Nanopore Force Spectroscopy and Sorting of Vesicles at Nanoscale

项目摘要 软纳米颗粒如外泌体、脂质体和病毒在生物和生理学中起着至关重要的作用， 这些功能包括（包括治疗性）功能，例如胞外和胞吞作用、膜运输和细胞间信号传导。 随着靶向药物/基因递送的进步，具有最小全身毒性的货物运载囊泡， 在细胞/组织靶点处的改善的摄取和受控的药物释放已经获得了大量的关注。一 这些软囊泡的关键功能方面是相对于货物内容物、膜 组合物和内/外介质与细胞器融合并穿过狭窄的孔。因此，在本发明中， 分析可变形性对于理解它们的功能和成功的药物工程是至关重要的。现有 像原子力显微镜（AFM）这样的经典技术需要费力和繁琐的程序， 低吞吐量。其他可用的方法来研究囊泡包裹的货物，如DNA酶 消化、荧光和UV吸收受到过夜程序、DNA提取（和标记） 和DNA标准曲线要求。在这项工作中，我们打算开发一种技术， 为了克服所有这些缺点，通过使用纳米孔来研究软纳米颗粒的可变形性， 分隔两个电解质室的纳米级通道，分析物颗粒可以通过该通道动电地 响应于施加的偏压，一次一个地从一个腔室行进到另一个腔室， 颗粒大小、形状和含量特有的扰动。纳米孔是坚固的，敏感的和廉价的 更高通量的微型传感器-能够在数秒至数分钟内研究数千个颗粒。 我们将首先开发用于脂质体的电变形性的计算模型，其取决于 电导率、货物密度和表面电荷（目标1a）。我们提出了一个自动重捕获协议，研究 通过在每个易位事件之后反转电压偏压，将相同的颗粒重新易位~25次， 相同的颗粒以产生关于脂质体的变形性的可靠统计的大的库。电- 可变形性将表示为正向和反向偏压下的相对电流降比。所获得的 结果将与商业上可获得的不可压缩的刚性颗粒（如聚苯乙烯）进行比较， 目标1b）。假设货物含量将通过以下方式影响脂质体的变形性： 改变了内部溶液的电导率，也许还改变了形状。我们建议合成纳米脂质体 容纳已知比例的ss/ds-DNA以测试该理论（Aim 2a）。通过研究DNA的电变形能力， 包封脂质体，与无载物脂质体相比，我们意图确定电- 根据货物含量（数量和百分比）的变形能力（目标2b）。此外，自动化 重新捕获方案将能够从总体中区分具有所需机械性能的样品 具有不同特性的囊泡。一旦并行化，就可以获得高通量数据来表征 刚性的任何纳米级软颗粒在单颗粒水平。

PROJECT SUMMARY Soft nanoparticles like exosomes, liposomes and viruses play a vital role in biological and physiological (including therapeutic) functions such as exo- and endocytosis, membrane trafficking, and intercellular signaling. With advancements in targeted drug/gene delivery, cargo carrying vesicles with minimal systemic toxicity, improved uptake and controlled drug release at the cellular/tissue targets have gained substantial attention. A key functional aspect of these soft vesicles is the ability to deform relative to the cargo content, membrane composition and inner/outer media to fuse with cellular organelles and pass through narrow pores. Thus, profiling deformability is critical for understanding their functions and successful drug engineering. The existing classical techniques like atomic force microscopy (AFM) demand laborious and cumbersome procedures, with low throughput. Other available methods to study the cargo encapsulated by the vesicles such as DNase digestion, fluorescence, and UV absorbance suffer from overnight procedures, DNA extraction (and tagging), and DNA standard curve requirements, respectively. In this proposed work, we intend to develop a technique to overcome all these shortcomings to study the deformability of soft nanoparticles by using a nanopore – a nanoscale channel separating two electrolyte chambers through which analyte particles can electrokinetically travel from one chamber to the other in response to an applied bias, one at a time, causing electrical perturbations unique to particle size, shape, and content. Nanopores are robust, sensitive and inexpensive miniature sensors of higher throughput – capable of studying thousands of particles within seconds to minutes. We will first develop a computational model(s) for electro-deformability of the liposomes which depends on conductivity, cargo density, and surface charge (Aim 1a). We propose an automated recapture protocol to study the same particle ~25 times by reversing the voltage bias after each translocation event to re-translocate the same particle to generate a large pool of reliable statistics on deformability of the liposomes. Electro- deformability would be expressed as the relative current drop ratio at forward and reverse biases. The obtained results will be compared with a commercially available, incompressible rigid particle like polystyrene to accredit the results (Aim 1b). It is assumed that the cargo content would affect the deformability of the liposomes by altering the inner solution conductivity and perhaps the shape. We propose to synthesize nanoliposomes housing ss/ds-DNA of known ratios to test this theory (Aim 2a). By studying the electro-deformability of DNA- encapsulated liposomes, in comparison with cargo-free liposomes, we intent to determine the degree of electro- deformability in response to the cargo content (amount and percentage) (Aim 2b). In addition, the automated recapture protocol will enable the discrimination of samples of desired mechanical properties out of a population of vesicles with varied properties. Once parallelized, high throughput data can be obtained to characterize rigidity of any nanoscale soft particle at the single-particle level.