Deciphering the chemical composition of Ganoderma lucidum from different geographical origins by mass spectrometry molecular networking coupled with multivariate analysis.

Abstract

Ganoderma lucidum is a medicinal fungus that has been widely used in China and many Asian countries for thousands of years. This once rare macrofungus has now been artificially cultivated in a number of regions in China. However, detailed knowledge of its composition across different geographical origins is still lacking, as are analytical methods for comprehensive profiling of the diverse phytochemicals contained in G. lucidum. In this work, an on-demand strategy based on high-resolution MS and molecular networking is applied for natural product characterization, which led to the identification of 84 constituents in G. lucidum. Moreover, multivariate analysis, including hierarchical cluster analysis and orthogonal partial least squares-discriminant analysis, was used to analyze the (dis)similarity of the G. lucidum samples collected from the three main production areas (i.e., Jilin, Henan and Shandong Province). The results revealed a significant variation in the chemical composition of samples from different provinces. Marker constituents corresponding to the differentiation were then screened in terms of the variable importance in projection value, P-value and fold change. A total of 24 constituents were identified as geoherbalism markers, such as ganoderenic acid A for Henan, ganolucidic acid B for Jilin and ganodernoid D for Shandong. This proof-of-concept application demonstrates that combining MS molecular networking with meticulous multivariate analysis can provide a sensitive and comprehensive analytical approach for the quality assessment of traditional Chinese medicine ingredients. This study also suggests that the bioactivity and efficacy from different origins should be further evaluated considering the large difference in chemical compositions.