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Updated: Mar 23, 2026

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS
Published on: May 20, 2013
A method for comparative metabolomics in urine using high resolution mass spectrometry.
Padma Ramakrishnan1, Sreenath Nair1, Kannan Rangiah1
1Metabolomics Facility, Centre for Cellular and Molecular Platforms, National Centre for Biological Sciences, GKVK, Bellary Road, Bangalore 560065, India.
This study developed a robust workflow for urine metabolite profiling using ultrahigh performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). The method successfully differentiated smokers from nonsmokers, identifying key metabolites for clinical metabolomics applications.
Area of Science:
- Analytical Chemistry
- Metabolomics
- Clinical Chemistry
Background:
- Metabolite profiling of biological fluids is crucial for accurate data extraction.
- Standardized workflows are needed for reliable metabolomic analysis.
Purpose of the Study:
- To develop and validate a comprehensive workflow for urine metabolite profiling.
- To assess the utility of the workflow in differentiating between smokers and nonsmokers.
Main Methods:
- Urine samples from smokers and nonsmokers analyzed using UHPLC-HRMS.
- Employed both Reversed Phase Chromatography (RPC) and Hydrophilic Interaction Liquid Chromatography (HILIC) with positive and negative ionization modes.
- Utilized spiked standards for data normalization and pooled quality controls (QCs) for reproducibility assessment.
Main Results:
- Identified a significant number of unique metabolites across four analytical modes (RPC/HILIC, positive/negative ionization).
- Statistical analysis demonstrated clear clustering between smokers and nonsmokers.
- Variable Importance in Projection (VIP) scores highlighted key differentiating metabolites.
Conclusions:
- The developed UHPLC-HRMS workflow provides a reproducible and effective method for urine metabolomic profiling.
- This workflow is applicable for comparative metabolomic studies in various disease models, advancing clinical metabolomics.
- The method successfully distinguished metabolic profiles between smokers and nonsmokers.
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