Capturing Cytoskeleton-Based Agitation of the Mouse Oocyte Nucleus Across Spatial Scales

Summary

This protocol provides an experimental framework to document the physical impact of the cytoskeleton on nuclear shape and the internal membrane-less organelles in the mouse oocyte system. The framework can be adapted for use in other cell types and contexts.

Abstract

A major challenge in understanding the causes of female infertility is to elucidate mechanisms governing the development of female germ cells, named oocytes. Their development is marked by cell growth and subsequent divisions, two critical phases that prepare the oocyte for fusion with sperm to initiate embryogenesis. During growth, oocytes reorganize their cytoplasm to position the nucleus at the cell center, an event predictive of successful oocyte development in mice and humans and, thus, their embryogenic potential. In mouse oocytes, this cytoplasmic reorganization was shown to be driven by the cytoskeleton, the activity of which generates mechanical forces that agitate, reposition, and penetrate the nucleus. Consequently, this cytoplasmic-to-nucleoplasmic force transmission tunes the dynamics of nuclear RNA-processing organelles known as biomolecular condensates. This protocol provides an experimental framework to document, with high temporal resolution, the impact of the cytoskeleton on the nucleus across spatial scales in mouse oocytes. It details the imaging and image analysis steps and tools necessary to evaluate i) cytoskeletal activity in the oocyte cytoplasm, ii) cytoskeleton-based agitation of the oocyte nucleus, and iii) its effects on biomolecular condensate dynamics in the oocyte nucleoplasm. Beyond oocyte biology, the methods elaborated here can be adapted for use in somatic cells to similarly address cytoskeleton-based tuning of nuclear dynamics across scales.

Introduction

Nuclear positioning is essential for multiple cellular and developmental functions^1,2,3,4,5. Mammalian female germ cells named oocytes remodel their cytoplasm to position the nucleus at the cell center despite undergoing an asymmetric division in size, which relies on subsequent chromosome off-centering⁶ (Figure 1). This centering of the nucleus predicts successful oocyte development in mice and humans^{7, 8}, and thus, their embryogenic potential (Figure 1).

Cytoplasmic remodeling in mouse oocytes is driven primarily by the actomyosin cytoskeleton⁹ (Figure 2). Its activity generates mechanical forces that agitate, reposition, and penetrate the nucleus¹⁰ (Figure 2). Consequently, this cytoplasmic-to-nucleoplasmic force transmission tunes the dynamics of nuclear messenger RNA-processing organelles named nuclear speckles¹¹, one of several membrane-less organelles in the nucleus known as biomolecular condensates^{12,13,14,15,16} (Figure 2).

Live imaging has been decisive in deciphering the functional implications of nuclear agitation. Movies of nuclear migration over hours, as well as high-temporal resolution movies of the actin mesh and the bulk cytoplasm, largely contributed to the elaboration of a theoretical model for nuclear positioning, linking different timescales⁹. Also, high temporal resolution movies of the cytoplasm, nuclear outline and nuclear components such as chromatin and nuclear condensates, highlighted the role of cytoskeleton-based agitation of the nucleus on RNA-processing and gene expression in mouse oocytes, bridging different spatiotemporal scales within the cell^10,11. Altogether, such a scale-crossing approach based on live imaging provided the first rationale linking cytoskeletal agitation of the nucleus to the developmental success of oocytes.

The protocol provides the imaging and image analysis pipeline used to study the transmission of cytoplasmic forces (generated primarily by F-actin and partly by microtubules) to the nucleus and its internal components in mouse oocytes. The outcome of these experiments is to capture the continuum of forces across spatial scales, from the cytoskeleton in the cytoplasm to the nuclear interior via high temporal resolution movies as shown in two recent studies^10,11, that established the link between cytoplasmic active movements, fluctuations of the nuclear outline, as well as movement and surface fluctuations of a single type of nuclear biomolecular condensates: nuclear speckles. The same approach may be applied to other model systems where cytoplasmic forces are expected to change, such as in the context of malignant cancer cells¹⁷.

