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Plasmodesmata

Plasmodesmata

The organs in a multicellular organism’s body are made up of tissues formed by cells. To work together cohesively, cells must communicate. One way that cells communicate is through direct contact with other cells. The points of contact that connect adjacent cells are called intercellular junctions.

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Related Experiment Video

Updated: Sep 28, 2025

Author Spotlight: Microscopic Analysis of Protein Localization at Plasmodesmata in Plants

Author Spotlight: Microscopic Analysis of Protein Localization at Plasmodesmata in Plants

Published on: November 1, 2024

More Insights from Ultrastructural and Functional Plasmodesmata Data Using PDinsight.

¹Wageningen University, Wageningen, The Netherlands. eva.deinum@wur.nl.

Methods in Molecular Biology (Clifton, N.J.)

|March 29, 2022

Summary

This summary is machine-generated.

PDinsight is a Python tool calculating plant cell wall permeability for symplasmic transport using plasmodesma (PD) data. It offers direct computation and explorative analysis for research questions, aiding in diffusion coefficient and particle size selection.

Keywords:

Effective wall permeability Modeling plasmodesmata Plasmodesmata geometries Symplasmic transport predictions

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Last Updated: Sep 28, 2025

Author Spotlight: Microscopic Analysis of Protein Localization at Plasmodesmata in Plants

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Published on: November 1, 2024

Identification of Plasmodesmal Localization Sequences in Proteins In Planta

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Published on: December 27, 2024

Area of Science:

Plant biology
Cell biology
Biophysics

Background:

Symplasmic transport is crucial for plant development and signaling.
Accurate estimation of effective wall permeability is essential for understanding this transport.
Plasmodesmata (PD) are key regulators of symplasmic connectivity.

Purpose of the Study:

Introduce PDinsight, a Python-based computational tool.
Facilitate the calculation of effective wall permeability for symplasmic transport.
Provide a flexible tool for both direct computation and explorative data analysis.

Main Methods:

Utilizes plasmodesma (PD) size and distribution data.
Implements a computational model for permeability calculations.
Offers distinct modes for complete or incomplete/unreliable data.

Main Results:

PDinsight enables direct computation of effective wall permeability.
The tool supports explorative analysis when data is limited or uncertain.
Guidance is provided on selecting diffusion coefficients and particle sizes for experimental probes.

Conclusions:

PDinsight is a valuable tool for researchers studying symplasmic transport.
The software enhances the ability to investigate PD-mediated transport dynamics.
It supports diverse research scenarios, from direct measurement to data-driven exploration.