New analytical methods for studying low abundance metabolome

代谢组学这一新兴领域的主要目标是分析特定生物系统中存在的所有小分子代谢物，以便更好地理解生命系统中发生的动态过程。然而，在单一分析中对数百或数千种代谢物进行综合研究的分析方法目前尚不发达，更适合中高丰度稳定代谢物，并且缺乏足够的验证程序。本研究计划旨在通过液相色谱-质谱（LC-MS）技术改进全球代谢组学的样品制备方法，在不牺牲高样品通量和分析速度的前提下，改进低丰度代谢物的检测和鉴定。特别是，我们计划研究新的提取材料、纳米颗粒和离子液体的使用，以确定最有用的新材料，用于设计基于磁分离平台的顺序提取/分馏方案。我们还将设计新的系统方案来评估给定样品中代谢物的生物利用度，以确定游离代谢物和总代谢物浓度，并评估这种新方法是否可以改善对生物标志物的搜索。该研究计划将回答当前代谢组学文献中未解决的重要问题，包括(i)如何在保持分析的全球性质的同时提高数据质量（ii）新兴材料如可定制纳米颗粒和离子液体是否可以改善代谢物覆盖范围优于经典方法（iii）如何确定最互补的正交方法用于样品制备并开发适合深度的标准化顺序提取方案即使在样本有限的情况下，对代谢组的挖掘以及（iv）代谢物的生物可利用性是否可以改善生物标志物发现和数据解释的过程。本项目开发的新分析方法将对改善靶向和非靶向代谢组学研究发挥关键作用，并促进这一新领域提取方法的更快进展和合理设计。

The main objective of the emerging field of metabolomics is the analysis of all small molecule metabolites present in a particular biological system in order to provide better understanding of dynamic processes occurring in living systems. However, the analytical approaches for the comprehensive study of hundreds or thousands of metabolites in a single analysis are currently underdeveloped, better-suited for medium to high-abundance stable metabolites and lack adequate validation procedures. The objective of the proposed research program is to improve sample preparation methods in global metabolomics by liquid chromatography - mass spectrometry (LC-MS) with the primary focus of improving the detection and identification of low abundance metabolites without sacrificing high sample throughput and speed of analysis. In particular, we plan to examine the use of new extraction materials, nanoparticles and ionic liquids to identify the most useful new materials for the design of a sequential extraction/fractionation protocol based on magnetic separation platform. We will also devise new systematic protocol to evaluate the biological availability of metabolites in a given sample to determine both free and total metabolite concentrations, and evaluate whether this novel approach can improve the search for biomarkers. The research program will answer important questions not addressed in current metabolomics literature including (i) how to improve data quality while maintaining the global nature of analysis (ii) whether emerging materials such as customizable nanoparticles and ionic liquids can improve metabolite coverage over classical approaches (iii) how to identify the most complementary orthogonal methods for sample preparation and develop standardized sequential extraction protocols suitable for deep mining of the metabolome even in sample-limited situations and (iv) whether biological availability of metabolite can improve the processes of biomarker discovery and data interpretation. The new analytical methods developed in this program will play a critical role to improve both targeted and untargeted metabolomics studies, and facilitate faster progress and rational design of extraction methods in this new field.