Session C05: Active Matter and Liquid Crystals in Biological and Bio-Inspired Systems III

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There is growing evidence for the importance of topological defects in morphogenesis with several recent experiments and simulations observing that the presence of defects fundamentally changes the morphodynamics of tissues and guides their shape changes. However, a detailed understanding and explanation of these observations is still missing.
We present an analytic theory describing the dynamics of an active surface, a two-dimensional deformable surface coupled to an active liquid crystal on the surface. We show how introducing defects can influence the dynamics of the active surface and, in particular, how a buckling-like instability can arise at the positon of a defect. We investigate the effect of the charge of the defect and supplement our analytic theory with simulations. Our findings offer an explanation for the recent observations and are relevant to understanding morphogenesis and active surfaces in general.   

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Morphogenetic programs in living systems reliably transform initially disordered tissues into highly ordered states, despite unfolding far from thermal equilibrium. The active physical mechanisms that generate and maintain order as part of these programs remain pooly understood. We uncover a four-fold orientationally ordered phase in the crustacean Parhyale hawaiensis and provide a quantitative profile of the tissue dynamics through which this order emerges. Light-sheet microscopy and tissue cartography reveal that actively orchestrated spatiotemporal profiles of cell division convert a disordered epithelial tissue into a robust tetratic phase with quasi-long range four-fold order. Waves of anisotropic cell proliferation propagate across the embryo with precise choreography so that defects introduced into the nascent lattice are healed by subsequent divisions. Using an active hydrodynamic model, we show that the tissue velocities leading to this ordered phase are incompressible and almost completely determined by the cell divisions. Strict control of cell proliferation rates and orientations enable cell divisions, which would otherwise fluidize the embryo, to serve as an active mechanism for generating four-fold order in a non-equilibrium system.   

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Tissue function requires specific spatial organization of different cell types, yet should be flexible to allow for cell division and growth. Liquid-crystal order can serve this purpose. We computationally reconstructed 3D tissue geometry from microscopy images of mouse liver tissue and analyzed it using concepts from biaxial liquid crystal theory. We show that nematic apical and basal cell polarity axes of hepatocytes (the main cell type in the liver) follow long-range liquid-crystal order. These tissue-level patterns of hepatocyte cell polarity are co-aligned with a structural anisotropy of two transport networks, blood-transporting sinusoids and bile-transporting canaliculi that intertwine the tissue. Silencing communication from hepatocytes to sinusoids via Integrin-β1 knockdown disrupted both liquid-crystal order of hepatocytes and organization of the sinusoidal network, suggesting that bi-directional communication between hepatocytes and sinusoids orchestrates liver tissue architecture. Using a network generation algorithm, we computationally explore the resilience of anisotropic sinusoidal networks to local damage, thus addressing the link between form and function in a complex tissue with liquid-crystal order.

Morales-Navarette et al. eLife (2019) DOI: 10.7554/eLife.44860   

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Phase-separation, or demixing, is an important behavior seen in biological materials, contributing to compartmentalization within cells as well as cell sorting and patterning. In confluent tissues, where there are no gaps between cells, micro-demixing due to shape differences between cells has been observed. In particulate matter, differences in size, shape and persistent motion have all been shown to cause large-scale demixing. More recently, a two-species particle-based model where each species had a different fixed diffusivity was also shown to completely demix via nucleation and coarsening. In this study, we ask whether a similar demixing via diffusivity persists in a confluent model for biological tissue. Using a Voronoi Model with two cell types that differ only in their translational noise, we analyze the dynamics using correlation functions and segregation metrics. We find no evidence of demixing in this model, in stark contrast to particulate systems. We also will discuss preliminary results on particle-based mixtures with different diffusivities at very high densities, to better understand how changing cell-cell interactions affect the mechanism for diffusion-based demixing.   

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Motility is commonly observed in microbes, allowing them to explore their environment and exploit new resources. However, the possibility that increased motility can actually impede success has remained largely unexplored to date. We study Pseudomonas aeruginosa cells that move across solid surfaces using microscopic grappling hooks called pili. Surprisingly, we find that a mutant strain which individually moves faster than wild-type cells moves more slowly as a densely-packed group. Using cell tracking, active nematic theory, and simulations of self-propelled rods, we show that this phenomenon is caused by the behaviour of +1/2 topological defects within the collective. When two +1/2 defects composed of the faster moving cells collide, active forces generated by the cells cause the two defects to fuse into a single +1 defect. This spontaneously escapes into the third dimension, reorienting the faster moving cells vertically and so arresting their motion. The slower moving wild-type cells avoid this trapping mechanism and remain in the plane, allowing them to move unimpeded into new territory and ultimately outgrow the mutant. Our results show that the physics of active liquid crystals can have profound implications for the ecology and evolution of microbial communities.   

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Controlling cell growth and proliferation is important for tissue engineering and biomedical applications. We develop liquid crystal elastomer substrates with photopatterned surface topography and in-plane director (1) in order to explore the effect of splay and bend deformation on the growth of human fibroblast cells. In the one dimensional pattern of splay and bend stripes, the cells show a preferential growth in the splay regions. The nuclei of cells growing in the splay regions exhibit a higher aspect ratio as compared to cells growing in the bend regions. In tissues with edges that mimic wounds and are perpendicular to the splay-bend stripes, the cells migrate faster in the splay regions with velocity vector antiparallel to the splay vector ndivn. This work demonstrates that the active force caused by gradients of the orientational order in tissues triggers polar migration of cells.

(1) Turiv T, et al. (2020) Topology control of human fibroblast cells monolayer by liquid crystal elastomer. Science Advances 6(20):eaaz6485.   

