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Mar 2020

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Determination of Microtubule Lattice Parameters from Cryo-electron Microscope Images Using TubuleJ
使用TubuleJ从冷冻电子显微镜图像确定微管晶格参数   

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Abstract

The α-β tubulin heterodimer undergoes subtle conformational changes during microtubule assembly. These can be modulated by external factors, whose effects on microtubule structure can be characterized on 2D views obtained by cryo-electron microscopy. Analysis of microtubule images is facilitated if they are straight enough to interpret and filter their image Fourier transform, which provide useful information concerning the arrangement of tubulin molecules inside the microtubule lattice. Here, we describe the use of the TubuleJ software to straighten microtubules and determine their lattice parameters. Basic 3D reconstructions can be performed to evaluate the relevance of these parameters. This approach can be used to analyze the effects of nucleotide analogues, drugs or MAPs on microtubule structure, or to select microtubule images prior to high-resolution 3D reconstructions.

Keywords: Tubulin (微管蛋白), Microtubules (微管), Microtubule lattice parameters (微管晶格参数), Microtubule polarity (微管极性), Cryo-electron microscopy (冷冻电子显微镜), Image analysis (图像分析), Helical assemblies (螺旋组装体), Three-dimensional reconstructions (三维重构)

Background

Microtubules are polymers of the α-β tubulin heterodimer that form tubes of about 25 nm in diameter and several µm in length. Tubulin binds two molecules of guanosine triphosphate (GTP), one of which is hydrolyzed to GDP during assembly. GTP-hydrolysis is key to microtubule dynamics, since it destabilizes their lattice and allows their fast rearrangements and turn-over during cell activity. Works with GTP analogues such as guanylyl-(α, β)-methylene-diphosphonate (GMPCPP) or guanosine 5'-(γ-thio)-triphosphate (GTPγS) gave rise to a model in which GTP-tubulin undergoes a compaction and rotation between its subunits during assembly and GTP-hydrolysis (Zhang et al., 2015). This model was recently challenged by a study that involved a range of nucleotide analogues and structural approaches, including X-ray crystallography, small angle X-ray diffraction and cryo-electron microscopy (Estévez-Gallego et al., 2020 ). This study led to the proposal that if tubulin sustains an expansion-compaction conformational change, this would occur after GTP-hydrolysis to facilitate inorganic phosphate release.

Other factors have been shown to modulate the tubulin compaction state or the protofilament skew angle of microtubules (Manka and Moores, 2018). End-binding proteins (EBs) that bind in-between protofilaments have been proposed to accelerate GTP-hydrolysis by compacting tubulin and to induce a left-handed lattice twist (Zhang et al., 2018 ). Taxol has been reported to give rise to an expanded state similar to that found in GMPCPP microtubules (Vale et al., 1994; Estevez-Gallego et al., 2020 ), suggesting that this state reflects a stable conformation of tubulin in microtubules.

While high-resolution analysis of microtubules is prone to describe these conformational changes at the near-atomic level, it requires a careful selection of homogeneous types of microtubules. When reassembled in vitro from pure tubulin, microtubules form a range of structures that differ in terms of protofilament and/or lateral helical start numbers (Chrétien and Fuller, 2000). To accommodate these variations, the protofilaments skew relative to the microtubule longitudinal axis (Langford, 1980). This produces moiré patterns in 2D projection views obtained by cryo-electron microscopy, which provide a direct measure of their protofilament skew angle (Chrétien and Wade, 1991). Moreover, this moiré pattern has an arrowhead shape that reflects microtubule polarity, providing that the protofilament handedness has been unambiguously determined ( Chrétien et al., 1996 ; Sosa and Chrétien, 1998). The compaction state of tubulin can be accurately measured on diffraction patterns of the microtubule images (Vale et al., 1994; Hyman et al., 1995), and the helical rise of the tubulin subunits, which reflects how they interact laterally, can be deduced when all other parameters are known (Chrétien and Fuller, 2000; Estévez-Gallego et al., 2020).

To facilitate analysis of microtubule images obtained by cryo-electron microscopy, we have developed TubuleJ as a plugin to the multi-platform ImageJ software ( Schneider et al., 2012). The basic principles of TubuleJ were originally described in (Blestel et al., 2009 ). The current version has been updated with new routines, and incorporates TomoJ ( Messaoudi et al., 2007) to perform fast 3D reconstructions of microtubules. The workflow of TubuleJ is presented in Figure 1.


Figure 1. TubuleJ workflow. A. TubuleJ menu. B. TubuleJ processing routines. Only the steps in black are described in this protocol. The steps ‘Untwist fiber from file’ and ‘Create stack from curved fiber’ are not described in this protocol. TubuleJ is divided in three “modules”. Module 1 (left) can be used with any type of fiber, while modules 2 (middle) and 3 (right) are specific to microtubules. Module 2 allows determination of microtubule lattice parameters, while module 3 allows basic 3D reconstructions, without differentiating the α-β tubulin monomers.

Equipment

  1. Mac-Pro (mi-2010), 2 x 3.46 GHz, 2 x 6-Core Intel Xeon, 96 Go 1333 MHz DDR3 RAM, SSD 1 To, 3 x 6 To Sata disks, 2 x NVIDIA Quadro K5000 graphic cards, macOS version 10.13.6 (Apple Inc.)

    Notes:

    1. With the current configuration, determination of microtubule lattice parameters and calculation of a 3D reconstruction can be performed in less than 10 min.

    2. Since ImageJ is multi-platform, the TubuleJ plugin can be installed and run on any computer equipped with compatible operating systems (MacOs, Linux, Windows). TubuleJ takes advantage of parallel processing (fast Fourier transforms with parallel FFTJ, 3D reconstructions with TomoJ). Therefore, mutli-core processors will speed up the calculations. Allocate a sufficient amount of RAM to ImageJ depending on your configuration and make sure it uses parallel processing (‘Edit -> Options -> Memory & Threads…’).

Software

  1. ImageJ software: https://imagej.nih.gov/ij/

  2. TubuleJ plugin to ImageJ: https://igdr.univ-rennes1.fr/TubuleJ/

  3. FFTJ (implemented in TubuleJ):https://sites.google.com/site/piotrwendykier/software/parallelfftj

    Parallel FFTJ is a multithreaded Fast Fourier Transform plugin for ImageJ.

  4. TomoJ (implemented in TubuleJ): https://sourceforge.net/projects/tomoj/

    TomoJ allows the preprocessing and registration of tilt series before performing 3D reconstructions.

  5. UCSF Chimera: https://www.cgl.ucsf.edu/chimera/

Procedure

  1. TubuleJ install

    1. Download TubuleJ and the test image from https://igdr.univ-rennes1.fr/TubuleJ/.

    2. Unzip TubuleJ.zip and install the TubuleJ folder inside the plugin folder of ImageJ.


  2. Microtubule selection

    1. Open the electron microscope image in ImageJ.

    2. Select ‘Plugins -> TubuleJ -> TubuleJ’. The interface of TubuleJ opens (Figure 1A).

    3. Click on ‘Select fiber’ and create a folder named ‘MTa’. Select this folder as your working directory.

      Note: Several microtubules are frequently present in a single image, which requires creating a separate folder for each microtubule that will be analyzed.

