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Methods Mol Biol. 2016;1401:175-95. doi: 10.1007/978-1-4939-3375-4_12.

Secondary Metabolic Pathway-Targeted Metabolomics.

Author information

1
Department of Chemistry, Yale University, New Haven, CT, 06510, USA.
2
Chemical Biology Institute, Yale University, West Haven, CT, 06516, USA.
3
Department of Chemistry, Yale University, New Haven, CT, 06510, USA. jason.crawford@yale.edu.
4
Chemical Biology Institute, Yale University, West Haven, CT, 06516, USA. jason.crawford@yale.edu.
5
Department of Microbial Pathogenesis, Yale School of Medicine, New Haven, CT, 06536, USA. jason.crawford@yale.edu.
6
Department of Chemistry, Yale University, 225 Prospect Street, P.O. Box 208107, New Haven, CT, 06520, USA. jason.crawford@yale.edu.

Abstract

This chapter provides step-by-step methods for building secondary metabolic pathway-targeted molecular networks to assess microbial natural product biosynthesis at a systems level and to aid in downstream natural product discovery efforts. Methods described include high-resolution mass spectrometry (HRMS)-based comparative metabolomics, pathway-targeted tandem MS (MS/MS) molecular networking, and isotopic labeling for the elucidation of natural products encoded by orphan biosynthetic pathways. The metabolomics network workflow covers the following six points: (1) method development, (2) bacterial culture growth and organic extraction, (3) HRMS data acquisition and analysis, (4) pathway-targeted MS/MS data acquisition, (5) mass spectral network building, and (6) network enhancement. This chapter opens with a discussion on the practical considerations of natural product extraction, chromatographic processing, and enhanced detection of the analytes of interest within complex organic mixtures using liquid chromatography (LC)-HRMS. Next, we discuss the utilization of a chemometric platform, focusing on Agilent Mass Profiler Professional software, to run MS-based differential analysis between sample groups and controls to acquire a unique set of molecular features that are dependent on the presence of a secondary metabolic pathway. Using this unique list of molecular features, the chapter then details targeted MS/MS acquisition for subsequent pathway-dependent network clustering through the online Global Natural Products Social Molecular Networking (GnPS) platform. Genetic information, ionization intensities, isotopic labeling, and additional experimental data can be mapped onto the pathway-dependent network, facilitating systems biosynthesis analyses. The finished product will provide a working molecular network to assess experimental perturbations and guide novel natural product discoveries.

KEYWORDS:

Chemical signaling; Comparative metabolomics; High-resolution mass spectrometry; Isotopic labeling; Molecular networking; Natural product discovery; Nonribosomal peptide biosynthesis; Secondary metabolism

PMID:
26831709
PMCID:
PMC5049693
DOI:
10.1007/978-1-4939-3375-4_12
[Indexed for MEDLINE]
Free PMC Article

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