Boundary-Sensing Mechanism in Branched Microtubule Networks

Abstract The self-organization of cytoskeletal networks in confined geometries requires sensing and responding to mechanical cues at nanometer to micron scales that allow for dynamic adaptation. Here, we show that the branching of microtubules (MTs) via branching MT nucleation combined with dynamic instability constitutes a boundary-sensing mechanism within confined spaces. Using a nanotechnology platform, we observe the self-organization of a branched MT network in a channel featuring a narrow junction and a closed end. Our observations reveal that branching MT nucleation occurs in the post-narrowing region only if that region exceeds a certain length before it terminates at the channel’s closed end. The length-dependent occurrence of branching MT nucleation arises from the dynamic instability of existing MTs when they interact with the channel’s closed end, combined with the specific timescale required for new MTs to nucleate at a point distant from the closed end, creating a mechanical feedback. Increasing the concentration of the base branching factor TPX2 accelerates nucleation kinetics and thus tunes the minimum length scale needed for occurrence of branching MT nucleation. As such, this feedback not only allows for adaptation to the local geometry, but also allows for tunable formation of MT networks in narrow (micron and submicron scale) channels. However, while a high concentration of TPX2 increases the kinetic rate of branching MT nucleation, it also stabilizes MTs at the channel’s closed end leading to MT growth and nucleation in the reversed direction, and thus hinders boundary sensing. After experimental characterization of boundary-sensing feedback, we propose a minimal model and execute numerical simulations. We investigate how this feedback, wherein growing MTs dynamically sense their physical environment and provide nucleation sites for new MTs, sets a length/time scale that steers the architecture of MT networks in confined spaces. This “search- and-branch” mechanism has implications for the formation of MT networks during neuronal morphogenesis, including axonal growth and the formation of highly branched dendritic networks, as well as for plant development and MT-driven guidance in fungi, and engineering nanotechnologies.