Novel analytical tools reveal that local synchronization of cilia coincides with tissue-scale metachronal waves in zebrafish multiciliated epithelia
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Norway
- Kavli Institute for Systems, Neuroscience and Centre for Neural Computation, Norwegian University of Science and Technology, Norway
- Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Sweden
- Institute for Data-Driven Technologies, Aachen University of Applied Sciences, Germany
- Center for Advancing Electronics, Technical University Dresden, Germany
- Cluster of Excellence 'Physics of Life', Technical University Dresden, Germany
Figures
Figure 1 with 1 supplement
The zebrafish nose as model system for a ciliated epithelium with small and densely packed multiciliated cells.
(A) Surface rendering of a 4-day-old zebrafish larva (top) and a zoom-in of the nasal cavity (bottom). (B) A representative example of a left nose marked by a red box in (A). In the maximum …
Figure 1—figure supplement 1
Quantification of multiciliated cell features in the zebrafish nose.
(A) Top, front and side view of the surface rendering of a zebrafish head at 4dpf (using a transgenic lines expressing Cherry in all cells, ubi:zebrabow). The approximate location of multiciliated …
Figure 2 with 4 supplements
Spectral analysis of cilia beating reveals local coherence but global heterogeneity.
(A) Schematic spectral analysis of a reference pixel. As cilia move through a pixel (black rectangle), the pixel intensity fluctuates. The Fourier transform of pixel intensity time series (top), …
Figure 2—figure supplement 1
Distribution of ciliary beat frequencies.
(A) Ciliary beat frequency of six different fish, for left (top) and right (bottom) noses show high levels of heterogeneity. (B) Ciliary beating remains relatively constant over time. Ciliary beat …
Figure 2—figure supplement 2
Cilia from individual cells beat at similar frequencies.
(A–B) Cilia from individual cells beat at a similar frequency. Representative examples of the beating of one cell versus the entire multiciliated epithelium. A hspGGFF19B:UAS:GFP animal, expressing …
Figure 2—figure supplement 3
Systematic analysis of relationships between coherence and spectral power.
A grid of 16 reference pixels with equal spacing across the nose were chosen for systematic analysis. The relationship between coherence and spectral power at the frequency of the reference pixel is …
Figure 2—figure supplement 4
Cilia beating displays local coherence in the zebrafish brain.
(A) Schematic representation of the adult brain explant and location of multiciliated cells on the tela choroida. (B) (Top) Peak coherence for three reference pixels (indicated with black crosses) …
Figure 3 with 1 supplement
An increase in fluid viscosity decreases ciliary beat frequency and extends the spatial range of cilia coherence.
(A–B) Ciliary beating frequency decreases under increasing viscosity conditions (0–2% methylcellulose) and partially recovers upon re-exposure to 0% methylcellulose (0%*). (A) Representative example …
Figure 3—figure supplement 1
Ciliary beating in different viscosity conditions.
(A) Difference probability histograms between the various viscosity conditions for the example shown in Figure 3C. (B) The fraction of synchronized pixels (coherence>0.25) increases with viscosity. …
Figure 4 with 2 supplements
Wave directions and wavelengths of local metachronal coordination.
(A-A’) Metachronal coordination observed using a conventional kymograph-based analysis. (A) A kymograph was drawn (red line in inset, representing transverse cilia beating) on a light transmission …
Figure 4—figure supplement 1
Metachronal wave directions and lengths.
(A) Wave parameters, wave direction (top), and wavelength (bottom), for a representative fish over the course of 10 min. (B) Wave direction (top), and wavelength (bottom), for a representative fish …
Figure 4—figure supplement 2
Cilia beating displays local metachronal coordination in the ependymal layer of the zebrafish brain.
(A–B) Neighboring pixels with similar frequency (beat frequency map, A) are segmented into frequency patches (B). (C) Phase angles are determined from Fourier transforms evaluated at the prominent …
Figure 5 with 4 supplements
Metachronal waves are chiral.
(A–B) Wave direction (top) and wavelength (bottom) for three left (A, red) and three mirrored right (B, green) noses show asymmetry in the wave direction between the left and right noses. …
Figure 5—figure supplement 1
Difference in wave direction between left and right noses.
