The authors would like to express their sincere gratitude to Professor Nicolas Bayens for generously providing access to the confocal microscope essential for this study.&#160;This work was funded in part by the Funds for Scientific Research (FNRS) under Grant Numbers F451218F and UG03019F, the Alzheimer Research Foundation (SAO-FRA) (to V.W.), A.M. is supported by a Research Fellowship from the FNRS. Figure 1&#160;was created on biorender.com.

Zebrafish were maintained under standard conditions, according to FELASA42 and institutional (Universit&#233; Libre de Bruxelles, Brussels, Belgium; ULB) guidelines and regulations. All experimental procedures were approved by the ULB Ethical Committee for Animal Welfare (CEBEA) from the ULB.
1. Zebrafish husbandry and embryo preparation
NOTE: The zebrafish transgenic line Tg(mpeg1:eGFP)gl22 that expresses the fluorescent eGFP protein in macrophages, including microglia, was used to generate the tracking data shown in this protocol. Other macrophage reporter lines are available from ZIRC and can also be used. In choosing the transgenic line, it is important to consider that a high signal intensity will facilitate image acquisition and cell segmentation.
<ol>
	<li>Maintain zebrafish (Danio rerio) at a temperature of 28 &#176;C and manage them in accordance with established protocols11.</li>
	<li>Stimulate mating by placing female and male fish together in a breeding tank, with a mesh bottom and a separator, in the late afternoon before the desired embryos&#39; birth date. Remove the separator the following morning to time the mating of the fish.</li>
	<li>Collect the fertilized eggs using a mesh and transfer them to a 100 mm Petri dish containing E3 medium (5 mM NaCl, 0.17 mM KCl, 0.33 mM CaCl2, 0.33 mM MgSO4) with 0.01% Methylene blue. Depending on the genetic background of the zebrafish transgenic line used, if pigment formation is to be inhibited to facilitate imaging, add 0.003% of N-phenylthiourea (PTU) to the E3 buffer in which embryos are developing, starting at 6 h post fertilization (hpf) and refreshing the solution every 2 days until the desired developmental stage is reached. 
	NOTE: To avoid long exposure to PTU that could affect embryonic development12, it is suggested to use, if available, a transgenic line on a pigment-deficient background, such as Casperw2, that allows for clear imaging without the need to expose embryos to PTU for an extended period of time13.</li>
	<li>If the embryos to be imaged are younger than 3 days post fertilization (dpf), dechorionate them at 24 hpf. Use a stereo microscope to confirm that all embryos have been dechorionated and are undamaged by the enzymatic treatment (see step 1.4.2).
	<ol>
		<li>In case of a limited number of eggs, do this manually by using fine dissecting forceps to pinch the chorion and pull outwards, carefully releasing each embryo from its chorion.</li>
		<li>In case of a higher number of eggs, perform the dechorionation enzymatically by incubating the eggs in bulk at room temperature (RT) in a 1 mg/mL Pronase solution in E3 medium for a brief period (typically 5-10 min, until the chorions break open under gently swishing). Next, the Pronase solution is discarded, and the embryos are rinsed thoroughly 3x with fresh E3, to remove any remaining chorion and residual enzyme.</li>
	</ol>
	</li>
</ol>
2. Zebrafish mounting
<ol>
	<li>Prepare a 1% low melting agarose solution in E3 buffer. Cool the agarose to 37 &#176;C in a benchtop heating block and add freshly made Tricaine methanesulfonate solution (160 mg/L), which will help keep the embryos anesthetized during imaging. Vortex the solution to thoroughly homogenize it.</li>
	<li>Anesthetize the embryos by adding 160 mg/L of Tricaine methanesulfonate to the Petri dish containing the embryos in E3 buffer. Check to verify that movement has stopped and select the zebrafish embryos with the desired fluorescence. Check the embryo&#39;s health by visualizing its heartbeat using a brightfield stereo microscope. Using a wide-tipped transfer pipette draw up one, or up to three, of the selected embryos and transfer them to a bottom glass imaging plate.</li>
	<li>Under a stereo microscope, use a pipette to remove as much medium as possible, being careful not to touch or damage the embryos; then, replace the medium with the previously prepared 1% low melting agarose solution. Next, use a plastic thin-tapered tip fixed to the end of a teasing needle to gently push each embryo to the bottom of the imaging plate, orienting it so that its dorsal side is facing the glass to ensure a good view of the optic tectum and a minimal amount of low melting agarose in between the embryo and the glass.</li>
	<li>Image the mounted embryo promptly using an inverted confocal microscope featuring a high-quality Plan Apo Objective (10x/0.45 Plan Apo or a 20x/0.75 Plan Apo used here). If the timelapse will be running for an extended period (over an hour), add one or two drops of E3 buffer with Tricaine methanesulfonate (160 mg/L) to the bottom glass imaging plate to keep the low-melting agarose from drying excessively. 
	NOTE: It is crucial to wait for the agarose to completely solidify before adding E3 buffer and tricaine methanesulfonate media to the imaging disk; otherwise, the fish could move slowly laterally and axially, thus causing a sample drift in the timelapse.</li>
	<li>Proceed to set up the timelapse acquisition for the desired time: set the image resolution to 1,024 x 1,024, with a pixel size of 0.49 &#181;m. Collect optical slices in 2-3 &#181;m increments to ensure an acceptable resolution on the z-axis. In the zebrafish embryo, enclose the optic tectum in a 100-150 &#181;m z-stack, depending on the developmental stage used. To ensure successful cell tracking, keep the time interval between frames between 30 s and 60 s.</li>
</ol>
3. Tracking analysis and data export
<ol>
	<li>Convert the timelapse file into IMS format using the Imaris file converter software (see Table of Materials). Upon launching the software, either drag and drop the files into the input area or utilize the Add Files&#8230;&#160;button to select them manually. In the Output menu, designate the location for the converted files, opting for either the same folder as the input files or specifying a particular folder. Ensure the dimensions of the voxel size displayed are correct by clicking on the Set Voxel Size button and once the voxel size is verified, press the Start All button to start the file conversion (See Supplemental File 1 for a step-by-step guide of all the data analysis). 
	NOTE: If the timelapse was performed on two or more embryos in parallel, the file will be automatically split into single positions, separating each embryo into different files. It is possible to use the software in batch mode and upload and convert multiple files at the same time. IMS files will be created and saved in the selected destination folder or the folder where the input files are located.</li>
	<li>Once launched, let the analysis software start in the Arena; click on Observe Folder to open the previously converted file. Once the file is loaded into the software, use the Slice view to scroll through the z-stack, using the slider in the Slice Toolbar situated on the left of the View Area, and measure some cell diameters by drawing the diameter of the selected cells using the pointer. Click and drag the mouse to draw a segment spanning the cell core; observe the length of the segment drawn in the Measure Toolbar, situated on the right of the View Area. 
	NOTE: Using the imaging settings in step 2.5, the cell body diameter can be expected to be between 6 &#181;m and 8 &#181;m.</li>
