The work describes the chromatographic separation optimization of polar lipids on Kinetex-EVO, particularly focusing on sulfolipids in spirulina microalgae (Arthrospira platensis). Gradient shape and mobile-phase modifiers (pH and buffer) were tested on lipid standards. Different conditions were evaluated, and resolution, peak capacity, and peak shape were calculated both in negative mode, for sulfolipids and phospholipids, and in positive mode, for glycolipids. A high-confidence lipid identification strategy was also applied. In collaboration with software creators and developers, Lipostar was implemented to improve the identification of phosphoglycerolipids and to allow the identification of glycosylmonoradyl- and glycosyldirady-lglycerols classes, the last being the main focus of this work. By this approach, an untargeted screening also for searching lipids not yet reported in the literature could be accomplished. The optimized chromatographic conditions and database search were tested for lipid identification first on the standard mixture, then on the polar lipid extract of spirulina microalgae, for which 205 lipids were identified.

Delving into the Polar Lipidome by Optimized Chromatographic Separation, High-Resolution Mass Spectrometry, and Comprehensive Identification with Lipostar: Microalgae as Case Study

Cruciani, Gabriele;Goracci, Laura;
2018

Abstract

The work describes the chromatographic separation optimization of polar lipids on Kinetex-EVO, particularly focusing on sulfolipids in spirulina microalgae (Arthrospira platensis). Gradient shape and mobile-phase modifiers (pH and buffer) were tested on lipid standards. Different conditions were evaluated, and resolution, peak capacity, and peak shape were calculated both in negative mode, for sulfolipids and phospholipids, and in positive mode, for glycolipids. A high-confidence lipid identification strategy was also applied. In collaboration with software creators and developers, Lipostar was implemented to improve the identification of phosphoglycerolipids and to allow the identification of glycosylmonoradyl- and glycosyldirady-lglycerols classes, the last being the main focus of this work. By this approach, an untargeted screening also for searching lipids not yet reported in the literature could be accomplished. The optimized chromatographic conditions and database search were tested for lipid identification first on the standard mixture, then on the polar lipid extract of spirulina microalgae, for which 205 lipids were identified.
2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1446056
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