A Semi-high-throughput Imaging Method and Data Visualization Toolkit to Analyze C. elegans Embryonic Development

Summary

This work describes a semi-high-throughput protocol that allows simultaneous 3D time-lapse imaging of embryogenesis in 80–100 C. elegans embryos in a single overnight run. Additionally, image processing and visualization tools are included to streamline data analysis. The combination of these methods with custom reporter strains enables detailed monitoring of embryogenesis.

Abstract

C. elegans is the premier system for the systematic analysis of cell fate specification and morphogenetic events during embryonic development. One challenge is that embryogenesis dynamically unfolds over a period of about 13 h; this half day-long timescale has constrained the scope of experiments by limiting the number of embryos that can be imaged. Here, we describe a semi-high-throughput protocol that allows for the simultaneous 3D time-lapse imaging of development in 80–100 embryos at moderate time resolution, from up to 14 different conditions, in a single overnight run. The protocol is straightforward and can be implemented by any laboratory with access to a microscope with point visiting capacity. The utility of this protocol is demonstrated by using it to image two custom-built strains expressing fluorescent markers optimized to visualize key aspects of germ-layer specification and morphogenesis. To analyze the data, a custom program that crops individual embryos out of a broader field of view in all channels, z-steps, and timepoints and saves the sequences for each embryo into a separate tiff stack was built. The program, which includes a user-friendly graphical user interface (GUI), streamlines data processing by isolating, pre-processing, and uniformly orienting individual embryos in preparation for visualization or automated analysis. Also supplied is an ImageJ macro that compiles individual embryo data into a multi-panel file that displays maximum intensity fluorescence projection and brightfield images for each embryo at each time point. The protocols and tools described herein were validated by using them to characterize embryonic development following knock-down of 40 previously described developmental genes; this analysis visualized previously annotated developmental phenotypes and revealed new ones. In summary, this work details a semi-high-throughput imaging method coupled with a cropping program and ImageJ visualization tool that, when combined with strains expressing informative fluorescent markers, greatly accelerates experiments to analyze embryonic development.

Introduction

The C. elegans embryo is an important model system for mechanistic cell biology and analysis of cell fate specification and morphogenetic events driving embryonic development^{1,2,3,4,5,6,7,8,9}. To date, much of the characterization of both cellular-level events and cell fate specification in the embryo has been achieved using relatively high temporal resolution one-at-a-time imaging experiments (i.e., acquisition every 10–100 s) of embryos expressing fluorescent markers. Although well suited for events on the order of seconds to tens of minutes, this approach becomes technically limiting for the characterization of longer processes, on the order of hours to days. Embryonic development from first cleavage to the end of elongation takes about 10 h. At this time-scale, semi-high-throughput methods that would allow for simultaneous lower time resolution imaging (i.e., acquisition at 5–20 min time intervals) of larger cohorts of embryos, from different conditions, would open up a new range of experiments; for example, enabling systematic large-scale screening efforts and the analysis of sufficient numbers of embryos for comparisons of the consequences of molecular perturbations.

Here, we describe a semi-high-throughput method for monitoring C. elegans embryogenesis that enables the simultaneous 3D time-lapse imaging of development in 80–100 embryos, from up to 14 different conditions, in a single overnight run. The protocol is straightforward to implement and can be carried out by any laboratory with access to a microscope with point visiting capabilities. The major steps in this protocol are outlined in Figure 1. In brief, embryos are dissected from gravid adults expressing fluorescent markers of interest and transfer young embryos (2–8 cell stage) to wells of a 384-well plate for imaging. In this format, the relatively small well size funnels embryos into a narrow area, which facilitates the identification of fields containing multiple embryos for time-lapse imaging. To maintain roughly synchronous development across the cohort of embryos, dissections are performed in chilled media and the plate is held on ice, which prevents significant development during the hour-long dissection time window. The plate is transferred to the microscope and embryos are filmed in a temperature-controlled room overnight, at 20 min time intervals, using a 60x oil immersion 1.35 NA lens, to collect the full z-range in 2 µm steps. Fifty fields, each containing between 1–5 embryos, are imaged in a single overnight run. Depending on the desired experiment, the time resolution could be increased (for example, imaging at 5–10 min intervals) by proportionally decreasing the number of imaged fields.

