High-resolution imaging of bacterial spatial organization with vertical cell imaging by nanostructured immobilization (VerCINI)

Molecular motor tug-of-war regulates elongasome cell wall synthesis dynamics in Bacillus subtilis

Most rod-shaped bacteria elongate by inserting new cell wall material into the inner surface of the cell sidewall. This is performed by class A penicillin binding proteins (PBPs) and a highly conserved protein complex, the elongasome, which moves processively around the cell circumference and inserts long glycan strands that act as barrel-hoop-like reinforcing structures, thereby giving rise to a rod-shaped cell. However, it remains unclear how elongasome synthesis dynamics and termination events are regulated to determine the length of these critical cell-reinforcing structures. To address this, we developed a method to track individual elongasome complexes around the entire circumference of Bacillus subtilis cells for minutes-long periods using single-molecule fluorescence microscopy. We found that the B. subtilis elongasome is highly processive and that processive synthesis events are frequently terminated by rapid reversal or extended pauses. We found that cellular levels of RodA regulate elongasome processivity, reversal and pausing. Our single-molecule data, together with stochastic simulations, show that elongasome dynamics and processivity are regulated by molecular motor tug-of-war competition between several, likely two, oppositely oriented peptidoglycan synthesis complexes associated with the MreB filament. Altogether these results demonstrate that molecular motor tug-of-war is a key regulator of elongasome dynamics in B. subtilis, which likely also regulates the cell shape via modulation of elongasome processivity.

Honeycomb gold specimen supports enabling orthogonal focussed ion beam-milling of elongated cells for cryo-ET

Cryo-focussed ion beam (FIB)-milling is a powerful technique that opens up thick, cellular specimens to high-resolution structural analysis by electron cryotomography (cryo-ET). FIB-milled lamellae can be produced from cells on grids, or cut from thicker, high-pressure frozen specimens. However, these approaches can put geometrical constraints on the specimen that may be unhelpful, particularly when imaging structures within the cell that have a very defined orientation. For example, plunge frozen rod-shaped bacteria orient parallel to the plane of the grid, yet the Z-ring, a filamentous structure of the tubulin-like protein FtsZ and the key organiser of bacterial division, runs around the circumference of the cell such that it is perpendicular to the imaging plane. It is therefore difficult or impractical to image many complete rings with current technologies. To circumvent this problem, we have fabricated monolithic gold specimen supports with a regular array of cylindrical wells in a honeycomb geometry, which trap bacteria in a vertical orientation. These supports, which we call "honeycomb gold discs", replace standard EM grids and when combined with FIB-milling enable the production of lamellae containing cross-sections through cells. The resulting lamellae are more stable and resistant to breakage and charging than conventional lamellae. The design of the honeycomb discs can be modified according to need and so will also enable cryo-ET and cryo-EM imaging of other specimens in otherwise difficult to obtain orientations.

Peptidoglycan synthesis drives a single population of septal cell wall synthases during division in Bacillus subtilis

Bacterial cell division requires septal peptidoglycan (sPG) synthesis by the divisome complex. Treadmilling of the essential tubulin homologue FtsZ has been implicated in septal constriction, though its precise role remains unclear. Here we used live-cell single-molecule imaging of the divisome transpeptidase PBP2B to investigate sPG synthesis dynamics in Bacillus subtilis. In contrast to previous models, we observed a single population of processively moving PBP2B molecules whose motion is driven by peptidoglycan synthesis and is not associated with FtsZ treadmilling. However, despite the asynchronous motions of PBP2B and FtsZ, a partial dependence of PBP2B processivity on FtsZ treadmilling was observed. Additionally, through single-molecule counting experiments we provide evidence that the divisome synthesis complex is multimeric. Our results support a model for B. subtilis division where a multimeric synthesis complex follows a single track dependent on sPG synthesis whose activity and dynamics are asynchronous with FtsZ treadmilling.

Single-cell patterning and characterisation of antibiotic persistent bacteria using bio-sCAPA

In microbiology, accessing single-cell information within large populations is pivotal. Here we introduce bio-sCAPA, a technique for patterning bacterial cells in defined geometric arrangements and monitoring their growth in various nutrient environments. We demonstrate bio-sCAPA with a study of subpopulations of antibiotic-tolerant bacteria, known as persister cells, which can survive exposure to high doses of antibiotics despite lacking any genetic resistance to the drug. Persister cells are associated with chronic and relapsing infections, yet are difficult to study due in part to a lack of scalable, single-cell characterisation methods. As >105 cells can be patterned on each template, and multiple templates can be patterned in parallel, bio-sCAPA allows for very rare population phenotypes to be monitored with single-cell precision across various environmental conditions. Using bio-sCAPA, we analysed the phenotypic characteristics of single Staphylococcus aureus cells tolerant to flucloxacillin and rifampicin killing. We find that antibiotic-tolerant S. aureus cells do not display significant heterogeneity in growth rate and are instead characterised by prolonged lag-time phenotypes alone.

DeepBacs for multi-task bacterial image analysis using open-source deep learning approaches

This work demonstrates and guides how to use a range of state-of-the-art artificial neural-networks to analyse bacterial microscopy images using the recently developed ZeroCostDL4Mic platform. We generated a database of image datasets used to train networks for various image analysis tasks and present strategies for data acquisition and curation, as well as model training. We showcase different deep learning (DL) approaches for segmenting bright field and fluorescence images of different bacterial species, use object detection to classify different growth stages in time-lapse imaging data, and carry out DL-assisted phenotypic profiling of antibiotic-treated cells. To also demonstrate the ability of DL to enhance low-phototoxicity live-cell microscopy, we showcase how image denoising can allow researchers to attain high-fidelity data in faster and longer imaging. Finally, artificial labelling of cell membranes and predictions of super-resolution images allow for accurate mapping of cell shape and intracellular targets. Our purposefully-built database of training and testing data aids in novice users' training, enabling them to quickly explore how to analyse their data through DL. We hope this lays a fertile ground for the efficient application of DL in microbiology and fosters the creation of tools for bacterial cell biology and antibiotic research.