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Fluocell for Ratiometric and High-Throughput Live-Cell Image Visualization and Quantitation

Spatiotemporal regulation of molecular activities dictates cellular function and fate. Investigation of dynamic molecular activities in live cells often requires the visualization and quantitation of fluorescent ratio image sequences with subcellular resolution and in high throughput. Hence, there i...

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Autores principales: Qin, Qin, Laub, Shannon, Shi, Yiwen, Ouyang, Mingxing, Peng, Qin, Zhang, Jin, Wang, Yingxiao, Lu, Shaoying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646842/
https://www.ncbi.nlm.nih.gov/pubmed/33163483
http://dx.doi.org/10.3389/fphy.2019.00154
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author Qin, Qin
Laub, Shannon
Shi, Yiwen
Ouyang, Mingxing
Peng, Qin
Zhang, Jin
Wang, Yingxiao
Lu, Shaoying
author_facet Qin, Qin
Laub, Shannon
Shi, Yiwen
Ouyang, Mingxing
Peng, Qin
Zhang, Jin
Wang, Yingxiao
Lu, Shaoying
author_sort Qin, Qin
collection PubMed
description Spatiotemporal regulation of molecular activities dictates cellular function and fate. Investigation of dynamic molecular activities in live cells often requires the visualization and quantitation of fluorescent ratio image sequences with subcellular resolution and in high throughput. Hence, there is a great need for convenient software tools specifically designed with these capabilities. Here we describe a well-characterized open-source software package, Fluocell, customized to visualize pixelwise ratiometric images and calculate ratio time courses with subcellular resolution and in high throughput. Fluocell also provides group statistics and kinetic analysis functions for the quantified time courses, as well as 3D structure and function visualization for ratio images. The application of Fluocell is demonstrated by the ratiometric analysis of intensity images for several single-chain Förster (or fluorescence) resonance energy transfer (FRET)-based biosensors, allowing efficient quantification of dynamic molecular activities in a heterogeneous population of single live cells. Our analysis revealed distinct activation kinetics of Fyn kinase in the cytosolic and membrane compartments, and visualized a 4D spatiotemporal distribution of epigenetic signals in mitotic cells. Therefore, Fluocell provides an integrated environment for ratiometric live-cell image visualization and analysis, which generates high-quality single-cell dynamic data and allows the quantitative machine-learning of biophysical and biochemical computational models for molecular regulations in cells and tissues.
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spelling pubmed-76468422020-11-06 Fluocell for Ratiometric and High-Throughput Live-Cell Image Visualization and Quantitation Qin, Qin Laub, Shannon Shi, Yiwen Ouyang, Mingxing Peng, Qin Zhang, Jin Wang, Yingxiao Lu, Shaoying Front Phys Article Spatiotemporal regulation of molecular activities dictates cellular function and fate. Investigation of dynamic molecular activities in live cells often requires the visualization and quantitation of fluorescent ratio image sequences with subcellular resolution and in high throughput. Hence, there is a great need for convenient software tools specifically designed with these capabilities. Here we describe a well-characterized open-source software package, Fluocell, customized to visualize pixelwise ratiometric images and calculate ratio time courses with subcellular resolution and in high throughput. Fluocell also provides group statistics and kinetic analysis functions for the quantified time courses, as well as 3D structure and function visualization for ratio images. The application of Fluocell is demonstrated by the ratiometric analysis of intensity images for several single-chain Förster (or fluorescence) resonance energy transfer (FRET)-based biosensors, allowing efficient quantification of dynamic molecular activities in a heterogeneous population of single live cells. Our analysis revealed distinct activation kinetics of Fyn kinase in the cytosolic and membrane compartments, and visualized a 4D spatiotemporal distribution of epigenetic signals in mitotic cells. Therefore, Fluocell provides an integrated environment for ratiometric live-cell image visualization and analysis, which generates high-quality single-cell dynamic data and allows the quantitative machine-learning of biophysical and biochemical computational models for molecular regulations in cells and tissues. 2019-10-23 2019-10 /pmc/articles/PMC7646842/ /pubmed/33163483 http://dx.doi.org/10.3389/fphy.2019.00154 Text en http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Article
Qin, Qin
Laub, Shannon
Shi, Yiwen
Ouyang, Mingxing
Peng, Qin
Zhang, Jin
Wang, Yingxiao
Lu, Shaoying
Fluocell for Ratiometric and High-Throughput Live-Cell Image Visualization and Quantitation
title Fluocell for Ratiometric and High-Throughput Live-Cell Image Visualization and Quantitation
title_full Fluocell for Ratiometric and High-Throughput Live-Cell Image Visualization and Quantitation
title_fullStr Fluocell for Ratiometric and High-Throughput Live-Cell Image Visualization and Quantitation
title_full_unstemmed Fluocell for Ratiometric and High-Throughput Live-Cell Image Visualization and Quantitation
title_short Fluocell for Ratiometric and High-Throughput Live-Cell Image Visualization and Quantitation
title_sort fluocell for ratiometric and high-throughput live-cell image visualization and quantitation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646842/
https://www.ncbi.nlm.nih.gov/pubmed/33163483
http://dx.doi.org/10.3389/fphy.2019.00154
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