With this protocol, even a single overnight run generates a significant amount of data (80–100 embryos spread out over 50 fields) and larger experiments can quickly become unmanageable with respect to data analysis. To facilitate processing, visualization and streamline analysis of this data, a program was built to crop out and orient embryos and perform pre-processing steps (optional), and an ImageJ macro that compiles the data to simplify viewing. These programs can be used to process images collected using conventional approaches, as they are independent of the imaging method, requiring only a single brightfield plane. The first program takes in a 4D field containing multiple embryos (GUI option or source code embryoCrop.py) or multiple 4D fields containing multiple embryos (screenCrop.py), tightly crops embryos and orients them in an anterior-posterior configuration. These programs also give users the option to perform background subtraction, drift correction, and attenuation correction. The resulting files are uniformly pre-processed, tightly cropped tiff stacks for each embryo that are amendable to automated image analysis. To make it simpler to view all embryos for each condition, an ImageJ macro (OpenandCombine_embsV2.ijm) was written, which assembles all embryos from a given condition into a single tiff stack and arrays brightfield images and maximum intensity projection color (RGB) overlays, side-by-side, for each embryo. The methods were validated by using them to characterize embryonic development after knock-down of 40 previously-described developmental genes in a pair of custom-built strains expressing fluorescent markers optimized to visualize key aspects of germ-layer specification and morphogenesis^10,11. Together, the semi-high throughput embryo imaging protocol and image processing tools will enable higher sample number experiments and large-scale screening efforts aimed at understanding developmental processes. In addition, these strains will also provide an efficient means for examining the effects of molecular perturbations on embryogenesis. 

Protocol

1. Preparing C. elegans Embryos for Semi-high-throughput Imaging

NOTE: The goal of this portion of the protocol is to load a population of semi-synchronized (2 to 8-cell stage) C. elegans embryos, dissected from suitable marker strains (Figure 2), into a glass-bottom 384-well plate for imaging. Other plate formats could also work, but the 384 well plates are preferred because the small well size constrains the spread of embryos to a relatively small area, which facilitates the identification of fields containing multiple embryos for time-lapse imaging. Roughly synchronizing the embryos ensures that the full course of development is captured for each of the embryos in a field.

1. Prepare 5–10 mL of 0.1 mg/mL solution of tetramisole hydrochloride (TMHC) anesthetic dissolved in ice cold M9 medium (0.45 M Na₂HPO₄∙7H₂O, 0.11 M KH₂PO₄, 0.04 M NaCl, 0.09 M NH₄Cl) to use during dissection and imaging. This media includes an anesthetic to ensure that moving hatched larva do not disrupt imaging of embryos at earlier developmental stages.
   NOTE: If using the cropping and visualization tools to analyze data acquired using standard agarose pad mounting methods, skip ahead to section 3 below.
2. Aliquot 70 µL of the prepared solution into individual wells of a glass-bottom 384-well plate with one well for each condition; avoid the outer two rows of the plate to prevent edge effects.
   NOTE: It is useful to mask surrounding wells using adhesive PCR plate foil (see example in Figure 1D) this preserves adjacent wells for future experiments and makes it easier to locate appropriate wells under the dissection microscope. Once the solution is aliquoted, keep the plate and remaining solution on ice throughout dissection.
3. Generate mouth pipets for transferring embryos from the depression slide (where the gravid hermaphrodites are dissected) to the wells. Pull capillary pipets (25 µL calibrated pipets) over a flame and break to generate a fine tapered end (Figure 1D). One pipet is needed per condition to prevent cross-contamination; discard pipet after use.
4. Use fine tweezers to transfer ~10 gravid adults under a dissection scope into 150 µL of the ice cold TMHC solution aliquoted onto a depression slide for each condition. Using the tweezers and a scalpel, dissect the worms to release the embryos.
5. Load a pulled capillary pipet into the aspirator attachment included with the pipets, and mouth pipet to transfer all of the 2 to 8-cell-stage embryos into an individual well of the prepared plate (Figure 1D). Avoid transferring late stage embryos and dissection debris. Examine under a dissection scope and if aggregates of embryos are present, mouth pipet up and down or tap clumps of embryos with pipet tip to disperse.
   NOTE: To prevent cross-contamination, clean dissection equipment and use a fresh mouth pipet while moving between conditions. Store plate on ice between dissections.
6. Once worms from all conditions have been dissected and embryos placed in their appropriate well, spin the 384-well plate for 1 min at 600 x g to settle the embryos.
7. Wipe the bottom of the plate with an ethanol-soaked wipe to remove any residue and place the plate on a confocal microscope equipped with a plate holder in a temperature-controlled environment.
   NOTE: The steps that follow detail this method using the lab setup; please modify acquisition conditions to suit experimental needs and equipment. Here, a confocal scanner box equipped with a microlens-enhanced dual Nipkow spinning disk, a 512 x 512 EM-CCD camera, a high-precision auto-XY-Stage (designated resolution 0.1 µm) and motorized z-axis control (designated resolution 0.1 µm) is used. This system is kept in a 16 °C room, which maintains the microscope temperature between 21 and 23 °C during overnight imaging.
8. To identify fields with suitable embryos, perform a pre-scan of each well using a 10x 0.4 NA objective and suitable imaging software. The most optimal fields will contain more than one early stage embryo that is in the same focal plane as other embryos and ideally will have minimal contact between adjacent embryos. Mark positions of suitable regions.
9. To select imaging fields, switch to the 60x objective and adjust the focal plane at each point visit to appropriately section the embryos. 1–4 fields per well are imaged, for a total of 50 fields across 14 wells, and each field can contain between one and five embryos. Overall, 4 to 15 embryos are selected from each condition for high-resolution imaging.
   NOTE: A key variable at this step is the use of sufficient oil; place oil on the objective, visiting points in each well to spread the oil around the surface of all of the wells and then apply an additional drop of oil to the objective prior to selection of fields.
10. Image the selected fields using a 60x 1.35 NA objective to acquire 18 z sections at 2 µm intervals every 20 min for 10 h. The imaging conditions using the germ-layer and morphogenesis reporter strains are as follows: brightfield, 90% power, 25 ms, 20%  gain; 488 nm, 100% power, 200 ms, 60% gain; 568 nm, 45% power, 150 ms, 60% gain.
11. After imaging is complete, assess embryonic lethality by performing a low magnification (10x 0.4 NA objective) whole well brightfield scan ~20–24 h following the start of overnight imaging.

