Correlative metabologenomics of 110 fungi reveals metabolite–gene cluster pairs

Lindsay K. Caesar, Fatma A. Butun, Matthew T. Robey, Navid J. Ayon, Raveena Gupta, David Dainko, Jin Woo Bok, Grant Nickles, Robert J. Stankey, Don Johnson, David Mead, Kristof B. Cank, Cody E. Earp, Huzefa A. Raja, Nicholas H. Oberlies, Nancy P. Keller, Neil L. Kelleher*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Natural products research increasingly applies -omics technologies to guide molecular discovery. While the combined analysis of genomic and metabolomic datasets has proved valuable for identifying natural products and their biosynthetic gene clusters (BGCs) in bacteria, this integrated approach lacks application to fungi. Because fungi are hyper-diverse and underexplored for new chemistry and bioactivities, we created a linked genomics–metabolomics dataset for 110 Ascomycetes, and optimized both gene cluster family (GCF) networking parameters and correlation-based scoring for pairing fungal natural products with their BGCs. Using a network of 3,007 GCFs (organized from 7,020 BGCs), we examined 25 known natural products originating from 16 known BGCs and observed statistically significant associations between 21 of these compounds and their validated BGCs. Furthermore, the scalable platform identified the BGC for the pestalamides, demystifying its biogenesis, and revealed more than 200 high-scoring natural product–GCF linkages to direct future discovery. [Figure not available: see fulltext.]

Original languageEnglish (US)
Pages (from-to)846-854
Number of pages9
JournalNature Chemical Biology
Issue number7
StatePublished - Jul 2023

ASJC Scopus subject areas

  • Molecular Biology
  • Cell Biology


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