Abstract
The respiratory tract is protected by mucus, a complex fluid transported along the epithelial surface by the coordinated beating of millions of microscopic cilia, hence the name of mucociliary clearance. Its impairment is associated with all severe chronic respiratory diseases. Yet, the relationship between ciliary density and the spatial scale of mucus transport, as well as the mechanisms that drive ciliary-beat orientations are much debated. Here, we show on polarized human bronchial epithelia that mucus swirls and circular orientational order of the underlying ciliary beats emerge and grow during ciliogenesis, until a macroscopic mucus transport is achieved for physiological ciliary densities. By establishing that the macroscopic ciliary-beat order is lost and recovered by removing and adding mucus, respectively, we demonstrate that cilia–mucus hydrodynamic interactions govern the collective dynamics of ciliary-beat directions. We propose a two-dimensional model that predicts a phase diagram of mucus transport in accordance with the experiments. This paves the way to a predictive in silico modelling of bronchial mucus transport in health and disease.
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Data availability
All data that support the plots within this paper and other findings of this study are available from the corresponding author upon reasonable request.
Code availability
Custom codes that were used to analyse experimental data within this manuscript are available from the corresponding author upon reasonable request.
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Acknowledgements
We thank P. Thomas and X.B. D’Journo, service de chirurgie thoracique, Hôpital NORD, AP-HM, for providing biological material. The MACBION project leading to this publication has received funding from Excellence Initiative of Aix-Marseille University - A*MIDEX, a French Investissements d’Avenir programme, and from the French National Research Agency (ANR) (SINUMER project ANR-18-CE45-0009-01). The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007–2013) under REA grant agreement number PCOFUND-GA-2013–609102, through the PRESTIGE programme coordinated by Campus France. A.N. was supported by a fellowship from Fondation pour la Recherche Médicale.
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E.L. and A.V. designed the study. S.G., U.D. and J.F. conceived the computational model. E.L. designed and carried out image analysis. E.L. and C.J. acquired experimental data. A.N. acquired the data on PCP. E.L., C.J. and A.N. analysed experimental data. S.G. implemented and performed simulations. D.G. performed bronchial epithelium cultures. All authors discussed the results and the manuscript. E.L., S.G. and A.V. wrote the paper.
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Extended data
Extended Data Fig. 1 Spatial distribution of ciliated clusters during ciliogenesis.
a, Size distributions of ciliated cluster for different cilia densities φ. The size of clusters is expressed as the number of ciliated cells with a mean cell area of 40 µm². At the beginning of ciliogenesis, most clusters are formed by 1–2 ciliated cells. Upon differentiation of new ciliated cells, more clusters are formed, which grow larger and eventually connect. We observe the appearance of a percolating cluster (for a density above 60 %), in coexistence with clusters of finite size. The size distribution for φ = 68 corresponds to the clusters of finite size, and the percolating cluster has disappeared. For each cilia density, φ and the cluster size distributions are computed on 9 tiles of size 440 µm x 330 µm. φ is the mean density + /- standard deviation. Data are from samples #5 and #6. b–f, Characteristic spatial distribution of ciliated cells at different φ. For φ = 4 %, only sparse clusters of few cells are present (b). While φ increases, the number and the size of clusters increase (c-e). For φ = 70 % we observe a percolating cluster, in coexistence with clusters of finite size (f). The colorbar indicates the number of ciliated cells per cluster and the largest cluster appears in yellow. Scale bars are 50 µm.
Extended Data Fig. 2 Cilia beat frequency (CBF).
a, Frequency map on an area where a swirl is present. The colour codes for the CBF and the CBF distribution is shown in b. Black regions correspond to locations where flowing opaque debris in the mucus prevent the visualization of beating cilia underneath. Scale bar = 40 µm. b, CBF distribution, CBF = 7.6 + /− 1.3 Hz. A lower cut-off has been defined at 4 Hz to prevent artefacts due to flowing debris. c, Kymograph plotted along the blue path displayed in a, corresponding to a ciliated area with the same CBF. Patterns on the kymograph allows to identify ciliary beats with the same phase. This is highlighted by the green lines at the beginning. Yet, the synchronization is not stable over time and the loss of synchronization is highlighted by the blue lines. Spatial scale bar is 20 µm and temporal scale bar is 0.1 s.
Extended Data Fig. 3 Planar cell polarity patterns in absence of mucus.
PCP protein Vangl1 over an area of ~1.3 mm x 1.1 mm in a sample (#21), where a millimetric swirl was initially present and then the mucus had been removed by performing successive washing. The sample has been fixed after one week in absence of mucus. The yellow lines are a guide for the eyes and represent the main orientations orthogonal to Vangl1 (featuring cilia beat directions). The millimetric circular order is lost and PCP exhibits instead numerous swirly patterns. Angle distributions of ciliary beats, computed from Vangl1 orientation, are plotted for 4 quadrants as in Fig. 3 (dashed triangles, arc of a circle with radius of 500 µm and subtending an angle of 35°). The red lines indicate the median of the distributions with α = 90 for top left, α = 96 for top right, α = 96 for bottom right and α = 83 for bottom left. Scale bar = 100 µm.
Supplementary information
Supplementary Information
Supplementary methods, tables and figures.
Supplementary Video 1
For a cilia density lower than 15%, the mucus remains still while the cilia are beating underneath. One can see heterogeneities in the mucus vibrating due to the beating cilia.
Supplementary Video 2
Onset of mucus transport for φ ≈ 25% on day 12, sample 13.
Supplementary Video 3
Pattern formation on day 13, sample 13, same field of view as Supplementary Video 2.
Supplementary Video 4
Swirl of mucus on day 14, sample 13, same field of view as Supplementary Video 2.
Supplementary Video 5
Example of two swirls of mucus that grow by successive accumulation of mucus transported their vicinity. On left side, the swirl is from sample 8, day 12 and on right side the swirl is from sample 7, day 12.
Supplementary Video 6
Millimetric swirl resulting from the growth of the swirl presented in Supplementary Video 5 (left side), sample 8, day 15.
Supplementary Video 7
Mucus swirls rotate clockwise or anticlockwise with equal probability. Left and middle panels show a global swirl. The right panel shows local swirls. Scale bars are 100 μm.
Supplementary Video 8
The left panel shows a raw video of beating cilia. The middle panel shows the resulting temporal standard deviation projection of the video. White strokes reveal the trajectories of the tip of ciliary bundles. Black areas are motionless parts of the video. The right panel shows an overlay of the computed director field of the beat directions and the standard deviation image. The director field is determined by computing the structure tensor (see Methods) to determine the direction of each white pixel on the standard deviation projection image from the middle panel. Scale bar is 20 µm.
Supplementary Video 9
Dehydrated mucus gets stuck above the cilia on a mature epithelium.
Supplementary Video 10
After addition of diluted mucus on the surface of a disorganized epithelium, a new millimetric mucus swirl emerges at the epithelial surface, associated with a strong circular orientational order of underlying ciliary beats (Fig. 4c). The field of view correspond to the central part of Fig. 4c.
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Loiseau, E., Gsell, S., Nommick, A. et al. Active mucus–cilia hydrodynamic coupling drives self-organization of human bronchial epithelium. Nat. Phys. 16, 1158–1164 (2020). https://doi.org/10.1038/s41567-020-0980-z
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DOI: https://doi.org/10.1038/s41567-020-0980-z
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