摘要:
磷脂在细胞调控以及辅助因子方面起着重要作用, 对生物样本中的磷脂进行分析有助于深入了解磷脂在有机生物体内的生理功能及其与疾病发生之间的关系.本研究基于超高效液相色谱-串联四极杆飞行时间质谱 (UPLC-Q-TOF MS) 的磷脂组学分析方法, 对磷脂分析所采用的流动相组成、提取溶剂和超声辅助提取时间等条件进行优化.结果表明:采用流动相A为0.1％甲酸水溶液, 流动相B为含0.1％甲酸的乙腈-异丙醇溶液 (50:50, V/V) 时, 可有效地分离磷脂化合物, 且重现性较好 (保留时间RSD值均小于0.1％, 峰面积RSD值均小于10％) ;热图结果表明, 以甲醇-乙腈溶液 (1:9, V/V) 作为提取溶剂, 超声辅助提取时间为2min时, 磷脂种类提取能力与去除非磷脂种类脂质干扰最优;主成分分析得分图和载荷图分别表明该方法具有良好的重复性和磷脂种类提取能力.该方法不仅能够满足不同种类血样的磷脂组学分析, 还可应用于临床磷脂组学研究.
Abstract:
Phospholipids (PLs) play important roles in cellular regulation and cofactors.Profiling of phospholipids in biological samples could be helpful to understand in-depth knowledge of its physical function in biological organisms and the association with the development of diseases.Hence, it is necessary to develop robust and efficient method fit-for-purpose for clinical research and widely phospholipidomics application.The experiment was performed on an UPLC-Q-TOF MS system coupled with Acquity UPLC C18 BEH column (2.1 mm×100 mm×1.7μm) .Raw data were acquired in both posi-tive and negative electron spray ionization (ESI) at MSE mode, and processed using Progenesis QI software for phospholipids characterization.Composition of mobile phase, solvent for serum pretreatment and sonication time were investigated.Multivariate analyses, principal component analysis (PCA) , including scores plots and loading plots were used for quick comparison and efficient identification of the investigated conditions.The optimized method was finally applied to four kinds of blood sample and a batch of clinical samples to verify the applicability.The optimal mobile phase composition was acetonitrile-isopropanol (50:50, V/V) (coefficient of variation (CV) of retention time less than 0.1％ and CV of peak area less than 10％) .The result of heatmap visualization showed that pre-cold methanol-acetonitrile (1:9, V/V) together with ultrasonic-assisted extraction for 2 min were the optimal method for the PLs extraction and non-phospholipids removal.Better reproducibility and extraction ability were also exhibited intuitively from the results of the score plots and loading plots after using PCA.The developed method was applied for four kinds of blood samples.For the purpose potentially applicable to metabolomics study, the method is also applied for plasma collected from clinical patients during diagnostic to determine the alternation of metabolic profiles.Seven major kinds of PLs consisting of 626 identifier in negative ESI and 302 identifier in positive ESI were identified including phosphatidylcholine (PC) , phosphatidylethanolamine (PE) , phosphatidylinositol (PI) , phosphatidic acid (PA) , phosphatidylglycerol (PG) , phosphatidylserine (PS) , sphingo-myelin (SM) .The results suggested that the developed method can not only satisfy phospholipidomics analysis of different kinds of blood samples, but also can be used in clinical research.
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