大规模临床样本高通量代谢组学分析新方法研究

The biological samples are highly complex because of large number of metabolites, huge concentration range, chemical diversity and the structural identity of each species. It requires extensive sample cleanup and chromatographic separation procedures, which hampers high-throughput analysis of large clinical cohorts. In order to improve the throughput and robustness of large-scale metabolomics analysis, a metabolic profiling method based on micro high performance liquid chromatography (or direct infusion)-nano electrospray ionization-Fourier transform ion cyclotron resonance mass spectrometry (MicroLC or DI-nanoESI-FTICR-MS) has been proposed. It is important to remove protein and phospholipids and other interferences from clinical serum/plasma sample before MS analyses. A SPE system will be designed for high-throughput sample pretreatment by using 96-mricroplate. The system could remove protein and phospholipids from sample, which can reduce ion suppression and increase sensitivity. An ultrahigh-field 15-Tesla (15T) FTICR-MS coupled with micro LC (or DI) will be employed for the untargeted metabolic profiling of clinical plasma/serum. The significant benefits of the microLC method are a high sensitivity, short analysis time and a notable reduction in matrix effects. Ultra-high resolution 15-Tesla (15T) FTICR-MS enables the analysis of complex biological sample, which offers superior ultra-high resolving power with accurate and precise mass-to-charge ratio (m/z) measurement of metabolites at isotopic resolution. The proposed MicroLC or DI-nanoESI-FTICR-MS method will integrate the advantages of both micro-LC/DI and ultra-high resolution MS, which will result in high throughput and robust for large scale clinical samples analysis. Data-pretreatment method will be investigated for decreasing the complexity of data and increasing the repeatability of long-term analysis. Methods for internal standard and quality control–based data correction will be developed to provide signal correction and integration of data from multiple analytical batches. Furthermore, this strategy can provide a powerful tool for high-throughput metabolomics investigation for large-scale clinical sample.

大规模临床样本高通量非靶向代谢组学分析是当前亟待解决的关键难题之一。本课题针对现有方法分析通量不足和重复性差等问题，以临床样本为研究对象，从样本预处理、数据采集和代谢组学数据预处理入手，开展新方法研究。首先为提高方法的通量和可靠性，研发高通量代谢组提取的多孔微板SPE系统，实现样本中蛋白和磷脂的快速高效去除，降低质谱离子抑制和离子源污染；其次建立微柱液相色谱（或直接进样）-纳升电喷雾-傅立叶变换离子回旋共振质谱（MicroLC or DI-nanoESI-FTICR-MS）的数据采集方法，通过直接进样或微柱高效液相色谱高灵敏度、快速分离，结合15特斯拉超高场FTICR-MS超高质谱分辨率、质量精度来实现高通量、高灵敏度分析；最后发展相应的代谢组学数据预处理方法，降低组学数据的复杂性和提高大规模组学分析数据的重复性和可靠性。该课题的实施将为大规模临床样本高通量代谢组学研究提供有效的技术手段。

大规模非靶向疾病代谢组学研究针对的是复杂临床生物样本中数以千百计的代谢物，涉及的样本数量多、分析周期长，对现有代谢组学分析方法是极大的挑战。大规模临床样本高通量非靶向代谢组学分析是当前亟待解决的关键难题之一。通常基于色谱-质谱联用技术的代谢组学方法通量较低。直接进样FTICR-MS尽管分析时间短，但复杂生物基质效应影响检测灵敏度，同时很难兼顾方法的通量、覆盖度与可靠性，且尚需发展相应的样本预处理技术和数据处理方法。本课题针对现有方法分析通量不足和重复性差等问题，以生物样本为研究对象，从样本预处理、数据采集和代谢组数据处理与定性等方面开展新方法研究。通过4年的项目实施，已完成项目预期目标。构建了一整套高通量代谢组学分析方法，包括构建了基于DI-15T FTICR MS的代谢物高通量分析新方法，该方法采用两步采集策略，第一步建立高可靠&高覆盖数据采集方法，最大限度获取生物样本中代谢物分子，构建分子库；第2步建立基于分子库导向的高通量数据采集方法，该方法通过获取高可靠&高覆盖分子库为桥梁，解决了目前超高分辨质谱方法无法兼顾通量、覆盖度&可靠性的瓶颈问题，方法的可靠性更高、代谢组覆盖范围更广，适合大规模代谢组数据分析。发展了DI-nano ESI-FTMS高通量代谢组学定性、定量方法和DI-nano-ESI-FTMS的稳定同位素标记代谢流分析新方法，方法具有代谢物一级、二级质谱信息覆盖广，实验过程简单，数据处理方便等优势，为大规模生物样本的代谢组学高通量分析提供解决方案。在本项目实施过程中已在国际期刊发表论文8篇，获得中国发明专利授权4项，申请中国发明专利4项。培养毕业博士研究生2人，在读博士4名。