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Published on: May 1, 2017
Principles of multiparametric optimization for phospholipidomics by 31P NMR spectroscopy
Norbert W Lutz1, Patrick J Cozzone2
1Centre de Résonance Magnétique Biologique et Médicale, UMR CNRS 7339, Faculté de Médecine de la Timone, Aix-Marseille Université, 27 bd. Jean Moulin, 13005, Marseille, France. norbert.lutz@univ-amu.fr.
Abstract:
Phospholipids have long been known to be the principal constituents of the bilayer matrix of cell membranes. While the main function of cell membranes is to provide physical separation between intracellular and extracellular compartments, further biological and biochemical functions for phospholipids have been identified more recently, notably in cell signaling, cell recognition and cell-cell interaction, but also in cell growth, electrical insulation of neurons and many other processes. Therefore, accurate and efficient determination of tissue phospholipid composition is essential for our understanding of biological tissue function. 31P NMR spectroscopy is a quantitative and fast method for analyzing phospholipid extracts from biological samples without prior separation. However, the number of phospholipid classes and subclasses that can be quantified separately and reliably in 31P NMR spectra of tissue extracts is critically dependent on a variety of experimental conditions. Until recently, little attention has been paid to the optimization of phospholipid 31P NMR spectra. This review surveys the basic physicochemical properties that determine the quality of phospholipid spectra, and describes an optimization strategy based on this assessment. Notably, the following experimental parameters need to be controlled for systematic optimization: (1) extract concentration, (2) concentration of chelating agent, (3) pH value of the aqueous component of the solvent system, and (4) temperature of the NMR measurement. We conclude that a multiparametric optimization approach is crucial to obtaining highly predictable and reproducible 31P NMR spectra of phospholipids.

