EasyLCMS: an asynchronous web application for the automated quantification of LC-MS data

Area of Science:

• Biochemistry
• Analytical Chemistry
• Bioinformatics

Background:

• Quantitative metabolomics and mathematical modeling require automated, simultaneous metabolite quantification.
• Existing tools often lack automated calibration, μmol concentration calculation, and are not optimized for LC-MS data.
• Current applications are predominantly desktop-based, limiting compatibility and data sharing, and do not support real-time interaction.

Purpose of the Study:

• To develop a web-based application for automated, simultaneous quantification of numerous metabolites.
• To address the non-linear retention time deviations specific to LC-MS data.
• To provide a user-friendly interface for real-time data correction and analysis.

Main Methods:

• Development of EasyLCMS, a web application utilizing asynchronous communication.
• Validation using over 1000 concentration comparisons against manual quantification in real samples.
• Application of clustering analysis to identify and resolve errors in metabolite quantification.

Main Results:

• EasyLCMS demonstrated high accuracy, with only 1% of quantifications showing >15% relative error.
• The application successfully integrated LC distortions and asynchronous web technology.
• Clustering analysis identified and helped resolve recurrent quantification errors.

Conclusions:

• EasyLCMS provides automated, simultaneous metabolite quantification for metabolomics and systems biology.
• The web-based platform offers dynamic interaction for pre-processed LC-MS data correction.
• Quantified data is compatible with downstream applications and mathematical modeling.