扫描电镜
超分子化学
纳米技术
纳米结构
阳离子聚合
材料科学
肽
胶体金
原位
化学
纳米颗粒
超分辨率
计算机科学
分子
有机化学
高分子化学
人工智能
图像(数学)
生物化学
作者
Mohit Kumar,Jiye Son,Richard H. Huang,Deborah Sementa,Magdelene Lee,Stephen O’Brien,Rein V. Ulijn
出处
期刊:ACS Nano
[American Chemical Society]
日期:2020-11-10
卷期号:14 (11): 15056-15063
被引量:17
标识
DOI:10.1021/acsnano.0c05029
摘要
Supramolecular materials have gained substantial interest for a number biological and nonbiological applications. However, for optimum utilization of these dynamic self-assembled materials, it is important to visualize and understand their structures at the nanoscale, in solution and in real time. Previous approaches for imaging these structures have utilized super-resolution optical imaging methods such as STORM, which has provided important insights, but suffers from drawbacks of complex sample preparation and slow acquisition times, thus limiting real-time in situ imaging of dynamic processes. We demonstrate a noncovalent fluorescent labeling design for STED-based super-resolution imaging of self-assembling peptides. This is achieved by in situ, electrostatic binding of anionic sulfonates of Alexa-488 dye to the cationic sites of lysine (or arginine) residues exposed on the peptide nanostructure surface. A direct, multiscale visualization of static structures reveals hierarchical organization of supramolecular fibers with sub-60 nm resolution. In addition, the degradation of nanofibers upon enzymatic hydrolysis of peptide could be directly imaged in real time, and although resolution was compromised in this dynamic process, it provided mechanistic insights into the enzymatic degradation process. Noncovalent Alexa-488 labeling and subsequent imaging of a range of cationic self-assembling peptides and peptide-functionalized gold nanoparticles demonstrated the versatility of the methodology for the imaging of cationic supramolecular structures. Overall, our approach presents a general and simple method for the electrostatic fluorescent labeling of cationic peptide nanostructures for nanoscale imaging under physiological conditions and probe dynamic processes in real time and in situ.
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