College of Chemical Engineering, Nanjing Forestry University, No. 159 Longpan Road, Nanjing 210037, China.
College of Chemical Engineering, Nanjing Forestry University, No. 159 Longpan Road, Nanjing 210037, China.
J Pharm Biomed Anal. 2024 May 15;242:116013. doi: 10.1016/j.jpba.2024.116013. Epub 2024 Feb 6.
Authentication and adulteration detection of closely related herbal medicines is a thorny issue in the quality control and market standardization of traditional Chinese medicine. Taking Fritillariae Bulbus (FB) as a case study, we herein proposed a three-step strategy that integrates mass spectrometry-based metabolomics and multivariate statistical analysis to identify specific markers, thereby accurately identifying FBs and determining the adulteration level. First, an ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based untargeted metabolomics method was employed to profile steroid alkaloids in five sorts of FB and screen potential differential markers. Then, the reliability of the screened markers was further verified by the distribution in different FB groups acquired from ultra-high performance liquid chromatography triple quadrupole mass spectrometry-based pseudotargeted metabolomics analysis. As a result, a total of 16 compounds were screened out to be the specific markers, which were successfully applied to distinguish five FBs by using discriminant analysis model. Besides, partial least squares regression models based on specific markers allowed accurate prediction of three sets of adulterated FBs. All the models afforded good linearity and good predictive ability with regression coefficient of prediction (R) > 0.9 and root mean square error of prediction (RMSEP) < 0.1. The reliable results of discriminant and quantitative analysis revealed that this proposed strategy could be potentially used to identify specific markers, which contributes to rapid chemical discrimination and adulteration detection of herbal medicines with close genetic relationship.
鉴定和检测中药材的掺伪问题是中药质量控制和市场标准化的一个难题。以贝母为例,我们提出了一种三步策略,该策略结合基于质谱的代谢组学和多元统计分析来识别特定的标志物,从而准确鉴定贝母并确定掺假水平。首先,采用超高效液相色谱-四极杆飞行时间质谱的非靶向代谢组学方法对五种贝母中的甾体生物碱进行分析,并筛选潜在的差异标志物。然后,通过超高效液相色谱三重四极杆质谱的伪靶向代谢组学分析,在不同的贝母组中进一步验证筛选出的标志物的分布情况,以验证其可靠性。结果共筛选出 16 种化合物作为特定标志物,成功地利用判别分析模型区分了五种贝母。此外,基于特定标志物的偏最小二乘回归模型能够准确预测三组掺假贝母。所有模型均具有良好的线性和预测能力,预测相关系数(R)>0.9,预测均方根误差(RMSEP)<0.1。判别和定量分析的可靠结果表明,该策略可用于鉴定特定标志物,有助于快速鉴别具有密切遗传关系的中药材的化学差异和掺伪检测。