南京大学龙亿涛小组近日通过纳米孔中随机碰撞驱动的动态特征，实现精确的单分子识别。相关论文于2025年1月2日发表于国际顶尖学术期刊《美国化学会杂志》上。

在这项研究中，该团队在K238Q气单胞菌溶素纳米孔中发现了一种独特的离子电流模式，其特征是在两个稳定的过渡态上叠加了瞬态尖峰。通过使用神经网络模型，该团队证明了这些以前被忽视的动态尖峰特征具有优越的判别能力，将准确率从44%提高到93%。

研究组发现稳定的过渡态是由ssDNA，与纳米孔的两个敏感位点同时相互作用产生的。所提出的随机碰撞模型为解释动态尖峰特征的产生提供了一个机制框架。该模型表明，连续跃迁促进了纳米孔分子相互作用的迭代、全面的快照。他们的发现引入了一种优化纳米孔技术的新方法，以捕获复杂的动态特征，并大大提高单分子鉴定的准确性。

研究人员表示，纳米孔技术在单分子鉴定方面具有巨大的潜力。然而，从离子电流信号中提取有意义的特征，和理解特定特征背后的分子机制仍然没有解决。

附：英文原文

Title: Dynamic Features Driven by Stochastic Collisions in a Nanopore for Precise Single-Molecule Identification

Author: Jia Wang, Shao-Chuang Liu, Zheng-Li Hu, Yi-Lun Ying, Yi-Tao Long

Issue&Volume: January 2, 2025

Abstract: Nanopore technology holds great potential for single-molecule identification. However, extracting meaningful features from ionic current signals and understanding the molecular mechanisms underlying the specific features remain unresolved. In this study, we uncovered a distinctive ionic current pattern in a K238Q aerolysin nanopore, characterized by transient spikes superimposed on two stable transition states. By employing a neural network model, we demonstrated that these previously overlooked dynamic spike features exhibit superior discriminative power, improving the accuracy from 44% to 93%. We identified that the stable transition states result from simultaneous interactions of ssDNA with the two sensitive sites of the nanopore. The proposed stochastic collision model offers a mechanistic framework for interpreting the generation of the dynamic spike features. This model indicates that the continuous transitions facilitate iterative, comprehensive snapshots of molecular interactions by nanopores. Our findings introduce a new approach for optimizing nanopore technology to capture complex dynamic features and substantially improve the accuracy of single-molecule identification.

DOI: 10.1021/jacs.4c13664

Source: https://pubs.acs.org/doi/abs/10.1021/jacs.4c13664