	<li>To automatically detect the cells, go back to the 3D view and click on the spot icon in the Object Toolbar to add a new Spots object in the object list and open the automatic Spots creation wizard. In the first step of the wizard, tick the option to segment only a region of interest. Then, enable the Track Spots (over time) option to compute the tracking data, as well as the Object-Object Statistics to allow comparison between spots and expand the range of data that will be available later in the analysis. Finally, proceed in the wizard by clicking the Next button in the lower right of the wizard window.</li>
	<li>In the second step, proceed to specify a region of interest (ROI) area that encloses the optic tectum of the embryo. Modify the size of the ROI by clicking and dragging the small white arrows present on each face of it. Once the ROI size is defined, extend it to all the recorded frames by adjusting the time interval.</li>
	<li>Then, select as Source Channel the channel used to detect the cells, and set the cell diameter measurement, previously obtained in step 3.2, as the Estimated XY Diameter. Enable the Background Subtraction option and click on Next.</li>
	<li>At this point in the Spot creation wizard, the software incorporates a quality filtering step wherein spots are filtered by the signal intensity measured at the center of each spot; in the channel where the spots were detected. Adjust the intensity threshold by entering the value directly in the data field for lower and upper threshold boxes or by dragging the corresponding-colored lines in the histogram shown at the bottom of the creation wizard, so that all cells are detected, including those localized deeper in the tissue, which usually show a lower signal intensity. All these changes are simultaneously visible in the View Area. 
	NOTE: It is possible to observe multiple spots labeling a single cell at this point, but this can be corrected later in the analysis. 
	In longer timelapses, if some photobleaching is seen, check the View Area of multiple frames before setting the threshold to make sure that all cells are also detected in the most recent and therefore, fainter frames.</li>
	<li>Once satisfied, click on Next to validate the selected quality thresholding. All the spots satisfying the quality thresholding parameter and having a diameter matching with the Estimated XY Diameter will be labeled as a spot. Visualize this as a preview in the View Area, where spots satisfying these two parameters will be superimposed on the Source Channel.</li>
	<li>In the next step, select the Autoregressive Motion as the tracking algorithm to track cells that have a more or less continuous motion. Judge the longest distance a cell moves between two time points by carefully observing the motion of the spots in between two frames and enter an estimated number in the Max Distance field. This is the distance that a spot is allowed to deviate from the predicted future position.</li>
	<li>Set the Maximum Gap size to the least number of time points in which the spot may disappear without interrupting the track. If the interval between frames is below 60 s, use a size of 3. If the time interval between frames is longer, increase the maximum gap size allowed to reduce track fragmentation.</li>
	<li>Enable the Fill gaps with all detected objects to drop the detection threshold close to the expected position predicted by the tracking algorithm and connect tracks that are interrupted by a failure of the spot detection. Finally, click on Next and let the software automatically generate tracks for all the previously generated spots.</li>
	<li>If the obtained tracks appear to be too numerous or fragmented go back in the creation wizard, by clicking on the Previous button, and adjust the maximum distance previously defined, either increasing or decreasing the number until most of the obtained tracks are representative of the cell movements. 
	NOTE: The number of tracks should roughly match the number of microglia cells, therefore, ranging between 30 and 50, depending on the embryo&#39;s age. However, before completion of the analysis, a higher number is expected due to erroneous tracks.</li>
	<li>Once the tracks have been calculated, the software incorporates a filtering step to filter out all the very brief tracks as they are often inaccurate or not informative. Exclude tracks shorter than 3-8 minutes (min) by entering the value directly in the data field for the lower limit of the track duration filter, or by dragging the corresponding-colored lines in the histogram shown at the bottom of the creation wizard. Click on Next to validate the filter and move on in the creation wizard. 
	NOTE: As mentioned before, by modifying the maximum (max) and minimum (min) track duration threshold, it is possible to preview the tracks that will be filtered and excluded from the analysis. The filtered tracks can then be duplicated in a new object for further analysis. The exact time threshold for filtering may vary based on the results of the previous creation wizard step. We recommend fine-tuning these filter settings by reviewing the preview in the View Area for optimal results.</li>
	<li>Since the Tg(mpeg1:eGFP) transgenic line labels all mononuclear phagocytes, skin macrophages in addition to microglia will also be detected in timelapse movies. Manually remove the tracks generated from skin macrophages from the analysis to focus on brain parenchymal microglia (Figure 3).</li>
	<li>Manually correct other potential mistakes in the tracks in the track editor, where each data point is displayed as an object in the track. Activate the circle select mode button on the right of the View Area and highlight tracks that require modifications or adjustments. Once the problematic track is selected, using the connect and disconnect buttons, edit it to correctly represent the cell movements. Use the track editor to also select and delete duplicated single spots or small track fragments that erroneously represent the same cell by selecting them with the circle select mode and pressing Canc or Delete to eliminate them. 
	NOTE: If the settings of the tracking are correct, this step should be required for only a small percentage of the tracked cells.</li>
	<li>If the microglia reporter line is used in combination with fluorescent transgenics labeling other cell types in the parenchyma, perform segmentation as a new surface object or spot object to visualize them. To do so, repeat the steps above (from steps 3.2 to 3.14), modifying the Source Channel input in step 3.5, for it to be the one used to image the second cell population, and taking care of adapting the descriptive parameters specific to the cells of interest such as Estimated XY Diameter (step 3.5), Max Distance (step 3.8) to the new cell population. Other steps can be repeated without changes. 
	NOTE: In case of a new surface creation, Estimated XY Diameter is replaced by a thresholding option based on Background Subtraction, where the input to be given is the diameter of the largest sphere which fits into the object. This value can be estimated from the Slice view using the Measure toolbar as explained in step 3.2.</li>
	<li>Once satisfied with the obtained tracks, extract the desired tracking statistics from the Statistic tab. Clicking on the settings button, select which statistics will be computed for each spot object or surface object previously created. In case more objects have been created in the same analysis, two spot objects or a spot and a surface object, statistics depicting the relative position of one object to the other, such as the shortest distance between the two, will also be available to export. 
	NOTE: All the desired values can be either specific or average values, and all raw data are downloadable as a Comma Separated Values (CSV) file using the buttons at the bottom of the Statistics tab. Provided that the analysis also includes other cell types, additional statistics on the relative distance of one object to the other will also become available.</li>
</ol>

