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

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

Synth Syst Biotechnol. 2017 Oct 21;2(4):276-286. doi: 10.1016/j.synbio.2017.10.001. eCollection 2017 Dec.

Authors

Miaomiao Liu¹, Tanja Grkovic¹, Xueting Liu², Jianying Han^{2

3}, Lixin Zhang², Ronald J Quinn¹

Affiliations

¹ Griffith Institute for Drug Discovery, Griffith University, Brisbane, QLD, 4111, Australia.
² Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.
³ Graduate University of Chinese Academy of Sciences, Beijing, 100049, China.

Abstract

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.

Keywords: Metabolites; NMR fingerprints; OSMAC.