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Related Experiment Video

Updated: Feb 10, 2026

Method for Recording Broadband High Resolution Emission Spectra of Laboratory Lightning Arcs

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Published on: August 27, 2019

A Complete Pipeline for Generating a High-Resolution LC-MS-Based Reference Mass Spectra Library.

Nir Shahaf¹, Asaph Aharoni¹, Ilana Rogachev²

¹Department of Plant and Environmental Sciences, Faculty of Biochemistry, Weizmann Institute of Science, Rehovot, Israel.

Methods in Molecular Biology (Clifton, N.J.)

|May 16, 2018

Summary

Creating mass spectrometry (MS) reference libraries for liquid chromatography (LC)-MS data is crucial for metabolomics. This study details a high-throughput method for automated library generation using plant metabolite standards.

Keywords:

Chemoinformatics LC-MS Mass spectrometry Metabolites Metabolomics Plant metabolism Reference libraries

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Last Updated: Feb 10, 2026

Method for Recording Broadband High Resolution Emission Spectra of Laboratory Lightning Arcs

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Published on: August 27, 2019

Generation of Native Chromatin Immunoprecipitation Sequencing Libraries for Nucleosome Density Analysis

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Published on: December 12, 2017

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS

Published on: May 20, 2013

Area of Science:

Analytical Chemistry
Metabolomics
Biochemistry

Background:

Mass spectrometry (MS) reference libraries are essential for identifying unknown compounds in metabolomics.
Established protocols exist for gas chromatography-MS (GC-MS), but not for liquid chromatography-MS (LC-MS).
This gap hinders high-throughput LC-MS data analysis and annotation.

Purpose of the Study:

To develop and present a high-throughput method for automated MS reference library generation for LC-MS data.
To detail the experimental and computational methodologies for creating such a library.
To showcase the application of this method in generating the WEIZMASS plant metabolite library.

Main Methods:

High-throughput experimental generation of chemical standard pools.
Computational conversion of experimental data into a unique MS reference library format.
Application of the methodology to plant metabolite samples.

Main Results:

Successful implementation of a high-throughput workflow for LC-MS data collection.
Automated generation of a comprehensive MS reference library (WEIZMASS) for plant metabolites.
Detailed documentation of the experimental and computational procedures.

Conclusions:

The presented approach enables efficient and automated MS reference library creation for LC-MS.
This facilitates reliable annotation of unknown metabolites in LC-MS-based metabolomics studies.
The WEIZMASS library serves as a valuable resource for plant metabolomics research.