Hydration-controlled bacterial motility and dispersal on surfaces

Abstract

Flagellar motility, a mode of active motion shared by many prokaryotic species, is recognized as a key mechanism enabling population dispersal and resource acquisition in microbial communities living in marine, freshwater, and other liquid-replete habitats. By contrast, its role in variably hydrated habitats, where water dynamics result in fragmented aquatic habitats connected by micrometric films, is debated. Here, we quantify the spatial dynamics of Pseudomonas putida KT2440 and its nonflagellated isogenic mutant as affected by the hydration status of a rough porous surface using an experimental system that mimics aquatic habitats found in unsaturated soils. The flagellar motility of the model soil bacterium decreased sharply within a small range of water potential (0 to −2 kPa) and nearly ceased in liquid films of effective thickness smaller than 1.5 μm. However, bacteria could rapidly resume motility in response to periodic increases in hydration. We propose a biophysical model that captures key effects of hydration and liquid-film thickness on individual cell velocity and use a simple roughness network model to simulate colony expansion. Model predictions match experimental results reasonably well, highlighting the role of viscous and capillary pinning forces in hindering flagellar motility. Although flagellar motility seems to be restricted to a narrow range of very wet conditions, fitness gains conferred by fast surface colonization during transient favorable periods might offset the costs associated with flagella synthesis and explain the sustained presence of flagellated prokaryotes in partially saturated habitats such as soil surfaces.

Dispersal is recognized as a key ecological process enabling populations’ access to new sites and pools of resources (1), thereby affecting structure and productivity of ecosystems (2, 3). Active bacterial motion (motility) takes on many forms that require various appendages (4). If surface-associated modes of motility such as twitching, gliding, or swarming seem restricted to some species (5), the ability to swim by rotating one or more flagella is shared by a large diversity of prokaryotes. This swimming motility has attracted considerable attention, primarily aimed at resolving the biophysical functioning of flagella and to a lesser degree, exploring its adaptive value. In marine environments, a large fraction of bacterial populations are flagellated (6), and swimming motility is often coupled with chemotaxis, conferring a clear benefit to these cells by allowing them to outswim diffusion and exploit transient substrate gradients (7, 8).

In contrast to water-replete environments where flagellar motility is essentially unrestricted, there exists strong physical limitations to flagellar motility in partially saturated media where aquatic microhabitats are often fragmented and connected only by thin liquid films of bacterial size or smaller (9). The limitations to bacterial motility in thin liquid films have, thus, long been posited but never directly quantified or described biophysically beyond the general notion that flagellar motility requires hydrated pathways. In addition, the fitness benefit associated with flagellar motility in partially saturated soils has been debated because of conflicting experimental data (10, 11).

Here, to avoid the complexity inherent to natural partially saturated microbial habitats such as soil matrixes and benefit from direct observation of bacterial dispersal at both individual and population scales under conditions of controlled hydration, we used the porous-surface model (PSM) (12). In this experimental system, bacteria are grown on a porous ceramic surface in thin aqueous films, whose effective thickness is controlled by applying a prescribed suction similar to how matric potential controls hydration in soils. The system allowed a quantitative assessment of the dispersal rate and competition of Pseudomonas putida KT2240 and a nonflagellated ΔfliM isogenic mutant as influenced by water potential at the colony and individual scales.

Results and Discussion

At the colony scale, we observed constant front expansion rates, in accordance with the model proposed by Skellam (13) for a population dispersing by random walk and exponential growth. The average rate of colony expansion for both the wild type and nonflagellated mutant decreased with decreasing matric potential (Fig. 1). The most significant differences in expansion rates between the strains were apparent at −0.5 and −1.2 kPa, where the wild type, capable of flagellar motility, dispersed more than 15 times faster than the mutant, which dispersed by cell shoving and Brownian motion only. This clearly shows the potential of flagellar motility for fast population dispersal on wet surfaces. A role of swarming motility, which, in P. putida KT2440, relies on short pili rather than flagella, is unlikely in our experiments, because it is expressed only under specific conditions (14) and manifests itself by en masse cell movements, which we did not observe.

Fig. 1.

Matric potential affects colony-expansion rates of P. putida KT2440 wild type (flagellated) and its ΔfliM isogenic mutant (nonflagellated) measured as radial expansion of colonies initiated from single cells. More negative matric potentials correspond to thinner surface liquid films. Error bars mark 1 SD (n varies from 6 to 14). Simulated colony-expansion rates are depicted by the line and shaded area (representing 1 SD).

