美国博德研究所Aviv Regev等研究人员合作发现，利用拉曼显微镜和Raman2RNA可预测活细胞中的单细胞RNA表达谱。该项研究成果于2024年1月10日在线发表在《自然—生物技术》杂志上。

研究人员报道了Raman2RNA（R2R），这是一种通过无标记高光谱拉曼显微镜图像和域翻译推断活细胞中单细胞表达谱的方法。研究人员利用基于锚定的单分子荧光原位杂交整合，或利用对抗性自动编码器的无锚生成，从拉曼图像中无损地预测单细胞RNA测序图谱。R2R优于明视野图像推断（余弦相似度：R2R>0.85，明视野<0.15）。

在将小鼠成纤维细胞重编程为诱导多能干细胞的过程中，R2R推断出了各种细胞状态的表达概况。通过对小鼠胚胎干细胞分化的活细胞追踪，R2R克服了表达空间的不连续性，追踪了早期出现的谱系分化和分化轨迹。R2R为未来探索活体基因组动态奠定了基础。

研究人员表示，单细胞RNA测序和其他分析测试有助于以前所未有的分辨率和规模研究细胞，但其本身具有破坏性。拉曼显微镜以亚细胞空间分辨率、无标记和无损的方式报告蛋白质和代谢物的振动能级，但它缺乏遗传和分子可解释性。

附：英文原文

Title: Prediction of single-cell RNA expression profiles in live cells by Raman microscopy with Raman2RNA

Author: Kobayashi-Kirschvink, Koseki J., Comiter, Charles S., Gaddam, Shreya, Joren, Taylor, Grody, Emanuelle I., Ounadjela, Johain R., Zhang, Ke, Ge, Baoliang, Kang, Jeon Woong, Xavier, Ramnik J., So, Peter T. C., Biancalani, Tommaso, Shu, Jian, Regev, Aviv

Issue&Volume: 2024-01-10

Abstract: Single-cell RNA sequencing and other profiling assays have helped interrogate cells at unprecedented resolution and scale, but are inherently destructive. Raman microscopy reports on the vibrational energy levels of proteins and metabolites in a label-free and nondestructive manner at subcellular spatial resolution, but it lacks genetic and molecular interpretability. Here we present Raman2RNA (R2R), a method to infer single-cell expression profiles in live cells through label-free hyperspectral Raman microscopy images and domain translation. We predict single-cell RNA sequencing profiles nondestructively from Raman images using either anchor-based integration with single molecule fluorescence in situ hybridization, or anchor-free generation with adversarial autoencoders. R2R outperformed inference from brightfield images (cosine similarities: R2R >0.85 and brightfield <0.15). In reprogramming of mouse fibroblasts into induced pluripotent stem cells, R2R inferred the expression profiles of various cell states. With live-cell tracking of mouse embryonic stem cell differentiation, R2R traced the early emergence of lineage divergence and differentiation trajectories, overcoming discontinuities in expression space. R2R lays a foundation for future exploration of live genomic dynamics.

DOI: 10.1038/s41587-023-02082-2

Source: https://www.nature.com/articles/s41587-023-02082-2