    4. Fix the pixel size to 2.16 Å (Figure 2A) and press ‘OK’.

      Note: The pixel size is automatically recovered from the header if present. If absent or inaccurate, it must be set at this stage. In the present case, the image header proposes 2.21 Å, but the actual magnification was calibrated using Tobacco Mosaic Virus, which gave a pixel size of 2.16 Å. If one aims to analyze the compaction state of tubulin (Hyman et al., 1995), it is important to calibrate precisely the images at the working magnifications, since changes in subunit monomer repeats are on the order of a few Å.

    5. Draw a line on the fiber of interest (Figure 2B) and press ‘OK’. This defines the rotation angle of the image.

    6. Draw a box around the fiber of interest (Figure 2C) and press ‘OK’. An image named ‘image_orig.tif’ is presented (Figure 2D). Select the whole image (Edit->Select All) and resize the image to, e.g., 189 in height, to minimize background (Image->Crop; Figure 2E). Save this image in the working directory.

      Notes:

      1. The procedure from microtubule selection (B) to 3D reconstruction (I) is provided in Video 1.

      2. As the plugins starts with the current image opened in ImageJ, any file format that can be opened in ImageJ can be used with TubuleJ. It includes classical formats such as tiff. With the install of TomoJ, formats dedicated to electron microscopy such as dm3, mrc, spider or mrc.bz2 are also accepted.



    Figure 2. Microtubule selection. A. Pixel size setting. B. Rotation of the microtubule image. C. Microtubule image boxing. D. Extracted region. E. Extracted region cropped to minimize background.



    Video 1.Microtubule image analysis and 3D reconstruction


  3. Microtubule straightening

    1. Select ‘image_orig.tif’ and click on ‘Untwist fiber’. Set the following parameters (Figure 3A): ‘Enter the width of the sub-images (pixels): 384’; ‘Enter the step size (pixels): 192’; ‘Enter the height of the straight fiber image (pixels): 185”. Let checked ‘Correct contrast’; ‘radius: 60’, let unchecked ‘Display middle step images’ and press ‘OK’. Orientations of the microtubule sub-regions with respect to the horizontal are indicated in the log window. The extracted image corrected for contrast variations is presented (Figure 3B), together with the first sub-region from the left roughly aligned horizontally (Figure 3C), and a line profile of the equator of the microtubule sub-region Fourier transform (Figure 3D).

      Notes:

      1. The width of the sub-regions will depend on the pixel size and the signal/noise ratio present in the images. We commonly use sub-image lengths comprised between 50 and 100 nm at the specimen level. The step size can be set to half the width size, and the height of the straight fiber about 65% larger than the width of a microtubule image (in pixels). Use an odd value for the width size to allow a proper centering of the microtubule image.Note: Grey gradients are essentially due to variations in ice thickness, e.g., from the border to the center of the carbon holes. These must be corrected for proper filtering of the microtubule images. The ‘radius’ option corresponds to the value of the Gaussian filter in ImageJ, which is used to produce a background image that is subtracted from the original image.

      2. The option ‘Display middle step images’ presents all the extracts (image named ‘Horizontal and centered windows’), as well as an image showing the local centers (white crosses) connected with a dark line. Analysis of these images can be useful to determine why the algorithm failed during the local determination of microtubule centers.

    2. Click at the level of the second large peak starting from the left (around 10 in frequency, Figure 3D). The progress of local center calculation can be followed in the log window. A straightened image corrected for contrast variations named ‘image_orig-straight’ is presented (Figure 3E).

      Notes:

      1. TubuleJ uses the phase of the J0 Bessel function to center the microtubule image (Blestel et al., 2009), which correspond to the 3 to 4 first large peaks in Figure 3D. The higher resolution peaks may overlap with JN (N = number of protofilaments, here N = 15). Selection of the second large peak at ~10 in frequency limits the contribution of the JN term that could corrupt the centering process.

      2. The straightened image is shorter than the original image, since point centers are taken from the middle of the first sub-region to that of the last sub-region. A procedure to straighten the entire image is provided in the TubuleJ manual. This procedure uses the ‘Untwist fiber from file’ routine not described in this protocol. This routine can also be used to adjust mis-centered points.



    Figure 3. Microtubule straightening. A. Straightening parameters. B. Contrast corrected image. C. First sub-region from the left. D. Line profile of the equator of the microtubule sub-region Fourier transform. The cross is placed at the level of the second large peak of the J0 Bessel term (red arrow). E. Straightened microtubule image.


  4. Microtubule centering

    1. Select ‘image_orig-straight’ and click on ‘Center straight fiber’, set the max width of the FFT to 2048 pixels (Figure 4A) and press ‘OK’. The Fourier transform of the image is presented (not shown) together with a profile on the equator of the microtubule image FFT (Figure 4B).

    2. Click at the level of the third large peak starting from the left (around 55 in frequency). An image named ‘image_orig-straight-Centered’ is presented’ (Figure 4C), and the translation along the ‘Y-axis’ is indicated in the log window. It should be minimal (less than 1 pixel) if the ‘image_orig-straight’ image has not been cropped.

      Notes:

      1. When protofilaments are skewed with respect to the longitudinal axis of the microtubule, the profile plot of the equator should be composed only of J0, without contribution of JN (see the power spectra in Figures 5A-5B and 6A). Hence, it is safe to click on a peak at higher resolution than in the straightening process.

      2. We have limited the size of the Fourier transform to 4,096 x 4,096 pixels since the centering procedure is computationally intensive. This process can take time, wait until it is finished.



    Figure 4. Microtubule centering. A. Setting of the FFT size. B. Line profile of the equator of the straightened microtubule image Fourier transform. The cross is placed at the level of the third large peak of the J0 Bessel term (red arrow). C. Centered image.


  5. Determination of protofilament handedness and tubulin subunit repeat along protofilaments

    1. Select ‘image_orig-straight-Centered’ and click on ‘Analyze FFT’. The Fourier transform of the image is presented together with a horizontal line crossing the power spectrum. Select the FFT window and zoom in until the diffraction pattern fills the image. Adjust the contrast to emphasize the layer-line pattern (e.g., from 0 to ~3.0E13 in the B&C window).

    2. Move the yellow line to cross the JS layer line (Figure 5A) and press ‘OK’.

    3. Move the yellow line to cross the JN-S layer line (Figure 5B) and press ‘OK’. Line profiles of JS and JN-S are presented (Figures 5C-5D).

    4. In the window ‘Analyze FFT parameters’ (Figure 5E), let the default values (‘approximate size in Å: 40.0’, and ‘range of search (in Å): 10’), and press ‘OK’. This sets the interval for searching peaks in the FFT. A window opens asking if you want to close intermediate windows. Press ‘OK’. Results are provided in the log window: The ‘monomer repeat’ is 40.87 Å and the protofilament skew angle ‘theta’ is positive. These values will be used to determine the protofilament skew angle (G) and to build image stacks suitable for 3D reconstruction (H).