The colony-expansion rate of the wild type decreased exponentially from an average of 521 μm/h for the wettest conditions (−0.5 kPa) to 14 μm/h at −2.0 kPa (Fig. 1). After this sharp decrease, the colonization rate leveled, suggesting that, on the PSM, −2.0 kPa marks a threshold, below which the contribution of flagellar motility to population dispersal becomes insignificant. Under drier conditions, we expect both types of bacteria to disperse by cell shoving only and thus, their colonies to expand at similar rates. The slightly faster expansion of the wild-type colonies observed at −3.6 kPa (Fig. 1) is attributed to the higher intrinsic-growth rate of this organism. Indeed, although the only difference between mutant and wild type resides in the fliM knock-out, the former presents a significantly reduced growth rate. This was evidenced in competition experiments in stirred liquid medium where the fitness of the mutant relative to that of the wild type was significantly smaller than 1 (0.82, SD = 0.04, n = 3, P = 0.016, two-tailed t test).

The mild matric potential that we prescribed does not per se restrict bacterial motion (12), but it acts through its control of the effective liquid-film thickness on the ceramic-plate surface. The relationship between matric potential and liquid-film thickness depends solely on surface wettability and roughness (15). At −2.0 kPa, which we identified as the limit beyond which the contribution of flagellar motility to colony expansion is negligible on the ceramic plates, the predicted effective liquid film is thinner than 1.5 μm (12).

To explain the strong reduction of colony-expansion rate observed over a relatively small range of matric potentials and provide a predictive tool for bacterial-dispersal rates on partially saturated rough surfaces, a simple mechanistic model is proposed linking bacterial velocity to viscous and capillary forces acting on motile cells. The key biophysical elements of the proposed model are summarized in Fig. 2. The model considers the effects of liquid-film thinning on the propulsive force, (16), for flagellar motion at maximum velocity in bulk liquid, V₀. On partially saturated surfaces, hydrodynamic interactions between bacterial cells and solid surface hinder motion, preventing cells from attaining their maximum velocity. Considering, for simplicity, an average 45° angle between the solid surface and cell trajectory, we obtain the following hydrodynamic interactions coefficient: , given in terms of cell-surface interactions for motion parallel, λ_P (17), and normal, λ_N (18), to surface, respectively. These interactions affect bacterial cell velocity according to and are associated with a corresponding resistive force: . The most significant hindering force on partially hydrated surfaces sets in when the liquid film becomes thinner than the cell diameter, resulting in interactions with liquid–air interfaces, including formation of a contact line on the cell surface, onset of normal capillary pressure, and introduction of a capillary pinning force (F_C) (19). We combine hydration-dependent resistive forces into a simple model where attainable bacterial cell velocity is proportional to the residual force available for flagellar propulsion: , with V = 0 for .

Fig. 2.

Cell velocity within idealized surface-roughness elements under different hydration conditions. (Left) A roughness element can be abstracted as a channel of triangular section, with depth H and spanning angle α. R is the cell radius, and r(μ) is the radius of curvature of the liquid-air meniscus determined by the ambient matric potential, μ. Depending on the channel geometry, cells can either be fully or partly immersed for a given matric potential. The forces exerted on swimming cells are different in these two situations, as depicted on Right. The cell velocity is modeled for cells swimming in two channels of the same depth (H = 100 μm) but contrasting spanning angles (α = 120° or 150°). The maximum average velocity V₀ was fixed to 18 μm/s, a value typically observed in saturated systems (32). F₀, F_λ, and F_C are the viscous drag force opposing motion in bulk liquid, the viscous force associated with cell-wall interactions, and the capillary pinning force, respectively. The horizontal dashed line marks the onset of capillarity.

This model component provides estimates of the potential cell velocity for local hydration conditions (which may vary spatially over a natural surface) that may then be directed by local chemotactic gradient and a random component (tumble-like) to define the actual direction and extent of displacement during a single run (or time step). These modifications are implemented by combining the random component (tumble-like change of run direction) and local chemotactic gradients by weighing these by a factor of (1 − ξ) and ξ, respectively, depending on normalized local chemoattractant gradient, ξ (defined as the ratio of local to maximal chemotactic gradient and calculated as the concentration difference across the local bond divided by the boundary concentration). The cellular motion is evaluated every 1.1 s (an assumed duration of a run and tumble cycle) (20), and the actual run velocity is obtained as: , with describing a random direction of cell motion and describing the displacement component along the chemoattractant gradient.

