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Single-cell lactate production rate as a measure of glycolysis in endothelial cells

Heterogeneous metabolism supports critical single-cell functions. Here, we describe deep-learning-enabled image analyses of a genetically encoded lactate-sensing probe which can accurately quantify metabolite levels and glycolytic rates at the single-cell level. Multiple strategies and test data hav...

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Detalles Bibliográficos
Autores principales: Harrison, Devin, Wu, David, Huang, Jun, Fang, Yun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433287/
https://www.ncbi.nlm.nih.gov/pubmed/34527962
http://dx.doi.org/10.1016/j.xpro.2021.100807
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author Harrison, Devin
Wu, David
Huang, Jun
Fang, Yun
author_facet Harrison, Devin
Wu, David
Huang, Jun
Fang, Yun
author_sort Harrison, Devin
collection PubMed
description Heterogeneous metabolism supports critical single-cell functions. Here, we describe deep-learning-enabled image analyses of a genetically encoded lactate-sensing probe which can accurately quantify metabolite levels and glycolytic rates at the single-cell level. Multiple strategies and test data have been included to obviate possible obstacles including successful sensor expression and accurate segmentation. This protocol reliably discriminates between metabolically diverse subpopulations which can be used to directly link metabolism to functional phenotypes by integrating spatiotemporal information, genetic or pharmacological perturbations, and real-time metabolic states. For complete details on the use and execution of this protocol, please refer to Wu et al. (2021a).
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spelling pubmed-84332872021-09-14 Single-cell lactate production rate as a measure of glycolysis in endothelial cells Harrison, Devin Wu, David Huang, Jun Fang, Yun STAR Protoc Protocol Heterogeneous metabolism supports critical single-cell functions. Here, we describe deep-learning-enabled image analyses of a genetically encoded lactate-sensing probe which can accurately quantify metabolite levels and glycolytic rates at the single-cell level. Multiple strategies and test data have been included to obviate possible obstacles including successful sensor expression and accurate segmentation. This protocol reliably discriminates between metabolically diverse subpopulations which can be used to directly link metabolism to functional phenotypes by integrating spatiotemporal information, genetic or pharmacological perturbations, and real-time metabolic states. For complete details on the use and execution of this protocol, please refer to Wu et al. (2021a). Elsevier 2021-09-08 /pmc/articles/PMC8433287/ /pubmed/34527962 http://dx.doi.org/10.1016/j.xpro.2021.100807 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Harrison, Devin
Wu, David
Huang, Jun
Fang, Yun
Single-cell lactate production rate as a measure of glycolysis in endothelial cells
title Single-cell lactate production rate as a measure of glycolysis in endothelial cells
title_full Single-cell lactate production rate as a measure of glycolysis in endothelial cells
title_fullStr Single-cell lactate production rate as a measure of glycolysis in endothelial cells
title_full_unstemmed Single-cell lactate production rate as a measure of glycolysis in endothelial cells
title_short Single-cell lactate production rate as a measure of glycolysis in endothelial cells
title_sort single-cell lactate production rate as a measure of glycolysis in endothelial cells
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433287/
https://www.ncbi.nlm.nih.gov/pubmed/34527962
http://dx.doi.org/10.1016/j.xpro.2021.100807
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