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Jan 2020

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Automated Analysis of Cerebrospinal Fluid Flow and Motile Cilia Properties in The Central Canal of Zebrafish Embryos
斑马鱼胚胎中央管中脑脊液流动和运动纤毛特性的自动分析   

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Abstract

Circulation of cerebrospinal fluid (CSF) plays an important role during development. In zebrafish embryo, the flow of CSF has been found to be bidirectional in the central canal of the spinal cord. In order to compare conditions and genetic mutants across each other, we recently automated the quantification of the velocity profile of exogenous fluorescent particles in the CSF. We demonstrated that the beating of motile and tilted cilia localized on the ventral side of the central canal was sufficient to generate locally such bidirectionality. Our approach can easily be extended to characterize CSF flow in various genetic mutants. We provide here a detailed protocol and a user interface program to quantify CSF dynamics. In order to interpret potential changes in CSF flow profiles, we provide additional tools to measure the central canal diameter, characterize cilia dynamics and compare experimental data with our theoretical model in order to estimate the impact of cilia in generating a volume force in the central canal. Our approach can also be of use for measuring particle velocity in vivo and modeling flow in diverse biological solutions.

Keywords: Cerebrospinal fluid (脑脊髓液), Fluid mechanics (液体力学), Central canal (中央管), Bidirectionality (双向性), Flow velocity profile (流体速度剖面), Cilia beating (纤毛跳动), Zebrafish (斑马鱼), Development (发育)

Background

In zebrafish embryos, cerebrospinal fluid (CSF) flow is observable from 24 h post fertilization (hpf) in the central canal of the spinal cord (Sternberg et al., 2018; Cantaut-Belarif et al., 2018) and later extends to the brain ventricles (Olstad et al., 2019). In the embryonic central canal, CSF flows bidirectionally: towards the tail on the ventral side and towards the head on the dorsal side (Sternberg et al., 2018; Cantaut-Belarif et al., 2018; Thouvenin et al., 2020). This bidirectionality is caused by the beating of polarized motile cilia mostly active in the ventral region of the central canal driving a caudally directed movement of fluid in the ventral region and creating a counter flow in the dorsal region.


Because of the narrow geometry of the central canal and the large contribution of Brownian motion, classical analysis tools failed to quantify the bidirectional properties of CSF flow. Recently, we developed an automated method based on kymograph analysis allowing the quantification of embryonic CSF flow (Thouvenin et al., 2020). One challenge now is to generalize this approach in order to compare a variety of genetic animal models and experimental conditions. This is of special interest for investigations on cilia-defective mutants in which motility defects are partial and the consequences on flow are not fully understood.


The goal of this protocol is to guide the computation of CSF flow profiles from fluorescence measurements. We developed a user-friendly interface program to generate flow profiles from collected data. We additionally provide a protocol to compare experimentally measured profiles of embryonic CSF flow to a theoretical profile. Our theoretical model relies on the assumption that the average flow rate is null. In this case, the volume force fv that gives rise to CSF flow can be computed and compared between different conditions. The volume force depends on different cilia parameters: fv=αfμ/h, where f is the average cilia beating frequency, h the width of the region occupied by the cilia, μ the viscosity, and α a dimensionless parameter. We finally show how to quantify the main cilia frequency f using transgenic embryos with cilia labeled by fluorescent proteins.


Materials and Reagents

  1. 2 ml Eppendorf tubes (Eppendorf, catalog number: 00 30120094 )

  2. Glass bottom Petri dish (MatTek Corporation, catalog number: P50G-1.5-14-F )

  3. Home-made Microinjection needles from Borosilicate Glass with Filament, OD 1 mm, ID 0.5 mm, length 10 cm, Fire polished (Sutter Instrument Company, catalog number: BF100-50-10 )

  4. FluoSphereTM size kit #2, six sizes (Molecular Probes, catalog number: F8888 )

    Note: This protocol is optimized for 20 nm carboxylate FluoSpheres of center wavelength 505/515 nm (yellow/green).

  5. Nacre, AB and Tüpfel long fin (TL) strains of Danio rerio aged between 1 and 6 days post fertilization (dpf) can be used to achieve the CSF flow profile quantification. When optical imaging is performed at the embryonic stage, the pigmentation observed in AB and TL lines is not affecting either imaging using spinning disk at shallow depth nor analysis. The comparison of experimental measures of CSF flow profile with the theoretical model only holds for zebrafish embryos. We used the Tg(β-actin:Arl13b-GFP) transgenic line to image cilia in vivo (Borovina et al., 2010)

  6. 3,000 MW TexasRed dextran, Excitation/Emission wavelength: 595/615 (ThermoFisher Scientific, catalog number: D3329 )

  7. α-bungarotoxin (TOCRIS, catalog number: 2133 )

    Note: We injected α-bungarotoxin solution to paralyze the fish, see Recipes to prepare the solution.

  8. Tricaine (ethyl 3-aminobenzoate methane sulfonate salt, Sigma-Aldrich, catalog number: A5040 )

  9. UltraPureTM low melting point agarose (Invitrogen, catalog number: 16520100 )

  10. NaCl (Sigma-Aldrich, catalog number: S7653 )

  11. KCl (Sigma-Aldrich, catalog number: P9333 )

  12. HEPES (Sigma-Aldrich, catalog number: H3375 )

  13. Alpha-D-Glucose (Sigma-Aldrich, catalog number: 158968 )

  14. CaCl2 dihydrate (Sigma-Aldrich, catalog number: H3375 )

  15. NaOH (Sigma-Aldrich, catalog number: 71687 )

  16. Artificial Cerebrospinal fluid (aCSF) (see Recipes)

  17. α-bungarotoxin solution (see Recipes)

  18. TexasRed solution (see Recipes)

  19. Injection Mix 1 (see Recipes)

  20. Injection Mix 2 (see Recipes)

Equipment

  1. Fine forceps (Fine Science Tools, catalog number: 11412-11 )

  2. Spinning disk microscope (Leica Microsystems, model: Inverted Leica DMI8 ) equipped with a Hamamatsu Orca Flash 4.0 camera (Maximum 100 frames per second full frame), using a 40× water immersion objective (N.A. = 0.8) or any similar

  3. Pipette puller (Narishige Ltd., model: PC-10 or PC-100 puller , or any similar)

  4. Sonicator (VWR, Ultrasonic Cell Disruptor, Vibra-CellTM VCX 130 )

  5. Picospitzer injector (World Precision Instruments, Sarasota, USA)

Software

  1. MATLAB 2018b (MathWorks, Mountain View, CA, USA) and image processing toolbox

  2. Fiji (Schindelin et al., 2012)

  3. Microsoft Excel 2010 (for .xlsx output format)

Procedure

  1. Injections and imaging of fluorescent beads

    Notes:

    1. To measure CSF flow profiles in the central canal of the spinal cord, we inject in brain ventricles a solution of 20 nm fluorescent beads diluted in artificial CSF (aCSF). Prior to injection, the sonication of this solution is a critical step to avoid aggregates of beads that would not enter the central canal. We successfully measured flow with beads of 20 nm and 45 nm but when diameter reaches 100 nm, beads fail to enter the central canal even after sonication. The bigger the particles, the brighter they are, and the less Brownian motion they experience, making the flow quantification more precise, but only if the beads can reach the central canal. Injection in the caudal central canal (Thouvenin et al., 2020) is possible but more complicated and not recommended as it may alter the CSF flow in the rostral central canal.

    2. We recommend injecting beads together with TexasRed to make sure that the injection was successful and to identify the boundaries of the central canal if needed. If so, 0.2% TexasRed can be added to the injection mix after the sonication step (injection Mix 2).

    3. From our experience, injections in the brain ventricles are easier (especially at larval stage) if the fish is dorsally-mounted. It is possible to perform the injection on dorsally-mounted animals, and then flip the agar block or unmount the fish to mount it again laterally in a new dish. As mounting/unmounting can increase the risk of hurting the larva, flipping a block of agar cut with a fine surgical knife (Fine Science Tools, catalog number: 10073-14) is recommended.

    4. To avoid motion artifacts, imaging of beads trajectory has to be performed on paralyzed animals. We simply added α-bungarotoxin directly to the injection mix in order to inject the animal only once and reduce experiment time.

    5. Video 1 illustrates the experimental procedure starting from the embryo dechorionation and mounting, and shows the ventricular injection.


    1. Injection mix and injection pipette preparation

      1. Dilute fluorescent beads (FluoSpheres) to a 2% concentration (v/v) in aCSF in a final volume of at least 100 µl. We also recommend using large 2 ml microtubes in order to avoid dispersion of the solution during the sonication step. Keep the mix on ice.

