Discovery of novel metabolites using click-chemistry tools

使用点击化学工具发现新型代谢物

• 批准号: RGPIN-2021-03993
• 负责人: MontenegroBurke, JRafael
• 金额: $ 2.99万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=742806
• 关键词: Discovery; novel; metabolites; using; click

Mass spectrometry (MS)-based metabolomics is an emerging field focused on the profiling of small, naturally occurring molecules collectively known as the "metabolome". Metabolomics provides a powerful strategy to understand and investigate quantitative changes associated with a unique phenotype at the molecular level. Specifically, the relatively novel approach of untargeted metabolomics provides a comprehensive systems-wide view of metabolites or pathways with direct functional consequences. However, compared to hypothesis-driven targeted approaches, untargeted approaches are hampered by difficulties in exact compound identification, issues with limited compound abundance in samples, and low interpretability with respect to biological significance. These limitations become more challenging in the case of unknown metabolites (the "dark metabolome"), which account for ~90% of detected compounds, leaving thousands of compounds that remain to be catalogued and potentially linked to biologically significant phenotypes. My research program is aimed at discovering and mapping unknown endogenous metabolites in living organisms and determining their biosynthesis and function. Here we propose to expand the metabolome coverage and discovery in untargeted metabolomics by developing a novel systematic approach based on innovative click-chemistry metabolic labeling for metabolite enrichment. This will allow systematic mapping of target pathways, identify new and low abundance metabolites and elucidate the biosynthesis of interesting metabolites. Aim 1: Develop an optimize click-chemistry tools and resources to tag, enrich and subsequently identify novel metabolic species. Aim 2: Map the sphingolipidome in eukaryotic metabolism and annotate new metabolic species. Aim 3: Determine the substrate and products of orphan and poorly annotated enzymes. The potential impact of this research is a crucial improvement in the metabolome coverage. It will enhance our ability to explore and map metabolic pathways and discover novel metabolic species and networks. The anticipated result of this research lies in an improved methodology to specifically enrich metabolites in targeted pathways and remove interfering molecules. The impact will range from basic research and understanding of metabolism to identifying targets for therapeutical treatments.

基于质谱（MS）的代谢组学是一个新兴的领域，专注于分析统称为“代谢组”的天然存在的小分子。代谢组学为在分子水平上理解和研究与独特表型相关的定量变化提供了强有力的策略。具体而言，非靶向代谢组学的相对新颖的方法提供了具有直接功能后果的代谢物或途径的全面系统范围的视图。然而，与假设驱动的靶向方法相比，非靶向方法受到精确化合物鉴定的困难、样品中化合物丰度有限的问题以及生物学意义的低可解释性的阻碍。这些限制在未知代谢物（“暗代谢物组”）的情况下变得更具挑战性，其占检测到的化合物的约90%，留下数千种化合物仍待编目并可能与生物学显著表型相关。我的研究项目旨在发现和绘制生物体中未知的内源性代谢物，并确定其生物合成和功能。 在这里，我们建议通过开发一种基于创新的点击化学代谢标记用于代谢物富集的新的系统方法来扩大非靶向代谢组学的代谢组覆盖范围和发现。这将允许靶途径的系统映射，鉴定新的和低丰度的代谢物，并阐明感兴趣的代谢物的生物合成。目标1：开发一个优化的点击化学工具和资源，以标记，富集和随后识别新的代谢物种。 目的2：构建真核生物鞘脂类代谢图谱，并注释新的代谢种类。 目的3：确定孤儿酶和注释不好的酶的底物和产物。 这项研究的潜在影响是代谢组覆盖率的关键改进。它将增强我们探索和绘制代谢途径的能力，并发现新的代谢物种和网络。这项研究的预期结果在于改进的方法，以特异性地富集靶向途径中的代谢物并去除干扰分子。其影响范围将从基础研究和对代谢的理解到确定治疗目标。