Nanopore Force Spectroscopy and Sorting of Vesicles at Nanoscale

项目总结 柔性纳米粒子，如外切体、脂质体和病毒，在生物和生理方面发挥着至关重要的作用。 (包括治疗)功能，如外吞和内吞、膜转运和细胞间信号转导。 随着靶向药物/基因传递的进步，携带货物的囊泡具有最小的全身毒性， 细胞/组织靶向摄取的改善和药物的控制释放得到了广泛的关注。一个 这些软泡的关键功能方面是相对于货物含量、膜的变形能力 组合物和内/外介质与细胞器融合并穿过狭窄的毛孔。因此， 分析其变形性对于了解它们的功能和成功的药物工程至关重要。现有的 原子力显微镜(AFM)等经典技术需要费力和繁琐的程序， 吞吐量低。其他可用于研究囊泡包裹的货物的方法，如DNA酶 消化、荧光和紫外线吸收会受到夜间程序、DNA提取(和标记)、 和DNA标准曲线要求分别。在这项拟议的工作中，我们打算开发一种技术 为了克服这些缺点，利用纳米孔来研究软纳米颗粒的变形性 纳米级通道分隔两个电解液室，分析物粒子可以通过该电解液室电动 根据施加的偏压一次一个地从一个腔室行进到另一个腔室，引起电 颗粒大小、形状和含量所特有的扰动。纳米孔坚固、灵敏且价格低廉 吞吐量更高的微型传感器--能够在几秒到几分钟内研究数千个颗粒。 我们将首先建立脂质体电变形性的计算模型(S)，该模型依赖于 电导率、货物密度和表面电荷(目标1a)。我们提出了一种自动重新捕获协议来研究 通过在每次移位事件后通过反转电压偏置来重新移位相同颗粒~25次 使用相同的颗粒来生成大量关于脂质体变形性的可靠统计数据。电-- 变形性将被表示为正向和反向偏置时的相对电流降比。所获得的 结果将与商业上可获得的、不可压缩的刚性粒子，如聚苯乙烯进行比较，以获得认可。 结果(目标1b)。假设货物含量会通过以下方式影响脂质体的变形性 改变了内部溶液的传导性，也许还改变了形状。我们建议合成纳米脂质体 储存已知比率的ss/ds-DNA以检验这一理论(目标2a)。通过研究DNA的电变形能力- 通过与无载药脂质体的比较，我们确定了包埋脂质体的电化程度。 货物含量(数量和百分比)的变形性(目标2b)。此外，自动化的 重新捕获协议将能够从总体中辨别出所需机械性能的样本 性质各异的囊泡。一旦并行化，就可以获得高吞吐量的数据来表征 任何纳米级软粒子在单粒子水平上的刚性。

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.