Wave parameters, including phase angles, wave direction, and wavelength, for all aligned left (A1–A2) and mirrored right (B1–B2) noses. Note that the transparency in wave direction reflects the …
Figure 5—figure supplement 2
Cilia orientation is mirrored in the left and right noses.
Immunohistochemistry on a left nose stained for gamma-tubulin (basal body marker, red) and glutamylated tubulin (cilia marker, white) for left (n=3) and right (n=2) noses. Ciliary direction measured …
Figure 5—figure supplement 3
No anatomical differences between left and right noses.
A systematic comparison of left (red) and right (green) noses (A) revealed no significant differences in the median CBF (B; left n=20; right n=24), nose (C; left n=13; right n=12) and cavity size (D;…
Figure 5—figure supplement 4
Sequential measurement of ciliary beating and fluid flow direction.
(A,D) Light transmission images of 4-day-old zebrafish larva left (A; n=14) or mirrored right (D; n=14) nose at ×63 magnification. Note that the images are rotated to align with the reference left …
Figure 6 with 1 supplement
Metachronal coordination enhances fluid pumping and reduces steric interactions, but does not affect fluid flow direction.
(A) Possible traveling wave solutions in a computational model of a cilia carpet. Left: Cilia are arranged on a triangular lattice (gray dots), with three-dimensional cilia beat pattern from Parameci…
Figure 6—figure supplement 1
Visualization of increasing noise strength on synthetic metachronal waves.
(A) Synthetic phase map of a metachronal wave with wave direction of 190º and wavelength 4 µm, represented with pixel resolution of 0.15 µm. Noise was modeled as superposition of independent Fourier …
Author response image 1
Coherence-versus-distance distributions for high and low frequencies.
(A) Histogram representing the CBF for all pixels and their segmentation into high and low CBF. In red are indicated the bottom 33% CBF values and in green the top 33% CBF values. (B) Map showing …
Author response image 2
Author response image 3
Impact of the binning of the power spectrum on CBF values shown on CBF heatmaps (top) and histograms (bottom).
We used a binning of 0.54Hz for all our analysis due to their minimal impact and good coverage of CBF values.
Author response image 4
Histogram showing the average CBF of multiciliated cells in the nose of the zebrafish larvae (n=130 animals).
From Reiten et al., 2017.
Author response image 5
Segmentations into frequency patches with or without binning and with a minimum patch size of 400 or 800 pixels.
Note that a binning of 0.54Hz and minimum size of 400 pixels (9 µm2) provides the best segmentation of the ciliated epithelium with a reasonable number of patches.
Author response image 6
Coherence analysis for 3 reference pixels for different recording lengths (10-240s).
Note that increasing recording length reduces the background values, but do not changes the overall coherence patterns. We recommend a duration of 30s to increase signal-to-noise ratio of the …
Videos
Video 1
Measurement of metachronal wave properties in segmented frequency patch.
Video 2
Measurement of metachronal wave in a 30 s long recording.
Each frame of the movie represents the analysis of 20s-long sliding windows. The timer indicates the center of the sliding window.
Video 3
Metachronal wave direction is stable over time (total of 10 min) as shown for four examples.
Every frame of the video corresponds to the output of a Fourier Transform calculated over a 30 s timebin.