Elucidating Microglia Behavior in Zebrafish Optic Tectum Development

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(157), e60593 (2020).</li><li>Tayanloo-Beik, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Zebrafish+modeling+of+autism+spectrum+disorders,+current+status+and+future+prospective.">Zebrafish modeling of autism spectrum disorders, current status and future prospective.</a> Front Psychiatry. 13, 911770 (2022).</li><li>D'Amora, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Zebrafish+as+an+innovative+tool+for+epilepsy+modeling:+State+of+the+art+and+potential+future+directions.">Zebrafish as an innovative tool for epilepsy modeling: State of the art and potential future directions.</a> Int J Mol Sci. 24 (9), 7702 (2023).</li><li>Langova, V., Vales, K., Horacek, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+zebrafish+and+laboratory+rodents+in+schizophrenia+research.">The role of zebrafish and laboratory rodents in schizophrenia research.</a> Front Psychiatry. 11, 549232 (2020).</li><li>Chia, K., Klingseisen, A., Sieger, D., Priller, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Zebrafish+as+a+model+organism+for+neurodegenerative+disease.">Zebrafish as a model organism for neurodegenerative disease.</a> Front Mol Neurosci. 15, 940484 (2022).</li><li>Astell, K. R., Sieger, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Zebrafish+in+vivo+models+of+cancer+and+metastasis.">Zebrafish in vivo models of cancer and metastasis.</a> Cold Spring Harb Perspect Med. 10 (8), 037077 (2020).</li></ol>

The authors declare no conflicts of interest.

The current protocol enables in vivo imaging of microglia dynamics in a vertebrate embryo and visualization of the acquired motility data. Microglia colonization of the developing brain occurs very early during embryogenesis and precedes critical events such as peaks of neurogenesis, astrogliogenesis, oligodendrogenesis, and many other cellular processes17. It is therefore not surprising that microglia play important functions in shaping specific aspects of brain development18, for example, through the regulation of neuronal differentiation, migration, and survival19,20,21, as well as synaptic pruning5&#160;and myelination22,23,24.
The contribution of dysfunctional microglia to the pathogenesis and/or progression of neurodevelopmental disorders is also increasingly being recognized25. Indeed, the early presence of microglia in the forming brain exposes these cells to distinct physiological states26&#160;and environmental changes. This can have a significant impact given that microglia are long-lived cells in both rodents and humans, being maintained during the lifespan through self-renewal of local progenitors27,28,29. We believe this protocol could serve as a powerful tool to better characterize the behavior of microglia in these distinct physiological states, as they develop, mature, and establish their network during the successive steps of brain morphogenesis.
Using the setup described here, we have successfully imaged and acquired data on zebrafish larvae as old as 6 dpf. Extending the analysis to later developmental stages will likely succeed but will require adjusting the imaging setup to take into consideration the increased sample size, especially along the z-axis. In attempting this, we suggest focusing on maintaining a low signal-to-noise ratio and fast scanning time, as they are key parameters for a successful analysis.
We suggest a minimum imaging time of 1 h to allow for microglia tracking; the longest imaging window that has been tested with this protocol is 8 h. Moreover, it is important for the tracking analysis to keep the time interval between frames as short as possible, ideally between 30 s and 60 s. This will allow for more accurate and detailed tracking data in downstream analyses. Therefore, especially if detecting more than one fluorophore, it is fundamental to avoid spectral overlap and ensure enough separation between the two fluorophore emission spectra to allow for a simultaneous acquisition, without signal bleedthrough.
Other protocols for high-quality timelapse recording of the zebrafish brain are available30, but this is the first one showing how to successfully track all microglia movement during embryonic development over an extended period. Although the workflow presented here focused on tracking microglia in a physiological context, it can be easily applied to the analysis of microglia in pathology. Indeed, several models of neurodevelopmental disorders, such as autism31, epilepsy32, and schizophrenia33, but also neurodegeneration34&#160;and cancer35, have been established in zebrafish that provide unique opportunities for determining microglial response and behavior in disease conditions.
Notably, this tracking protocol is highly versatile and could also be instrumental for shedding light on the migration patterns of various cell types across diverse anatomical regions of the zebrafish embryo, thus potentially opening up avenues for additional applications, beyond the microglial investigation scope described in this article. Moreover, by harnessing the ability to combine multiple fluorescent transgenic lines, we gain the ability to discern the spatial relationship between microglia and other cell types of the brain microenvironment, with the potential to visualize cellular interactions and cross-talks throughout timelapse recordings, in a non-invasive way. This could be instrumental in unraveling the physiological significance of microglia behavior and contribute to a deeper characterization of these highly motile cells.

