Bacterial swarming: a model system for studying dynamic self-assembly

Copeland, Matthew F.; Weibel, Douglas B.

doi:10.1039/b812146j

Cited by 261 publications

(283 citation statements)

References 159 publications

(329 reference statements)

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“…While on hard-agar plates (agar 41.5%), cells grow into non-motile colonies and retain their planktonic morphology and phenotype. Cells isolated from the edge of the soft-agar plate have distinctively more flagella than cells from a hard-agar plate (Copeland and Weibel, 2009). Increased motility is thus an advantage on soft-agar plates because it allows cells to reach more nutrients.…”

Section: Is5 Hops Upstream Of Flhd þ Only When Cells Swim On Motilitymentioning

confidence: 99%

“…It is well known that for softagar plates (agar o0.4%) the pore size of the gel is larger than the bacterial cells, allowing them to penetrate into the polymer network and swim (Copeland and Weibel, 2009). While on hard-agar plates (agar 41.5%), cells grow into non-motile colonies and retain their planktonic morphology and phenotype.…”

Section: Is5 Hops Upstream Of Flhd þ Only When Cells Swim On Motilitymentioning

confidence: 99%

“…The frequency of IS5 hopping was also tested on plates with the same nutrient content as soft-agar plates, but with higher amounts of agar (1.5%), which serves to immobilize the E. coli cells, and on regular LB-agar plates with more nutrients (1.5% agar), which also does not support motility (Copeland and Weibel, 2009). In both cases, after 12 h, 24 h, 48 h and 72 h, the frequency of IS5 hopping upstream of flhD þ was unchanged and remained very low (B10 À7 , estimated by qPCR).…”

Section: Is5 Hops Upstream Of Flhd þ Only When Cells Swim On Motilitymentioning

confidence: 99%

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IS5 inserts upstream of the master motility operon flhDC in a quasi-Lamarckian way

Wang

Wood

2011

The ISME Journal

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Mutation rates may be influenced by the environment. Here, we demonstrate that insertion sequence IS5 in Escherichia coli inserts into the upstream region of the flhDC operon in a manner that depends on whether the environment permits motility; this operon encodes the master regulator of cell motility, FlhDC, and the IS5 insertion increases motility. IS5 inserts upstream of flhD þ when cells are grown on soft-agar plates that permit swimming motility, but does not insert upstream of this locus on hard-agar plates that do not permit swimming motility or in planktonic cultures. Furthermore, there was only one IS5 insertion event on soft-agar plates, indicating insertion of IS5 into flhDC is not due to general elevated IS5 transposition throughout the whole genome. We also show that the highly motile cells with IS5 upstream of flhD þ have greater biofilm formation, although there is a growth cost due to the energetic burden of the enhanced motility as these highly motile cells have a lower yield in rich medium and reduced growth rate. Functional flagella are required for IS5 insertion upstream of flhD þ as there was no IS5 insertion upstream of flhD þ for flhD, flgK and motA mutants, and the mutation is stable. Additionally, the IS5 mutation occurs during biofilm formation, which creates genetic and phenotypic diversity. Hence, the cells appear to 'sense' whether motility is feasible before a sub-population undergoes a mutation to become hypermotile; this sensing appears related to the master transcription regulator, FlhDC.

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Section: Is5 Hops Upstream Of Flhd þ Only When Cells Swim On Motilitymentioning

confidence: 99%

Section: Is5 Hops Upstream Of Flhd þ Only When Cells Swim On Motilitymentioning

confidence: 99%

Section: Is5 Hops Upstream Of Flhd þ Only When Cells Swim On Motilitymentioning

confidence: 99%

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IS5 inserts upstream of the master motility operon flhDC in a quasi-Lamarckian way

Wang

Wood

2011

The ISME Journal

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“…In contrast to externally driven systems (such as sheared materials), active matter is driven out of equilibrium at the scale of its microscopic constituents. Well-studied examples include biological tissues [3], bacterial suspensions [4] and active granular and colloidal particles [5][6][7][8].Epithelial tissues constitute a biologically relevant active system composed of densely packed eukaryotic cells [3,[9][10][11][12][13][14]. Such tissues display a surprisingly fast and collective dynamics, which would not take place under equilibrium conditions [10].…”

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confidence: 99%

Discontinuous fluidization transition in time-correlated assemblies of actively deforming particles

