Biology subjects

Agam, O.

Publications and source records attributed to Agam, O..

3 recordsLinked to original sources

bioRxiv2025

The Dual Nature of Body-Axis Formation in Hydra Regeneration: Polarity-Morphology Concurrency

The formation of a body-axis is central to animal development and involves both polarity and morphology. While polarity is traditionally associated with biochemical patterning, the morphological aspect of axis formation remains elusive. In regenerating Hydra tissues, we find that morphological evolution in all tissue samples depends on inherited positional information from the donors axis, and a foot precursor emerges early in the process. From the onset of regeneration, the Ca{superscript 2} excitations that drive actomyosin forces for tissue reshaping follow a gradient aligned with the head-foot polarity direction. We conclude that polarity and morphological axis progression occur concurrently through interlinked processes, and that the foot plays a dominant role in this process, a role usually attributed to the head organizer. A simple toy model accounts for the observed regeneration dynamics and illustrates the mechanochemical integration of polarity and morphogenesis. We expect the insights from Hydra to be relevant to broader developmental systems.

biophysics↗

bioRxiv2024

Fluctuation-Driven Morphological Patterning: A Novel Approach to Morphogenesis

Recent experimental investigations into Hydra regeneration revealed a remarkable phenomenon: the morphological transformation of a tissue fragment from the incipient spherical configuration to a tube-like structure - the hallmark of a mature Hydra - has the dynamical characteristics of a first-order phase-transition, with calcium field fluctuations within the tissue playing an essential role. This morphological transition was shown to be generated by activation over an energy barrier within an effective potential that underlies morphogenesis. Inspired by this intriguing insight, we propose a novel mechanism where stochastic fluctuations drive the emergence of morphological patterns. Thus, the inherent fluctuations determine the nature of the dynamics and are not incidental noise in the background of the otherwise deterministic dynamics. Instead, they play an important role as a driving force that defines the attributes of the pattern formation dynamics and the nature of the transition itself. Here, we present a simple model that captures the essence of this novel mechanism for morphological pattern formation. Specifically, we consider a one-dimensional tissue arranged as a closed contour embedded in a two-dimensional space, where the local curvature of the contour is coupled to a non-negative scalar field. An effective temperature parameter regulates the strength of the fluctuations in the system. The tissue exhibits fluctuations near a circular shape at sufficiently low coupling strengths, but as the coupling strength exceeds some critical value, the circular state becomes unstable. The nature of the transition to the new state, namely whether it is a first-order-like or a second-order-like transition, depends on the temperature and the effective cutoff on the wavelength of the spatial variations in the system. It is also found that entropic barriers separate the various metastable states of the system.

biophysics↗

bioRxiv2023

Hydra morphogenesis as phase-transition dynamics

We utilize whole-body Hydra regeneration from a small tissue segment to develop a physics framework for animal morphogenesis. Introducing experimental controls over this process, an external electric field and a drug that blocks gap junctions, allows us to characterize the essential step in the morphological transition - from a spherical shape to an elongated spheroid. We find that spatial fluctuations of the Ca2+ distribution in the Hydras tissue drive this transition and construct a field-theoretic model that explains the morphological transition as a first-order-like phase transition resulting from the coupling of the Ca2+ field and the tissues local curvature. Various predictions of this model are verified experimentally.

biophysics↗