High-speed atomic force microscopy: extracting high-resolution information through image analysis.
High-speed atomic force microscopy: extracting high-resolution information through image analysis.
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高速原子力显微镜：通过图像分析提取高分辨率信息。
DOI：
10.1007/s12551-023-01168-0
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发表时间：
2023
影响因子：
--
通讯作者：
Heath GR
中科院分区：
文献类型：
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作者：
Heath GR
蛋白质的作用可以比作错综复杂的纳米机器，包括共同工作的移动部件，以执行特定任务和实现生物目标。要提高我们对生物功能的理解，就需要深入了解这些纳米机器组件的运动，在单机(单一蛋白质)的水平上观察它们。高速原子力显微镜(HS-AFM)(Ando等人2001)代表了单分子纳米成像的前沿，能够在环境条件下在分子水平上实时可视化动态过程。这一相对较新的能力，在它们执行其功能时以高分辨率观察分子结构，揭示了对以前被系综技术所掩盖的分子行为的重大见解(Heath和Scheuring 2019)。例如最近发现的关于TrPV3的S在色氨酸四聚体家族中以五聚体状态瞬时存在(Lansky等人。2023)，PIEZO1‘S通过力相关的展平变形激活(Lin等.2019年)，以及肌球蛋白V采取步骤的机制(Kodera等人。2010)。HS-AFM生成的3D地形视频包含大量数据，以超过100,000赫兹的速率记录，时间跨度从几秒钟到几个小时不等。每个像素/数据点可以包含关于被研究表面的结构和动力学的丰富数据。因此，数据处理和分析必须设计为高通量，同时还必须仔细考虑可能存在的噪声、漂移、变化的尖端卷积和分子动力学。鉴于潜在可用的丰富信息，HS-AFM数据分析工具的进步具有增加我们对复杂生物分子过程的理解的巨大潜力。我在IUPAB/NanoLSI关于将计算和理论方法应用于原子力显微镜的联合研讨会上的演讲使我有机会讲述图像文件和图像分析方法的历史，并描述最近开发的局部化AFM方法。在这篇评论中，我将从图像分析的角度描述AFM图像形成的要点，然后我将在此基础上描述使用局部化AFM提高AFM空间分辨率的方法，这是一种从超分辨率显微镜中提取概念的图像分析方法。
The actions of proteins can be likened to intricate nanomachines, comprising moving parts working collectively to execute specific tasks and achieve biological objectives. Advancing our comprehension of biological function demands insight into the movements of these nano-machine components, observing them at the single-machine (single protein) level. High-speed atomic force microscopy (HS-AFM)(Ando et al. 2001) represents the forefront of single-molecule nanoscale imaging, enabling real-time visualization of dynamic processes at molecular levels under ambient conditions. This relatively recent capability to observe molecular structures in high-resolution while they execute their functions has unveiled significant insights into molecular behavior previously obscured by ensemble techniques (Heath and Scheuring 2019). Examples include the recent discoveries concerning TRPV3’s transient existence in a pentameric state within a family of TRP tetramers (Lansky et al. 2023), PIEZO1’s activation through force-dependent flattening deformation (Lin et al. 2019), and the mechanism of steps taken by myosin V (Kodera et al. 2010). The 3D topographic videos generated by HS-AFM encompass substantial volumes of data, recorded at rates exceeding 100,000 Hz and spanning from several seconds to hours. Each pixel/data point may contain rich data about the structure and dynamics of the surface being studied. Therefore, data processing and analysis must be designed for high throughput while also taking careful consideration to the noise, drift, varying tip convolution, and molecule dynamics that may be present. Given the wealth of information potentially available, advancements in HS-AFM data analysis tools have significant potential to increase our understanding of complex biomolecular processes. My lecture at the Joint IUPAB/NanoLSI Workshop on Computational and Theoretical Methods Applied to Atomic Force Microscopy gave an opportunity to speak about the history of image files and image analysis methods and describe the recently developed Localization AFM method. In this commentary, I will describe AFM image formation covering important points from an image analysis perspective, I will then build on this to describe methods for improvement AFM spatial resolution using localization AFM, an image analysis method which takes concepts from super resolution microscopy.