Biodiscovery of potential antibacterial diagnostic metabolites from the endolichenic fungus Xylaria venustula using LC–MS-based metabolomics

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Santiago, Krystle Angelique A. and Edrada-Ebel, RuAngelie and dela Cruz, Thomas Edison E. and Cheow, Yuen Lin and Ting, Adeline Su Yien (2021) Biodiscovery of potential antibacterial diagnostic metabolites from the endolichenic fungus Xylaria venustula using LC–MS-based metabolomics. Biology, 10 (3). 191. ISSN 2079-7737 (https://doi.org/10.3390/biology10030191)

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Abstract

Three species of the lichen Usnea (U. baileyi (Stirt.) Zahlbr., U. bismolliuscula Zahlbr. and U. pectinata Stirt.) and nine associated endolichenic fungi (ELF) were evaluated using a metabolomics approach. All investigated lichen crude extracts afforded antibacterial activity against Staphylococcus aureus (minimum inhibitory concentration (MIC): 0.0625 mg/mL), but none was observed against Escherichia coli, while the ELF extract Xylaria venustula was found to be the most active against S. aureus (MIC: 2.5 mg/mL) and E. coli (MIC: 5 mg/mL). X. venustula was fractionated and tested for to determine its antibacterial activity. Fractions XvFr1 to 5 displayed bioactivities against both test bacteria. Selected crude extracts and fractions were subjected to metabolomics analyses using high-resolution LC–MS. Multivariate analyses showed the presence of five secondary metabolites unique to bioactive fractions XvFr1 to 3, which were identified as responsible for the antibacterial activity of X. venustula. The p-values of these metabolites were at the margin of significance level, with methyl xylariate C (P_60) being the most significant. However, their high variable importance of projection (VIP) scores (>5) suggest these metabolites are potential diagnostic metabolites for X. venustula for “dual” bioactivity against S. aureus and E. coli. The statistical models also showed the distinctiveness of metabolites produced by lichens and ELF, thus supporting our hypotheses of ELF functionality similar to plant endophytes.

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