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Computational framework for single-cell spatiotemporal dynamics of optogenetic membrane recruitment

We describe a modular computational framework for analyzing cell-wide spatiotemporal signaling dynamics in single-cell microscopy experiments that accounts for the experiment-specific geometric and diffractive complexities that arise from heterogeneous cell morphologies and optical instrumentation....

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Detalles Bibliográficos
Autores principales: Kuznetsov, Ivan A., Berlew, Erin E., Glantz, Spencer T., Hannanta-Anan, Pimkhuan, Chow, Brian Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308134/
https://www.ncbi.nlm.nih.gov/pubmed/35880018
http://dx.doi.org/10.1016/j.crmeth.2022.100245
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author Kuznetsov, Ivan A.
Berlew, Erin E.
Glantz, Spencer T.
Hannanta-Anan, Pimkhuan
Chow, Brian Y.
author_facet Kuznetsov, Ivan A.
Berlew, Erin E.
Glantz, Spencer T.
Hannanta-Anan, Pimkhuan
Chow, Brian Y.
author_sort Kuznetsov, Ivan A.
collection PubMed
description We describe a modular computational framework for analyzing cell-wide spatiotemporal signaling dynamics in single-cell microscopy experiments that accounts for the experiment-specific geometric and diffractive complexities that arise from heterogeneous cell morphologies and optical instrumentation. Inputs are unique cell geometries and protein concentrations derived from confocal stacks and spatiotemporally varying environmental stimuli. After simulating the system with a model of choice, the output is convolved with the microscope point-spread function for direct comparison with the observable image. We experimentally validate this approach in single cells with BcLOV4, an optogenetic membrane recruitment system for versatile control over cell signaling, using a three-dimensional non-linear finite element model with all parameters experimentally derived. The simulations recapitulate observed subcellular and cell-to-cell variability in BcLOV4 signaling, allowing for inter-experimental differences of cellular and instrumentation origins to be elucidated and resolved for improved interpretive robustness. This single-cell approach will enhance optogenetics and spatiotemporally resolved signaling studies.
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spelling pubmed-93081342022-07-24 Computational framework for single-cell spatiotemporal dynamics of optogenetic membrane recruitment Kuznetsov, Ivan A. Berlew, Erin E. Glantz, Spencer T. Hannanta-Anan, Pimkhuan Chow, Brian Y. Cell Rep Methods Article We describe a modular computational framework for analyzing cell-wide spatiotemporal signaling dynamics in single-cell microscopy experiments that accounts for the experiment-specific geometric and diffractive complexities that arise from heterogeneous cell morphologies and optical instrumentation. Inputs are unique cell geometries and protein concentrations derived from confocal stacks and spatiotemporally varying environmental stimuli. After simulating the system with a model of choice, the output is convolved with the microscope point-spread function for direct comparison with the observable image. We experimentally validate this approach in single cells with BcLOV4, an optogenetic membrane recruitment system for versatile control over cell signaling, using a three-dimensional non-linear finite element model with all parameters experimentally derived. The simulations recapitulate observed subcellular and cell-to-cell variability in BcLOV4 signaling, allowing for inter-experimental differences of cellular and instrumentation origins to be elucidated and resolved for improved interpretive robustness. This single-cell approach will enhance optogenetics and spatiotemporally resolved signaling studies. Elsevier 2022-07-06 /pmc/articles/PMC9308134/ /pubmed/35880018 http://dx.doi.org/10.1016/j.crmeth.2022.100245 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kuznetsov, Ivan A.
Berlew, Erin E.
Glantz, Spencer T.
Hannanta-Anan, Pimkhuan
Chow, Brian Y.
Computational framework for single-cell spatiotemporal dynamics of optogenetic membrane recruitment
title Computational framework for single-cell spatiotemporal dynamics of optogenetic membrane recruitment
title_full Computational framework for single-cell spatiotemporal dynamics of optogenetic membrane recruitment
title_fullStr Computational framework for single-cell spatiotemporal dynamics of optogenetic membrane recruitment
title_full_unstemmed Computational framework for single-cell spatiotemporal dynamics of optogenetic membrane recruitment
title_short Computational framework for single-cell spatiotemporal dynamics of optogenetic membrane recruitment
title_sort computational framework for single-cell spatiotemporal dynamics of optogenetic membrane recruitment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308134/
https://www.ncbi.nlm.nih.gov/pubmed/35880018
http://dx.doi.org/10.1016/j.crmeth.2022.100245
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