2. Embryonic Lethality Scoring

1. Using the post-run 10x scanned fields, assess embryonic lethality and larval defects by counting hatched worms and unhatched embryos for each well.
2. Score unhatched embryos as embryonic lethal. Exclude arrested one- to four-cell-stage embryos from lethality count, since young dissected embryos sometimes fail to complete eggshell formation (if meiosis II is not yet complete) and permeability defects can lead to osmotic complications during the first two divisions.
3. Score partially hatched or fully hatched worms with body morphology or behavioral defects, such as dumpy or paralyzed, as 'abnormal larva'.

3. Automated Cropping (Figure 3A)

NOTE: The software is housed in two locations: (1) Zenodo houses a user-friendly version of the software¹² that does not require any programming expertise. (2) Github contains the source code for our embryoCropUI.py and screenCrop.py software¹³, which require proficiency with Python. Detailed instructions for downloading and operating both versions of the program can be found below.

1. Automated cropping using embryoCropUI executable version (user friendly version)
   1. To use the embryoCropUI program, first download the program from Zenodo (https://zenodo.org/record/3235681#.XPAnn4hKg2w)¹².
      1. Download the MacOS or Windows format version of the program (note that the MacOS version requires MacOS X10.11 or higher).
      2. Download the instructions file (GUI_Instructions_zenodo_repoV2.docx), which provides step by step instruction for testing and using the embryoCropUI program.
      3. Download the test_files.zip to test if the program is properly functioning on the platform (see instructions).
   2. Once downloaded, unzip and navigate to find the embryoCropUI executable (…\embryoCropUI\_WINDOWS\embryoCropUI\embryoCropUI.exe) or (…\embryoCropUI\_MacOS\embryoCropUI\embryoCropUI.exe). Double click to launch (or chose 'open with' terminal) and run the embryoCropUI executable.
   3. The GUI executable crops one 4D field of view at a time. In the upper left-hand corner, select the open button to load the specific field to crop (multi-tiff). If cropping a tiff series, with multiple dimensions (i.e., z, time, channel), load only the first image in the series within the folder (one tiff series per folder).
   4. Once images have been loaded, specify the following information: number of z- slices, (Z), number of time points (T), number of channels (C), the channel that corresponds to DIC or brightfield (first=1, second=2, etc.).
   5. Select additional processing to run on the images. The program offers Drift Correction, Background Subtraction, and Attenuation Correction.
   6. Specify parameters for Background Subtraction and Attenuation Correction to guide processing efforts in the GUI prompt. For Background Subtract, define the largest feature size to reflect the size of meaningful signal; this feature size should not be considered as background and must be an odd number value. Input a value from 0-1 for Attenuation Correction. The Attenuation Correction value reflects the percent of original intensity that remains at the furthest depth of the object being imaged.
      NOTE: Background Subtraction and Attenuation Correction must be run together.
   7. Specify the image collection order (i.e., channel-z-time (czt), or z-channel-time (zct)).
   8. Specify the microns per pixel for the images based on the camera being used.
      NOTE: Poor image cropping will occur if pixel size is not properly defined.
   9. Select Run at the bottom left corner. A new subfolder labeled “crop” will be created in in the same path as the uncropped folder; cropped versions will be saved in this location. Depending on file size, cropping should complete within seconds to minutes.
2. Automated cropping using screenCrop.py (batch version alternative to embryoCrop GUI described above; Python savvy users only)^10,13
   1. To use screenCrop.py, the Python software version for cropping of larger data sets in a batch format, clone or download the source code from Github (github.com/renatkh/embryo_crop.git).
   2. Read the instructions for configuring a proper virtual environment and follow the file-naming system described; both of which are detailed in the README file in the Github repository: https://github.com/renatkh/embryo_crop/blob/master/README.md.