      2. Sonicate beads by giving 3 pulses of 3-4 s each at a power output of 50 W. Make sure the mix containing diluted beads stays on ice (sonication is exothermic).

      3. Pull microinjection needles from borosilicate glass capillaries with a 2-step needle puller. Adjust temperature and pulling force to produce a long and sharp funnel shape needle with an approximate tip diameter of 1-3 µm (equivalent to egg injection pipettes).

      4. Prepare injection Mix 1 or Mix 2 (see Recipes).

      5. Fill the pipette with 4 μl of injection Mix.

      6. Connect the pipette to the Picospritzer device (Parker, Hollis, NH, USA).

      7. Cut the extremity of the pipette with pliers to get a 1-3 nanoliters injection drop. The volume of the drops can be calibrated prior to the experiment.

      8. (Optional) To calibrate the volume of the drops at a fixed ejection pressure, fill the injection pipette with a defined and fixed volume of aCSF (e.g., 0.2 µl), and connect the pipette to the picospitzer device. Prepare a dish containing mineral oil and inject drops in the mineral oil until the injection pipette is empty. Count the number of drops ejected and use it to calculate the average volume of each drop. The volumes of the drops can be adjusted by changing the ejection pressure or the diameter of the pipette tip.


    2. Embryos mounting and injection (see Video 1)

      1. Dechorionate 26-28 hpf embryos manually using fine forceps. Other dechorionation techniques such as the enzymatic digestion should be equally efficient.

      2. Anesthetize the embryos in 0.02% w/v Tricaine solution (or in a dish in contact with ice) to stop spontaneous twitches during the mounting step and rinse once mounting is done.

      3. Mount the embryos laterally in 1.5% w/v low melting point agarose. Make sure to orient thoroughly the posterior axis of the animal to image sufficiently flat and long portions of the lumen of the central canal. Add at least 1 ml of system water when agarose has solidified so that the embryo can breathe and to dilute the remaining tricaine solution.

      4. Inject previously prepared solution mix in the hindbrain (or ‘rhombencephalic’) ventricle (Figure 1). If 0.2% TexasRed were added (injection Mix 2), injection quality can be controlled by observing the brain ventricles filled with the colored solution. If not (injection Mix 1), injection quality can be assessed by observing a slight and transient swelling of the ventricle (see Video1).

      5. Put injected embryos at 28 °C for 1 h to allow the diffusion of fluorescent beads down to the central canal. Make sure system water covers the entire surface of the dish to compensate for evaporation.


        Video 1. Experimental procedure for mounting and injecting fluorescent beads in zebrafish embryos

    3. Optical imaging of fluorescent beads in the central canal

      Notes:

      1. Time-lapse images can be acquired at 26 °C using a spinning disk confocal microscope mounted in a thermostatic chamber. This allows a better control of temperature variations that may affect CSF flow properties and/or cilia beating properties.

      2. We recommend to orient the embryo always in the same direction with the rostral side on the left and the dorsal side on the top. If not, correct orientation can be restored via image processing. Note that, in wild type embryos, the ventral wall of the central canal is typically flatter than the dorsal wall.

      3. Imaging could be performed with any imaging system as long as the signal to noise ratio (SNR) is high enough, and the imaging speed is above a few frames/s. Upright or inverted spinning disk can be chosen. Spinning disk imaging seems the most adequate but widefield microscope could be suitable as well with bright fluorescent beads. Confocal or two-photon microscopes could also be used, although the imaging speed might be limited with classical confocal setups and in two-photon microscopes, the salt-and-pepper noise generated might be problematic.

      4. If TexasRed is injected together with 505/515 nm emitting beads, make sure that the emission filters of the microscope allow dual color imaging (avoid using long-pass filters that would lead to bleed-through).

      5. Because imaging was mostly performed in the sagittal plane at the embryonic and larval stage using visible laser for excitation, pigmentation was not an issue and did not therefore require the use of PTU.


      1. As the central canal shape and cilia properties may differ along the rostrocaudal axis, we recommend imaging always at the same rostro-caudal position. In our case, we focused on 3 segments above the yolk extension (Figure 1). Because spinning disk microscopes perform sharp optical sectioning, we advise using either the Differential Interference Contrast (DIC) or transmitted light channel to image somites and central canal together. If TexasRed was injected, the red epifluorescence channel can be superimposed to visualize the central canal using epifluorescence before switching to the spinning disk mode (Figure 1).

      2. Perform time-lapse 2D acquisitions at 10 frames/s for 30 s. Carefully mount the fish so that the central canal is horizontal over a long distance. By choosing the Z plane in which the apparent diameter of the central canal is maximal in the sagittal plane, imaging occurs at the center of the central canal, onto the midline. By doing so, with the 40× NA = 0.8 objective, the central canal mostly fits within the optical section.

      3. FluoSpheres flowing in the CSF are photostable: high laser power can be used with minimal photobleaching in order to get high signal to noise ratio.

      4. Use the program GeneProfile to generate the CSF flow profile from the acquired data. See Data analysis section for more details.

      5. Fit the CSF flow profile to the theoretical bidirectional flow expected in wild type embryos using the same program GeneProfile. See Data analysis section for more details.



      Figure 1. Brain ventricle injection site and injection quality assessment. Left panel: Injection site of fluorescent beads in the hindbrain ventricle of a 30 h post fertilization (hpf) embryo. An hour after injections in the hindbrain ventricle, 20 nm beads have propagated along the central canal. Right panel: TexasRed (top) and 20 nm beads (bottom) imaging with spinning disk in the central canal of the spinal cord above the yolk extension. Scale bar: 10 µm.


  2. Quantification of the kinematics of motile cilia

    1. Embryo mounting and paralysis

      1. Dechorionate 26-28 hpf Tg(β-actin:Arl13b-GFP) embryos (Borovina et al., 2010) screened for GFP.

      2. Put the embryos in 0.02% w/v Tricaine solution (or in a dish in contact with ice) to stop spontaneous twitches during the mounting step.

      3. Mount the embryos laterally in 1.5 % w/v low melting point agarose in a glass bottom Petri dish. When agarose has solidified, add system water. Make sure that Tricaine is diluted out.

      4. Paralyze embryos. Prepare injection pipette similarly to Step A1. Fill the pipette with a solution of 500 µM α-bungarotoxin. Perform a single 1 nl injection in the caudal-most muscles and check that it induces a full paralysis. If the central canal needs to be visualized properly, TexasRed can be injected together with α-bungarotoxin in the muscles, by replacing aCSF with TexasRed solution when diluting the α-bungarotoxin stock aliquots (see Recipes). TexasRed is able to cross the blood brain barrier and penetrate inside the central canal at early developmental stages.

    2. Optical imaging of cilia dynamics

      1. Make sure the temperature of the room is controlled at 26 °C ± 2 °C to avoid variations in cilia beating frequency across experiments.

      2. Using a spinning disk microscope, monitor the motility of cilia via time-lapse acquisitions in 2D using a blue laser for excitation of the Arl13-GFP. Acquire a single image of TexasRed injected in the brain ventricles using a green laser for excitation to reliably measure the central canal diameter. In order to capture the highest beating frequencies, acquisition rates of 100-200 Hz should be chosen. If the system relies on a CMOS camera, the frame rate can be increased by positioning the central canal along the lines of the camera and reducing to the minimum the number of lines to image the central canal. Exposure time should be sufficient to visualize GFP-positive cilia.

      3. Use the program cilia analysis to extract cilia beating frequency, length and angle. See Data analysis section for more details.

Data analysis

On top of the experimental procedures, we detail below two independent analysis workflows.

    The first analysis (Section A) enables to obtain the CSF flow profile from the time series of bead trajectories acquired in Part Procedure-A. This also allows measuring the total CSF flow rate (Section B), which is expected to be null in WT embryos (Thouvenin et al., 2020). If adequate (see conditions below), the experimentally measured CSF flow can be fitted to a bidirectional flow model (Thouvenin et al., 2020) in order to extract the volume force generated by the motile cilia.

    The second analysis workflow (Section C) uses the cilia beating movies (Procedure-B) to extract cilia parameters, including each cilia main beating frequency, length, and angle.

    If appropriate, the last section (Section D) aims to combine the outputs from the two analysis workflows and extract a parameter we called α, an ad hoc coupling parameter that measures how multiple cilia efficiently work together to generate a flow.

