Integration of molecular networking and fingerprint analysis for studying constituents in Microctis Folium

Abstract

Microctis Folium is the dried leaves of a plant ( Microcos paniculata L.) used to improve the digestive system, alleviate diarrhoea, and relieve fever, but information regarding its chemical composition has rarely been reported. The traditional research approach of determining chemical composition has included isolating, purifying, and identifying compounds with high-cost and time-consuming processes. In this study, molecular networking (MN) and fingerprint analysis were integrated as a comprehensive approach to study the chemical composition of Microctis Folium by an ultra fast liquid chromatography-photo diode array detector-triple-time of flight-tandem mass spectrometry (UFLC-DAD-Triple TOF-MS/MS). Large numbers of mass spectrometric data were processed to identify constituents, and the identified compounds and their unknown analogues were comprehensively depicted as visualized figures comprising distinct families by MN. A validated fingerprint methodology was established to quantitatively determine compounds in Microctis Folium. Ultimately, 165 constituents were identified in Microctis Folium for the first time and the identified compounds and approximately five hundred unknown analogues were applied to create visualized figures by MN, indicating compound groups and their chemical structure analogues in Microctis Folium. The validated fingerprint methodology was indicated to be specific, repeatable, precise, and stable and was used to determine 15 batches of samples during three seasons in three districts. Furthermore, seasonal or geographic environmental influences on the chemical profile were estimated by principal coordinate analysis. The results can be used to control the quality of Microctis Folium, observe seasonal or geographic environmental influences on the chemical profiles, and provide a reference for further exploitation of potential active unknown analogues in the future.

Metabolomics-Guided Elucidation of Plant Abiotic Stress Responses in the 4IR Era: An Overview

“…GNPS, a web-based ecosystem for the sharing, storage and analysis of raw, processed or annotated MS spectral data, enables the generation and analyses of molecular networks ( Figure 4 ) [ 6 , 227 ]. MN through GNPS also enables rapid dereplication, the process of identifying known metabolites, as well as detection of analogs and the discovery of novel metabolites from the acquired MS spectral data [ 224 , 228 ].…”

“…Dereplication is achieved by automatically matching the thousands of MS/MS spectra acquired to public MS/MS spectral libraries within GNPS [ 224 , 229 ]. The large-scale spectral matching of MS spectral data is one approach that GNPS uses to facilitate the analysis of vast number of samples, as exemplified by the analysis of 15 batches of Microctis Folium ( Microcos paniculata L.) leaf extracts that resulted in the identification of 168 metabolites, of which 165 metabolites were identified for the first time in Microctis Folium, and approximately 500 analogues could also be annotated [ 227 ]. In addition to GNPS, MS2LDA is another metabolome mining tool that uses an unsupervised Latent Dirichlet Allocation (LDA) algorithm to group molecules based on shared molecular substructures (i.e., as conserved fragments and neutral loss features), referred to as Mass2Motifs, regardless of their overall spectral similarity ( Figure 4 ) [ 8 , 230 ].…”

Feature-Based Molecular Networks Identification of Bioactive Metabolites from Three Plants of the Polynesian Cosmetopoeia Targeting the Dermal Papilla Cells of the Hair Cycle

“…Furthermore, the formerly restricted number of detectable compounds with traditional methods is lifted by untargeted molecular analyses. Molecular networks applied to natural products research have made it possible to map the true complexity and metabolite richness of plant extracts [ 2 , 3 ].…”