As resident macrophages in the central nervous system (CNS), microglia represent a distinct non-neuronal population that accounts for up to 15% of all glial cells in the adult brain. Studying microglia biology has gained increasing attention in recent years due to their established importance in development, physiology, and disease1. Under physiological conditions, microglial cells are highly dynamic, continuously surveying the brain parenchyma2,3. This behavior allows microglia to colonize the brain and play pivotal roles in its development such as shaping neuronal circuitry4, synaptic pruning5, and vasculogenesis6. Furthermore, this inherent dynamic nature allows microglia to constantly monitor the CNS for signs of infection, injury, or any deviations from homeostasis7. To dissect these intricate cell dynamics, live imaging of microglia across space and time is indispensable. Fortunately, the optical transparency of externally developing zebrafish embryos, coupled with the availability of well-characterized transgenic reporter lines that fluorescently label microglia, positions zebrafish as an ideal vertebrate model for such investigations. Live imaging in zebrafish embryos offers a non-invasive approach that does not require surgery or extensive tissue manipulation, minimizing potential perturbations to the CNS status. This is a critical consideration when studying microglial cells, as they are highly sensitive to even subtle changes in the extracellular environment8.
Here, we provide a guideline to successfully track 3D microglial cell movements in the zebrafish embryo, allowing for an unprecedented view of microglia behavior within the intact architecture of the developing brain parenchyma (see Figure 1&#160;for a graphical overview of the protocol). This step-by-step protocol details how to set up and image zebrafish microglia at different developmental stages and how to extract high-resolution data on microglia cell motility to provide valuable insights into their migratory patterns and responses to environmental cues. We also demonstrate this protocol can be adapted to perform live multi-color imaging, thus extending its applicability to studying microglia in combination with transgenic lines that mark neighboring cells, including neurons3, oligodendrocytes9, and endothelial cells10&#160;(as shown in Figure 2). By adding to the toolbox that allows one to directly observe and characterize the dynamics of microglia behavior&#160;in real time and in their natural environment, this protocol will likely contribute to better elucidating microglia functionality during early development, both in physiology and disease.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1 L Breeding tanks</td>
			<td>Tecniplast</td>
			<td>ZB10BTE</td>
			<td></td>
		</tr>
		<tr>
			<td>1-phenyl-2-thiourea (PTU)</td>
			<td>Sigma-Aldrich</td>
			<td>P7629</td>
			<td>Diluted to 0.2 mM in E3 to prevent embryo pigmentation</td>
		</tr>
		<tr>
			<td>Bottom glass imaging dish</td>
			<td>FluoroDish</td>
			<td>FD3510-100</td>
			<td></td>
		</tr>
		<tr>
			<td>Disposable Graduated transfer pipette</td>
			<td>avantor</td>
			<td>16001-188</td>
			<td></td>
		</tr>
		<tr>
			<td>Dry block heater</td>
			<td>Novolab</td>
			<td>Grant QBD4</td>
			<td>To keep low melting agarose at 37 &#176;C</td>
		</tr>
		<tr>
			<td>Ethyl 3-aminobenzoate methanesulfonate (Tricaine)</td>
			<td>Sigma-Aldrich</td>
			<td>E10521-50G</td>
			<td></td>
		</tr>
		<tr>
			<td>Imaris 10.0</td>
			<td>Oxford Instruments</td>
			<td></td>
			<td>analysis software</td>
		</tr>
		<tr>
			<td>Imaris File Converter</td>
			<td>Oxford Instruments</td>
			<td></td>
			<td>https://imaris.oxinst.com/big-data</td>
		</tr>
		<tr>
			<td>Laser-scanning confocal microscope</td>
			<td>Nikon</td>
			<td>Eclipse Ti2-E</td>
			<td></td>
		</tr>
		<tr>
			<td>Methylene blue</td>
			<td>Sigma-Aldrich</td>
			<td>M9140-25G</td>
			<td></td>
		</tr>
		<tr>
			<td>microloader tips</td>
			<td>Eppendorf</td>
			<td>5242956003</td>
			<td></td>
		</tr>
		<tr>
			<td>NuSieve GTG Agarose</td>
			<td>Lonza</td>
			<td>&#160;50081</td>
			<td></td>
		</tr>
		<tr>
			<td>Petri dishes (90 mm)</td>
			<td>avantor</td>
			<td>391-0559</td>
			<td></td>
		</tr>
		<tr>
			<td>Pronase</td>
			<td>Sigma-Aldrich</td>
			<td>11459643001</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Stainless Steel Forceps Dumont No. 5</td>
			<td>FineScienceTools</td>
			<td>11254-20</td>
			<td></td>
		</tr>
		<tr>
			<td>Stereo microscope</td>
			<td>Leica</td>
			<td>Leica M80</td>
			<td>To mount the embryos</td>
		</tr>
		<tr>
			<td>teasing needle</td>
			<td>avantor</td>
			<td>76549-024</td>
			<td></td>
		</tr>
	</tbody>
</table>

live imaging and characterization of microglia dynamics in the zebrafish embryo

Microglia are highly dynamic cells and their migration and colonization of the brain parenchyma is a crucial step for proper brain development and function. Externally developing zebrafish embryos possess optical transparency, which along with well-characterized transgenic reporter lines that fluorescently label microglia, make zebrafish an ideal vertebrate model for such studies. In this paper, we take advantage of the unique features of the zebrafish model to visualize the dynamics of microglia cells in vivo and under physiological conditions. We use confocal microscopy to record a timelapse of microglia cells in the optic tectum of the zebrafish embryo and then, extract tracking data using the IMARIS 10.0 software to obtain the cells' migration path, mean speed, and distribution in the optic tectum at different developmental stages. This protocol can be a useful tool to elucidate the physiological significance of microglia behavior in various contexts, contributing to a deeper characterization of these highly motile cells.

