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Updated: Jan 22, 2026

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
Published on: September 20, 2022
Tissue-Specific Sample Dilution: An Important Parameter to Optimise Prior to Untargeted LC-MS Metabolomics
Zhanxuan E Wu1,2,3, Marlena C Kruger4,5, Garth J S Cooper6,7
1Food Nutrition & Health, Food and Bio-based Products, AgResearch Limited, Palmerston North 4442, New Zealand.
Determining optimal injection concentration is crucial for accurate untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics. This study presents a workflow to optimize sample preparation for diverse matrices like pig liver and adipose tissue, ensuring reliable feature detection.
Area of Science:
- Metabolomics
- Analytical Chemistry
- Biochemistry
Background:
- Untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics requires optimized sample preparation.
- Selection of appropriate injection concentration is critical but often undescribed for new sample matrices.
Purpose of the Study:
- To develop and validate a workflow for determining optimal injection concentrations for untargeted LC-MS metabolomics.
- To address the challenge of sample preparation for novel matrices, specifically pig adipose and liver tissues.
Main Methods:
- Bi-phasic extraction was employed for simultaneous lipid and polar metabolite analysis.
- Serial dilutions of pooled samples were analyzed by LC-MS to assess signal linearity.
- Optimal concentrations were determined by evaluating reproducible and linear features.
Main Results:
- Optimum lipid fraction concentrations: 125 mg/mL (liver) and 7.81 mg/mL (adipose).
- Optimum polar fraction concentration: 250 mg/mL (both tissues).
- Deviations from optimal concentrations led to signal overloading, poor linearity, or reduced feature reproducibility.
Conclusions:
- A simple, matrix-agnostic workflow for optimizing injection concentration in untargeted LC-MS metabolomics was established.
- Properly determining injection concentration is critical for robust and reproducible metabolomic profiling.
- The workflow is applicable across various matrices and LC-MS systems.
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