Hyperswarming adaptations in a bacterium improve collective motility without enhancing single cell motility

Swarming of P. aeruginosa: Through the lens of biophysics

Swarming is a collective flagella-dependent movement of bacteria across a surface that is observed across many species of bacteria. Due to the prevalence and diversity of this motility modality, multiple models of swarming have been proposed, but a consensus on a general mechanism for swarming is still lacking. Here, we focus on swarming by Pseudomonas aeruginosa due to the abundance of experimental data and multiple models for this species, including interpretations that are rooted in biology and biophysics. In this review, we address three outstanding questions about P. aeruginosa swarming: what drives the outward expansion of a swarm, what causes the formation of dendritic patterns (tendrils), and what are the roles of flagella? We review models that propose biologically active mechanisms including surfactant sensing as well as fluid mechanics-based models that consider swarms as thin liquid films. Finally, we reconcile recent observations of P. aeruginosa swarms with early definitions of swarming. This analysis suggests that mechanisms associated with sliding motility have a critical role in P. aeruginosa swarm formation.

How individual P. aeruginosa cells with diverse stator distributions collectively form a heterogeneous macroscopic swarming population

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 WT strain, with MotAB stators produced ∼40-fold more than MotCD stators. However, recruitment of MotCD stators in free swimming cells requires higher liquid viscosities, while MotAB stators are readily recruited at low viscosities. Importantly, we find that cells with MotCD stators are ∼10x more likely to have an active motor compared to cells without, so wild-type, WT, populations are intrinsically heterogeneous and not reducible to MotAB-dominant or MotCD-dominant behavior. 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 recruitment. 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.

Importance

After extensive study, it is now known that there exist multifactorial influences on swarming motility in P. aeruginosa , but it is not clear precisely why stator selection in the flagellum motor is so important or how this process is collectively initiated or arrested. Here, we show that for P. aeruginosa PA14, MotAB stators are produced ∼40-fold more than MotCD stators, but recruitment of MotCD over MotAB stators requires higher liquid viscosities. 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 active ∼10x more often than MotAB. What emerges from this complex landscape of stator recruitment 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 they potentially relate to surface sensing circuitry.

Long-range alteration of the physical environment mediates cooperation between Pseudomonas aeruginosa swarming colonies

Pseudomonas aeruginosa makes and secretes massive amounts of rhamnolipid surfactants that enable swarming motility over biogel surfaces. But how these rhamnolipids interact with biogels to assist swarming remains unclear. Here, I use a combination of optical techniques across scales and genetically engineered strains to demonstrate that rhamnolipids can induce agar gel swelling over distances >10,000× the body size of an individual cell. The swelling front is on the micrometric scale and is easily visible using shadowgraphy. Rhamnolipid transport is not restricted to the surface of the gel but occurs through the whole thickness of the plate and, consequently, the spreading dynamics depend on the local thickness. Surprisingly, rhamnolipids can cross the whole gel and induce swelling on the opposite side of a two-face Petri dish. The swelling front delimits an area where the mechanical properties of the surface properties are modified: water wets the surface more easily, which increases the motility of individual bacteria and enables collective motility. A genetically engineered mutant unable to secrete rhamnolipids (ΔrhlA), and therefore unable to swarm, is rescued from afar with rhamnolipids produced by a remote colony. These results exemplify the remarkable capacity of bacteria to change the physical environment around them and its ecological consequences.

Enterobacter sp. Strain SM1_HS2B Manifests Transient Elongation and Swimming Motility in Liquid Medium