To validate the proposed model, we experimentally quantified individual cell trajectories at the surface of the PSM for different matric potential values (Movies S1 and S2 show typical examples). The descriptors of individual trajectories varied considerably because of the specific microtopography experienced by each cell; however, the average velocity and dispersal distance clearly decreased with decreasing matric potential (Fig. 3). Single-cell motility was simulated by applying the model presented above to cells swimming in an idealized 2D rough surface consisting of a network of angular channels of various geometries that accommodate variable liquid configuration (21). The simulated descriptors of cell motility are in good agreement with the experimental results, even without specific parameter fitting or other adjustments (Fig. 3). These results highlight the dominant role of capillary pinning forces in constraining bacterial motility.

Fig. 3.

Comparison of experimentally observed and simulated descriptors of swimming motility on partially saturated rough surfaces. Experimental values were obtained by analyzing the trajectories of individual cells at the surface of the PSM set at various matric potentials. Simulated values are obtained by simulating the motion of 200 cells within an idealized roughness network. All of the data are expressed as mean ± SEM, with n > 248 for experimental trajectories and n = 600 for simulations. (A) Fraction of time cells display significant motility (significant motility is defined as velocities larger than 3 μm/s, the experimental detection limit). (B) Mean cell velocity during phases of significant motility. (C) Scaled maximal cellular travel distance. The maximal travel distance is the distance between the starting point of a cell and the most distant point of its trajectory. The trajectories were recorded over 28 s for experimental measurements and 33 s for simulations. The distance data were scaled by the mean maximal travel distance observed in the wettest conditions (28 and 59 μm for experiments and simulations, respectively).

Subsequently, the cell-motility model was implemented to simulate population dispersal and reproduce experimental-colony expansion rates. Cell growth and motility were modeled at the individual cell scale (22), and chemotaxis was included by biasing cell movement to neighboring channels with high nutrient content. An example of colony expansion is shown in Fig. S1. The model predictions were consistent with the experimental dispersal rates (Fig. 1), showing that population dispersal correctly emerges from the individual-scale behavior in agreement with previous theoretical derivations (13, 23, 24). SI Results and Discussion has further discussion on the comparison between the model and experiments.

As evidenced by our observations and model predictions, thin liquid films such as those found under most circumstances in soils strongly limit the dispersal rate of bacterial populations. Does flagellar motility, then, confer any selective advantage in this physically constrained environment? Competition experiments between the wild type and nonflagellated mutant, coinoculated as randomly distributed single cells at the surface of the PSM, showed hydration-conditional fitness effects (Fig. 4). At −3.6 kPa, the two strains developed colonies of similar size, and the relative fitness of the mutant was close to 1 (0.91, SD = 0.04, n = 9 and 0.96, SD = 0.03, n = 12 for low and high inoculation density, respectively). In these relatively dry conditions, the potentially motile wild type cannot disperse by flagellar motility. Therefore, the sites colonized by each strain remained spatially separated, preventing direct competition, partly alleviating the intrinsic inferiority of the mutant (25). The situation was different under wet conditions (−0.5 kPa), permissive for efficient flagellar motility. In this condition, the mutant had a very low relative fitness (0.54, SD = 0.03, n = 9 and 0.74, SD = 0.06, n = 5 for low and high inoculation density, respectively). These values are significantly smaller than those observed in liquid culture (one-tailed t test, P = 6.7 × 10⁻⁸ and P = 0.047 for low and high density, respectively), because the wild type quickly colonized the surface and thus, intercepted substrate fluxes more efficiently than the nonflagellated mutant.

Fig. 4.

The competition between P. putida KT2440 wild type (flagellated; green) and its ΔfliM isogenic mutant (nonflagellated; red) at the surface of a porous ceramic plate is affected by matric potential and inoculation density. On average, 20 and 1,500 cells were inoculated at a 1:1 strain ratio for low and high inoculation densities, respectively. The images were acquired after 2- or 5-d growth at 22 °C for −0.5 and −3.6 kPa, respectively. The plate, 4.2 cm in diameter, is limited by a silicone o-ring, which appears bright red in the pictures. Each mosaic image is composed of about 45 fields of view. The images are representative of observations made on 5–12 independent replicate plates. The contrast of the images has been digitally enhanced.