   3. Once environmental variables and naming conventions have been properly established, open parameters.py and screenCrop.py in an editor of choice.
   4. To modify adjustable parameters without touching the source code, edit the parameters.py file.
      NOTE: it is also possible to directly change parameters within the header of screenCrop.py.
      1. If using the parameters.py configuration file, change the use_configure setting to True. If using direct editing within screenCrop.py, leave the use_configure setting at False.
      2. Locate the following information within the parameters.py file and make modifications to suit desired imaging parameters and file structure:
         1. loadFolder (line 9): Change to the drive on which the files are stored (e.g., Z:/, D://, etc.)
         2. date (line 7): Change to the folder containing files for the imaging session. This is referred to as 'Experiment Folder Name' in the CSV tracking file (see instructions).
         3. trackingFile (line 11): Change to the path to the CSV file in which experiment information is stored.
         4. z (line 13): Set as the number of z planes.
         5. nT (line14): Set as the number of timepoints.
         6. nWells (line 19): Set as the number of wells used.
         7. pointVisits (line 20): Set as the maximum number of point visits (per well).
         8. In line 10 find the location currently occupied by 'CV1000/' and input the outer folder used in the file path. To avoid issues, use the following convention: 'XXXXXXX/'.
         9. In Line 12, input a valid file path for storing aspect ratio data for cropped data.
         10. In Lines 15, 16, 17, and 18 input True/False for whether the images go through the following processing:
             1. Input True or False for drift correction on Line 15.
             2. Input True or False for background subtract on Line 16. Feature size must be empirically determined for different marker strains and pixel sizes. In the configuration here, feature size was defined as 41 for the Germ-Layer strain and 201 for the Morphogenesis strain. Background subtract must be done in conjunction with attenuation correction.
             3. Input True or False for attenuation correction on Line 17.
             4. Input True or False for anterior posterior rotation on Line 18.
   5. Once all changes have been made, cropping can begin. To do this, switch to screenCrop.py and select the play icon in the toolbar, in the drop-down menu select Run As > Python Run.
   6. As cropping can take several hours to complete for a large dataset (50 point visits 18 z steps, 3 channels, 31 timepoints), track progress of cropping in the console window. Once cropping is completed, a small window will show previews of the cropped images before saving. For each image there are 3 options:
      1. Save: Press Space Bar to save the image if the image is cropped properly with no areas of interest being cut off.
      2. X: Press X if the image appears to have areas of interest cut off; the image will be saved with an X in front of the name to separate it from the other images.
      3. Delete: Press D to delete the cropped image if the image is not cropped properly or the embryo is not satisfactory.
         NOTE: The images will be saved to a subfolder named "Cropped" in the Load Folder (defined in Line 9 of the program).

4. Visualization (Figure 4)

NOTE: OpenandCombine_embsV2.ijm^10,12 is an ImageJ macro that will construct an easy to view tiff file from all the images for a specific strain and condition. Installation of FIJI/ImageJ^14,15 is required. This macro runs according to our file structure; it will need to be modified to work with other file structures. A guide to proper file structure and detailed description of important considerations can be found at the end of the GUI_Instructions_zenodo_repoV2.docx file on the Zenodo repository. Please read through these instructions completely before imaging to properly name and structure files to interface best with this macro. For reference, our file location structure looks like this:
Z:\cropped\Target\Strain\Emb#\Target_Emb#_15 Digit Unique Identifier _W##F#_T##_Z##_C#.tif
i.e. Z:\cropped\EMBD0001\GLS\Emb1\EMBD0001_Emb1_20140327T135219_W02F1_T01_Z01_C1.tif