  1. CSF flow profile generation

    Specifically for this protocol, we developed a user-interface platform to allow users to generate CSF flow profiles as easily as possible. Here, we present the analysis workflow (Figure 2) and how to generate a first CSF flow profile from the fluorescent beads measurements. More subtle fine tuning of parameters is available within the user interface to adapt to variable imaging conditions, and is fully described in the document ManualGeneProfile.pdf file that can be found with the software.

        As input, the analysis takes 2D time lapses of beads flowing in the central canal (Figure 2A1). In order to generate kimographs, we swap for a given dorsoventral position the axes so that the X axis corresponds to the rostrocaudal position and the Y axis to time. Then, the beads trajectories appear as lines whose slopes reflect the direction and speed of the particles along the rostrocaudal axis. In order to build the flow profile, the program filters each kymograph and performs automatic segmentation of all lines in each kymograph (Figure 2B2). It then extracts the slope of each line, and converts it into the particle velocity, in order to build a histogram of velocities for each dorso-ventral position (Figure 2B3). By calculating the average velocity at each position, we generate the CSF flow profile (Figure 2C1).



    Figure 2. Principle of the CSF flow profile analysis workflow. The CSF flow profiles are calculated using 2D time lapses of fluorescent beads flowing in the central canal (A1), and our custom user interface software (A2). The Start Kymograph button starts the analysis by first calculating kymographs from 2D time lapses by swapping dimensions (B1). Each kymograph is filtered, and all lines, corresponding to one particle trajectory, are segmented (B2). The angle of each line is then transformed to a particle velocity value, and aggregated into a speed histogram for each D-V position (B3). The flow profile is then calculated by extracting the mean and standard error of each histogram (C1). The flow profile can finally be fitted to our bidirectional flow model, to extract quantitative flow parameters (C2). Horizontal scale bars are 15 µm and vertical scale bar is 5 s.


    1. Launch program

      1. Run Main_GeneProfile.m (requires MATLAB 2018b or later).

      2. Alternatively, download and install the standalone application. Once it is installed, go to the command window and navigate to the installed folder. Run: application\GeneProfile.

    2. The user interface window in Figure 2A2 opens.

    3. Select .tif files to analyze. Multiple files can be selected at once, and they will be processed one by one.

    4. Enter the frame time in seconds and pixel size in microns, corresponding to the experimental parameters.

    5. For the analysis to work, the central canal should be as horizontal and flat as possible. Choose the longest horizontal portion of the canal with a few pixels outside the central canal on both sides (Figure 2A1). The rotation and crop of the region of interest can be done either manually, with Fiji, or any equivalent software, or using the provided user interface by clicking the RotationAndCrop button. In this case, a new interface aiming to select a region of interest appears when the StartKymograph button is pressed.

    6. Run Start Kymograph to calculate the kymograph and the histograms of beads velocity at each dorso-ventral position. It then measures the mean of each histogram to compute the flow profile. In case multiples input .tif files are used, each profile is displayed sequentially. The data is saved in the Matlab workspace in a matrix called CSFProfile, and is also saved in the desired output.

    7. Possible outputs are .mat, .xlsx, or both, and set in the user interface. For the .xlsx output, Excel has to be installed on the computer. The .mat generates a structure that contains, for each file, the dorso-ventral position, the flow at each position, the standard error, as well as the speed histograms at the extrema of the flow profile. In the .xlsx output, the data from each file is saved in a different sheet, and the dorso-ventral position, the flow at each position, and the standard error are saved.

    8. The program ends by closing the interface window.


  2. Fitting the velocity profile with a model

    In Thouvenin et al. (2020), we developed a simple model accounting for the bidirectionality of CSF flow in zebrafish embryos. In this protocol, the users can use our script to automatically fit their experimental data of CSF flow to the theoretical model we developed (Figure 2C2). This allows users to check 1) whether their experimental conditions lead to a similar CSF flow than the one we observed in the central canal of wild type (WT) zebrafish embryos, and if this is the case 2) to extract quantitative parameters from the fit. The program allows extracting 4 hydrodynamics parameters: 1) The volume force generated by motile cilia, 2) the pressure gradient that is established in the canal to oppose the cilia beating, 3) the width of the region bearing motile cilia, and 4) the diameter of the central canal. In order for the fit to be meaningful, the two assumptions of our bidirectional flow model should be respected: a cylindrical geometry for the central canal and the “no net flux” condition (Thouvenin et al., 2020). As a reminder, under these two assumptions, we showed that the averaged velocity profile can be fairly described by a piecewise second-order polynomial, defined as:

    where a1, a2, a3, b1 and b2 are expressed as a function of the parameters of the problem:



    Here d is the diameter of the channel and μ the viscosity of the CSF, dP/dx is the pressure gradient and fv is the average force per unit volume generated by the cilia. The latter two parameters can be measured experimentally from the CSF velocity profiles processed with the GeneProfile interface.

        Our theoretical model describes a symmetric bidirectional flow for which the net total flow rate is null. In the user interface, before launching the fitting tool, we provide the user an estimate of the bidirectionality of the flow, called β that is defined as:



        β varies between 0% for a purely monodirectional flow and 100% for a purely bidirectional flow (the flow rate advected caudally equals the flow rate advected rostrally).
      We advise users not to perform the fit of velocity profiles for values of β < 70%, because under this arbitrary threshold, the “no flux” condition is no longer valid, and therefore the parameters of the fit are meaningless.

    1. Once the flow profile is calculated (Data analysis Section A), the “Fit Model” button on the right (Figure 2A2) turns green. The fit can be performed by pushing this button.

    2. Two possibilities can arise:

      1. If β < 70%, we estimate that the flow is not bidirectional enough to fit the velocity with our model, and display the warning message “We advise the user not to go further”. If the two assumptions for our model are not respected, we advise to click on the “Stop here” button in order to stop the fitting process. If the measured flow profile was robustly measured, having a low β means that the flow could not be simply explained by the action of motile cilia in a closed cylindrical geometry and that another model should be developed by taking into account other physical effects.

      2. If β > 70%, the flow can be reasonably fitted with the simple model, and a verification message is sent to the user. Click on “Yes”.

    3. The experimental velocity profile (in blue on the bottom right plot of the user interface, Figure 2A2) is then fitted by the theoretical model (in red on the plot). The plot is also saved in .fig and .png format (Figure 2C2). The .fig file allows the user to modify the plot, and do aesthetic changes, as well as to save in vector formats (.eps, .pdf, .svg).

    4. Several information can be extracted from the fit, which are detailed below. The data are stored in either an .xls file, and/or a .mat file, called “TheoreticalProfiles”, where:

      1. The velocity is stored in a 10000 x 1 vector called “Profile” (in μm/s) and the rostro-caudal position in a 10000 x 1 vector called “X” (in μm).

      2. The volume force fv generated by the cilia is stored in the variable called “f_v” (in N.m-3).

      3. The pressure gradient dP/dx, opposing the cilia beating due to the closed geometry of the central canal, is stored in the variable “GradP” (in N.m-3).

      4. The width of the ciliary region, where the volume force fv is generated in the model, is stored in the variable “l_cilia” (in μm).

      5. The measured diameter of the central canal is stored in the variable “Diameter” (in μm). Note that, if required, we advise to use a direct measurement with TexasRed to measure the central canal diameter, since deducing the diameter from the kymograph may be imprecise.


  3. Cilia frequency measurement

    This section aims to describe the analysis protocol to estimate the main beating frequency of cilia (see Thouvenin et al., 2020), from the fluorescence cilia time lapse acquisitions described in the section Procedure B.

        Similarly to section Data Analysis A, we describe here the principle of the analysis workflow (Figure 3), as well as key instructions to perform a first analysis. Detailed instructions, as well as descriptions of fine-tuning parameters are available in an external document ManualCilia.pdf that can be found with the shared code.

        The program first loads the imaging data with cilia dynamics versus time (Figure 3A), and applies a local average filter (of size 4 by default) to increase the cilia SNR. For each pixel in the filtered data, the time series is extracted and Fourier transformed (Figure 3B). The 5 maximal peaks of the Fourier spectrum are extracted, but, by default, only the first one is used. The frequency of the other peaks can be used for validation (e.g., if sampling errors are made, the sum of the frequencies of the first and second peak is equal to the acquisition frequency). A 2D image with the main frequency found at each pixel is thus created (Figure 3C). In noisy regions, it outputs a random frequency, but in cilia regions it draws regions of interests of a given frequency that we considered to be single cilium. Each of these regions of interest containing more than 40 pixels (7.5 μm2) is finally segmented and analyzed. The parameters frequency, diameter, eccentricity, area, angle, and major axis length are extracted and associated to their corresponding cilia parameters.