Protocol

All animal experiments were performed in accordance with the guidelines of the European Community and were approved by the French Ministry of Agriculture (authorization No. 75-1170) and by the Direction Générale de la Recherche et de l'Innovation (DGRI; GMO agreement number DUO-5291). Mice were housed in the animal facility on a 12 h light/dark cycle, with an ambient temperature of 22-24 °C and humidity of 40%-50%. Mice used here include female OF1 (Oncins France 1, 8 to 12 weeks old) and female C57BL/6 (10 to 14 weeks old).

1. Oocyte collection and preparation

1. Collect oocytes from 8 to 14-week old mice as described in¹⁸ and¹⁹.
   1. Briefly, first extract ovaries from mice as in¹⁸ into pre-warmed (37 °C) M2+Bovine Serum Albumin (BSA) medium supplemented with 1 µM Milrinone¹⁹, which prevents meiosis resumption in oocytes.
   2. Puncture ovarian follicles with surgical needles to release growing oocytes from antral follicles (end of oocyte growth²⁰).
   3. Collect oocytes of the size needed for experiments (growing and/or fully grown oocytes) with a micropipette specialized for oocyte collection, before washing and moving into dishes with fresh medium under mineral oil.
2. Mechanically dissociate oocytes from antral follicular cells by pipetting up-and-down and leave to stabilize for 1 h in the incubator at 37 °C prior to proceeding with subsequent experimental steps.
   ​NOTE: Oocytes are kept at 37 °C during all experimental steps. For this protocol, the largest oocytes, which are the fully-grown ones, were collected.

2. Oocyte microinjection

NOTE: To capture cytoskeleton-based activity in the cytoplasm, brightfield live-imaging is used. Microinjection of fluorescent markers is therefore not necessary, and the protocol can be resumed at step 3. To image the nuclear outline, Rango, a probe displaying YFP tag at its N-terminus and a CFP tag at its C-terminus^21,22, was used. When imaged in oocytes at 488 nm, it labels the whole nucleus, except for the nucleolus²³, and displays a very sharp nuclear outline. To visualize nuclear speckles, SRSF2-GFP (NM_011358), a marker of nuclear speckles¹¹, was used. The same medium is used for oocyte collection, microinjection, complementary RNA translation, and live cell imaging.

1. Linearize Rango plasmid with SfiI or SRSF2-GFP plasmid with AgeI restriction enzymes.
2. Synthetize capped complimentary RNAs (cRNA) with the appropriate in vitro transcription kit according to the promoter (T3 for Rango and T7 for SRSF2-GFP) and purify them using a column purification kit, as previously described²⁴.
   NOTE: Polyadenylate SRSF2-GFP RNA using a polyadenylation kit to increase cRNA stability. Two different promoters are used due to differences in the plasmid backbone.
3. Measure cRNA concentrations using a microvolume spectrophotometer.
4. Dilute Rango cRNA to 1000 ng/µL and SRSF2-GFP cRNA to 600 ng/µL in dH₂O.
5. Centrifuge cRNA aliquot at 4 °C for at least 60 min at 25,000 x g before microinjection.
6. Inject cRNAs coding for YFP-Rango or SRSF2-GFP as described in^11,25 into the cytoplasm of oocytes in 37 °C M2+ BSA+Milrinone medium using a microinjector.
7. Incubate oocytes for at least 2 h in culture medium at 37 °C for cRNA translation.
8. Deposit oocytes into small (5 µL) culture medium droplets on a 35 mm tissue culture dish with cover glass bottom covered with mineral oil. Place one oocyte per droplet to avoid photobleaching of neighboring oocytes.

3. Live cell imaging

NOTE: Live mouse oocytes were examined with an inverted confocal microscope equipped with a Plan- APO 40x/1.25 NA oil immersion objective, a motorized scanning deck, an incubation chamber (37 °C), a CCD camera coupled to a filter wheel, and a spinning-disk. High temporal resolution images are acquired using Metamorph (hereafter referred to as the imaging software) in stream acquisition mode.

