State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, No. 2, Sipailou, Nanjing 210096, People's Republic of China.
Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, P. R. China.
ACS Appl Bio Mater. 2021 Aug 16;4(8):6394-6403. doi: 10.1021/acsabm.1c00587. Epub 2021 Jul 21.
Although nanopore as a single-molecule sensing platform has proven its potential in various applications, data analysis of nanopores remains challenging. Herein, we introduce a method with increased accuracy in nanopore analysis based on the central limit theorem (CLT). An optimal voltage used in detection is determined from the standard deviations of blockage currents and time constants at various voltage biases. Compared with the conventional data analysis method, blockage signals processed with the CLT result in more concentrated distributions of blockage currents and durations. It allows fitting a Gaussian to the duration histogram and avoids the influence of bin sizes on time constants in duration analysis. The proposed method is further validated by applying it to detect isolated microRNAs with solid-state nanopores. Under the optimal voltage, different nucleic acids present in the isolation process are translocated through the nanopore. By processing the event signals with the CLT, all the nucleic acids including the microRNA are well differentiated. The method proposed here should also be applicable for sensing other biomolecules with the solid-state nanopores.
尽管纳米孔作为一种单分子传感平台已经在各种应用中证明了其潜力，但纳米孔的数据分析仍然具有挑战性。在此，我们基于中心极限定理 (CLT) 引入了一种在纳米孔分析中提高准确性的方法。在不同的电压偏置下，通过阻塞电流和时间常数的标准偏差确定检测中使用的最佳电压。与传统数据分析方法相比，用 CLT 处理的阻塞信号导致阻塞电流和持续时间的分布更加集中。它允许将高斯拟合到持续时间直方图中，并避免在持续时间分析中-bin 大小对时间常数的影响。通过应用于固态纳米孔检测分离的 microRNA，进一步验证了该方法。在最佳电压下，分离过程中存在的不同核酸穿过纳米孔。通过用 CLT 处理事件信号，可以很好地区分包括 microRNA 在内的所有核酸。这里提出的方法也应该适用于固态纳米孔检测其他生物分子。
