Three-dimensional structured illumination microscopy with enhanced axial resolution

dc.contributor.author Li, Xuesong
dc.contributor.author Wu, Yicong
dc.contributor.author Su, Yijun
dc.contributor.author Rey-Suarez, Ivan
dc.contributor.author Matthaeus, Claudia
dc.contributor.author Updegrove, Taylor B.
dc.contributor.author Wei, Zhuang
dc.contributor.author Zhang, Lixia
dc.contributor.author Sasaki, Hideki
dc.contributor.author Li, Yue
dc.contributor.author Guo, Min
dc.contributor.author Giannini, John P.
dc.contributor.author Vishwasrao, Harshad D.
dc.contributor.author Chen, Jiji
dc.contributor.author Lee, Shih-Jong J.
dc.contributor.author Shao, Lin
dc.contributor.author Liu, Huafeng
dc.contributor.author Ramamurthi, Kumaran S.
dc.contributor.author Taraska, Justin W.
dc.contributor.author Upadhyaya, Arpita
dc.contributor.author La Riviere, Patrick
dc.contributor.author Shroff, Hari
dc.date.accessioned 2023-08-29T14:46:14Z
dc.date.available 2023-08-29T14:46:14Z
dc.date.issued 2023-01-26
dc.description © The Author(s), 2023. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Li, X., Wu, Y., Su, Y., Rey-Suarez, I., Matthaeus, C., Updegrove, T., Wei, Z., Zhang, L., Sasaki, H., Li, Y., Guo, M., Giannini, J., Vishwasrao, H., Chen, J., Lee, S.-J., Shao, L., Liu, H., Ramamurthi, K., Taraska, J., Upadhyaya, A., La Riviere, P., & Shroff, H. Three-dimensional structured illumination microscopy with enhanced axial resolution. Nature Biotechnology, (2023): 1–13, https://doi.org/10.1038/s41587-022-01651-1.
dc.description.abstract The axial resolution of three-dimensional structured illumination microscopy (3D SIM) is limited to ∼300 nm. Here we present two distinct, complementary methods to improve axial resolution in 3D SIM with minimal or no modification to the optical system. We show that placing a mirror directly opposite the sample enables four-beam interference with higher spatial frequency content than 3D SIM illumination, offering near-isotropic imaging with ∼120-nm lateral and 160-nm axial resolution. We also developed a deep learning method achieving ∼120-nm isotropic resolution. This method can be combined with denoising to facilitate volumetric imaging spanning dozens of timepoints. We demonstrate the potential of these advances by imaging a variety of cellular samples, delineating the nanoscale distribution of vimentin and microtubule filaments, observing the relative positions of caveolar coat proteins and lysosomal markers and visualizing cytoskeletal dynamics within T cells in the early stages of immune synapse formation.
dc.description.sponsorship This research was supported by the intramural research programs of the National Institute of Biomedical Imaging and Bioengineering; the National Heart, Lung, and Blood Institute; and the National Cancer Institute within the National Institutes of Health (NIH). A.U. acknowledges support from NIH grant R01GM131054 and National Science Foundation grant PHY-1915534. We thank the Office of Data Science Strategy, NIH, for providing a seed grant enabling us to train deep learning models using cloud-based computational resources. H.L. acknowledges support from the National Key Research and Development Program of China (2020AAA0109502), the Key Research and Development Program of Zhejiang Province (2021C03029) and the Talent Program of Zhejiang Province (2021R51004). H. Shroff and P.L.R. acknowledge the Whitman and Fellows program at the Marine Biological Laboratory for providing funding and space for discussions that were valuable to this work. This work was supported by the Howard Hughes Medical Institute (HHMI). This article is subject to HHMI’s Open Access to Publications policy. HHMI laboratory heads have previously granted a non-exclusive CC BY 4.0 license to the public and a sub-licensable license to HHMI in their research articles. Pursuant to those licenses, the author-accepted manuscript of this article can be made freely available under a CC BY 4.0 license immediately upon publication.
dc.identifier.citation Li, X., Wu, Y., Su, Y., Rey-Suarez, I., Matthaeus, C., Updegrove, T., Wei, Z., Zhang, L., Sasaki, H., Li, Y., Guo, M., Giannini, J., Vishwasrao, H., Chen, J., Lee, S.-J., Shao, L., Liu, H., Ramamurthi, K., Taraska, J., Upadhyaya, A., La Riviere, P., & Shroff, H. (2023). Three-dimensional structured illumination microscopy with enhanced axial resolution. Nature Biotechnology, 1–13.
dc.identifier.doi 10.1038/s41587-022-01651-1
dc.identifier.uri https://hdl.handle.net/1912/66804
dc.publisher Nature Research
dc.relation.uri https://doi.org/10.1038/s41587-022-01651-1
dc.rights Attribution 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by/4.0/ *
dc.title Three-dimensional structured illumination microscopy with enhanced axial resolution
dc.type Article
dspace.entity.type Publication
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