1. Open the Acquire window of the imaging software.
2. Set exposure time to 500 ms, camera area on Full Chip and binning on 1.
3. In the Acquire tab, set illumination for the required channel. To image cytoplasmic activity, illuminate oocytes with transmitted light. To image the nucleus labelled with YFP-Rango or SRSF2-GFP, illuminate oocytes with an excitation wavelength of 491 nm.
4. For cytoplasmic stirring or YFP-Rango experiments, focus on the oocyte nucleolus which can be easily observed with transmitted light (Figure 3A). One single plane will be acquired. For nuclear speckle experiments, focus on SRSF2-GFP droplets (Figure 3C).
5. In the Special tab, set parameters in order to optimize acquisition speed as below.
   Camera shutter: Open for exposure
   Clear mode: CLEAR PRESEQUENCE
6. Open the Stream Acquisition window of the imaging software. Set the streaming parameters according to the experiment. For both studies^10,11, use the parameters described below.
   1. In the Acquire tab, set the following parameters.
      Acquisition mode: Stream to RAM
      Number of frames: 480 (can be decreased to 240 frames to decrease imaging time)
      Camera parameters: Acquire images at frame rate
      Number (Nb) of frames to skip: 0
   2. In the Digital Camera Controller Parameters tab, set the following parameters.
      Camera state: HALT
      Shutter mode: OPEN NEVER
      Clear mode: CLEAR PRESEQUENCE
      Nb of frames to average: 1
      NOTE 1: In Stream mode, once the exposure time is set, movie duration is determined by the number of frames. For example, 500 ms exposure time and 480 frames generate a movie of 4 min. A preview can be displayed during image acquisition.
7. Adjust a region of interest (ROI) around the object. Minimizing the area of the ROI reduces acquisition time.
8. Click on Acquire in the Stream Acquisition window to launch the movie.
9. Save movie as a .tif file at the end of acquisition.
   NOTE: To follow nuclear structures during high temporal resolution movies, nuclear probes (YFP-Rango and SRSF2-GFP) should have a high signal-to-noise ratio to facilitate segmentation of the objects during further steps of image analysis. Exogenous SRSF2-GFP expression profiles should be comparable to endogenous nuclear speckle immunostainings (Figure 3C-D). Changes in SRSF2-GFP expression profiles relative to endogenous staining may reflect high doses of cRNA injection and translation²⁶ (Figure 3C-D).

4. Image analysis: Cytoplasmic stirring

NOTE: The cytoplasmic stirring which reflects intensity of actin-based cytoskeletal activity in oocytes is determined by image correlation analyses using a software from a previous publication of the lab⁹ and available on²⁷. The software measures how much pixel intensities are conserved between consecutive images. The output is the loss of correlation between images in time, starting at 1 and decreasing exponentially with time, as in⁹.

1. Align raw time-lapse images (Δt=0.5 s) using the Fiji StackReg plugin (Plugins>StackReg). To install the plugin StackReg²⁸, enable the BIG-EPFL update site²⁹ to gain access to the plugin.
2. Calculate bright-field image correlations in 3 to 4 cytoplasmic regions of ~300 µm² following the steps below.
   1. Crop the regions and save them as separate movie files. Open the Terminal window.
   2. Type oocyte, press the Space Bar and then press Enter. A window called Signal and Slot appears. Choose the cropped movie files that will be analyzed.
      NOTE: Several movies can be selected at the same time.
3. The application returns files in the same folder as the movies. Three different files with .csv, .eps and .xls extensions are generated. The .xls file contains the data to draw the correlation plots for one region. Average correlation values from different regions within a cell.
4. For visual clarity purposes, transform final correlation values by subtracting the value of each timepoint from 1 to obtain an inverted exponential-like curve as in ¹¹.