      Notes:

      1. The Fourier transform of a helical fiber is characterized by layer lines that correspond to the different helical families present in this fiber. These layer lines are mathematically described by Bessel functions. In the case of microtubules, the Bessel function of order ‘0’ (J0) is due to the tubular nature of microtubules. It lies on the ‘equator’ of the Fourier transform, and is used to precisely center microtubule images (see Blestel et al., 2009, for details). The Bessel function of order ‘N’ (JN) arises from the linear arrangement of the tubulin molecules along the N protofilaments. Since the protofilaments are almost parallel to the microtubule longitudinal axis, JN lies close to J0 (Figure 5A). The Bessel function of order ‘S’ is due to the lateral interactions between tubulin monomers around the microtubule lattice. A full turn of this helix includes S monomers in height (between S = 2 and S = 4 in most microtubule types). JS lies close to the ‘meridian’ of the Fourier transform of microtubule images (Figure 5A, the meridian is perpendicular to the equator). The Bessel function of order ‘N-S’ is geometrically related to JN and JS. JN-S is further away from the meridian than JS (Figure 5A).

      2. Determination of the protofilament skew angle sign is based on the following rule (Chrétien et al., 1996): When JS is farther away from the equator than JN-S, theta is negative, and when JS is closer to the equator than JN-S, theta is positive.



    Figure 5. Analysis of the microtubule Fourier transform. A. Selection of the JS layer line. The main layer lines are indicated. J0 lies on the equator of the Fourier transform. JS is closer to the equator than JN-S, indicating that the microtubule has right-handed protofilaments. B. Selection of the JN-S layer line. C. Line profile along JS. D. Line profile along JN-S. E. Peak search interval.


  6. Microtubule image filtering and determination of microtubule polarity

    1. Select ‘image_orig-straight_Centered’ and click on ‘Filter fiber’.

    2. Select the FFT window (Figure 6A) and zoom in until the diffraction pattern fills the image.

    3. Select the rectangular tool of ImageJ and draw a rectangle that incorporate the J0 and the first peak of the JN term on each side of the equator and press ‘OK’.

    4. Enter 21 lines and press ‘OK’. Click ‘Yes’ to accept the selected region and answer ‘No’ in the window ‘Do you want to select other layer lines?’. An image named ‘filtered image’ is presented (Figure 6B), which emphasizes the moiré pattern originating from the skewed protofilaments imaged in projection.

    5. The moiré pattern has an ‘arrowhead’ shape pointing to the left of the image. Since the protofilaments are right-handed (theta is positive), the microtubule is oriented with its plus end pointing to the left.
      Note: The arrowhead pattern is due to the asymmetric shape of tubulin when viewed along the microtubule axis (see Figures 9D and 10). The directionality of this pattern reverses when protofilament have opposite chirality (Chrétien et al., 1996; Sosa and Chrétien, 1998). The rule to determine microtubule polarity is the following: The fringe pattern points towards the plus end of microtubules with right-handed protofilaments (θ > 0), and towards the minus end of microtubules with left-handed protofilaments (θ < 0).



    Figure 6. Microtubule image filtering. A. Selection of J0 and of the first peak JN. B. Filtered image. The moiré pattern displays an arrowhead shape that points toward the left of the image.


  7. Determination of the protofilament skew angle

    1. Select ‘filtered image’ and click on ‘Determine protofilament angle’. Select the ‘filtered image’ (Figure 7A) and move the line with the arrow key so that it crosses minima and maxima of the fringe pattern (6 pixels up) and press ‘OK’.

      Note: In the case of a microtubule with an even protofilament number, the line should be adequately placed in the middle of the filtered image. Here, the protofilament number is odd (N = 15), which necessitates moving the line slightly off center to cross maxima and minima of the moiré pattern.

    2. Three line plots open corresponding to the line profile (‘line intensities’, Figure 7B), a smoothed version to attenuate local variations if present (not shown), and the absolute value of the smoothed line profile (‘line intensities after abs()’ Figure 7C). A window opens providing the measured period (in pixels, Figure 7D), the pixel size and the protofilament separation (set as default to 48.95 Å). Let the ‘negative pf angle’ unchecked since it has been previously determined to be positive and press ‘OK’. A window opens to close intermediate windows, press ‘OK’.

    3. Close the filtered image.

    The moiré period L (1906.56 Å) and the protofilament skew angle theta (+1.47 Å) are given in the log window.

    Note: The protofilament skew angle θ is calculated according to the following formula:

    where  δx denotes the separation between adjacent protofilaments. The separation between protofilaments x is difficult to retrieve from individual images. If several types of microtubules are present in the specimen, this can be estimated by measuring the change in image width with protofilament number (Chrétien and Wade, 1991). The default value of 48.95 Å was derived from medium-resolution 3D maps of microtubules with from 11 to 16 protofilaments (Sui and Downing, 2010).



    Figure 7. Determination of the protofilament skew angle. A. Selection of the moiré profile. B. Line profile revealing the moiré period (distance between two maxima or minima). C. Absolute value of the moiré period. This strategy has been implemented to measure low protofilament skew angles where only half the moiré repeat is present (like in most 13_3 microtubules).


  8. Stack generation

    1. Select ‘image_orig-straight_Centered’ and press ‘Create stack from straight MT’. Fix the protofilament number to 15 and the helical-start number to 4 (Figure 8A). Let the other parameters as provided and press ‘OK’.

      Notes:

      1. A ‘Create stack from curved MT’ routine is provided to extract stack images from the original (contrast corrected) microtubule image (saved as ‘orig_corrected.tif’ in the working directory). This option can be useful if one wishes to process the image stack with other 3D reconstruction software.

      2. A rigorous determination of N and S would require a detailed analysis of the positions and phases of the layer lines in the Fourier transform of the images (Stewart, 1988), which goes beyond the scope of this protocol. The parity of N can be determined from the symmetry of the fringe pattern: it is centered for even protofilament numbers, and off-center for odd protofilament numbers. The value of N can then be estimated by comparing the microtubule diameter with that of other microtubules present in the specimen, and also by comparing the fringe pattern with published images of microtubules with different N_S configurations (Chrétien and Fuller, 2000). The helical start number S can be estimated from the sign of the protofilament skew angle (Table 1). In the present case, N = 15 and θ is positive, hence S = 4.


      Table 1. Sign of θ for the main microtubule types assembled in vitro from purified tubulin (taken from Chrétien and Fuller, 2000), n. o.: not observed.

      These latter N_S configurations require protofilament skew angles > ± 4°, which may represent a limit in the twist that the tubulin molecule can accommodate.

    2. A window opens asking the approximate MT length (86 pixels; Figure 8B). Let this value and press ‘OK’. The incremental ‘Z-shift ‘(1.26 pixels) and ‘Angular shift’ (-95.966°) assigned to the stack images are given in the result window.

      Notes:

      1. The ‘Helical rise’ (r = 9.64 Å) corresponds to the longitudinal stagger between tubulin monomers in adjacent protofilaments. It is calculated according to the following formula:

        where S denotes the monomer helical start number, ‘a’ the tubulin subunits repeat along protofilaments, N the protofilament number,x the separation between protofilaments, and L the moiré period (with the sign of θ).

      2. The ‘approximate MT length’ value determines the height of the volume that will be calculated at the following step so that it encompasses at least 4 monomer helical starts.

    3. A histogram opens showing the angle distribution assigned to the images of the stack (‘Angle distribution’), Figure 8C. A stack is presented (‘image_orig-straight_Centered_angle_-95.966’, Figure 8D), which is composed of 2214 images corresponding to views extracted at each subunit monomer position along the microtubule image.



      Figure 8. Stack generation. A. Stack generation parameters. B. Stack height. C. Angular distribution of the stack images. D. Image stack.


    4. Table 2 summarizes the microtubule lattice parameters derived from this analysis:

      Table 2. Microtubule lattice parameters. Polarity is from plus end (left) to minus end (right) in the original image.
       

