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In tissues as diverse as amphibian skin and the human airway, the cilia that propel fluid are grouped in sparsely distributed multiciliated cells (MCCs). We investigate fluid transport in this "mosaic" architecture, with emphasis on the trade-offs that may have been responsible for its evolutionary selection. Live imaging of MCCs in embryos of the frog Xenopus laevis shows that cilia bundles behave as active vortices that produce a flow field accurately represented by a local force applied to the fluid. A coarse-grained model that self-consistently couples bundles to the ambient flow reveals that hydrodynamic interactions between MCCs limit their rate of work so that they best shear the tissue at a finite but low area coverage, a result that mirrors findings for other sparse distributions such as cell receptors and leaf stomata.
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34797132
???displayArticle.pmcLink???PMC7616087 ???displayArticle.link???Phys Rev Lett ???displayArticle.grants???[+]
FIG. 1. Ectoderm of embryonic Xenopus laevis at tailbud stages. (a) Schematic side view of MCCs (red) intermixed with secreting cells. (b) Location of MCCs across the embryo (adapted from Refs. [22,23]) and cilia-driven flow (blue arrows). (c) Confocal image of cell membranes (stained by membrane-RFP), with MCCs segmented in red, in ventral region of skin.
FIG. 3. Response of cilia bundles to exogenous shear. (a),(b) Vorticity and velocity vectors before and during perfusion. (c) Velocities u(z;0) and u(z;Ëγe), shear flow Ëγez, and sum Cu(z;0)+Ëγez fitting u(z;Ëγe), where C= F(Ëγe)/F(0). (d) Variation with shear of estimated force F, velocity V and shear rate Ëθ=âu(z)/âz|â measured above cilia tips, and rate of work WâËθV (overlapping Ëθ), normalized by values at Ëγe=0. Shaded regions are 95% confidence intervals of averages over 10 samples.
FIG. 4.
Collective efficiency of a distribution of point forces, in the space of coverage Ï and dissipative coupling constant λ. Dashed lines trace optimization ridges of the extra forces per bundle Fa and Fw driving (a) flow in the outer region and (b) shear above nonciliated cells.
Fig. 2. Flow fields.(a) Lateral view of MCC showing (dashed) path of cilia tips and force F. (b) Experimental velocity field and vorticity in plane normal to skin near several MCCs. (c) Near an MCC, as in (b), with direction of cilia tip motion (black arrows) on ∂Ωc.(d) Estimated flow field u0 for an isolated MCC (blue arrows): Point forces (red arrows) are used to fit velocity near cilia tips. Lateral velocity at (e) x, y (0, 0) and (f) (±40 μm, 0) in experiment (exp) and theory, with u0 driven by an isolated bundle and uc by a bundle exposed to endogenous flow ua (see also Figs. S2–S4 [29]).
Fig. 3. Response of cilia bundles to exogenous shear.(a),(b) Vorticity and velocity vectors before and during perfusion. (c) Velocities u(z; 0) and u(z;γ˙e), shear flow γ˙ez, and sum Cu(z;0)+γ˙ez fitting u(z;γ˙e), where C=F(γ˙e)/F(0). (d) Variation with shear of estimated force F, velocity V and shear rate θ˙=∂u(z)/∂z|ℓ measured above cilia tips, and rate of work W∝θ˙V (overlapping θ˙), normalized by values at γ˙e=0. Shaded regions are 95% confidence intervals of averages over 10 samples.
Fig. 4. Collective efficiency of a distribution of point forces, in the space of coverage ϕ and dissipative coupling constant λ.Dashed lines trace optimization ridges of the extra forces per bundle Fa and Fw driving (a) flow in the outer region and (b) shear above nonciliated cells.
Ainsworth,
Cilia: tails of the unexpected.
2007, Pubmed,
Xenbase
Ainsworth,
Cilia: tails of the unexpected.
2007,
Pubmed
,
Xenbase
Berg,
Physics of chemoreception.
1977,
Pubmed
Brooks,
Multiciliated cells.
2014,
Pubmed
Brumley,
Flagellar synchronization through direct hydrodynamic interactions.
2014,
Pubmed
Faubel,
Cilia-based flow network in the brain ventricles.
2016,
Pubmed
Ferreira,
Physical limits of flow sensing in the left-right organizer.
2017,
Pubmed
Goldstein,
Green Algae as Model Organisms for Biological Fluid Dynamics.
2015,
Pubmed
Hörmanseder,
H3K4 Methylation-Dependent Memory of Somatic Cell Identity Inhibits Reprogramming and Development of Nuclear Transfer Embryos.
2017,
Pubmed
,
Xenbase
Juan,
Multi-scale spatial heterogeneity enhances particle clearance in airway ciliary arrays.
2020,
Pubmed
Karimi,
Xenbase: a genomic, epigenomic and transcriptomic model organism database.
2018,
Pubmed
,
Xenbase
Khelloufi,
Spatiotemporal organization of cilia drives multiscale mucus swirls in model human bronchial epithelium.
2018,
Pubmed
Mitchell,
The evolution of eukaryotic cilia and flagella as motile and sensory organelles.
2007,
Pubmed
Nagata,
Isolation, characterization, and extra-embryonic secretion of the Xenopus laevis embryonic epidermal lectin, XEEL.
2005,
Pubmed
,
Xenbase
Osterman,
Finding the ciliary beating pattern with optimal efficiency.
2011,
Pubmed
Park,
Dishevelled controls apical docking and planar polarization of basal bodies in ciliated epithelial cells.
2008,
Pubmed
,
Xenbase
Pazour,
Proteomic analysis of a eukaryotic cilium.
2005,
Pubmed
Pedley,
Squirmers with swirl: a model for Volvox swimming.
2016,
Pubmed
Pellicciotta,
Entrainment of mammalian motile cilia in the brain with hydrodynamic forces.
2020,
Pubmed
Soares,
Polarity in Ciliate Models: From Cilia to Cell Architecture.
2019,
Pubmed
Thouvenin,
Origin and role of the cerebrospinal fluid bidirectional flow in the central canal.
2020,
Pubmed
Vasilyev,
Collective cell migration drives morphogenesis of the kidney nephron.
2009,
Pubmed
Werner,
Using Xenopus skin to study cilia development and function.
2013,
Pubmed
,
Xenbase