Many species of bacteria change their morphology and behavior under external stresses. In this study, we report transient elongation and swimming motility of a novel Enterobacter sp. strain, SM1_HS2B, in liquid broth under a standard growth condition. When growing in the Luria-Bertani medium, HS2B cells delay their cell division and elongate. Although transient over a few hours, the average cell length reaches over 10 times that of the stationary-state cells. The increase is also cumulative following repeated growth cycles stimulated by taking cells out of the exponential phase and adding them into fresh medium every 2 hours. The majority of the cells attain swimming motility during the exponential growth phase, and then they lose swimming motility over the course of several hours. Both daughter cells due to division of a long swimming cell retain the ability to swim. We confirm that the long HS2B cells swim with rigid-body rotation along their body axis. These findings based on microscopic observation following repeated cycles of growth establish HS2B as a prototype strain with sensitive dependence of size and motility on its physical and biochemical environment. IMPORTANCE Bacteria undergo morphological changes in order to cope with external stresses. Among the best-known examples are cell elongation and hyperflagellation in the context of swarming motility. The subject of this report, SM1_HS2B, is a hyperswarming strain of a newly identified species of enterobacteria, noted as Enterobacter sp. SM1. The key finding that SM1_HS2B transiently elongates to extreme length in fresh liquid medium offers new insights on regulation in bacterial growth and division. SM1_HS2B also manifests transient but vigorous swimming motility during the exponential phase of growth in liquid medium. These properties establish HS2B as a prototype strain with sensitive dependence of size and motility on its physical and biochemical environment. Such a dependence may be relevant to swarming behavior with a significant environmental or physiological outcome.

Methods to Evaluate Bacterial Motility and Its Role in Bacterial–Host Interactions

Bacterial motility is a widespread characteristic that can provide several advantages for the cell, allowing it to move towards more favorable conditions and enabling host-associated processes such as colonization. There are different bacterial motility types, and their expression is highly regulated by the environmental conditions. Because of this, methods for studying motility under realistic experimental conditions are required. A wide variety of approaches have been developed to study bacterial motility. Here, we present the most common techniques and recent advances and discuss their strengths as well as their limitations. We classify them as macroscopic or microscopic and highlight the advantages of three-dimensional imaging in microscopic approaches. Lastly, we discuss methods suited for studying motility in bacterial–host interactions, including the use of the zebrafish model.

Evidence for biosurfactant-induced flow in corners and bacterial spreading in unsaturated porous media

The spread of pathogenic bacteria in unsaturated porous media, where air and liquid coexist in pore spaces, is the major cause of soil contamination by pathogens, soft rot in plants, food spoilage, and many pulmonary diseases. However, visualization and fundamental understanding of bacterial transport in unsaturated porous media are currently lacking, limiting the ability to address the above contamination- and disease-related issues. Here, we demonstrate a previously unreported mechanism by which bacterial cells are transported in unsaturated porous media. We discover that surfactant-producing bacteria can generate flows along corners through surfactant production that changes the wettability of the solid surface. The corner flow velocity is on the order of several millimeters per hour, which is the same order of magnitude as bacterial swarming, one of the fastest known modes of bacterial surface translocation. We successfully predict the critical corner angle for bacterial corner flow to occur based on the biosurfactant-induced change in the contact angle of the bacterial solution on the solid surface. Furthermore, we demonstrate that bacteria can indeed spread by producing biosurfactants in a model soil, which consists of packed angular grains. In addition, we demonstrate that bacterial corner flow is controlled by quorum sensing, the cell-cell communication process that regulates biosurfactant production. Understanding this previously unappreciated bacterial transport mechanism will enable more accurate predictions of bacterial spreading in soil and other unsaturated porous media.

Mechanistic underpinning of cell aspect ratio-dependent emergent collective motions in swarming bacteria

Self-propelled bacteria can exhibit a large variety of non-equilibrium self-organized phenomena. Swarming is one such fascinating dynamical scenario where a number of motile individuals group into dynamical clusters and move in synchronized flows and vortices. While precedent investigations into rod-like particles confirm that an increased aspect-ratio promotes alignment and order, recent experimental studies in bacteria Bacillus subtilis show a non-monotonic dependence of the cell-aspect ratio on their swarming motion. Here, by computer simulations of an agent-based model of self-propelled, mechanically interacting, rod-shaped bacteria under overdamped conditions, we explore the collective dynamics of a bacterial swarm subjected to a variety of cell-aspect ratios. When modeled with an identical self-propulsion speed across a diverse range of cell aspect ratios, simulations demonstrate that both shorter and longer bacteria exhibit slow dynamics whereas the fastest speed is obtained at an intermediate aspect ratio. Our investigation highlights that the origin of this observed non-monotonic trend of bacterial speed and vorticity with the cell-aspect ratio is rooted in the cell-size dependence of motility force. The swarming features remain robust for a wide range of surface density of the cells, whereas asymmetry in friction attributes a distinct effect. Our analysis identifies that at an intermediate aspect ratio, an optimum cell size and motility force promote alignment, which reinforces the mechanical interactions among neighboring cells leading to the overall fastest motion. Mechanistic underpinning of the collective motions reveals that it is a joint venture of the short-range repulsive and the size-dependent motility forces, which determines the characteristics of swarming.

