Rapid qualitative profiling of metabolites present in Fusarium solani, a rhizospheric fungus derived from Senna spectabilis, using GC/MS and UPLC-QTOF/MS^E techniques assisted by UNIFI information system

Abstract

Fungi are an important source of natural products found in a variety of plant species. A wide range of methods for the detection of metabolites present in fungi have been reported in the literature. The search for methodologies that allow the rapid detection of compounds present in crude extracts is crucial to enable the metabolite annotation doing a qualitative analysis of the complex matrix. Mass spectrometry is an important ally when it comes to in silico detection of previously reported metabolites. In this work, the ethyl acetate extract of Fusarium solani was analyzed by gas chromatography coupled to mass spectrometry (GC/MS) after derivatization process. The ethyl acetate extract was also investigated by liquid chromatography coupled with high-resolution tandem mass spectrometry assisted by the UNIFI software system. A library containing previously reported metabolites from the Fusarium genus was added to the UNIFI platform. Simultaneously, the extract was analyzed through anticholinesterase and antifungal assays. The analysis of the derivatized extract by GC/MS led to the putative identification of five metabolites, and the investigation using Ultra-High Performance Liquid Chromatography - Quadrupole Time-of-Flight Mass Spectrometry (UPLC-QTOF) analysis in data-independent acquisition mode (mass spectrometry) led to the annotation of 15 compounds present in the built-in Fusarium library added to the UNIFI system. The Fusarium solani extract showed potential anticholinesterase and in vitro antifungal activity supported by the detection of bioactive metabolites.

Microorganisms: the secret agents of the biosphere, and their key roles in biotechnology

“…The dereplication of mass spectrometry data has emerged as an important strategy for the structural elucidation of known compounds and allowed the identification of metabolites present in the extracts of some rhizosphere fungi, such as Fusarium solani and F. oxysporum. By comparison with consolidated databases and using molecular networking, a complete view of metabolic production and the discriminant analysis of chemical profiles were achieved, allowing the identification of several metabolites that discriminated both cultures (Vieira et al 2020).…”

Identification of chemical constituents in pomegranate seeds based on ultra‐high‐performance supercritical fluid chromatography coupled with quadrupole time‐of‐flight mass spectrometry

“…32 When analyzing complex mixtures, a large amount of information about the fragment ions can be obtained so that there will be no loss in chemical information and data gathering efficiency. 33 The MS E method has the potential to improve the signal-to-noise ratio of the resulting deconvoluted MS/MS spectra. 31 UHPSFC-ESI-QTOF-MS, combining the advantages of UHPSFC with the exact mass measurement offered by QTOF-MS, is an effective analytical approach to rapidly screen and identify compounds of interest.…”

“…The efficiency and reliability of identifying unknown compounds can be improved using the MS E mode 32 . When analyzing complex mixtures, a large amount of information about the fragment ions can be obtained so that there will be no loss in chemical information and data gathering efficiency 33 . The MS E method has the potential to improve the signal‐to‐noise ratio of the resulting deconvoluted MS/MS spectra 31 …”

Systematic characterization of chemical constituents in Mahuang decoction by UHPLC tandem linear ion trap‐Orbitrap mass spectrometry coupled with feature‐based molecular networking

“…Thus, computer‐aided tools, which fully take advantage of the abundant information and work intelligently, are in great need. Commercial software, such as Waters UNIFI [13, 14] and Thermo Fisher Compound Discoverer [15], were mainly developed for targeted screening against known databases. In a previous study [16], a predicted metabolites screening method was developed to accomplish the screening of the ginsenosides based on the UNIFI platform, which displayed the advantages for mono‐type components.…”