Liu Ya-Juan, Kyne Michelle, Kang Chao, Wang Cheng
Key Laboratory of Molecular Target & Clinical Pharmacology, and the NMPA & State Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences & the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, 511436, China.
School of Chemistry, National University of Ireland, Galway, Galway, H91 CF50, Ireland.
Biosens Bioelectron. 2025 Feb 15;270:116970. doi: 10.1016/j.bios.2024.116970. Epub 2024 Nov 19.
Raman spectroscopy provides a robust approach for detailed analysis of the chemical and molecular profiles of extracellular vesicles (EVs). Recent advancements in Raman techniques have significantly enhanced the sensitivity and accuracy of EV characterization, enabling precise detection and profiling of molecular components within EV samples. This review introduces and compares various Raman-based techniques for EV characterization. These include Raman spectroscopy (RS), which provides fundamental molecular information; Raman trapping analysis (RTA), which combines optical trapping with Raman scattering for the manipulation and analysis of individual EVs; surface-enhanced Raman spectroscopy (SERS), which enhances the Raman signal through the use of metallic nanostructures, significantly improving sensitivity; and microfluidic SERS, which integrates SERS with microfluidic platforms to allow high-throughput, label-free analysis of EVs in biological fluids. In addition to comparing various Raman techniques, this review provides a comprehensive analysis that includes comparisons of machine learning methods, EV isolation techniques, and characterization strategies. By integrating these approaches, the review presents a holistic perspective on Raman-based EV analysis, covering profiling, purity, heterogeneity and size analysis as well as imaging. The combined assessment of Raman technologies with advanced computational and experimental methodologies supports the development of more robust diagnostic and therapeutic applications involving EVs.
拉曼光谱法为细胞外囊泡（EVs）的化学和分子特征的详细分析提供了一种强大的方法。拉曼技术的最新进展显著提高了EVs表征的灵敏度和准确性，能够精确检测和分析EVs样品中的分子成分。本综述介绍并比较了用于EVs表征的各种基于拉曼的技术。这些技术包括：提供基本分子信息的拉曼光谱法（RS）；将光镊与拉曼散射相结合以操纵和分析单个EVs的拉曼捕获分析（RTA）；通过使用金属纳米结构增强拉曼信号、显著提高灵敏度的表面增强拉曼光谱法（SERS）；以及将SERS与微流控平台集成以实现对生物流体中EVs进行高通量、无标记分析的微流控SERS。除了比较各种拉曼技术外，本综述还提供了全面的分析，包括对机器学习方法、EVs分离技术和表征策略的比较。通过整合这些方法，本综述从整体上阐述了基于拉曼的EVs分析，涵盖了特征分析、纯度、异质性和大小分析以及成像。将拉曼技术与先进的计算和实验方法相结合的评估，有助于开发更强大的涉及EVs的诊断和治疗应用。
