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Merciai F, Basilicata MG, La Gioia D, Salviati E, Caponigro V, Ciaglia T, Musella S, Crescenzi C, Sommella E, Campiglia P. Sub-5-min RP-UHPLC-TIMS for high-throughput untargeted lipidomics and its application to multiple matrices. Anal Bioanal Chem 2024; 416:959-970. [PMID: 38078946 DOI: 10.1007/s00216-023-05084-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 11/10/2023] [Accepted: 11/27/2023] [Indexed: 01/23/2024]
Abstract
Untargeted lipidomics, with its ability to take a snapshot of the lipidome landscape, is an important tool to highlight lipid changes in pathology or drug treatment models. One of the shortcomings of most untargeted lipidomics based on UHPLC-HRMS is the low throughput, which is not compatible with large-scale screening. In this contribution, we evaluate the application of a sub-5-min high-throughput four-dimensional trapped ion mobility mass spectrometry (HT-4D-TIMS) platform for the fast profiling of multiple complex biological matrices. Human AC-16 cells and mouse brain, liver, sclera, and feces were used as samples. By using a fast 4-min RP gradient, the implementation of TIMS allows us to differentiate coeluting isomeric and isobaric lipids, with correct precursor ion isolation, avoiding co-fragmentation and chimeric MS/MS spectra. Globally, the HT-4D-TIMS allowed us to annotate 1910 different lipid species, 1308 at the molecular level and 602 at the sum composition level, covering 58 lipid subclasses, together with quantitation capability covering more than three orders of magnitude. Notably, TIMS values were highly comparable with respect to longer LC gradients (CV% = 0.39%). These results highlight how HT-4D-TIMS-based untargeted lipidomics possess high coverage and accuracy, halving the analysis time with respect to conventional UHPLC methods, and can be used for fast and accurate untargeted analysis of complex matrices to rapidly evaluate changes of lipid metabolism in disease models or drug discovery campaigns.
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Affiliation(s)
- Fabrizio Merciai
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 13284084, Fisciano, SA, Italy
| | | | - Danila La Gioia
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 13284084, Fisciano, SA, Italy
- PhD Program in Drug Discovery and Development, University of Salerno, Fisciano, SA, Italy
| | - Emanuela Salviati
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 13284084, Fisciano, SA, Italy
| | - Vicky Caponigro
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 13284084, Fisciano, SA, Italy
| | - Tania Ciaglia
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 13284084, Fisciano, SA, Italy
| | - Simona Musella
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 13284084, Fisciano, SA, Italy
| | - Carlo Crescenzi
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 13284084, Fisciano, SA, Italy
| | - Eduardo Sommella
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 13284084, Fisciano, SA, Italy.
| | - Pietro Campiglia
- Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 13284084, Fisciano, SA, Italy
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