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Lipidomic analysis and comparison of human body fluids and exosomes by various MS techniques
Autoři: Peterka Ondřej | Jirásko Robert | Chocholoušková Michaela | Wolrab Denise | Kuchař Ladislav | Holčapek Michal
Rok: 2019
Druh publikace: ostatní - přednáška nebo poster
Strana od-do: nestránkováno
Tituly:
Jazyk Název Abstrakt Klíčová slova
eng Lipidomic analysis and comparison of human body fluids and exosomes by various MS techniques Lipidomics is a subgroup of metabolomics aimed at the analysis of lipid species. Lipids play important roles in cells, and the individual lipids differ in the length of nonpolar fatty acyl chain(s) and polar/ionic head groups. They are potential biomarkers for some human diseases due to various biological functions as soon energy storage or precursors for metabolic processes. Ultrahigh-performance supercritical fluid chromatography (UPHSFC) and ultrahigh-performance liquid chromatography (UHPLC) with sub-2 µm particles columns enable high separation efficiency and short analysis time. Nowadays, mass spectrometry (MS) is a main technique for the lipid analysis and connection with separation methods enable the identification and quantification of a large number of lipids from various lipid categories. Matrix-assisted laser desorption/ionization coupled with Orbitrap MS with 9-aminoacridine matrix provides a selective ionization for polar lipids (mainly anionic lipids and sulfoglycosphingolipids containing two and even more hexosyl units) in the negative mode. Exosomes were isolated from human plasma by commercial kit (Invitrogen) and the total lipid extracts were prepared by modified Folch procedure. Human plasma, serum, and exosomes of healthy volunteers were used for the lipidomic comparison. Then, differences between kidney cancer patients and healthy controls were investigated. For lipid quantification, mixture of internal standards (1 standard per lipid class) was used. The signal stability was controlled by quality control (pooled sample – mixture of representative samples containing internal standards). Data were processed (noise reduction and obtained accurate masses) for reduced possibility of false identification. Our laboratory-made software LipidQuant was used for the semi-automated identification, isotopic correction, and quantitation of lipid species. Software Simca 13.0.3 (Umetrics) was used for multivariate data analysis. Statistical projection methods