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Rapid identification of erythrocyte phospholipids in Sprague–Dawley rats by ultra high performance liquid chromatography with electrospray ionization quadrupole time‐of‐flight tandem mass spectrometry
Author(s) -
Pi Juanjuan,
Wu Xia,
Yang Shitian,
Zeng Pingyan,
Feng Yifan
Publication year - 2015
Publication title -
journal of separation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.72
H-Index - 102
eISSN - 1615-9314
pISSN - 1615-9306
DOI - 10.1002/jssc.201401120
Subject(s) - chromatography , chemistry , mass spectrometry , electrospray ionization , quadrupole time of flight , tandem mass spectrometry , electrospray , analytical chemistry (journal) , high performance liquid chromatography , tandem , liquid chromatography–mass spectrometry , protein mass spectrometry , materials science , composite material
A rapid, sensitive, and reliable approach for analyzing five kinds of erythrocyte phospholipids in Sprague–Dawley rats was provided by ultra high performance liquid chromatography coupled with electrospray ionization quadrupole time‐of‐flight tandem mass spectrometry with MassLynx TM MassFragment. Improving conventional high performance liquid chromatography techniques, ultra high performance liquid chromatography integrated with quadrupole time‐of‐flight tandem mass spectrometry offers high sensitivity and increased analytical speed by using columns packed with sub‐2 μm particles (1.7 μm), which allows a faster separation to be achieved. Through this method, 83 phospholipids were tentatively characterized based on their mass spectra and tandem mass spectra, as well as by matching the in‐house formula database within a mass error of 5 ppm, including 40 phosphatidylcholines, 24 phosphatidyl ethanolamines, three phosphatidylinositols, six phosphatidylserines, and ten sphingomyelins. Our present results proved that the established method could be used to qualitatively analyze complex erythrocyte phospholipids in Sprague–Dawley rats and provide a useful data base for pharmacology and phospholipidomics to seek potential biomarkers of disease prediction.