  9. 3D reconstruction
    1. Click on ‘Compute MT 3D reconstruction’. Let ‘Invert intensities?’ checked and the ‘weighting radius’ to 0.0 (Figure 9A), then press ‘OK’.

      Notes:

      1. Images taken on a camera under defocused conditions display protein as dark. Contrast inversion is thus necessary to examine these data in UCSF Chimera (J). Scanned images recorded on negatives display the protein density as white. In that case, uncheck the ‘Invert intensities?’ button.

      2. The weighting radius can be set to higher values (between 0 and 0.5) in order to attenuate the contribution of low frequencies, which are amplified during back projection (Radermacher, 1992). Yet, this is done at the expense of increasing the noise in the final 3D reconstruction.

    2. A ‘Progression…’ window opens (Figure 9B): wait until the ‘stack_straight_3dReconstruction’ is calculated (Figure 9C). Scroll through this volume, the tubulin subunits (shown in white) are clearly visible in the volume. Select ‘Image -> Stacks -> Reslice [/]…’ then select ‘Start at: top’ and press ‘OK’ (Figure 9D). The asymmetry of the tubulin subunits indicates that we are looking at this map from the plus end ( Chrétien et al., 1996 ; Sosa and Chrétien, 1998; see also (J)). The top-to-bottom orientation of the 3D map corresponds to the left-to-right orientation in the original image, which indicates that the polarity was well assigned.

    3. Select ‘stack_straight_3dReconstruction’ and click on ‘Elongate 3D MT’ (Figure 9E). Let the 3 first parameters as default, fix the final length to 1024 and press ‘OK’. This generates an elongated version of the microtubule where the protofilament skew and its handedness can be observed (Figure 9F).

      Note: The z shift and angle shift used to elongate the microtubule correspond to the parameters of the basic one start helix that join all the tubulin subunits within the microtubule lattice. These values are also used to perform the 3D reconstruction of the microtubule, see Blestel et al. (2009) for deeper details.



      Figure 9. Microtubule 3D reconstruction. A. 3D reconstruction parameters. B. Progression bar. C. 3D reconstruction. D. 3D reconstruction observed from the top. E. Elongation parameters. F. Elongated version of the microtubule. The right-handed skew of the protofilaments is clearly visible.


    4. Examine the working directory, several files have been created (listed in chronological order):

      1. calibration.cvs: pixelSize, the pixel size in Å.

      2. image_orig.tif: the region extracted from the original image.

      3. image_corrected.tif: the region extracted from the original image corrected for contrast variations.

      4. centers.txt: number of local centers and their x, y coordinates.

      5. straight_image.tif: the straightened image.

      6. image_orig-straight_Centered.tif: the straight image centered.

      7. analyzeFFT.csv: pixelSize, the pixel size in Å; monomerRepeat, the monomer repeat along protofilaments (in Å); thetaSign, the sign of theta (1 positive, -1 negative).

      8. filtered image.tif: the filtered image.

      9. protofilament.csv: l(pixel), the moiré period in pixels; pixelSize, the pixel size (in Å); L(angstrom), the moiré period (in Å), Pf separation(angstrom); the protofilament separation (in Å); theta, the protofilament skew angle (in °).

      10. angle_distribution.csv: the number of views assigned in the stack for each angle (Y), from 0° to 359° (X).

      11. angles.txt: the angular orientation assigned to the images of the stack.

      12. elongation.csv: zshift, the Z-rise of tubulin monomers with respect to the longitudinal axis of the microtubule; angleshift, the angular increment of tubulin monomers around the microtubule Z axis; nbProtofilaments, the protofilament number; helicalRise, the helical rise of tubulin subunits along adjacent protofilaments.

      13. stack_straight.tif: the image stack used for 3D reconstruction.

      14. stack_straight_3dreconstruction.tif: the 3D reconstruction of the microtubule.

      15. 3dReconstruction_elongated.tif: the elongated version of the 3D reconstruction.


  10. Observation of the 3D reconstructions with UCSF Chimera

    1. Open the ‘stack_straight_3dreconstruction.tif’ volume saved in the working directory into UCSF Chimera.

    2. Display the command line: ‘Menu->Favorites->Command line’.

    3. Open the camera viewer: ‘Menu->Tools->Viewing Controls->Camera’ and select ‘orthographic’.

    4. Open the Volume viewer: ‘Menu->Tools->Volume Data->Volume Viewer’, and in the ‘Features’ menu, check ‘Brightness and Transparency’, ‘Coordinates’, and ‘Threshold and Color’.

    5. Adjust the ‘Level’ to enlarge tubulin densities (e.g., to ‘Level = 300’) and set the ‘Transparency’ to 0.50.

    6. In the command line, enter ‘turn x 90 1’.

    7. Set the voxel size to 2.16 Å and press center.

    8. Select the ‘Side View’ tab of the ‘Viewing window’ and press ‘View All’.

    9. Open the tubulin map 1tub: ‘Menu->File->Fetch by ID…’, check the ‘PDB’ button, enter 1tub and press ‘Fetch’.

    10. In the command line, enter ‘move 62,-30,-30 mod #1; turn y 90 1 mod #1 center #1’. The tubulin map is oriented with its plus end viewed from the top (Figure 10A). Comparison of the overall shape of the 1tub model with that of the microtubule map confirms that the plus end points towards the top of the reconstruction.

    11. In the command line, enter ‘move -45,-110,0 mod #0’. Select ‘Volume Viewer->Tools->Fit in Map’ and fit ‘1tub (#1) in map ‘stack_straight_3dreconstruction.tif (#0)’. Inspect the fit of the 1tub model inside the 3D density of the microtubule (Figures 10B-10F).

      Notes:

      1. The good agreement between the overall shape of the 1tub model and the 3D reconstruction, including the correspondence of structural motifs such as densities corresponding to the lateral interactions, the H1-S2-loop pointing inward and the C-terminal α-helices pointing outward (Figure 10B), give a fair confidence that the parameters derived from the analysis were adequately determined.

      2. The original image has not been corrected for the effect of the Contrast Transfer Function. This can be performed before processing the images in TubuleJ in order to improve the quality of the final reconstruction.

    12. Save the session in the working directory as ‘MTa.py’.

    13. Close the session and open ‘3dReconstruction_elongated.tif’.

    14. Set the step size to 2 and adjust the ‘Level’ to 300. The right-handed skew of the protofilaments is clearly visualized in this elongated version of the microtubule 3D reconstruction (Figure 10G).

    15. Save the session as ‘MTa_Elongated.py’.

      Note: The visualization procedure using UCSF Chimera is provided in Video 2.



Figure 10. Visualization of the 3D reconstruction with UCSF Chimera. A. Comparison of the 3D reconstruction with the 1tub tubulin model. B. Fit of 1tub into the 3D reconstruction. Plus end view. Structural features that allow a good match between the tubulin model and the 3D reconstruction are indicated. C. Minus end view. D. Inside view. E. Outside view. F. Side view. G. Elongated version of the 3D reconstruction.


Video 2. Observation of the 3D reconstruction using UCSF Chimera

Acknowledgments

This work was funded by the Agence Nationale de la Recherche (ANR-16-C11-0017-01). We thank S. Blestel who wrote the original version of TubuleJ. The determination of microtubule centers used in TubuleJ was published in Blestel et al. (2009). TubuleJ was used in Estévez-Gallego et al. (2020) to analyze the structure of microtubules assembled in the presence of GTP, GMPCPP and GDP-BeF3-.

