We combine DNA origami structures with glass nanocapillaries to reversibly form hybrid DNA origami nanopores. Trapping of the DNA origami onto the nanocapillary is proven by imaging fluorescently labeled DNA origami structures and simultaneous ionic current measurements of the trapping events. We then show two applications highlighting the versatility of these DNA origami nanopores. First, by tuning the pore size we can control the folding of dsDNA molecules ("physical control"). Second, we show that the specific introduction of binding sites in the DNA origami nanopore allows selective detection of ssDNA as a function of the DNA sequence ("chemical control").

We show DNA origami nanopores that respond to high voltages by a change in conformation on glass nanocapillaries. Our DNA origami nanopores are voltage sensitive as two distinct states are found as a function of the applied voltage. We suggest that the origin of these states is a mechanical distortion of the DNA origami. A simple model predicts the voltage dependence of the structural change. We show that our responsive DNA origami nanopores can be used to lower the frequency of DNA translocation by 1 order of magnitude.

We present here the measurement of the diffusivity of spherical particles closely confined by narrow microchannels. Our experiments yield a two-dimensional map of the position-dependent diffusion coefficients parallel and perpendicular to the channel axis with a resolution down to 129 nm. The diffusivity was measured simultaneously in the channel interior, the bulk reservoirs, as well as the channel entrance region. In the channel interior we found strongly anisotropic diffusion. While the perpendicular diffusion coefficient close to the confining walls decreased down to approximately 25% of the value on the channel axis, the parallel diffusion coefficient remained constant throughout the entire channel width. In addition to the experiment, we performed finite element simulations for the diffusivity in the channel interior and found good agreement with the measurements. Our results reveal the distinctive influence of strong confinement on Brownian motion, which is of significance to microfluidics as well as quantitative models of facilitated membrane transport.

Nonlinear field dependence of electrophoresis in high fields has been investigated theoretically, yet experimental studies have failed to reach consensus on the effect. In this work, we present a systematic study on the nonlinear electrophoresis of highly charged submicron particles in applied electric fields of up to several kV/cm. First, the particles are characterized in the low-field regime at different salt concentrations and the surface charge density is estimated. Subsequently, we use microfluidic channels and video tracking to systematically characterize the nonlinear response over a range of field strengths. Using velocity measurements on the single particle level, we prove that nonlinear effects are present at electric fields and surface charge densities that are accessible in practical conditions. Finally, we show that nonlinear behavior leads to unexpected particle trapping in channels. :1907.04278v1 [cond-mat.soft] arXiv

Nanopore sensing is a versatile technique for the analysis of molecules on the single-molecule level. However, extracting information from data with established algorithms usually requires time-consuming checks by an experienced researcher due to inherent variability of solid-state nanopores. Here, we develop a convolutional neural network (CNN) for the fully automated extraction of information from the time-series signals obtained by nanopore sensors. In our demonstration, we use a previously published data set on multiplexed single-molecule protein sensing. The neural network learns to classify translocation events with greater accuracy than previously possible, while also increasing the number of analyzable events by a factor of 5. Our results demonstrate that deep learning can achieve significant improvements in single molecule nanopore detection with potential applications in rapid diagnostics.