Journal article 1148 views
Nanoparticle vesicle encoding for imaging and tracking cell populations
Nature Methods, Volume: 11, Issue: 11, Pages: 1177 - 1181
Swansea University Authors:
Paul Rees , Rowan Brown
, Huw Summers
Full text not available from this repository: check for access using links below.
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...
Published in: | Nature Methods |
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ISSN: | 1548-7105 1548-7105 |
Published: |
2014
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URI: | https://cronfa.swan.ac.uk/Record/cronfa20509 |
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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 |
|
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facultyofscienceandengineering |
hierarchy_top_title |
Faculty of Science and Engineering |
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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 |
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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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1763750818768486400 |
score |
11.021648 |