Competing interests

TubuleJ was deposited to the Agency for the Protection of programs (APP) under the code number IDDN.FR.001.240023.000.S.P.2011.000.21000.

References

  1. Blestel, S., Kervrann, C. and Chrétien, D. (2009). A Fourier-based method for detecting curved microtubule centers: Application to straightening of cryo-electron microscope images. Proceedings of the IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston. 2009, June 28-July 1 298-301.
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简介

[摘要]的α - β微管蛋白异源二聚体经历微管组装期间细微的构象变化。这些可以由外部因素调节,其对微管结构的影响可以在通过冷冻电子显微镜获得的二维视图上表征。如果微管图像足够直,可以解释和过滤其图像,则有助于微管图像的分析,这将提供有关微管蛋白分子在微管晶格内排列的有用信息。在这里,我们描述了使用TubuleJ软件来拉直微管并确定其晶格参数。可以执行基本的3D重建来评估这些参数的相关性。此方法可用于分析核苷酸类似物,药物或MAP对微管结构的影响,或在高分辨率3D重建之前选择微管图像。

[背景]微管是聚合物α - β微管蛋白异源二聚体,在直径和几个μ约25nm形式管米长。微管蛋白结合两个分子的三磷酸鸟苷(GTP),其中一个在组装过程中被水解成GDP。GTP水解是微管动力学的关键,因为它破坏了其晶格的稳定性,并允许它们在细胞活动期间快速重排和翻转。与GTP作品类似物如鸟苷酰- (α ,β ) -亚甲基二膦酸盐(GMPCPP)或鸟苷5' - (γ -硫代) -三磷酸(GTP γ小号)产生了一个模型,其中GTP微管蛋白经历压实在组装和GTP水解过程中其亚基之间的旋转(Zhang et al 。,2015)。该模型最近受到一项涉及一系列核苷酸类似物和结构方法的研究的挑战,其中包括X射线晶体学,小角度X射线衍射和低温电子显微镜(Estévez - Gallego等人,2020年)。这项研究得出的建议是,如果微管蛋白维持扩张-压缩构象变化,则将在GTP水解后发生,以促进无机磷酸盐的释放。

已经显示出其他因素可调节微管的紧缩状态或微丝的原丝偏斜角(Manka and Moores ,2018)。端结合蛋白(EBS),其结合在原丝之间已经提出了通过压缩的微管蛋白,以加速GTP水解和诱导左手捻晶格(张ê吨人。,2018)。据报道,紫杉醇会产生类似于GMPCPP微管的扩张状态(Vale等,1994;Estévez- Gallego等,2020),表明该状态反映了微管中微管蛋白的稳定构象。

尽管对微管的高分辨率分析易于描述接近原子水平的这些构象变化,但仍需要仔细选择均质类型的微管。当从纯微管蛋白体外重组时,微管形成一系列结构,这些结构在原丝和/或侧向螺旋起始数方面有所不同(Chrétien和Fuller ,2000)。为了适应这些变化,原丝相对于微管纵轴偏斜(Langford,1980)。这就产生了在2D投影视图中通过低温电子显微镜观察到的莫尔图案,这些图像可以直接测量其原丝的偏斜角(Chrétien和Wade ,1991)。此外,这种云纹图案具有反映微管极性的箭头形状,前提是已经明确确定了原丝的手感(Chrétien等,1996; Sosa和Chrétien,1998)。可以根据微管图像的衍射图准确测量微管蛋白的紧缩状态(Vale等,1994; Hyman等,1995),微管蛋白亚基的螺旋上升反映了它们在横向上的相互作用。当所有其他参数都已知时推论得出(Chrétien和Fuller ,2000;Estévez- Gallego等,2020)。

为了便于分析通过低温电子显微镜获得的微管图像,我们开发了TubuleJ作为多平台ImageJ软件的插件(Schneider等,201 2 )。TubuleJ的基本原理最初在(Blestel et al 。,2009)中进行了描述。当前版本已使用新的例程进行了更新,并结合了TomoJ (Messaoudi等人,2007)来执行微管的快速3D重建。图1显示了TubuleJ的工作流程。



图1. TubuleJ工作流程。A. TubuleJ菜单。B. TubuleJ处理例程。本协议仅描述了黑色的步骤。此协议中未介绍“从文件中取消光纤缠绕”步骤和“从弯曲光纤中创建堆叠”步骤。TubuleJ分为三个“模块”。模块1(左)可用于任何类型的光纤,而模块2(中)和模块3(右)专用于微管。模块2允许确定微管晶格参数,而模块3允许基本3D重建,而无需区分α - β微管蛋白单体。

关键字:微管蛋白, 微管, 微管晶格参数, 微管极性, 冷冻电子显微镜, 图像分析, 螺旋组装体, 三维重构

设备

 

Mac-Pro(mi-2010),2 x 3.46 GHz,2 x 6核Intel Xeon,96 Go 1333 MHz DDR3 RAM,SSD 1 To,3 x 6 To Sata磁盘,2 x NVIDIA Quadro K5000图形卡,macOS版本10.13.6(Apple Inc.)
笔记:

一种。使用当前配置,可以在不到10分钟的时间内完成微管晶格参数的确定和3D重建的计算。       

b。由于ImageJ是多平台的,因此TubuleJ插件可以在任何装有兼容操作系统(MacO ,Linux,Windows)的计算机上安装和运行。TubuleJ需要并行处理(快速傅立叶变换具有平行FFTJ,3D重建与优点TomoJ )。因此,辑阵-core处理器将加速计算。根据您的配置为ImageJ分配足够的RAM,并确保它使用并行处理(“编辑->选项->内存和线程…”)。      

 

软件

 

ImageJ软件:https : //imagej.nih.gov/ij/
TubuleJ插件到ImageJ:https : //igdr.univ-rennes1.fr/TubuleJ/
FFTJ(在TubuleJ中实现):https : //sites.google.com/site/piotrwendykier/software/parallelfftj
并行FFTJ是ImageJ的多线程快速傅立叶变换插件。

TomoJ (在TubuleJ中实现):https : //sourceforge.net/projects/tomoj/
TomoJ允许在执行3D重建之前对倾斜序列进行预处理和配准。

加州大学旧金山分校Chimera:https : //www.cgl.ucsf.edu/chimera/
 

程序

 

TubuleJ安装
从https://igdr.univ-rennes1.fr/TubuleJ/下载TubuleJ和测试图像。
解压缩TubuleJ.zip并将TubuleJ文件夹安装在ImageJ的插件文件夹中。
 

微管选择
打开电子显微镜伊马GE以lm ageJ。
选择“插件-> TubuleJ- > TubuleJ ” 。TubuleJ的界面打开(图1A)。
单击“选择光纤”,然后创建一个名为“ MTa ”的文件夹。选择此文件夹作为您的工作目录。
注意:单个图像中经常会出现多个微管,这需要为每个要分析的微管创建一个单独的文件夹。

