High Coverage Quantitative Lipidomic Analysis for Multiple Biological Matrices Using Ultrahigh-Performance Liquid-Chromatography and Tandem Mass Spectrometry

The lipid composition (lipidome) in biological samples is extremely complex, having diverse biofunctions. Quantifying lipidomes with high coverage is vital to understand such functions but challenging due to their levels spanning several orders of magnitude, limited available standards, and poor chromatographic performances for many acidic lipids such as sphingosine-1-phosphate, phosphatidylserines, and phosphatidic acids. Here, we report a reliable method for high-coverage quantitative lipidomics using ultrahigh-performance liquid chromatography and tandem mass spectrometry (UHPLC-MS/MS). By using both pH and ammonium gradients in elution, all lipids, especially acidic ones, had obviously improved LC separation. By using 267 lipid standards in 49 subclasses, we also established quantitative structure-retention relationship models to predict the retention time (<i>t</i><sub>R</sub>) with good accuracy (Δ<i>t</i><sub>R</sub> < 0.33 min, MRE ∼3.4%) for all lipid subclasses. With UHPLC-MS/MS in multiple-reaction monitoring mode, we subsequently developed a quantitative lipidomics method using three UHPLC conditions to enable coverage of over 21,700 lipids in 190 subclasses with good sensitivity, precision, accuracy and stability. We further confirmed its applicability by quantifying 2375 lipids in seven typical biological matrices including human plasma, urine, and non-small-cell lung cancer cells together with <i>E</i>. <i>coli</i>, <i>Arabidopsis</i> leaves, mouse liver tissue, and feces. This offers a high-coverage quantitative method for understanding molecular phenotypes associated with lipid functions in physiology and pathophysiology.

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Journal
Analytical Chemistry
Published
2026-03-03
DOI
https://doi.org/10.1021/acs.analchem.5c06487
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
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article

High Coverage Quantitative Lipidomic Analysis for Multiple Biological Matrices Using Ultrahigh-Performance Liquid-Chromatography and Tandem Mass Spectrometry

Yongquan Xue, Shuaiyao Wang, Chenhan Zhang, Qingxia Huang et al.
Analytical Chemistry
Metabolomics and Mass Spectrometry Studies
article

High Coverage Quantitative Lipidomic Analysis for Multiple Biological Matrices Using Ultrahigh-Performance Liquid-Chromatography and Tandem Mass Spectrometry

Yongquan Xue, Shuaiyao Wang, Chenhan Zhang, Qingxia Huang, Qingyan Chen, Di Zhang, Xi Zhang, Haoran Hu, Jingxian Zhang, H F Tang, H X Yao, Ting Liu, Yushi Li, Longlong Chen, Pinghui Liu, Men Yu, Yulan Wang, Qi Wang
article en

Abstract

The lipid composition (lipidome) in biological samples is extremely complex, having diverse biofunctions. Quantifying lipidomes with high coverage is vital to understand such functions but challenging due to their levels spanning several orders of magnitude, limited available standards, and poor chromatographic performances for many acidic lipids such as sphingosine-1-phosphate, phosphatidylserines, and phosphatidic acids. Here, we report a reliable method for high-coverage quantitative lipidomics using ultrahigh-performance liquid chromatography and tandem mass spectrometry (UHPLC-MS/MS). By using both pH and ammonium gradients in elution, all lipids, especially acidic ones, had obviously improved LC separation. By using 267 lipid standards in 49 subclasses, we also established quantitative structure-retention relationship models to predict the retention time (<i>t</i><sub>R</sub>) with good accuracy (Δ<i>t</i><sub>R</sub> < 0.33 min, MRE ∼3.4%) for all lipid subclasses. With UHPLC-MS/MS in multiple-reaction monitoring mode, we subsequently developed a quantitative lipidomics method using three UHPLC conditions to enable coverage of over 21,700 lipids in 190 subclasses with good sensitivity, precision, accuracy and stability. We further confirmed its applicability by quantifying 2375 lipids in seven typical biological matrices including human plasma, urine, and non-small-cell lung cancer cells together with <i>E</i>. <i>coli</i>, <i>Arabidopsis</i> leaves, mouse liver tissue, and feces. This offers a high-coverage quantitative method for understanding molecular phenotypes associated with lipid functions in physiology and pathophysiology.

Analytical ChemistryVol. 98(10)
Nanyang Technological University (SG), Fudan University (CN), Shanghai Chengtou (China) (CN), Daiseung Medics (South Korea) (KR)
No poverty
Openalex Percentile: Top 35%
Metabolomics and Mass Spectrometry Studies
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