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Updated: Oct 7, 2025

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS
Published on: May 20, 2013
Comprehensive Evaluation of Blood Plasma and Serum Sample Preparations for HRMS-Based Chemical Exposomics: Overlaps
Jade Chaker1, David Møbjerg Kristensen1,2, Thorhallur Ingi Halldorsson3,4
1Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000 Rennes, France.
Abstract:
Sample preparation of biological samples can have a substantial impact on the coverage of small molecules detectable using liquid chromatography-high-resolution mass spectrometry (LC-HRMS). This initial step is particularly critical for the detection of externally derived chemicals and their metabolites (internal chemical exposome) generally present at trace levels. Hence, our objective was to investigate how blood sample preparation methods affect the detection of low-abundant chemicals and to propose alternative methods to improve the coverage of the internal chemical exposome. We performed a comprehensive evaluation of 12 sample preparation methods (SPM) using phospholipid and protein removal plates (PLR), solid phase extraction plates (SPE), supported liquid extraction cartridge (SLE), and conventionally used protein precipitation (PPT). We implemented new quantitative and qualitative criteria for nontargeted analyses (detection frequency, recoveries, repeatability, matrix effect, low-level spiking significance, method detection limits, throughput, and ease of use) to amply characterize these SPM in a step-by-step-type approach. As a final step, PPT and one PLR plate were applied to cohort plasma and serum samples injected in triplicate to monitor batch repeatability, and annotation was performed on the related data sets to compare the respective impacts of these SPM. We demonstrate that sample preparation significantly affects both the range of observable compounds and the level at which they can be observed (only 43%-54% of total features are overlapping between the two SPM). We propose to use PPT and PLR on the same samples by implementing a simple analytical workflow as their complementarity would allow the broadening of the visible chemical space.
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