Department of Chemical Engineering, Aragon Institute of Nanoscience (INA), University of Zaragoza, 50018 Zaragoza, Spain.
Networking Research Center on Bioengineering Biomaterials and Nanomedicine (CIBER-BBN), 28029 Madrid, Spain.
Int J Mol Sci. 2022 Jan 21;23(3):1150. doi: 10.3390/ijms23031150.
The question of whether exosome lipids can be considered as potential cancer biomarkers faces our current limited knowledge of their composition. This is due to the difficulty in isolating pure exosomes, the variability of the biological sources from which they are extracted, and the uncertainty of the methods for lipid characterization. Here, we present a procedure to isolate exosomes and obtain a deep, repeatable, and rapid phospholipid (PL) composition of their lipid extracts, from embryonic murine fibroblasts (NIH-3T3 cell line) and none (B16-F1) and high (B16-F10) metastatic murine skin melanoma cells. The analytical method is based on High Performance Thin-Layer Chromatography with Ultraviolet and fluorescence densitometry and coupled to Electrospray (ESI)-tandem Mass Spectrometry (MS). Under the conditions described in this work, separation and determination of PL classes, (sphingomyelins, SM; phosphatidylcholines, PC; phosphatidylserines, PS; and phosphatidylethanolamines, PE) were achieved, expressed as µg PL/100 µg exosome protein, obtained by bicinchoninic acid assay (BCA). A detailed structural characterization of molecular species of each PL class was performed by simultaneous positive and negative ESI-MS and MS/MS directly from the chromatographic plate, thanks to an elution-based interface.
外体脂质是否可以被视为潜在的癌症生物标志物，这一问题受到我们目前对其组成的有限认识的限制。这是由于难以分离纯净的外体、它们提取的生物来源的可变性以及脂质特征描述方法的不确定性所致。在这里，我们提出了一种从胚胎鼠成纤维细胞（NIH-3T3 细胞系）和非（B16-F1）和高（B16-F10）转移性鼠皮肤黑色素瘤细胞中分离外体并获得其脂质提取物中深度、可重复且快速的磷脂（PL）组成的程序。分析方法基于高效薄层色谱法，结合紫外和荧光密度法，并与电喷雾（ESI）-串联质谱（MS）联用。在本工作中描述的条件下，实现了 PL 类（神经鞘磷脂，SM；磷脂酰胆碱，PC；磷脂酰丝氨酸，PS；和磷脂酰乙醇胺，PE）的分离和测定，以每 100 µg 外体蛋白中的 µg PL 表示，通过双缩脲法测定（BCA）获得。通过基于洗脱的接口，直接从色谱板上进行正离子和负离子 ESI-MS 和 MS/MS 的同时分析，实现了对每个 PL 类的分子物种的详细结构特征的描述。
