Titration-Based Assessment of Matrix Effects in Direct Infusion Mass Spectrometry
- 1Department of Chemistry for Life Sciences, Uppsala University, 752 37 Uppsala, Sweden
- 2Center of Excellence for the Chemical Mechanisms of Life, Uppsala University, 752 37 Uppsala, Sweden
Abstract
Electrospray ionization mass spectrometry (ESI-MS) is a standard and robust technique for analysis of a large variety of biomolecules. Direct infusion approaches offer rapid, high-throughput analysis of small sample volumes but are inherently susceptible to matrix effects during electrospray ionization. These matrix effects can substantially alter analyte ionization and gas-phase response and thereby complicate the interpretation of analyte abundances in complex biological samples. Herein, we developed a titration-based workflow to identify matrix effects and distinguish true changes in endogenous analyte abundance from ionization artifacts using direct infusion probe mass spectrometry (DIP-MS). Rat brain tissue extracts, rat insulinoma cell extracts, and isotopically labeled internal standards were used to model different matrix complexities to define condition-based differences in matrix effects. Thereafter, by mixing paired extracts in different ratios and fitting linear regression models, we assessed analyte-specific responses to sample-specific matrices. Moreover, we uncovered ion suppression or enhancement of hundreds of analytes by comparing regression slopes using interaction tests. We find that using endogenous analytes in our titration-based workflow gives a good indication of matrix effects for certain analyte classes. However, using a preselected panel of internal standards is strongly favorable for reliably identifying matrix effects during ionization. Altogether, combining our titration workflow, a selected panel of internal standards, and regression modeling provides a sensitive way of detecting matrix effects and for distinguishing true metabolite abundance changes from ionization artifacts.
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BibTeX
@article{persson2026titrationbased,
title = {{Titration-Based Assessment of Matrix Effects in Direct Infusion Mass Spectrometry}},
author = {Pontus Persson and Gabor Toth and Natália Remper and Lucie Davidová and Ingela Lanekoff},
journal = {Journal of the American Society for Mass Spectrometry},
year = {2026},
month = oct,
doi = {10.1021/jasms.6c00220},
url = {https://doi.org/10.1021/jasms.6c00220},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Titration-Based Assessment of Matrix Effects in Direct Infusion Mass Spectrometry
AU - Pontus Persson
AU - Gabor Toth
AU - Natália Remper
AU - Lucie Davidová
AU - Ingela Lanekoff
PY - 2026
DA - 2026/10/24
JO - Journal of the American Society for Mass Spectrometry
DO - 10.1021/jasms.6c00220
UR - https://doi.org/10.1021/jasms.6c00220
AB - Electrospray ionization mass spectrometry (ESI-MS) is a standard and robust technique for analysis of a large variety of biomolecules. Direct infusion approaches offer rapid, high-throughput analysis of small sample volumes but are inherently susceptible to matrix effects during electrospray ionization. These matrix effects can substantially alter analyte ionization and gas-phase response and thereby complicate the interpretation of analyte abundances in complex biological samples. Herein, we developed a titration-based workflow to identify matrix effects and distinguish true changes in endogenous analyte abundance from ionization artifacts using direct infusion probe mass spectrometry (DIP-MS). Rat brain tissue extracts, rat insulinoma cell extracts, and isotopically labeled internal standards were used to model different matrix complexities to define condition-based differences in matrix effects. Thereafter, by mixing paired extracts in different ratios and fitting linear regression models, we assessed analyte-specific responses to sample-specific matrices. Moreover, we uncovered ion suppression or enhancement of hundreds of analytes by comparing regression slopes using interaction tests. We find that using endogenous analytes in our titration-based workflow gives a good indication of matrix effects for certain analyte classes. However, using a preselected panel of internal standards is strongly favorable for reliably identifying matrix effects during ionization. Altogether, combining our titration workflow, a selected panel of internal standards, and regression modeling provides a sensitive way of detecting matrix effects and for distinguishing true metabolite abundance changes from ionization artifacts.
SN - 1044-0305
SN - 1879-1123
ER -