Dimitrios J Floros1,2, Paul R Jensen3, Pieter C Dorrestein2, Nobuhiro Koyama2,4. 1. Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA. 2. Skaggs School of Pharmacy and Pharmaceutical Sciences, Collaborative Mass Spectrometry Innovation Center, University of California, San Diego, La Jolla, CA, USA. 3. Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA. 4. Graduate School of Pharmaceutical Sciences, Kitasato University, Tokyo, Japan inventory the chemistries associated with 1000 marine microorganisms.
Abstract
INTRODUCTION: Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections. OBJECTIVE: Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs. METHOD: In this work we utilize untargeted LC-MS/MS based metabolomics together with molecular networking to. RESULT: This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B. CONCLUSION: Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries.
INTRODUCTION: Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections. OBJECTIVE: Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs. METHOD: In this work we utilize untargeted LC-MS/MS based metabolomics together with molecular networking to. RESULT: This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B. CONCLUSION: Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries.
Entities:
Keywords:
Marine natural products; Mass spectrometry; Metabolomics; Molecular networking
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