Kanazawa NanoLSI Research Podcast: Revealing atomistic structures behind AFM imaging

Revealing atomistic structures behind AFM imaging

https://nanolsi.kanazawa-u.ac.jp/en/achievements/revealing-atomistic-structures-behind-afm-imaging/

Atomic force microscopy (AFM) enables the visualization of the dynamics of single biomolecules during their functional activity. However, all observations are restricted to regions that are accessible by a fairly big probing tip during scanning. Hence, the AFM only records images of biomolecular surfaces with limited spatial resolution, thereby missing important information that is required for a detailed understanding of the observed phenomena.

To facilitate the interpretation of experimental imaging, Romain Amyot and Holger Flechsig from the Kanazawa NanoLSI have developed the mathematical framework and computational methods to reconstruct 3D atomistic structures from AFM surface scans. 
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Transcript of this podcast

Hello and welcome to the NanoLSI podcast. 

In this episode we feature the latest research published by Romain Amyot and Holger Flechsig of the Computational Science group at the Kanazawa University NanoLSI.

The research described in this podcast was published in the journal PLOS Computational Biology in March 2022. 

Revealing atomistic structures behind AFM imaging

https://nanolsi.kanazawa-u.ac.jp/en/achievements/revealing-atomistic-structures-behind-afm-imaging/

Atomic force microscopy (AFM) enables the visualization of the dynamics of single biomolecules during their functional activity. However, all observations are restricted to regions that are accessible by a fairly big probing tip during scanning. Hence, the AFM only records images of biomolecular surfaces with limited spatial resolution, thereby missing important information that is required for a detailed understanding of the observed phenomena.

To facilitate the interpretation of experimental imaging, Romain Amyot and Holger Flechsig from the Kanazawa NanoLSI have developed the mathematical framework and computational methods to reconstruct 3D atomistic structures from AFM surface scans. 

In this paper they describe applications for high-speed AFM imaging ranging from single molecular machines, protein filaments, to even large-scale assemblies of protein lattices, and demonstrate how the full atomistic information advances the molecular understanding beyond topographic images.

Their approach employs simulation AFM, which was previously established by Amyot and Flechsig and distributed within the free BioAFMviewer software package. 

Simulation AFM computationally emulates experimental scanning of biomolecules to translate structural data into simulation AFM topographic images that can be compared to real AFM images. 

The researchers implemented a procedure of automated fitting to identify the high-resolution molecular structure behind a limited-resolution experimental AFM image. It is therefore possible to retrieve full 3D atomistic information from just a scan of the protein surface obtained under AFM observations. 

To illustrate the potential of this achievement, Flechsig says: “Imagine that instead of just seeing the tip of an iceberg, you are now able to see everything hidden under the sea, to the extent that you can even detect impurities or density differences within its structure, helping you to explain the icebergs’ coloration.”

To share these developments with the global Bio-AFM community, all computational methods are embedded within the user-friendly BioAFMviewer interactive software interface. The new methods have already be

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