From plasmodesma geometry to effective symplasmic permeability through biophysical modelling
Abstract
Regulation of molecular transport via intercellular channels called plasmodesmata (PDs) is important for both coordinating developmental and environmental responses among neighbouring cells, and isolating (groups of) cells to execute distinct programs. Cell-to-cell mobility of fluorescent molecules and PD dimensions (measured from electron micrographs) are both used as methods to predict PD transport capacity (i.e., effective symplasmic permeability), but often yield very different values. Here, we build a theoretical bridge between both experimental approaches by calculating the effective symplasmic permeability from a geometrical description of individual PDs and considering the flow towards them. We find that a dilated central region has the strongest impact in thick cell walls and that clustering of PDs into pit fields strongly reduces predicted permeabilities. Moreover, our open source multi-level model allows to predict PD dimensions matching measured permeabilities and add a functional interpretation to structural differences observed between PDs in different cell walls.
Data availability
PDinsight can be downloaded from GitHub: https://github.com/eedeinum/PDinsight. Documentation on the use of PDinsight.py is included as an appendix to the manuscript with additional information at the head of the example parameter file. More extensive documentation is included with PDinsight on GitHub. PDinsight also has a citable DOI through Zenodo: 10.5281/zenodo.3536704. The PDinsight parameter files used for this manuscript are included as Source Code 1.
Article and author information
Author details
Funding
European Molecular Biology Organization (ASTF 105 - 2012)
- Eva E Deinum
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
- Bela M Mulder
Engineering and Physical Sciences Research Council (EF/M027740/1)
- Yoselin Benitez-Alfonso
Leverhulme Trust (RPG-2016-13)
- Yoselin Benitez-Alfonso
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Deinum et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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