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Related Experiment Video

Updated: May 31, 2026

Preparation of Food Samples Using Homogenization and Microwave-Assisted Wet Acid Digestion for Multi-Element Determination with ICP-MS

Preparation of Food Samples Using Homogenization and Microwave-Assisted Wet Acid Digestion for Multi-Element Determination with ICP-MS

Published on: December 22, 2023

Elemental composition determination based on MS(n).

Miguel Rojas-Chertó¹, Piotr T Kasper, Egon L Willighagen

¹Netherlands Metabolomics Centre, Leiden/Amsterdam Center for Drug Research, Leiden, The Netherlands. m.rojas@lacdr.leidenuniv.nl

Bioinformatics (Oxford, England)

|July 16, 2011

Summary

This summary is machine-generated.

A new tool, Multistage Elemental Formula (MEF), aids in metabolite identification by correctly assigning elemental composition using multistage mass spectrometry (MS(n)) data, improving biomarker discovery and drug development.

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Area of Science:

Metabolomics
Analytical Chemistry
Biochemistry

Background:

Metabolite identification is crucial for biomarker discovery, systems biology, and drug development.
Determining elemental composition is a key initial step in metabolite structure elucidation.
High-resolution mass spectrometry (HRMS) provides exact mass but may not yield a unique elemental composition.

Purpose of the Study:

To present the Multistage Elemental Formula (MEF) tool for accurate elemental composition assignment in metabolites.
To leverage multistage mass spectrometry (MS(n)) data for improved compound identification.
To reduce ambiguity in elemental composition determination for metabolites and their fragments.

Main Methods:

The MEF tool analyzes elemental compositions of precursor ions and fragment ions in MS(n) data.
It reduces the list of potential elemental compositions by considering parent-descendant relationships.
The efficacy of MEF was validated using MS(n) data from various metabolites.

Main Results:

MEF enables correct assignment of elemental composition to compounds, fragment ions, and neutral losses.
The study investigated the relationship between mass accuracy, MS(n) tree topology, and unique elemental composition assignment.
MEF demonstrated efficacy in assigning elemental compositions for tested metabolites.

Conclusions:

The MEF tool represents a significant advancement toward semi-automatic de novo metabolite identification.
Accurate elemental composition assignment using MS(n) data is facilitated by the MEF approach.
This method enhances the utility of mass spectrometry in metabolomics research.