S.D.O. was supported by the National Institute of General Medical Sciences-sponsored University of California San Diego Institutional Research and Academic Career Development Award (NIH/IRACDA K12 GM068524). A.D. and K.O. were supported by the Ludwig Institute for Cancer Research, which also provided them with research funding used to support this work. We are grateful to Andrew Chisholm for his advice in the early phases of this project, Ronald Biggs for contributions to this project after the initial method development phase, and Dave Jenkins and Andy Shiau for support and access to the Small Molecule Discovery group&#8217;s high-content imaging system.

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.
<ol>
	<li>Prepare 5&#8211;10 mL of 0.1 mg/mL solution of tetramisole hydrochloride (TMHC) anesthetic dissolved in ice cold M9 medium (0.45 M Na2HPO4&#8729;7H2O, 0.11 M&#160;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.</li>
	<li>Aliquot 70 &#181;L 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.</li>
	<li>Generate mouth pipets for transferring embryos from the depression slide (where the gravid hermaphrodites are dissected) to the wells. Pull capillary pipets (25 &#181;L 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.</li>
	<li>Use fine tweezers to transfer ~10 gravid adults under a dissection scope into 150 &#181;L 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.</li>
	<li>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.</li>
	<li>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.</li>
	<li>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 &#181;m) and motorized z-axis control (designated resolution 0.1 &#181;m) is used. This system is kept in a 16 &#176;C room, which maintains the microscope temperature between 21 and 23 &#176;C during overnight imaging.</li>
	<li>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.</li>
	<li>To select imaging fields, switch to the 60x objective and adjust the focal plane at each point visit to appropriately section the embryos. 1&#8211;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.</li>
	<li>Image the selected fields using a 60x 1.35 NA objective to acquire 18 z sections at 2 &#181;m 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%&#160; gain; 488 nm, 100% power, 200 ms, 60% gain; 568 nm, 45% power, 150 ms, 60% gain.</li>
	<li>After imaging is complete, assess embryonic lethality by performing a low magnification (10x 0.4 NA objective) whole well brightfield scan ~20&#8211;24 h following the start of overnight imaging.</li>
</ol>
2. Embryonic Lethality Scoring
<ol>
	<li>Using the post-run 10x scanned fields, assess embryonic lethality and larval defects by counting hatched worms and unhatched embryos for each well.</li>
	<li>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.</li>
	<li>Score partially hatched or fully hatched worms with body morphology or behavioral defects, such as dumpy or paralyzed, as &#39;abnormal larva&#39;.</li>
</ol>
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.
<ol>
	<li>Automated cropping using embryoCropUI executable version (user friendly version)
	<ol>
		<li>To use the embryoCropUI program, first download the program from Zenodo (https://zenodo.org/record/3235681#.XPAnn4hKg2w)12.
		<ol>
			<li>Download the MacOS or Windows format version of the program (note that the MacOS version requires MacOS X10.11 or higher).</li>
			<li>Download the instructions file (GUI_Instructions_zenodo_repoV2.docx), which provides step by step instruction for testing and using the embryoCropUI program.</li>
			<li>Download the test_files.zip to test if the program is properly functioning on the platform (see instructions).</li>
		</ol>
		</li>
		<li>Once downloaded, unzip and navigate to find the embryoCropUI executable (&#8230;\embryoCropUI\_WINDOWS\embryoCropUI\embryoCropUI.exe) or (&#8230;\embryoCropUI\_MacOS\embryoCropUI\embryoCropUI.exe). Double click to launch (or chose &#39;open with&#39;&#160;terminal) and run the embryoCropUI executable.</li>
		<li>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).</li>
		<li>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.).</li>
		<li>Select additional processing to run on the images. The program offers Drift Correction, Background Subtraction, and Attenuation Correction.</li>
		<li>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.</li>
		<li>Specify the image collection order (i.e., channel-z-time (czt), or z-channel-time (zct)).</li>
		<li>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.</li>
		<li>Select Run at the bottom left corner. A new subfolder labeled &#8220;crop&#8221; 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.</li>
	</ol>
	</li>
	<li>Automated cropping using screenCrop.py (batch version alternative to embryoCrop GUI described above; Python savvy users only)10,13
	<ol>
		<li>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).</li>
		<li>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.</li>
