State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
Institute of Theoretical and Computational Chemistry, Key Laboratory of Mesoscopic Chemistry of the Ministry of Education (MOE), School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
Biosensors (Basel). 2022 Oct 15;12(10):875. doi: 10.3390/bios12100875.
Establishing a systematic molecular information analysis strategy for cell culture models is of great significance for drug development and tissue engineering technologies. Here, we fabricated single silver nanowires with high surface-enhanced Raman scattering activity to extract SERS spectra in situ from two-dimensional (2D) and three-dimensional (3D) cell culture models. The silver nanowires were super long, flexible and thin enough to penetrate through multiple cells. A single silver nanowire was used in combination with a four-dimensional microcontroller as a cell endoscope for spectrally analyzing the components in cell culture models. Then, we adopted a machine learning algorithm to analyze the obtained spectra. Our results show that the abundance of proteins differs significantly between the 2D and 3D models, and that nucleic acid-rich and protein-rich regions can be distinguished with satisfactory accuracy.
建立系统的细胞培养模型分子信息分析策略对于药物开发和组织工程技术具有重要意义。在这里，我们制备了具有高表面增强拉曼散射活性的单根银纳米线，以从二维（2D）和三维（3D）细胞培养模型中实时提取表面增强拉曼散射（SERS）光谱。这些银纳米线超长、灵活且足够薄，可以穿透多个细胞。一根银纳米线与一个四维微控制器结合使用，作为细胞内窥镜，对细胞培养模型中的成分进行光谱分析。然后，我们采用机器学习算法来分析获得的光谱。结果表明，2D 和 3D 模型中的蛋白质丰度有显著差异，并且可以以令人满意的准确度区分富含核酸和富含蛋白质的区域。
