Super-Resolution Imaging of Neuronal Structures with Structured Illumination Microscopy

被引:3
作者
Paul, Tristan C. [1 ]
Johnson, Karl A. [1 ]
Hagen, Guy M. [1 ]
机构
[1] Univ Colorado, UCCS BioFrontiers Ctr, 1420 Austin Bluffs Pkwy, Colorado Springs, CO 80918 USA
来源
BIOENGINEERING-BASEL | 2023年 / 10卷 / 09期
基金
美国国家卫生研究院;
关键词
fluorescence microscopy; structured illumination; brain; Bayesian methods; super-resolution;
D O I
10.3390/bioengineering10091081
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Super-resolution structured illumination microscopy (SR-SIM) is an optical fluorescence microscopy method which is suitable for imaging a wide variety of cells and tissues in biological and biomedical research. Typically, SIM methods use high spatial frequency illumination patterns generated by laser interference. This approach provides high resolution but is limited to thin samples such as cultured cells. Using a different strategy for processing raw data and coarser illumination patterns, we imaged through a 150-micrometer-thick coronal section of a mouse brain expressing GFP in a subset of neurons. The resolution reached 144 nm, an improvement of 1.7-fold beyond conventional widefield imaging.
引用
收藏
页数:13
相关论文
共 62 条
[1]  
Allen Institute for Brain Science, 2004, Allen Institute for Brain Science (2011). Allen Mouse Brain Atlas
[2]   Nanoscopy in a Living Mouse Brain [J].
Berning, Sebastian ;
Willig, Katrin I. ;
Steffens, Heinz ;
Dibaj, Payam ;
Hell, Stefan W. .
SCIENCE, 2012, 335 (6068) :551-551
[3]   Imaging intracellular fluorescent proteins at nanometer resolution [J].
Betzig, Eric ;
Patterson, George H. ;
Sougrat, Rachid ;
Lindwasser, O. Wolf ;
Olenych, Scott ;
Bonifacino, Juan S. ;
Davidson, Michael W. ;
Lippincott-Schwartz, Jennifer ;
Hess, Harald F. .
SCIENCE, 2006, 313 (5793) :1642-1645
[4]   Multicolor structured illumination microscopy and quantitative control of polychromatic light with a digital micromirror device [J].
Brown, Peter T. ;
Kruithoff, Rory ;
Seedorf, Gregory J. ;
Shepherd, Douglas P. .
BIOMEDICAL OPTICS EXPRESS, 2021, 12 (06) :3700-3716
[5]   Untrained, physics-informed neural networks for structured illumination microscopy [J].
Burns, Zachary ;
Liu, Zhaowei .
OPTICS EXPRESS, 2023, 31 (05) :8714-8724
[6]   Open-3DSIM: an open-source three-dimensional structured illumination microscopy reconstruction platform [J].
Cao, Ruijie ;
Li, Yaning ;
Chen, Xin ;
Ge, Xichuan ;
Li, Meiqi ;
Guan, Meiling ;
Hou, Yiwei ;
Fu, Yunzhe ;
Xu, Xinzhu ;
Jiang, Shan ;
Gao, Baoxiang ;
Xi, Peng .
NATURE METHODS, 2023, 20 (08) :1183-+
[7]   Deconvolution methods for structured illumination microscopy [J].
Chakrova, Nadya ;
Rieger, Bernd ;
Stallinga, Sjoerd .
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 2016, 33 (07) :B12-B20
[8]   csiLSFM combines light- sheet fluorescence microscopy and coherent structured illumination for a lateral resolution below 100 nm [J].
Chang, Bo-Jui ;
Meza, Victor Didier Perez ;
Stelzer, Ernst H. K. .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2017, 114 (19) :4869-4874
[9]  
Chaudhuri S., 2011, Super-Resolution Imaging
[10]   Superresolution structured illumination microscopy reconstruction algorithms: a review [J].
Chen, Xin ;
Zhong, Suyi ;
Hou, Yiwei ;
Cao, Ruijie ;
Wang, Wenyi ;
Li, Dong ;
Dai, Qionghai ;
Kim, Donghyun ;
Xi, Peng .
LIGHT-SCIENCE & APPLICATIONS, 2023, 12 (01)