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Super-Resolution Label-free Volumetric Vibrational Imaging

Qian, Chenxi and Miao, Kun and Lin, Li-En and Chen, Xinhong and Du, Jiajun and Wei, Lu (2021) Super-Resolution Label-free Volumetric Vibrational Imaging. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20210111-140338961

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Abstract

Innovations in high-resolution optical imaging have allowed visualization of nanoscale biological structures and connections. However, super-resolution fluorescence techniques, including both optics-oriented and sample-expansion based, are limited in quantification and throughput especially in tissues from photobleaching or quenching of the fluorophores, and low-efficiency or non-uniform delivery of the probes. Here, we report a general sample-expansion vibrational imaging strategy, termed VISTA, for scalable label-free high-resolution interrogations of protein-rich biological structures with resolution down to 82 nm. VISTA achieves decent three-dimensional image quality through optimal retention of endogenous proteins, isotropic sample expansion, and deprivation of scattering lipids. Free from probe-labeling associated issues, VISTA offers unbiased and high-throughput tissue investigations. With correlative VISTA and immunofluorescence, we further validated the imaging specificity of VISTA and trained an image-segmentation model for label-free multi-component and volumetric prediction of nucleus, blood vessels, neuronal cells and dendrites in complex mouse brain tissues. VISTA could hence open new avenues for versatile biomedical studies.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/2021.01.08.425961DOIDiscussion Paper
https://github.com/Li-En-Good/VISTARelated ItemCode
ORCID:
AuthorORCID
Qian, Chenxi0000-0003-4815-5565
Miao, Kun0000-0001-6567-3650
Lin, Li-En0000-0003-3086-6991
Chen, Xinhong0000-0003-0408-0813
Wei, Lu0000-0001-9170-2283
Additional Information:The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. This version posted January 9, 2021. We thank Xun Wang and Dr. Lilien Voong for fruitful discussions. We are grateful to Can Li and Prof. Marianne Bronner for sharing the zebrafish embryo slices. Chenxi Qian acknowledges the support of the Natural Sciences and Engineering Research Council of Canada (NSERC Postdoctoral Fellowship). Lu Wei acknowledges the support of National Institutes of Health (NIH Director’s New Innovator Award, DP2 GM140919-01), Amgen (Amgen Early Innovation Award) and the start-up funds from California Institute of Technology. Data availability: The authors declare that all data supporting the findings of the present study are available in the article and its supplementary figures and tables, or from the corresponding author upon request. Code availability: MATLAB code used for PSF determination and Python code for U-Net training and prediction in this paper is available at https://github.com/Li-En-Good/VISTA. The authors have declared no competing interest.
Funders:
Funding AgencyGrant Number
Natural Sciences and Engineering Research Council of Canada (NSERC)UNSPECIFIED
NIHDP2 GM140919-01
AmgenUNSPECIFIED
CaltechUNSPECIFIED
Record Number:CaltechAUTHORS:20210111-140338961
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210111-140338961
Official Citation:Super-Resolution Label-free Volumetric Vibrational Imaging. Chenxi Qian, Kun Miao, Li-En Lin, Xinhong Chen, Jiajun Du, Lu Wei. bioRxiv 2021.01.08.425961; doi: https://doi.org/10.1101/2021.01.08.425961
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107395
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:11 Jan 2021 23:05
Last Modified:11 Jan 2021 23:05

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