Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.
Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.
Bioelectrochemistry. 2021 Apr;138:107731. doi: 10.1016/j.bioelechem.2020.107731. Epub 2020 Dec 29.
Plasmid DNA (pDNA) has been widely used for non-viral gene delivery. After pDNA molecules enter a mammalian cell, they may be trapped in subcellular structures or degraded by nucleases. Only a fraction of them can function as templates for transcription in the nucleus. Thus, an important question is, what is the minimal amount of pDNA molecules that need to be delivered into a cell for transgene expression? At present, it is technically a challenge to experimentally answer the question. To this end, we developed a statistical framework to establish the relationship between two experimentally quantifiable factors - average copy number of pDNA per cell among a group of cells after transfection and percent of the cells with transgene expression. The framework was applied to the analysis of electrotransfection under different experimental conditions in vitro. We experimentally varied the average copy number per cell and the electrotransfection efficiency through changes in extracellular pDNA dose, electric field strength, and pulse number. The experimental data could be explained or predicted quantitatively by the statistical framework. Based on the data and the framework, we could predict that the minimal number of pDNA molecules in the nucleus for transgene expression was on the order of 10. Although the prediction was dependent on the cell and experimental conditions used in the study, the framework may be generally applied to analysis of non-viral gene delivery.
质粒 DNA(pDNA)已被广泛用于非病毒基因传递。pDNA 分子进入哺乳动物细胞后,可能会被细胞内结构捕获或被核酸酶降解。只有一小部分能够在核内作为转录模板发挥作用。因此,一个重要的问题是,需要将多少 pDNA 分子递送到细胞中才能进行转基因表达?目前,从技术上看,实验回答这个问题具有挑战性。为此,我们开发了一个统计框架,以建立两个可实验量化的因素之间的关系 - 转染后一组细胞中每个细胞的 pDNA 平均拷贝数和表达转基因的细胞百分比。该框架应用于体外不同实验条件下的电转染分析。我们通过改变细胞外 pDNA 剂量、电场强度和脉冲数来实验性地改变每个细胞的平均拷贝数和电转染效率。统计框架可以定量解释或预测实验数据。基于这些数据和框架,我们可以预测转基因表达所需的细胞核内 pDNA 分子数量至少为 10。尽管该预测依赖于研究中使用的细胞和实验条件,但该框架可能普遍适用于非病毒基因传递的分析。