Bioactivity-driven fungal metabologenomics identifies antiproliferative stemphone analogs and their biosynthetic gene cluster.
Biochemometrics
Biosynthesis
Fungi
Metabologenomics
Natural products
Secondary metabolism
Journal
Metabolomics : Official journal of the Metabolomic Society
ISSN: 1573-3890
Titre abrégé: Metabolomics
Pays: United States
ID NLM: 101274889
Informations de publication
Date de publication:
02 Aug 2024
02 Aug 2024
Historique:
received:
09
04
2024
accepted:
16
07
2024
medline:
3
8
2024
pubmed:
3
8
2024
entrez:
2
8
2024
Statut:
epublish
Résumé
Fungi biosynthesize chemically diverse secondary metabolites with a wide range of biological activities. Natural product scientists have increasingly turned towards bioinformatics approaches, combining metabolomics and genomics to target secondary metabolites and their biosynthetic machinery. We recently applied an integrated metabologenomics workflow to 110 fungi and identified more than 230 high-confidence linkages between metabolites and their biosynthetic pathways. To prioritize the discovery of bioactive natural products and their biosynthetic pathways from these hundreds of high-confidence linkages, we developed a bioactivity-driven metabologenomics workflow combining quantitative chemical information, antiproliferative bioactivity data, and genome sequences. The 110 fungi from our metabologenomics study were tested against multiple cancer cell lines to identify which strains produced antiproliferative natural products. Three strains were selected for further study, fractionated using flash chromatography, and subjected to an additional round of bioactivity testing and mass spectral analysis. Data were overlaid using biochemometrics analysis to predict active constituents early in the fractionation process following which their biosynthetic pathways were identified using metabologenomics. We isolated three new-to-nature stemphone analogs, 19-acetylstemphones G (1), B (2) and E (3), that demonstrated antiproliferative activity ranging from 3 to 5 µM against human melanoma (MDA-MB-435) and ovarian cancer (OVACR3) cells. We proposed a rational biosynthetic pathway for these compounds, highlighting the potential of using bioactivity as a filter for the analysis of integrated-Omics datasets. This work demonstrates how the incorporation of biochemometrics as a third dimension into the metabologenomics workflow can identify bioactive metabolites and link them to their biosynthetic machinery.
Identifiants
pubmed: 39095664
doi: 10.1007/s11306-024-02153-8
pii: 10.1007/s11306-024-02153-8
doi:
Substances chimiques
Biological Products
0
Antineoplastic Agents
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
90Subventions
Organisme : National Science Foundation
ID : REU CHE-2150091
Organisme : Engineering and Physical Sciences Research Council
ID : EP/W021129/1
Organisme : NIH HHS
ID : R01 GM112739-05A1
Pays : United States
Organisme : NIH HHS
ID : P01 CA125066
Pays : United States
Organisme : NIH HHS
ID : 2R01 AT009143
Pays : United States
Organisme : NIH HHS
ID : F32 GM132679
Pays : United States
Informations de copyright
© 2024. The Author(s).
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