Ye Hui, Zhu Lin, Wang Lin, Liu Huiying, Zhang Jun, Wu Mengqiu, Wang Guangji, Hao Haiping
Key Lab of Drug Metabolism and Pharmacokinetics, State Key Laboratory of Natural Medicines, China Pharmaceutical University, Tongjiaxiang #24, Nanjing 210009, China.
Key Lab of Drug Metabolism and Pharmacokinetics, State Key Laboratory of Natural Medicines, China Pharmaceutical University, Tongjiaxiang #24, Nanjing 210009, China.
Anal Chim Acta. 2016 Feb 11;907:60-8. doi: 10.1016/j.aca.2015.11.045. Epub 2015 Dec 20.
Multiple reaction monitoring (MRM) is a universal approach for quantitative analysis because of its high specificity and sensitivity. Nevertheless, optimization of MRM parameters remains as a time and labor-intensive task particularly in multiplexed quantitative analysis of small molecules in complex mixtures. In this study, we have developed an approach named Stepped MS(All) Relied Transition (SMART) to predict the optimal MRM parameters of small molecules. SMART requires firstly a rapid and high-throughput analysis of samples using a Stepped MS(All) technique (sMS(All)) on a Q-TOF, which consists of serial MS(All) events acquired from low CE to gradually stepped-up CE values in a cycle. The optimal CE values can then be determined by comparing the extracted ion chromatograms for the ion pairs of interest among serial scans. The SMART-predicted parameters were found to agree well with the parameters optimized on a triple quadrupole from the same vendor using a mixture of standards. The parameters optimized on a triple quadrupole from a different vendor was also employed for comparison, and found to be linearly correlated with the SMART-predicted parameters, suggesting the potential applications of the SMART approach among different instrumental platforms. This approach was further validated by applying to simultaneous quantification of 31 herbal components in the plasma of rats treated with a herbal prescription. Because the sMS(All) acquisition can be accomplished in a single run for multiple components independent of standards, the SMART approach are expected to find its wide application in the multiplexed quantitative analysis of complex mixtures.
多反应监测(MRM)因其高特异性和高灵敏度,是一种通用的定量分析方法。然而,MRM参数的优化仍然是一项耗时费力的任务,尤其是在对复杂混合物中的小分子进行多重定量分析时。在本研究中,我们开发了一种名为阶梯式全扫描质谱依赖跃迁(SMART)的方法来预测小分子的最佳MRM参数。SMART首先需要在Q-TOF上使用阶梯式全扫描质谱技术(sMS(All))对样品进行快速高通量分析,该技术由一系列全扫描质谱事件组成,在一个循环中从低碰撞能量(CE)逐步递增到高CE值。然后,通过比较连续扫描中感兴趣的离子对的提取离子色谱图来确定最佳CE值。发现SMART预测的参数与使用标准混合物在同一供应商的三重四极杆上优化的参数非常吻合。还采用了在不同供应商的三重四极杆上优化的参数进行比较,发现其与SMART预测的参数呈线性相关,这表明SMART方法在不同仪器平台上具有潜在的应用价值。通过将该方法应用于同时定量分析用中药方剂治疗的大鼠血浆中的31种草药成分,进一步验证了该方法。由于sMS(All)采集可以在一次运行中独立于标准品完成对多种成分的分析,因此SMART方法有望在复杂混合物的多重定量分析中得到广泛应用。