使用超高效液相色谱结合带电表面混合技术和高分辨率质谱进行稳健且可重复的脂质分离的非靶向脂质组学
Non-targeted Lipidomics Using a Robust and Reproducible Lipid Separation Using UPLC with Charged Surface Hybrid Technology and High-Resolution Mass Spectrometry.
作者信息
Isaac Giorgis, Shulaev Vladimir, Plumb Robert S
机构信息
Waters Corporation, Milford, MA, USA.
Department of Biological Sciences and Advanced Environmental Research Institute, College of Arts and Sciences,, The University of North Texas, Denton, TX, USA.
出版信息
Methods Mol Biol. 2022;2396:175-186. doi: 10.1007/978-1-0716-1822-6_13.
Lipids play an important role in the energy storage, cellular signaling, and pathophysiology of diseases such as cancer, neurodegenerative diseases, infections, and diabetes. Due to high importance of diverse lipid classes in human health and disease, manipulating lipid abundance and composition is an important target for metabolic engineering. The extreme structural diversity of lipids in real biological samples is challenging for analytical techniques due to large difference in physicochemical properties of individual lipid species. This chapter describes lipidomic analysis of large sample sets requiring reliable and robust methodology. Rapid and robust methods facilitate the support of longitudinal studies allowing the transfer of methodology between laboratories. We describe a high-throughput reversed-phase LC-MS methodology using Ultra Performance Liquid Chromatography (UPLC) with charged surface hybrid technology and accurate mass detection for high-throughput non-targeted lipidomics. The methodology showed excellent specificity, robustness, and reproducibility for over 100 LC-MS injections.
脂质在能量储存、细胞信号传导以及癌症、神经退行性疾病、感染和糖尿病等疾病的病理生理学中发挥着重要作用。由于不同脂质类别在人类健康和疾病中具有高度重要性,操纵脂质丰度和组成是代谢工程的一个重要目标。实际生物样品中脂质的极端结构多样性对分析技术构成了挑战,因为各个脂质种类的物理化学性质差异很大。本章介绍了对大量样本集进行脂质组学分析所需的可靠且稳健的方法。快速且稳健的方法有助于支持纵向研究,允许在不同实验室之间转移方法。我们描述了一种高通量反相液相色谱 - 质谱方法,该方法使用具有带电表面混合技术的超高效液相色谱(UPLC)以及用于高通量非靶向脂质组学的精确质量检测。该方法在超过100次液相色谱 - 质谱进样中表现出优异的特异性、稳健性和重现性。