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Powered by flagella, many bacterial species exhibit collective motion on a solid surface commonly known as swarming. Physical changes like cell elongation and hyper flagellation are known to accompany the swarming phenotype. However, less noticeable are the contrasts of collective motion between the swarming and planktonic cells of comparable density. Here, we show that when confined by microwells of specific sizes mounted on an agar surface, novel bacterium Enterobacter sp. SM3 under swarming condition exhibit a “single-swirl” motion pattern distinct from “multi-swirls” formed by its concentrated planktonic counterpart. We hypothesized that a “rafting behavior” of the swarming bacteria upon dilution might account for the motion pattern difference. We verified the conjecture via numerical simulations where swarming cells are modeled with lower repulsion and more substantial alignment. Our new technical approach also enabled us to observe swarming on a tissue surface and to perform physiologically relevant studies in the future.   

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Many cell types possess long-range orientational order [1], responsible for influencing cell-cell communication and patterns of cell migration. It is therefore possible to consider ensembles of cells in analogy with nematic liquid crystals (NLCs). In particular, monolayers of spindle-like cells show almost perfect NLC behavior [2]. As liquid crystals, cells also form topological defects, which can be classified on the basis of their topological charge. These are either formed spontaneously in cell monolayers, or induced by controlled boundary conditions [3, 4].
We create topographical patters with micro-ridges to align cells and impose distortions and topological defects [5]. We can thus analyze the alignment of cells in the vicinity of the topological defects under different conditions and observe multiple possible solutions that the cells utilize to adapt to the boundaries. We compare the alignment of various cell types with the micro-ridges and the organization of the monolayers on the patterns. The geometry of the micro-ridges allows us to vary the degree of confinement of the cells, so that we can establish an analogy between this and the anchoring strength in NLCs.

[1] X. Li et al., Proc. Natl. Acad. Sci. 114, 8974-8979 (2017)
[2], G. Duclos et al., Soft Matter 10, 2346–2353 (2014)
[3] G. Duclos et al., Nat. Phys. 13, 58–62 (2017)
[4] T. Turiv et al., Sci. Adv. 6, eaaz6485 (2020)
[5] K. Endresen et al., arXiv:1912.03271 (2020)   

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Autonomous collective motion of identical agents in nonequilibrium is fundamental to many biological and engineering systems. An example from biology is bacterial swarms, that are prototypical dense multi-phase active fluids. Here we present a new method for modeling such fluids under confinement. We use a continuum multiscale mean-field approach to represent each phase by its first three orientational moments, and couple their evolution with those of the suspending fluid. The resulting coupled system is solved using a parallel level set based hybrid Finite Difference-Finite Volume solver on Quadtree meshes for high computational efficiency and maximal flexibility in the confinement geometry. Motivated by recent experimental work, we employ our method to study emergent flows in bacterial swarms. Our computational exploration demonstrate that we can reproduce the observed emergent collective patterns including active dissolution and crystallization. This work lays the foundation for a systematic characterization of natural and synthetic systems such as bacterial colonies, bird flocks, fish schools, colloidal swimmers, or programmable active matter.   

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Nematic liquid crystal environment enables directional propulsion of spherical droplets representing aqueous dispersion of bacterial microswimmers¹ . Here we explore how the dynamics of active droplets can be controlled by patterning the nematic environment with singular and nonsingular director field. We use the plasmonic metamasks technique to pattern the director in a one-dimensionally periodic sequence of splay and bend deformations and in the form of defects, such as semi-integer singular disclinations and integer nonsingular disclinations. We demonstrate that interactions of the active droplet with the director gradients of the environment can be used to control propagation direction, speed, and locations of traps that stop propulsion.

1 Rajabi, M., Baza, H., Turiv, T. & Lavrentovich, O. D. Directional self-locomotion of active droplets enabled by nematic environment. Nat. Phys., doi:https://doi.org/10.1038/s41567-020-01055-5 (2020).   

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Colonies of motile and growing bacteria can be considered active materials that display distinct collective behaviors based on parameters such as bacteria morphology, motility, and environmental confinement. Previously, efforts have focused on categorizing individual phases of distinct behavior, such as clustering or active turbulence. We present a growing colony of motile E. coli at an oil-water interface in which system evolution can be directly and continuously observed using time-lapse microscopy over eight hours. We use image analysis and particle image velocimetry to characterize multiple observed behaviors, which we label clustering, active turbulence, and glassy dynamics. The changes between behaviors are driven by increases in packing fraction due to bacteria growth. We believe that this is a useful model system for the investigation of continuous phase transitions in active materials, particularly the transitions into and away from the widely studied active turbulent phase.   

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Bacteria swarming, cell migration and the collective motion animal groups are all examples of active matter. A paradigmatic system that captures the essence of activity is the Brownian particles (ABP) model, which considers self-propelled disks with excluded volume interactions¹. ABP systems with no alignment exhibit an athermal clustering instability to a phase-separated regime. Several exciting properties such as large density fluctuations, structure factors and hexatic order parameters have been measured showing a clear contrast to equilibrium systems². Yet, as we study active systems of increasing complexity, it becomes more and more challenging to a priori identify the right order parameters. As an alternative, here we propose to perform cluster tomography in space and time by measuring the spatial gap size distribution³ and inter-event time distribution⁴ within particle clusters. We show that such measures can reliably detect different regimes and characterise the transitions between them, even without system-specific order parameters, providing a versatile tool to study a broad range of active systems.

¹Fily, et al. PRL (2012).
²Digregorio et al. PRL (2018).
³Kovács, et al. PRB (2014).
⁴Goh, et al. EPL (2008).