Comprehensive prediction of secondary metabolite structure and biological activity from microbial genome sequences

Michael A. Skinnider (), Chad W. Johnston, Mathusan Gunabalasingam, Nishanth J. Merwin, Agata M. Kieliszek, Robyn J. MacLellan, Haoxin Li, Michael R. M. Ranieri, Andrew L. H. Webster, My P. T. Cao, Annabelle Pfeifle, Norman Spencer, Q. Huy To, Dan Peter Wallace, Chris A. Dejong () and Nathan A. Magarvey
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Michael A. Skinnider: McMaster University
Chad W. Johnston: McMaster University
Mathusan Gunabalasingam: McMaster University
Nishanth J. Merwin: McMaster University
Agata M. Kieliszek: Adapsyn Bioscience
Robyn J. MacLellan: Adapsyn Bioscience
Haoxin Li: Adapsyn Bioscience
Michael R. M. Ranieri: McMaster University
Andrew L. H. Webster: McMaster University
My P. T. Cao: McMaster University
Annabelle Pfeifle: Adapsyn Bioscience
Norman Spencer: Adapsyn Bioscience
Q. Huy To: McMaster University
Dan Peter Wallace: Adapsyn Bioscience
Chris A. Dejong: Adapsyn Bioscience
Nathan A. Magarvey: McMaster University

Nature Communications, 2020, vol. 11, issue 1, 1-9

Abstract: Abstract Novel antibiotics are urgently needed to address the looming global crisis of antibiotic resistance. Historically, the primary source of clinically used antibiotics has been microbial secondary metabolism. Microbial genome sequencing has revealed a plethora of uncharacterized natural antibiotics that remain to be discovered. However, the isolation of these molecules is hindered by the challenge of linking sequence information to the chemical structures of the encoded molecules. Here, we present PRISM 4, a comprehensive platform for prediction of the chemical structures of genomically encoded antibiotics, including all classes of bacterial antibiotics currently in clinical use. The accuracy of chemical structure prediction enables the development of machine-learning methods to predict the likely biological activity of encoded molecules. We apply PRISM 4 to chart secondary metabolite biosynthesis in a collection of over 10,000 bacterial genomes from both cultured isolates and metagenomic datasets, revealing thousands of encoded antibiotics. PRISM 4 is freely available as an interactive web application at http://prism.adapsyn.com .

Date: 2020
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DOI: 10.1038/s41467-020-19986-1

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