本项目聚焦于代谢组学“数据采集”关键步骤，针对目前基于LC/MS的代谢组学分析方法存在的覆盖窄、选择性差、灵敏度低、响应歧视等瓶颈问题，从“多维”和“同步”两个角度出发，探索发展基于“多维组合衍生化”和“同步选择性提取”的宽覆盖、高灵敏的靶向代谢组学LC/MS新方法和技术体系：包括配对衍生化试剂结构优化、磁性介孔硅胶纳米探针制备、串联衍生化策略、并联衍生化策略、基于同源离子识别和质谱诊断离子的类成分鉴定等。建立整合“已知物质绝对定量”与“未知物质半定量”组合检测的、能覆盖3-5类代谢物、6-8个代谢途径、近500种非脂类代谢物的高灵敏宽覆盖LC/MS定量分析新方法，并实际应用于儿童毛细支气管炎分子分型研究，从代谢调控角度比较不同亚型患儿雾化吸入药物治疗的反应差异性。本课题的开展将推动代谢组分析向“高精准、宽覆盖”方向发展，所建立的技术体系和分析方法将为药物体内效应分子研究提供有力支撑。

A key step in metabolomics is to perform accurate quantification of the metabolomes in comparative samples with high coverage. In order to break through the common technical barriers such as narrow coverage, poor selectivity, low sensitivity and response discrimination etc in mass spectrometry based non-targeted metabolomics，in this project, multi-dimensional derivatization and synchronous selective-extraction were used in combination with LC-MS to develop high coverage targeted metabolomics approach. It involves the optimization of derivatization reagents, preparation of magnetic mesoporous silica gel nanoparticles, tandem derivatization, parallel derivatization and screening of diagnostic ion for endogenous metabolites identification. Consequently, a high coverage and highly sensitive LC/MS method covering 3-5 classes of metabolites, 6-8 metabolic pathways, nearly 500 kinds of non-lipid metabolites would be established and validated integrating absolute and relative quantification. The developed noval LC/MS method would be applied to screen out biomarker for the molecular classification of children bronchiolitis. The predictable success of this research project will rich and perfect the theory and method of metabolomics.