Information and motility exchange in collectives of active particles

We examine the interplay of motility and information exchange in a model of run-and-tumble active particles where the particle's motility is encoded as a bit of information that can be exchanged upon contact according to the rules of AND and OR logic gates in a circuit. Motile AND particles become non-motile upon contact with a non-motile particle. Conversely, motile OR particles remain motile upon collision with their non-motile counterparts. AND particles that have become non-motile additionally "reawaken", i.e., recover their motility, at a fixed rate μ, as in the SIS (susceptible, infected, susceptible) model of epidemic spreading, where an infected agent can become healthy again, but keeps no memory of the recent infection, hence it is susceptible to a renewed infection. For μ = 0, both AND and OR particles relax irreversibly to absorbing states of all non-motile or all motile particles, respectively. The relaxation kinetics is, however, faster for OR particles that remain active throughout the process. At finite μ, the AND dynamics is controlled by the interplay between reawakening and collision rates. The system evolves to a state of all motile particles (an absorbing state in the language of absorbing phase transitions) for μ > μc and to a mixed state with coexisting motile and non-motile particles (an active state in the language of absorbing phase transitions) for μ < μc. The final state exhibits a rich structure controlled by motility-induced aggregation. Our work can be relevant to biochemical signaling in motile bacteria, the spreading of epidemics and of social consensus, as well as light-controlled organization of active colloids.

Collective Dynamics of Model Pili-Based Twitcher-Mode Bacilliforms

Pseudomonas aeruginosa, like many bacilliforms, are not limited only to swimming motility but rather possess many motility strategies. In particular, twitching-mode motility employs hair-like pili to transverse moist surfaces with a jittery irregular crawl. Twitching motility plays a critical role in redistributing cells on surfaces prior to and during colony formation. We combine molecular dynamics and rule-based simulations to study twitching-mode motility of model bacilliforms and show that there is a critical surface coverage fraction at which collective effects arise. Our simulations demonstrate dynamic clustering of twitcher-type bacteria with polydomains of local alignment that exhibit spontaneous correlated motions, similar to rafts in many bacterial communities.

Reentrant Efficiency of Phototaxis in Chlamydomonas reinhardtii Cells

Phototaxis is one of the most fundamental stimulus-response behaviors in biology wherein motile microorganisms sense light gradients to swim toward the light source. Apart from single-cell survival and growth, it plays a major role at the global scale of aquatic ecosystems and bioreactors. We study phototaxis of single-celled algae Chlamydomonas reinhardtii as a function of cell number density and light stimulus using high spatiotemporal video microscopy. Surprisingly, the phototactic efficiency has a minimum at a well-defined number density, for a given light gradient, above which the phototaxis behavior of a collection of cells can even exceed the performance obtainable from single isolated cells. We show that the origin of enhancement of performance above the critical concentration lies in the slowing down of the cells, which enables them to sense light more effectively. We also show that this steady-state phenomenology is well captured by modeling the phototactic response as a density-dependent torque acting on an active Brownian particle.

The Ultimate Guide to Bacterial Swarming: An Experimental Model to Study the Evolution of Cooperative Behavior

Cooperation has fascinated biologists since Darwin. How did cooperative behaviors evolve despite the fitness cost to the cooperator? Bacteria have cooperative behaviors that make excellent models to take on this age-old problem from both proximate (molecular) and ultimate (evolutionary) angles. We delve into Pseudomonas aeruginosa swarming, a phenomenon where billions of bacteria move cooperatively across distances of centimeters in a matter of a few hours. Experiments with swarming have unveiled a strategy called metabolic prudence that stabilizes cooperation, have showed the importance of spatial structure, and have revealed a regulatory network that integrates environmental stimuli and direct cooperative behavior, similar to a machine learning algorithm. The study of swarming elucidates more than proximate mechanisms: It exposes ultimate mechanisms valid to all scales, from cells in cancerous tumors to animals in large communities.

