Guided Assembly and Patterning of Intrinsically Fluorescent Amyloid Fibers with Long-Range Order.

Fibrillar amyloids exhibit a fascinating range of mechanical, optical, and electronic properties originating from their characteristic ß-sheet-rich structure. Harnessing these functionalities in practical applications has so far been hampered by a limited ability to control the amyloid self-assembly process at the macroscopic scale. Here, we use core-shell electrospinning with microconfinement to assemble amyloid-hybrid fibers, consisting of densely aggregated fibrillar amyloids stabilized by a polymer shell. Up to centimeter-long hybrid fibers with micrometer diameter can be arranged into aligned and ordered arrays and deposited onto substrates or produced as free-standing networks. Properties that are characteristic of amyloids, including their high elastic moduli and intrinsic fluorescence signature, are retained in the hybrid fiber cores, and we show that they fully persist through the macroscopic fiber patterns. Our findings suggest that microlevel confinement is key for the guided assembly of amyloids from monomeric proteins.

Optical Voltage Sensing Using DNA Origami.

We explore the potential of DNA nanotechnology for developing novel optical voltage sensing nanodevices that convert a local change of electric potential into optical signals. As a proof-of-concept of the sensing mechanism, we assembled voltage responsive DNA origami structures labeled with a single pair of FRET dyes. The DNA structures were reversibly immobilized on a nanocapillary tip and underwent controlled structural changes upon application of an electric field. The applied field was monitored through a change in FRET efficiency. By exchanging the position of a single dye, we could tune the voltage sensitivity of our DNA origami structure, demonstrating the flexibility and versatility of our approach. The experimental studies were complemented by coarse-grained simulations that characterized voltage-dependent elastic deformation of the DNA nanostructures and the associated change in the distance between the FRET pair. Our work opens a novel pathway for determining the mechanical properties of DNA origami structures and highlights potential applications of dynamic DNA nanostructures as voltage sensors.

Programming Light-Harvesting Efficiency Using DNA Origami.

The remarkable performance and quantum efficiency of biological light-harvesting complexes has prompted a multidisciplinary interest in engineering biologically inspired antenna systems as a possible route to novel solar cell technologies. Key to the effectiveness of biological "nanomachines" in light capture and energy transport is their highly ordered nanoscale architecture of photoactive molecules. Recently, DNA origami has emerged as a powerful tool for organizing multiple chromophores with base-pair accuracy and full geometric freedom. Here, we present a programmable antenna array on a DNA origami platform that enables the implementation of rationally designed antenna structures. We systematically analyze the light-harvesting efficiency with respect to number of donors and interdye distances of a ring-like antenna using ensemble and single-molecule fluorescence spectroscopy and detailed Förster modeling. This comprehensive study demonstrates exquisite and reliable structural control over multichromophoric geometries and points to DNA origami as highly versatile platform for testing design concepts in artificial light-harvesting networks.

Machine learning assisted interferometric structured illumination microscopy for dynamic biological imaging.

Structured Illumination Microscopy, SIM, is one of the most powerful optical imaging methods available to visualize biological environments at subcellular resolution. Its limitations stem from a difficulty of imaging in multiple color channels at once, which reduces imaging speed. Furthermore, there is substantial experimental complexity in setting up SIM systems, preventing a widespread adoption. Here, we present Machine-learning Assisted, Interferometric Structured Illumination Microscopy, MAI-SIM, as an easy-to-implement method for live cell super-resolution imaging at high speed and in multiple colors. The instrument is based on an interferometer design in which illumination patterns are generated, rotated, and stepped in phase through movement of a single galvanometric mirror element. The design is robust, flexible, and works for all wavelengths. We complement the unique properties of the microscope with an open source machine-learning toolbox that permits real-time reconstructions to be performed, providing instant visualization of super-resolved images from live biological samples.