Structural characterisation and discrimination of the aerial parts of Paris polyphylla var. yunnanensis and Paris polyphylla var. chinensis by UHPLC-QTOF-MS coupled with multivariate data analysis.

Abstract

As sources of Rhizoma Paridis are facing shortages, utilising the aerial parts of Paris polyphylla has emerged as a promising additional source. However, the components in the aerial parts still need to be explored, and it is difficult to distinguish the aerial parts of P. polyphylla Smith var. yunnanensis (PPY) and P. polyphylla var. chinensis (PPC), two varieties of P. polyphylla. This study aimed to establish a comprehensive platform to characterise steroid saponins from the aerial parts of PPY and PPC and to discriminate these two varieties. A dereplication approach and ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) analysis were used for the characterisation of steroidal saponins in the aerial parts of PPY and PPC. Multivariate statistical analysis was performed to differentiate these two varieties and screen discriminant variables. In addition, a genetic algorithm-optimised for support vector machines (GA-SVM) model was developed to predict P. polyphylla samples. The distribution of steroidal saponins in PPY and PPC was visualised by a heatmap. A total of 102 compounds were characterised from the aerial parts of PPY and PPC by dereplication. A clear separation of PPY and PPC was achieved, and 35 saponins were screened as marker compounds. The established GA-SVM model showed excellent prediction performance with a prediction accuracy of 100%. Many steroid saponins that have been reported in Rhizoma Paridis also exist in the aerial parts of P. polyphylla. Samples from the aerial parts of PPY and PPC could be discriminated using our platform.