5. Image analysis: Cytoplasmic vector maps

NOTE: Mouse oocyte cytoplasmic vector maps were generated by the Spatiotemporal Image Correlation Spectroscopy (STICS) plugin³⁰ previously implemented for detecting cytoplasmic flows in mouse oocytes³¹ on Fiji ³² and available on ³³. The maps show cytoplasmic flow velocity magnitude and direction, as in⁹ and¹¹.

1. Convert bright-field time-lapse images (Δt=0.5 s) to 32-bit format.
2. Realign images with the Fiji StackReg plugin in Plugins > StackReg and choose Rigid Body transformation.
3. With the plugin stack subtract moving average jru v2(in Detrend tools of the STICS plugins suite), get rid of stationary structures in the movie by subtracting the time-averaged image of the movie. Check boxes Subtract Static Average and Output Sub Stack, select Maintain Spatial Average and set period on 5.
4. Draw a ROI around the oocyte, excluding the cortex to avoid border effects of the plugin.
5. Launch the STICS map jru V2 plugin (in ICS tools), with subregion size of 32 pixels, step size of 16 pixels, STICS temporal shift of 3, X and Y offsets of 0, velocity multiplier of 8, magnitude threshold of 0 and check boxes of Normalize Vector Length, Center Vectors, Output Velocities and Use Movie Mask.
   ​NOTE: The plugin generates a map of the oocyte in .tif format, displaying cytoplasmic flows as vectors with colors indicating flow amplitudes, as in⁹ and¹¹, and an excel file with measured flow velocities.

6. Image analysis: Nuclear outline fluctuations

NOTE: Nuclear outline fluctuations which reflect nuclear membrane agitation can be determined from movies of nuclei labelled with YFP-Rango (Figure 4A,C). Image analysis for nuclear outline fluctuations requires Fiji and the installation of plugins StackReg (enable the BIG-EPFL update site²⁹ to gain access to the StackReg plugin), PureDenoise³⁴ and Ovocyte_nucleus. The StackReg plugin performs images registration to correct for possible global motion. The PureDenoise plugin removes noise of multidimensional images corrupted by mixed Poisson-Gaussian noise and smoothens the nuclear outline. The Ovocyte_nucleus plugin thresholds the signal and fills the hole corresponding to the nucleolus in order to create a binary nucleus mask, realign it with StackRreg and calculate the distance r from the centroid of the nucleus mask to the circumference of the mask for all θ angles (θ° from 0° to 360° by 1° increment), as in Figure 4. All codes for these plugins can be found at ³⁵.

1. On Fiji, in the Plugins > CIRB > Verlhac menu, select Ovocyte Nucleus Shape.
2. In the dialog box, perform the following selection.
   1. Select the folder containing the movies to analyze.
   2. Select the θ angle (a value from 1° to 360° can be chosen and a value of 1° was used for optimal outline resolution), the margins for cropping (5 µm is recommended in order to keep the whole nucleus).
   3. Select the XY calibration and the time interval. Click on OK.
      NOTE: Results are provided as .xls files in an out folder in the folder containing the original movies. This file displays all measured radii r for each time t and each angle θ. An example of output file is provided in Supplementary Table 1. The out folder also contains a movie of the nucleus mask.
3. Using a spreadsheet, calculate the mean radius R over all the time points t for each defined θ angle. This allows to plot the mean shape over time (Figure 4B). See example in Supplementary Table 2.
4. For each t and θ subtract the mean radius R over time from the radius r. The variance (r-R)² is a measure of nuclear envelope fluctuations.
5. Calculate the mean of the fluctuations for all time points t and all angles θ for each nucleus and eventually for all nuclei from one condition.
   NOTE: When the shape of nuclei is significantly altered such as in the case of a disrupted cytoskeleton, nuclei labelled with YFP-Rango are rotated on Fiji to orient the smooth part up and the invagination down, prior to proceeding with analysis of nuclear outline fluctuations, as in¹⁰.

7. Image analysis: Nuclear speckle movements (diffusive dynamics)

NOTE: Nuclear speckle movement analysis allows to deduce the type of dynamics (driven, diffusive, or confined) of those organelles from their tracks.