Microglial cells expressing Green fluorescent protein (eGFP) and endothelial cells expressing DsRed in Tg(mpeg1:eGFPgl22; kdrl:cres898; actb2:loxP-STOP-loxP-DsRedexpress,sd5) triple transgenic embryos14 were imaged at 3 dpf, according to the described protocol. A single zebrafish embryo was mounted in 1% low melting agarose on a bottom glass plate and the imaging process did not hinder the embryo&#39;s growth during the acquisition time. The timelapse was recorded using a commercial point-scanning confocal microscopy system equipped with a 10x 0.45 NA dry objective lens, and 488 nm and 561 nm excitation lasers were used for imaging microglia and endothelial cells, respectively. In addition, the time interval, image resolution, pixel size, and z step were 30 seconds (s), 1024x1024, 0.49 &#181;m, and 2.5 &#181;m, respectively. The timelapse recording lasted 3.5 hours (h).
The acquired field of view covered the whole head of the embryo, but the analysis focused specifically on the optic tectum, as during the first week of development, microglia are mainly restricted to the neuronal soma layer of this region of the dorsal midbrain, allowing investigators to visualize the whole population simultaneously15. The 3D tracking analysis was performed using Imaris 10.0, as explained above. As shown in Figure 4, the tracking was successful, resulting in 25 tracks, matching the expected number of microglia cells present in the optic tectum at 3 dpf16. A minimal manual tracks correction was required. Figure 5 shows an example of the data that is possible to extract from a successful tracking experiment. The simultaneous labeling of macrophages and endothelial cells allows for the quantification of microglia&#39;s position relative to the latter, allowing researchers to visualize each cell&#39;s relative distance to the closest endothelial cell in time and examine the frequency and number of potential interactions (Figure 5).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/66533/66533fig01.jpg" /> 
Figure 1: Overview of the experimental procedure. (A) Zebrafish embryo preparation and anesthesia. (B) Sample mounting and positioning. (C) Image acquisition. (D) Image processing and extraction of motility data. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/66533/66533fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/66533/66533fig02.jpg" /> 
Figure 2: Microglia imaging and interactions with the brain cellular environment in the zebrafish embryo. (A) Brightfield image of a 3 dpf embryonic zebrafish head and brain (dorsal view), labeling the optic tectum and hindbrain. The brain of the embryonic zebrafish can be imaged in its entirety at this stage due to its small size and optical transparency. (B-D) Microglia location and behavior can be visualized by the use of transgenic lines such as (B,C) Tg(mpeg1:eGFP)gl22 and (D) Tg(mpeg1:mcherry)gl23, and focusing on the OT. (B) Neurons and their cell bodies can be identified using the reporter line Tg(XlTubb:DsRed)zf148 and microglia-neuron interactions can be visualized by merging the two channels in lines that co-express both transgenes. Seen is a merge of the green (microglia) and red (neurons, in magenta) signals. (C,D) Reporter lines can also shed light on microglia (in green) interactions with endothelial cells, here labeled in red using the (C) double Tg(kdrl:cres898; actb2:LOXP-STOP-LOXP-Dsredexpress, sd5) transgenics, or with glial cells such as oligodendrocytes and their precursors, using the (D) double Tg(olig2:EGFP; mpeg1:mcherry ) transgenic line. 1: oligodendrocytes and progenitor cells in the OT, 2: eurydendroid neurons in the cerebellum. Scale bars = 50 &#181;m. Abbreviations: dpf = days post fertilization; OT = optic tectum; HB = hindbrain. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/66533/66533fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/66533/66533fig03.jpg" /> 
Figure 3: Morphological and spatial disparity between skin macrophages and microglia in a 3 dpf zebrafish embryo. (A,B) Dorsal view of a Tg(mpeg1:eGFP)gl22 zebrafish embryo at 3 dpf, depicting (A) parenchymal microglia cells (marked by magenta asterisks) versus skin macrophages (white asterisks), identified based on their relative position along the z-axis, as seen in (B), which shows the monochrome 3D image rendered with z-axis color-coding. (C,D) Lateral view of (C) A and (D) B, showcasing the z-depths of mpeg1:eGFP+ cells within the embryo&#39;s head and highlighting the superficial localization of skin macrophages as compared to microglial cells. (E-K) High magnification of each cell indicated by an asterisk in A and B, providing a detailed visualization of the distinct morphologies between (E-G) amoeboid microglia and (H-K) elongated skin macrophages. Scale bars= 30 &#181;m. Abbreviation: dpf = days post fertilization. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/66533/66533fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/66533/66533fig04.jpg" /> 
Figure 4: Tracking of microglial cells in a 3 dpf zebrafish embryo. (A) Head dorsal view of a 3 dpf Tg(kdrl:cres898; actb2:LOXP-STOP-LOXP-Dsredexpress,sd5;mpeg1:eGFPgl22) triple transgenic embryo, showing microglia (green) and the surface rendering of the vessels (magenta). (B-D) Representative tracking of microglia movements over a (B) 3.5 h time window. Individual cells are seen to follow complex trajectories. (C) Detail from timelapse, showing a magnified view of the region in B enclosed by the dashed square. Six frames from the movie (45 min apart) are presented, documenting microglia establishing transient contacts with endothelial cells in their microenvironment. (D) Trajectories of individual microglial cell migration within the optic tectum, with the X, Y, and Z axes representing spatial dimensions. Scale bar = 50 &#181;m. Abbreviation: dpf = days post fertilization. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/66533/66533fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/66533/66533fig05.jpg" /> 
Figure 5: Visualization of the data obtained. Example of the spatial data that can be obtained using the described protocol. The graphs depict (A) the average speed of microglial cells, (B) the average distance they cover in 1 h, (C) their mean square displacement, and (D) their distribution in space at different times. The vessel&#39;s surface rendering also allowed for the measurement of the shortest distance between microglia and endothelial cells at any given time, both at (E) single-cell level and as a (F) global average. For A,B, and D, each dot represents an individual cell. N = one embryo. <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/66533/66533fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplemental File 1: <a href="https://jove.unicartagenaproxy.elogim.com/files/ftp_upload/66533/66533_20240306_SupplementalFile1 (2).zip" target="_blank">Please click here to download this File.</a>

Read this Scientific Article Protocol about Live Imaging and Characterization of Microglia Dynamics in the Zebrafish Embryo at JoVE.com

Author Spotlight: Using Zebrafish to Explore Microglia Migration During Brain Development

We demonstrate a method that takes advantage of fast scanning confocal microscopy to perform live imaging of microglia cells in the developing zebrafish optic tectum, allowing for the analysis of the dynamics of these cells in vivo.