1. Download OpenandCombine_embsV2 and GUI_Instructions_zenodo_repoV2.docx from Zenodo (https://zenodo.org/record/3235681#.XPAnn4hKg2w).
2. Prepare the following information:
   -The location where the image folders are stored (following cropping).
   -The image folder name(s) for the specific condition(s) to be processed (i.e., EMBD0002). This is referred to as "Target" in the above example
   -A 15 digit alpha-numeric unique identifier that is specific to a given overnight experiment—this identifier is the data acquisition folder name (i.e., 20140402T140154) and the unique identifier is embedded in the individual tiff file name (EMBD0002_Emb1_20140402T140154_W06F2_T01_Z01_C1) for every embryo imaged on that day. The macro uses this identifier to check for embryos acquired on the same date and can assemble repeated conditions, with separate dates, into separate ImageJ files.
3. Open ImageJ, and drag-and-drop the macro file, OpenandCombine_embsV2.ijm, to the ImageJ bar, or open the macro directly.
4. Once the macro is open, locate lines 3 and 4. Input the information gathered in (section 4.2) according to the following steps:
   1. In Line 3 (RNAL), input the target name for the images to be processed. Input each target in the following structure newArray("XXXXXXXX/"); include quotations. To run multiple conditions at once, separate with a comma and keep all target names within the parenthesis (i.e., newArray("EMBD0000/","EMBD0001/","EMBD0002/").
   2. In Line 4 (date), input the 15 digit alpha-numeric unique identifier in quotations, for example newArray("20140402T140154").
5. Press Run at the bottom left of the macro window. A window will appear, which will launch a prompt to navigate to the outer folder containing the cropped image folders (specified in 4.4.1).
6. Once selected, another window will appear, which will allow specification of imaging parameters.
   1. Enter the number of channels, the number of Z slices, the font size for the text used in labeling the compiled images, and the color for each of the channels.
   2. Check on/off auto contrasting in all channels.
7. Once all parameters have been specified, click OK at the bottom of the window. The composite file will begin to assemble; this will take several minutes, per condition, to complete.
8. Once completed, review the files that are left open if desired. They can be closed without saving, as the macro has already saved the files to a newly created folder which is named in the following manner: outer folder name (specified in the prompt of section 4.5) + "-fiji-processed-output" (i.e., Z:\ cropped-fiji-processed-output\EMBD0002_GLS_20140402T140154.tif).

Results

A significant challenge in characterizing the effect of molecular perturbations on C. elegans embryonic development is that it takes about 10 h for embryos to progress from first cleavage to the end of elongation at 20°¹⁶. A semi-high-throughput method in which large cohorts of embryos can be simultaneously imaged is useful for events on this time-scale because it permits imaging of multiple conditions in parallel with a sufficient ensemble size for each condition to enable quantitative a...

Discussion

This work describes a suite of tools and methods that were developed to enable larger-scale efforts to profile the function of genes in embryonic development in C. elegans. Our semi-high-throughput method allows 3D time-lapse imaging of embryonic development at 20 min resolution for 80–100 embryos in a single experiment. While this protocol can be adapted for use with any desired marker strain(s), this work demonstrates the potential of the method using two custom strains developed to monitor events during...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Aspirator Tube Assembly	Drummond Scientific	2-000-000
Calibrated Pipette (25 mL)	Drummond Scientific	2-000-025
Cell Voyager Software	Yokogawa Electric Corp	Included with CV1000
Conical Tube (15 mL)	USA Scientific	1475-0501
CV1000 Microscope	Yokogawa Electric Corp	CV1000
Depression slide (3-well)	Erie Scientific	1520-006
Dissection Microscope	Nikon	SMZ-645
Eppendorf Centrifuge 5810R	Eppendorf	5811 07336
ImageJ/FIJI	Open Source	https://imagej.net/Fiji
M9 Buffer	Lab Prepared	https://openwetware.org/wiki/M9_salts
Microcentrifuge Tube (1.5 mL)	USA Scientific	1615-5500
Microseal F-foil Seal	Bio-Rad	MSF1001
NGM Plates	Lab Prepared	http://www.wormbook.org/chapters/www_strainmaintain/strainmaintain.html#d0e214
Scalpel #15	Bard Parker	REF 371615
Sensoplate Plus, 384 Well, F-bottom, Glass Bottom	Greiner Bio-One	781855
Tetramisole Hydrochloride	Sigma Aldirch	T1512-10G
Tweezers, Dumont #3	Electron Microscopy Sciences	0109-3-PO
U-PlanApo objective (10× 0.4 NA)	Olympus	1-U2B823
U-PlanApo objective (60× 1.35 NA)	Olympus	1-U2B832