Biophysical modeling and experimental analysis of the dynamics of C. elegans body-wall muscle cells

This study combines experimental techniques and mathematical modeling to investigate the dynamics of C. elegans body-wall muscle cells. Specifically, by conducting voltage clamp and mutant experiments, we identify key ion channels, particularly the L-type voltage-gated calcium channel (EGL-19) and potassium channels (SHK-1, SLO-2), which are crucial for generating action potentials. We develop Hodgkin-Huxley-based models for these channels and integrate them to capture the cells' electrical activity. To ensure the model accurately reflects cellular responses under depolarizing currents, we develop a parallel simulation-based inference method for determining the model's free parameters. This method performs rapid parallel sampling across high-dimensional parameter spaces, fitting the model to the responses of muscle cells to specific stimuli and yielding accurate parameter estimates. We validate our model by comparing its predictions against cellular responses to various current stimuli in experiments and show that our approach effectively determines suitable parameters for accurately modeling the dynamics in mutant cases. Additionally, we discover an optimal response frequency in body-wall muscle cells, which corresponds to a burst firing mode rather than regular firing mode. Our work provides the first experimentally constrained and biophysically detailed muscle cell model of C. elegans, and our analytical framework combined with robust and efficient parametric estimation method can be extended to model construction in other species.

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Publication Details

Journal
PLoS Computational Biology
Published
2025-01-27
DOI
https://doi.org/10.1371/journal.pcbi.1012318
Citations
2
Primary Topic
Genetics, Aging, and Longevity in Model Organisms
Type
article
Field-Weighted Citation Impact
1.91

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article

Biophysical modeling and experimental analysis of the dynamics of C. elegans body-wall muscle cells

Shangbang Gao, Victor J. Barranca, Douglas Zhou, Songting Li et al.
2 citations
PLoS Computational Biology
Genetics, Aging, and Longevity in Model Organisms
1.91
article

Biophysical modeling and experimental analysis of the dynamics of C. elegans body-wall muscle cells

Shangbang Gao, Victor J. Barranca, Douglas Zhou, Songting Li, Jennifer Crodelle, Y X Shi, Xuexing Du
article en
2 citations

Abstract

This study combines experimental techniques and mathematical modeling to investigate the dynamics of C. elegans body-wall muscle cells. Specifically, by conducting voltage clamp and mutant experiments, we identify key ion channels, particularly the L-type voltage-gated calcium channel (EGL-19) and potassium channels (SHK-1, SLO-2), which are crucial for generating action potentials. We develop Hodgkin-Huxley-based models for these channels and integrate them to capture the cells' electrical activity. To ensure the model accurately reflects cellular responses under depolarizing currents, we develop a parallel simulation-based inference method for determining the model's free parameters. This method performs rapid parallel sampling across high-dimensional parameter spaces, fitting the model to the responses of muscle cells to specific stimuli and yielding accurate parameter estimates. We validate our model by comparing its predictions against cellular responses to various current stimuli in experiments and show that our approach effectively determines suitable parameters for accurately modeling the dynamics in mutant cases. Additionally, we discover an optimal response frequency in body-wall muscle cells, which corresponds to a burst firing mode rather than regular firing mode. Our work provides the first experimentally constrained and biophysically detailed muscle cell model of C. elegans, and our analytical framework combined with robust and efficient parametric estimation method can be extended to model construction in other species.

PLoS Computational BiologyVol. 21(1)
Swarthmore College (US), Shanghai Jiao Tong University (CN), Middlebury College (US), Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality, Shanghai Jiao Tong University, National Key Research and Development Program of China
Life in Land
Openalex Percentile: Top 18%
Genetics, Aging, and Longevity in Model Organisms
1.91
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