Live Imaging and Characterization of Microglia Dynamics in the Zebrafish Embryo

Microglia are highly dynamic cells and their migration and colonization of the brain parenchyma is a crucial step for proper brain development and ...

live-imaging-characterization-microglia-dynamics-zebrafish

Universidad de Cartagena UDEC

Research

JoVE Journal

Immunology and Infection

930 Views.  Université Libre de Bruxelles (ULB). We demonstrate a method that takes advantage of fast scanning confocal microscopy to perform live imaging of microglia cells in the developing zebrafish optic tectum, allowing for the analysis of the dynamics of these cells in vivo.

Video: Author Spotlight: Using Zebrafish to Explore Microglia Migration During Brain Development

In vivo Imaging of Transgenic Leishmania Parasites in a Live Host

Distinct species of Leishmania, a protozoan parasite of the family Trypanosomatidae, typically cause different human disease manifestations. The most common forms of disease are visceral leishmaniasis (VL) and cutaneous leishmaniasis (CL). Mouse models of leishmaniasis are widely used, but quantification of parasite burdens during murine disease requires mice to be euthanized at various times after infection. Parasite loads are then measured either by microscopy, limiting dilution assay, or qPCR amplification of parasite DNA. The in vivo imaging system (IVIS) has an integrated software package that allows the detection of a bioluminescent signal associated with cells in living organisms. Both to minimize animal usage and to follow infection longitudinally in individuals, in vivo models for imaging Leishmania spp. causing VL or CL were established. Parasites were engineered to express luciferase, and these were introduced into mice either intradermally or intravenously. Quantitative measurements of the luciferase driving bioluminescence of the transgenic Leishmania parasites within the mouse were made using IVIS. Individual mice can be imaged multiple times during longitudinal studies, allowing us to assess the inter-animal variation in the initial experimental parasite inocula, and to assess the multiplication of parasites in mouse tissues. Parasites are detected with high sensitivity in cutaneous locations. Although it is very likely that the signal (photons/second/parasite) is lower in deeper visceral organs than the skin, but quantitative comparisons of signals in superficial versus deep sites have not been done. It is possible that parasite numbers between body sites cannot be directly compared, although parasite loads in the same tissues can be compared between mice. Examples of one visceralizing species (L. infantum chagasi) and one species causing cutaneous leishmaniasis (L. mexicana) are shown. The IVIS procedure can be used for monitoring and analyzing small animal models of a wide variety of Leishmania species causing the different forms of human leishmaniasis.

In vivo Imaging of Transgenic Leishmania Parasites in a Live Host

An in vivo imaging system is used to generate quantitative measurements of murine infection with the Trypanosomatid protozoan Leishmania. This is a non-invasive and non-lethal method for detecting parasites expressing luciferase within many tissues throughout the course of chronic Leishmania spp. infection.

Distinct species of Leishmania, a protozoan parasite of the family Trypanosomatidae, typically cause different human disease manifestations. The most ...

Use of an Optical Trap for Study of Host-Pathogen Interactions for Dynamic Live Cell Imaging

Dynamic live cell imaging allows direct visualization of real-time interactions between cells of the immune system1, 2; however, the lack of spatial and temporal control between the phagocytic cell and microbe has rendered focused observations into the initial interactions of host response to pathogens difficult. Historically, intercellular contact events such as phagocytosis3 have been imaged by mixing two cell types, and then continuously scanning the field-of-view to find serendipitous intercellular contacts at the appropriate stage of interaction. The stochastic nature of these events renders this process tedious, and it is difficult to observe early or fleeting events in cell-cell contact by this approach. This method requires finding cell pairs that are on the verge of contact, and observing them until they consummate their contact, or do not. To address these limitations, we use optical trapping as a non-invasive, non-destructive, but fast and effective method to position cells in culture.
Optical traps, or optical tweezers, are increasingly utilized in biological research to capture and physically manipulate cells and other micron-sized particles in three dimensions4. Radiation pressure was first observed and applied to optical tweezer systems in 19705, 6, and was first used to control biological specimens in 19877. Since then, optical tweezers have matured into a technology to probe a variety of biological phenomena8-13.
We describe a method14 that advances live cell imaging by integrating an optical trap with spinning disk confocal microscopy with temperature and humidity control to provide exquisite spatial and temporal control of pathogenic organisms in a physiological environment to facilitate interactions with host cells, as determined by the operator. Live, pathogenic organisms like Candida albicans and Aspergillus fumigatus, which can cause potentially lethal, invasive infections in immunocompromised individuals15, 16 (e.g. AIDS, chemotherapy, and organ transplantation patients), were optically trapped using non-destructive laser intensities and moved adjacent to macrophages, which can phagocytose the pathogen. High resolution, transmitted light and fluorescence-based movies established the ability to observe early events of phagocytosis in living cells. To demonstrate the broad applicability in immunology, primary T-cells were also trapped and manipulated to form synapses with anti-CD3 coated microspheres in vivo, and time-lapse imaging of synapse formation was also obtained. By providing a method to exert fine spatial control of live pathogens with respect to immune cells, cellular interactions can be captured by fluorescence microscopy with minimal perturbation to cells and can yield powerful insight into early responses of innate and adaptive immunity.

A method is described to individually select, manipulate, and image live pathogens using an optical trap coupled to a spinning disk microscope. The optical trap provides spatial and temporal control of organisms and places them adjacent to host cells. Fluorescence microscopy captures dynamic intercellular interactions with minimal perturbation to cells.

Dynamic live cell imaging allows direct visualization of real-time interactions between cells of the immune system1, 2; however, the lack of spatial and ...

