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On the inference of ERK signaling dynamics from protein biosensor measurements

The extracellular signal-regulated kinase (ERK) signaling pathway plays prominent roles in cell growth, proliferation, and differentiation. ERK signaling is dynamic, involving phosphorylation/dephosphorylation, nucleocytoplasmic shuttling, and interactions with scores of protein substrates in the cy...

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Autores principales: Rahman, Shah Md. Toufiqur, Haugh, Jason M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Cell Biology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208096/
https://www.ncbi.nlm.nih.gov/pubmed/36884295
http://dx.doi.org/10.1091/mbc.E22-10-0476
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author Rahman, Shah Md. Toufiqur
Haugh, Jason M.
author_facet Rahman, Shah Md. Toufiqur
Haugh, Jason M.
author_sort Rahman, Shah Md. Toufiqur
collection PubMed
description The extracellular signal-regulated kinase (ERK) signaling pathway plays prominent roles in cell growth, proliferation, and differentiation. ERK signaling is dynamic, involving phosphorylation/dephosphorylation, nucleocytoplasmic shuttling, and interactions with scores of protein substrates in the cytosol and in the nucleus. Live-cell fluorescence microscopy using genetically encoded ERK biosensors offers the potential to infer those dynamics in individual cells. In this study, we have monitored ERK signaling using four commonly used translocation- and Förster resonance energy transfer-based biosensors in a common cell stimulation context. Consistent with previous reports, we found that each biosensor responds with unique kinetics; it is clear that there is not a single dynamic signature characterizing the complexity of ERK phosphorylation, translocation, and kinase activity. In particular, the widely adopted ERK Kinase Translocation Reporter (ERKKTR) gives a readout that reflects ERK activity in both compartments. Mathematical modeling offers an interpretation of the measured ERKKTR kinetics, in relation to cytosolic and nuclear ERK activity, and suggests that biosensor-specific dynamics substantially influence the measured output.
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spelling pubmed-102080962023-07-20 On the inference of ERK signaling dynamics from protein biosensor measurements Rahman, Shah Md. Toufiqur Haugh, Jason M. Mol Biol Cell Articles The extracellular signal-regulated kinase (ERK) signaling pathway plays prominent roles in cell growth, proliferation, and differentiation. ERK signaling is dynamic, involving phosphorylation/dephosphorylation, nucleocytoplasmic shuttling, and interactions with scores of protein substrates in the cytosol and in the nucleus. Live-cell fluorescence microscopy using genetically encoded ERK biosensors offers the potential to infer those dynamics in individual cells. In this study, we have monitored ERK signaling using four commonly used translocation- and Förster resonance energy transfer-based biosensors in a common cell stimulation context. Consistent with previous reports, we found that each biosensor responds with unique kinetics; it is clear that there is not a single dynamic signature characterizing the complexity of ERK phosphorylation, translocation, and kinase activity. In particular, the widely adopted ERK Kinase Translocation Reporter (ERKKTR) gives a readout that reflects ERK activity in both compartments. Mathematical modeling offers an interpretation of the measured ERKKTR kinetics, in relation to cytosolic and nuclear ERK activity, and suggests that biosensor-specific dynamics substantially influence the measured output. The American Society for Cell Biology 2023-05-05 /pmc/articles/PMC10208096/ /pubmed/36884295 http://dx.doi.org/10.1091/mbc.E22-10-0476 Text en © 2023 Rahman and Haugh. “ASCB®,” “The American Society for Cell Biology®,” and “Molecular Biology of the Cell®” are registered trademarks of The American Society for Cell Biology. https://creativecommons.org/licenses/by-nc-sa/4.0/This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial-Share Alike 4.0 International Creative Commons License.
spellingShingle Articles
Rahman, Shah Md. Toufiqur
Haugh, Jason M.
On the inference of ERK signaling dynamics from protein biosensor measurements
title On the inference of ERK signaling dynamics from protein biosensor measurements
title_full On the inference of ERK signaling dynamics from protein biosensor measurements
title_fullStr On the inference of ERK signaling dynamics from protein biosensor measurements
title_full_unstemmed On the inference of ERK signaling dynamics from protein biosensor measurements
title_short On the inference of ERK signaling dynamics from protein biosensor measurements
title_sort on the inference of erk signaling dynamics from protein biosensor measurements
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208096/
https://www.ncbi.nlm.nih.gov/pubmed/36884295
http://dx.doi.org/10.1091/mbc.E22-10-0476
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