The authors would like to thank Stefano Di Talia, Alberto Puliafito, Venkatraman Seshan and Panagiotis Xenopoulos, for input on data handling, analysis and representation, Berenika Plusa for assistance in the design of the immunofluorescence protocol and antibody testing and members of the Hadjantonakis lab for comments on the manuscript and on the development of this protocol. Work in our lab is supported by the National Institutes of Health R01-HD052115 and R01-DK084391, and by NYSTEM N13G-236.

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<li>Kang, M., Piliszek, A., Artus, J., Hadjantonakis, A. -K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((FGF4+is+required+for+lineage+restriction+and+salt-and-pepper+distribution+of+primitive+endoderm+factors+but+not+their+initial+expression+in+the+mouse%5BTitle%5D)+AND+%22Development%22%5BJournal%5D)">FGF4 is required for lineage restriction and salt-and-pepper distribution of primitive endoderm factors but not their initial expression in the mouse.</a> Development. 140 (2), 267-279 (2013).</li>
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<li>Behringer, R. R., Gertsenstein, M., Vintersten Nagy, K., Nagy, A. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aBehringer%2C+RR+%22Manipulating+the+mouse+embryo%3A+a+laboratory+manual%22">Manipulating the mouse embryo: a laboratory manual</a>. , Cold Spring Harbor Laboratory Press. Cold Spring Harbor, New York. (2014).</li>
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<li>Frankenberg, S., Shaw, G., Freyer, C., Pask, A. J., Renfree, M. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Early+cell+lineage+specification+in+a+marsupial%3A+a+case+for+diverse+mechanisms+among+mammals%5BTitle%5D)+AND+%22Development%22%5BJournal%5D)">Early cell lineage specification in a marsupial: a case for diverse mechanisms among mammals.</a> Development. 140, 965-975 (2013).</li>
<li>Artus, J., Vandormael-Pournin, S., Frödin, M., Nacerddine, K., Babinet, C., Cohen-Tannoudji, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Impaired+mitotic+progression+and+preimplantation+lethality+in+mice+lacking+OMCG1%2C+a+new+evolutionarily+conserved+nuclear+protein%5BTitle%5D)+AND+%22Molecular+and+cellular+biology%22%5BJournal%5D)">Impaired mitotic progression and preimplantation lethality in mice lacking OMCG1, a new evolutionarily conserved nuclear protein.</a> Molecular and cellular biology. 25 (14), 6289-6302 (2005).</li>
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</ol>

The authors declare no conflicts of interest.

The present protocol describes a method to perform a quantitative analysis of whole-mount immunofluorescence on preimplantation stage mouse embryos. A robust immunofluorescence protocol 22 is followed by high-resolution, whole-mount confocal imaging and by image segmentation using a tailored piece of software 4. While the choice of immunofluorescence protocol is not critical, we find the one presented here 22 to be fast, reliable and to provide robust signal for many of the antibodies we have tested. Other protocols may be followed, provided their application is consistent across equivalent experiments. While many factors affect the outcome of each individual experiment, and direct comparison between experiments is not necessarily possible, we have found that striving for consistency across repetitions and performing sufficient technical replicates greatly reduces variability. Therefore, once optimized, fixation and immunolabeling reagents and protocols, as well as imaging conditions should be kept constant between equivalent experiments.
The main problems that may arise during the application of this protocol fall into two groups: 1) poor quality staining, with dim signal, and 2) suboptimal segmentation, with many errors (i.e., over- and under-segmentation). Low quality immunofluorescence is generally due to improper fixation of the samples or to the antibodies not being suitable for whole-mount immunofluorescence. Ensure PFA is fresh (either freshly prepared or thawed to RT from -20 &#186;C no longer than a week prior). Given the small size of preimplantation embryos, 10-min fixation in PFA should suffice. However, we have found certain antibodies to yield a stronger signal with longer fixation times (see Materials). If an antibody that has been previously tested provides weak signal, try different fixation protocols. Not all antibodies perform robustly on whole-mount immunofluorescence and the choice of primary antibody is critical for the outcome of the experiment. New antibodies should be tested on embryos and the optimal concentration determined empirically. In the Materials chart we provide details of a number antibodies we have tested and use routinely. Refer to the published literature or to the manufacturer&#39;s information when considering new antibodies. Note that not all antibodies suitable for Western blot work in whole-mount immunofluorescence, and the concentrations necessary for immunofluorescence may be up to one order of magnitude higher. Commercial secondary antibodies generally work well out of the box, however, be consistent in the use of primary-secondary antibody combinations throughout equivalent experiments that are going to be compared.
The quality of image segmentation depends on both the quality of the nuclear staining and on the nuclear density in the ICM of the embryo. Always strive for bright, sharp nuclei and use a high-resolution objective (40X or more). If the nuclear stain signal is low, use a fresh aliquot or a new batch. As long as the nuclear stain is not used for quantification, the acquisition parameters can be adjusted for each embryo in order to record sharp, bright nuclei. Likewise, if a channel other than the nuclear staining is used for segmentation, the signal-to-noise ratio of that particular channel will determine the quality of the segmentation. Late stage blastocysts (E4.0 onwards) present a very high nuclear density within the ICM. Therefore, it is at these stages that high quality staining is most critical. Nevertheless, segmentation errors will take place most often at these stages. Introduce the estimated nuclear diameter and the image noise level on the MINS pipeline, explore the outcome of each step using the &#39;View&#39; button and adjust the parameters until a satisfactory result is obtained. Use the parameters that produce the best segmentation and manually correct errors during data processing. Note that late stage embryos (~E4.5) have a high cell count and manual data correction will be time consuming.
The limitations of this protocol are determined by the confocal microscope system used for image acquisition. As discussed, use a high-magnification objective, with a working distance that allows Z-axis imaging of the entire embryo (preimplantation mouse embryos can reach up to 150 - 160 &#181;m in diameter). Similarly, the number of epitopes that can be detected will be determined by the number of channels the microscope can acquire at once. Using this protocol, three different epitopes besides the DNA (4 channels in total) can be labeled simultaneously on each sample. Ensure the instrument is calibrated for each fluorescence channel, the gating is optimized and that the laser output is consistent.
The methods described here allow the analysis of cell position along the XYZ axes as well as the quantification of protein expression levels in situ for every single cell in mouse blastocysts. In our experience, alternative methods using any other available software cannot provide the level of resolution that the pipeline applied in this protocol can (see 4 for a direct comparison with other tools). The high nuclear density found in the ICM of the blastocyst causes other tools to generate so many mistakes that the extent of manual correction required makes their use impractical. Alternatively, manual cell counting and fluorescence measurements have been previously used for subsets of cells or defined regions of the embryo 10,11,18,19,24. However, manual counting and measurement of all fluorescence channels and cell position, across all XYZ axes, for the tens of cells present in each embryo would be so time consuming that it would not allow for the high-throughput analysis for which our protocol was devised. Moreover, manual assessment of fluorescence levels is prone to bias, while a pipeline such as the one described here allows an objective measurement of fluorescence intensities for the subsequent determination of cell identity. In order to assign cell identities, the investigator should establish a standard criterion to be applied across all samples for a particular experimental set up. Given the different factors - biological and technical - that can affect the outcome of immunolabeling, this criterion should be determined using appropriate control experiments and previously published data wherever possible. We envision a near future where an algorithm may be designed for automatic determination of cell identity regardless of the experiment. However, such a tool will only come from more extensive application and improvement of the current method, most likely coupled with machine learning algorithms.
Finally, given the simplicity of this pipeline and the stereotypical morphology of mouse preimplantation embryos, this protocol is easily scalable for the analysis of large numbers of embryos, thus allowing high-throughput analyses of null phenotypes 5,6 or any other experimental manipulation 7. Finally, while the current protocol has been designed and optimized for the analysis of preimplantation mouse embryos and ESC colonies, we see no reason a priori why it could not be applied to other systems with similar characteristics - namely high nuclear density. We encourage others to experiment and adapt this protocol to other scenarios and provide feedback for its future improvement.

