Abstract:Scaffolded DNA origami has proven to be a powerful and efficient technique to fabricate functional nanomachines by programming the folding of a single-stranded DNA template strand into three-dimensional (3D) nanostructures, designed to be precisely motion-controlled. Although two-dimensional (2D) imaging of DNA nanomachines using transmission electron microscopy and atomic force microscopy suggested these nanomachines are dynamic in 3D, geometric analysis based on 2D imaging was insufficient to uncover the exa… Show more
“…The map allowed us to determine another conformation of DNA origami. These features of the density maps were very similar to the previous publication 2 , in which the low-pass filter was only used to increase the image contrast. Figure 7 3D tomogram of the DNA origami by cryo-PS-ET.…”
Section: Overview Of the Algorithmsupporting
confidence: 79%
“…7A ). It should be pointed out that IPET reconstruction of these DNA origami particles was previously published 2 , in which only a low-pass filter was used to enhance image contrast. Here, to evaluate our proposed enhancement algorithm, the low-pass filtering was conducted before enhancement and IPET reconstruction.…”
Section: Overview Of the Algorithmmentioning
confidence: 99%
“…Averaging the structures from different particles without prior knowledge of their structure identity, or ignored the nature flexibility or fluctuation of the particles may lead to artifacts in protein structure determination such as blurring or eliminating the flexible domains. The typical flexble proteins include the double strand DNA (dsDNA) 2 – 5 , antibody 6 – 8 , lipoprotein and neuron proteins 9 – 14 . As an example of the IgG1 antibody, by enforced averaging the particle images of IgG antibody in single-particle 3D reconstruction 6 – 8 , one or two domains could disappeared.…”
Three-dimensional (3D) reconstruction of a single protein molecule is essential for understanding the relationship between the structural dynamics and functions of the protein. Electron tomography (ET) provides a tool for imaging an individual particle of protein from a series of tilted angles. Individual-particle electron tomography (IPET) provides an approach for reconstructing a 3D density map from a single targeted protein particle (without averaging from different particles of this type of protein), in which the target particle was imaged from a series of tilting angles. However, owing to radiation damage limitations, low-dose images (high noise, and low image contrast) are often challenging to be aligned for 3D reconstruction at intermediate resolution (1–3 nm). Here, we propose a computational method to enhance the image contrast, without increasing any experimental dose, for IPET 3D reconstruction. Using an edge-preserving smoothing-based multi-scale image decomposition algorithm, this method can detect the object against a high-noise background and enhance the object image contrast without increasing the noise level or significantly decreasing the image resolution. The method was validated by using both negative staining (NS) ET and cryo-ET images. The successful 3D reconstruction of a small molecule (<100 kDa) indicated that this method can be used as a supporting tool to current ET 3D reconstruction methods for studying protein dynamics via structure determination from each individual particle of the same type of protein.
“…The map allowed us to determine another conformation of DNA origami. These features of the density maps were very similar to the previous publication 2 , in which the low-pass filter was only used to increase the image contrast. Figure 7 3D tomogram of the DNA origami by cryo-PS-ET.…”
Section: Overview Of the Algorithmsupporting
confidence: 79%
“…7A ). It should be pointed out that IPET reconstruction of these DNA origami particles was previously published 2 , in which only a low-pass filter was used to enhance image contrast. Here, to evaluate our proposed enhancement algorithm, the low-pass filtering was conducted before enhancement and IPET reconstruction.…”
Section: Overview Of the Algorithmmentioning
confidence: 99%
“…Averaging the structures from different particles without prior knowledge of their structure identity, or ignored the nature flexibility or fluctuation of the particles may lead to artifacts in protein structure determination such as blurring or eliminating the flexible domains. The typical flexble proteins include the double strand DNA (dsDNA) 2 – 5 , antibody 6 – 8 , lipoprotein and neuron proteins 9 – 14 . As an example of the IgG1 antibody, by enforced averaging the particle images of IgG antibody in single-particle 3D reconstruction 6 – 8 , one or two domains could disappeared.…”
Three-dimensional (3D) reconstruction of a single protein molecule is essential for understanding the relationship between the structural dynamics and functions of the protein. Electron tomography (ET) provides a tool for imaging an individual particle of protein from a series of tilted angles. Individual-particle electron tomography (IPET) provides an approach for reconstructing a 3D density map from a single targeted protein particle (without averaging from different particles of this type of protein), in which the target particle was imaged from a series of tilting angles. However, owing to radiation damage limitations, low-dose images (high noise, and low image contrast) are often challenging to be aligned for 3D reconstruction at intermediate resolution (1–3 nm). Here, we propose a computational method to enhance the image contrast, without increasing any experimental dose, for IPET 3D reconstruction. Using an edge-preserving smoothing-based multi-scale image decomposition algorithm, this method can detect the object against a high-noise background and enhance the object image contrast without increasing the noise level or significantly decreasing the image resolution. The method was validated by using both negative staining (NS) ET and cryo-ET images. The successful 3D reconstruction of a small molecule (<100 kDa) indicated that this method can be used as a supporting tool to current ET 3D reconstruction methods for studying protein dynamics via structure determination from each individual particle of the same type of protein.
“…In Fig. 2K, a specific tangent developable is shown, whose axes correspond to the axes of a Bennett linkage, an overconstrained spatial mechanism (34,35), shown in Fig. 2L.…”
The trend toward smaller mechanism footprints and volumes, while maintaining the ability to perform complex tasks, presents the opportunity for exploration of hypercompact mechanical systems integrated with curved surfaces. Developable surfaces are shapes that a flat sheet can take without tearing or stretching, and they represent a wide range of manufactured surfaces. This work introduces “developable mechanisms” as devices that emerge from or conform to developable surfaces. They are made possible by aligning hinge axes with developable surface ruling lines to enable mobility. Because rigid-link motion depends on the relative orientation of hinge axes and not link geometry, links can take the shape of the corresponding developable surface. Mechanisms are classified by their associated surface type, and these relationships are defined and demonstrated by example. Developable mechanisms show promise for meeting unfilled needs using systems not previously envisioned.
“…Origami-inspired mechanisms have been demonstrated to hold significant potential for solving a variety of engineering problems 1 , including the deployment of antennas 2 and solar panels 3 , shelters 4 , radiators for spacecraft 5 , surgical equipment 6 , nanomachines 7 – 9 , robotics 10 , 11 electronics 12 and airbag stowage 13 . However, one barrier preventing origami from being fully utilized involves successfully including thickness in the mechanism 14 .…”
Origami concepts show promise for creating complex deployable systems. However, translating origami to thick (non-paper) materials introduces challenges, including that thick panels do not flex to facilitate folding and the chances for self-intersection of components increase. This work introduces methods for creating permutations of linkage-based, origami-inspired mechanisms that retain desired kinematics but avoid self-intersection and enable their connection into deployable networks. Methods for reconfiguring overconstrained linkages and implementing them as modified origami-inspired mechanisms are proved and demonstrated for multiple linkage examples. Equations are derived describing the folding behavior of these implementations. An approach for designing networks of linkage-based origami vertices is demonstrated and applications for tessellations are described. The results offer the opportunity to exploit origami principles to create deployable systems not previously feasible.
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