        If a comparison between dorsal and ventral cilia is of interest (Thouvenin et al., 2020), the program allows to manually draw a line at the center of the central canal and classify cilia as dorsal or ventral with respect to their relative position from the central line. This procedure is not described further here, but can be found in the document “ManualCilia.pdf” located in the same folder as the shared Matlab code.



    Figure 3. Principle of the beating cilia analysis. 2D time lapses of cilia beating (A) are analyzed by measuring the time Fourier transform at each pixel (B). 3 spectra corresponding to the pixel at the center of the three regions drawn in (A) are plotted. The frequency of the peak of maximum amplitude (arrows in (B)) is extracted for all spectra, to form a frequency map (C), showing regions of constant frequency corresponding to individual cilia. All cilia are then segmented by keeping only the largest regions of constant frequency (of area above 40 pixels) (D). Scale bar is 15 µm.


    1. Open the program NewAnalysisCilia.m with MATLAB.

    2. If the acquisition frequency is different from 100 Hz, correct the value at the beginning of the code (Line 8).

    3. Run the code.

    4. Select a folder where the .tif files with cilia imaging data can be found. If several acquisitions are located in the same folder, all .tif files will be analyzed sequentially, and cilia parameters from all experiments will be concatenated.

    5. All the rest of the analysis is automatic afterwards according to the workflow described above.

    6. The programs outputs one .mat file with 4 matrices. The most interesting matrix is called AllFreq and contains 9 parameters (lines) for all detected cilia (columns). If several files are analyzed, the matrix AllFreq concatenates the parameters of all cilia from all files and saves the number of the file from which the cilia was taken. The 6 first parameters are respectively the beating frequency, the apparent diameter of the region described by the cilia, its angle, eccentricity, area, and major axis. The seventh parameter is an indicator for ventral (1) or dorsal (0) cilia if a central line was drawn (-1 otherwise). The eighth parameter is the number of the file from which the cilia was measured. The last parameter is an indicator of proximity to the central canal (1 if close to the central canal) if a line at the center of the central canal is drawn, in order to exclude cilia outside the central canal. The Freq and Freq_FromPSD matrices display the 5 main frequencies found at each pixel, calculated either from a simple Fourier transform or from the power spectrum density of the last .tif file analyzed. The FrequencyMap matrix gives a 2D map with the main frequency found at each pixel after spatial filtering (Figure 3C).


  4. Quantification of the volume force fv and cilia parameters

    From the beads measurement (Procedure A), the CSF flow can be analyzed qualitatively (e.g., more or less vortices) and quantitatively by measuring the velocity profile (Data analysis A). The diameter of the central canal, as well as the flow rate were obtained from this measurement. The central canal diameter is one output of the fit of the bidirectional flow model and can be recovered because the velocity is zero on the dorsal and ventral boundaries of the central canal. The volume force fv generated by the collective action of cilia could also be quantified using our bidirectional flow model (Data analysis Section B). In this section, we propose to estimate the parameters characterizing cilia and the CSF that control the volume force (see definition below).
        The volume force fv, measures the average force created by the collective action of cilia and divided by the volume of the ciliary region. It can be expressed as:

    fv=αμf/h

    where μ is the viscosity of the CSF, f is the average cilia frequency, h is the width of the region occupied by the beating cilia and α is a dimensionless parameter. For users who measured the average cilia frequency f, the coefficient α can be estimated, as all the other parameters are henceforth known: fv is the force provided by the fitting tool and h can be either extracted from the fitting tool or from the cilia beating analysis. The viscosity of the CSF, μ can be approximated to 10-3 Pa.s, as the viscosity of water, and is supposed constant. The coupling coefficient α provides a mean to compare the collective efficiency of beating cilia in order to generate a flow in either WT or mutant embryos (Thouvenin et al., 2020). Note that we assumed the CSF viscosity to be a constant between wild type and mutant embryos, but this assumption should be verified.
        To provide comparative data, a value of α = 0.5 was obtained for 30 hpf wild type embryos (Thouvenin et al., 2020), with = 5 μm, = 40 Hz and μ = 10-3 Pa.s, which corresponds to a volume force fv = 4000 N/m3.

Notes

  1. From measurement on beads, CSF flow can be analyzed qualitatively to estimate recirculation spots and quantitatively to measure the velocity profile. We can extract from these measurements the diameter of the central canal as beads explore the entire lumen of the central canal as well as the flow rate.

  2. If the overall flow rate is close to 0, the CSF flow profile can be fitted by the bidirectional flow model (Thouvenin et al., 2020) to obtain the volume force generated by the collective action of cilia.

  3. Using Tg(β-actin:Arl13b-GFP) embryos, the average cilia length and beating frequency can be extracted. Thus, if we assume the CSF viscosity to be constant, the coupling coefficient α, measuring the efficiency of the beating cilia to generate a flow, can be compared between mutants and wild type embryos.

  4. In case error messages occur using this interface, please contact us with a precise description of the error, and we will update the code online.

  5. The excel output may fail on some computers, especially if a "click to run" version of office is installed, or if office is not properly registered. If it is the case, please try to uninstall and reinstall office on your computer. Please contact us in case you still experience issues.

  6. All MATLAB scripts and test files are shared on GitHub: https://github.com/wyartlab/BioProtocol_CSFflowMeasurement.

Recipes

  1. aCSF solution

    Prepare a solution containing in mM:

    134 NaCl

    2.9 KCl

    1.2 MgCl2

    10 HEPES

    10 glucose

    2 CaCl2

    Note: Osmolarity has to be 290 mOsM ± 3 mOsm, and pH needs to be adjusted to 7.8 with NaOH.

  2. TexasRed solution

    Prepare a 0.2% solution (w/v) of TexasRed in aCSF

  3. α-bungarotoxin solution

    Prepare 1 μl stock aliquots of α-bungarotoxin at 1 mM

    Stock solutions can be stored at -20 °C and diluted in aCSF to get working concentrations of 100 µM for brain ventricle injections, and 500 µM for muscle injections

  4. Injection Mix 1

    For a 10 μl final volume:

    Mix 5 μl of FluoSpheres (2% v/v concentration in aCSF, sonicated)

    4 μl aCSF

    1 μl α-bungarotoxin (1 mM)

  5. Injection Mix 2

    For a 10 μl final volume:

    Mix 5 μl of FluoSpheres (2% v/v concentration in aCSF, sonicated)

    4 μl TexasRed (0.2% v/v concentration in aCSF)

    1 μl α-bungarotoxin (1 mM)

Acknowledgments

This work was funded by Human Frontier Science Program (HFSP) Research Grant (grant n° RGP063-2018), and the New York Stem Cell Foundation (NYSCF) Robertson Investigator award (grant n° NYSCF-R-NI39) for Claire Wyart and an ICM postdoctoral fellowship kindly attributed to OT and the Big Brain Theory (BBT) program from ICM to support the salary of YCB. The research leading to these results has also received funding from the program ‘Investissements d’avenir’ ANR-10-IAIHU-06 (Big Brain Theory ICM Program), ANR-11-INBS-0011 (NeurATRIS: Translational Research Infrastructure for Biotherapies in Neurosciences).

Competing interests

The authors declare no conflict of interest.

References

  1. Borovina, A., Superina, S., Voskas, D. and Ciruna, B. (2010). Vangl2 directs the posterior tilting and asymmetric localization of motile primary cilia. Nat Cell Biol 12(4): 407-412.

  2. Cantaut-Belarif, Y., Sternberg, J. R., Thouvenin, O., Wyart, C. and Bardet, P. L. (2018). The Reissner Fiber in the Cerebrospinal Fluid Controls Morphogenesis of the Body Axis. Curr Biol 28(15): 2479-2486 e2474.
  3. Olstad, E. W., Ringers, C., Hansen, J. N., Wens, A., Brandt, C., Wachten, D., Yaksi, E. and Jurisch-Yaksi, N. (2019). Ciliary Beating Compartmentalizes Cerebrospinal Fluid Flow in the Brain and Regulates Ventricular Development. Curr Biol 29(2): 229-241 e226.
  4. Schindelin, J., Arganda-Carreras, I., Frise, E., Kaynig, V., Longair, M., Pietzsch, T., Preibisch, S., Rueden, C., Saalfeld, S., Schmid, B., Tinevez, J. Y., White, D. J., Hartenstein, V., Eliceiri, K., Tomancak, P. and Cardona, A. (2012). Fiji: an open-source platform for biological-image analysis. Nat Methods 9(7): 676-682.
  5. Sternberg, J. R., Prendergast, A. E., Brosse, L., Cantaut-Belarif, Y., Thouvenin, O., Orts-Del'Immagine, A., Castillo, L., Djenoune, L., Kurisu, S., McDearmid, J. R., Bardet, P. L., Boccara, C., Okamoto, H., Delmas, P. and Wyart, C. (2018). Pkd2l1 is required for mechanoception in cerebrospinal fluid-contacting neurons and maintenance of spine curvature. Nat Commun 9(1): 3804.
  6. Thouvenin, O., Keiser, L., Cantaut-Belarif, Y., Carbo-Tano, M., Verweij, F., Jurisch-Yaksi, N., Bardet, P. L., van Niel, G., Gallaire, F. and Wyart, C. (2020). Origin and role of the cerebrospinal fluid bidirectional flow in the central canal. Elife 9: e47699.

