【摘要】 采用超高效液相色谱-四极杆飞行时间高分辨质谱(UPLC-QTOFMS)联用技术,对血清前处理进行了考察和优化,并对液-质联用分析条件进行了优化,旨在建立用于血清中广谱小分子代谢物分析的高通量强耐用代谢组学方法,以期满足大批次生物样本数代谢组学研究的要求(样本数≥400个).通过考察不同有机溶剂沉淀蛋白对血清中蛋白的去除程度及38个代表性标准品化合物的提取效果,确定采用甲醇/乙腈(体积比1∶9)沉淀蛋白法.血清和有机溶剂的体积比不小于1∶4时,达到最佳的沉淀蛋白处理效果,符合大批量样本测试的要求;预先冷藏沉淀蛋白的有机溶剂,涡旋2 min,超声1 min,加入有机溶剂后冷冻静置10 min,可以进一步提高前处理沉淀蛋白和化合物提取的效果.通过对不同流动相体系和梯度条件的考察,对液-质联用分析条件进行了优化.方法学考察结果表明,本方法重现性、精密度及稳定性均良好.对重现性和48 h稳定性数据进行变异系数分析和主成分分析法的多维分析,证明本方法在代谢组学研究中的可重复性及所得数据的可靠性.本方法高通量强耐用,每天可测定100多个血清样本(13 min测定1个样本),适用于代谢组学研究,特别是大批次生物样本的代谢组学研究.更多还原

【Abstract】 A robust and high throughput method was developed based on ultra performance liquid chromato-graphy and quadruple/time-of-flight mass spectrometry(UPLC-QTOFMS) for performing global metabolic profiling analysis on a large batch of human serum.Proteins in serum samples were precipitated by organic solvents.Using 38 reference standards,we compared serum preparation methods for protein precipitation by different organic solvents.Different conditions for global metabolic profiling analysis were performed and optimized on UPLC-QTOFMS.We also assayed the reproducibility,precision and stability of the method of profiling.The results indicated that methanol/acetonitrile(volume ratio 1∶ 9) could effectively and reproducibly precipitated human serum proteins,performing the best extracting effect on the assayed reference standards.At least four fold of pre-cold organic solvents coupled with vortex for 2 min,ultrasonic treatment for 1 min and stayed at-20 ℃ for 10 min were the most optimal for the extracting effect and protein precipitation.The results,according to the reproducibility,precision and stability,showed that the method was satisfactory in global metabolic profiling analysis of human serum.Furthermore,reproducibility of the method verified by principal component analysis(PCA) was consistent with the coefficient of variation(CV) analysis in the results.The method was adapted to metabolomics study,especially the large batch metabolomics study,with a high throughput of over 100 samples a day(13 min for each sample run).更多还原