		<li>Once environmental variables and naming conventions have been properly established, open parameters.py and screenCrop.py in an editor of choice.</li>
		<li>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.
		<ol>
			<li>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.</li>
			<li>Locate the following information within the parameters.py file and make modifications to suit desired imaging parameters and file structure:
			<ol>
				<li>loadFolder (line 9): Change to the drive on which the files are stored (e.g., Z:/, D://, etc.)</li>
				<li>date (line 7): Change to the folder containing files for the imaging session. This is referred to as &#39;Experiment Folder Name&#39;&#160;in the CSV tracking file (see instructions).</li>
				<li>trackingFile (line 11): Change to the path to the CSV file in which experiment information is stored.</li>
				<li>z (line 13): Set as the number of z planes.</li>
				<li>nT (line14): Set as the number of timepoints.</li>
				<li>nWells (line 19): Set as the number of wells used.</li>
				<li>pointVisits (line 20): Set as the maximum number of point visits (per well).</li>
				<li>In line 10 find the location currently occupied by &#39;CV1000/&#39;&#160;and input the outer folder used in the file path. To avoid issues, use the following convention: &#39;XXXXXXX/&#39;.</li>
				<li>In Line 12, input a valid file path for storing aspect ratio data for cropped data.</li>
				<li>In Lines 15, 16, 17, and 18 input True/False for whether the images go through the following processing:
				<ol>
					<li>Input True or False for drift correction on Line 15.</li>
					<li>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.</li>
					<li>Input True or False for attenuation correction on Line 17.</li>
					<li>Input True or False for anterior posterior rotation on Line 18.</li>
				</ol>
				</li>
			</ol>
			</li>
		</ol>
		</li>
		<li>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 &#62; Python Run.</li>
		<li>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:
		<ol>
			<li>Save: Press Space Bar to save the image if the image is cropped properly with no areas of interest being cut off.</li>
			<li>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.</li>
			<li>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 &#34;Cropped&#34;&#160;in the Load Folder (defined in Line 9 of the program).</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
4. Visualization (Figure 4)
NOTE: OpenandCombine_embsV2.ijm10,12 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/ImageJ14,15 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
<ol>
	<li>Download OpenandCombine_embsV2 and GUI_Instructions_zenodo_repoV2.docx from Zenodo (https://zenodo.org/record/3235681#.XPAnn4hKg2w).</li>
	<li>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 &#34;Target&#34;&#160;in the above example 
	-A 15 digit alpha-numeric unique identifier that is specific to a given overnight experiment&#8212;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.</li>
	<li>Open ImageJ, and drag-and-drop the macro file, OpenandCombine_embsV2.ijm, to the ImageJ bar, or open the macro directly.</li>
	<li>Once the macro is open, locate lines 3 and 4. Input the information gathered in (section 4.2) according to the following steps:
	<ol>
		<li>In Line 3 (RNAL), input the target name for the images to be processed. Input each target in the following structure newArray(&#34;XXXXXXXX/&#34;); include quotations. To run multiple conditions at once, separate with a comma and keep all target names within the parenthesis (i.e., newArray(&#34;EMBD0000/&#34;,&#34;EMBD0001/&#34;,&#34;EMBD0002/&#34;).</li>
		<li>In Line 4 (date), input the 15 digit alpha-numeric unique identifier in quotations, for example newArray(&#34;20140402T140154&#34;).</li>
	</ol>
	</li>
	<li>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).</li>
	<li>Once selected, another window will appear, which will allow specification of imaging parameters.
	<ol>
		<li>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.</li>
		<li>Check on/off auto contrasting in all channels.</li>
	</ol>
	</li>
	<li>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.</li>
	<li>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) + &#34;-fiji-processed-output&#34;&#160;(i.e., Z:\ cropped-fiji-processed-output\EMBD0002_GLS_20140402T140154.tif).</li>
</ol>

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A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cell+division.">Cell division.</a> WormBook. , 1-40 (2006).</li><li>Insley, P., Shaham, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+C.+elegans+embryo+alignments+reveal+brain+neuropil+position+invariance+despite+lax+cell+body+placement.">Automated C. elegans embryo alignments reveal brain neuropil position invariance despite lax cell body placement.</a> PLoS One. 13 (3), 0194861 (2018).</li></ol>

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&#8211;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...

