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Using soft X-ray tomography for rapid whole-cell quantitative imaging of SARS-CoV-2-infected cells

High-resolution and rapid imaging of host cell ultrastructure can generate insights toward viral disease mechanism, for example for a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. Here, we employ full-rotation soft X-ray tomography (SXT) to examine organelle remodeling indu...

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Main Authors: Loconte, Valentina (Author) , Chen, Jian-Hua (Author) , Cortese, Mirko (Author) , Ekman, Axel (Author) , Le Gros, Mark A. (Author) , Larabell, Carolyn (Author) , Bartenschlager, Ralf (Author) , Weinhardt, Venera (Author)
Format: Article (Journal)
Language:English
Published: October 28, 2021
In: Cell reports. Methods
Year: 2021, Volume: 1, Issue: 7, Pages: 1-13, e1-3
ISSN:2667-2375
DOI:10.1016/j.crmeth.2021.100117
Online Access:Resolving-System, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.crmeth.2021.100117
Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S2667237521001818
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Author Notes:Valentina Loconte, Jian-Hua Chen, Mirko Cortese, Axel Ekman, Mark A. Le Gros, Carolyn Larabell, Ralf Bartenschlager, and Venera Weinhardt
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Summary:High-resolution and rapid imaging of host cell ultrastructure can generate insights toward viral disease mechanism, for example for a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. Here, we employ full-rotation soft X-ray tomography (SXT) to examine organelle remodeling induced by SARS-CoV-2 at the whole-cell level with high spatial resolution and throughput. Most of the current SXT systems suffer from a restricted field of view due to use of flat sample supports and artifacts due to missing data. In this approach using cylindrical sample holders, a full-rotation tomogram of human lung epithelial cells is performed in less than 10 min. We demonstrate the potential of SXT imaging by visualizing aggregates of SARS-CoV-2 virions and virus-induced intracellular alterations. This rapid whole-cell imaging approach allows us to visualize the spatiotemporal changes of cellular organelles upon viral infection in a quantitative manner.
Item Description:Gesehen am 09.12.2021
Physical Description:Online Resource
ISSN:2667-2375
DOI:10.1016/j.crmeth.2021.100117

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