全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
-  2019 

Characterizing DNA Nanotube Networks Assembled via Y-Junction DNA Origami Seeds

DOI: https://doi.org/10.1016/j.bpj.2018.11.1475

Full-Text   Cite this paper   Add to My Lib

Abstract:

DNA nanotechnology offers a means to synthesize custom nano-structured materials from the ground up in a hierarchical fashion. While the assembly of DNA nanostructures from small (nanometer-scale) monomeric components has been studied extensively, a general model for the hierarchical assembly of rigid or semiflexible units into multimicron-scale structures remains elusive. To study such hierarchical assembly, we have developed a system for assembling extend networks of semiflexible DNA nanotubes. These nanotubes assemble from nanometer scale tiles into materials via the nucleated growth from sites on rigid, Y-shaped nanotube seeds. In this process, nanotubes first grow from these Y-shaped seeds to form 3-armed nanotube architectures. These architectures then in turn assemble into networks that include as many as 80 seeds and can extend over areas as large as 900 μm 2. We measure the kinetics of network growth and find that the assembly of these networks can be explained by a stochastic model of hierarchical assembly that assumes a single joining rate between DNA nanotube ends. Because the number of nucleation sites on the seeds and their spatial arrangement can be systematically varied by design, this system allows the assembly of a wide variety of networks and characterization of the assembly mechanisms that lead to different types of material architectures at length scales of tens to hundreds of microns. Further, by activating/deactivating the incorporated Y-shaped DNA origami junctions via strand displacement we are also able to direct networks to change form, suggesting a model system for understanding not only the formation of filament networks at this length-scale but also their reconfiguration

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133