Abstract：
This study utilized solid-state nanopores, combined with artificial intelligence (AI), to analyze the double-stranded polynucleotides encoding angiotensin-converting enzyme 2, receptor-binding domain, and N protein, important parts of SARS-CoV-2 infection. By examining ionic current signals during DNA translocation, we revealed the dynamic interactions and structural characteristics of these nucleotide sequences and also quantified their abundance. Nanopores of sizes 3 and 10 nm were efficiently fabricated and characterized, ensuring an optimal experimental approach. Our results showed a clear relationship between DNA capture rates and concentration, proving our method\'s effectiveness. Notably, longer DNA sequences had higher capture rates, suggesting their importance for potential disease marker analysis. The 3 nm nanopore demonstrated superior performance in our DNA analysis. Using dwell time measurements and excluded currents, we were able to distinguish the longer DNA fragments, paving the way for a DNA length-based analysis. Overall, our research underscores the potential of nanopore technology, enhanced with AI, in analyzing COVID-19-related DNA and its implications for understanding disease severity. This provides insight into innovative diagnostic and treatment strategies.
摘要：
这项研究利用了固态纳米孔，结合人工智能(AI)，分析双链多核苷酸编码血管紧张素转换酶2，受体结合域，和N蛋白，SARS-CoV-2感染的重要部分。通过检查DNA易位过程中的离子电流信号，我们揭示了这些核苷酸序列的动态相互作用和结构特征，并量化了它们的丰度。有效地制造和表征了尺寸为3和10nm的纳米孔，确保最佳的实验方法。我们的结果显示DNA捕获率和浓度之间有明确的关系，证明我们方法的有效性。值得注意的是,较长的DNA序列具有较高的捕获率，表明它们对潜在疾病标志物分析的重要性。3nm纳米孔在我们的DNA分析中表现出优异的性能。使用停留时间测量和排除的电流，我们能够区分较长的DNA片段，为基于DNA长度的分析铺平了道路。总的来说,我们的研究强调了纳米孔技术的潜力，用AI增强，分析COVID-19相关DNA及其对了解疾病严重程度的意义。这提供了对创新诊断和治疗策略的见解。