The mouse preimplantation embryo is a paradigm to study the emergence and maintenance of pluripotency in vivo, as well as a model for the study of cell fate specification and de novo epithelialization in mammals. The preimplantation stages of mammalian development are dedicated to the establishment of the three cell lineages that make up the blastocyst, namely the pluripotent epiblast - which gives rise to most somatic tissues and germ cells - and two extraembryonic lineages, the trophectoderm (TE) and the primitive endoderm (PrE) (Figure 1A) 1,2. This protocol describes the procedures to (1) harvest and fix preimplantation stage mouse embryos, (2) perform immunofluorescence to label proteins of interest, (3) carry out whole-mount imaging using a confocal microscope with z-sectioning capabilities and (4) perform nuclear segmentation of confocal images and subsequent quantitative image analyses. This pipeline allows the unbiased measurement of protein levels for the assignment of cell identities to characterize subpopulations of cells in situ. This protocol can be carried out in as little as 3 - 4 days for a single litter (generally up to 10 mouse embryos), from embryo collection to the data analysis (Figure 1B). The simultaneous analysis of several litters would increase the imaging and data analysis time burden, thus extending the overall length of the protocol.
The preimplantation stage mouse embryo is an experimentally tractable system which, given its small size and stereotypical morphology 3, is well suited for in toto imaging of cellular processes with single-cell resolution. To carry out an unbiased, systems-level analysis of a statistically relevant number of embryos, an automated, quantitative analysis pipeline is desirable. However, due to the high nuclear density of the inner cell mass (ICM) of the blastocyst (Figure 1A, 2D), conventional image segmentation platforms fail to provide sufficient accuracy to establish an automated or semi-automated workflow. On the other hand, manual segmentation, while accurate, does not allow the processing of large cohorts of cells and embryos, nor is it suitable for a reproducible, unbiased determination of cell identities - which is especially critical when studying developmental stages where patterns of marker expression have not fully resolved (e.g., do not exhibit a binary distribution across a population). We have recently developed and validated an image segmentation method tailored for mouse preimplantation stage embryos and for mouse embryonic stem cells (ESCs) that achieves high accuracy, while requiring minimal user input 4-8.
The analysis pipeline presented here revolves around the MATLAB-based image segmentation tool Modular Interactive Nuclear Segmentation (MINS) 4. MINS performs unsupervised nuclear segmentation on large batches of confocal Z-stacks after the user has established a minimal number of image properties, using a graphical user interface (GUI) (Table 1) 4. This pipeline has proven efficient for the generation of high throughput data on protein expression and cell localization in both wild type, experimentally treated and genetically modified embryos and ESCs 5-7. In the present protocol, we describe the application of MINS to the segmentation of preimplantation-stage embryo images. For examples of MINS performance on ESCs please refer to 4,7. The automated nuclear segmentation step significantly reduces the time burden of the cell identification process, whereas the spatial and fluorescence intensity measurements allow an unbiased determination of cell identities and the generation of three-dimensional maps of gene expression domains and cell position in the embryo (Figure 1C). Moreover, the scalability of this workflow makes it applicable to the analysis of individual litters through large cohorts of experimentally treated embryos, or embryos of different genetic backgrounds 5,6. MINS is freely available at&#160; http://katlab-tools.org (the software requires a MATLAB license).
No approach developed to date allows the generation of such in-depth data on protein expression and cell localization in mouse preimplantation embryos. All attempts thus far at quantifying these types of data have been restricted to the manual determination and quantitation of cell numbers for different populations in the embryo (either entirely manually, or software-assisted) 9-19. This approach (incorporating MINS software) has been tailored for and tested on mouse preimplantation embryos and ESCs; nevertheless its performance on other systems with high nuclear density, although yet untested, is expected to be equivalent.

