光谱学与光谱分析, 2012, 32 (9): 2422, 网络出版: 2012-09-26   

拉曼光谱检测生物大分子损伤的研究进展

Progress in Study of Biomolecular Damages by Raman Spectroscopy
作者单位
北京工业大学生命科学与生物工程学院, 北京 100124
摘要
拉曼光谱是基于拉曼散射效应而发展起来的一种光谱分析技术, 体现的是分子的振动或转动信息。 由于拉曼光谱技术与常规化学分析技术相比, 具有对样品无损、 样品制备简单和所需样品量少等特点, 广泛用于生物大分子结构变化的研究。 拉曼光谱不仅可以用于蛋白质、 核酸和脂类等生物大分子损伤的快速检测, 而且可以用于癌症的诊断与手术治疗。 通过对比正常组织与癌变组织的拉曼光谱, 可以找到两种组织特征吸收峰的差异, 从而为癌症的最终确诊和确定肿瘤切除范围提供重要信息。 文章综述了拉曼光谱检测生物大分子损伤的研究进展, 介绍了利用表面增强拉曼光谱、 傅里叶变换拉曼光谱和紫外共振拉曼光谱等技术在检测蛋白质二级结构、 膜脂及DNA损伤中的应用, 并展望了未来拉曼光谱技术的发展前景。
Abstract
Raman spectroscopy is an analytical techniques based on Raman scattering, which gives information of molecular vibration and rotation. Raman spectroscopy has been widely employed in the investigations of the structure of biomolacules, because it has many advantages over the common chemical analysis. Raman spectroscopy is non-destructive to the samples. Moreover, it requires simple sample preparation and small sample amount. Raman spectroscopy can be used not only for fast detections of damages of biological macromolecules, such as proteins, nucleic acids and lipids, but also for diagnosis and surgical treatments of cancer. By comparing the Raman spectra of normal tissue and cancer tissue, the differences in the characteristic absorption peaks between the two kinds of tissues can be confirmed, which provides significant information for final diagnosis of cancer and determination of the resection extent of tumor. This paper reviewed the researches on biomolecular damages by Raman spectral inspections. It described the applications of Raman spectral techniques, such as surface-enhanced Raman spectroscopy, Fourier transform Raman and UV resonance Raman spectroscopy, in the detection of protein secondary structures, membrane lipids and DNA damages. A prospect of the development of Raman spectroscopy in the future was given.

李莉莉, 赵丽娇, 钟儒刚. 拉曼光谱检测生物大分子损伤的研究进展[J]. 光谱学与光谱分析, 2012, 32(9): 2422. LI Li-li, ZHAO Li-jiao, ZHONG Ru-gang. Progress in Study of Biomolecular Damages by Raman Spectroscopy[J]. Spectroscopy and Spectral Analysis, 2012, 32(9): 2422.

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