Evolution at the Edge of Expanding Populations

Predicting the evolution of expanding populations is critical to controlling biological threats such as invasive species and cancer metastasis. Expansion is primarily driven by reproduction and dispersal, but nature abounds with examples of evolution where organisms pay a reproductive cost to disperse faster. When does selection favor this "survival of the fastest"? We searched for a simple rule, motivated by evolution experiments where swarming bacteria evolved into a hyperswarmer mutant that disperses ∼100% faster but pays a growth cost of ∼10% to make many copies of its flagellum. We analyzed a two-species model based on the Fisher equation to explain this observation: the population expansion rate (v) results from an interplay of growth (r) and dispersal (D) and is independent of the carrying capacity: v = 2 ( rD ) 1 / 2 . A mutant can take over the edge only if its expansion rate (v2) exceeds the expansion rate of the established species (v1); this simple condition ( v 2 > v 1 ) determines the maximum cost in slower growth that a faster mutant can pay and still be able to take over. Numerical simulations and time-course experiments where we tracked evolution by imaging bacteria suggest that our findings are general: less favorable conditions delay but do not entirely prevent the success of the fastest. Thus, the expansion rate defines a traveling wave fitness, which could be combined with trade-offs to predict evolution of expanding populations.

Connecting single-cell properties to collective behavior in multiple wild isolates of the Enterobacter cloacae complex

Some strains of motile bacteria self-organize to form spatial patterns of high and low cell density over length scales that can be observed by eye. One such collective behavior is the formation in semisolid agar media of a high cell density swarm band. We isolated 7 wild strains of the Enterobacter cloacae complex capable of forming this band and found its propagation speed can vary 2.5 fold across strains. To connect such variability in collective motility to strain properties, each strain’s single-cell motility and exponential growth rates were measured. The band speed did not significantly correlate with any individual strain property; however, a multilinear analysis revealed that the band speed was set by a combination of the run speed and tumbling frequency. Comparison of variability in closely-related wild isolates has the potential to reveal how changes in single-cell properties influence the collective behavior of populations.

Metabolism and the Evolution of Social Behavior

How does metabolism influence social behavior? This fundamental question at the interface of molecular biology and social evolution is hard to address with experiments in animals, and therefore, we turned to a simple microbial system: swarming in the bacterium Pseudomonas aeruginosa. Using genetic engineering, we excised a locus encoding a key metabolic regulator and disrupted P. aeruginosa's metabolic prudence, the regulatory mechanism that controls expression of swarming public goods and protects this social behavior from exploitation by cheaters. Then, using experimental evolution, we followed the joint evolution of the genome, the metabolome and the social behavior as swarming re-evolved. New variants emerged spontaneously with mutations that reorganized the metabolome and compensated in distinct ways for the disrupted metabolic prudence. These experiments with a unicellular organism provide a detailed view of how metabolism-currency of all physiological processes-can determine the costs and benefits of a social behavior and ultimately influence how an organism behaves towards other organisms of the same species.

Spreading of nonmotile bacteria on a hard agar plate: Comparison between agent-based and stochastic simulations

We study spreading of a nonmotile bacteria colony on a hard agar plate by using agent-based and continuum models. We show that the spreading dynamics depends on the initial nutrient concentration, the motility, and the inherent demographic noise. Population fluctuations are inherent in an agent-based model, whereas for the continuum model we model them by using a stochastic Langevin equation. We show that the intrinsic population fluctuations coupled with nonlinear diffusivity lead to a transition from a diffusion limited aggregation type of morphology to an Eden-like morphology on decreasing the initial nutrient concentration.

