Dataset Information

MRMQuant: Automated MRM Data Quantitation for Large-Scale Targeted Metabolomics Analysis.

ABSTRACT: Multiple reaction monitoring (MRM) is a powerful and popular technique used for metabolite quantification in targeted metabolomics. Accurate and consistent quantitation of metabolites from the MRM data is essential for subsequent analyses. Here, we developed an automated tool, MRMQuant, for targeted metabolomic quantitation using high-throughput liquid chromatography-tandem mass spectrometry MRM data to provide users with an easy-to-use tool for accurate MRM data quantitation with minimal human intervention. This tool has many user-friendly functions and features to inspect and correct the quantitation results as required. MRMQuant possesses the following features to ensure accurate quantitation: (1) dynamic signal smoothing, (2) automatic deconvolution of coeluted peaks, (3) absolute quantitation via standard curves and/or internal standards, (4) visualized inspection and correction, (5) corrections applicable to multiple samples, and (6) batch-effect correction.

SUBMITTER: Lynn KS

PROVIDER: S-EPMC11339730 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

MRMQuant: Automated MRM Data Quantitation for Large-Scale Targeted Metabolomics Analysis.

Lynn Ke-Shiuan KS Tang Hsiang-Yu HY Lo Chi-Jen CJ Yang Cheng-Hung CH Tseng Yi-Ting YT Cheng Mei-Ling ML

Analytical chemistry 20240811 33

Multiple reaction monitoring (MRM) is a powerful and popular technique used for metabolite quantification in targeted metabolomics. Accurate and consistent quantitation of metabolites from the MRM data is essential for subsequent analyses. Here, we developed an automated tool, MRMQuant, for targeted metabolomic quantitation using high-throughput liquid chromatography-tandem mass spectrometry MRM data to provide users with an easy-to-use tool for accurate MRM data quantitation with minimal human ...[more]

PMID: 39127919

Similar Datasets

Project description:IntroductionWe previously developed a tandem mass spectrometry-based label-free targeted metabolomics analysis framework coupled to two distinct chromatographic methods, reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC), with dynamic multiple reaction monitoring (dMRM) for simultaneous detection of over 200 metabolites to study core metabolic pathways.ObjectivesWe aim to analyze a large-scale heterogeneous data compendium generated from our LC-MS/MS platform with both RPLC and HILIC methods to systematically assess measurement quality in biological replicate groups and to investigate metabolite abundance changes and patterns across different biological conditions.MethodsOur metabolomics framework was applied in a wide range of experimental systems including cancer cell lines, tumors, extracellular media, primary cells, immune cells, organoids, organs (e.g. pancreata), tissues, and sera from human and mice. We also developed computational and statistical analysis pipelines, which include hierarchical clustering, replicate-group CV analysis, correlation analysis, and case-control paired analysis.ResultsWe generated a compendium of 42 heterogeneous deidentified datasets with 635 samples using both RPLC and HILIC methods. There exist metabolite signatures that correspond to various phenotypes of the heterogeneous datasets, involved in several metabolic pathways. The RPLC method shows overall better reproducibility than the HILIC method for most metabolites including polar amino acids. Correlation analysis reveals high confidence metabolites irrespective of experimental systems such as methionine, phenylalanine, and taurine. We also identify homocystine, reduced glutathione, and phosphoenolpyruvic acid as highly dynamic metabolites across all case-control paired samples.ConclusionsOur study is expected to serve as a resource and a reference point for a systematic analysis of label-free LC-MS/MS targeted metabolomics data in both RPLC and HILIC methods with dMRM.

Dataset Information

MRMQuant: Automated MRM Data Quantitation for Large-Scale Targeted Metabolomics Analysis.

Publications

MRMQuant: Automated MRM Data Quantitation for Large-Scale Targeted Metabolomics Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets