Self-assembly of biological networks via adaptive patterning revealed by avian intradermal muscle network formation

Abstract

Networked structures integrate numerous elements into one functional unit, while providing a balance between efficiency, robustness, and flexibility. Understanding how biological networks self-assemble will provide insights into how these features arise. Here, we demonstrate how nature forms exquisite muscle networks that can repair, regenerate, and adapt to external perturbations using the feather muscle network in chicken embryos as a paradigm. The self-assembled muscle networks arise through the implementation of a few simple rules. Muscle fibers extend outward from feather buds in every direction, but only those muscle fibers able to connect to neighboring buds are eventually stabilized. After forming such a nearest-neighbor configuration, the network can be reconfigured, adapting to perturbed bud arrangement or mechanical cues. Our computational model provides a bioinspired algorithm for network self-assembly, with intrinsic or extrinsic cues necessary and sufficient to guide the formation of these regenerative networks. These robust principles may serve as a useful guide for assembling adaptive networks in other contexts.