<table><tbody><tr><td>&lt;strong&gt;Embryo collection&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Blunt probe for plug checking</td><td>Roboz</td><td>RS-9580</td><td></td></tr><tr><td>Forceps</td><td>Roboz</td><td>RS-4978</td><td></td></tr><tr><td>Surgery scissors</td><td>Roboz</td><td>RS-5910</td><td></td></tr><tr><td>Glass Pasteur pipettes</td><td>Fisher</td><td>13-678-20C</td><td></td></tr><tr><td>Pre-assembled aspirator tube &amp;amp; mouthpiece</td><td>Sigma</td><td>A5177</td><td></td></tr><tr><td>Longer rubber tubing</td><td>Fisher</td><td>14-178-2AA&amp;nbsp;&amp;nbsp;&amp;nbsp;</td><td></td></tr><tr><td>M2</td><td>Millipore</td><td>MR-015-D</td><td></td></tr><tr><td>FHM</td><td>Millipore</td><td>MR-024-D</td><td></td></tr><tr><td>Acid Tyrode&#039;s solution</td><td>Millipore</td><td>MR-004-D</td><td></td></tr><tr><td>Penicillin/Streptomycin</td><td>Gibco</td><td>15140</td><td></td></tr><tr><td>Bovine Serum Albumin&amp;nbsp;</td><td>Sigma</td><td>A9647</td><td></td></tr><tr><td>4-well plates</td><td>Nunc/Thermo-Fisher</td><td>12-566-300&amp;nbsp;&amp;nbsp;&amp;nbsp;</td><td></td></tr><tr><td>&lt;strong&gt;Immunofluorescence&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>96-well U-bottom plates</td><td>Fisher</td><td>14-245-73</td><td></td></tr><tr><td>Triton X-100</td><td>Sigma</td><td>T8787</td><td></td></tr><tr><td>Glycine</td><td>Sigma</td><td>G7403</td><td></td></tr><tr><td>Horse serum</td><td>Sigma</td><td>H0146</td><td></td></tr><tr><td>&lt;strong&gt;Primary antibodies&lt;/strong&gt;</td><td></td><td></td><td>&lt;strong&gt;Concentration&lt;/strong&gt;</td></tr><tr><td>CDX2</td><td>Biogenex</td><td>AM392-5M</td><td>1:200</td></tr><tr><td>GATA6</td><td>R&amp;amp;D</td><td>AF1700</td><td>1:100</td></tr><tr><td>GATA4</td><td>Santa Cruz</td><td>sc-9053</td><td>1:100, 10 min fixation</td></tr><tr><td>GATA4</td><td>Santa Cruz</td><td>sc-1237</td><td>1:100, O/N fixation</td></tr><tr><td>SOX17</td><td>R&amp;amp;D</td><td>AF1924</td><td>1:100</td></tr><tr><td>Nanog</td><td>ReproCELL</td><td>RCAB0002P-F</td><td>1:500</td></tr><tr><td>OCT4</td><td>Santa Cruz</td><td>sc-5279</td><td>1:100, 10 min to O/N fixation</td></tr><tr><td>DAB2</td><td>BD</td><td>BD-610464</td><td>1:200</td></tr><tr><td>Secondary antibodies</td><td>Life Technologies</td><td>Various</td><td>1:500</td></tr><tr><td>Hoechst 33342</td><td>Life Technologies</td><td>H3570</td><td></td></tr><tr><td>&lt;strong&gt;Imaging&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>35 mm glass-bottom dishes</td><td>MatTek</td><td>P35G-1.5-14-C</td><td></td></tr><tr><td>&lt;strong&gt;Segmentation&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Computer running 64-bit Windows OS</td><td></td><td>n/a</td><td>Verify minimal system requirements at http://katlab-tools.org and in Lou et al., (2014) Stem Cell Reports</td></tr><tr><td>MATLAB (software)</td><td>Mathworks</td><td>n/a</td><td></td></tr><tr><td>MINS (software)</td><td>Free</td><td>n/a</td><td>http://katlab-tools.org</td></tr></tbody></table>

quantitative analysis of protein expression to study lineage specification in mouse preimplantation embryos

This protocol presents a method to perform quantitative, single-cell in situ analyses of protein expression to study lineage specification in mouse preimplantation embryos. The procedures necessary for embryo collection, immunofluorescence, imaging on a confocal microscope, and image segmentation and analysis are described. This method allows quantitation of the expression of multiple nuclear markers and the spatial (XYZ) coordinates of all cells in the embryo. It takes advantage of MINS, an image segmentation software tool specifically developed for the analysis of confocal images of preimplantation embryos and embryonic stem cell (ESC) colonies. MINS carries out unsupervised nuclear segmentation across the X, Y and Z dimensions, and produces information on cell position in three-dimensional space, as well as nuclear fluorescence levels for all channels with minimal user input. While this protocol has been optimized for the analysis of images of preimplantation stage mouse embryos, it can easily be adapted to the analysis of any other samples exhibiting a good signal-to-noise ratio and where high nuclear density poses a hurdle to image segmentation (e.g., expression analysis of embryonic stem cell (ESC) colonies, differentiating cells in culture, embryos of other species or stages, etc.).