Environment determines evolutionary trajectory in a constrained phenotypic space

Constraints on phenotypic variation limit the capacity of organisms to adapt to the multiple selection pressures encountered in natural environments. To better understand evolutionary dynamics in this context, we select Escherichia coli for faster migration through a porous environment, a process which depends on both motility and growth. We find that a trade-off between swimming speed and growth rate constrains the evolution of faster migration. Evolving faster migration in rich medium results in slow growth and fast swimming, while evolution in minimal medium results in fast growth and slow swimming. In each condition parallel genomic evolution drives adaptation through different mutations. We show that the trade-off is mediated by antagonistic pleiotropy through mutations that affect negative regulation. A model of the evolutionary process shows that the genetic capacity of an organism to vary traits can qualitatively depend on its environment, which in turn alters its evolutionary trajectory.

DOI:http://dx.doi.org/10.7554/eLife.24669.001

In nature organisms face many challenges, and species adapt to their environment by changing heritable traits over the course of many generations. How organisms adapt is often limited by trade-offs, in which improving one trait can only come at the expense of another.

In the laboratory, scientists use well-controlled environments to study how populations adapt to specific challenges without interference from their natural habitat. Most experiments, however, only look at simple challenges and do not take into account that organisms in the wild face many pressures at the same time. Fraebel et al. wanted to know what happens when an organism’s performance depends on two traits that are restricted by a trade-off. The experiments used populations of the bacterium Escherichia coli, which can go through hundreds of generations in a week, providing ample opportunity to study mutations and their impact on heritable traits.

Through a combination of mathematical modeling and experiments, Fraebel et al. found that the environment is crucial for determining how bacteria adapt when their swimming speed and population growth rate are restricted by a trade-off. When nutrients are plentiful, E. coli populations evolve to spread faster by swimming more quickly despite growing more slowly. Yet, if nutrients are scarcer, the bacteria evolve to spread faster by growing more quickly despite swimming more slowly. In each scenario, the experiments identified single mutations that changed both swimming speed and growth rate by modifying regulatory activity in the cell.

A better understanding of how an organism’s genetic architecture, its environment and trade-offs are connected may help identify the traits that are most easily changed by mutations. The ultimate goal would be to be able to predict evolutionary responses to complex selection pressures.

DOI:http://dx.doi.org/10.7554/eLife.24669.002

Inhibition of P. aeruginosa c-di-GMP phosphodiesterase RocR and swarming motility by a benzoisothiazolinone derivative

Various important cellular processes in bacteria are controlled by c-di-GMP, such as motility, biofilm formation and virulence factors production. C-di-GMP is synthesized from two molecules of GTP by diguanylate cyclases (DGCs) and its actions are terminated by EAL or HD-GYP domain phosphodiesterases (PDEs), which hydrolyze c-di-GMP to linear pGpG or GMP. Thus far the majority of efforts have been dedicated to the development of inhibitors of DGCs but not PDEs. This is probably because the old view was that inhibiting any c-di-GMP PDE would lead to biofilm formation, an undesirable phenotype. Recent data however suggest that some PDEs only change the localized (not global) concentration of c-di-GMP to increase bacterial virulence and do not affect biofilm formation. A challenge therefore is to be able to develop selective PDE inhibitors that inhibit virulence-associated PDEs but not inhibit PDEs that regulate bacterial biofilm formation. Using high throughput docking experiments to screen a library of 250 000 commercially available compounds against E. coli YahA (also called PdeL), a benzoisothiazolinone derivative was found to bind to the c-di-GMP binding site of YahA with favorable energetics. Paradoxically the in silico identified inhibitor (a benzoisothiazolinone derivative) did not inhibit the hydrolysis of c-di-GMP by YahA, the model PDE that was used in the docking, but instead inhibited RocR, which is a PDE from the opportunistic pathogen P. aeruginosa (PA). RocR promotes bacterial virulence but not biofilm dispersal, making it an ideal PDE to target for anti-virulence purposes. This newly identified RocR ligand displayed some selectivity and did not inhibit other P. aeruginosa PDEs, such as DipA, PvrR and PA4108. DipA, PvrR and PA4108 are key enzymes that reduce global c-di-GMP concentration and promote biofilm dispersal; therefore the identification of an inhibitor of a PA PDE, such as RocR, that does not inhibit major PDEs that modulate global c-di-GMP is an important step towards the development of selective c-di-GMP PDEs that could have interesting biomedical applications. The identified RocR ligand could also inhibit P. aeruginosa (PAO1) swarming but not swimming or biofilm formation. Rhamnolipid production was decreased, explaining the inhibition of swarming.

