Data-driven quantitative modeling of bacterial active nematics

Li, He; Shi, Xia-qing; Huang, Mingji; Chen, Xiao; Xiao, Mei; Liu, Chenli; Chaté, Hugues; Zhang, Hepeng

doi:10.1073/pnas.1812570116

Cited by 121 publications

(97 citation statements)

References 74 publications

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“…10b). The former, while realizable in thermotropic liquid crystals and perhaps even bacterial active nematics [45], is supressed by the long constituents of the microtubule active nematic. Given the constraints imposed by the director-defined material lines, we observe a preference for the latter mechanism.…”

Section: Discussionmentioning

confidence: 99%

Self-organized dynamics and the transition to turbulence of confined active nematics

Opathalage

Norton

Juniper

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

158

134

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We study how confinement transforms the chaotic dynamics of bulk microtubule-based active nematics into regular spatiotemporal patterns. For weak confinements, multiple continuously nucleating and annihilating topological defects self-organize into persistent circular flows of either handedness. Increasing confinement strength leads to the emergence of distinct dynamics, in which the slow periodic nucleation of topological defects at the boundary is superimposed onto a fast procession of a pair of defects. A defect pair migrates towards the confinement core over multiple rotation cycles, while the associated nematic director field evolves from a distinct double spiral towards a nearly circularly symmetric configuration. The collapse of the defect orbits is punctuated by another boundary-localized nucleation event, that sets up long-term doubly-periodic dynamics.Comparing experimental data to a theoretical model of an active nematic, reveals that theory captures the fast procession of a pair of + 1 2 defects, but not the slow spiral transformation nor the periodic nucleation of defect pairs. Theory also fails to predict the emergence of circular flows in the weak confinement regime. The developed confinement methods are generalized to more complex geometries, providing a robust microfluidic platform for rationally engineering two-dimensional autonomous flows. arXiv:1810.09032v2 [cond-mat.soft]

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Section: Discussionmentioning

confidence: 99%

Self-organized dynamics and the transition to turbulence of confined active nematics

Opathalage

Norton

Juniper

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

158

134

View full text Add to dashboard Cite

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“…1B). The novel twodimensional set-up of a thin, single-layer of cells, brings out a complex experimentally based phase diagram with various features which could not be obtained with earlier multilayer studies [Zhang 2010, Peruani 2012, Ilkanaiv 2017, Li 2019 or naturally expanding colonies [Jeckel 2019].…”

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confidence: 99%

A phase diagram for bacterial swarming

et al. 2020

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Bacterial swarming is a rapid mass-migration, in which thousands of cells spread collectively to colonize a surface. Physically, swarming is a natural example of active particles that use energy to generate motion. Accordingly, understanding the constraints physics imposes on the dynamics is essential to understand the mechanisms underlying the swarming phenomenon. We present new experiments of swarming Bacillus subtilis mutants with different aspect ratios and densities. Analyzing the dynamics reveals a rich phase diagram of qualitatively distinct swarming regimes, describing how the shape and density of cells govern the global dynamical characteristics of the entire swarm. Moreover, we show that under standard conditions bacteria inhabit a region of phase space that is associated with rapid mixing and robust dynamics, with homogeneous density and no preferred direction of motion. This contrasts characteristic clustering behavior of selfpropelled rods that is recovered only for very elongated mutant species. Thus, bacteria have adapted their physics to optimize the principle functions assumed for swarming. 2 Micro-organisms such as bacteria, sperm-, epithelial-and cancer-cells, as well as immune T-cells and even inanimate active particles, generate collective flows and demonstrate a wealth of newly discovered emergent dynamical patterns [Szabó Be'er 2019]. This report addresses the dynamics of swarming bacteria a biological state to which some bacterial species transition, in which rod-shaped cells, powered by flagellar rotation, migrate rapidly on surfaces en-mass [Harshey 2003; Darnton 2010; Kearns 2010; Tuson 2013]. Swarming allows efficient expansion and colonization of new territories, even under harsh and adverse conditions such as starvation or antibiotic stress [Lai 2009; Benisty 2015]. Revealing the biological and physical mechanisms underlying bacterial swarming is therefore a key to our understanding of how bacteria spread and invade new niches. The transition to swarming involves several critical intra-cellular processes such as an increase in flagellar number and changes in cell shape, suggesting these changes promote favorable swarming conditions [Harshey 2003; Kearns 2010; Tuson 2013; Mukherjee 2015; Be'er 2019]. Quantifying the "quality" of swarming can be done using the tools of statistical physics by analyzing the dynamical properties of large, out-ofequilibrium, self-propelled collectives [Ramaswamy 2010; Vicsek 2012; Bär 2019].Accordingly, one of the primary goals of such quantification is to obtain a phase diagram that would describe the possible dynamical states of swarms as a function of controlled parameters such as density and cell aspect ratio. As bacteria move and grow, they trace an effective path through the phase diagram, transitioning between different swarming regimes. Thus, a phase diagram provides a map that explains how the microscopic mechanical properties of cells, which are regulated by complex bio-

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“…Considering possible experimental realisations, our model predictions apply to active growing systems, where hydrodynamic interactions and nematic orientational order play an important role. Such nematic ordering has been reported in various biological systems including bacterial colonies [48,66], cultures of amoeboid cells [67], fibroblast cells [46,16], human bronchial cells [68], neural progenitor stem cells [69], and Madin-Darby Kanine Kidney (MDCK) epithelial monolayers [35,70]. Investigating the degree to which experiment and theory can be matched by the adaptation of parameters and boundary conditions in the model or the reasons for deviations is a powerful way of unraveling the role of mechanics in determining the behaviour of such active biological matter.…”

Section: Discussionmentioning

confidence: 79%

Active matter invasion

Kempf

Mueller²,

Frey

et al. 2019

Soft Matter

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Biological active materials such as bacterial biofilms and eukaryotic cells thrive in confined micro-spaces. Here, we show through numerical simulations that confinement can serve as a mechanical guidance to achieve distinct modes of collective invasion when combined with growth dynamics and the intrinsic activity of biological materials. We assess the dynamics of the growing interface and classify these collective modes of invasion based on the activity of the constituent particles of the growing matter. While at small and moderate activities the active material grows as a coherent unit, we find that blobs of active material collectively detach from the cohort above a well-defined activity threshold. We further characterise the mechanical mechanisms underlying the crossovers between different modes of invasion and quantify their impact on the overall invasion speed.

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Data-driven quantitative modeling of bacterial active nematics

Cited by 121 publications

References 74 publications

Self-organized dynamics and the transition to turbulence of confined active nematics

Self-organized dynamics and the transition to turbulence of confined active nematics

A phase diagram for bacterial swarming

Active matter invasion

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