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High spatial-resolution imaging of label-free in vivo protein aggregates by VISTA

Lin, Li-En and Miao, Kun and Qian, Chenxi and Wei, Lu (2021) High spatial-resolution imaging of label-free in vivo protein aggregates by VISTA. Analyst, 146 (13). pp. 4135-4145. ISSN 0003-2654. PMCID PMC8238904. doi:10.1039/d1an00060h. https://resolver.caltech.edu/CaltechAUTHORS:20210512-125027084

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Abstract

Amyloid aggregation, formed by aberrant proteins, is a pathological hallmark for neurodegenerative diseases, including Alzheimer's disease and Huntington's disease. High-resolution holistic mapping of the fine structures from these aggregates should facilitate our understanding of their pathological roles. Here, we achieved label-free high-resolution imaging of the polyQ and the amyloid-beta (Aβ) aggregates in cells and tissues utilizing a sample-expansion stimulated Raman strategy. We further focused on characterizing the Aβ plaques in 5XFAD mouse brain tissues. 3D volumetric imaging enabled visualization of the whole plaques, resolving both the fine protein filaments and the surrounding components. Coupling our expanded label-free Raman imaging with machine learning, we obtained specific segmentation of aggregate cores, peripheral filaments together with cell nuclei and blood vessels by pre-trained convolutional neural network models. Combining with 2-channel fluorescence imaging, we achieved a 6-color holistic view of the same sample. This ability for precise and multiplex high-resolution imaging of the protein aggregates and their micro-environment without the requirement of labeling would open new biomedical applications.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1039/d1an00060hDOIArticle
http://www.rsc.org/suppdata/d1/an/d1an00060h/d1an00060h1.pdfPublisherSupplementary Information
https://github.com/Li-En-Good/VISTARelated ItemCode
ORCID:
AuthorORCID
Lin, Li-En0000-0003-3086-6991
Miao, Kun0000-0001-6567-3650
Qian, Chenxi0000-0003-4815-5565
Wei, Lu0000-0001-9170-2283
Additional Information:© The Royal Society of Chemistry 2021. Received 11th January 2021, Accepted 7th April 2021, First published on 12th April 2021. We thank the Caltech Biological Imaging Facility for software support. We are grateful to Bryce Manifold (University of Washington) and the Caltech OLAR staffs for technical support. 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 (DP2GM140919-01), Amgen (Amgen Early Innovation Award), and the start-up funds from California Institute of Technology. Data and code availability: All data supporting the findings of the present study are available in the article and its supplementary figures, or from the corresponding author upon request. The code for U-Net training, prediction, and evaluation in this paper is available at https://github.com/Li-En-Good/VISTA. The authors declare no conflicts of interest.
Funders:
Funding AgencyGrant Number
Natural Sciences and Engineering Research Council of Canada (NSERC)UNSPECIFIED
NIHDP2GM140919-01
AmgenUNSPECIFIED
CaltechUNSPECIFIED
Issue or Number:13
PubMed Central ID:PMC8238904
DOI:10.1039/d1an00060h
Record Number:CaltechAUTHORS:20210512-125027084
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210512-125027084
Official Citation:High spatial-resolution imaging of label-free in vivo protein aggregates by VISTA, Analyst, 2021, 146, 4135-4145; DOI: 10.1039/d1an00060h
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109103
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:12 May 2021 20:40
Last Modified:04 Aug 2021 23:41

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