How P. aeruginosa cells with diverse stator composition collectively swarm

Abstract

Swarming is a macroscopic phenomenon in which surface bacteria organize into a motile population. The flagellar motor that drives swarming in Pseudomonas aeruginosa is powered by stators MotAB and MotCD. Deletion of the MotCD stator eliminates swarming, whereas deletion of the MotAB stator enhances swarming. Interestingly, we measured a strongly asymmetric stator availability in the wild-type (WT) strain, with MotAB stators produced at an approximately 40-fold higher level than MotCD stators. However, utilization of MotCD stators in free swimming cells requires higher liquid viscosities, while MotAB stators are readily utilized at low viscosities. Importantly, we find that cells with MotCD stators are ~10× more likely to have an active motor compared to cells uses the MotAB stators. The spectrum of motility intermittency can either cooperatively shut down or promote flagellum motility in WT populations. In P. aeruginosa, transition from a static solid-like biofilm to a dynamic liquid-like swarm is not achieved at a single critical value of flagellum torque or stator fraction but is collectively controlled by diverse combinations of flagellum activities and motor intermittencies via dynamic stator utilization. Experimental and computational results indicate that the initiation or arrest of flagellum-driven swarming motility does not occur from individual fitness or motility performance but rather related to concepts from the "jamming transition" in active granular matter.IMPORTANCEIt is now known that there exist multifactorial influences on swarming motility for P. aeruginosa, but it is not clear precisely why stator selection in the flagellum motor is so important. We show differential production and utilization of the stators. Moreover, we find the unanticipated result that the two motor configurations have significantly different motor intermittencies: the fraction of flagellum-active cells in a population on average with MotCD is active ~10× more often than with MotAB. What emerges from this complex landscape of stator utilization and resultant motor output is an intrinsically heterogeneous population of motile cells. We show how consequences of stator recruitment led to swarming motility and how the stators potentially relate to surface sensing circuitry.

Keywords: crowded environment; flagellar motility; flagellar shut-down; heterogeneous populations; intermittency; stators; swarming; unjamming.

Fig 1

Convergence of swimming speeds by the MotCD motor to the WT and MotAB motors with increasing viscosity and asymmetric production of stator-type sets in WT. (A) The dual proton-driven stator system, MotAB and MotCD, of P. aeruginosa. Stators are utilized to provide the torque necessary to rotate the flagella. Three motor configurations can be formed: the swarming MotABCD (WT) motor, the swarming deficient MotAB motor, and hyper-swarmer MotCD motor. A representative swarming pattern for each motor type is presented above each stator set. (B) Measurement of swimming speeds for the three stator configurations harvested from a liquid planktonic or swarming culture: two-stator WT (MotABCD) and the MotAB and MotCD single-stator motors at different viscosities (by increasing the percent concentration of methylcellulose in solution). At least 100 trajectories per viscosity condition were measured. Error bars denote the first and third quartiles of the distribution about the mean. (C) Western blot detection of the MotA::His₆ and MotC::His₆ epitope-tagged proteins expressed in membrane fractions of the strains indicated. In lanes 1 through 3, the proteins are expressed from the respective endogenous loci under native promoter control. Samples in lane 3 are derived from the strain in which both the motA and motC genes express the respective proteins fused to the His₆ epitope. In lanes 4 and 5, samples from the ΔmotC strain harbor either the empty vector control (lane 4) or a multi-copy plasmid for expression of the MotC::His₆ protein under arabinose induction via the P_bad promoter. Arrows point to the location of the indicated proteins. The asterisk (*) indicates a non-specific band present in all samples and used as a normalization control for quantification. Strains were grown for 16 hours in either liquid (top panel) or swarm agar plates (bottom panel) with 0.05% arabinose to induce plasmid-borne MotC::His₆ expression. Proteins were detected using an anti-His₆ monoclonal antibody. The bar plot on the right shows the quantification of the MotA::His₆ and MotC::His₆ proteins from three biological replicates of samples from the motA::His₆ motC::His₆ double-tagged strain grown under the indicated conditions (panel d, lane 3, top and bottom). Data were analyzed by one-way analysis of variance followed by Tukey’s post-test comparison. ns, not significantly different.

Fig 2

Measurement of fraction of active cells and their swimming speeds in the stagnant liquid agar swarming lag phase environment. (A) Diagram of a swarming plate assay experiment. Three stages illustrated: (i) inoculation of cells from liquid growth culture, (ii) a swarming lag phase before cells reach confluency, and (iii) the collective swarming expansion. (B) Illustration of experimental setup used for the swarming lag phase microenvironment (left). Two distinct populations were identified in this microenvironment setup (right): flagellar motile cells showed ballistic motion, while flagellar immotile cells moved with a diffusive motion. (C) The flagellar motile fraction was quantified using the categories described in B. The population activity was tracked every 2 hours for 3 min, over a period of 8 hours. Three replicates were used per strain; at least 140 trajectories were used per timepoint for each replicate. (D) Measured swimming speeds performed by the flagellar motile population in plot C. At least 200 trajectories per timepoint. Error bars denote the first and third quartiles of the distribution about the mean.

