henhaobio
Sign in

bioRxivBiophysicsPreprint

Space partitioning by self-organized epithelial networks

Ronny Tonato ZambranoiD, Ayla Biallas, Frédérique MittleriD, Alice NicolasiD, Xavier GidroliD, Sophie AchardiD, Lionel HervéiD, Guillaume GodefroyiD, Maxim Y. BalakireviD

PDFDOI

Abstract

Branching epithelia build supracellular networks that must simultaneously ensure connectivity, mechanical integrity, and efficient space partitioning, yet a general framework for how such networks form beyond the endothelial lineage has been lacking. Here we show that epithelial cells from multiple branching organs spontaneously self-organize into extended reticulate networks in simplified environments, revealing a conserved network-forming capacity. Combining wide-field lensless holographic imaging, deep-learning segmentation (EpiNet), and graph-theoretic analysis, we resolve a reproducible assembly sequence - contact initiation, clustering, percolation, and post-percolation relaxation - and quantify its geometry across scales. Actomyosin contractility controls both the growth of connectivity and the relaxation dynamics that set network geometry, tuning the effective cost of forming connections and thereby selecting between tree-like and reticulate topologies. After percolation, epithelial networks behave as active tension networks that progressively refine space partitioning toward centroidal, near-optimal configurations while maintaining a characteristic mesh size through continuous edge nucleation. These findings establish epithelial network formation as a generic, physically regulated mode of tissue self-organization and provide a quantitative framework linking single-cell mechanics, network topology, and space-partitioning dynamics, with implications for branching morphogenesis, organoid models, and tissue engineering.

Citations
0

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISBarai '25Rennert '23Marpeaux '26Ouyang '20Sharma '21Scott '24
66% semantic matchCell Biology
Amlan Barai, Matis Soleilhac, Wang Xi+11 more·Nature Communications·Jul 4, 2025· 17 citations