A systems approach using OSMAC, Log P and NMR fingerprinting: An approach to novelty

Miaomiao Liu; Tanja Grkovic; Xueting Liu; Jianying Han; Lixin Zhang; Ronald J. Quinn

doi:10.1016/j.synbio.2017.10.001

Synthetic and Systems Biotechnology (Dec 2017)

A systems approach using OSMAC, Log P and NMR fingerprinting: An approach to novelty

Miaomiao Liu,
Tanja Grkovic,
Xueting Liu,
Jianying Han,
Lixin Zhang,
Ronald J. Quinn

Affiliations

Miaomiao Liu: Griffith Institute for Drug Discovery, Griffith University, Brisbane, QLD, 4111, Australia
Tanja Grkovic: Griffith Institute for Drug Discovery, Griffith University, Brisbane, QLD, 4111, Australia
Xueting Liu: Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
Jianying Han: Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
Lixin Zhang: Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
Ronald J. Quinn: Griffith Institute for Drug Discovery, Griffith University, Brisbane, QLD, 4111, Australia

DOI: https://doi.org/10.1016/j.synbio.2017.10.001
Journal volume & issue: Vol. 2, no. 4
pp. 276 – 286

Abstract

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The growing number of sequenced microbial genomes has revealed a remarkably large number of secondary metabolite biosynthetic clusters for which the compounds are still unknown. The aim of the present work was to apply a strategy to detect newly induced natural products by cultivating microorganisms in different fermentation conditions. The metabolomic analysis of 4160 fractions generated from 13 actinomycetes under 32 different culture conditions was carried out by 1H NMR spectroscopy and multivariate analysis. The principal component analysis (PCA) of the 1H NMR spectra showed a clear discrimination between those samples within PC1 and PC2. The fractions with induced metabolites that are only produced under specific growth conditions was identified by PCA analysis. This method allows an efficient differentiation within a large dataset with only one fractionation step. This work demonstrates the potential of NMR spectroscopy in combination with metabolomic data analysis for the screening of large sets of fractions.

Published in Synthetic and Systems Biotechnology

ISSN: 2405-805X (Online)
Publisher: KeAi Communications Co., Ltd.
Country of publisher: China
LCC subjects: Technology: Chemical technology: Biotechnology; Science: Biology (General)
Website: https://www.keaipublishing.com/en/journals/synthetic-and-systems-biotechnology/

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