Self-forming biological scaffolding | Kurzweil AI

bio_scaffoldingA new model system of the cytoskeleton (cellular skeleton) of living cells is akin to a mini-laboratory designed to explore how the cells’ functional structures assemble.

Physicist Volker Schaller and his colleagues from Technical University in Munich, Germany, presents one hypothesis concerning self-organization. It hinges on the finding that a homogeneous protein network, once subjected to stresses generated by molecular motors, compacts into highly condensed fibers.

The contractile machinery inside cells is arguably the most prominent example of cells’ ability to self-organize cellular proteins into highly ordered functional structures involved in cell division or cell migration, for example.

The researchers are attempting to elucidate how such highly self-organized structures emerge from a less ordered and homogeneous collection of constituent proteins called actin filaments — one of the main scaffold proteins in cells made of biopolymers — and associated molecular motors. The latter exerts forces by pressing along the filament, an energy consuming process.

Schaller and colleagues developed a minimal model system of the cellular skeleton, consisting of actin filaments held together by cross-linking proteins and molecular motors. They found that this minimal system is sufficient to reproduce similar self-organization processes observed in nature.

In particular, they showed that a homogeneous network of actin filaments held together by the cross-linking protein α-actinin can rapidly be reorganized by molecular motor proteins. It contracts to form a highly heterogeneous set of compact fibres consisting of millions of individual filaments, resembling scaffold structures inside the cellular skeleton.

The authors also realized that the efficiency of this reorganization process, and therefore the length scale of the fibers created, directly depend on motor activity. The fibers can range between 5μm and up to 100μm in length for low and high motor activity, respectively.


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