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Register a new userBacteria display optimal transport near surfaces -- bacteria as intermittent active chiral particles: trapped by hydrodynamics, escaping by adhesion
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The near-surface swimming patterns of bacteria are strongly determined by the hydrodynamic interactions between bacteria and the surface, which trap bacteria in smooth circular trajectories that lead to inefficient surface exploration. Here, we show by combining experiments and a data-driven mathematical model that surface exploration of enterohemorrhagic Escherichia coli (EHEC) -- a pathogenic strain of E. coli causing serious illnesses such as bloody diarrhea -- results from a complex interplay between motility and transient surface adhesion events. These events allow EHEC to break the smooth circular trajectories and regulate their transport properties by the use stop-adhesion events that lead to a characteristic intermittent motion on surfaces. We find that the experimentally measured frequency of stop-adhesion events in EHEC is located at the value predicted by the developed mathematical model that maximizes bacterial surface diffusivity. We indicate that these results and the developed model apply to other bacterial strains on different surfaces, which suggests that swimming bacteria use transient adhesion to regulate surface motion.
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We characterize cell motion in experiments and show that the transition to collective motion in colonies of gliding bacterial cells confined to a monolayer appears through the organization of cells into larger moving clusters. Collective motion by non-equilibrium cluster formation is detected for a critical cell packing fraction around 17%. This transition is characterized by a scale-free power-law cluster size distribution, with an exponent $0.88pm0.07$, and the appearance of giant number fluctuations. Our findings are in quantitative agreement with simulations of self-propelled rods. This suggests that the interplay of self-propulsion of bacteria and the rod-shape of bacteria is sufficient to induce collective motion.
It is well known that flagellated bacteria swim in circles near surfaces. However, recent experiments have shown that a sulfide-oxidizing bacterium named Thiovulum majus can transition from swimming in circles to a surface bound state where it stops swimming while remaining free to move laterally along the surface. In this bound state, the cell rotates perpendicular to the surface with its flagella pointing away from it. Using numerical simulations and theoretical analysis, we demonstrate the existence of a fluid-structure interaction instability that causes cells with relatively short flagella to become surface bound.
Periodic reversals of the direction of motion in systems of self-propelled rod shaped bacteria enable them to effectively resolve traffic jams formed during swarming and maximize their swarming rate. In this paper, a connection is found between a microscopic one dimensional cell-based stochastic model of reversing non-overlapping bacteria and a macroscopic non-linear diffusion equation describing dynamics of the cellular density. Boltzmann-Matano analysis is used to determine the nonlinear diffusion equation corresponding to the specific reversal frequency. Macroscopically (ensemble-vise) averaged stochastic dynamics is shown to be in a very good agreement with the numerical solutions of the nonlinear diffusion equation. Critical density $p_0$ is obtained such that nonlinear diffusion is dominated by the collisions between cells for the densities $p>p_0$. An analytical approximation of the pairwise collision time and semi-analytical fit for the total jam time per reversal period are also obtained. It is shown that cell populations with high reversal frequencies are able to spread out effectively at high densities. If the cells rarely reverse then they are able to spread out at lower densities but are less efficient at spreading out at at higher densities.
From biofilm and colony formation in bacteria to wound healing and embryonic development in multicellular organisms, groups of living cells must often move collectively. While considerable study has probed the biophysical mechanisms of how eukaryotic cells generate forces during migration, little such study has been devoted to bacteria, in particular with regard to the question of how bacteria generate and coordinate forces during collective motion. This question is addressed here for the first time using traction force microscopy. We study two distinct motility mechanisms of Myxococcus xanthus, namely twitching and gliding. For twitching, powered by type-IV pilus retraction, we find that individual cells exert local traction in small hotspots with forces on the order of 50 pN. Twitching of bacterial groups also produces traction hotspots, however with amplified forces around 100 pN. Although twitching groups migrate slowly as a whole, traction fluctuates rapidly on timescales <1.5 min. Gliding, the second motility mechanism, is driven by lateral transport of substrate adhesions. When cells are isolated, gliding produces low average traction on the order of 1 Pa. However, traction is amplified in groups by a factor of ~5. Since advancing protrusions of gliding cells push on average in the direction of motion, we infer a long-range compressive load sharing among sub-leading cells. Together, these results show that the forces generated during twitching and gliding have complementary characters and both forces are collectively amplified in groups.
We present a multi-scale model to study the attachment of spherical particles with a rigid core, coated with binding ligands and in equilibrium with the surrounding, quiescent fluid medium. This class of fluid-immersed adhesion is widespread in many natural and engineering settings. Our theory highlights how the micro-scale binding kinetics of these ligands, as well as the attractive / repulsive surface potential in an ionic medium effects the eventual macro-scale size distribution of the particle aggregates (flocs). The results suggest that the presence of elastic ligands on the particle surface allow large floc aggregates by inducing efficient inter-floc collisions (i.e., a large, non-zero collision factor). Strong electrolytic composition of the surrounding fluid favors large floc formation as well.
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