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Swarming is a collective form of coordinated bacterial motility that increases antibiotic resistance and production of virulence factors in the host1,2,3. This multicellular behavior occurs on semi-solid surfaces that resemble those of mucous layers covering epithelial membranes in the lungs4,5. Biosurfactants are commonly produced by swarming populations to overcome the surface tension on surfaces and the production of these is regulated by complex cell-cell signaling systems, also known as quorum sensing6,7,8. Many species of bacteria are capable of swarming, including Pseudomonas aeruginosa, Staphylococcus aureus, and Escherichia coli9,10,11,12. The swarming patterns created by bacteria are diverse and are affected by the physical and chemical properties of the surface layer including nutrient composition, porosity, and moisture13,14. In addition to surface properties, growth temperature and ambient humidity affect several aspects of swarming dynamics, including swarming rate and patterns12,13,14,15. The growth variables that affect swarming create challenges that impact experimental reproducibility and the ability to interpret results. Here, we describe a simple standardized method to monitor the dynamics of bacterial swarms through time-lapse imaging. The method describes how to control critical growth conditions that significantly affect the progression of swarming. Compared to traditional methods of swarm analysis, this time-lapse imaging method enables tracking the motility of multiple swarms concurrently during extended periods of time and with high resolution. These aspects improve the depth of data that can be gained from monitoring swarms and facilitate the identification of factors that affect swarming.
Swarming in P. aeruginosa is facilitated through the production and release of rhamnolipids and 3-(3-hydroxyalkanoyloxy)alkanoic acids into the surrounding area6,16. The introduction of stress from sub-lethal concentrations of antibiotics or infection by phage virus impacts the organization of swarms. In particular, these stresses induce P. aeruginosa to release the quorum sensing molecule 2-heptyl-3-hydroxy-4-quinolone, also known as the Pseudomonas quinolone signal (PQS)17,18. In swarm assays that contain two populations of swarms, PQS produced by the stress-induced population repels untreated swarms from entering the area containing the stress (Figure 1). This collective stress response constitutes a danger communication signaling system that warns P. aeruginosa about nearby threats18,19. The effects of stress on P. aeruginosa, the activation of the collective stress response, and the repulsion of swarms can be visualized using the time-lapse imaging method described here. The protocol described here explains how to: (1) prepare agar plates for swarming, (2) culture P. aeruginosa for two types of assays (traditional swarming assays or collective stress response assays) (Figure 1), (3) acquire time-lapse images, and (4) use ImageJ to compile and analyze the images.
Briefly, P. aeruginosa from an overnight culture is spotted in the middle of a swarming agar plate while P. aeruginosa that are infected with phage or treated with antibiotics are spotted at the satellite positions. The progression of P. aeruginosa swarming is monitored on a consumer document flatbed scanner that is placed in a humidity-regulated 37 °C incubator. The scanner is controlled by a software that automatically scans the plates at regular intervals over the swarm growth period, typically 16–20 h. This method yields concurrent time-lapse videos of up to six 10 cm swarming plates. The images are compiled into movies and the repulsion of swarms by stress-induced populations is quantified by using freely available ImageJ software. Special consideration is given to ensure consistency and reproducibility between different swarming experiments.