论文标题
通过超快速调整和空间光谱学习的单个活细胞和整个大脑的指纹光谱SRS成像
Fingerprint Spectroscopic SRS Imaging of Single Living Cells and Whole Brain by Ultrafast Tuning and Spatial-Spectral Learning
论文作者
论文摘要
刺激的拉曼散射(SRS)通过无标记的振动成像提供了对生活系统中实时化学分布的前所未有的见解。具体而言,指纹区域中的SR可以使用特定和分离的拉曼特征来解决复杂的生物环境中的多种化学物质。然而,由于小指纹拉曼横截面以及缺乏高光谱分辨率和高富度性的超快采集方案,尚未实现具有微秒光谱采集的指纹SRS成像。在这里,我们报告了一个指纹光谱SRS平台,该平台使用实验室构建的超快延迟线调谐系统,在20微秒内以10 cm-1光谱分辨率获取无失真的SRS光谱。同时,我们通过使用空间谱剩余学习网络来显着提高信噪比,从而达到可比较的质量,其质量与带有两个数量级的图像更长的像素停留时间。总的来说,我们的系统以微秒的光谱采集速度实现了可靠的指纹光谱SRS,从而在从现场单个微生物到组织切片的样品中实现了成像并跟踪多种生物分子的样品,以前不可能在高度挤满的碳纤维碳质区域中进行SRS成像。为了显示该方法的广泛效用,我们已经证明了活胰腺癌MIA PACA-2细胞中脂质代谢的高速成像。然后,我们在小鼠全脑中对胆固醇,脂肪酸和蛋白质进行了高分辨率图。最后,我们通过利用系统的优质光谱和时间分辨率来绘制微生物样品中两个生物燃料的生产。
Label-free vibrational imaging by stimulated Raman scattering (SRS) provides unprecedented insight into real-time chemical distributions in living systems. Specifically, SRS in the fingerprint region can resolve multiple chemicals in a complex bio-environment using specific and well-separated Raman signatures. Yet, fingerprint SRS imaging with microsecond spectral acquisition has not been achieved due to the small fingerprint Raman cross-sections and the lack of ultrafast acquisition scheme with high spectral resolution and high fidelity. Here, we report a fingerprint spectroscopic SRS platform that acquires a distortion-free SRS spectrum with 10 cm-1 spectral resolution in 20 microseconds using a lab-built ultrafast delay-line tuning system. Meanwhile, we significantly improve the signal-to-noise ratio by employing a spatial-spectral residual learning network, reaching comparable quality to images taken with two orders of magnitude longer pixel dwell times. Collectively, our system achieves reliable fingerprint spectroscopic SRS with microsecond spectral acquisition speed, enabling imaging and tracking of multiple biomolecules in samples ranging from a live single microbe to a tissue slice, which was not previously possible with SRS imaging in the highly congested carbon-hydrogen region. To show the broad utility of the approach, we have demonstrated high-speed compositional imaging of lipid metabolism in living pancreatic cancer Mia PaCa-2 cells. We then performed high-resolution mapping of cholesterol, fatty acid, and protein in the mouse whole brain. Finally, we mapped the production of two biofuels in microbial samples by harnessing the superior spectral and temporal resolutions of our system.