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Abstract Recent advances in computer-aided design tools have helped rapidly advance the development of wireframe DNA origami nanostructures. Specifically, automated tools now exist that can convert an input polyhedral mesh into a DNA origami nanostructure, greatly reducing the design difficulty for wireframe DNA origami nanostructures. However, one limitation of these automated tools is that they require a designer to fully conceptualize their intended nanostructure, which may be limited by their own preconceptions. Here, a generative design framework is introduced capable of generating many wireframe DNA origami nanostructures without the need for a predefined mesh. User-defined objectives that guide the generative process are input as either single- or multi-objective optimization problems. A graph grammar is used to both contextualize physical properties of the DNA nanostructure and control the types of generated design features. This framework allows a designer to explore upon and ideate among many generated nanostructures that comply with their own unique constraints. A web-based graphical user interface is provided, allowing users to compare various generated solutions side by side in an interactive environment. Overall, this work illustrates how a constrained generative design framework can be implemented as an assistive tool in exploring design-feature trade-offs of wireframe DNA nanostructures, resulting in novel wireframe nanostructures. 

This paper presents polycarbonate negative topographies used as substrates for the templated self- assembly of microsphere-based microrobots. This approach protects primary structures from damage during molding and de-molding, providing high fidelity negatives of arrays for assembly via templated assembly by selective removal (TASR). We show that reducing the surface energy mismatch between the microspheres and substrate results in yield increases up to 790%. This work addresses yield-related challenges of multicomponent microsystem assembly with existing PDMS-based templated assembly methods. The application of this technology in DNA microswimmer fabrication is demonstrated. 

Magnetically-actuated swimming microrobots are an emerging tool for navigating and manipulating materials in confined spaces. Recent work has demonstrated that it is possible to build such systems at the micro and nanoscales using polymer microspheres, magnetic particles and DNA nanotechnology. However, while these materials enable an unprecedented ability to build at small scales, such systems often demonstrate significant polydispersity resulting from both the material variations and the assembly process itself. This variability makes it difficult to predict, let alone optimize, the direction or magnitude of microswimmer velocity from design parameters such as link shape or aspect ratio. To isolate questions of a swimmer's design from variations in its physical dimensions, we present a novel experimental platform using two-photon polymerization to build a two-link, buoyant milliswimmer with a fully customizable shape and integrated flexible linker (the swimmer is underactuated, enabling asymmetric cyclic motion and net translation). Our approach enables us to control both swimming direction and repeatability of swimmer performance. These studies provide ground truth data revealing that neither the first order nor second order models currently capture the key features of milliswimmer performance. We therefore use our experimental platform to develop design guidelines for tuning the swimming speeds, and we identify the following three approaches for increasing speed: (1) tuning the actuation frequency for a fixed aspect ratio, (2) adjusting the aspect ratio given a desired range of operating frequencies, and (3) using the weaker value of linker stiffness from among the values that we tested, while still maintaining a robust connection between the links. We also find experimentally that spherical two-link swimmers with dissimilar link diameters achieve net velocities comparable to swimmers with cylindrical links, but that two-link spherical swimmers of equal diameter do not. 

ABSTRACT Dynamic and flexible nucleic acid models can provide current and future scientists with physical intuition for the structure of DNA and the ways that DNA and its synthetic mimics can be used to build self-assembling structures and advanced nanomachines. As more research labs and classrooms dive into the field of structural nucleic acid nanotechnology, students and researchers need access to interactive, dynamic, handheld models. Here, we present a 3D-printable kit for the construction of DNA and peptide nucleic acid (PNA). We have engineered a previous modular DNA kit to reduce costs while improving ease of assembly, flexibility, and robustness. We have also expanded the scope of available snap-together models by creating the first 3D-printable models of γPNA, an emerging material for nuclease- and protease-resistance nanotechnology. Building on previous research, representative nucleic acid duplexes were split into logical monomer segments, and atomic coordinates were used to create solid models for 3D printing. We used a human factors approach to customize 3 types of articulated snap-together connectors that allow for physically relevant motion characteristic of each interface in the model. Modules are easy to connect and separate manually but stay together when the model is manipulated. To greatly reduce cost, we bundled these segments for printing, and we created a miniaturized version that uses less than half the printing material to build. Our novel 3D-printed articulated snap-together models capture the flexibility and robustness of DNA and γPNA nanostructures. Resulting handheld helical models replicate the geometries in published structures and can now flex to form crossovers and allow biologically relevant zipping and unzipping to allow complex demonstrations of nanomachines undergoing strand displacement reactions. Finally, the same tools used to create these models can be readily applied to other types of backbones and nucleobases for endless research and education possibilities. 

Abstract The ability to model physiological systems through 3D neural in-vitro systems may enable new treatments for various diseases while lowering the need for challenging animal and human testing. Creating such an environment, and even more impactful, one that mimics human brain tissue under mechanical stimulation, would be extremely useful to study a range of human-specific biological processes and conditions related to brain trauma. One approach is to use human cerebral organoids (hCOs) in-vitro models. hCOs recreate key cytoarchitectural features of the human brain, distinguishing themselves from more traditional 2D cultures and organ-on-a-chip models, as well as in-vivo animal models. Here, we propose a novel approach to emulate mild and moderate traumatic brain injury (TBI) using hCOs that undergo strain rates indicative of TBI. We subjected the hCOs to mild (2 s⁻¹) and moderate (14 s⁻¹) loading conditions, examined the mechanotransduction response, and investigated downstream genomic effects and regulatory pathways. The revealed pathways of note were cell death and metabolic and biosynthetic pathways implicating genes such as CARD9, ENO1, and FOXP3, respectively. Additionally, we show a steeper ascent in calcium signaling as we imposed higher loading conditions on the organoids. The elucidation of neural response to mechanical stimulation in reliable human cerebral organoid models gives insights into a better understanding of TBI in humans. 

Cell penetrating peptides (CPPs), also known as protein transduction domains (PTDs), first identified ~25 years ago, are small, 6–30 amino acid long, synthetic, or naturally occurring peptides, able to carry variety of cargoes across the cellular membranes in an intact, functional form. Since their initial description and characterization, the field of cell penetrating peptides as vectors has exploded. The cargoes they can deliver range from other small peptides, full-length proteins, nucleic acids including RNA and DNA, liposomes, nanoparticles, and viral particles as well as radioisotopes and other fluorescent probes for imaging purposes. In this review, we will focus briefly on their history, classification system, and mechanism of transduction followed by a summary of the existing literature on use of CPPs as gene delivery vectors either in the form of modified viruses, plasmid DNA, small interfering RNA, oligonucleotides, full-length genes, DNA origami or peptide nucleic acids.