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冷冻电镜分析脂质纳米粒用于表征 siRNA 递送载体。

Analysis of lipid nanoparticles by Cryo-EM for characterizing siRNA delivery vehicles.

机构信息

Informatics IT, Merck & Co, Inc., West Point, PA, USA.

出版信息

Int J Pharm. 2011 Jan 17;403(1-2):237-44. doi: 10.1016/j.ijpharm.2010.10.025. Epub 2010 Oct 23.

DOI:10.1016/j.ijpharm.2010.10.025
PMID:20974237
Abstract

Lipid nanoparticles are self-assembling, dynamic structures commonly used as carriers of siRNA, DNA, and small molecular therapeutics. Quantitative analysis of particle characteristics such as morphological features can be very informative as biophysical properties are known to influence biological activity, biodistribution, and toxicity. However, accurate characterization of particle attributes and population distributions is difficult. Cryo-Electron Microscopy (Cryo-EM) is a leading characterization method and can reveal diversity in particle size, shape and lamellarity, however, this approach is traditionally used for qualitative review or low throughput image analysis due to inherent EM micrograph contrast characteristics and artifacts in the images which limit extraction of quantitative feature values. In this paper we describe the development of a semiautomatic image analysis framework to facilitate reliable image enhancement, object segmentation, and quantification of nanoparticle attributes in Cryo-EM micrographs. We apply this approach to characterize two formulations of siRNA-loaded lipid nanoparticles composed of cationic lipid, cholesterol, and poly(ethylene glycol)-lipid, where the formulations differ only by input component ratios. We found Cryo-EM image analysis provided reliable size and morphology information as well as the detection of smaller particle populations that were not detected by standard dynamic light scattering (DLS) analysis.

摘要

脂质纳米颗粒是自组装的动态结构,通常用作 siRNA、DNA 和小分子治疗药物的载体。定量分析颗粒特征,如形态特征,可以提供非常有价值的信息,因为已知生物物理性质会影响生物活性、分布和毒性。然而,准确表征颗粒属性和群体分布是困难的。冷冻电子显微镜(Cryo-EM)是一种领先的表征方法,可以揭示颗粒大小、形状和层状的多样性,然而,由于 EM 显微照片的固有对比度特征和图像中的伪影,这种方法传统上仅用于定性评估或低通量图像分析,这限制了定量特征值的提取。在本文中,我们描述了一种半自动图像分析框架的开发,以促进在 Cryo-EM 显微照片中可靠地增强图像、分割对象和量化纳米颗粒属性。我们应用这种方法来表征两种由阳离子脂质、胆固醇和聚(乙二醇)脂质组成的负载 siRNA 的脂质纳米颗粒制剂,其中制剂仅通过输入成分比例不同。我们发现 Cryo-EM 图像分析提供了可靠的大小和形态信息,以及通过标准动态光散射(DLS)分析检测不到的较小颗粒群体的检测。

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