1. Select stream-mode images of oocytes expressing SRSF2-GFP droplets that primarily move in the X-Y axis.
2. Correct for bleaching of time-lapse images of oocytes expressing SRSF2- GFP using the histogram matching method in Fiji (Image > Adjust > Bleach Correction).
3. Realign images with the Fiji StackReg plugin.
4. Track SRSF2-GFP droplet centers using the Fiji Manual Tracking plugin (Plugins > Tracking > Manual Tracking). Press Add Track to start tracking and press End Track when finished. Do not activate centering correction.
5. Copy tracks to a spreadsheet file to proceed with temporal Mean Square Displacements (MSD) calculations as in ¹¹, and calculate temporal MSDs from each 20 s droplet trajectories.
6. Fit curves (msd(t) = beta x t^α) with the Nelder-Mead method using R software to estimate the diffusion exponent alpha (α).
7. Measure the effective diffusion coefficient to be able to compare the different conditions since the diffusion is expected to be anomalous (α< 1).
8. Calculate the effective diffusion coefficient D_eff from a linear fit (alpha=1) on the 40 first points (20 s) of the temporal MSD curve and normalize by droplet size (D_eff in µm²/s x 3/2 πr in µm).

8. Image analysis: Nuclear speckle surface fluctuations

NOTE: Nuclear speckle contour evolution in time, a read-out of active force transmission onto these organelles, was measured with a custom-built plugin Radioak³⁶ for use in Fiji and available on³⁷. The plugin extracts the values of radii of a given selection for all angles around the selection center. Shape variation over time was measured by comparing the value of the radius relative to its average value for each angle. The plugin allows to quantify the shape fluctuations and offers an option to visualize these dynamics. To install it, download the Radioak_.jar file and place it in the plugins folder of Fiji. Restart Fiji. This plugin is an updated version of the plugin used to analyse nuclear outline fluctuations above and implement a comparable pipeline.

1. In stream movies of SRSF2-GFP droplets, select larger droplets of comparable sizes (radius ~2.5 µm).
   NOTE: If droplets are too small, insufficient resolution will lead to aberrant surface fluctuation measurements.
2. Crop time-lapse images of droplets spanning 15 s (Δt= 0.5 s) by drawing a rectangle around the droplet and select Image > Crop (Figure 5).
3. Realign images with the Fiji StackReg plugin in Plugins > StackReg and choose Rigid Body transformation.
4. Smoothen image to remove noise around droplet using the Fiji Smoothen option under Process.
5. Create binary mask of droplet using Convert to Mask option in Fiji under Process > Binary. Use Default method and Dark for background (Figure 5).
6. Analyze the generated binary droplet mask using the Analyze Particles option in Fiji under Analyze, select Clear Results and Add to Manager options and save the region of interests (ROIs) in the RoiManager (More > Save) in zip format to be read by Radioak. The ROIs must be saved in a folder called contours in the same folder of the movies, in files called imagename_UnetCortex.zip for each movie to be found by Radioak.
7. In the Fiji Plugins > CIRB > Radioak menu, select either Get Radii to process one movie only or Do One Folder to analyze all movies of the same folder.
   NOTE: A window pops up to select the angle number and scale. Radioak was launched with 1° angle increments from 0° to 360° (input of 360) and the radii values were extracted.
8. Select the movie or the folder containing the movies to analyze. Results are provided as .xls files (one for each movie) in a radioakres directory in the folder containing the original movies. Each file displays all measured radii r (in µm if the scale parameter was filled) for each time t (in slice) and each angle (in radians; Figure 5; see example of .xls output in Supplementary Table 3).
9. In the spreadsheet, calculate the mean radius R over all the time points t for each defined angle (see example in Supplementary Table 4). This allows to plot the mean shape over time.
10. Plot the variance (r-R)² in µm² which corresponds to the measure of droplet surface fluctuations.

