Using AFM and automated image analysis to study the correlation between cell shape and bacterial cell wall fibre network orientation in B. subtilis

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AFM in Life Sciences
Dr Laia Pasquina-Lemonche (3), Dr Oliver Meacock (1), Dr Abimbola Feyisara-Olulana (3), Prof Ethan Garner (2), Prof Jamie Hobbs (3)
2. Harvard University
3. University of Sheffield

AFM, high-resolution, image analysis, fibre network, bacterial cell wall, peptidoglycan, Bacillus subtilis

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To develop long-awaited new treatments for resistant infectious diseases, we need to understand vital components of bacteria cells: their cell wall (peptidoglycan, PG). However, standard techniques lack resolution to provide a molecular description of PG. Here I will apply ultra-resolution microscopy and software analysis to quantitatively decipher the PG fibrous network with unprecedented resolution. This will allow us to understand the relationship between cell shape, PG synthesis and PG architecture, fuelling rational design of new antimicrobials to find better solutions against resistant strains.

After years of research using atomic force microscopy (AFM), the conclusion is that the cell wall, composed mainly of peptidoglycan is a highly porous heterogeneous hydrogel with four different architectures [1]. In this project, we use PeakForce Tapping mode to decipher the molecular architecture (on the order of 1 nm) of Bacillus subtilis PG. The architecture is a complex mesh composed of pores and a fibre network with different orientations depending on the region and age of the cell. B. subtilis is a rod and it has two types of synthesis machineries with different trajectories: the MreB protein moves in helical trajectories along the short axis of the cell and the PBP2 protein moves randomly distributed along the cell [2]. Therefore, mutant strains where the activity of MreB or PBP2 proteins can be either overexpressed or underexpressed were imaged with high resolution AFM. The PG fibre network from their internal region were imaged and analysed with a custom-made automated analysis routine, removing human bias and unprecedentedly increasing the data points/image to 106 [3]. The results from this work shed light into the relationship between the proteins trajectories, the cell shape and the peptidoglycan organisation at nanometric level.


[1] L. Pasquina-Lemonche*, J. Burns*, et al. Nature, 582, 294-297 (2020). 

[2] Dion MF, Kapoor M, Sun Y, et al. Nat Microbiol. 4(8):1294-1305. (2019)

[3] O. Meacock*, L. Pasquina-Lemonche*, A. Feyisara-Ouluana, W. M Durham, E. Garner, S. J Foster, J. K Hobbs (in preparation).