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High‐Throughput Natural Products Discovery in Fungi Using FAC‐MS Technology
Author(s) -
Clevenger Kenneth D,
Bok Jin Woo,
Ye Rosa,
Miley Galen P,
Verdan Maria H,
Velk Thomas,
Chen Cynthia,
Yang KaHoua,
Gao Peng,
Robey Matthew,
Lamprecht Matthew,
Thomas Paul M,
Islam Md N,
Palmer Jonathan,
Wu Chengcang C,
Keller Nancy P,
Kelleher Neil L
Publication year - 2017
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.31.1_supplement.766.6
Subject(s) - throughput , natural (archaeology) , chemistry , computer science , biology , telecommunications , wireless , paleontology
Ascomycete fungal genomes typically each contain >50 different secondary metabolite biosynthetic gene clusters (BGCs). With an estimated pool of >500,000 ascomycete fungal species on earth, the corresponding chemical potential that could be harnessed for human technological challenges such as disease and agriculture is truly massive. However, the vast majority of fungal‐encoded chemical space is uncharted and difficult to access due to difficulties culturing and genetically manipulating most fungi. We report a high‐throughput heterologous expression and metabolomic profiling technology using untargeted liquid chromatography‐mass spectrometry (LC‐MS) with ultrahigh mass accuracy to systematically identify the secondary metabolite (SM) products of heterologously expressed fungal BGCs. This platform uses fungal artificial chromosomes (FACs) to capture full‐length BGCs derived from unbiased large‐insert libraries of genomic DNA of Aspergillus terreus, A. aculeatus, and A. wenti ( Fig. A) . Host A. nidulans strains transformed with FACs ( Fig. B) are then screened by LC‐MS ( Fig. C), and FAC‐encoded products are identified by a robust scoring system to identify spectral features most likely associated with each FAC ( Fig. D). Deletions of specific backbone and tailoring genes within FACs (achieved through facile E. coli genetics) then empirically validate assignment of metabolites to BGCs and facilitate analyses of biosynthesis ( Fig. E). We use this “FAC‐MS” platform to screen 56 FACs and report detection of 15 completely novel secondary metabolites from 56 FACs, a ~27% “hit rate”, including an A. terreus FAC encoding three distinct metabolites identified as a novel macrolactone, a sesterterpenoid, and the orphan benzodiazepine benzomalvin A, which is 300‐fold overexpressed by the FAC‐strain. Deletants of benzomalvin A backbone and tailoring genes allow us to propose and test the first biosynthetic model for this molecule, as well as demonstrate the readiness with which such studies can be carried out using the FAC‐MS technology. Wide application of the FAC‐MS pipeline should have a major impact on fungal natural products research in the mid‐term future by greatly increasing the scale and rate at which fungal secondary metabolites can be systematically unearthed and introduced into pharmaceutical and agricultural screening campaigns. Support or Funding Information This work was supported in part by an SBIR award from the National Institute of Allergy and Infectious Diseases at the National Institutes of Health under grant R44AI094885 to C.C.W. at Intact Genomics, Inc. and to J.W.B and N.L.K. N.L.K. also acknowledges AT009143 for partial support of this work. FAC‐MS PipelineA) Fungal artificial chromosomes (FACs) capture full‐length biosynthetic gene clusters (BGCs) derived from unbiased large‐insert libraries of genomic DNA of Aspergillus terreus, A. aculeatus, and A. wenti. B and C ) Host A. nidulans strains transformed with FACs are then screened by LC‐MS. D ) FAC‐encoded products are identified by a robust scoring system. E ) Deletions of backbone genes in FACs empirically validate assignment of metabolites to BGCs and dissect biosyntheses.