ArticleMetabolites2019
Tissue-Specific Sample Dilution: An Important Parameter to Optimise Prior to Untargeted LC-MS Metabolomics.
Article in Metabolites, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 31 citations in OpenAlex.
- Article
- Systematic evaluation of pre-analytical variables on synovial fluid metabolomic profiles using GC-ToF-MS and UHPLC-MS.The Analyst · 2026Article
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- Accuracy, linearity, and statistical differences in comparative quantification in untargeted plant metabolomics using LC-ESI-Orbitrap-MS.Analytical and bioanalytical chemistry · 2025Article
- The Metabolic and Lipidomic Fingerprint of Torin1 Exposure in Mouse Embryonic Fibroblasts Using Untargeted Metabolomics.Metabolites · 2024Article
- Development of an Untargeted LC-MS Metabolomics Method with Postcolumn Infusion for Matrix Effect Monitoring in Plasma and Feces.Journal of the American Society for Mass Spectrometry · 2024Article
- Signal Response Evaluation Applied to Untargeted Mass Spectrometry Data to Improve Data Interpretability.Journal of the American Society for Mass Spectrometry · 2023Article
- Spatial Metabolomics Reveals the Multifaceted Nature of Lamprey Buccal Gland and Its Diverse Mechanisms for Blood-Feeding.Communications biology · 2023Article
- Dried Blood Spot (DBS) Methodology Study for Biomarker Discovery in Lysosomal Storage Disease (LSD).Metabolites · 2021Article
- Metabolomic signatures for visceral adiposity and dysglycaemia in Asian Chinese and Caucasian European adults: the cross-sectional TOFI_Asia study.Nutrition & metabolism · 2020Article
- n-Butylamine for Improving the Efficiency of Untargeted Mass Spectrometry Analysis of Plasma Metabolite Composition.International journal of molecular sciences · 2019Article
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
When developing a sample preparation protocol for LC-MS untargeted metabolomics of a new sample matrix unfamiliar to the laboratory, selection of a suitable injection concentration is rarely described. Here we developed a simple workflow to address this issue prior to untargeted LC-MS metabolomics using pig adipose tissue and liver tissue. Bi-phasic extraction was performed to enable simultaneous optimisation of parameters for analysis of both lipids and polar extracts. A series of diluted pooled samples were analysed by LC-MS and used to evaluate signal linearity. Suitable injected concentrations were determined based on both the number of reproducible features and linear features. With our laboratory settings, the optimum concentrations of tissue mass to reconstitution solvent of liver and adipose tissue lipid fractions were found to be 125 mg/mL and 7.81 mg/mL respectively, producing 2811 (ESI+) and 4326 (ESI-) linear features from liver, 698 (ESI+) and 498 (ESI-) linear features from adipose tissue. For analysis of the polar fraction of both tissues, 250 mg/mL was suitable, producing 403 (ESI+) and 235 (ESI-) linear features from liver, 114 (ESI+) and 108 (ESI-) linear features from adipose tissue. Incorrect reconstitution volumes resulted in either severe overloading or poor linearity in our lipid data, while too dilute polar fractions resulted in a low number of reproducible features (<50) compared to hundreds of reproducible features from the optimum concentration used. Our study highlights on multiple matrices and multiple extract and chromatography types, the critical importance of determining a suitable injected concentration prior to untargeted LC-MS metabolomics, with the described workflow applicable to any matrix and LC-MS system.
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