Representative Results

Image panels in Figure 3 show examples of a typical fully grown oocyte (Figure 3A), the nucleoplasm in a fully grown oocyte expressing YFP-Rango (Figure 3B), the nucleoplasm in a fully grown oocyte expressing a correct (left panel; Figure 3C) or an excessive (right panel; Figure 3C) dose of SRSF2-GFP cRNA, and an immunostaining of nuclear speckles in a fully grown oocyte using the SC35 antibody (Figure 3D). The correct dose of SRSF2-GFP cRNA to microinject was defined based on visual comparisons between expression profiles of SRSF2-GFP with endogenous profiles of nuclear speckles.

Cytoplasmic stirring forces in oocytes, as shown by previous work from the lab using STICS vector maps and image correlation analysis (see⁹ and¹¹), can be decreased by cytoskeletal perturbations, both genetic (e.g., FMN2-mutant mouse) and chemical (e.g., Cytochalasin D). STICS maps of control oocytes display numerous vectors, with colors indicating high flow velocities, whereas maps of oocytes with disrupted cytoskeletal forces display less vectors, with colors indicating low flow velocities. Similarly, image correlation is lost very fast in control oocytes compared to oocytes with disrupted cytoskeletal forces. This is observable on correlation curves, with a faster decrease of the curve for control oocytes compared to oocytes with disrupted cytoskeletal forces⁹ or a faster increase when the curve is inverted¹¹.

Cytoskeletal forces agitate the nucleus and its interior organelles, in particular nuclear condensates like nuclear speckles^10,11. In Figure 4A, the nucleus of control oocytes is subjected to important peripheral fluctuations, which is visible using the nuclear probe YFP-Rango. Nucleus shape in oocytes with disrupted cytoskeletal forces is stable during time (Figure 4C). Analysis of nuclear outline fluctuations is key to precisely quantify the agitation. By determining the variance of the distance from the nucleus centroid to its periphery, (r-R)² (Figure 4B), fluctuations could be quantified, showing that nuclear agitation is 6 times higher in control oocytes than in oocytes with disrupted cytoskeletal forces¹⁰. In Figure 5A-B, nuclear speckles (SRSF2-GFP⁺ droplets) are shown in control and disrupted contexts of cytoplasmic forces at high temporal resolution. In controls, the droplet surface fluctuates significantly more than droplet surfaces in oocytes with disrupted cytoplasmic forces, which can be visualized and quantified using the Radioak³² plugin. Visually, green and red colors (Radioak output seen on bottom images of Figure 5A-B) indicate angles where the plugin detected surface changes between consecutive images and white indicates a lack of surface changes.

Figure 1: Illustration of late mouse oogenesis and early embryogenesis. Illustration of nucleus centering that occurs in late oocyte growth, chromosome off centering that occurs during oocyte division, and early steps (1-cell and 2-cell stages) of embryogenesis. The female genomes (oocyte nucleus and female pronucleus) are in pink, the male pronucleus is in blue. The embryo nuclei (after fusion of parental genomes) are purple. Please click here to view a larger version of this figure.

Figure 2: Illustration of cytoplasmic and nuclear remodeling across scales in growing mouse oocytes. This figure summarizes key findings from^9,10,11. Illustration of actomyosin-based remodeling of the cytoplasm, nuclear agitation, and functional nuclear biomolecular condensate remodeling across spatiotemporal scales. The scale-crossing remodeling of nuclear speckles enhances biomolecular reactions associated with their function (i.e., splicing of pre-mRNA). Note that this protocol allows the assessment of nuclear agitation only across spatial scales but not temporal ones, since all imaging is done with the same temporal resolution of 0.5 s between image frames. Please click here to view a larger version of this figure.

