Abstract
Mass spectrometry-based quantitative lipidomics is an emerging field aiming to uncover the intricate relationships between lipidomes and disease development. However, quantifying lipidomes comprehensively in a high-throughput manner remains challenging owing to the diverse lipid structures. Here we propose a diazobutanone-assisted isobaric labelling strategy as a rapid and robust platform for multiplexed quantitative lipidomics across a broad range of lipid classes, including various phospholipids and glycolipids. The diazobutanone reagent is designed to conjugate with phosphodiester or sulfate groups, while accommodating various functional groups on different lipid classes, enabling subsequent isobaric labelling for high-throughput multiplexed quantitation. Our method demonstrates excellent performance in terms of labelling efficiency, detection sensitivity, quantitative accuracy and broad applicability to various biological samples. Finally, we performed a six-plex quantification analysis of lipid extracts from lean and obese mouse livers. In total, we identified and quantified 246 phospholipids in a high-throughput manner, revealing lipidomic changes that may be associated with obesity in mice.
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Data availability
The data that support the findings of this study are available in the Supplementary Information and source data of this article. Raw data files were uploaded to the MassIVE database (massive.ucsd.edu/ProteoSAFe/static/massive.jsp) under accession number MSV000091941. The phospholipid database, LipidBlast, is available at prime.psc.riken.jp/compms/msdial/main.html#MSP. Source data are provided with this paper.
Code availability
Scripts are available on Zenodo (https://doi.org/10.5281/zenodo.8417892). The script was utilized for the identification and quantification of phospholipids and sulfated glycolipids. Briefly, the converted raw data in mzXML format undergo an exact mass match against a lipid database. The MS2 spectra of the matched precursors are then extracted and screened for both diagnostic and acylium ions. Finally, the abundance of reporter ions is extracted from the MS2 spectra of the identified lipids.
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Acknowledgements
This study was supported in part by grant funding from the NIH (R01AG052324, R01AG078794, P41GM108538, and R01DK071801). We also appreciate funding support from a Washington University/University of Wisconsin Diabetes Research Center pilot and feasibility grant (P30DK020579). L.L. acknowledges the funding support of NIH shared instrument grants (NIH-NCRR S10RR029531, S10OD028473 and S10OD025084), a Vilas Distinguished Achievement Professorship and the Charles Melbourne Johnson Distinguished Chair Professorship with funding provided by the Wisconsin Alumni Research Foundation and University of Wisconsin-Madison School of Pharmacy. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the paper.
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Contributions
T.-J.G. and L.L. developed the initial concept. T.-J.G. and P.-K.L. designed the research and performed most of the experiments and data analysis. Y.-W.W. and T.-J.G. wrote R code and conducted statistical analysis. M.T.F. and D.B.D. prepared mouse disease models. Y.L. prepared cell cultures. S.X. provided experimental feedback and assistance. T.-J.G., P.-K.L. and L.L. discussed the results and wrote the paper. M.T.F., S.X. and Y.L. edited the paper.
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The University of Wisconsin-Madison has filed a patent application (18/518,234) based on this work. L.L., T.-J.G. and P.-K.L. are named as inventors on this provisional patent application. The other authors declare no competing interests.
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Supplementary information
Supplementary Information
Supplementary Figs. 1–14, Tables 1 and 2 and Methods.
Supplementary Data 1
Details of PL acyl chain and species.
Source data
Source Data Fig. 2
Statistical source data.
Source Data Fig. 3
Intensity of MS1 and MS2 spectra.
Source Data Fig. 5
Statistical source data and details of PL species.
Source Data Fig. 6
Statistical source data and details of PL species.
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Gu, TJ., Liu, PK., Wang, YW. et al. Diazobutanone-assisted isobaric labelling of phospholipids and sulfated glycolipids enables multiplexed quantitative lipidomics using tandem mass spectrometry. Nat. Chem. (2024). https://doi.org/10.1038/s41557-023-01436-2
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DOI: https://doi.org/10.1038/s41557-023-01436-2
