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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.

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Department of Chemistry, Yale University, New Haven, CT, 06510, USA.
Chemical Biology Institute, Yale University, West Haven, CT, 06516, USA.
Department of Chemistry, Yale University, New Haven, CT, 06510, USA.
Chemical Biology Institute, Yale University, West Haven, CT, 06516, USA.
Department of Microbial Pathogenesis, Yale School of Medicine, New Haven, CT, 06536, USA.
Department of Chemistry, Yale University, 225 Prospect Street, P.O. Box 208107, New Haven, CT, 06520, USA.


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.


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

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