将像素大小固定为2.16Å(图2A),然后按“确定”。
注意:如果存在像素大小,则会自动从标题中恢复像素大小。如果不存在或不正确,则必须在此阶段进行设置。在当前情况下,图像标题为2.21Å,但是实际放大倍数是使用烟草花叶病毒校准的,该像素的像素大小为2.16Å。如果要分析微管蛋白的紧实状态(Hyman等,1995),由于亚基单体重复序列的变化约为几埃,因此在工作放大倍数下精确校准图像非常重要。

在目标光纤上画一条线(图2B),然后按“确定”。这定义了图像的旋转角度。
在感兴趣的光纤周围画一个方框(图2C),然后按“确定”。呈现了一个名为“ image_orig.tif ”的图像(图2D)。选择整个图像(“编辑”->“全选”),然后将图像调整为例如189的高度,以最小化背景(图像->裁剪;图2E)。将此图像保存在工作目录中。
笔记:

一种。视频1中提供了从微管选择(B)到3D重建(I)的过程。                     

b。由于插件从在ImageJ中打开的当前图像开始,因此TubuleJ可以使用在ImageJ中可以打开的任何文件格式。它包括tiff等经典格式。通过安装TomoJ,也可以接受专用于电子显微镜的格式,例如dm3,mrc,spider或mrc.bz2。      



图2.微管选择。A.像素大小设置。B.微管图像的旋转。C.微管图像拳击。D.提取区域。E.裁剪提取区域以使背景最小化。

 



视频1.微管图像分析和3D重建

 

微管矫直
选择“ image_orig.tif ”,然后单击“ Untwist fiber”。设置以下参数(图3A):'输入子图像的宽度(像素):384'; '输入步长(像素):192'; “输入直纤维图像的高度(像素):185”。让我们检查“正确的对比度”;“半径:60”,请取消选中“显示中间台阶图像”,然后按“确定”。在日志窗口中指示了微管子区域相对于水平的方向。呈现了针对对比度变化进行校正的提取图像(图3B),以及从左侧开始的第一个子区域(水平方向大致对齐)(图3C)以及微管子区域傅里叶变换的赤道的线轮廓(图3D) )。
笔记:

一种。子区域的宽度将取决于像素大小和图像中存在的信噪比。我们通常在标本级别使用50至100 nm之间的子图像长度。步长可以设置为宽度的一半,而直纤维的高度大约比微管图像的宽度(像素)大65%。对宽度尺寸使用奇数值,以使微管图像正确居中。注意:灰色渐变主要是由于冰厚度的变化,例如,从碳孔的边界到中心。为了正确过滤微管图像,必须对其进行校正。'radius'选项对应于ImageJ中的高斯滤波器的值,该值用于生成从原始图像中减去的背景图像。                      
                                                                                                                                                                                                                 

b。选项“显示中间步骤图像”显示所有摘录(名为“水平和居中窗口”的图像),以及显示用黑线连接的局部中心(白叉)的图像。这些图像的分析可能有助于确定为什么在局部确定微管中心时算法失败。      

单击从左侧开始的第二个大峰值的水平(频率约为10,图3D)。可以在日志窗口中跟踪本地中心计算的进度。呈现了针对对比度变化进行校正的矫正图像,称为“ image_orig -straight”(图3E)。
笔记:

一种。TubuleJ使用J 0贝塞尔函数的相位来使微管图像居中(Blestel等,2009),其对应于图3D中的3-4个第一大峰。较高分辨率的峰可能与J N重叠(N =原生丝数,此处N = 15)。选择频率在〜10处的第二个大峰值限制了J N项的贡献,这可能会破坏对中过程。       

b。由于点中心是从第一个子区域的中间到最后一个子区域的中心,因此拉直后的图像比原始图像短。TubuleJ手册中提供了使整个图像变直的过程。此过程使用此协议中未描述的“从文件中解绕光纤”例程。此例程也可用于调整偏心点。      



图3.微管矫直。A.矫直参数。B.对比校正图像。C.从左边开始的第一个子区域。D.微管子区域傅里叶变换的赤道的线轮廓。十字放置在J 0 Bessel项的第二个大峰值的水平(红色箭头)。E.拉直的微管图像。

 

微管对中
选择“ image_orig -straight”,然后单击“ Center Straight Fiber”,将FFT的最大宽度设置为2048像素(图4A),然后按“ OK”。图像的傅里叶变换(未显示)与微管图像FFT的赤道上的轮廓一起显示(图4B)。
单击从左边开始的第三个大峰值的水平(频率大约为55)。出现了一个名为“ image_orig -straight-Centered”的图像(图4C),并且在日志窗口中指示了沿“ Y轴”的平移。如果未裁剪' image_orig -straight'图像,则它应最小(小于1像素)。
笔记:

一种。当原丝相对于微管的纵轴倾斜时,赤道的剖面图应仅由J 0组成,而没有J N的贡献(请参见图5A-5 B和6A中的功率谱)。因此,以比校正过程中更高的分辨率单击峰是安全的。       

b。我们已经限制了傅里叶变换大小至4 ,096×4 ,096像素,因为中心的过程是计算密集型的。此过程可能需要一段时间,请等到完成为止。      



图4.微管居中。A.设置FFT大小。B.经拉直的微管图像的傅立叶变换的赤道的线轮廓。十字放置在J 0 Bessel项的第三个大峰值的水平(红色箭头)。C.居中图像。

 

确定原丝的手感和沿原丝重复的微管蛋白亚基
选择“ image_orig -straight-Centered”,然后单击“ Analyze FFT”。呈现图像的傅立叶变换以及与功率谱交叉的水平线。选择FFT窗口并放大,直到衍射图样填满图像。调整对比度以强调图层线条图案(例如,在B&C窗口中,从0到〜3.0E13)。
移动黄线越过J S层线(图5A),然后按“确定”。
移动黄线越过J N-S层线(图5B),然后按“确定”。的线剖面Ĵ小号和Ĵ N-S被呈现(图小号5C- 5 d)。
在“分析FFT参数”窗口(图5E)中,设置默认值(“以Å为单位的近似大小:40.0”和“以Å为单位的搜索范围:10”),然后按“确定”。这设置了在FFT中搜索峰值的间隔。将打开一个窗口,询问您是否要关闭中间窗口。按“确定”。结果显示在对数窗口中:“单体重复”为40.87Å,原丝偏斜角“θ”为正。这些值将用于确定原丝偏斜角(G)并构建适合3D重建(H)的图像堆栈。
笔记:

一种。螺旋光纤的傅立叶变换的特征在于与该光纤中存在的不同螺旋族相对应的层线。这些层线在数学上由Bessel函数描述。在微管的情况下,阶数为“ 0”(J0)的贝塞尔函数是由于微管的管状性质所致。它位于傅立叶变换的“赤道”上,用于精确地使微管图像居中(有关详细信息,请参阅Blestel等,2009)。“ N”阶(JN)的贝塞尔函数来自微管蛋白分子沿N个原丝的线性排列。由于原丝大致平行于微管纵向轴线,JN位置靠近J0(图URE 5A)。“ S”阶的贝塞尔函数是由于微管晶格周围的微管蛋白单体之间的横向相互作用。此螺旋的一整圈包括高度为S的单体(在大多数微管类型中,S = 2至S = 4)。JS位置靠近所述傅里叶微管的图像的变换“子午线”(图URE 5A,经络垂直于赤道)。阶“ N-S”的贝塞尔函数在几何上与JN和JS有关。JN-S从子午线比JS(图更远是URE 5A)。       

b。原丝偏斜角符号的确定基于以下规则(Chrétien等,1996):当J S比J N-S距赤道更远时,θ为负,当J S比J距赤道更近时。NS ,θ是正的。      

 



