Analysis of Biofilm Assembly by Large Area Automated AFM
Traditionally, AFM was a difficult technique to automate, mainly due to a lack of good Application Programming Interfaces (APIs).
However, Nanosurf's Python library now allows users to fully control AFM operations through scripting. This has enabled many laboratories to automate their processes and incorporate complex analysis routines.
In this publication, the authors introduce an automated large-area AFM approach to study biofilm formation. This method achieves high resolution over millimeter-scale areas. The technique, supported by machine learning for image stitching and cell detection, offers detailed insights into the spatial arrangement and cellular shapes during the early stages of biofilm assembly. The study specifically shows a preferred cellular orientation, forming a honeycomb pattern in Pantoea sp. YR343, and suggests that flagella play a role beyond just initial attachment. This highlights the method's potential for understanding and controlling bacterial adhesion.
Millan-Solsona, R., Brown, S. R., Zhang, L., Madugula, S. S., Zhao, H., Dumerer, B., Bible, A. N., Lavrik, N. V., Vasudevan, R. K., Biswas, A., Morrell-Falvey, J. L., Retterer, S., Checa, M., & Collins, L. (2025). Analysis of biofilm assembly by large area automated AFM. npj Biofilms and Microbiomes, 11(75).
