TY - JOUR

T1 - Delving into the polar lipidome by optimized chromatographic separation, high-resolution mass spectrometry, and comprehensive identification with Lipostar

T2 - Microalgae as case study

AU - La Barbera, Giorgia

AU - Antonelli, Michela

AU - Cavaliere, Chiara

AU - Cruciani, Gabriele

AU - Goracci, Laura

AU - Montone, Carmela Maria

AU - Piovesana, Susy

AU - Laganà, Aldo

AU - Capriotti, Anna Laura

N1 - (Ekstern)

PY - 2018

Y1 - 2018

N2 - 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 glycosyldiradyl-glycerols 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.

AB - 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 glycosyldiradyl-glycerols 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.

UR - http://www.scopus.com/inward/record.url?scp=85054148267&partnerID=8YFLogxK

U2 - 10.1021/acs.analchem.8b03482

DO - 10.1021/acs.analchem.8b03482

M3 - Journal article

C2 - 30204416

AN - SCOPUS:85054148267

VL - 90

SP - 12230

EP - 12238

JO - Industrial And Engineering Chemistry Analytical Edition

JF - Industrial And Engineering Chemistry Analytical Edition

SN - 0003-2700

IS - 20

ER -