Fig 3

Single-cell motility measurement of cells in a crowded environment of their own kin and 2D confinement. (A) Diagram of experimental setup for tracking swarming bacteria on a soft agar medium surface (top left). Cells harvested from a swarm plate with 1%–5% (vol/vol) co-culture of cells carrying a constitutively expressed copy of GFP on a plasmid (lower left, right). This approach permitted precise single-cell tracking in an environment crowded with thousands of cells per field of view. Scale bar in zoom-in inserts, 10 µm. (B) Representative trajectories of tracked cells in the crowded environment over a period of 30 seconds. The trajectories presented for each indicated strain come from a compilation of different fields of view from at least three replicates. (C) Violin plot of measured radius of gyration for the single-cell trajectories in the crowded environment for the three indicated strains, as displayed in B. At least 139 cells were tracked per strain. (D) Co-inoculation containing a small fraction of cells, 5%–20% (vol/vol), with a FliC^T394C mutation for maleimide staining, was used for direct quantification of actively rotating flagella. The bar plot on the right reports the fraction of active flagella observed for each strain. At least 12 fields of view from four replicates were used and at least 200 flagella per strain were counted. Scale bar, 5 µm. (E) Swimming speeds of cells moving in a 2D thin liquid volume medium confined between a 0.55% agar surface and imaging glass coverslip, under a diluted cell volume fraction, Φ (Movie S4). At least 180 trajectories were measured per strain. For panels C–E, data sets were analyzed by one-way analysis of variance followed by Tukey’s post-test comparison. *P  <  0.05, **P < 0.001; ns, not significantly different.

Fig 4

Physical modeling of the crowded environment predicts a landscape of unjamming transitions for different combinations of the flagellum motor force output and fraction of active flagellum cells. (A) Simulations of a crowd of self-propelled rods to evaluate the influence of population heterogeneity, flagellar motile vs immotile, with varying flagellar force outputs on collective motility. The simulations were tested at a volume fraction (Φ) of 0.96 and cell aspect ratio of 4. The fraction of motile particles (θ_MO) and their flagellar output (F_f) were varied. (B) Normalized mean radius of gyration, Rg_N, for the particles in the tested crowded systems as illustrated in A. The values were normalized by the mean radius of gyration of the homogeneous system with all immotile particles (F_f = 0). Contour map was estimated by interpolation between the grid of tested conditions (circular markers). (C) The asymmetry in translational movement between the motile and immotile fractions for the heterogeneous systems was measured as the ratio in mean Rg for the two populations (Rg_IM/Rg_MO). An Rg_IM/Rg_MO < 1 corresponds to longer trajectories performed by the motile fraction, relative to the motility that the motile fraction induced on the immotile fraction in the crowd; a ratio of 1 corresponds to equal degree of translation performed by both immotile and motile particles. (D) Normalized swarming area as a function of increased concentration of the swarming strain (WT and MotCD motors) in mixed culture with the flagellum-deficient ΔflgK mutant. The ΔflgK strain lacks a functional flagellum and, hence, is swarming deficient. Error bars denote the quartiles of the distribution about the mean.

Fig 5

Increasing MotCD:MotAB ratio leads to increased swarming motility. (A) Expression of MotCD via an arabinose-inducible plasmid (pMotCD) increases WT swarming phenotype (pMQ72 is an empty vector control). All strains were grown in soft agar swarming plates with 1% arabinose. No significant difference was observed between the WT/pMQ72 and WT/pMotCD at 0% arabinose. At least six plate replicates per condition. Error bars denote the first and third quartiles of the distribution about the mean. (B) Alternative expression via arabinose-inducible plasmid of MotCD (pMotCD) or MotAB (pMotAB) in the MotAB motor or MotCD motor strain, respectively. Progressive expression of pMotCD induced swarming motility in non-swarming MotAB motor, even to comparable levels to MotCD motor strain swarming; inversely, increasing induction of pMotAB leads to a progressive swarming arrest of hyper-swarming MotCD motor strain. (C) Quantification of flagellar motile fraction at 0.2% arabinose induction of pMotCD or pMotAB in the MotAB motor or MotCD motor strain, respectively. pMotCD increased fraction of motile cells in the MotAB motor strain, while pMotAB reduced the flagellar motile fraction in the MotCD motor strain. *P  <  0.05, **P < 0.001; ns, not significantly different. Data were analyzed by one-way analysis of variance followed by Tukey’s post-test comparison. Lower panel shows representative segmented swarm areas for the four different stator ratio configurations. (D) Model of stator-type dynamics and their expected influence on the motor intermittency in a crowded swarming environment (high flagellar load). All three motor types are expected to maximize flagellar output under this viscous condition, i.e., motors fully or mostly decorated with stators. The WT heterogeneous motor asymmetrically uses MotAB stators due to its higher affinity at low-to-mid range viscosities and elevated expression compared to the MotCD stator (Fig. 1B and C). To further hinder the motor utilization of MotCD, we previously described the cyclic di-GMP-dependent binding of FlgZ to the MotC subunit of this stator and its sequestering from the motor (15, 42). We postulate here that the presence of MotCD stators helps stabilize the flagellum activity, i.e., maintaining an active flagellar motor. The MotCD motor sustains populations a high flagellar motile fraction. In contrast, the MotAB motor is prone to a flagellar shutdown with an extremely low flagellar motile fraction. We propose that the rivaling influence of MotAB and MotCD on the flagellar motor is dependent on the relative levels of “free” available stators between the two stator types, with such availabilities being influenced by stator production and molecular interactions. Hence, as well as modulating the flagellar torque output, the MotAB and MotCD stators may integrate molecular signals to regulate the flagellar activity state, long-term intermittency, among the heterogeneous population.