To facilitate data interpretation and presentation, care should be taken not to damage the embryos during collection and manipulation, so that all cells and their relative position can be analyzed. Figure 2A - D shows examples of intact blastocysts at different stages with an expanded cavity. Should damage occur, extra care should be taken when analyzing and interpreting results.
The quality and reliability of the data generated using this protocol is dependent on the quality of the fixation and on the signal-to-noise ratio of the antibodies used to detect the proteins of interest. Always use fresh fixative and test new antibodies, with appropriate positive and negative controls, before beginning a set of experiments. Figure 2A shows examples of good antibodies for a number of nuclear proteins. Figure 2B shows an example of a good antibody for a cytoplasmic protein (DAB2). Figure 2C shows an example of a bad staining, with low signal-to-noise ratio, where the sample was fixed for only 10 min. In this case, the antibody used for GATA4 (Santa Cruz, sc-1237) requires O/N fixation to provide a strong signal (see 24 for instances of embryos fixed O/N and stained with this antibody). Increasing the signal level during post-processing reveals a very noisy image. By contrast the anti-GATA4 used for Figure 2A (sc-9053) provides high signal-to-noise ratio after only 10-min fixation. Details for these and other robust antibodies are provided in the Materials section.
The limiting factors for a good MINS segmentation are a) the magnification of the objective used for imaging, b) the Z-resolution and c) the quality of the nuclear staining. Figure 2D shows examples of embryos imaged with an oil immersion 40X objective with a NA of 1.30 and a 0.21 mm WD. Middle panels show magnifications of the ICMs where individual nuclei and the border between them can be distinguished. If not using DNA staining (i.e., Hoechst, DAPI, TO-PRO3, YO-YO1, etc.) fluorescence values for quantification, acquisition parameters can be individually adjusted to obtain the best signal. Bottom panels show how the more advanced the embryo, the higher the nuclear density and thus the higher the chance of segmentation errors (arrowhead and arrow). Figure 3 shows examples of errors that MINS can commit, such as detecting apoptotic nuclei as live cells (asterisks in panels in Figure 3Aa, Ab, Ad), over-segmentation (arrow and arrowheads in Figure 3Ac) or under-segmentation (arrow in Figure 3Ad). Figure 3B shows a sequence of Z-slices of an under-segmentation event, where two cells have been identified as one. Note how MINS segmentation takes the Z-axis into account to segment a volume that comprises all slices where a given cell is present.
Finally, the specifics of the data analysis will depend on the question under study, therefore, guidelines for the analysis process cannot be given here. However, we have found certain initial data transformations to be useful. Figure 4B - D shows plots of the fluorescence values for the markers NANOG and GATA6 in the ICM of the embryo shown in Figure 4A. Figure 4B shows the raw fluorescence values obtained from MINS (after manual correction of under- and over-segmentation). Figure 4C shows the same data after a logarithmic transformation, which separates the values from the plot axes (a square root transformation is also possible and yields a similar plot). Figure 4D shows the same data after automatically correcting the values for the Z-associated attenuation in fluorescence, as explained in step 4.5.2.2 of the protocol. Examples of this Z-associated fluorescence decay are given in the image in Figure 4E and the plots in 4F. Figure 4G shows the effect of the data transformation explained in 4.5.2.2. Colors representing either epiblast (red, NANOG+, GATA6-) or PrE (blue, NANOG-, GATA6+) identity have been added to the plot as a function of the NANOG and GATA6 values. In this particular example, cells where the ratio of log[GATA6]/log[NANOG] &#62;1.25 were considered PrE, cells where the ratio of log[GATA6]/log[NANOG] &#60; 1 were considered EPI, and cells with an intermediate ratio were considered uncommitted (none in this case). All data transformations and plots have been done in Rstudio, however, the choice of software is not critical and will depend on the end user.
<img alt="Figure 1" src="/files/ftp_upload/53654/53654fig1.jpg" /> 
Figure 1. Embryo Location, Timeline and Analysis Pipeline. (A) Schematic of one (of two) mouse uterine horn and the stages of preimplantation development, aligned with the region of the horn where they should be found. (B) Experimental timeline with timing for each step. Steps of the protocol and pause points (blue) are indicated. (C) Summary of image acquisition and analysis pipeline using MINS. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53654/53654fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/53654/53654fig2.jpg" /> 
Figure 2. Examples of Immunofluorescence and Nuclear Density. (A) Examples of good immunofluorescence results with tested antibodies for nuclear transcription factors. Anti-CDX2 was detected with an AlexaFluor 488 donkey anti-mouse secondary antibody, anti-GATA6 with an AlexaFluor 568 donkey anti-goat, anti-NANOG with an AlexaFluor 647 donkey anti-rabbit, anti-GATA4&#160;(Santa Cruz, sc-9053)&#160;with an AlexaFluor 488 donkey anti-rabbit and anti-OCT4 with an AlexaFluor 647 donkey anti-mouse. All primary antibodies are listed in the Materials Table. Cytoplasmic GATA4 nuclear staining is non-specific, and appears also in Gata4 null embryos (not shown). (B) Example of good immunofluorescence for a cytoplasmic protein, DAB2. It has been detected using an AlexaFluor 488 donkey anti-mouse. (C) Example of bad immunofluorescence, with a low signal-to-noise ratio for a nuclear factor. GATA4 has been detected with an anti-GATA4 raised in goat (Santa Cruz, sc-1237; whereas sc-9053 (rabbit anti-GATA4) was used in (A)) and an AlexaFluor 568 donkey anti-goat. (D) Examples of intact embryos with good nuclear staining showing how nuclear density increases with embryo age and how this increases errors in MINS segmentation (arrowhead - oversegmentation - and arrow - undersegmentation). Scale = 20 &#181;m. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53654/53654fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/53654/53654fig3.jpg" /> 