Non-invasive Imaging of Disseminated Candidiasis in Zebrafish Larvae

Disseminated candidiasis caused by the pathogen Candida albicans is a clinically important problem in hospitalized individuals and is associated with a 30 to 40% attributable mortality6. Systemic candidiasis is normally controlled by innate immunity, and individuals with genetic defects in innate immune cell components such as phagocyte NADPH oxidase are more susceptible to candidemia7-9. Very little is known about the dynamics of C. albicans interaction with innate immune cells in vivo. Extensive in vitro studies have established that outside of the host C. albicans germinates inside of macrophages, and is quickly destroyed by neutrophils10-14. In vitro studies, though useful, cannot recapitulate the complex in vivo environment, which includes time-dependent dynamics of cytokine levels, extracellular matrix attachments, and intercellular contacts10, 15-18. To probe the contribution of these factors in host-pathogen interaction, it is critical to find a model organism to visualize these aspects of infection non-invasively in a live intact host. 
The zebrafish larva offers a unique and versatile vertebrate host for the study of infection. For the first 30 days of development zebrafish larvae have only innate immune defenses2, 19-21, simplifying the study of diseases such as disseminated candidiasis that are highly dependent on innate immunity. The small size and transparency of zebrafish larvae enable imaging of infection dynamics at the cellular level for both host and pathogen. Transgenic larvae with fluorescing innate immune cells can be used to identify specific cells types involved in infection22-24. Modified anti-sense oligonucleotides (Morpholinos) can be used to knock down various immune components such as phagocyte NADPH oxidase and study the changes in response to fungal infection5. In addition to the ethical and practical advantages of using a small lower vertebrate, the zebrafish larvae offers the unique possibility to image the pitched battle between pathogen and host both intravitally and in color. 
The zebrafish has been used to model infection for a number of human pathogenic bacteria, and has been instrumental in major advances in our understanding of mycobacterial infection3, 25. However, only recently have much larger pathogens such as fungi been used to infect larva5, 23, 26, and to date there has not been a detailed visual description of the infection methodology. Here we present our techniques for hindbrain ventricle microinjection of prim25 zebrafish, including our modifications to previous protocols. Our findings using the larval zebrafish model for fungal infection diverge from in vitro studies and reinforce the need to examine the host-pathogen interaction in the complex environment of the host rather than the simplified system of the Petri dish5.

The rapid development, small size and transparency of zebrafish are tremendous advantages for the study of innate immune control of infection1-4. Here we demonstrate techniques for infecting zebrafish larvae using the fungal pathogen Candida albicans by microinjection, methodology recently used to implicate phagocyte NADPH oxidase activity in control of fungal dimorphism5.

Disseminated candidiasis caused by the pathogen Candida albicans is a clinically important problem in hospitalized individuals and is associated with a 30 ...

Real-time Live Imaging of T-cell Signaling Complex Formation

Protection against infectious diseases is mediated by the immune system 1,2. T lymphocytes are the master coordinators of the immune system, regulating the activation and responses of multiple immune cells 3,4. T-cell activation is dependent on the recognition of specific antigens displayed by antigen presenting cells (APCs). The T-cell antigen receptor (TCR) is specific to each T-cell clone and determines antigen specificity 5. The binding of the TCR to the antigen induces the phosphorylation of components of the TCR complex. In order to promote T-cell activation, this signal must be transduced from the membrane to the cytoplasm and the nucleus, initiating various crucial responses such as recruitment of signaling proteins to the TCR;APC site (the immune synapse), their molecular activation, cytoskeletal rearrangement, elevation of intracellular calcium concentration, and changes in gene expression 6,7. The correct initiation and termination of activating signals is crucial for appropriate T-cell responses. The activity of signaling proteins is dependent on the formation and termination of protein-protein interactions, post translational modifications such as protein phosphorylation, formation of protein complexes, protein ubiquitylation and the recruitment of proteins to various cellular sites 8. Understanding the inner workings of the T-cell activation process is crucial for both immunological research and clinical applications.
Various assays have been developed in order to investigate protein-protein interactions; however, biochemical assays, such as the widely used co-immunoprecipitation method, do not allow protein location to be discerned, thus precluding the observation of valuable insights into the dynamics of cellular mechanisms. Additionally, these bulk assays usually combine proteins from many different cells that might be at different stages of the investigated cellular process. This can have a detrimental effect on temporal resolution. The use of real-time imaging of live cells allows both the spatial tracking of proteins and the ability to temporally distinguish between signaling events, thus shedding light on the dynamics of the process 9,10. We present a method of real-time imaging of signaling-complex formation during T-cell activation. Primary T-cells or T-cell lines, such as Jurkat, are transfected with plasmids encoding for proteins of interest fused to monomeric fluorescent proteins, preventing non-physiological oligomerization 11. Live T cells are dropped over a coverslip pre-coated with T-cell activating antibody 8,9, which binds to the CD3/TCR complex, inducing T-cell activation while overcoming the need for specific activating antigens. Activated cells are constantly imaged with the use of confocal microscopy. Imaging data are analyzed to yield quantitative results, such as the colocalization coefficient of the signaling proteins.

We describe a live-cell imaging method that provides insight into protein dynamics during the T-cell activation process. We demonstrate the combined usage of the T-cell spreading assay, confocal microscopy and imaging analysis to yield quantitative results to follow signaling complex formation throughout T-cell activation.

Protection against infectious diseases is mediated by the immune system 1,2. T lymphocytes are the master coordinators of the immune system, regulating ...

Culturing Microglia from the Neonatal and Adult Central Nervous System

Microglia are the resident macrophage-like cells of the central nervous system (CNS) and, as such, have critically important roles in physiological and pathological processes such as CNS maturation in development, multiple sclerosis, and spinal cord injury. Microglia can be activated and recruited to action by neuronal injury or stimulation, such as axonal damage seen in MS or ischemic brain trauma resulting from stroke. These immunocompetent members of the CNS are also thought to have roles in synaptic plasticity under non-pathological conditions. We employ protocols for culturing microglia from the neonatal and adult tissues that are aimed to maximize the viable cell numbers while minimizing confounding variables, such as the presence of other CNS cell types and cell culture debris. We utilize large and easily discernable CNS components (e.g. cortex, spinal cord segments), which makes the entire process feasible and reproducible. The use of adult cells is a suitable alternative to the use of neonatal brain microglia, as many pathologies studied mainly affect the postnatal spinal cord. These culture systems are also useful for directly testing the effect of compounds that may either inhibit or promote microglial activation. Since microglial activation can shape the outcomes of disease in the adult CNS, there is a need for in vitro systems in which neonatal and adult microglia can be cultured and studied.

