Institute of Structural and Molecular Biology, Birkbeck, University of London, London WC1E 7HX, UK; Centre for Structural Systems Biology, Heinrich-Pette-Institut, Leibniz-Institut für Experimentelle Virologie and Universitätsklinikum Hamburg Eppendorf, Hamburg, Germany.
The Henry Royce Institute and Department of Materials Science and Engineering, The University of Sheffield, Sir Robert Hadfield Building, Sheffield S1 3JD, United Kingdom; Department of Materials Science and Engineering, University of Sheffield, Sheffield S1 3JD, UK.
Methods. 2021 Sep;193:68-79. doi: 10.1016/j.ymeth.2021.01.008. Epub 2021 Feb 4.
We present TopoStats, a Python toolkit for automated editing and analysis of Atomic Force Microscopy images. The program automates identification and tracing of individual molecules in circular and linear conformations without user input. TopoStats was able to identify and trace a range of molecules within AFM images, finding, on average, ~90% of all individual molecules and molecular assemblies within a wide field of view, and without the need for prior processing. DNA minicircles of varying size, DNA origami rings and pore forming proteins were identified and accurately traced with contour lengths of traces typically within 10 nm of the predicted contour length. TopoStats was also able to reliably identify and trace linear and enclosed circular molecules within a mixed population. The program is freely available via GitHub (https://github.com/afm-spm/TopoStats) and is intended to be modified and adapted for use if required.
我们展示了 TopoStats，这是一个用于自动编辑和分析原子力显微镜图像的 Python 工具包。该程序无需用户输入即可自动识别和跟踪圆形和线性构象中的单个分子。TopoStats 能够识别和跟踪 AFM 图像中的一系列分子，平均在较宽的视场范围内找到约 90%的所有单个分子和分子组装体，并且无需进行预先处理。不同大小的 DNA 迷你环、DNA 折纸环和形成孔的蛋白质被识别并准确地追踪，其追踪的轮廓长度通常与预测的轮廓长度相差 10nm 以内。TopoStats 还能够可靠地识别和跟踪混合群体中的线性和封闭圆形分子。该程序可通过 GitHub（https://github.com/afm-spm/TopoStats）免费获得，并且可以根据需要进行修改和调整以适应使用。
