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: 10494610
• 负责人: Raja Mazumder
• 金额: $ 109.41万
• 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/10494610
• 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 and Outreach; Educational Curriculum; Ensure; Event; Evolution; Feedback; Funding; Future; Gene Expression; Gene Proteins; Generations; Genes; Genetic Transcription; Genomics; Glycobiology; Glycoconjugates; Glycoproteins; Growth; Health; Individual; International; Intuition; Investigation; 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; data communication; data format; data harmonization; data modeling; data portal; data visualization; design; disease phenotype; experience; glycosylation; glycosyltransferase; improved; knowledgebase; lipidomics; machine learning algorithm; meetings; metabolomics; next generation; novel; outreach; 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）的知识基础，可在糖生物学领域积累数据和 将其与其他数据类型联系起来。 Glygen是独一无二的；没有其他目前或事先的信息资源 这样的综合任务。在某种程度上，在糖生物学领域中可获取知识的滞后增长， 与其他 - 组或生物医学研究领域相比，反映了聚糖结构的固有复杂性， 它与基因和蛋白质不同，以分支和异构形式存在，其生物合成不属于 良好的模板驱动过程（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 分泌途径调节机制共同产生动态细胞和组织特异性模式 蛋白质和脂质糖基化。另外，可以定期修改糖蛋白上的每个糖基化位点 通过一个聚糖结构的合奏之一，一种称为微分近期性的糖蛋白特征。重要的是， 微观均质性不是随机的，而是反映了特定细胞和组织的固有生物合成能力以及 可以通过疾病来改变。这些结构和生物合成复杂性是造成 糖基和糖基化的组织和疾病特异性功能，因此需要捕获，并且需要捕获 以一种可以查询并链接到其他类型的数据的方式在知识库中表示。格莱根 旨在扩展其基本数据模型，以适应新的，更复杂的数据类型，增强和 集成新的数据类型，并实施可靠的建模，统一程序和工具以改进 聚糖和糖缀合物数据的发现和探索。增强整体资源功能 将通过前端改进来实现以适应用户偏好并确保出色的数据 沟通和可视化。改善Glygen及其合作伙伴数据库的互连性以及 跨资源增强数据共享将继续是Glygen项目的核心原则。所有结果 协调数据将通过高度允许的许可获得，以便于将其集成到其他资源中， 例如NCBI，EBI，SIB和其他国际努力，以及独立的轻松再利用 研究人员，教育者，生物信息学家和商业实体。在下一个项目期结束时Glygen 期望成为糖科学数据的首选，整合的资源，类似于现有蛋白质和 基因组资源并为相同广泛的生物医学研究人员提供服务。