Juan-Colás, José orcid.org/0000-0002-1031-915X, Hitchcock, Ian S orcid.org/0000-0001-7170-6703, Coles, Mark orcid.org/0000-0001-8079-9358 et al. (2 more authors) (2018) Quantifying single-cell secretion in real time using resonant hyperspectral imaging. Proceedings of the National Academy of Sciences of the United States of America. pp. 13204-13209. ISSN 1091-6490
Abstract
Cell communication is primarily regulated by secreted proteins, whose inhomogeneous secretion often indicates physiological disorder. Parallel monitoring of innate protein-secretion kinetics from individual cells is thus crucial to unravel systemic malfunctions. Here, we report a label-free, high-throughput method for parallel, in vitro, and real-time analysis of specific single-cell signaling using hyperspectral photonic crystal resonant technology. Heterogeneity in physiological thrombopoietin expression from individual HepG2 liver cells in response to platelet desialylation was quantified demonstrating how mapping real-time protein secretion can provide a simple, yet powerful approach for studying complex physiological systems regulating protein production at single-cell resolution.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018, The Author(s). |
Keywords: | Label-free,Photonic biosensing,Photonic crystal,Single-cell analysis |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Physics (York) The University of York > Faculty of Sciences (York) > Electronic Engineering (York) The University of York > Faculty of Sciences (York) > Biology (York) The University of York > Faculty of Sciences (York) > Centre for Immunology and Infection (CII) (York) The University of York > Faculty of Sciences (York) > Hull York Medical School (York) |
Funding Information: | Funder Grant number EPSRC EP/P030017/1 UNSPECIFIED MR/K021125/1 |
Depositing User: | Pure (York) |
Date Deposited: | 07 Nov 2018 11:40 |
Last Modified: | 31 Oct 2024 00:59 |
Published Version: | https://doi.org/10.1073/pnas.1814977115 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1073/pnas.1814977115 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:138313 |