Figure 3. Examples of MINS Errors. (A) Sequence of individual Z-sections from one embryo showing examples of MINS segmentation errors. Apoptotic cells which are nevertheless identified as nuclei are marked with an asterisk (*) in panels a, b and d. In panel b, ID #39 (arrowhead), albeit very small, does identify the corresponding nucleus and can thus be left uncorrected. In panel c, ID #66 (arrow) spans two different nuclei, which have in turn been identified separately (arrowheads, IDs #65 #54 and #53). In panel d, two cells (ID #63) have been identified as a single one (see arrow marking the thin border) and this record should therefore be duplicated for cell counting purposes. (B) MINS detects cells along the Z-axis. The images show a sequence of Z-slices of two cells that have been erroneously scored as a single one (#123). Note how the blue area delimiting the nuclei is continuous along Z. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53654/53654fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/53654/53654fig4.jpg" /> 
Figure 4. Example of Segmentation and Data Transformations. (A) Images of ICM cells of a blastocyst stained for NANOG and GATA6 and snapshot of nuclear segmentation of the same embryo using MINS on the nuclear staining channel (Hoechst 33342). (B-D) NANOG and GATA6 fluorescence values in ICM cells measured by MINS plotted as raw data (B), after performing logarithmic transformation (C) and after correcting values for the fluorescence decay along the Z axis and automatically assigning cell identities based on the corrected values (D). (E - G) Examples of data correction for fluorescence decay along the Z axis. (E) Images of a blastocyst labeled with Hoechst and anti-CDX2+AlexaFluor 488 (AF488), showing fluorescence decrease along the Z axis. (F) Scatter plots of fluorescence values along the Z axis for Hoechst and AF488 for a pool of embryos including the one shown in (E). Gray line represents the regression curve for each set of values. (G) Same data as in F after compensating fluorescence decay for each cell using the following factor: Z coordinate * the slope of the linear model (see step 4.5.2.2 in the protocol). Panels E - G were originally published by the authors in the Node (http://thenode.biologists.com/99problems/discussion/) Each dot represents one cell. Scale = 20&#181;m. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/53654/53654fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>User Input</td>
		</tr>
		<tr>
			<td>Brightness threshold* (facilitates nuclear detection in dim images)</td>
		</tr>
		<tr>
			<td>Relative X/Y-Z resolution</td>
		</tr>
		<tr>
			<td>Channel to segment</td>
		</tr>
		<tr>
			<td>Nuclear diameter</td>
		</tr>
		<tr>
			<td>Image noise level</td>
		</tr>
		<tr>
			<td>MINS Output</td>
		</tr>
		<tr>
			<td>Segmentation Z-stack with nuclei IDs</td>
		</tr>
		<tr>
			<td>Nuclear volume</td>
		</tr>
		<tr>
			<td>XYZ coordinates for each nucleus</td>
		</tr>
		<tr>
			<td>Average and summation of fluorescence values for each fluorescence channel and nucleus&#160;</td>
		</tr>
		<tr>
			<td>Advantages</td>
		</tr>
		<tr>
			<td>Accurate segmentation (&#62;85%) of nuclei throughout the stack &#8212; recognizes all occurrences of a nucleus in adjacent z-sections</td>
		</tr>
		<tr>
			<td>Single cell resolution</td>
		</tr>
		<tr>
			<td>Unsupervised segmentation of batches of embryos</td>
		</tr>
		<tr>
			<td>Segmentation pipelines can either be saved and re-used or adjusted for each particular embryo</td>
		</tr>
	</tbody>
</table>
Table 1. MINS Features
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td rowspan="3">Load Image</td>
			<td>At the prompt, introduce the Z relative resolution for the image. It can be obtained from the file metadata using the default reader or applying the following formula: X (or Y) resolution/Z resolution (all in &#181;m).</td>
		</tr>
		<tr>
			<td>Enter the sequence number (1 - 5) for the channel to be segmented. Using the DNA stain channel for segmentation will detect all cells in the image, however, other channels may be segmented separately too.</td>
		</tr>
		<tr>
			<td>Enter the frame to begin segmentation at (1 by default). Only applies to files with multiple time frames.</td>
		</tr>
		<tr>
			<td>Enhance Image (optional)</td>
			<td>The white and black point of the image can be adjusted to facilitate detection. Generally lowering the white point and re-scaling to 0 - 255 (for 8-bit images) or 0 - 4096 (for 12-bit images) will make the image brighter and facilitate detection of dim nuclei.</td>
		</tr>
		<tr>
			<td rowspan="2">Detect Nuclei</td>
			<td>Select the estimated nuclear diameter (generally between 30 and 40 px in blastocysts).</td>
		</tr>
		<tr>
			<td>For noisy images the noise level can be adjusted. Otherwise, the default value will be applied.</td>
		</tr>
		<tr>
			<td>Segment Nuclei</td>
			<td>Use default parameters.</td>
		</tr>
		<tr>
			<td>Classify Nuclei</td>
			<td>MINS can distinguish trophectoderm (TE) from inner cell mass (ICM) cells in preimplantation embryos based on position. This can also be done manually or based on fluorescence levels if a TE marker is used.</td>
		</tr>
		<tr>
			<td rowspan="5">Export Results</td>
			<td>Select the files to be generated:</td>
		</tr>
		<tr>
			<td>- segmentation overlaid over the channel used (.tiff sequence file),&#160;</td>
		</tr>
		<tr>
			<td>- segmentation only (.tiff sequence file),</td>
		</tr>
		<tr>
			<td>- spreadsheet with IDs for all cells detected, XYZ coordinates and fluorescence levels (average and sum) for all channels for each cell (.csv file).&#160;</td>
		</tr>
		<tr>
			<td>All files exported by default. Files are saved in the same directory where images are located.</td>
		</tr>
	</tbody>
</table>
Table 2. MINS Segmentation Pipeline