简介

[摘要]脑脊液(CSF)的循环在发育过程中起着重要的作用。在斑马鱼胚胎中,已发现脑脊液在脊髓中央管中是双向流动的。为了相互比较条件和遗传突变体,我们最近自动化了CSF中外源性荧光颗粒速度分布的定量。我们证明了位于中央管腹侧的运动性和倾斜纤毛的跳动足以产生局部这种双向性。我们的方法可以很容易地扩展以表征各种遗传突变体中的脑脊液流动。我们在此提供详细的协议和用户界面程序,以量化CSF动态。为了解释CSF流量曲线中的潜在变化,我们提供了其他工具来测量中央管直径,表征纤毛动力学并将实验数据与我们的理论模型进行比较,以评估纤毛对在中央管中产生体积力的影响。我们的方法也可用于测量体内的粒子速度并在各种生物溶液中模拟流量。

[背景]在斑马鱼胚胎中,从受精后24小时(hpf)开始在脊髓中央管中观察到脑脊液(CSF)的流动(Sternberg等,2018 ; Cantaut-Belarif等,2018 )和更高版本。延伸到脑室(Olstad等人,2019)。在胚胎中央管中,CSF双向流动:朝向腹侧的尾巴和朝向背侧的头(Sternberg等人,2018; Cantaut-Belarif等人,2018; Thouvenin等人,2020)。这种双向性是由极化活动性纤毛的跳动引起的,该纤毛主要在中央管的腹侧区域中活动,从而驱动腹侧区域中的流体向尾端定向运动,并在背侧区域产生逆流。
由于中央管的几何形状狭窄且布朗运动的贡献很大,因此经典的分析工具无法量化CSF流动的双向特性。最近,我们开发了一种基于运动记录仪分析的自动化方法,该方法可以量化胚胎CSF流量(Thouvenin等,2020)。现在的挑战是推广这种方法,以便比较各种遗传动物模型和实验条件。这是特殊的对纤毛缺陷突变体,其中的调查兴趣蠕动缺陷是局部的,在上流动的后果是没有完全理解。

该协议的目的是指导荧光测量来计算脑脊液流量。我们开发了一个用户友好的界面程序,可从收集的数据生成流量剖面。我们还提供了一个协议,以比较实验测量的胚胎CSF流量与理论值之间的关系。我们的理论模型依赖于这一假设平均流速为空。在这种情况下,可以计算出引起CSF流量的体积力,并在不同条件下进行比较。的体积力依赖于不同的参数纤毛:,其中是平均纤毛拍频,该区域的宽度由所占据的纤毛,粘度,和一个无量纲的PA rameter。我们最终展示了如何使用带有荧光蛋白标记的纤毛的转基因胚胎来量化纤毛的主要频率。

关键字:脑脊髓液, 液体力学, 中央管, 双向性, 流体速度剖面, 纤毛跳动, 斑马鱼, 发育

材料和试剂

2 m l Eppendorf管(Eppendorf,目录号:0030120094)
GLAS屁股培养皿(马蒂克公司,CA talog号:P50G-1.5-14-F)
从自制显微注射针硼硅酸盐玻璃长丝,OD 1mm时,ID 0.5mm时,长10厘米,火抛光(萨特仪器公司,CA talog号:BF100-50-10)
FluoSphere TM大小试剂盒#2,六种尺寸(分子探针,CA talog号:F8888)
注意:此协议针对中心波长505/515 nm(黄色/绿色)的20 nm羧酸盐FluoSpheres进行了优化。


Ñ亩,AB和Tüpfel长鳍(TL)株斑马鱼斑马老化1和6天之间小号受精后(DPF )可以被用于实现CSF流动轮廓定量。当在执行光学成像的胚胎阶段,所述色素沉着观察到在AB和TL线是不影响任一成像用旋转盘在浅的深度也不分析。该比较的CSF流分布的实验措施与理论模型仅保持用于斑马鱼胚胎。我们使用Tg(β-actin:Arl13b-GFP)转基因品系对体内纤毛成像(Borovina et al。,2010 )
3000 MW TexasRed葡聚糖,激发/发射波长:615分之595(赛默飞世科学,CA talog号:D3329)
α银环蛇毒素(TOCRIS,CA talog号:2133)
注:我们注入α银环蛇毒素的解决方案来麻痹鱼,ş EE配方,制成溶液。


三卡因(3-氨基苯甲酸乙酯甲磺酸盐,Sigma-Aldrich公司,CA talog号:A5040)
超纯TM低熔点琼脂糖(Invitrogen公司,CA talog号:16520100)
的NaCl(Sigma公司- Aldrich公司,CA talog号:S7653)
氯化钾(Sigma公司- Aldrich公司,CA talog号:P9333)
HEPES(Sigma公司- Aldrich公司,CA talog号:H3375)
α-d-葡萄糖(西格玛- Aldrich公司,CA talog号:158968)
的CaCl 2二水合物(西格玛- Aldrich公司,CA talog号:H3375)
将NaOH(西格玛- Aldrich公司,CA talog号码:71687)
一个rtificial脑脊液(学联)(见食谱)
α-真菌毒素溶液(请参阅食谱)
TexasRed解决方案(请参阅食谱)
注射混合物1(请参见配方)
注射混合料2(请参见配方)

设备

细钳(Fine Science Tools,目录号:11412-11 )
配备了Hamamatsu Orca Flash 4.0相机(最大每秒100张全帧)的旋转圆盘显微镜(Leica Microsys ,型号:倒置Leica DMI8),使用40倍水浸物镜(NA = 0.8)或任何类似物
移液器拉拔器(Narishige Ltd.,型号:PC-10或PC-100拉拔器,或任何类似产品)
声波发生器(VWR,超声波细胞破碎仪,Vibra-Cell TM V CX 130)
Picospitzer进样器(世界精密仪器公司,美国萨拉索塔)
 
软件

中号ATLab的2018B(MathWorks公司,山景观,CA,US A)和图像处理工具箱
斐济(Schindelin等人,2012年)
Microsoft Excel 2010(用于.xlsx输出格式)

程序

荧光珠的注射和成像
笔记:


为了测量电Ë在脊髓的中央管CSF流动分布,我们注入在脑室的在人工CSF(aCSF中)稀释20个纳米荧光珠的溶液。在注射之前,此溶液的超声处理是避免珠子聚集体(不会进入中央管)的关键步骤。我们成功地用20 nm和45 nm的珠子测量了流量,但是当直径达到100 nm时,即使经过超声处理,珠子也无法进入中央管。颗粒越大,它们越亮,它们所经历的布朗运动就越少,这使得流量定量更加精确,但前提是这些珠子可以到达中央管。可以在尾中央管中注射(Thouvenin等人,2020),但更为复杂,不建议这样做,因为它可能会改变在鼻中央管中的CSF流量。
我们建议用TexasRed一起注入珠,以确保注射是成功的,并确定了边界了的,如果需要中央管。如果是这样,可以在超声处理步骤(进样混合物2)之后将0.2%的TexasRed添加到进样混合物中。
根据我们的经验,在脑室注射更容易(尤其是在幼虫阶段),如果鱼背-装。可以对背侧安装的动物进行注射,然后翻转琼脂块或卸下鱼,以再次将其横向安装在新盘中。由于安装/卸载可以增加伤害幼虫的风险,翻转琼脂切的块有精美手术刀(精细的科学工具,目录号:10073-14)建议。
为了避免运动伪影,必须对瘫痪的动物进行磁珠轨迹成像。我们只是直接添加α金环蛇毒素的注射混合,以注入动物只有一次,红眼Ë实验时间。
视频1说明了从胚胎去绒毛和安装开始的实验程序,并显示了心室注射。