The C. elegans embryo is an important model system for mechanistic cell biology and analysis of cell fate specification and morphogenetic events driving embryonic development1,2,3,4,5,6,7,8,9. 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&#8211;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&#8211;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&#8211;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&#8211;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 &#181;m steps. Fifty fields, each containing between 1&#8211;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&#8211;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&#8211;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 morphogenesis10,11. 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.&#160;

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			<td>Yokogawa Electric Corp</td>
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			<td>Erie Scientific</td>
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			<td>http://www.wormbook.org/chapters/www_strainmaintain/strainmaintain.html#d0e214</td>
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			<td height="21" style="height:21px;">Scalpel #15</td>
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			<td height="21" style="height:21px;">U-PlanApo objective (10&#215; 0.4NA)</td>
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			<td height="21" style="height:21px;">U-PlanApo objective (60&#215; 1.35 NA)</td>
			<td>Olympus</td>
			<td>1-U2B832</td>
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a semi-high-throughput imaging method and data visualization toolkit to analyze c. elegans embryonic development

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&#8211;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.

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&#176;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 quantitat...

Watch this Scientific Journal Video about A Semi-high-throughput Imaging Method and Data Visualization Toolkit to Analyze C. elegans Embryonic Development at JoVE.com

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

This work describes a semi-high-throughput protocol that allows simultaneous 3D time-lapse imaging of embryogenesis in 80&#8211;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.

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

C. elegans is the premier system for the systematic analysis of cell fate specification and morphogenetic events during embryonic development. One ...

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6.6K Views.  Ludwig Institute for Cancer Research, San Diego. 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.

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

Visualization of Chondrocyte Intercalation and Directional Proliferation via Zebrabow Clonal Cell Analysis in the Embryonic Meckel&#8217;s Cartilage

Development of the vertebrate craniofacial structures requires precise coordination of cell migration, proliferation, adhesion and differentiation. Patterning of the Meckel&#39;s cartilage, a first pharyngeal arch derivative, involves the migration of cranial neural crest (CNC) cells and the progressive partitioning, proliferation and organization of differentiated chondrocytes. Several studies have described CNC migration during lower jaw&#160;morphogenesis, but the details of how the chondrocytes achieve organization in the growth and extension of Meckel&#8217;s cartilage remains unclear. The sox10 restricted and chemically induced Cre recombinase-mediated recombination generates permutations of distinct fluorescent proteins (RFP, YFP and CFP), thereby creating a multi-spectral labeling of progenitor cells and their progeny, reflecting distinct clonal populations. Using confocal time-lapse photography, it is possible to observe the chondrocytes behavior during the development of the zebrafish Meckel&#8217;s cartilage.
Multispectral cell labeling enables scientists to demonstrate extension of the Meckel&#8217;s chondrocytes.&#160;During extension phase of the Meckel&#8217;s cartilage, which prefigures the mandible, chondrocytes intercalate to effect extension as they stack in an organized single-cell layered row. Failure of this organized intercalating process to mediate cell extension provides the cellular mechanistic explanation for hypoplastic mandible that we observe in mandibular malformations.

Visualization of Chondrocyte Intercalation and Directional Proliferation via Zebrabow Clonal Cell Analysis in the Embryonic Meckel&amp;#8217;s Cartilage

Cell organization of craniofacial bones has long been hypothesized but never directly visualized. Multi-spectral cell labeling and in vivo live imaging allows visualization of dynamic cell behavior in zebrafish lower jaw. Here, we detail the protocol to manipulate Zebrabow transgenic fish and directly observe cell intercalation and morphological changes of chondrocytes in the Meckel&#8217;s cartilage.

Development of the vertebrate craniofacial structures requires precise coordination of cell migration, proliferation, adhesion and differentiation. ...

Transcriptome Profiling of In-Vivo Produced Bovine Pre-implantation Embryos Using Two-color Microarray Platform

Early embryonic loss is a large contributor to infertility in cattle. Moreover, bovine becomes an interesting model to study human preimplantation embryo development due to their similar developmental process. Although genetic factors are known to affect early embryonic development, the discovery of such factors has been a serious challenge. Microarray technology allows quantitative measurement and gene expression profiling of transcript levels on a genome-wide basis. One of the main decisions that have to be made when planning a microarray experiment is whether to use a one- or two-color approach. Two-color design increases technical replication, minimizes variability, improves sensitivity and accuracy as well as allows having loop designs, defining the common reference samples. Although microarray is a powerful biological tool, there are potential pitfalls that can attenuate its power. Hence, in this technical paper we demonstrate an optimized protocol for RNA extraction, amplification, labeling, hybridization of the labeled amplified RNA to the array, array scanning and data analysis using the two-color analysis strategy.