Watch this Scientific Journal Video about Quantitative Analysis of Protein Expression to Study Lineage Specification in Mouse Preimplantation Embryos at JoVE.com

Quantitative Analysis of Protein Expression to Study Lineage Specification in Mouse Preimplantation Embryos

This protocol presents a method to perform quantitative, single-cell in situ analysis of protein expression to study lineage specification in mouse preimplantation embryos. The procedures necessary for collection of blastocysts, whole-mount immunofluorescent detection of proteins, imaging of samples on a confocal microscope, and nuclear segmentation and image analysis are described.

This protocol presents a method to perform quantitative, single-cell in situ analyses of protein expression to study lineage specification in mouse ...

quantitative-analysis-protein-expression-to-study-lineage

Nanyang Technological University

Research

JoVE Journal

Developmental Biology

10.8K Views.  Sloan Kettering Institute.  Dit protocol geeft een werkwijze kwantitatieve eencellige voeren in situ analyse van eiwitexpressie van afstamming specificatie mouse pre-implantatie embryo bestuderen. De noodzakelijke voor het verzamelen van blastocysten procedures, whole-mount immunofluorescentie detectie van eiwitten, beeldvorming van de monsters op een confocale microscoop, en nucleaire segmentatie en beeldanalyse worden beschreven. 

Video: Quantitative Analysis of Protein Expression to Study Lineage Specification in Mouse Preimplantation Embryos

Loss- and Gain-of-function Approach to Investigate Early Cell Fate Determinants in Preimplantation Mouse Embryos

Gene silencing and overexpression techniques are instrumental for the identification of genes involved in embryonic development. Direct target gene modification in preimplantation embryos provides a means to study the underlying mechanisms of genes implicated in, for instance, cellular differentiation into the trophectoderm (TE) and the inner cell mass (ICM). Here, we describe a protocol that examines the role of neogenin as an authentic receptor for initial cell fate determination in preimplantation mouse embryos. First, we discuss the experimental manipulations that were used to produce gain and loss of neogenin function by microinjecting neogenin cDNA and shRNA; the effectiveness of this approach was confirmed by a strong correlation between the pair-wise expression levels of either red fluorescent protein (RFP) or green fluorescent protein (GFP) and the immunocytochemical quantification of neogenin expression. Secondly, overexpression of neogenin in preimplantation mouse embryos leads to normal ICM development while neogenin knockdown causes the ICM to develop abnormally, implying that neogenin could be a receptor that relays extracellular cues to drive blastomeres to early cell fates. Given the success of this detailed protocol in investigating the function of a novel embryonic developmental stage-specific receptor, we propose that it has the potential to aid in exploration and identification of other stage-specific genes during embryogenesis.

The goal of this protocol is to describe a loss- and gain-of function method that is applicable to identify neogenin as a stage-specific receptor that leads to trophectoderm and inner cell mass differentiation in preimplantation mouse embryos.

 Gene silencing and overexpression techniques are instrumental for the identification of genes involved in embryonic development. Direct target gene ...

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 ...

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

During somitogenesis, pairs of epithelial somites form in a progressive manner, budding off from the anterior end of the pre-somitic mesoderm (PSM) with a strict species-specific periodicity. The periodicity of the process is regulated by a molecular oscillator, known as the "segmentation clock," acting in the PSM cells. This clock drives the oscillatory patterns of gene expression across the PSM in a posterior-anterior direction. These so-called clock genes are key components of three signaling pathways: Wnt, Notch, and fibroblast growth factor (FGF). In addition, Notch signaling is essential for synchronizing intracellular oscillations in neighboring cells. We recently gained insight into how this may be mechanistically regulated. Upon ligand activation, the Notch receptor is cleaved, releasing the intracellular domain (NICD), which moves to the nucleus and regulates gene expression. NICD is highly labile, and its phosphorylation-dependent turnover acts to restrict Notch signaling. The profile of NICD production (and degradation) in the PSM is known to be oscillatory and to resemble that of a clock gene. We recently reported that both the Notch receptor and the Delta ligand, which mediate intercellular coupling, themselves exhibit dynamic expression at both the mRNA and protein levels. In this article, we describe the sensitive detection methods and detailed image analysis tools that we used, in combination with the computational modeling that we designed, to extract and overlay expression data from distinct points in the expression cycle. This allowed us to construct a spatio-temporal picture of the dynamic expression profile for the receptor, the ligand, and the Notch target clock genes throughout an oscillation cycle. Here, we describe the protocols used to generate and culture the PSM explants, as well as the procedure to stain for the mRNA or protein. We also explain how the confocal images were subsequently analyzed and temporally ordered computationally to generate ordered sequences of clock expression snapshots, hereafter defined as "kymographs," for the visualization of the spatiotemporal expression of Delta-like1 (Dll1) and Notch1 throughout the PSM.