混合注射液和移液器的准备
将荧光珠(FluoSpheres)稀释至aCSF中2%的浓度n(v / v),最终体积至少为100 µl 。我们也建议使用大的2 ml微型管,以避免在超声处理过程中溶液分散。将混合物放在冰上。
通过在50 W的输出功率下发出3个3-4 s的脉冲来对小球进行超声处理。确保包含稀释小球的混合物留在冰上(超声是放热的)。
用两步式拔针器从硼硅酸盐玻璃毛细管中拉出显微注射针。调节温度和拉力,以生产出长而尖的漏斗形针,其尖端直径约为1-3 µm(相当于鸡蛋注射液移液器)。
准备注射混合物1或混合物2(请参见配方)。
用4μl注射混合液填充移液器。
移液管连接到Picosp ř itzer设备(帕克,霍利斯,NH,USA) 。
用钳子将移液器的末端切开,以获得1-3纳升的注射量。液滴的体积可以在实验前进行校准。
(可选)为了校准液滴的体积在固定喷射压力,填注移液管具有限定和固定aCSF中(体积例如,0.2μ升),以及移液管连接到picospitzer设备。准备一个装有矿物油的培养皿,然后向矿物油中滴注直至吸液管中的液体倒空。计算喷射出的液滴的数量,并使用它来计算每个液滴的平均体积。液滴的体积可以通过改变喷射压力或移液器吸头的直径来调节。
胚胎安装和注射液N(小号EE视频1)
用细镊子手动去除26-28hpf胚胎。其他去绒毛技术(例如酶消化)也应同样有效。
在0.02%w / v Tricaine溶液中(或在与冰接触的皿中)麻醉胚胎,以在安装步骤中停止自发抽搐,并在安装完成后冲洗。
将胚胎横向装入1.5%w / v低熔点琼脂糖中。确保彻底调整动物的后轴方向,以使中央管腔足够平坦且较长的部分成像。添加至少1m升系统水的当琼脂糖已经凝固,使得胚胎可以呼吸和稀释剩余的三卡因溶液。
将先前准备的溶液混合物注入后脑(或“菱形”脑室)中(图1 )。如果0.2%TexasRed瓦特ERE添加(注入混合物2),注射质量可以通过观察脑室充满着色溶液来控制。如果不是(注射混合物1),注射质量可以通过观察轻微的和心室的瞬态肿胀(评估小号EE视频1)。
将注射的胚胎在28°C下放置1 h,以使荧光珠向下扩散到中央管。确保系统水覆盖培养皿的整个表面,以补偿蒸发。



视频1.在斑马鱼胚胎中安装和注入荧光珠的实验程序



中央管中荧光珠的光学成像
注意事项:


可以使用安装在恒温箱中的旋转盘共聚焦显微镜在26 °C下获取延时图像。这样可以更好地控制可能影响CSF流动特性和/或纤毛跳动特性的温度变化。
我们建议将胚胎的朝向始终保持相同的方向,左侧的鼻侧和顶部的背侧。如果没有,则可以通过图像处理恢复正确的方向。注意,在野生型胚胎中,中央管的腹壁通常比背壁平坦。
只要信噪比(SNR)足够高,并且成像速度高于几帧/秒,就可以使用任何成像系统执行成像。可以选择竖立或倒置的旋转盘。旋转盘成像似乎是最合适的,但宽视野显微镜也适用于明亮的荧光珠。也可以使用共焦或两光子显微镜,尽管成像速度可能会受到经典共焦设置的限制,并且在两光子显微镜中,产生的盐和胡椒粉噪声可能会出现问题。
如果将TexasRed与505/515 nm发射珠一起注入,请确保显微镜的发射滤镜可进行双色成像(避免使用会导致渗漏的长通滤镜)。
由于成像大多是在胚胎和幼虫阶段使用可见激光激发在矢状面进行的,因此色素沉着不是问题,因此不需要使用PTU 。

由于中央管的形状和纤毛特性沿尾尾轴可能会有所不同,因此我们建议始终在相同的尾tro尾位置进行影像学检查。在我们的案例中,我们专注于卵黄延伸上方的3个片段(图1)。由于旋转圆盘显微镜执行清晰的光学切片,因此我们建议使用微分干涉对比(DIC)或透射光通道将体腔和中央管成像在一起。如果TexasRed注入,红色落射荧光信道可以被叠加到可视化使用中央管epifluorescen Ç Ë切换到旋转盘模式(图1)之前。
以10帧/秒的速度执行延时2D采集,持续30 s。小心地安装鱼,使中央运河在长距离内保持水平。通过选择Z平面,其中中央管的表观直径在矢状平面中最大,成像发生在中央管的中心,到中线。这样,在物镜为40 × NA = 0.8的情况下,中央管大部分适合光学部分。
在CSF中流动的FluoSpheres具有光稳定性:可以使用高激光功率,同时进行最少的光漂白,以获得高信噪比。
使用程序GeneProfile从获取的数据生成CSF流配置文件。请参阅数据一个了解更多详情nalysis部分。
使用相同的程序GeneProfile将CSF流量剖面拟合到野生型胚胎中预期的理论双向流量。请参阅数据一个了解更多详情nalysis部分。



图1 。脑室注射部位和注射质量评估。左图:受精(hpf )胚胎后30 h后脑心室中荧光珠的注射位点。注射到后脑室后一个小时,有20 nm的小珠沿中央管扩散。右图:TexasRed(上)和20 nm珠(下)成像,在卵黄延伸上方的脊髓中央管中有旋转盘。比例尺:10 µm。



定量的运动学的运动纤毛
胚胎安装和瘫痪
筛选了GFP的去皮的26-28 hpf Tg(β-actin:Arl13b-GFP)胚胎(Borovina等人,2010 )。
将胚胎放入0.02%w / v Tricaine溶液中(或置于与冰接触的培养皿中),以在安装步骤中停止自发抽搐。
在玻璃底培养皿中,将胚胎横向置于1.5%w / v低熔点琼脂糖中。琼脂糖凝固后,加入适量的水。确保将三卡因稀释。
使胚胎麻痹。与步骤A1类似,准备注射移液器。在移液器中加入500 µMα-真菌毒素溶液。对尾部最末端的肌肉进行单次1 n l注射,并检查其是否引起完全瘫痪。如果中央管需要适当可视化,TexasRed可以一起用α-银环蛇毒素注射在肌肉,通过稀释α银环蛇毒素股票等分试样时(与TexasRed溶液替换aCSF中小号EE食谱)。TexasRed能够在早期发育阶段穿过血脑屏障并穿透中央管内部。
纤毛动力学的光学成像
确保将房间温度控制在t 26°C ±2°C以避免整个实验中纤毛跳动频率的变化。
使用旋转盘显微镜,米onitor纤毛经由TI的运动性我推移收购2D使用用于Arl13-GFP的激发的蓝色激光。甲Ç叠纸TexasRed的单个图像在大脑脑室注射使用绿色激光为激发可靠地测量中央管的直径。为了捕获最高的跳动频率,应选择100-200 Hz的采集速率。如果系统依靠CMOS相机,则可以通过沿相机的线放置中央通道并将图像中心线成像的线数减少到最少来提高帧速率。曝光时间应足以可视化GFP阳性纤毛。
使用程序纤毛分析来提取纤毛的跳动频率,长度和角度。请参阅数据一个了解更多详情nalysis部分。
 
数据一nalysis

在实验程序之上,我们在下面详细介绍了两个独立的分析工作流程。


通过第一部分分析(A部分),可以从零件过程A中获取的磁珠轨迹的时间序列中获得CSF流量分布。这也允许测量总的CSF流速(B节),预计在WT胚胎中该流速将为零(Thouvenin等,2020)。如果足够(请参阅下面的条件),可以将实验测量的脑脊液流量拟合到双向流量模型(Thouvenin等人,2020),以提取运动性纤毛产生的体积力。


第二个分析工作流程(C节)使用纤毛拍打电影(过程B)提取纤毛参数,包括每个纤毛的主要拍打频率,长度和角度。


如果合适,最后一部分(D部分)旨在合并两个分析工作流程的输出,并提取一个称为α的参数,该参数是一个临时耦合参数,用于测量多个纤毛如何有效地协同工作以生成流。



A. CSF流量剖面生成      
专门针对此协议,我们开发了一个用户界面平台,以允许用户尽可能轻松地生成CSF流配置文件。在这里,我们介绍了分析工作流程(图2)以及如何从荧光珠测量结果生成第一个CSF流量曲线。的参数更微妙的微调是在用户界面内提供,以适应可变的成像条件,并在被充分地描述文档手册GeneProfile。可以在软件中找到的pdf文件。


