From active matter to embryoid self-organization

Thesis

How do collectively organized multi-cellular life forms emerge from seemingly homogeneous groups of cells? A physical theory of development has remained elusive due to the complexity of multiscale population dynamics, wherein multiple tissues continuously remodel cell-cell interfaces throughout fate specification, division, death, and migration. Rather than focusing on mechanical signatures within individual lineages or cell types, this thesis posits that macroscopic patterning is encoded in progenitor cells, motivating a statistical physics description of germ layer tissue formation.

By combining experimental data analysis with a minimal active matter model and applying methods from non-equilibrium statistical mechanics to embryology, this work redefines a longstanding biomedical problem. Experimental stochastic nuclear trajectories are first ensemble-averaged and conditioned on precursor and differentiated cell fates, revealing distinct growth phases and diffusive regimes associated with tissue identity. These experimentally derived statistical observables are then used to inform a data-driven theoretical framework in which embryonic cleavage is modeled in silico using a Reductional Division Model (RDM), treating the embryo as a proliferation-driven non-equilibrium system characterized by finite lifetimes, generational dependence, changing number density, volume conservation, and confinement, thereby defining a new class of isovolumetric active matter.

Numerical solutions combined with data analysis identify key physical ingredients required for tissue self-organization. In simulation, the RDM incorporates generational inheritance of tissue-specific cell cycle distributions and adhesion strengths reproduces key emergent behaviours observed experimentally, including anomalous diffusive oscillations, (a)synchronous growth rates, and phase-separated boundaries between tissues. These results indicate that stable embryonic configurations arise from a continuous balance between energy injection through proliferation and dissipation via steric relaxation. This interplay links mechanical transitions at tissue boundaries to cell fate dynamics, providing a statistical physics framework for understanding spatio-temporally driven pattern formation during development.

Authors: Lish, SR

• DOI: 10.5287/ora-1apjddoa5
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: proliferating active matter; data-driven theory; non-equilibrium statistical physics; tissue morphogenesis; embryoid self-organization
• Subjects: theoretical biophysics; Embryology; biomedical sciences; active matter