Swimming performance of Bradyrhizobium diazoefficiens is an emergent property of its two flagellar systems

Many bacterial species use flagella for self-propulsion in aqueous media. In the soil, which is a complex and structured environment, water is found in microscopic channels where viscosity and water potential depend on the composition of the soil solution and the degree of soil water saturation. Therefore, the motility of soil bacteria might have special requirements. An important soil bacterial genus is Bradyrhizobium, with species that possess one flagellar system and others with two different flagellar systems. Among the latter is B. diazoefficiens, which may express its subpolar and lateral flagella simultaneously in liquid medium, although its swimming behaviour was not described yet. These two flagellar systems were observed here as functionally integrated in a swimming performance that emerged as an epistatic interaction between those appendages. In addition, each flagellum seemed engaged in a particular task that might be required for swimming oriented toward chemoattractants near the soil inner surfaces at viscosities that may occur after the loss of soil gravitational water. Because the possession of two flagellar systems is not general in Bradyrhizobium or in related genera that coexist in the same environment, there may be an adaptive tradeoff between energetic costs and ecological benefits among these different species.

Bacterial flagellar motility on hydrated rough surfaces controlled by aqueous film thickness and connectedness

Recent studies have shown that rates of bacterial dispersion in soils are controlled by hydration conditions that define size and connectivity of the retained aqueous phase. Despite the ecological implications of such constraints, microscale observations of this phenomenon remain scarce. Here, we quantified aqueous film characteristics and bacterial flagellated motility in response to systematic variations in microhydrological conditions on porous ceramic surfaces that mimic unsaturated soils. We directly measured aqueous film thickness and documented its microscale heterogeneity. Flagellar motility was controlled by surface hydration conditions, as cell velocity decreased and dispersion practically ceased at water potentials exceeding –2 kPa (resulting in thinner and disconnected liquid films). The fragmentation of aquatic habitats was delineated indirectly through bacterial dispersal distances within connected aqueous clusters. We documented bacterial dispersal radii ranging from 100 to 10 μm as the water potential varied from 0 to –7 kPa, respectively. The observed decrease of flagellated velocity and dispersal ranges at lower matric potentials were in good agreement with mechanistic model predictions. Hydration-restricted habitats thus play significant role in bacterial motility and dispersal, which has potentially important impact on soil microbial ecology and diversity.

Integration of Metabolic and Quorum Sensing Signals Governing the Decision to Cooperate in a Bacterial Social Trait

Many unicellular organisms live in multicellular communities that rely on cooperation between cells. However, cooperative traits are vulnerable to exploitation by non-cooperators (cheaters). We expand our understanding of the molecular mechanisms that allow multicellular systems to remain robust in the face of cheating by dissecting the dynamic regulation of cooperative rhamnolipids required for swarming in Pseudomonas aeruginosa. We combine mathematical modeling and experiments to quantitatively characterize the integration of metabolic and population density signals (quorum sensing) governing expression of the rhamnolipid synthesis operon rhlAB. The combined computational/experimental analysis reveals that when nutrients are abundant, rhlAB promoter activity increases gradually in a density dependent way. When growth slows down due to nutrient limitation, rhlAB promoter activity can stop abruptly, decrease gradually or even increase depending on whether the growth-limiting nutrient is the carbon source, nitrogen source or iron. Starvation by specific nutrients drives growth on intracellular nutrient pools as well as the qualitative rhlAB promoter response, which itself is modulated by quorum sensing. Our quantitative analysis suggests a supply-driven activation that integrates metabolic prudence with quorum sensing in a non-digital manner and allows P. aeruginosa cells to invest in cooperation only when the population size is large enough (quorum sensing) and individual cells have enough metabolic resources to do so (metabolic prudence). Thus, the quantitative description of rhlAB regulatory dynamics brings a greater understating to the regulation required to make swarming cooperation stable.