图5.微管傅里叶变换的分析。A.选择J S层线。指示了主层线。J 0位于傅立叶变换的赤道上。J S比J N-S更靠近赤道,表明微管具有右手的原丝。B.选择J N-S层线。C.沿J S的线轮廓。D.沿J N-S的线轮廓。E.峰值搜索间隔。

 

微管图像过滤和微管极性的确定
选择“ image_orig-straight_Centered ”,然后单击“滤光纤维”。
选择FFT窗口(图6A)并放大直到衍射图填充图像。
选择ImageJ的矩形工具,并在赤道的每一侧绘制一个包含J 0和J N项的第一个峰的矩形,然后按“确定”。
输入21行,然后按“确定”。单击“是”接受所选区域,然后在“是否要选择其他图层线?”窗口中回答“否”。呈现了一个名为“过滤后的图像”的图像(图6B),该图像强调了莫尔图案,该莫尔图案源自投影中成像的歪斜原丝。
波纹图案具有指向图像左侧的“箭头”形状。由于原丝是右手的(θ为正),因此微管的正端指向左侧。
注意:箭头图案是由于沿微管轴观察时微管蛋白的不对称形状引起的(请参见图9D和10)。当原丝具有相反的手性时,这种模式的方向性相反(Chrétien等,1996; Sosa和Chrétien,1998)。确定微管极性的规则如下:条纹图案指向带有右手原丝(θ > 0)的微管正端和指向带有左手原丝(θ < 0)的微管负端。
 



图6.微管图像过滤。A.选择Ĵ 0和第一峰的Ĵ Ñ 。B.过滤的图像。波纹图案显示的箭头形状指向图像的左侧。

 

初丝偏斜角的确定
选择“过滤图像”,然后单击“确定原丝角度”。选择“过滤后的图像” (图7A)并使用箭头键移动线,使其越过条纹图案的最小值和最大值(向上6个像素),然后按“确定”。
注意:如果微管的原丝数目均匀,则该线应适当放置在过滤图像的中间。在这里,原丝数是奇数(N = 15),因此必须将线稍微偏离中心移动,以越过莫尔条纹的最大值和最小值。

打开三个与线轮廓相对应的线图(“线强度”,图7B),用于减弱局部变化(如果存在)的平滑版本(未显示)以及平滑线轮廓的绝对值(“ abs()之后的线强度) '图7C)。将打开一个窗口,提供测量的周期(以像素为单位,图7D),像素大小和原丝间隔(默认设置为48.95Å)。由于先前已确定它为正,因此取消选中“负pf角”,然后按“确定”。打开一个窗口以关闭中间窗口,然后按“确定”。
关闭过滤的图像。
在对数窗口中给出了莫尔条纹周期L (1906.56Å)和原丝偏斜角theta(+1.47Å)。

注意:原丝偏斜角θ根据以下公式计算:

 



其中x表示相邻原丝之间的间隔。原丝x之间的分离很难从单个图像中检索。如果样本中存在几种类型的微管,可以通过测量图像宽度随原丝数的变化来估计(Chrétien和Wade ,1991 )。默认值48.95Å是从具有11至16个原丝的中分辨率微管3D图获得的(Sui和Downing,2010年)。 

 



图7.确定原丝偏斜角。A.莫尔轮廓的选择。B.线形揭示了云纹期(两个最大值或最小值之间的距离)。C.云纹期的绝对值。已实施该策略以测量低原丝偏斜角,其中仅出现一半的莫尔纹重复(就像在大多数13_3微管中一样)。

 

堆栈生成
选择“ image_orig-straight_Centered ”,然后按“从直线MT创建堆栈”。将原丝编号固定为15,将螺旋起始编号固定为4(图8A)。设置其他参数,然后按“确定”。
笔记:

一种。提供了“从弯曲MT创建堆栈”例程,以从原始(经对比度校正)微管图像(在工作目录中另存为“ orig_corrected.tif ” )中提取堆栈图像。如果希望使用其他3D重建软件处理图像堆栈,则此选项很有用。       

b。严格确定N和S要求对图像的傅里叶变换(Stewart,1988)中的层线的位置和相位进行详细分析,这超出了该协议的范围。N的奇偶性可以通过条纹图案的对称性来确定:对于偶数的原丝数,其中心位于中心;对于奇数的原丝数,其中心位于中心。N的值可以通过比较微管直径与存在于样品中的其它微管来估计,并且还通过条纹图案具有不同N_S配置微管的发布的图像(Chréti比较EN和Fuller ,2000)。可以从原丝偏斜角的符号(表1)估算出螺旋起始数S。在当前情况下,N = 15并且θ为正,因此S = 4。      

 

表1 。从纯化的微管蛋白体外组装的主要微管类型的θ符号(取自Chrétien和Fuller ,2000年),否:未观察到。后面这些N_S构型要求原丝偏斜角>±4°,这可能代表微管蛋白分子可以适应的扭曲极限。

ñ

10

11

12

13

14

15

16

S = 2

--

--

--

--

--

没有

没有

S = 3

+

+

+

+/-

--

--

--

S = 4

没有

没有

没有

+

+

+

+

 

将打开一个窗口,询问大约MT长度(86像素;图8B)。设置该值,然后按“确定”。在结果窗口中给出了分配给堆栈图像的增量“ Z平移”(1.26像素)和“角度平移”(-95.966°)。
笔记:

一种。“螺旋上升”(r = 9.64Å)对应于相邻原丝中微管蛋白单体之间的纵向错位。根据以下公式计算:       

 



其中S表示单体螺旋起始编号,微管蛋白亚基沿着原丝重复,a为原丝数量N,原丝之间的间隔x,摩尔纹期为L(符号θ )。

b。“大约MT长度”值确定了将在后续步骤中计算的体积高度,以使其包含至少4个单体螺旋起点。      

甲histogr上午打开,显示分配给该堆栈(“角度分布”),图11的图像中的角度分布URE 8C。展示了一个堆栈(“ image_orig-straight_Centered_angle_-95.966”,图8D),该堆栈由2214张图像组成,这些图像对应于沿微管图像在每个子单元单体位置提取的视图。
 



图8.堆栈生成。A.堆栈生成参数。B.堆高。C.堆栈图像的角度分布。D.图像堆栈。

 

表2总结了此分析得出的微管晶格参数:
 

表2 。微管晶格参数。极性从原始图像的正端(左)到负端(右)。

ñ

小号

一个(Å)

r (Å)

 θ (° ) 

极性

15

4

40 .87

9.64

+1.47

+ /-

 

3D重建
单击“计算MT 3D重建”。让“反转强度?” 选中,并将“加权半径”设置为0.0(图9A),然后按“确定”。
笔记:

一种。在散焦条件下在相机上拍摄的图像显示蛋白质为深色。因此,为了在UCSF Chimera中检查这些数据,必须进行对比度反演(J)。记录在底片上的扫描图像将蛋白质密度显示为白色。在这种情况下,请取消选中“反转强度?” 按钮。       

b。可以将加权半径设置为较高的值(0到0.5之间),以减弱低频的影响,低频的影响在反投影过程中会放大(Radermacher ,1992)。然而,这样做的代价是在最终的3D重建中增加了噪声。      