Tjhung

Berthier

2017

Phys. Rev. E

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Tracking experiments in dense biological tissues reveal a diversity of sources for local energy injection at the cell scale. The effect of cell motility has been largely studied, but much less is known about the effect of the observed volume fluctuations of individual cells. We devise a simple microscopic model of 'actively-deforming' particles where local fluctuations of the particle size constitute a unique source of motion. We demonstrate that collective motion can emerge under the sole influence of such active volume fluctuations. We interpret the onset of diffusive motion as a nonequilibrium first-order phase transition, which arises at a well-defined amplitude of selfdeformation. This behaviour contrasts with the glassy dynamics produced by self-propulsion, but resembles the mechanical response of soft solids under mechanical deformation. It thus constitutes the first example of active yielding transition.Active matter represents a class of nonequilibrium systems that is currently under intense scrutiny [1,2]. In contrast to externally driven systems (such as sheared materials), active matter is driven out of equilibrium at the scale of its microscopic constituents. Well-studied examples include biological tissues [3], bacterial suspensions [4] and active granular and colloidal particles [5][6][7][8].Epithelial tissues constitute a biologically relevant active system composed of densely packed eukaryotic cells [3,[9][10][11][12][13][14]. Such tissues display a surprisingly fast and collective dynamics, which would not take place under equilibrium conditions [10]. This dynamics has been ascribed to at least three distinct active processes [13]: (i) self-propulsion through cell motility such as crawling [15], (ii) self-deformation through protrusion and contraction [16][17][18], and (iii) cell division and apoptosis [14]. The vertex model for tissues [12,19,20] includes the first two of these active processes and predicts a continuous static transition from an arrested to a flowing state [21]. Another theoretical line of research is based on self-propelled particles [22] which display at high density a nonequilibrium glass transition [23,24] accompanied by a continuous increase of space and time correlations which diverge on approaching the arrested phase [25][26][27]. However, typical correlation lengthscales in tissues do not seem to diverge [9,11,28,29].To disentangle the dynamic consequences of the various sources of activity in tissues at large scale, we suggest to decompose the original complex problem into simpler ones, and to study particle-based models which only include a specific source of activity. This strategy was followed earlier for self-propulsion, but experiments are instead often modelled by complex models with many competing processes [18,29,30]. We argue that it is relevant to introduce a simplified model to analyse the effect of active particle deformation in a dense assembly of nonpropelled soft objects. Specifically, we model a dense system that is driven out of equilibrium locally th...

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“…A series of experiments over the last decade [1][2][3][4][5][6][7][8][9][10] has shed light on generic ordering principles that appear to govern collective dynamics of living matter [11][12][13][14][15], from large-scale animal swarming [1,2] to mesoscale turbulence in microbial suspensions [3][4][5][6][7][8] and microscale selforganization in motility assays [9,10]. Although very different in size and composition, these systems are often jointly termed ''active'' fluids, for which there is now a range of continuum theories [12,[14][15][16][17][18][19][20][21][22][23][24].…”

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confidence: 99%

The Aquatic Dance of Bacteria

Aranson¹

2013

Physics

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Self-sustained turbulent structures have been observed in a wide range of living fluids, yet no quantitative theory exists to explain their properties. We report experiments on active turbulence in highly concentrated 3D suspensions of Bacillus subtilis and compare them with a minimal fourth-order vector-field theory for incompressible bacterial dynamics. Velocimetry of bacteria and surrounding fluid, determined by imaging cells and tracking colloidal tracers, yields consistent results for velocity statistics and correlations over 2 orders of magnitude in kinetic energy, revealing a decrease of fluid memory with increasing swimming activity and linear scaling between kinetic energy and enstrophy. The best-fit model allows for quantitative agreement with experimental data. [3][4][5][6][7][8] and microscale selforganization in motility assays [9,10]. Although very different in size and composition, these systems are often jointly termed ''active'' fluids, for which there is now a range of continuum theories [12,[14][15][16][17][18][19][20][21][22][23][24]. From these have come important qualitative insights into instability mechanisms [13][14][15][16]21,25] driving dynamical pattern formation, but a quantitative picture remains inchoate; even for the simplest active (e.g., bacterial or algal) suspensions uncertainty remains about which hydrodynamic equations and transport coefficients [26,27] provide an adequate minimal description, due in large part to the inability of existing data to constrain the manifold parameters in these models. One approach to remedy this problem is to characterize collective turbulent dynamics of bacteria [17,18] and other low Reynolds number swimmers, just as in high Reynolds number fluid turbulence, in terms of kinetic energy, mean squared vorticity (enstrophy) and spatiotemporal correlation functions, and to compare with an appropriate longwavelength theory (i.e., Navier-Stokes-type equations). We present such an analysis here, measuring collective behavior in dense suspensions of the bacterium Bacillus subtilis in comparison to predictions of a (fourth-order) continuum model for bacterial flow [7,28]. [3,4,29,30], freestanding films [5,8,27,31], on surfaces [6,32,33], or quasi-2D microfluidic chambers [7] focused separately on the bacterial and fluid components, leaving uncertain how accurately passive tracers [34,35] reflect collective bacterial dynamics. The experiments reported here, performed in closed 3D microfluidic chambers, allowed near-simultaneous measurements of cell and tracer motion, and exploit a natural reduction in bacterial swimming activity due to oxygen depletion [8,29,36] to obtain data spanning 2 orders of magnitude in fluid kinetic energy. Combined with extensive 3D numerical simulations of the model, this data allows robust parameter estimates. Quantitative agreement between experiment and theory suggests that this model presents a viable generalization of the Navier-Stokes equations to incompressible active fluids. Previous experimental studies of bacterial s...

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Bacterial swarming: a model system for studying dynamic self-assembly

Cited by 261 publications

References 159 publications

IS5 inserts upstream of the master motility operon flhDC in a quasi-Lamarckian way

IS5 inserts upstream of the master motility operon flhDC in a quasi-Lamarckian way

Discontinuous fluidization transition in time-correlated assemblies of actively deforming particles

The Aquatic Dance of Bacteria

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