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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....
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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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. |
format | Online Article Text |
id | pubmed-9308134 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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