用硫代磷酰香兰素比色法和拉曼光谱表征细胞外囊泡

IF 3.3 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Frontiers in bioscience (Landmark edition) Pub Date : 2024-10-23 DOI:10.31083/j.fbl2910366
Alexey Senkovenko, Gleb Skryabin, Evgeniia Parshina, Alexey Piryazev, Elena Tchevkina, Dmitry Bagrov
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引用次数: 0

摘要

背景:细胞外囊泡 (EV) 的详细表征对于其在医学诊断中的应用至关重要。然而,由于细胞外囊泡化学成分的复杂性和细胞外囊泡群体的异质性,对它们进行表征极具挑战性。在此,我们介绍两种有助于克服这一挑战的分析程序:方法:使用超速离心法从条件细胞培养基中分离出小的 EVs,并使用纳米粒子跟踪分析(NTA)和透射电子显微镜(TEM)对其进行表征。拉曼光谱用于评估分离样品的总体成分以及从中提取的脂质。硫代磷酸香兰素(SPV)比色法用于量化脂质的含量:结果:对六个 EVs 样品进行了表征。用 SPV 法测得的脂质含量与用 NTA 法测得的基于粒度和浓度的定量估计值基本吻合。拉曼光谱中观察到的大多数峰值可归因于蛋白质或脂质,并通过脂质提取证实了它们的来源。根据拉曼光谱估算出了蛋白质与脂质的比例:本研究中描述的实验程序将有助于克服对 EVs 进行快速、高信息量表征的挑战。
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Characterization of Extracellular Vesicles by Sulfophosphovanillin Colorimetric Assay and Raman Spectroscopy.

Background: Detailed characterization of extracellular vesicles (EVs) is crucial for their application in medical diagnostics. However, the complexity of their chemical composition and the heterogeneity of EV populations make their characterization challenging. Here we describe two analytical procedures that can help overcome this challenge.

Methods: Small EVs were isolated from conditioned cell culture media using ultracentrifugation and characterized using nanoparticle tracking analysis (NTA) and transmission electron microscopy (TEM). Raman spectroscopy was used to assess the overall composition of the isolated samples and lipids extracted from them. Sulfophosphovanillin (SPV) colorimetric assay was used to quantify the contents of lipid.

Results: Six samples of EVs were characterized. The lipid contents measured using SPV assay was in reasonable agreement with the quantitative estimates based on the particle size and concentration measured using NTA. The most peaks observed in the Raman spectra could be attributed to either proteins or lipids, and their origins was confirmed by lipid extraction. The protein-to-lipid ratio was estimated based on the Raman spectra.

Conclusions: The experiential procedures described in this study will help to overcome the challenge of quick and highly informative characterization of the EVs.

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