases in a way that they can be queried and linked to other types of data. GlyGen aims to expand its underlying data model to accommodate new and more complex datatypes, augmenting and integrating new data types, and implementing robust modeling, unified procedures, and tools to improve discovery and exploration of glycan and glycoconjugate data. Enhancement of the overall resource functionality will be achieved through front-end improvements to accommodate user preferences and ensure exceptional data communication and visualization. Improving the interconnectivity of GlyGen and its partner databases as well as enhancing data-sharing across resources will continue to be core principles of the GlyGen project. All resulting harmonized data will be available through highly permissive licenses for easy integration into other resources, such as NCBI, EBI, SIB and other international efforts, as well as for easy repurposing by independent researchers, educators, bioinformaticians, and commercial entities. By the end of the next project period GlyGen expects to become the go-to, well-integrated resource for glycoscience data, similar to existing protein and genomic resources and serving the same broad community of biomedical researchers.

抽象的 GlyGen 是一个成熟的（五年前）知识库，积累了糖生物学领域的数据， 将其与其他数据类型连接起来。 GlyGen 是独一无二的；目前或之前没有其他信息资源进行过 这样一个综合性的使命。在某种程度上，糖生物学领域可获取知识的增长滞后， 与其他组学或生物医学研究领域相比，反映了聚糖结构固有的复杂性， 与基因和蛋白质不同，它们以分支和异构形式存在，其生物合成不能归因于 特征明确的模板驱动过程，例如转录或翻译。相反，聚糖生物合成 由糖基转移酶、底物转运蛋白和糖基转移酶群的调节表达介导 分泌途径调节机制共同产生动态的细胞和组织特异性模式 蛋白质和脂质糖基化。此外，糖蛋白上的每个糖基化位点可以常规地进行修饰 由一组聚糖结构组成，一种称为微观异质性的糖蛋白特征。重要的是， 微观异质性不是随机的，而是反映了特定细胞和组织内在的生物合成能力， 可能会因疾病而改变。这些结构和生物合成的复杂性是 聚糖和糖基化的组织和疾病特异性功能，因此需要捕获和 以可以查询并链接到其他类型数据的方式在知识库中表示。甘氨酸 旨在扩展其底层数据模型以适应新的和更复杂的数据类型，增强和 集成新的数据类型，并实施稳健的建模、统一的程序和工具来改进 聚糖和复合糖数据的发现和探索。整体资源功能增强 将通过前端改进来实现，以适应用户偏好并确保卓越的数据 沟通和可视化。改善 GlyGen 及其合作伙伴数据库的互连性 加强跨资源的数据共享将继续是 GlyGen 项目的核心原则。所有结果 将通过高度宽松的许可证提供统一的数据，以便轻松集成到其他资源中， 例如 NCBI、EBI、SIB 和其他国际努力，以及易于独立的重新利用 研究人员、教育工作者、生物信息学家和商业实体。到下一个项目期结束时 GlyGen 预计将成为糖科学数据的首选、集成良好的资源，类似于现有的蛋白质和 基因组资源并为同样广泛的生物医学研究人员群体提供服务。