Discovery of novel metabolites using click-chemistry tools

以质谱（MS）为基础的代谢组学是一个新兴领域，专注于分析天然存在的小分子，统称为“代谢组”。代谢组学为理解和研究分子水平上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，相对新颖的非靶向代谢组学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困难，样品中化合物丰度有限的问题以及生物意义方面的低可解释性的阻碍。在未知代谢物（“暗代谢组”）的情况下，这些限制变得更具挑战性，这些代谢物占检测到的化合物的约90%，留下数千种化合物仍有待分类，并可能与生物学上显着的表型相关。我的研究项目旨在发现和绘制生物体内未知的内源性代谢物，并确定它们的生物合成和功能。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的代谢物富集的新颖系统方法来扩大代谢组学的覆盖范围和非靶向代谢组学的发现。这将允许系统地绘制目标通路，识别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：开发一种优化的点击化学工具和资源来标记、丰富和随后识别新的代谢物种。目的2：绘制鞘脂组在真核生物代谢中的图谱，并注释新的代谢物种。目的3：确定孤儿酶和低注释酶的底物和产物。这项研究的潜在影响是代谢组覆盖范围的关键改善。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。本研究的预期结果在于改进的方法来特异性地富集目标途径中的代谢物并去除干扰分子。其影响将从基础研究和对新陈代谢的理解到确定治疗目标。

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.