Speaker
Description
High-resolution atomic force microscopy (AFM) provides unparalleled visualisation of molecular structures and interactions in liquid, achieving sub-molecular resolution without the need for labelling or averaging. This capability enables detailed imaging of dynamic and flexible molecules like DNA and proteins, revealing their own conformational changes as well as interactions with one another. Despite its powerful potential, AFM’s application in the biosciences is hindered by challenges in image analysis, including inherent imaging artefacts and complexities in data extraction. To address this, we developed TopoStats, an open-source Python package for high-throughput processing and analysis of raw AFM images. TopoStats provides an automated pipeline for file loading, image filtering, cleaning, segmentation, and feature extraction, producing clean, flattened images and detailed statistical information on single molecules. We showcase TopoStats’ capabilities by demonstrating its use for automated quantification across a range of samples - from DNA and DNA-protein interactions to larger-scale materials science applications. Our aim is for TopoStats to significantly enhance the quality of AFM data analysis, support the development of robust and open analytical tools, and contribute to the advancement of AFM research worldwide.
| Authors | Laura Wiggins*, Max Gamill, Sylvia Whittle, Neil Shephard, Alice Pyne |
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| Keywords | Open-source, AFM, image analysis, automation, python toolkit, DNA |