Transcriptome Profiling of In-Vivo Produced Bovine Pre-implantation Embryos Using Two-color Microarray Platform

Microarray technology allows quantitative measurement and gene expression profiling of transcripts on a genome-wide basis. Therefore, this protocol provides an optimized technical procedure in a two-color custom made bovine array using Day 7 bovine embryos to demonstrate the feasibility of using low amount of total RNA.

Early embryonic loss is a large contributor to infertility in cattle. Moreover, bovine becomes an interesting model to study human preimplantation embryo ...

A Versatile Mounting Method for Long Term Imaging of Zebrafish Development

Zebrafish embryos offer an ideal experimental system to study complex morphogenetic processes due to their ease of accessibility and optical transparency. In particular, posterior body elongation is an essential process in embryonic development by which multiple tissue deformations act together to direct the formation of a large part of the body axis. In order to observe this process by long-term time-lapse imaging it is necessary to utilize a mounting technique that allows sufficient support to maintain samples in the correct orientation during transfer to the microscope and acquisition. In addition, the mounting must also provide sufficient freedom of movement for the outgrowth of the posterior body region without affecting its normal development. Finally, there must be a certain degree in versatility of the mounting method to allow imaging on diverse imaging set-ups. Here, we present a mounting technique for imaging the development of posterior body elongation in the zebrafish D. rerio. This technique involves mounting embryos such that the head and yolk sac regions are almost entirely included in agarose, while leaving out the posterior body region to elongate and develop normally. We will show how this can be adapted for upright, inverted and vertical light-sheet microscopy set-ups. While this protocol focuses on mounting embryos for imaging for the posterior body, it could easily be adapted for the live imaging of multiple aspects of zebrafish development.

Here, we present a versatile mounting method that allows for the long-term time-lapse imaging of the posterior body development of live zebrafish embryos without perturbing normal development.

Zebrafish embryos offer an ideal experimental system to study complex morphogenetic processes due to their ease of accessibility and optical transparency. ...

A Simple Method to Identify Kinases That Regulate Embryonic Stem Cell Pluripotency by High-throughput Inhibitor Screening

Embryonic stem cells (ESCs) can self-renew or differentiate into all cell types, a phenomenon known as pluripotency. Distinct pluripotent states have been described, termed &#34;na&#239;ve&#34; and &#34;primed&#34; pluripotency. The mechanisms that control na&#239;ve-primed transition are poorly understood. In particular, we remain poorly informed about protein kinases that specify na&#239;ve and primed pluripotent states, despite increasing availability of high-quality tool compounds to probe kinase function. Here, we describe a scalable platform to perform targeted small molecule screens for kinase regulators of the na&#239;ve-primed pluripotent transition in mouse ESCs. This approach utilizes simple cell culture conditions and standard reagents, materials and equipment to uncover and validate kinase inhibitors with hitherto unappreciated effects on pluripotency. We discuss potential applications for this technology, including screening of other small molecule collections such as increasingly sophisticated kinase inhibitors and emerging libraries of epigenetic tool compounds.

Here, we present a quantitative and scalable protocol to perform targeted small molecule screens for kinase regulators of the na&#239;ve-primed pluripotent transition.

Embryonic stem cells (ESCs) can self-renew or differentiate into all cell types, a phenomenon known as pluripotency. Distinct pluripotent states have been ...

