Sensing and control with nucleic acid hybrid nanoactuators

In the previous funding phase, we worked on the control of dynamic molecular processes using DNA or RNA-based nanoscaffolds. Different types of DNA and RNA nanostructures were used to arrange enzymes, proteins, nanoparticles or functional nucleic acid molecules into close proximity in order to elicit or enhance catalytic, sensor, or computational functions. Technologically, the greatest advance was made in the context of a so-called “DNA robot arm”, which we had re-designed to enable robust mechanical behavior and high yield production. We further succeeded to employ electrical fields to manipulate the roboarm, which allowed for fast and precise control of its motion.

In order to further improve the switching characteristics of the roboarm system, in the current funding phase we will investigate the physics of the actuation process in greater detail. This involves the variation of the size and shape of the roboarm, optimization of buffer conditions, and the investigation of undesired, non-specific interactions of movable parts with each other and with the substrate. In collaboration with Gerland (A03), we will address the question how the electrical field couples to and exerts force on the combined DNA roboarm-counterion system. We further aim to explore other actuation mechanisms such as light-induced switching (via photoswitches or nanoparticle manipulation – cf. Lohmüller, A08), and we will attempt roboarm movement in three spatial dimensions. Readout of roboarm motion will be further improved in collaboration with Lamb (B03, 3D tracking) and Jungmann (A11, DNA-PAINT, barcoding), and also dark-field microscopy with nanoparticle-labeled structures (A08, Lohmüller). Based on the fastest available readout scheme, we will then attempt to realize active feedback control of roboarm motion. Apart from applications in single-molecule biosensing, we will explore fundamental questions related to the assembly of large arrays of roboarms and interactions within these arrays. Here we aim to employ concepts from algorithmic self-assembly to generate arrays, which are modified with different types of roboarms that may respond differently to external stimuli or sensory inputs. Furthermore, we will develop arrays, in which neighboring arms can physically interact and thus cooperatively create array-wide superstructures (e.g. all arms oriented in the same direction), which could be useful as a novel sensor scheme. This could potentially be also applied for cellular automaton-like computation within the arrays, which we will explore in collaboration with the Gerland group (A03). Next to the roboarm work, we will continue to develop RNA origami scaffold structures, which can be produced via in vitro or in vivo gene expression. In collaboration with the Braun (A04) and Schneider (A12) groups, we will use these scaffolds for the generation of evolvable molecular structures and in vivo sensors.