The segmentation clock drives oscillatory gene expression across the pre-somitic mesoderm (PSM). Dynamic Notch activity is key to this process. We use imaging and computational analyses to extract temporal dynamics from spatial expression data to demonstrate that Delta ligand and Notch receptor expression oscillate in the vertebrate PSM.

During somitogenesis, pairs of epithelial somites form in a progressive manner, budding off from the anterior end of the pre-somitic mesoderm (PSM) with a ...

Robust Comparison of Protein Levels Across Tissues and Throughout Development Using Standardized Quantitative Western Blotting

Western blotting is a technique that is commonly used to detect and quantify protein expression. Over the years, this technique has led to many advances in both basic and clinical research. However, as with many similar experimental techniques, the outcome of Western blot analyses is easily influenced by choices made in the design and execution of the experiment. Specific housekeeping proteins have traditionally been used to normalize protein levels for quantification, however, these have a number of limitations and have therefore been increasingly criticized over the past few years. Here, we describe a detailed protocol that we have developed to allow us to undertake complex comparisons of protein expression variation across different tissues, mouse models (including disease models), and developmental timepoints. By using a fluorescent total protein stain and introducing the use of an internal loading standard, it is possible to overcome existing limitations in the number of samples that can be compared within experiments and systematically compare protein levels across a range of experimental conditions. This approach expands the use of traditional western blot techniques, thereby allowing researchers to better explore protein expression across different tissues and samples.

This method describes a robust and reproducible approach for the comparison of protein levels in different tissues and at different developmental timepoints using a standardized quantitative western blotting approach.

Western blotting is a technique that is commonly used to detect and quantify protein expression. Over the years, this technique has led to many advances ...

Biochemistry

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 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.

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

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Single cell mRNA sequencing has made significant progress in the last several years and has become an important tool in the field of developmental biology. It has been successfully used to identify rare cell populations, discover novel marker genes, and decode spatial and temporal developmental information. The single cell method has also evolved from the microfluidic based Fluidigm C1 technology to the droplet-based solutions in the last two to three years. Here we used the heart as an example to demonstrate how to profile the mouse embryonic tissue cells using the droplet based scRNA-Seq method. In addition, we have integrated two strategies into the workflow to profile multiple samples in a single experiment. Using one of the integrated methods, we have simultaneously profiled more than 9,000 cells from eight heart samples. These methods will be valuable to the developmental biology field by providing a cost-effective way to simultaneously profile single cells from different genetic backgrounds, developmental stages, or anatomical locations.

Here we presented a multiplexed single cell mRNA sequencing method to profile gene expression in mouse embryonic tissues. The droplet-based single cell mRNA sequencing (scRNA-Seq) method in combination with multiplexing strategies can profile single cells from multiple samples simultaneously, which significantly reduces reagent costs and minimizes experimental batch effects.

Single cell mRNA sequencing has made significant progress in the last several years and has become an important tool in the field of developmental ...

Preparation of Small RNA Libraries for Sequencing from Early Mouse Embryos

MicroRNAs (miRNAs) are important for the complex regulation of cell fate decisions and developmental timing. In vivo studies of the contribution of miRNAs during early development are technically challenging due to the limiting cell number. Moreover, many approaches require a miRNA of interest to be defined in assays such as northern blotting, microarray, and qPCR. Therefore, the expression of many miRNAs and their isoforms have not been studied during early development. Here, we demonstrate a protocol for small RNA sequencing of sorted cells from early mouse embryos to enable relatively unbiased profiling of miRNAs in early populations of neural crest cells. We overcome the challenges of low cell input and size selection during library preparation using amplification and gel-based purification. We identify embryonic age as a variable accounting for variation between replicates and stage-matched mouse embryos must be used to accurately profile miRNAs in biological replicates. Our results suggest that this method can be broadly applied to profile the expression of miRNAs from other lineages of cells. In summary, this protocol can be used to study how miRNAs regulate developmental programs in different cell lineages of the early mouse embryo.

We describe a technique for profiling microRNAs in early mouse embryos. This protocol overcomes the challenge of low cell input and small RNA enrichment. This assay can be used to analyze changes in miRNA expression over time in different cell lineages of the early mouse embryo.

MicroRNAs (miRNAs) are important for the complex regulation of cell fate decisions and developmental timing. In vivo studies of the contribution of miRNAs ...

Cell-Lineage Guided Mass Spectrometry Proteomics in the Developing (Frog) Embryo

Characterization of molecular events as cells give rise to tissues and organs raises a potential to better understand normal development and design efficient remedies for diseases. Technologies enabling accurate identification and quantification of diverse types and large numbers of proteins would provide still missing information on molecular mechanisms orchestrating tissue and organism development in space and time. Here, we present a mass spectrometry-based protocol that enables the measurement of thousands of proteins in identified cell lineages in Xenopus laevis (frog) embryos. The approach builds on reproducible cell-fate maps and established methods to identify, fluorescently label, track, and sample cells and their progeny (clones) from this model of vertebrate development. After collecting cellular contents using microsampling or isolating cells by dissection or fluorescence-activated cell sorting, proteins are extracted and processed for bottom-up proteomic analysis. Liquid chromatography and capillary electrophoresis are used to provide scalable separation for protein detection and quantification with high-resolution mass spectrometry (HRMS). Representative examples are provided for the proteomic characterization of neural-tissue fated cells. Cell-lineage-guided HRMS proteomics is adaptable to different tissues and organisms. It is sufficiently sensitive, specific, and quantitative to peer into the spatio-temporal dynamics of the proteome during vertebrate development.