Although bacteria are not multicellular organisms, they commonly live in large communities and engage in many cooperative behaviors. Cooperation can allow bacteria to access additional nutrients, but it requires the secretion of products that will be shared by the community. How bacteria make the molecular decision to cooperate within a community is still not completely understood. The bacterium Pseudomonas aeruginosa regulates the secretion of one of these shared products, rhamnolipids, using information about population density and nutrient availability in its environment. Expression of the operon rhlAB is required for the bacteria to produce rhamnolipids. We use a combined computational and experimental approach to investigate how P. aeruginosa continually combines current information of population density and nutrient availability to determine if it should express rhlAB. We find that when conditions are nutrient rich, P. aeruginosa uses population density to modulate the amount rhlAB expression, however when the bacteria are starved for nutrients the starvation condition largely determines how the bacteria will express rhlAB. Because the bacteria continually adjust expression based on the current conditions, the molecular decision to produce rhamnolipids can be adjusted if either population density or nutrient conditions change. Our combined computational and experimental approach sheds new light on the rich regulatory dynamics that govern a cellular decision to cooperate.

Positioning of bacterial chemoreceptors

For optimum growth, bacteria must adapt to their environment, and one way that many species do this is by moving towards favourable conditions. To do so requires mechanisms to both physically drive movement and provide directionality to this movement. The pathways that control this directionality comprise chemoreceptors, which, along with an adaptor protein (CheW) and kinase (CheA), form large hexagonal arrays. These arrays can be formed around transmembrane receptors, resulting in arrays embedded in the inner membrane, or they can comprise soluble receptors, forming arrays in the cytoplasm. Across bacterial species, chemoreceptor arrays (both transmembrane and soluble) are localised to a variety of positions within the cell; some species with multiple arrays demonstrate this variety within individual cells. In many cases, the positioning pattern of the arrays is linked to the need for segregation of arrays between daughter cells on division, ensuring the production of chemotactically competent progeny. Multiple mechanisms have evolved to drive this segregation, including stochastic self-assembly, cellular landmarks, and the utilisation of ParA homologues. The variety of mechanisms highlights the importance of chemotaxis to motile species.

Collective dynamics of soft active particles

We present a model of soft active particles that leads to a rich array of collective behavior found also in dense biological swarms of bacteria and other unicellular organisms. Our model uses only local interactions, such as Vicsek-type nearest-neighbor alignment, short-range repulsion, and a local boundary term. Changing the relative strength of these interactions leads to migrating swarms, rotating swarms, and jammed swarms, as well as swarms that exhibit run-and-tumble motion, alternating between migration and either rotating or jammed states. Interestingly, although a migrating swarm moves slower than an individual particle, the diffusion constant can be up to three orders of magnitude larger, suggesting that collective motion can be highly advantageous, for example, when searching for food.

Type IV pili interactions promote intercellular association and moderate swarming of Pseudomonas aeruginosa

Pseudomonas aeruginosa is a ubiquitous bacterium that survives in many environments, including as an acute and chronic pathogen in humans. Substantial evidence shows that P. aeruginosa behavior is affected by its motility, and appendages known as flagella and type IV pili (TFP) are known to confer such motility. The role these appendages play when not facilitating motility or attachment, however, is unclear. Here we discern a passive intercellular role of TFP during flagellar-mediated swarming of P. aeruginosa that does not require TFP extension or retraction. We studied swarming at the cellular level using a combination of laboratory experiments and computational simulations to explain the resultant patterns of cells imaged from in vitro swarms. Namely, we used a computational model to simulate swarming and to probe for individual cell behavior that cannot currently be otherwise measured. Our simulations showed that TFP of swarming P. aeruginosa should be distributed all over the cell and that TFP-TFP interactions between cells should be a dominant mechanism that promotes cell-cell interaction, limits lone cell movement, and slows swarm expansion. This predicted physical mechanism involving TFP was confirmed in vitro using pairwise mixtures of strains with and without TFP where cells without TFP separate from cells with TFP. While TFP slow swarm expansion, we show in vitro that TFP help alter collective motion to avoid toxic compounds such as the antibiotic carbenicillin. Thus, TFP physically affect P. aeruginosa swarming by actively promoting cell-cell association and directional collective motion within motile groups to aid their survival.