Tables
Key resources table
| Reagent type (species) or resource | Designation | Source or reference | Identifiers | Additional information |
|---|---|---|---|---|
| Genetic reagent (zebrafish) | Et(hspGGFF19B:Gal4)Tg(UAS:gfp) | Reiten et al., 2017; Asakawa et al., 2008 | ZDB-ALT-080523–22 | |
| Genetic reagent (zebrafish) | Tg(foxj1a:gCaMP6s)nw9 | This study | N/A | Trangenic zebrafish line expressing the calcium indicator GCamp6s in multiciliated cells of the nose, Jurisch-Yaksi lab, NTNU |
| Genetic reagent (zebrafish) | Tg(Ubi:zebrabow) | Pan et al., 2013 | ZDB-ALT-130816–1 | |
| Genetic reagent (zebrafish) | mitfab692 | Lister et al., 1999 | ZDB-ALT-010919–2 | |
| Antibody | Mouse monoclonal glutamylated tubulin (GT335) | Adipogen | Cat#AG-20B-0020-C100; RRID: AB_2490210 | Dilution 1:400 |
| Antibody | Rabbit polyclonal Gamma-tubulin | Thermo Fisher | Cat# PA5-34815; RRID: AB_2552167 | Dilution 1:400 |
| Antibody | Rabbit Polyclonal anti beta-catenin | Cell Signalling Technologies | Cat#9562; RRID:AB_331149 | Dilution 1:200 |
| Antibody | Chicken Polyclonal Anti-GFP | Abcam | Cat#ab13970; RRID:AB_300798 | Dilution 1:1,000 |
| Antibody | Goat Polyclonal anti-rabbit IgG (H+L) Highly Cross-adsorbed Alexa Fluor 555 | Thermo Fisher | Cat# A32732; RRID:AB_2633281 | Dilution 1:1,000 |
| Antibody | Goat Polyclonal anti-mouse IgG (H+L) Highly Cross-adsorbed Alexa Fluor 647 | Thermo Fisher | Cat#A32728; RRID:AB_2633277 | Dilution 1:1,000 |
| Chemical compound, drug | Alpha-bungarotoxin | Invitrogen | Cat#BI601 | |
| Chemical compound, drug | Ultrapure LMP agarose | Fisher Scientific | Cat#16520100 | |
| Chemical compound, drug | DAPI | Invitrogen | Cat# D1306 | Dilution 1:1,000 |
| Software, algorithm | ImageJ/Fiji | Schindelin et al., 2012 | ||
| Software, algorithm | Cell counter plugin for Fiji/ImageJ | Kurt De Vos, University of Sheffield | https://imagej.net/Cell_Counter | |
| Software, algorithm | BigWarp | Saalfeld lab, Janelia https://imagej.net/BigWarp; Bogovic et al., 2016 | ||
| Software, algorithm | Zebrascope software in Labview | Ahrens lab, Janelia Farm; Vladimirov et al., 2014 | ||
| Software, algorithm | Manta Controller | Yaksi lab, NTNU; Reiten et al., 2017 | ||
| Software, algorithm | Fast Fourier Analysis | MATLAB, this paper; Jurisch-Yaksi, 2023 | https://github.com/Jurisch-Yaksi-lab/CiliaCoordination | |
| Software, algorithm | Coherence analysis | MATLAB, this paper; Jurisch-Yaksi, 2023 | https://github.com/Jurisch-Yaksi-lab/CiliaCoordination | |
| Software, algorithm | Wave analysis | MATLAB, this paper; Jurisch-Yaksi, 2023 | https://github.com/Jurisch-Yaksi-lab/CiliaCoordination | |
| Software, algorithm | Computation model of cilia carpet | Solovev and Friedrich, 2022b; Solovev and Friedrich, 2021a; Solovev and Friedrich, 2021b; Solovev and Friedrich, 2021c | https://github.com/icemtel/reconstruct3d_opt, https://github.com/icemtel/stokes, and https://github.com/icemtel/carpet | |
| Software, algorithm | ColorBrewer: Attractive and Distinctive Colormaps | Brewer, 2022; Cynthia Brewer | https://github.com/DrosteEffect/BrewerMap/releases/tag/3.2.3, GitHub. Retrieved December 4, 2022 | |
| Software, algorithm | Beeswarm | Stevenson, 2019; Ian Stevenson | https://github.com/ihstevenson/beeswarm GitHub. Retrieved December 4, 2022. | |
| Other | Sutter laser puller | Sutter | Model P-200 | pulling needles for injection |
| Other | Pressure injector | Eppendorf | Femtojet 4i | injection of bungartoxin for paralysis |
| Other | Confocal microscope | Zeiss | Examiner Z1 | confocal imaging |
| Other | 20 x water immersion Plan-Apochromat NA 1 | Zeiss | 421452-9880-000 | confocal imaging |
| Other | Light-sheet objective | Nikon | 20 x Plan-Apochromat, NA 0.8 | light-sheet imaging |
| Other | Transmission microscope | Bresser, Olympus | transmission imaging | |
| Other | Transmission microscope objective | Zeiss | 63 X, NA 0.9 | transmission imaging |
