Molecular Networking Discloses the Chemical Diversity of Flavonoids and Selaginellins in Selaginella convoluta

Fast mass spectrometry search and clustering of untargeted metabolomics data

The throughput of mass spectrometers and the amount of publicly available metabolomics data are growing rapidly, but analysis tools such as molecular networking and Mass Spectrometry Search Tool do not scale to searching and clustering billions of mass spectral data in metabolomics repositories. To address this limitation, we designed MASST+ and Networking+, which can process datasets that are up to three orders of magnitude larger than those processed by state-of-the-art tools.

Methyl jasmonate induces selaginellin accumulation in Selaginella convoluta

INTRODUCTION

Selaginellins are specialized metabolites and chemotaxonomic markers for Selaginella species. Despite the growing interest in these compounds as a result of their bioactivities, they are accumulated at low levels in the plant. Hence, their isolation and chemical characterization are often difficult, time consuming, and limiting for biological tests. Elicitation with the phytohormone methyl jasmonate (MeJA) could be a strategy to increase the content of selaginellins addressing their low availability problem, that also impairs pharmacological investigations.

MATHERIALS AND METHODS

In this study, we examined MeJA elicitation in Selaginella convoluta plants, a medicinal plant found in northeastern Brazil, by treating them with two different concentrations (MeJA: 50 and 100 µM), followed by chemical profiling after 12, 24 and 48 h after application. Samples were harvested and analyzed by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS).

RESULTS AND DISCUSSCION

MeJA treatment significantly impacted the chemical phenotype. Regarding shoots differences in the time-dependent increased accumulation of all metabolites when plants were subjected to 100 µM MeJA were observed while in roots, most metabolites had their concentrations decreased in a time-dependent fashion at the same conditions. Results support organ, MeJA concentration and time post-treatment dependence of specialized metabolite accumulation, mainly the flavonoids and selaginellins. The amount of Selaginellin G in shoots of MeJA-treated specimens increased in 5.63-fold relative to control. The molecular networking approach allowed for the putative annotation of 64 metabolites, among them, the MeJA treatment followed by targeted metabolome analysis also allowed to annotate seven unprecedented selaginellins. Additionally, the in silico bioactive potential of the annotated selaginellins highlighted targets related to neurodegenerative disorders, antiproliferative, and antiparasitic issues. Taken together, data point out MeJA exposure as a strategy to induce potentially bioactive selaginellins accumulation in S. convoluta, this approach could enable a deep investigation about the metabolic function of these metabolites in the genus as well as regarding pharmacological exploration of the undervalued potential.

LC-HRMS/MS-Based Metabolomics Approaches Applied to the Detection of Antifungal Compounds and a Metabolic Dynamic Assessment of Orchidaceae

The liquid chromatography-mass spectrometry (LC-MS)-based metabolomics approach is a powerful technology for discovering novel biologically active molecules. In this study, we investigated the metabolic profiling of Orchidaceae species using LC-HRMS/MS data combined with chemometric methods and dereplication tools to discover antifungal compounds. We analyze twenty ethanolic plant extracts from Vanda and Cattleya (Orchidaceae) genera. Molecular networking and chemometric methods were used to discriminate ions that differentiate healthy and fungal-infected plant samples. Fifty-three metabolites were rapidly annotated through spectral library matching and in silico fragmentation tools. The metabolomic profiling showed a large production of polyphenols, including flavonoids, phenolic acids, chromones, stilbenoids, and tannins, which varied in relative abundance across species. Considering the presence and abundance of metabolites in both groups of samples, we can infer that these constituents are associated with biochemical responses to microbial attacks. In addition, we evaluated the metabolic dynamic through the synthesis of stilbenoids in fungal-infected plants. The tricin derivative flavonoid- and the loliolide terpenoidfound only in healthy plant samples, are promising antifungal metabolites. LC-HRMS/MS, combined with state-of-the-art tools, proved to be a rapid and reliable technique for fingerprinting medicinal plants and discovering new hits and leads.