作为输入,分析需要2D时间流逝的珠子在中央管中流动(图2A1)。为了生成运动记录器,我们将f或给定的腹背位置交换为轴,以使X轴对应于后尾骨位置,而Y轴对应于time 。然后,小珠的轨迹显示为线,其斜率反映了粒子沿前尾尾轴的方向和速度。为了建立流量剖面,程序会过滤每个运动记录仪,并对每个运动记录仪中的所有行进行自动分段(图2B2)。然后,它提取每条线的斜率,并将其转换为粒子速度,以建立每个背腹位置的速度直方图(图2B3)。通过计算每个位置的平均速度,我们生成CSF流量分布图(图2C1)。






图2. CSF流量概况分析工作流程的原理。使用在中央管中流动的荧光珠的二维时间流逝(A1)和我们的自定义用户界面软件(A2)计算CSF流量曲线。“开始运动记录仪”按钮通过交换尺寸(B1),首先根据2D时间流逝计算运动记录仪,从而开始分析。过滤每个运动图,并分割对应于一个粒子轨迹的所有线(B2)。然后将每条线的角度转换为粒子速度值,并汇总为每个DV位置的速度直方图(B3)。然后,通过提取每个直方图(C1)的平均值和标准误差来计算流量曲线。最终可以将流量曲线拟合到我们的双向流量模型中,以提取定量流量参数(C2)。水平刻度尺为15 µm,垂直刻度尺为5 s。



启动程序
ř未Main_GeneProfile.m(需要M ATLab的2018B或更高版本)。
或者,下载并安装独立应用程序。安装完成后,转到命令窗口并导航到已安装的文件夹。运行:application \ GeneProfile。
将打开图2 A2中的用户界面窗口。
选择.tif文件进行分析。一次可以选择多个文件,它们将被一个接一个地处理。
输入与实验参数相对应的帧时间(以秒为单位)和像素大小(以微米为单位)。
为了使分析有效,中央通道应尽可能水平和平坦。选择运河中最长的水平部分,两侧中央运河外要有几个像素(图2A1 )。感兴趣的区域的旋转和裁剪可以通过Fiji或任何等效软件手动进行,也可以通过提供的用户界面通过单击RotationAndCrop按钮来完成。在这种情况下,按下StartKymograph按钮时,将出现一个旨在选择关注区域的新界面。
运行“启动Kymograph”以计算每个背腹位置的Kymograph和磁珠速度的直方图。然后,它测量每个直方图的平均值以计算流量分布。如果使用多个输入.tif文件,则会依次显示每个配置文件。数据以名为CSFProfile的矩阵形式保存在Matlab工作区中,并且也保存在所需的输出中。
可能的输出是.mat,.xlsx或两者,并在用户界面中设置。对于.xlsx输出,必须在计算机上安装E xcel 。.mat生成一个结构,其中包含每个文件的背腹位置,每个位置处的流量,标准误差以及流量曲线的极值处的速度直方图。在.xlsx输出中,每个文件中的数据都保存在不同的工作表中,并且背腹位置,每个位置的流量和标准错误都被保存。
该程序通过关闭界面窗口结束。

B.用模型拟合速度剖面      
在图文宁等人。(2020),我们开发了一个简单的模型来说明斑马鱼胚胎中CSF流动的双向性。在该协议中,用户可以使用我们的脚本将他们的CSF流实验数据自动调整为我们开发的理论模型(图2C2)。这允许小号用户检查1)他们的实验条件是否导致比我们在中央管中观察到的一个类似的CSF流野生型(WT )斑马鱼的胚胎,并且如果是这种情况2),以提取从量化参数合身。该程序允许提取4个流体力学参数:1)运动性纤毛产生的体积力; 2)在运河中建立的,抵抗纤毛跳动的压力梯度; 3)携带运动性纤毛的区域的宽度;以及4)中央管的直径。为了使配合有意义,我们的双向流动模型的两个假设应该尊重:对于中央管和“无净通量”条件圆柱形的几何形状(Thouvenin等人。,2020)。提醒一下,在这两个假设下,我们表明平均速度分布可以由分段二阶多项式公平地描述,定义为:












其中,,,和被表示为问题的参数的函数: 


















这是通道的直径和CSF的粘度,是压力梯度,是纤毛产生的每单位体积的平均力。后两个参数可以从用GeneProfile接口处理的CSF速度曲线中进行实验测量。 


  我们的理论模型描述了一个对称的双向流,其净总流率为零。在用户界面中,是前启动安装工具,我们提供的用户流的双向性,称为的估计被定义为:








变化对于纯单向流和%0%100对于纯双向流动(流量平流输送尾部等于流量平流输送嘴侧)。


  建议用户不执行的速度分布拟合˚F或值的<70% ,因为下该任意的阈值,“无通量”条件不再有效,因此,配合的参数是无意义的。


一旦FLO瓦特轮廓被计算(数据分析A部分),右侧(以下简称“拟合模型”按钮图2A2 )变为绿色。可以通过按下该按钮来进行拟合。
可能出现两种可能性:
如果f <70%,我们估计流量的双向流动不足以使速度适合我们的模型,并显示警告消息“我们建议用户不要走得更远”。如果不遵守我们模型的两个假设,我们建议单击“在此处停止”按钮以停止拟合过程。如果测得的气流文件被鲁棒地测定,具有低的β装置,所述流动不能简单地通过运动纤毛的在一个封闭的圆柱形几何形状的动作和另一模型应该通过考虑其他物理效应来开发说明。
我˚F > 70%时,流程可以合理地装配有简单的模型,以及验证消息被发送给用户。点击“是”。
然后,通过理论模型拟合实验速度曲线(在用户界面右下角的蓝色,图2A2中),(在曲线上的红色)。该图还以.fig和.png格式保存(图2C2 )。Ť他.FIG文件允许用户修改的情节,并做审美的变化,以及在矢量格式保存(.EPS,.PDF,.SVG)。
可以从拟合中提取一些信息,详细信息如下。数据存储在.xls文件和/或.mat文件(称为“ TheoreticalProfiles”)中,其中:
速度存储在10000 x 1的矢量中,称为“轮廓”(以μm/ s为单位),而弓形尾状位存储在10000 x 1的矢量中,以“ X”表示(以μm为单位)。
由纤毛产生的体积力存储在称为“ f_v”的变量中(Nm -3 )。 
由于中央管的封闭几何形状,与纤毛跳动相对的压力梯度存储在变量“ GradP”中(以Nm -3表示)。
在模型中产生体积力的睫状区的宽度存储在变量“ l_cilia”(以μm为单位)中。 
中心管的测量直径存储在变量“直径”(以μm为单位)中。请注意,如果需要,我们建议使用TexasRed直接测量来测量中心管直径,因为从运动记录仪推断直径可能是不准确的。

C。       纤毛频率测量
本节旨在描述分析规程,以根据程序B部分中所述的荧光纤毛时间流逝获取来估算纤毛的主要跳动频率(s EE Thouvenin等,2020)。


与“数据分析A”部分相似,我们在这里描述分析工作流程的原理(图3)以及执行首次分析的关键说明。的详细说明,以及微调参数的描述是在可用外部文档ManualCilia.pdf可与共享代码中找到。


该程序首先将纤毛动力学与时间的关系加载到成像数据中(图3A),然后应用局部平均滤波器(默认大小为4)来提高纤毛SNR。对于滤波后的数据中的每个像素,时间序列将被提取并进行傅立叶变换(图3B)。提取了傅里叶光谱的5个最大峰,但是默认情况下,仅使用第一个峰。其他峰的频率可用于验证(例如,如果发生采样错误,则第一和第二峰的频率之和等于采集频率)。这样就创建了一个在每个像素处都具有主频率的2D图像(图3C)。在嘈杂的地区,其输出随机频率,但在纤毛地区它绘制的给定频率,我们认为是单一的利益区慈利嗯。每个包含多于40个像素(7.5微米兴趣这些区域中的2 )是最后分段和分析。提取参数频率,直径,偏心距,面积,角度和主轴长度,并将其与相应的纤毛参数关联。


如果之间的比较背侧和腹侧纤毛是感兴趣(Thouvenin等人,2020),该程序允许在中央管和分类纤毛作为背的中心手动绘制一条线或腹侧与对于到它们的相对位置从所述中心线。此过程此处不再赘述,但可以在与共享Matlab代码位于同一文件夹中的文档“ ManualCilia.pdf ”中找到。





图3.跳动纤毛分析的原理。通过测量每个像素(B)的时间傅立叶变换来分析纤毛跳动(A)的2D时间流逝。绘制了与在(A)中绘制的三个区域的中心处的像素相对应的3个光谱。为所有频谱提取最大振幅峰值的频率(箭头(B)),以形成频率图(C),显示与单个纤毛相对应的恒定频率区域。然后,通过仅保持恒定频率(大于40像素的区域)的最大区域来对所有纤毛进行分割(D)。比例尺为15 µm。



