Characterisation of bacterial-nanoparticle interactions via STORM and SEM: Optimising magnetic labelling strategies for biosensor integration

• Stochastic Optical Reconstruction Microscopy (STORM) imaging reveals clustered antigen epitope distribution on Bacillus cereus spores with nanometric resolution • Optimized scanning electron microscopy (SEM) protocol quantifies magnetic nanoparticle (MNP) binding and size-dependent aggregation on bacterial surfaces • 100nm MNPs show superior dispersion and minimal clustering vs. 250 nm MNPs on Bacillus cereus spore surface • Novel vacuum-assisted MNP filtration protocol enhances SEM image clarity • Integrated STORM-SEM workflow optimises magnetic labelling for biosensors Magnetic nanoparticles are critical components in biosensors for pathogen detection, enabling magnetic capture, signal amplification, and integration with microfluidic systems. However, the nanoscale mechanisms underlying magnetic nanoparticle–bacteria interactions remain poorly characterised, limiting labelling reproducibility and biosensor sensitivity. This study employed super-resolution stochastic optical reconstruction microscopy (STORM) and scanning electron microscopy (SEM) to investigate the spatial distribution of magnetic nanoparticles on 2µm polystyrene beads and Bacillus cereus spores, used as a safe surrogate for Bacillus anthracis . STORM imaging revealed clustered antibody binding at the spore periphery, consistent with structured epitope presentation in the exosporium. Over 80% of localisations were assigned to nanoclusters, confirming non-random antigen distribution. SEM analysis demonstrated that 100nm dextran-coated iron oxide magnetic nanoparticles provided superior surface dispersion and lower aggregation compared to 250nm dextran-coated iron oxide magnetic nanoparticles. A vacuum-assisted filtration protocol significantly enhanced magnetic nanoparticle uniformity and specificity while removing loosely associated aggregates. These findings support the use of 100nm magnetic nanoparticles for biosensor integration and establish a robust image-based workflow for assessing nanoparticle binding at single-cell resolution. This work provides mechanistic insight into bacterial surface labelling and offers a framework for optimising magnetic labelling strategies for future biosensing and diagnostic applications.