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A high-throughput technique to map cell images to cell positions using a 3D imaging flow cytometer

We develop a high-throughput technique to relate positions of individual cells to their three-dimensional (3D) imaging features with single-cell resolution. The technique is particularly suitable for nonadherent cells where existing spatial biology methodologies relating cell properties to their pos...

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Autores principales: Zhang, Zunming, Tang, Rui, Chen, Xinyu, Waller, Lauren, Kau, Alston, Fung, Anthony A., Gutierrez, Bien, An, Cheolhong, Cho, Sung Hwan, Shi, Lingyan, Lo, Yu-Hwa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8872737/
https://www.ncbi.nlm.nih.gov/pubmed/35173045
http://dx.doi.org/10.1073/pnas.2118068119
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author Zhang, Zunming
Tang, Rui
Chen, Xinyu
Waller, Lauren
Kau, Alston
Fung, Anthony A.
Gutierrez, Bien
An, Cheolhong
Cho, Sung Hwan
Shi, Lingyan
Lo, Yu-Hwa
author_facet Zhang, Zunming
Tang, Rui
Chen, Xinyu
Waller, Lauren
Kau, Alston
Fung, Anthony A.
Gutierrez, Bien
An, Cheolhong
Cho, Sung Hwan
Shi, Lingyan
Lo, Yu-Hwa
author_sort Zhang, Zunming
collection PubMed
description We develop a high-throughput technique to relate positions of individual cells to their three-dimensional (3D) imaging features with single-cell resolution. The technique is particularly suitable for nonadherent cells where existing spatial biology methodologies relating cell properties to their positions in a solid tissue do not apply. Our design consists of two parts, as follows: recording 3D cell images at high throughput (500 to 1,000 cells/s) using a custom 3D imaging flow cytometer (3D-IFC) and dispensing cells in a first-in–first-out (FIFO) manner using a robotic cell placement platform (CPP). To prevent errors due to violations of the FIFO principle, we invented a method that uses marker beads and DNA sequencing software to detect errors. Experiments with human cancer cell lines demonstrate the feasibility of mapping 3D side scattering and fluorescent images, as well as two-dimensional (2D) transmission images of cells to their locations on the membrane filter for around 100,000 cells in less than 10 min. While the current work uses our specially designed 3D imaging flow cytometer to produce 3D cell images, our methodology can support other imaging modalities. The technology and method form a bridge between single-cell image analysis and single-cell molecular analysis.
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spelling pubmed-88727372022-02-25 A high-throughput technique to map cell images to cell positions using a 3D imaging flow cytometer Zhang, Zunming Tang, Rui Chen, Xinyu Waller, Lauren Kau, Alston Fung, Anthony A. Gutierrez, Bien An, Cheolhong Cho, Sung Hwan Shi, Lingyan Lo, Yu-Hwa Proc Natl Acad Sci U S A Biological Sciences We develop a high-throughput technique to relate positions of individual cells to their three-dimensional (3D) imaging features with single-cell resolution. The technique is particularly suitable for nonadherent cells where existing spatial biology methodologies relating cell properties to their positions in a solid tissue do not apply. Our design consists of two parts, as follows: recording 3D cell images at high throughput (500 to 1,000 cells/s) using a custom 3D imaging flow cytometer (3D-IFC) and dispensing cells in a first-in–first-out (FIFO) manner using a robotic cell placement platform (CPP). To prevent errors due to violations of the FIFO principle, we invented a method that uses marker beads and DNA sequencing software to detect errors. Experiments with human cancer cell lines demonstrate the feasibility of mapping 3D side scattering and fluorescent images, as well as two-dimensional (2D) transmission images of cells to their locations on the membrane filter for around 100,000 cells in less than 10 min. While the current work uses our specially designed 3D imaging flow cytometer to produce 3D cell images, our methodology can support other imaging modalities. The technology and method form a bridge between single-cell image analysis and single-cell molecular analysis. National Academy of Sciences 2022-02-16 2022-02-22 /pmc/articles/PMC8872737/ /pubmed/35173045 http://dx.doi.org/10.1073/pnas.2118068119 Text en https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Biological Sciences
Zhang, Zunming
Tang, Rui
Chen, Xinyu
Waller, Lauren
Kau, Alston
Fung, Anthony A.
Gutierrez, Bien
An, Cheolhong
Cho, Sung Hwan
Shi, Lingyan
Lo, Yu-Hwa
A high-throughput technique to map cell images to cell positions using a 3D imaging flow cytometer
title A high-throughput technique to map cell images to cell positions using a 3D imaging flow cytometer
title_full A high-throughput technique to map cell images to cell positions using a 3D imaging flow cytometer
title_fullStr A high-throughput technique to map cell images to cell positions using a 3D imaging flow cytometer
title_full_unstemmed A high-throughput technique to map cell images to cell positions using a 3D imaging flow cytometer
title_short A high-throughput technique to map cell images to cell positions using a 3D imaging flow cytometer
title_sort high-throughput technique to map cell images to cell positions using a 3d imaging flow cytometer
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8872737/
https://www.ncbi.nlm.nih.gov/pubmed/35173045
http://dx.doi.org/10.1073/pnas.2118068119
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