用MATLAB打开程序NewAnalysisCilia.m。
如果采集频率与100 Hz不同,请在代码的开头(第8行)更正该值。
运行代码。
选择一个文件夹,可以在其中找到具有纤毛成像数据的.tif文件。如果同一文件夹中有多个采集,则将依次分析所有.tif文件,并将所有实验的纤毛参数连接起来。
之后,其余所有分析将根据上述工作流程自动进行。
程序输出一个带有4个矩阵的.mat文件。最有趣的矩阵称为AllFreq ,其中包含所有检测到的纤毛(列)的9个参数(行)。如果分析了多个文件,则矩阵AllFreq会连接所有文件中所有纤毛的参数,并保存从中获取纤毛的文件编号。6个第一参数分别是拍打频率,由纤毛描述的区域的表观直径,其角度,偏心距,面积和主轴线。第七个参数是如果绘制了中心线(否则为-1)的腹侧(1)或背侧(0)纤毛的指示器。第八个参数是测量纤毛的文件编号。最后一个参数是如果在中心管中心绘制一条线以排除中心管外的纤毛,则指示接近中心管(如果接近中心管,则为1)。Freq和Freq_FromPSD矩阵显示在每个像素处找到的5个主要频率,这些频率是通过简单的傅立叶变换或最后分析的.tif文件的功率谱密度计算得出的。所述FrequencyMap矩阵给出2D地图与主频率发现在空间滤波(后每个像素˚F igure 3C)。

D.体积力和纤毛参数的量化        
通过磁珠测量(过程A),可以通过测量速度分布(数据分析A)对CSF流量进行定性(例如,或多或少的涡旋)和定量分析。中央管的直径以及流速是通过该测量获得的。该中央管直径是双向流动模型的拟合的一个输出,并且可以恢复,因为速度是零上中央管的背部和腹部的边界。的体积力由纤毛的集体行动生成也可以使用我们的双向流动模型(数据的量化alysis小号挠度B)。在本节中,我们建议估计表征纤毛和控制体积力的CSF的参数(请参见下面的定义)。   

  该体积力,测量通过纤毛的集体行动创造和睫状区的体积除以平均力。它可以表示为:





其中CSF的粘度,平均纤毛频率,拍打的纤毛所占据区域的宽度以及无量纲参数。对于用户谁MEAS ured平均纤毛频率,系数可以被估计,因为所有的其它参数今后已知的:是由配合工具提供力并且可以从装配工具或从纤毛打浆分析来要么萃取。作为水的粘度,CSF的粘度可以近似为10 -3 Pa.s,并且被认为是恒定的。耦合系数α提供了一个平均值,可以比较跳动的纤毛的集体效率,以便在野生型或突变型胚胎中产生血流(Thouvenin等人,2020)。请注意,我们假设CSF粘度在野生型和突变型胚胎之间是恒定的,但这一假设应得到验证。

  为了提供比较数据,获得了30 hpf野生型胚胎的值(Thouvenin et al。,2020),μm,Hz和  μ=10 -3 Pa.s,其对应于体积力N / m 3 。 


笔记



通过对珠粒的测量,可以定性分析CSF流量以估计回流点,并定量测量速度曲线。我们可以从这些测量值中提取中央管的直径,因为珠子可以探索中央管的整个管腔以及流速。
如果总流速接近于0,则可以通过双向流动模型(Thouvenin等人,2020)拟合CSF流量曲线,以获得纤毛的集体作用所产生的体积力。
使用Tg(β-肌动蛋白:Arl13b-GFP)胚胎,可以提取平均纤毛长度和跳动频率。因此,如果我们假设CSF粘度是常数,耦合系数α,测量跳动纤毛生成流的效率,可以突变体和野生型胚胎之间进行比较。
如果使用此界面出现错误消息,请与我们联系并提供错误的准确描述,我们将在线更新代码。
Excel输出在某些计算机上可能会失败,尤其是在安装了“单击运行”版本的Office或未正确注册Office的情况下。在这种情况下,请尝试在计算机上卸载并重新安装Office。如果您仍然遇到问题,请与我们联系。
所有MATLAB脚本和测试文件都在GitHub上共享:https : //github.com/wyartlab/BioProtocol_CSFflowMeasurement。

菜谱

aCSF解决方案
准备包含mM的溶液:


氯化钠134


2.9氯化钾


1.2氯化镁2


10个HEPES


10葡萄糖


2氯化钙2


注意:渗透压必须为290 mOsM± 3 mOsm,并且需要将NaOH的pH值调节至7.8。


TexasRed解决方案
在aCSF中准备0.2%(w / v)的TexasRed溶液


α-真菌毒素溶液
准备1μl的等分于1 mM的α-菌丝毒素


储备液可以储存在-20 °C并在aCSF中稀释,以使脑室注射的工作浓度为100 µM,肌肉注射的工作浓度为500 µM


注射混合料1
对于10μl的最终体积:


混合5μ升FluoSpheres的(ACSF中2%V / V浓度,超声处理)


4微升aCSF


1微升α-真菌毒素(1毫米)


注射混合物2
对于10μl的最终体积:


混合5μ升FluoSpheres的(ACSF中2%V / V浓度,超声处理)


4μ升TexasRed(ACSF中0.2%体积/体积浓度)


1微升α-真菌毒素(1毫米)



致谢



这项工作是由人类前沿科学计划(HFSP)研究补助金(授权号RGP063-2018)和纽约干细胞基金会(NYSCF)的罗伯逊研究人员奖(授权号NYSCF-R-NI39)资助的,克莱尔·怀亚特(Claire Wyart)和ICM博士后研究金,这应归功于OT和ICM的“大脑理论”计划,以支持YCB的薪水。导致这些结果的研究也获得了来自“投资研究”计划ANR-10-IAIHU-06(大脑理论ICM计划),ANR-11-INBS-0011(NeurATRIS:生物医学转化研究基础设施)的资助。神经科学)。



利益争夺



作者宣称没有利益冲突。



参考



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Cantaut-Belarif,Y.,Sternberg,JR,Thouvenin,O.,Wyart,C.和Bardet,PL(2018)。脑脊液中的赖斯纳纤维控制体轴的形态发生。Curr Biol 28(15):2479-2486 e2474。
华盛顿州奥尔斯塔德(Olstad,EW),林格斯(Ringers),汉森(J.Hansen),温斯(A.Wens),布兰特(Brandt),沃克滕(D.),雅克西(Eaksi)和北卡罗来纳州尤里斯·雅克西(Jurisch-Yaksi)(2019)。睫状跳动使大脑中的脑脊液流动并调节心室发育。Curr Biol 29(2):229-241 e226。
Schindelin,J.,Arganda-Carreras,I.,Frise,E.,Kaynig,V.,Longair,M.,Pietzsch,T.,Preibisch,S.,Rueden,C.,Saalfeld,S.,Schmid,B ,Tinevez,JY,White,DJ,Hartenstein,V.,Eliceiri,K.,Tomancak,P.和Cardona,A.(2012)。斐济:一个用于生物图像分析的开源平台。Nat Methods 9(7):676-682。
Sternberg,JR,Prendergast,AE,Brosse,L.,Cantaut-Belarif,Y.,Thouvenin,O.,Orts-Del'Immagine,A.,Castillo,L.,Djenoune,L.,Kurisu,S.,McDearmid ,JR,Bardet,PL,Boccara,C.,Okamoto,H.,Delmas,P。和Wyart,C。(2018年)。Pkd2l1是脑脊髓液接触神经元的机械感受和维持脊柱弯曲所必需的。Nat Commun 9(1):3804。
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引用: Readers should cite both the Bio-protocol article and the original research article where this protocol was used:
  1. Thouvenin, O., Cantaut-Belarif, Y., Keiser, L., Gallaire, F. and Wyart, C. (2021). Automated Analysis of Cerebrospinal Fluid Flow and Motile Cilia Properties in The Central Canal of Zebrafish Embryos. Bio-protocol 11(5): e3932. DOI: 10.21769/BioProtoc.3932.
  2. Thouvenin, O., Keiser, L., Cantaut-Belarif, Y., Carbo-Tano, M., Verweij, F., Jurisch-Yaksi, N., Bardet, P. L., van Niel, G., Gallaire, F. and Wyart, C. (2020). Origin and role of the cerebrospinal fluid bidirectional flow in the central canal. Elife 9: e47699.
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