Mass Spectrometry-based Untargeted Metabolomics

National Institute Of Environmental Health Sciences

Investigators

Linked publications, trials & patents

Abstract

The Metabolomics Core Facility (MCF) completed a variety of projects during this year, the year in which it was established, in support of the objectives of the NIEHS and NIH. The MCF analyzed 1500 samples analyzed from 11 different scientists representing 8 principal investigators from 4 branches at NIEHS. The primary effort this year, the year in which the Core was established, was developing and implementing protocols for sample extraction, data acquisition, and data analysis. Further, a new high resolution mass spectrometry system (Bruker timsTOF Pro) and a liquid handling robot (Hamilton Starlet) were installed in the core. An untargeted metabolomics method was developed and implemented using a reverse-phase liquid chromatography - mass spectrometry approach. The data are collected using a data-dependent method (DDA) in which MS1 and MS/MS information (used in identification) are collected concurrently. Over 600 chemical standards were analyzed, interpreted, and compiled into an MS/MS spectral database for annotation. Using the developed untargeted metabolomics method, the Core has analyzed human plasma and urine, murine kidney and liver homogenates, Drosophila extracts, and others. A typical experiment results in the annotation (putative identification) of approximately 300-600 chemicals with the remaining MS features remaining knowns. Such results are on par with established metabolomics cores and academic laboratories performing LC-MS based metabolomics analyses. In addition to the acquisition method, the Core has developed a series of R scripts and Jupyter Notebooks to facilitate data analysis, quality assurance, and quality control procedures including pooled quality control measures, linear response evaluation, dispersion ratio, and others. The result of this year's developments is a robust, high-quality untargeted metabolomics data acquisition method and data processing pipeline to serve NIEHS and NIH investigators. A project to establish a quantitative method for novel bile acids reported by Quinn et al. 2020 (https://doi.org/10.1038/s41586-020-2047-9) was undertaken with a materials transfer agreement with Pieter Dorrestein (University of California San Diego).