Natural partially saturated habitats such as soils and the surface of plant leaves are subject to dynamic variations in hydration conditions, the extent and frequency of which depend on climate and/or irrigation practices. To address the question of whether the occurrence of short periods of favorable wetness conditions might modify flagellar-based dispersal behavior, we experimentally evaluated the expression of flagellar motility under dry–wet cycles. Inoculated PSMs, maintained at dry conditions (−3.6 kPa), were subjected to two short daily increases in hydration status (2 × 5 min; −0.5 kPa). Despite the very short duration of the wet periods, the motile strain was able to disperse, yielding larger colonies than on the control surfaces that were continuously maintained at −3.6 kPa (Fig. S2). Accelerated surface colonization associated with dry–wet cycles was not observed for the nonflagellated mutant strain. We, therefore, conclude that P. putida KT2440 can take advantage of short and infrequent wet events to disperse by flagellar motility.

Our data show that, under conditions of partial hydration common in many terrestrial microbial habitats, the thickness and geometry of liquid films control active bacterial motion and dispersal. Viscous and capillary pinning forces reduce the swimming velocity of individual cells, resulting in low surface-colonization rates at the population scale. More than bacterial intrinsic-growth kinetic parameters, surface microtopography, hydration status, and bacterial flagellation are essential parameters in surface colonization. Because the fitness gain associated with fast dispersal can be large when nutrient-rich microsites are available (Fig. 4) and because bacteria are able to take advantage of very short wet events to disperse by flagellar motility (Fig. S2), even rare wet events could offset the cost associated with flagellar synthesis and explain the sustained presence of flagellated cells in soil habitats. This shows the very tight couplings between microbial and physical processes in soil, which mediate the emergent properties of soil systems (26).

Materials and Methods

Bacterial Strains.

P. putida KT2440, a flagellated bacterium initially isolated from the rhizosphere (27), was used as the model strain. A nonflagellated ΔfliM mutant was obtained by allelic exchange with a truncated version of fliM carrying the Gm-resistance gene aacC1 framed by lox sequences. The aacC1 gene was then excised to yield an antibiotic resistance-free mutant (28). Both strains were tagged by inserting a constitutively expressed fluorescent protein-encoding gene at a neutral position of their genome (29). To increase the fluorescence signal for single-cell observations, pJBA128, a multicopy plasmid carrying a gfp gene (30), was additionally introduced into the gfp-expressing wild-type strain. The bacteria were routinely cultivated on FAB medium (31) supplemented with 5 mM benzoate.

Experiments on the PSM.

The PSM allows growing and observing fluorescent cells at the surface of a porous ceramic plate (diameter = 4.2 cm; maximum pore size = 1.7 μm) under prescribed suction, which controls surface liquid-film thickness (12). Liquid FAB medium with 5 mM benzoate as the sole carbon source was used to wet the plate and sustain microbial growth. The inoculation of the surface of the PSM was performed as in ref. 12.

Observations of the PSM surface were realized at different scales using a Leica MZ16FA stereomicroscope. Time-lapse videos (27 s, 100 images) were acquired at high magnification (field of view = 0.15 mm²) to document swimming motility at the cell scale. Individual trajectories were detected and analyzed with Image Pro Plus (MediaCybernetics). Population-scale dispersal was quantified as previously described (12).

Competition Experiments.

To measure the relative fitness of the strains, we performed competition experiments where the abundance of the strains was measured at coinoculation time and at the end of incubation time. The fitness (W) of the mutant relative to that of the wild type was calculated as (2) (Eq. 1):

where m₀ and m_F are initial and final abundances of the mutant and wt₀ and wt_F are those of the wild type.

Relative fitnesses were estimated in stirred liquid medium (17 mL FAB, benzoate 5 mM) and at the surface of the PSM (same medium). In the latter case, the areas colonized by each strain were used as proxy for their abundance to compute relative-fitness values.

Modeling.

We modeled a population of motile cells within a surface-roughness network of size 17.2 × 17.2 mm (100 × 87 sites). The initial substrate concentration in aqueous phase was set to 0.2 mg/L and was maintained constant at the top and right boundaries of the domain. The bottom and left boundaries of the simulation domain were no-flux boundaries. Simulations were initiated by inoculating 200 bacterial cells in four sites at the bottom left corner of the domain. Triplicate simulations were conducted for each value of matric potential: −0.0001, −0.5, −1, −1.5, and −2 kPa for simulating single-cells motion and −0.5, −1, −1.5, −2, and −3.6 kPa for colony-expansion analyses. Details of the model and its parameters (Table S1 and S2) are presented in SI Materials and Methods.