Lipid Annotation by Combination of UHPLC-HRMS (MS), Molecular Networking, and Retention Time Prediction: Application to a Lipidomic Study of In Vitro Models of Dry Eye Disease

Type Article
Date 2020-06
Language English
Author(s) Magny Romain1, 2, Regazzetti Anne2, Kessal Karima1, 3, Genta-Jouve GregoryORCID2, 4, Baudouin ChristopheORCID1, 3, 5, Melik-Parsadaniantz Stephane1, Brignole-Baudouin Francoise1, 2, 3, Laprevote OlivierORCID2, 6, Auzeil Nicolas2
Affiliation(s) 1 : Sorbonne Univ UM80, Inst Vis, IHU ForeSight, INSERM UMR 968,CNRS UMR 7210, F-75006 Paris, France.
2 : Univ Paris, Fac Pharm, Chim Toxicol Analyt & Cellulaire, UMR CNRS 8038 CiTCoM, F-75006 Paris, France.
3 : Ctr Hosp Natl Ophtalmol Quinze Vingts, IHU ForeSight, F-75006 Paris, France.
4 : Univ Guyane, Lab Ecol Evolut Interact Syst Amazoniens LEEISA, CNRS Guyane, USR 3456, Cayenne 97300, French Guiana.
5 : Univ Versailles St Quentin En Yvelines, Hop Ambroise Pare, AP HP, F-92100 Boulogne, France.
6 : Hop Europeen Georges Pompidou, AP HP, Serv Biochim, F-75006 Paris, France.
Source Metabolites (2218-1989) (Mdpi), 2020-06 , Vol. 10 , N. 6 , P. 225 (18p.)
DOI 10.3390/metabo10060225
WOS© Times Cited 3
Note This article belongs to the Special Issue Advances in Lipidomics: Biomedicine, Nutrients and Methodology
Keyword(s) lipidomic, liquid chromatography, tandem mass spectrometry, molecular network, dry eye disease, hyperosmolarity
Abstract

Annotation of lipids in untargeted lipidomic analysis remains challenging and a systematic approach needs to be developed to organize important datasets with the help of bioinformatic tools. For this purpose, we combined tandem mass spectrometry-based molecular networking with retention time (t(R)) prediction to annotate phospholipid and sphingolipid species. Sixty-five standard compounds were used to establish the fragmentation rules of each lipid class studied and to define the parameters governing their chromatographic behavior. Molecular networks (MNs) were generated through the GNPS platform using a lipid standards mixture and applied to lipidomic study of anin vitromodel of dry eye disease,i.e., human corneal epithelial (HCE) cells exposed to hyperosmolarity (HO). These MNs led to the annotation of more than 150 unique phospholipid and sphingolipid species in the HCE cells. This annotation was reinforced by comparing theoretical to experimental t(R)values. This lipidomic study highlighted changes in 54 lipids following HO exposure of corneal cells, some of them being involved in inflammatory responses. The MN approach coupled to t(R)prediction thus appears as a suitable and robust tool for the discovery of lipids involved in relevant biological processes.

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Magny Romain, Regazzetti Anne, Kessal Karima, Genta-Jouve Gregory, Baudouin Christophe, Melik-Parsadaniantz Stephane, Brignole-Baudouin Francoise, Laprevote Olivier, Auzeil Nicolas (2020). Lipid Annotation by Combination of UHPLC-HRMS (MS), Molecular Networking, and Retention Time Prediction: Application to a Lipidomic Study of In Vitro Models of Dry Eye Disease. Metabolites, 10(6), 225 (18p.). Publisher's official version : https://doi.org/10.3390/metabo10060225 , Open Access version : https://archimer.ifremer.fr/doc/00695/80734/