Visualization and Quantitative Analysis of Embryonic Angiogenesis in Xenopus tropicalis

Blood vessels supply oxygen and nutrients throughout the body, and the formation of the vascular network is under tight developmental control. The efficient in vivo visualization of blood vessels and the reliable quantification of their complexity are key to understanding the biology and disease of the vascular network. Here, we provide a detailed method to visualize blood vessels with a commercially available fluorescent dye, human plasma acetylated low density lipoprotein DiI complex (DiI-AcLDL), and to quantify their complexity in Xenopus tropicalis. Blood vessels can be labeled by a simple injection of DiI-AcLDL into the beating heart of an embryo, and blood vessels in the entire embryo can be imaged in live or fixed embryos. Combined with gene perturbation by the targeted microinjection of nucleic acids and/or the bath application of pharmacological reagents, the roles of a gene or of a signaling pathway on vascular development can be investigated within one week without resorting to sophisticated genetically engineered animals. Because of the well-defined venous system of Xenopus and its stereotypic angiogenesis, the sprouting of pre-existing vessels, vessel complexity can be quantified efficiently after perturbation experiments. This relatively simple protocol should serve as an easily accessible tool in diverse fields of cardiovascular research.

Visualization and Quantitative Analysis of Embryonic Angiogenesis in Xenopus tropicalis

This protocol demonstrates a fluorescence-based method to visualize the vasculature and to quantify its complexity in Xenopus tropicalis. Blood vessels can be imaged minutes after the injection of a fluorescent dye into the beating heart of an embryo after genetic and/or pharmacological manipulations to study cardiovascular development in vivo.

Blood vessels supply oxygen and nutrients throughout the body, and the formation of the vascular network is under tight developmental control. The ...

Multi-Photon Time Lapse Imaging to Visualize Development in Real-time: Visualization of Migrating Neural Crest Cells in Zebrafish Embryos

Congenital eye and craniofacial anomalies reflect disruptions in the neural crest, a transient population of migratory stem cells that give rise to numerous cell types throughout the body. Understanding the biology of the neural crest has been limited, reflecting a lack of genetically tractable models that can be studied in vivo and in real-time. Zebrafish is a particularly important developmental model for studying migratory cell populations, such as the neural crest. To examine neural crest migration into the developing eye, a combination of the advanced optical techniques of laser scanning microscopy with long wavelength multi-photon fluorescence excitation was implemented to capture high-resolution, three-dimensional, real-time videos of the developing eye in transgenic zebrafish embryos, namely Tg(sox10:EGFP) and Tg(foxd3:GFP), as sox10 and foxd3 have been shown in numerous animal models to regulate early neural crest differentiation and likely represent markers for neural crest cells. Multi-photon time-lapse imaging was used to discern the behavior and migratory patterns of two neural crest cell populations contributing to early eye development. This protocol provides information for generating time-lapse videos during zebrafish neural crest migration, as an example, and can be further applied to visualize the early development of many structures in the zebrafish and other model organisms.

A combination of the advanced optical techniques of laser scanning microscopy with long wavelength multi-photon fluorescence excitation was implemented to capture high-resolution, three-dimensional, real-time imaging of neural crest migration in Tg(sox10:EGFP) and Tg(foxd3:GFP) zebrafish embryos.

Congenital eye and craniofacial anomalies reflect disruptions in the neural crest, a transient population of migratory stem cells that give rise to ...

Immobilization of Caenorhabditis elegans to Analyze Intracellular Transport in Neurons

Axonal transport and intraflagellar transport (IFT) are essential for axon and cilia morphogenesis and function. Kinesin superfamily proteins and dynein are molecular motors that regulate anterograde and retrograde transport, respectively. These motors use microtubule networks as rails. Caenorhabditis elegans (C. elegans) is a powerful model organism to study axonal transport and IFT in vivo. Here, I describe a protocol to observe axonal transport and IFT in living C. elegans. Transported cargo can be visualized by tagging cargo proteins using fluorescent proteins such as green fluorescent protein (GFP). C. elegans is transparent and GFP-tagged cargo proteins can be expressed in specific cells under cell-specific promoters. Living worms can be fixed by microbeads on 10% agarose gel without killing or anesthetizing the worms. Under these conditions, cargo movement can be directly observed in the axons and cilia of living C. elegans without dissection. This method can be applied to the observation of any cargo molecule in any cells by modifying the target proteins and/or the cells they are expressed in. Most basic proteins such as molecular motors and adaptor proteins that are involved in axonal transport and IFT are conserved in C. elegans. Compared to other model organisms, mutants can be obtained and maintained more easily in C. elegans. Combining this method with various C. elegans mutants can clarify the molecular mechanisms of axonal transport and IFT.

