Physical scaling of size and shape in an early diverging animal

In most animals, identified as self-organizing multicellular clonal clusters with complex tissue architectures, size control is strictly encoded as a part of the developmental program. These mechanisms however evolved to work in concert with material and environmental physical constraints, thus resulting in apparent scaling laws comparing size and measurable features of form across organisms. Using an early diverging animal with highly regenerative tissue architecture, we ask how size and shape of the earliest freely growing multicellular clusters would have been regulated in the absence of strictly encoded plans. We utilize high-throughput scanning microscopy to collect long term temporal datasets on the growth trajectories of individual organisms to identify scaling laws governing measurable changes in shape metrics with size. We then utilize physical and chemical perturbations to understand robustness of these trajectories and find attractors in shape spaces. Finally, using computational modelling of self-organized growth of discrete networks, we provide theoretical insights into the observed laws and open up space for exploration of further complexity.