US researchers are developing self-organising nanostructures that can initiate wave-like motions such as those observed among the tiny hairs of the lungs.
In the body, these cilia act to clear microscopic debris from the lungs and determine the correct location of organs during development. Their beating motions are synchronised to produce metachronal waves.
Due to the importance of ciliary functions for health, there is great interest in understanding the mechanism that controls the cilias’ beating patterns. But learning exactly how cilia movement is coordinated has been challenging: each cilium contains more than 600 different proteins.
‘We’ve shown that there is a new approach toward studying the beating,’ said project lead Prof Zvonimir Dogic of Brandeis University. ‘Instead of deconstructing the fully functioning structure, we can start building complexity from the ground up.’
The experimental system was comprised of three main components: microtubule filaments — tiny hollow cylinders found in both animal and plant cells; motor proteins called kinesin, which consume chemical fuel to move along microtubules; and a bundling agent that induces assembly of filaments into bundles
The researchers found that under a particular set of conditions these very simple components spontaneously organise into active bundles that beat in a periodic manner.
In addition to observing the beating of isolated bundles, the researchers were also able to assemble a dense field of bundles that spontaneously synchronised their beating patterns into travelling waves.
Self-organising processes of many kinds have recently become a focus of the physics community. These processes range in scale from microscopic cellular functions and swarms of bacteria to macroscopic phenomena such as flocking of birds and traffic jams. Since controllable experiments with birds, crowds at football stadiums and traffic are virtually impossible to conduct, the experiments described by Sanchez and colleagues could serve as a model for testing a broad range of theoretical predictions.