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Related Experiment Video

Updated: May 31, 2026

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Published on: March 14, 2013

AMDORAP: non-targeted metabolic profiling based on high-resolution LC-MS.

Hiroki Takahashi¹, Takuya Morimoto, Naotake Ogasawara

¹Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara 630-0192, Japan.

BMC Bioinformatics

|June 28, 2011

Summary

A new method, AMDORAP, enhances mass-to-charge ratio (m/z) detection accuracy in liquid chromatography-high-resolution orbitrap mass spectrometry (LC-MS) for metabolomics and proteomics. This tool provides reliable m/z values for biological sample analysis.

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Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

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Published on: March 14, 2013

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

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$Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems$

Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems

Published on: September 23, 2021

Area of Science:

Analytical Chemistry
Biochemistry
Molecular Biology

Background:

Liquid chromatography-mass spectrometry (LC-MS) with orbitrap analyzers is crucial for metabolomics and proteomics.
High mass accuracy is a key feature of orbitrap technology.
Accurate m/z values are essential for reliable metabolic fingerprinting using high-resolution LC-MS.

Purpose of the Study:

To develop a novel, user-friendly method for precise m/z detection in LC-MS data.
To improve the accuracy of m/z value determination for biological samples.

Main Methods:

Development of a new m/z detection algorithm named AMDORAP.
Application of AMDORAP to analyze real biological samples (Bacillus subtilis strains).
Comparison of AMDORAP's performance against other LC-MS processing tools using authentic compounds.

Main Results:

AMDORAP demonstrated superior performance in m/z value accuracy.
Error rates for m/z values obtained by AMDORAP were within ±3 ppm.
The method was validated using LC-orbitrap analysis of Bacillus subtilis.

Conclusions:

AMDORAP significantly improves m/z value detection accuracy compared to existing LC-MS tools.
Accurate m/z values are critical for understanding the links between biological effects and cellular metabolites.
AMDORAP is freely available as an open-source tool for comparative LC-orbitrap analysis.