Department of Basic Science, Graduate School of Arts and Sciences, The University of Tokyo, Meguro-ku, Tokyo 153-8902, Japan.
Department of Basic Science, Graduate School of Arts and Sciences, The University of Tokyo, Meguro-ku, Tokyo 153-8902, Japan; Research Center for Complex Systems Biology, The University of Tokyo, Meguro-ku, Tokyo 153-8902, Japan.
Cell Syst. 2018 Jul 25;7(1):104-117.e4. doi: 10.1016/j.cels.2018.05.015. Epub 2018 Jun 20.
Raman microscopy is an imaging technique that has been applied to assess molecular compositions of living cells to characterize cell types and states. However, owing to the diverse molecular species in cells and challenges of assigning peaks to specific molecules, it has not been clear how to interpret cellular Raman spectra. Here, we provide firm evidence that cellular Raman spectra and transcriptomic profiles of Schizosaccharomyces pombe and Escherichia coli can be computationally connected and thus interpreted. We find that the dimensions of high-dimensional Raman spectra and transcriptomes measured by RNA sequencing can be reduced and connected linearly through a shared low-dimensional subspace. Accordingly, we were able to predict global gene expression profiles by applying the calculated transformation matrix to Raman spectra, and vice versa. Highly expressed non-coding RNAs contributed to the Raman-transcriptome linear correspondence more significantly than mRNAs in S. pombe. This demonstration of correspondence between cellular Raman spectra and transcriptomes is a promising step toward establishing spectroscopic live-cell omics studies.
拉曼显微镜是一种成像技术，已被应用于评估活细胞的分子组成，以鉴定细胞类型和状态。然而，由于细胞中存在多种分子物种，以及为特定分子分配峰的挑战，因此尚不清楚如何解释细胞拉曼光谱。在这里，我们提供了确凿的证据，表明酿酒酵母和大肠杆菌的细胞拉曼光谱和转录组谱可以通过计算连接，从而进行解释。我们发现，通过 RNA 测序测量的高维拉曼光谱和转录组的维度可以通过共享的低维子空间线性减少和连接。因此，我们能够通过将计算出的变换矩阵应用于拉曼光谱来预测全局基因表达谱，反之亦然。在酿酒酵母中，高表达的非编码 RNA 比 mRNA 对拉曼-转录组线性对应关系的贡献更大。这一细胞拉曼光谱和转录组之间对应关系的证明，是朝着建立光谱活细胞组学研究迈出的有希望的一步。