Cell-Lineage Guided Mass Spectrometry Proteomics in the Developing Frog Embryo

Here we describe a mass spectrometry-based proteomic characterization of cell lineages with known tissue fates in the vertebrate Xenopus laevis embryo.

Characterization of molecular events as cells give rise to tissues and organs raises a potential to better understand normal development and design ...

Chemistry

Chromatin Immunoprecipitation Assay for Tissue-specific Genes using Early-stage Mouse Embryos

Chromatin immunoprecipitation (ChIP) is a powerful tool to identify protein:chromatin interactions that occur in the context of living cells 1-3. This technique has been widely exploited in tissue culture cells, and to a lesser extent, in primary tissue. The application of ChIP to rodent embryonic tissue, especially at early times of development, is complicated by the limited amount of tissue and the heterogeneity of cell and tissue types in the embryo. Here we present a method to perform ChIP using a dissociated embryonic day 8.5 (E8.5) embryo. Sheared chromatin from a single E8.5 embryo can be divided into up to five aliquots, which allows the investigator sufficient material for controls and for investigation of specific protein:chromatin interactions.
We have utilized this technique to begin to document protein:chromatin interactions during the specification of tissue-specific gene expression programs. The heterogeneity of cell types in an embryo necessarily restricts the application of this technique because the result is the detection of protein:chromatin interactions without distinguishing whether the interactions occur in all, a subset of, or a single cell type(s). However, examination of tissue-specific genes during or following the onset of tissue-specific gene expression is feasible for two reasons. First, immunoprecipitation of tissue specific factors necessarily isolates chromatin from the cell type where the factor is expressed. Second, immunoprecipitation of coactivators and histones containing post-translational modifications that are associated with gene activation should only be found at genes and gene regulatory sequences in the cell type where the gene is being or has been activated. The technique should be applicable to the study of most tissue-specific gene activation events.
In the example described below, we utilized E8.5 and E9.5 mouse embryos to examine factor binding at a skeletal muscle specific gene promoter. Somites, which are the precursor tissues from which the skeletal muscles of the trunk and limbs will form, are present at E8.5-9.54,5. Myogenin is a regulatory factor required for skeletal muscle differentiation 6-9. The data demonstrate that myogenin is associated with its own promoter in E8.5 and E9.5 embryos. Because myogenin is only expressed in somites at this stage of development 6,10, the data indicate that myogenin interactions with its own promoter have already occurred in skeletal muscle precursor cells in E8.5 embryos.

We demonstrate a chromatin immunoprecipitation (ChIP) method to identify factor interactions at tissue-specific genes during or after the onset of tissue-specific gene expression in mouse embryonic tissue. This protocol should be widely applicable for the study of tissue-specific gene activation as it occurs during normal embryonic development.

Chromatin immunoprecipitation (ChIP) is a powerful tool to identify protein:chromatin interactions that occur in the context of living cells 1-3. This ...

Biology

Isolation and Genotyping of Gastrulating Mouse Embryo for Single-Cell Sequencing

Single-Cell RNA Sequencing of Mutant Whole Mouse Embryos: From the Epiblast to the End of Gastrulation

Over the last decade, single-cell approaches have become the gold standard for studying gene expression dynamics, cell heterogeneity, and cell states within samples. Before single-cell advances, the feasibility of capturing the dynamic cellular landscape and rapid cell transitions during early development was limited. In this paper, a robust pipeline was designed to perform single-cell and nuclei analysis on mouse embryos from embryonic day E6.5 to E8, corresponding to the onset and completion of gastrulation. Gastrulation is a fundamental process during development that establishes the three germinal layers: mesoderm, ectoderm, and endoderm, which are essential for organogenesis. Extensive literature is available on single-cell omics applied to wild-type perigastrulating embryos. However, single-cell analysis of mutant embryos is still scarce and often limited to FACS-sorted populations. This is partially due to the technical constraints associated with the need for genotyping, timed pregnancies, the count of embryos with desired genotypes per pregnancy, and the number of cells per embryo at these stages. Here, a methodology is presented designed to overcome these limitations. This method establishes breeding and timed pregnancy guidelines to achieve a higher chance of synchronized pregnancies with desired genotypes. Optimization steps in the embryo isolation process coupled with a same-day genotyping protocol (3 h) allow for microdroplet-based single-cell to be performed on the same day, ensuring the high viability of cells and robust results. This method further includes guidelines for optimal nuclei isolations from embryos. Thus, these approaches increase the feasibility of single-cell approaches of mutant embryos at the gastrulation stage. We anticipate that this method will facilitate the analysis of how mutations shape the cellular landscape of the gastrula.

Author Spotlight: A Pipeline to Analyze Lineage-Specific Mutant Embryos at Single-Cell Resolution

This paper establishes a pipeline for high-quality single-cell and nuclei suspensions of gastrulating mouse embryos for sequencing of single cells and nuclei.

Over the last decade, single-cell approaches have become the gold standard for studying gene expression dynamics, cell heterogeneity, and cell states ...

Quantitative Analysis of Protein Expression to Study Lineage Specification in Mouse Preimplantation Embryos

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