Efficient identification of fungal antimicrobial principles by tandem MS and NMR database

Authors

M.-S. Lee
Y.-L. Yang
C.-Y. Wu
Y.-L. Chen
C.-K. Lee
S.-S. Tzean
T.-H. Lee

Abstract

The continuous re-isolation of the known and non-applicable compounds that is time-consuming and wasting resources is still a critical problem in the discovery of bioactive entities from natural resources. To efficiently address the problem, high performance liquid chromatography-diode array detector-microfractionation (HPLC-DAD-microfractionation) guided by disk agar diffusion assay was developed, and the active compounds were further identified using the tandem mass spectrometry (MS/MS)-based molecular networking. Of 150 fungal strains screened, the methanolic extracts of Phoma herbarum PPM7487, Cryptosporiopsis ericae PPM7405, and Albifimbria verrucaria PPM945 exhibited potent antimicrobial activity against Candida albicans SC5314 and Cryptococcus neoformans H99 in the preliminary agar diffusion assay. The concept of OSMAC (one strain many compounds) was employed in the fungal cultures in order to enrich the diversity of the 2nd metabolites in this study. HPLC coupled with off-line bioactivity-directed profiling of the extracts enabled a precise localization of the compounds responsible for the conspicuous antimicrobial activity. The purified active compounds were identified based mainly on MS/MS database, and further supported by 13C nuclear magnetic resonance (NMR) spectral data compared to the literatures. In addition to nineteen known compounds, a new trichothecene derivative 1, namely trichoverrin D, was isolated and identified through this protocol. The antifungal activities of all the pure isolates were evaluated, and the structure activity relationships were also inferred. This report has demonstrated the combination of HPLC microfractination and MS/MS coupled by NMR spectral dereplication for speeding up the antimicrobial natural products discovery process. © 2019

Abstract Image

ScienceDirect Link

10.1016/j.jfda.2019.06.003

Recommended Citation

Lee, M.-S.; Yang, Y.-L.; Wu, C.-Y.; Chen, Y.-L.; Lee, C.-K.; Tzean, S.-S.; and Lee, T.-H. (2019) "Efficient identification of fungal antimicrobial principles by tandem MS and NMR database," Journal of Food and Drug Analysis: Vol. 27 : Iss. 4 , Article 4.
Available at: https://doi.org/10.1016/j.jfda.2019.06.003

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