Self-organization drives symmetry-breaking, scaling, and critical growth transitions in stem cell-derived organoids

TL;DR

This study reveals how self-organized mechanisms in stem cell-derived organoids lead to size-dependent symmetry-breaking, scaling laws, and critical growth transitions, providing a minimal model for tissue pattern formation.

Contribution

It introduces a combined experimental and theoretical framework demonstrating size-dependent patterning and growth dynamics in organoids, highlighting the role of self-organization and boundary feedback.

Findings

Small colonies spontaneously break symmetry while larger ones remain symmetric.

Mesodermal domain area scales with colony size following a power law.

Growth dynamics exhibit a biphasic pattern with a critical transition.

Abstract

The emergence of spatial patterns and organized growth is a hallmark of developing tissues. While symmetry-breaking and scaling laws govern these processes, how cells coordinate spatial patterning with size regulation remains unclear. Here, we combine quantitative imaging, a Turing activator-repressor model with self-organized reactive boundaries, and in vitro models of early mouse development to study mesodermal pattern formation in two-dimensional (2D) gastruloids. We show that colony size dictates symmetry: small colonies (radius approximately 100 micrometers) spontaneously break symmetry, while larger ones remain centro-symmetric, consistent with size-dependent positional information and model predictions. The mesodermal domain area scales robustly with colony size following a power law, independent of cell density, indicating that cells sense and respond to gastruloid size. Time-lapse imaging reveals a biphasic growth law: an early power-law expansion followed by exponential arrest, marking a dynamical phase transition. These dynamics, conserved across sizes, reflect features of criticality seen in physical systems, where self-organization, scaling, and boundary feedback converge. Our findings uncover a minimal mechanism for size-dependent pattern formation and growth control. This framework enables quantitative investigation of symmetry-breaking and scaling in self-organizing tissues, offering insights into the physical principles underlying multicellular organization.