Figure 3: Sample images of the fully grown oocyte and the nucleoplasm. (A) Bright-field image of a fully grown oocyte showing chromatin (cyan) that encircles the nucleolus. A dotted white circle outlines the nucleus. (B) Live oocyte nucleus expressing YFP-Rango; note the absence of fluorescence in the nucleolus. (C) Example of live oocyte nucleus expressing SRSF2-GFP after microinjection of correct doses of cRNA (left panel) or high doses of cRNA (right panel); note the condensed (droplet) and dissolved phases on the left and their absence in the condition on the right. (D) Nuclear speckle immunostaining in a fixed oocyte; note the endogenous expression profile that is comparable to the one in C (left panel). Scale bars = 5 µm. Please click here to view a larger version of this figure.

Figure 4: Plugin outputs of control and disrupted nuclear outline fluctuations. (A) Time-lapse of a control oocyte nucleus expressing YFP-Rango (top) and its corresponding binary mask generated by the Ovocyte_nucleus plugin (bottom). (B) Principle of nuclear outline fluctuations measurements over time and in a given direction. Directions are defined by a revolving angle θ of 1° increment from 0° to 360°. Two representative shapes at t=0 s (yellow) and t=135 s (purple) are represented. The blue shape corresponds to the mean shape over time. (C) Nuclear outline fluctuations of a nucleus in an oocyte with decreased cytoskeletal forces due to disruption of both F-actin (FMN2-mutant mouse) and microtubules (Nocodazole treatment; as in¹⁰). Scale bars = 5 µm. Please click here to view a larger version of this figure.

Figure 5: Plugin outputs of control and disrupted droplet surface fluctuations. (A) Crop of a control SRSF2-GFP nuclear droplet imaged at 500 ms per frame and shown in Ice Look Up Table (LUT) (top); binary mask of the same droplet generated by Fiji (center); and Radioak plugin outputs after analysis of surface fluctuations of the droplet (bottom), with green and red indicating angles where the plugin detected surface changes between consecutive images and white indicating a lack of surface changes. (B) Surface fluctuations of a nuclear droplet in oocytes with decreased cytoskeletal forces due to disruption of both F-actin and microtubules (as in¹¹). Scale bars = 5 µm. Please click here to view a larger version of this figure.

Supplementary Table 1: Example of Ovocyte_nucleus plugin analysis output. The same nucleus analyzed as the one shown in Figure 4A. Theta (θ) is the angle in degrees and t1 to t600 correspond to the frame number, which can be converted in time. The radii are in µm. Please click here to download this File.

Supplementary Table 2: Sample spreadsheet used to calculate nuclear outline fluctuations. The same nucleus analyzed as the one shown in Figure 4A. Theta (θ) is the angle in degrees and t1 to t600 correspond to the frame number, which can be converted in time. Tab Raw and average: The radii are in µm. Tab r-R: The r-R distances are in µm. Table (r-R)²: The fluctuation values are in µm². Tabs x and y correspond to the Cartesian coordinates of the radii from the Raw and average tab. They allow to draw the mean shape of the nucleus over time in the mean shape tab. Please click here to download this File.

Supplementary Table 3: Example of Radioak plugin analysis output. The same droplet analyzed as the one shown in Figure 5A. The measured radii at distinct timepoints and angles are shown. The radii are in µm. Please click here to download this File.

Supplementary Table 4: Sample spreadsheet used to calculate nuclear droplet surface fluctuations. The same droplet analyzed as the one shown in Figure 5A. Theta (θ) is the angle in degrees and t1 to t600 correspond to the frame number, which can be converted in time. Tab Raw and average: The radii are in µm. Tab r-R: The r-R distances are in µm. Table (r-R)²: The fluctuation values are in µm². Tabs x and y correspond to the Cartesian coordinates of the radii from the Raw and average tab. Please click here to download this File.

Discussion

Key steps in this protocol include proper microinjection of oocytes without affecting their survival or normal function^9,10,11, as well as microinjecting predefined amounts of cRNA that would allow correct visualization of relevant structures, like nuclear speckles.

