Condensed Matter Theory

Abstract:

Rotary motors play key roles in energy transduction, from macroscale windmills to nanoscale turbines such as ATP synthase in cells. Despite our abilities to construct engines at many scales, developing functional synthetic turbines at the nanoscale has remained challenging. Here, we experimentally demonstrate rationally designed nanoscale DNA origami turbines with three chiral blades. These DNA nanoturbines are 24-27 nm in height and diameter and can utilize transmembrane electrochemical potentials across nanopores to drive DNA bundles into sustained unidirectional rotations of up to 10 revolutions s^-1. The rotation direction is set by the designed chirality of the turbine. All-atom molecular dynamics simulations show how hydrodynamic flows drive this turbine. At high salt concentrations, the rotation direction of turbines with the same chirality is reversed, which is explained by a change in the anisotropy of the electrophoretic mobility. Our artificial turbines operate autonomously in physiological conditions, converting energy from naturally abundant electrochemical potentials into mechanical work. The results open new possibilities for engineering active robotics at the nanoscale.

Abstract:

Biomorphs, Richard Dawkins's iconic model of morphological evolution, are traditionally used to demonstrate the power of natural selection to generate biological order from random mutations. Here we show that biomorphs can also be used to illustrate how developmental bias shapes adaptive evolutionary outcomes. In particular, we find that biomorphs exhibit phenotype bias, a type of developmental bias where certain phenotypes can be many orders of magnitude more likely than others to appear through random mutations. Moreover, this bias exhibits a strong preference for simpler phenotypes with low descriptional complexity. Such bias towards simplicity is formalised by an information-theoretic principle that can be intuitively understood from a picture of evolution randomly searching in the space of algorithms. By using population genetics simulations, we demonstrate how moderately adaptive phenotypic variation that appears more frequently upon random mutations can fix at the expense of more highly adaptive biomorph phenotypes that are less frequent. This result, as well as many other patterns found in the structure of variation for the biomorphs, such as high mutational robustness and a positive correlation between phenotype evolvability and robustness, closely resemble findings in molecular genotype-phenotype maps. Many of these patterns can be explained with an analytic model based on constrained and unconstrained sections of the genome. We postulate that the phenotype bias towards simplicity and other patterns biomorphs share with molecular genotype-phenotype maps may hold more widely for developmental systems.