| Literature DB >> 34782739 |
Weisong Zhao1, Shiqun Zhao2, Liuju Li2, Xiaoshuai Huang3, Shijia Xing2, Yulin Zhang2, Guohua Qiu1, Zhenqian Han1, Yingxu Shang4, De-En Sun5, Chunyan Shan6, Runlong Wu2, Lusheng Gu7, Shuwen Zhang7, Riwang Chen8, Jian Xiao9, Yanquan Mo2, Jianyong Wang8, Wei Ji7, Xing Chen5, Baoquan Ding4, Yanmei Liu2,10, Heng Mao11, Bao-Liang Song9, Jiubin Tan12,13, Jian Liu1,14, Haoyu Li15,16,17, Liangyi Chen18,19,20.
Abstract
A main determinant of the spatial resolution of live-cell super-resolution (SR) microscopes is the maximum photon flux that can be collected. To further increase the effective resolution for a given photon flux, we take advantage of a priori knowledge about the sparsity and continuity of biological structures to develop a deconvolution algorithm that increases the resolution of SR microscopes nearly twofold. Our method, sparse structured illumination microscopy (Sparse-SIM), achieves ~60-nm resolution at a frame rate of up to 564 Hz, allowing it to resolve intricate structures, including small vesicular fusion pores, ring-shaped nuclear pores formed by nucleoporins and relative movements of inner and outer mitochondrial membranes in live cells. Sparse deconvolution can also be used to increase the three-dimensional resolution of spinning-disc confocal-based SIM, even at low signal-to-noise ratios, which allows four-color, three-dimensional live-cell SR imaging at ~90-nm resolution. Overall, sparse deconvolution will be useful to increase the spatiotemporal resolution of live-cell fluorescence microscopy.Entities:
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Year: 2021 PMID： 34782739 DOI： 10.1038/s41587-021-01092-2
Source DB: PubMed Journal: Nat Biotechnol ISSN： 1087-0156 Impact factor: 54.908