Immobilization of Caenorhabditis elegans to Analyze Intracellular Transport in Neurons

Caenorhabditis elegans (C. elegans) is a good model to study axonal and intracellular transport. Here, I describe a protocol for in vivo recording and analysis of axonal and intraflagellar transport in C. elegans.

Axonal transport and intraflagellar transport (IFT) are essential for axon and cilia morphogenesis and function. Kinesin superfamily proteins and dynein ...

Organotypic Culture Method to Study the Development Of Embryonic Chicken Tissues

The embryonic chicken is commonly used as a reliable model organism for vertebrate development. Its accessibility and short incubation period makes it ideal for experimentation. Currently, the study of these developmental pathways in the chicken embryo is conducted by applying inhibitors and drugs at localized sites and at low concentrations using a variety of methods. In vitro tissue&#160;culturing is a technique that enables the study of tissues separated from the host organism, while simultaneously bypassing many of the physical limitations present when working with whole embryos, such as the susceptibility of embryos to high doses of potentially lethal chemicals. Here, we present an organotypic culturing protocol for culturing the embryonic chicken half head in vitro, which presents new opportunities for the examination of developmental processes beyond the currently established methods.

Here, we present an organotypic culturing protocol to grow embryonic chicken organs in vitro. Using this method, the development of embryonic chicken tissue can be studied, while maintaining a high degree of control over the culture environment.

The embryonic chicken is commonly used as a reliable model organism for vertebrate development. Its accessibility and short incubation period makes it ...

Computational Analysis of the Caenorhabditis elegans Germline to Study the Distribution of Nuclei, Proteins, and the Cytoskeleton

The Caenorhabditis elegans (C. elegans) germline is used to study several biologically important processes including stem cell development, apoptosis, and chromosome dynamics. While the germline is an excellent model, the analysis is often two dimensional due to the time and labor required for three-dimensional analysis. Major readouts in such studies are the number/position of nuclei and protein distribution within the germline. Here, we present a method to perform automated analysis of the germline using confocal microscopy and computational approaches to determine the number and position of nuclei in each region of the germline. Our method also analyzes germline protein distribution that enables the three-dimensional examination of protein expression in different genetic backgrounds. Further, our study shows variations in cytoskeletal architecture in distinct regions of the germline that may accommodate specific spatial developmental requirements. Finally, our method enables automated counting of the sperm in the spermatheca of each germline. Taken together, our method enables rapid and reproducible phenotypic analysis of the C. elegans germline.

Computational Analysis of the Caenorhabditis elegans Germline to Study the Distribution of Nuclei, Proteins, and the Cytoskeleton

We present an automated method for three-dimensional reconstruction of the Caenorhabditis elegans germline. Our method determines the number and position of each nucleus within the germline and analyses germline protein distribution and cytoskeletal structure.

The Caenorhabditis elegans (C. elegans) germline is used to study several biologically important processes including stem cell development, apoptosis, and ...

Isotropic Light-Sheet Microscopy and Automated Cell Lineage Analyses to Catalogue Caenorhabditis elegans Embryogenesis with Subcellular Resolution

Caenorhabditis elegans (C. elegans) stands out as the only organism in which the challenge of understanding the cellular origins of an entire nervous system can be observed, with single cell resolution, in vivo. Here, we present an integrated protocol for the examination of neurodevelopment in C. elegans embryos. Our protocol combines imaging, lineaging and neuroanatomical tracing of single cells in developing embryos. We achieve long-term, four-dimensional (4D) imaging of living C. elegans&#160;embryos with nearly isotropic spatial resolution through the use of Dual-view Inverted Selective Plane Illumination Microscopy (diSPIM). Nuclei and neuronal structures in the nematode embryos are imaged and isotropically fused to yield images with resolution of ~330 nm in all three dimensions. These minute-by-minute high-resolution 4D data sets are then analyzed to correlate definitive cell-lineage identities with gene expression and morphological dynamics at single-cell and subcellular levels of detail. Our protocol is structured to enable modular implementation of each of the described steps and enhance studies on embryogenesis, gene expression, or neurodevelopment.

Here, we present a combinatorial approach using high-resolution microscopy, computational tools, and single-cell labeling in living C. elegans embryos to understand single cell dynamics during neurodevelopment.

Caenorhabditis elegans (C. elegans) stands out as the only organism in which the challenge of understanding the cellular origins of an entire nervous ...