Integrating LC-MS based molecular networks and comparative metabolomics for variety identification and origin tracing of Zanthoxylum nitidum (Roxb.) DC

Abstract

Both varietal attributes and geographical indications are crucial for the quality and medicinal efficacy of Zanthoxylum nitidum (Roxb.) DC, therefore, its variety identification and origin tracing are of considerable importance. In this study, an integrating strategy, UHPLC-Q/TOF-MS based metabolomics coupled with molecular network strategy, was proposed to firstly differentiate Z. nitidum from two counterfeits, and trace three geographic origins of Z. nitidum. A total of 167 components were annotated in metabolomics of Z. nitidum using the molecular networking method metabolomics. Principal component analysis showed distinct metabolic phenotype variation between Z. nitidum and its adulterants, as well as among three origins produced-Z. nitidum samples. Furthermore, orthogonal partial least squares discriminant analysis (OPLS-DA) revealed 15 biomarkers for variety discrimination, and 12 biomarkers for geographic origin discrimination of Z. nitidum. The OPLS-DA models established by these 15 biomarkers and 12 biomarkers could differentiate Z. nitidum from adulterants samples, and distinguish Z. nitidum samples from three geographical origins, respectively. This study demonstrated that our proposed comparative metabolomics coupled with molecular networks strategy has analyzing potential for identifying and determining the varieties and geographic origins of Z. nitidum, providing a useful reference for its quality control in the marketplace and clinical.