将打开一个“ Progression…”窗口(图9B):等待直到计算出“ stack_straight_3dReconstruction”(图9C)。滚动浏览该体积,在该体积中清晰可见微管蛋白亚基(以白色显示)。选择' Image- > Stacks- > Reslice [/]…',然后选择'Start at:top',然后按'OK'(图9D)。所述ASY微管蛋白亚单位的mmetry表明我们看这个地图从正端(克雷蒂安等人,1996;索萨和克雷蒂安,1998;另见(J))。3D贴图的从上到下方向与原始图像中的从左到右方向相对应,这表明极性分配正确。
选择“ stack_straight_3dReconstruction”,然后单击“伸长3D MT”(图9E)。将第三个参数作为默认值,将最终长度固定为1024,然后按“确定”。这产生了微管的细长形式,在其中可以观察到原丝偏斜和它的惯用性(图9F)。
注意:用于拉长微管的z偏移和角度偏移对应于基本的一个起始螺旋的参数,该基本起始螺旋连接微管晶格中的所有微管蛋白亚基。这些值还用于执行微管的3D重建,请参见Blestel等。(2009)以获得更详细的信息。

 

              

              图9.微管3D重建。A. 3D重建参数。B.进度条。C. 3D重建。D.从顶部观察到的3D重建。E.伸长率参数。F.微管的延长版。原型丝的右手斜度清晰可见。

 

检查工作目录,已创建了几个文件(按时间顺序列出):
一种。Calibration.cvs :pixelSize ,以Å为单位的像素大小。       

b。image_orig.tif :从原始图像提取的区域。      

C。image_corrected.tif :从原始图像提取的区域已针对对比度变化进行了校正。       

d。centres.txt:本地中心的数量及其x,y坐标。      

e。Straight_image.tif :拉直的图像。       

F。image_orig-straight_Centered.tif :以直线图像为中心。        

G。analyticsFFT.csv:pixelSize ,以Å为单位的像素大小;monomerRepeat ,单体重复沿原丝(以A); thetaSign ,theta的符号(1个正数,-1个负数)。      

H。已过滤image.tif :已过滤图像。      

一世。protofilament.csv:l(像素),莫尔周期(以像素为单位);pixelSize ,像素大小(以Å为单位);L(埃),莫尔周期(埃),Pf分离(埃);原丝分离(以Å为单位);θ,原丝偏斜角(°)。        

j。angle_distribution.csv:在堆栈中为每个角度(Y)分配的视图数,范围为0°至359°(X)。        

k。angles.txt:分配给堆栈图像的角度方向。      

l。elongation.csv:zshift ,微管蛋白单体相对于微管纵轴的Z轴上升;angleshift ,微管蛋白单体绕微管Z轴的角增量;nbProtofilaments ,原型线号;helicalRise ,微管蛋白亚单位沿相邻原丝的螺旋上升。        

米 stack_straight.tif :用于3D重建的图像堆栈。    

。stack_straight_3dreconstruction.tif:微管的3D重建。      

o。3dReconstruction_elongated.tif:3D重建的拉长版本。      

 

UCSF Chimera对3D重建的观察
将保存在工作目录中的“ stack_straight_3dreconstruction.tif”卷打开到UCSF Chimera中。
显示命令行:“菜单->收藏夹->命令行”。
打开相机查看器:“菜单- >工具->查看控件->相机”,然后选择“正交”。
打开“体积”查看器:“菜单->工具->体积数据->体积查看器”,然后在“功能”菜单中,选中“亮度和透明度”,“坐标”以及“阈值和颜色”。
调整“等级”来放大微管蛋白的密度(例如,为“等级= 300”)和设置“透明度”至0.50。
在命令行中,输入'turn x 90 1' 。
将体素大小设置为2.16Å,然后按居中。
选择“查看窗口”的“侧视图”选项卡,然后按“查看全部”。
打开微管蛋白图1tub:“菜单->文件->按ID提取...”,选中“ PDB”按钮,输入1tub并按“提取”。
在命令行中输入' move 62,-30,-30 mod#1; y 90 1 mod#1中心#1 '。从顶部观察微管蛋白图的正端(图10A)。将1tub模型的整体形状与微管图的整体形状进行比较,可以确认正端点指向重建的顶部。
在命令行中,输入“ move -45,-110,0 mod#0”。选择'Volume Viewer-> Tools-> Fit in Map',然后将'1tub(#1)放入地图'stack_straight_3dreconstruction.tif(#0)'中。检查微管(图的三维密度内的1tub模型的拟合小号10B- 10 F)。
注意事项:

一种。1tub模型的整体形状与3D重建之间的良好一致性包括结构图案的对应关系,例如与横向相互作用相对应的密度,H1-S2-环向内指向和C端α-螺旋向外指向(图10B)充分确定了从分析得出的参数已经确定。       

b。原始图像尚未针对对比度传递函数的效果进行校正。这可以在处理TubuleJ中的图像之前执行,以提高最终重建的质量。      

将会话保存在工作目录中为“ MTa.py”。
关闭会话并打开“ 3dReconstruction_elongated.tif”。
将步长设置为2,并将“水平”设置为300。在这种细长的微管3D重建版本中,可以清晰地看到原丝的右手倾斜(图10G)。
将会话另存为“ MTa_Elongated.py”。
注意:视频2中提供了使用UCSF Chimera的可视化过程。



图10.使用UCSF Chimera进行3D重建的可视化。A.将1D微管蛋白模型与3D重建进行比较。B.使1tub适合3D重建。加上端视图。指出了允许微管蛋白模型与3D重建良好匹配的结构特征。C.负端视图。D.内部视图。E.外观。F.侧视图。G. 3D重建的加长版。

 



视频2.使用UCSF Chimera进行3D重建的观察

 

致谢

 

这项工作得到了资助法新社国立德拉RECHERCHE(ANR-16 C11-0017-01)。我们感谢S. Blestel谁写的原始版本TubuleJ 。在Blestel等人中发表了TubuleJ中使用的微管中心的测定。(2009)。TubuleJ用于Estévez- Gallego等人。(2020)来分析GTP,GMPCPP和GDP-BEF的存在组装的微管结构3 - 。

 

利益争夺

 

TubuleJ已以代码IDID.FR.001.240023的形式存放到程序保护局(APP)。000.SP 2011.000.21000。

 

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Copyright Ku et al. This article is distributed under the terms of the Creative Commons Attribution License (CC BY 4.0).
引用: Readers should cite both the Bio-protocol article and the original research article where this protocol was used:
  1. Ku, S., Messaoudi, C., Guyomar, C., Kervrann, C. and Chrétien, D. (2020). Determination of Microtubule Lattice Parameters from Cryo-electron Microscope Images Using TubuleJ. Bio-protocol 10(21): e3814. DOI: 10.21769/BioProtoc.3814.
  2. Estévez-Gallego, J., Josa-Prado, F., Ku, S., Buey, R. M., Balaguer, F. A., Prota, A. E., Lucena-Agell, D., Kamma-Lorger, C., Yagi, T., Iwamoto, H., Duchesne, L., Barasoain, I., Steinmetz, M. O., Chrétien, D., Kamimura, S., Díaz, J. F. and Oliva, M. A. (2020). Structural model for differential cap maturation at growing microtubule ends. ELife 9: e50155.
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