Abstract

Intercellular electrical coupling is an essential means of communication between cells. It is important to obtain quantitative knowledge of such coupling between cardiomyocytes and non-excitable cells when, for example, pathological electrical coupling between myofibroblasts and cardiomyocytes yields increased arrhythmia risk or during the integration of donor (e.g., cardiac progenitor) cells with native cardiomyocytes in cell-therapy approaches. Currently, there is no direct method for assessing heterocellular coupling within multicellular tissue. Here we demonstrate experimentally and computationally a new contactless assay for electrical coupling, OptoGap, based on selective illumination of inexcitable cells that express optogenetic actuators and optical sensing of the response of coupled excitable cells (e.g., cardiomyocytes) that are light-insensitive. Cell–cell coupling is quantified by the energy required to elicit an action potential via junctional current from the light-stimulated cell(s). The proposed technique is experimentally validated against the standard indirect approach, GapFRAP, using light-sensitive cardiac fibroblasts and non-transformed cardiomyocytes in a two-dimensional setting. Its potential applicability to the complex three-dimensional setting of the native heart is corroborated by computational modelling and proper calibration. Lastly, the sensitivity of OptoGap to intrinsic cell-scale excitability is robustly characterized via computational analysis.

Details

Title
OptoGap is an optogenetics-enabled assay for quantification of cell–cell coupling in multicellular cardiac tissue
Author
Boyle, Patrick M 1 ; Yu, Jinzhu 2 ; Klimas Aleksandra 3 ; Williams, John C 2 ; Trayanova, Natalia A 4 ; Entcheva Emilia 3 

 Johns Hopkins University, Department of Biomedical Engineering, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311); Johns Hopkins University, Institute for Computational Medicine, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311); University of Washington, Department of Bioengineering, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657); University of Washington, Institute for Stem Cell and Regenerative Medicine, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657); University of Washington, Center for Cardiovascular Biology, Seattle, USA (GRID:grid.34477.33) (ISNI:0000000122986657) 
 Stony Brook University, Department of Biomedical Engineering, Stony Brook, USA (GRID:grid.36425.36) (ISNI:0000 0001 2216 9681) 
 Stony Brook University, Department of Biomedical Engineering, Stony Brook, USA (GRID:grid.36425.36) (ISNI:0000 0001 2216 9681); George Washington University, Department of Biomedical Engineering, Washington, USA (GRID:grid.253615.6) (ISNI:0000 0004 1936 9510) 
 Johns Hopkins University, Department of Biomedical Engineering, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311); Johns Hopkins University, Institute for Computational Medicine, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311); Johns Hopkins University, Alliance for Cardiovascular Diagnostic and Treatment Innovation, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2519561614
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.