Uncovering bacterial-mammalian cell interactions via single-cell tracking.

BACKGROUND: The interactions between bacterial pathogens and host cells are characterized by a multitude of complexities, leading to a wide range of heterogeneous outcomes. Despite extensive research, we still have a limited understanding of how bacterial motility in complex environments impacts their ability to tolerate antibiotics and adhere to mammalian cell surfaces. The challenge lies in unraveling the complexity of these interactions and developing quantitative microscopy approaches to predict the behavior of bacterial populations. RESULTS: To address this challenge, we directed our efforts towards Pseudomonas aeruginosa, a pathogenic bacterium known for producing thick films in the lungs of cystic fibrosis patients, and Escherichia coli, used as a proof of concept to develop and demonstrate our single-cell tracking approaches. Our results revealed that P. aeruginosa exhibits diverse and complex interactions on mammalian cell surfaces, such as adhesion, rotational motion, and swimming, unlike the less interactive behavior of Escherichia coli. Our analysis indicated that P. aeruginosa demonstrated lower mean-squared displacement (MSD) values and greater adherence to mammalian cells compared to E. coli, which showed higher MSD slopes and less frequent adherence. Genetic mutations in membrane proteins of P. aeruginosa resulted in altered displacement patterns and reduced adhesion, with the ΔfliD mutant displaying a more Gaussian displacement distribution and significantly less adherence to mammalian cells. Adhesion and tolerance mechanisms are diverse and complex, potentially involving distinct pathways; however, our findings highlight the therapeutic potential of targeting the fliD gene (encoding a critical flagellum protein), as its deletion not only reduced adherence but also antibiotic tolerance. CONCLUSIONS: Overall, our findings underscore the importance of single cell tracking in accurately assessing bacterial behavior over short time periods and highlight its significant potential in guiding effective intervention strategies.