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Nanoparticle vesicle encoding for imaging and tracking cell populations

Paul Rees Orcid Logo, John W Wills, Rowan Brown Orcid Logo, James Tonkin, Mark D Holton, Nicole Hondow, Andrew P Brown, Rik Brydson, Val Millar, Anne E Carpenter, Huw Summers Orcid Logo

Nature Methods, Volume: 11, Issue: 11, Pages: 1177 - 1181

Swansea University Authors: Paul Rees Orcid Logo, Rowan Brown Orcid Logo, Huw Summers Orcid Logo

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DOI (Published version): 10.1038/nmeth.3105

Abstract

For phenotypic behavior to be understood in the context of cell lineage and local environment, properties of individual cells must be measured relative to population-wide traits. However, the inability to accurately identify, track and measure thousands of single cells via high-throughput microscopy...

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Published in: Nature Methods
ISSN: 1548-7105 1548-7105
Published: 2014
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URI: https://cronfa.swan.ac.uk/Record/cronfa20509
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spelling 2020-12-17T10:38:43.1953507 v2 20509 2015-03-24 Nanoparticle vesicle encoding for imaging and tracking cell populations 537a2fe031a796a3bde99679ee8c24f5 0000-0002-7715-6914 Paul Rees Paul Rees true false d7db8d42c476dfa69c15ce06d29bd863 0000-0003-3628-2524 Rowan Brown Rowan Brown true false a61c15e220837ebfa52648c143769427 0000-0002-0898-5612 Huw Summers Huw Summers true false 2015-03-24 MEDE For phenotypic behavior to be understood in the context of cell lineage and local environment, properties of individual cells must be measured relative to population-wide traits. However, the inability to accurately identify, track and measure thousands of single cells via high-throughput microscopy has impeded dynamic studies of cell populations. We demonstrate unique labeling of cells, driven by the heterogeneous random uptake of fluorescent nanoparticles of different emission colors. By sequentially exposing a cell population to different particles, we generated a large number of unique digital codes, which corresponded to the cell-specific number of nanoparticle-loaded vesicles and were visible within a given fluorescence channel. When three colors are used, the assay can self-generate over 17,000 individual codes identifiable using a typical fluorescence microscope. The color-codes provided immediate visualization of cell identity and allowed us to track human cells with a success rate of 78% across image frames separated by 8 h. Journal Article Nature Methods 11 11 1177 1181 1548-7105 1548-7105 14 9 2014 2014-09-14 10.1038/nmeth.3105 COLLEGE NANME Biomedical Engineering COLLEGE CODE MEDE Swansea University 2020-12-17T10:38:43.1953507 2015-03-24T10:32:55.6568532 Faculty of Science and Engineering School of Engineering and Applied Sciences - Biomedical Engineering Paul Rees 0000-0002-7715-6914 1 John W Wills 2 Rowan Brown 0000-0003-3628-2524 3 James Tonkin 4 Mark D Holton 5 Nicole Hondow 6 Andrew P Brown 7 Rik Brydson 8 Val Millar 9 Anne E Carpenter 10 Huw Summers 0000-0002-0898-5612 11
title Nanoparticle vesicle encoding for imaging and tracking cell populations
spellingShingle Nanoparticle vesicle encoding for imaging and tracking cell populations
Paul Rees
Rowan Brown
Huw Summers
title_short Nanoparticle vesicle encoding for imaging and tracking cell populations
title_full Nanoparticle vesicle encoding for imaging and tracking cell populations
title_fullStr Nanoparticle vesicle encoding for imaging and tracking cell populations
title_full_unstemmed Nanoparticle vesicle encoding for imaging and tracking cell populations
title_sort Nanoparticle vesicle encoding for imaging and tracking cell populations
author_id_str_mv 537a2fe031a796a3bde99679ee8c24f5
d7db8d42c476dfa69c15ce06d29bd863
a61c15e220837ebfa52648c143769427
author_id_fullname_str_mv 537a2fe031a796a3bde99679ee8c24f5_***_Paul Rees
d7db8d42c476dfa69c15ce06d29bd863_***_Rowan Brown
a61c15e220837ebfa52648c143769427_***_Huw Summers
author Paul Rees
Rowan Brown
Huw Summers
author2 Paul Rees
John W Wills
Rowan Brown
James Tonkin
Mark D Holton
Nicole Hondow
Andrew P Brown
Rik Brydson
Val Millar
Anne E Carpenter
Huw Summers
format Journal article
container_title Nature Methods
container_volume 11
container_issue 11
container_start_page 1177
publishDate 2014
institution Swansea University
issn 1548-7105
1548-7105
doi_str_mv 10.1038/nmeth.3105
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Biomedical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Biomedical Engineering
document_store_str 0
active_str 0
description For phenotypic behavior to be understood in the context of cell lineage and local environment, properties of individual cells must be measured relative to population-wide traits. However, the inability to accurately identify, track and measure thousands of single cells via high-throughput microscopy has impeded dynamic studies of cell populations. We demonstrate unique labeling of cells, driven by the heterogeneous random uptake of fluorescent nanoparticles of different emission colors. By sequentially exposing a cell population to different particles, we generated a large number of unique digital codes, which corresponded to the cell-specific number of nanoparticle-loaded vesicles and were visible within a given fluorescence channel. When three colors are used, the assay can self-generate over 17,000 individual codes identifiable using a typical fluorescence microscope. The color-codes provided immediate visualization of cell identity and allowed us to track human cells with a success rate of 78% across image frames separated by 8 h.
published_date 2014-09-14T03:24:16Z
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score 11.037603

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