High contrast, isotropic, and uniform 3D-imaging of centimeter-scale scattering samples using structured illumination light-sheet microscopy with axial sweeping

利用轴向扫描结构光照明光片显微镜对厘米级散射样品进行高对比度、各向同性和均匀的三维成像

阅读:1

Abstract

Light-sheet fluorescent microscopy (LSFM) has, in recent years, allowed for rapid 3D-imaging of cleared biomedical samples at larger and larger scale. However, even in cleared samples, multiple light scattering often degrades the imaging contrast and widens the optical sectioning. Accumulation of scattering intensifies these negative effects as light propagates inside the tissue, which accentuates the issues when imaging large samples. With axially swept light-sheet microscopy (ASLM), centimeter-scale samples can be scanned with a uniform micrometric optical sectioning. But to fully utilize these benefits for 3D-imaging in biomedical tissue samples, suppression of scattered light is needed. Here, we address this by merging ASLM with light-sheet based structured illumination into Structured Illumination Light-sheet Microscopy with Axial Sweeping (SILMAS). The SILMAS method thus enables high-contrast imaging, isotropic micrometric resolution and uniform optical sectioning in centimeter-scale scattering samples, creating isotropic 3D-volumes of e.g., whole mouse brains without the need for any computation-heavy post-processing. We demonstrate the effectiveness of the approach in agarose gel phantoms with fluorescent beads, and in an PFF injected alpha-synuclein transgenic mouse model tagged with a green fluorescent protein (SynGFP). SILMAS imaging is compared to standard ASLM imaging on the same samples and using the same optical setup, and is shown to increase contrast by as much as 370% and reduce widening of optical sectioning by 74%. With these results, we show that SILMAS improves upon the performance of current state-of-the-art light-sheet microscopes for large and imperfectly cleared tissue samples and is a valuable addition to the LSFM family.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。