Establishing the link between cytoplasmic and (intra)-nuclear dynamics is essential when studying how the cytoskeleton agitates the nucleus or its interior. This protocol, with slight modifications, allows that by correlating cytoplasmic stirring intensities to nuclear YFP-Rango or SRSF2-GFP droplet dynamics (as in¹¹). To proceed, oocytes should first be filmed for 120 s in bright-field mode to capture cytoplasmic stirring, prior to being immediately filmed for 120 s with a 491 nm laser to capture nuclear outline or droplet dynamics. In case of nuclear SRSF2-GFP droplets, the correlation can simply be assessed by comparing their effective diffusion coefficients (see step 7 in this protocol) to the inverted maximal intensity values of cytoplasmic stirring obtained using image correlation analyses (see step 4 in this protocol). Another important point is the size of condensates chosen for analyses of droplet surface fluctuations. Droplets of a similar diameter should be selected for comparative analyses to prevent bias, as size modulates intensity of surface fluctuations.

There are some limitations for this protocol. Analyses of nuclear outline fluctuations rely on full intra-nuclear staining, such as YFP-Rango or NLS-GFP. For analyses on nuclear speckles, microinjection of excessive amounts of SRSF2-GFP cRNA can lead to apparent alterations in phase separating properties of this condensate marker (Figure 3C), as previously reviewed by others²⁶. Verifying that exogenous protein expression profiles are comparable to the endogenous ones is therefore critical. Moreover, relatively small droplets (<2 µm radius) should be excluded from surface fluctuation analysis pipelines due to limitations of spatial resolution with the tools defined here. This resolution issue can usually be solved by the use of more resolutive microscopes which, for instance, could be necessary to probe surface fluctuations of smaller condensates in the oocyte nucleus or in the significantly smaller nucleus of somatic cells.

Overall, this protocol allows the capture of actin and microtubule cytoskeleton-based agitation of the mouse oocyte nucleus across scales. Specifically, it allows the documentation of cytoskeleton-based mobilization of the cytoplasm, nuclear outline fluctuations, together with liquid-like nuclear speckle displacements and surface fluctuations. Although some studies in other cell types address some of these matters^38,39,40 via distinct protocols of varying complexity at individual spatial scales, this simple protocol provides the tools necessary to address the mentioned cellular dynamics across multiple scales in a single work pipeline for the first time. Moreover, data generated from this approach, when complemented with biophysical modeling as in^10,11, enable a minimally invasive evaluation of: i) changes in nuclear mechanics¹⁰; ii) the transmission of cytoskeleton-based active forces in the cytoplasm to condensates in the nucleus¹¹; and iii) the dissipation of this active energy across different cellular compartments^10,11. Importantly, this protocol is versatile, as it may be adapted not only to other nuclear condensates like the nucleolus²³, but also to other cell types like cancer cells, where changes in both cytoskeletal and nuclear condensate behaviors were documented^17,41.

Materials

Name	Company	Catalog Number	Comments
Bovine Serum Albumin (BSA)	Sigma	A3311
CSU-X1-M1 spinning disk	Yokogawa
DMI6000B microscope	Leica
Femtojet microinjector	Eppendorf
Fiji
Filter wheel	Sutter Instruments Roper Scientific
Fluorodish	World Precision Instruments	FD35-100
Metamorph software	Universal Imaging,		version 7.7.9.0
Mineral oil	Sigma Aldrich	M8410-1L
NanoDrop 2000	Thermo Scientific
OF1 and C57BL/6 mice	Charles River Laboratories
Poly(A) Tailing kit	Thermo Fisher	AM1350
Retiga 3 CCD camera	QImaging
RNAeasy kit	Qiagen	74104
SC35 antibody	Abcam	ab11826	Nuclear speckle antibody; mouse IgG1 anti-SRSF2/SC35 (1:400)
SRSF2-GFP plasmid	OriGene Technologies	MG202528	NM_011358
Stripper Micropipette	XLAB Solutions		specialized for oocyte collection
T3 mMessage mMachine	Thermo Fisher	AM1384
T7 mMessage mMachine	Thermo Fisher	AM13344
Thermostatic chamber	Life Imaging Service
Windows Excel	Windows