Institute of Photonics and Photon-Technology, Northwest University, #229 North Taibai Road, Xi'an, 710069, Shaanxi, China.
Department of Physics, Northwest University, Xi'an, 710069, Shaanxi, China.
Appl Microbiol Biotechnol. 2019 Aug;103(16):6759-6769. doi: 10.1007/s00253-019-09952-3. Epub 2019 Jun 22.
Confocal Raman microspectral imaging (CRMI) is an advanced cell-imaging method that maps endogenous molecular compositions with their unique spectral fingerprint indicators. The aim of this work was to provide a visualized understanding of subcellular features of live osteosarcoma cells using a 532-nm laser excitation without the use of dyes or molecular probes. Both malignant osteoblast and spindle osteosarcoma cells derived from the BALB/c mouse osteosarcoma cell line K7M2 were investigated in this work. After preprocessing the obtained spectral dataset, K-means cluster analysis (KCA) is employed to reconstruct Raman spectroscopic maps of single biological cells by identifying regions of the cellular membrane, cytoplasm, organelles, and nucleus with their corresponding mean spectra. Principal component analysis (PCA) was further employed to indicate variables of significant influence on the separation of the spectra of each cellular component. The biochemical components of the two cell types were then extracted by showing the spectral and distribution features attributed to proteins, lipids, and DNA. Using this standardized CRMI technique and multivariate analysis approaches, the results obtained could be a sound foundation for a typical Raman imaging protocol of live cellular biomedical analysis.
共焦拉曼显微成像（CRMI）是一种先进的细胞成像方法，它可以对具有独特光谱指纹指标的内源性分子成分进行映射。本工作的目的是利用 532nm 激光激发，无需使用染料或分子探针，提供活骨肉瘤细胞亚细胞特征的可视化理解。本工作研究了源自 BALB/c 小鼠骨肉瘤细胞系 K7M2 的恶性成骨细胞和梭形骨肉瘤细胞。在对获得的光谱数据集进行预处理后，通过识别细胞膜、细胞质、细胞器和细胞核及其相应的平均光谱，采用 K-均值聚类分析（KCA）来重建单个生物细胞的拉曼光谱图。进一步采用主成分分析（PCA）来表示对各细胞成分光谱分离有显著影响的变量。然后通过显示归因于蛋白质、脂质和 DNA 的光谱和分布特征，提取两种细胞类型的生化成分。使用这种标准化的 CRMI 技术和多元分析方法，获得的结果可以为活细胞生物医学分析的典型拉曼成像方案提供坚实的基础。
