Loss of Collective Motion in Swarming Bacteria Undergoing Stress

Lu, Shengtao; Bi, Wuguo; Liu, Fang; Wu, Xiangyang; Xing, Bengang; Yeow, Edwin K. L.

doi:10.1103/physrevlett.111.208101

Cited by 20 publications

(54 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In general, the selective interactions introduced in this paper could make models of social agents more realistic. Furthermore, the proposed kinetic theory could be helpful for a closely related version of the Vicsek model, which was introduced by Lu et al [27] to describe their experiments on the collective motion of Bacillus subtilis.…”

Section: Discussionmentioning

confidence: 99%

“…3 one also sees perfect agreement with the three-mode analytical solution, Eq. (27), near the threshold.…”

Section: F a Numerical Methods For The Fredholm Equationmentioning

confidence: 99%

“…Starting from the third line, equations (27) can be solved successively leading to expressions of the higher modes in terms of the first modeg 1 ,…”

Section: Analytical Solution and Mean-field Tricritical Point For mentioning

confidence: 99%

“…3, where the blue dashed curve describes the analytical solution of Eq. (27). This approximation neglects all modesg k with k larger than three.…”

Section: Analytical Solution and Mean-field Tricritical Point For mentioning

confidence: 99%

See 3 more Smart Citations

Tricritical points in a Vicsek model of self-propelled particles with bounded confidence

2014

View full text Add to dashboard Cite

We study the orientational ordering in systems of self-propelled particles with selective interactions. To introduce the selectivity we augment the standard Vicsek model with a bounded-confidence collision rule: a given particle only aligns to neighbors who have directions quite similar to its own. Neighbors whose directions deviate more than a fixed restriction angle α are ignored. The collective dynamics of this systems is studied by agent-based simulations and kinetic mean field theory. We demonstrate that the reduction of the restriction angle leads to a critical noise amplitude decreasing monotonically with that angle, turning into a power law with exponent 3/2 for small angles. Moreover, for small system sizes we show that upon decreasing the restriction angle, the kind of the transition to polar collective motion changes from continuous to discontinuous. Thus, an apparent tricritical point with different scaling laws is identified and calculated analytically. We investigate the shifting and vanishing of this point due to the formation of density bands as the system size is increased. Agent-based simulations in small systems with large particle velocities show excellent agreement with the kinetic theory predictions. We also find that at very small interaction angles the polar ordered phase becomes unstable with respect to the apolar phase. We derive analytical expressions for the dependence of the threshold noise on the restriction angle. We show that the mean-field kinetic theory also permits stationary nematic states below a restriction angle of 0.681 π. We calculate the critical noise, at which the disordered state bifurcates to a nematic state, and find that it is always smaller than the threshold noise for the transition from disorder to polar order. The disordered-nematic transition features two tricritical points: At low and high restriction angle the transition is discontinuous but continuous at intermediate α. We generalize our results to systems that show fragmentation into more than two groups and obtain scaling laws for the transition lines and the corresponding tricritical points. A novel numerical method to evaluate the nonlinear Fredholm integral equation for the stationary distribution function is also presented. This method is shown to give excellent agreement with agent-based simulations, even in strongly ordered systems at noise values close to zero.

show abstract

Section: Discussionmentioning

confidence: 99%

“…3 one also sees perfect agreement with the three-mode analytical solution, Eq. (27), near the threshold.…”

Section: F a Numerical Methods For The Fredholm Equationmentioning

confidence: 99%

“…Starting from the third line, equations (27) can be solved successively leading to expressions of the higher modes in terms of the first modeg 1 ,…”

Section: Analytical Solution and Mean-field Tricritical Point For mentioning

confidence: 99%

“…3, where the blue dashed curve describes the analytical solution of Eq. (27). This approximation neglects all modesg k with k larger than three.…”

Section: Analytical Solution and Mean-field Tricritical Point For mentioning

confidence: 99%

See 2 more Smart Citations

Tricritical points in a Vicsek model of self-propelled particles with bounded confidence

2014

View full text Add to dashboard Cite

show abstract

“…Upon light illumination, the photodynamic action of protoporphyrin IX generated reactive oxygen species, which disrupted the function of flagellar motors and caused cells to become more tumbly, thus increasing the noise level. The authors measured the collective speed of cells during light illumination and demonstrated loss of collective motion due to increased noise level [95].The physicochemical environment of swarm cells can be controlled using microfluidic devices. Swiecicki et al used a microfluidic device to control the height of the liquid environment of E. coli swarm cells and recovered the key features of collective swarming dynamics, such as cluster formation [60].…”

mentioning

confidence: 99%

Collective motion of bacteria in two dimensions

2016

Quant. Biol.

View full text Add to dashboard Cite

Collective motion can be observed in biological systems over a wide range of length scales, from large animals to bacteria. Collective motion is thought to confer an advantage for defense and adaptation. A central question in the study of biological collective motion is how the traits of individuals give rise to the emergent behavior at population level. This question is relevant to the dynamics of general self-propelled particle systems, biological self-organization, and active fluids. Bacteria provide a tractable system to address this question, because bacteria are simple and their behavior is relatively easy to control. In this mini review we will focus on a special form of bacterial collective motion, i.e., bacterial swarming in two dimensions. We will introduce some organization principles known in bacterial swarming and discuss potential means of controlling its dynamics. The simplicity and controllability of 2D bacterial behavior during swarming would allow experimental examination of theory predictions on general collective motion.Keywords: bacterial swarming; biofilm; flagellar motility; gliding motility; biological self-organization; emergent behavior INTRODUCTION Collective motion is the coordinated self-organized movement of many individuals arising from physical, chemical, or social interactions between these individuals [1]. Collective motion is ubiquitous in nature. Familiar examples include fish schooling [2], bird flocking [3,4], and insect swarming [5]. At microscale, animal cells and microorganisms also display collective motion, such as cancer invasion and tissue development [6], phytoplankton (algae) blooms in surface waters [7], amoebae aggregation under starvation [8], and bacterial swarming during the formation of biofilms and fruiting bodies [9,10]. Collective motion is thought to confer an advantage for defending predators [2,3] and for adapting to the environment [9,10].Despite the vast differences in length scale and propulsion mechanism, collective motion across biological systems shares a similar feature: global order arises spontaneously from local interactions between individuals that do not have access to global information. Intriguingly, the traits of individuals determine the emergent global order in a non-intuitive manner; change of individuals' traits may lead to dramatically different collective behavior. Therefore, a central aim in the study of biological collective motion is to reveal its organization principles, i.e., how the traits of individuals give rise to the emergent behavior at population level. This question is not only important to biology, but also of great interest to other disciplines, such as physics, engineering, and computer science. For example, biological collective motion provides insights for understanding the physics of self-organization in non-equilibrium systems [1]; organization principles revealed in biological collective motion have inspired the design of aerial robots that can perform autonomous group flights [11], the design of swarming robots ...

show abstract

Effective strategies of collective evacuation from an enclosed space

Shao¹,

Yang²

2015

Physica A: Statistical Mechanics and its Applications

View full text Add to dashboard Cite

Loss of Collective Motion in Swarming Bacteria Undergoing Stress

Cited by 20 publications

References 33 publications

Tricritical points in a Vicsek model of self-propelled particles with bounded confidence

Tricritical points in a Vicsek model of self-propelled particles with bounded confidence

Collective motion of bacteria in two dimensions

Effective strategies of collective evacuation from an enclosed space

Contact Info

Product

Resources

About