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通过超灵敏重加权可见受激拉曼散射实现细胞代谢的无标记纳米显微镜成像。

Label-free nanoscopy of cell metabolism by ultrasensitive reweighted visible stimulated Raman scattering.

作者信息

Lin Haonan, Seitz Scott, Tan Yuying, Lugagne Jean-Baptiste, Wang Le, Ding Guangrui, He Hongjian, Rauwolf Tyler J, Dunlop Mary J, Connor John H, Porco John A, Tian Lei, Cheng Ji-Xin

机构信息

Department of Electrical and Computer Engineering, Boston University, Boston, MA, USA.

Department of Biomedical Engineering, Boston University, Boston, MA, USA.

出版信息

Nat Methods. 2025 May;22(5):1040-1050. doi: 10.1038/s41592-024-02575-1. Epub 2025 Jan 16.

Abstract

Super-resolution imaging of cell metabolism is hindered by the incompatibility of small metabolites with fluorescent dyes and the limited resolution of imaging mass spectrometry. We present ultrasensitive reweighted visible stimulated Raman scattering (URV-SRS), a label-free vibrational imaging technique for multiplexed nanoscopy of intracellular metabolites. We developed a visible SRS microscope with extensive pulse chirping to improve the detection limit to ~4,000 molecules and introduced a self-supervised multi-agent denoiser to suppress non-independent noise in SRS by over 7.2 dB, resulting in a 50-fold sensitivity enhancement over near-infrared SRS. Leveraging the enhanced sensitivity, we employed Fourier reweighting to amplify sub-100-nm spatial frequencies that were previously overwhelmed by noise. Validated by Fourier ring correlation, we achieved a lateral resolution of 86 nm in cell imaging. We visualized the reprogramming of metabolic nanostructures associated with virus replication in host cells and subcellular fatty acid synthesis in engineered bacteria, demonstrating its capability towards nanoscopic spatial metabolomics.

摘要

细胞代谢的超分辨率成像受到小代谢物与荧光染料不相容以及成像质谱分辨率有限的阻碍。我们提出了超灵敏重加权可见受激拉曼散射(URV-SRS),这是一种用于细胞内代谢物多重纳米显微镜检查的无标记振动成像技术。我们开发了一种具有广泛脉冲啁啾的可见SRS显微镜,将检测限提高到约4000个分子,并引入了一种自监督多智能体去噪器,将SRS中的非独立噪声抑制超过7.2 dB,从而使灵敏度比近红外SRS提高了50倍。利用增强的灵敏度,我们采用傅里叶重加权来放大以前被噪声淹没的亚100纳米空间频率。通过傅里叶环相关验证,我们在细胞成像中实现了86纳米的横向分辨率。我们可视化了与宿主细胞中的病毒复制以及工程细菌中的亚细胞脂肪酸合成相关的代谢纳米结构的重编程,证明了其在纳米级空间代谢组学方面的能力。

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