We outline methods for the efficient and quick isolation/culture of viable microglia from the neonatal cerebral cortex and adult spinal cord. The dissection and plating of cortical microglia can be accomplished within 90 minutes, with the subsequent microglial harvest taking place ~ 10 days following the initial dissection.

Microglia are the resident macrophage-like cells of the central nervous system (CNS) and, as such, have critically important roles in physiological and ...

Live Cell Imaging of Alphaherpes Virus Anterograde Transport and Spread

Advances in live cell fluorescence microscopy techniques, as well as the construction of recombinant viral strains that express fluorescent fusion proteins have enabled real-time visualization of transport and spread of alphaherpes virus infection of neurons. The utility of novel fluorescent fusion proteins to viral membrane, tegument, and capsids, in conjunction with live cell imaging, identified viral particle assemblies undergoing transport within axons. Similar tools have been successfully employed for analyses of cell-cell spread of viral particles to quantify the number and diversity of virions transmitted between cells. Importantly, the techniques of live cell imaging of anterograde transport and spread produce a wealth of information including particle transport velocities, distributions of particles, and temporal analyses of protein localization. Alongside classical viral genetic techniques, these methodologies have provided critical insights into important mechanistic questions. In this article we describe in detail the imaging methods that were developed to answer basic questions of alphaherpes virus transport and spread.

Live cell imaging of alphaherpes virus infections enables analysis of the dynamic events of directed transport and intercellular spread. Here, we present methodologies that utilize recombinant viral strains expressing fluorescent fusion proteins to facilitate visualization of viral assemblies during infection of primary neurons.

Advances in live cell fluorescence microscopy  techniques, as well as the construction of recombinant viral strains that  express fluorescent fusion ...

The Mesenteric Lymph Duct Cannulated Rat Model: Application to the Assessment of Intestinal Lymphatic Drug Transport

The intestinal lymphatic system plays key roles in fluid transport, lipid absorption and immune function. Lymph flows directly from the small intestine via a series of lymphatic vessels and nodes that converge at the superior mesenteric lymph duct. Cannulation of the mesenteric lymph duct thus enables the collection of mesenteric lymph flowing from the intestine. Mesenteric lymph consists of a cellular fraction of immune cells (99% lymphocytes), aqueous fraction (fluid, peptides and proteins such as cytokines and gut hormones) and lipoprotein fraction (lipids, lipophilic molecules and apo-proteins). The mesenteric lymph duct cannulation model can therefore be used to measure the concentration and rate of transport of a range of factors from the intestine via the lymphatic system. Changes to these factors in response to different challenges (e.g., diets, antigens, drugs) and in disease (e.g., inflammatory bowel disease, HIV, diabetes) can also be determined. An area of expanding interest is the role of lymphatic transport in the absorption of orally administered lipophilic drugs and prodrugs that associate with intestinal lipid absorption pathways. Here we describe, in detail, a mesenteric lymph duct cannulated rat model which enables evaluation of the rate and extent of lipid and drug transport via the lymphatic system for several hours following intestinal delivery. The method is easily adaptable to the measurement of other parameters in lymph. We provide detailed descriptions of the difficulties that may be encountered when establishing this complex surgical method, as well as representative data from failed and successful experiments to provide instruction on how to confirm experimental success and interpret the data obtained.

Here we describe a technique to cannulate the mesenteric lymph duct in rats which enables quantification of lipid and drug transport via the lymphatic system following intestinal delivery. The technique can be adapted to assess mesenteric lymph concentrations and/or transport of fluid, immune cells, peptides, proteins and lipophilic molecules.

The intestinal lymphatic system plays key roles in fluid transport, lipid absorption and immune function. Lymph flows directly from the small intestine ...

Non-invasive Imaging of the Innate Immune Response in a Zebrafish Larval Model of Streptococcus iniae Infection

The aquatic pathogen, Streptococcus iniae, is responsible for over 100 million dollars in annual losses for the aquaculture industry and is capable of causing systemic disease in both fish and humans. A better understanding of S. iniae disease pathogenesis requires an appropriate model system. The genetic tractability and the optical transparency of the early developmental stages of zebrafish allow for the generation and non-invasive imaging of transgenic lines with fluorescently tagged immune cells. The adaptive immune system is not fully functional until several weeks post fertilization, but zebrafish larvae have a conserved vertebrate innate immune system with both neutrophils and macrophages. Thus, the generation of a larval infection model allows the study of the specific contribution of innate immunity in controlling S. iniae infection.
The site of microinjection will determine whether an infection is systemic or initially localized. Here, we present our protocols for otic vesicle injection of zebrafish aged 2-3 days post fertilization as well as our techniques for fluorescent confocal imaging of infection. A localized infection site allows observation of initial microbe invasion, recruitment of host cells and dissemination of infection. Our findings using the zebrafish larval model of S. iniae infection indicate that zebrafish can be used to examine the differing contributions of host neutrophils and macrophages in localized bacterial infections. In addition, we describe how photolabeling of immune cells can be used to track individual host cell fate during the course of infection.

Non-invasive Imaging of the Innate Immune Response in a Zebrafish Larval Model of Streptococcus iniae Infection

Here, we present a protocol for the generation and imaging of a localized bacterial infection in the zebrafish otic vesicle.

The aquatic pathogen, Streptococcus iniae, is responsible for over 100 million dollars in annual losses for the aquaculture industry and is capable of ...

Deciphering and Imaging Pathogenesis and Cording of Mycobacterium abscessus in Zebrafish Embryos

Zebrafish (Danio rerio) embryos are increasingly used as an infection model to study the function of the vertebrate innate immune system in host-pathogen interactions.&#160;The ease of obtaining large numbers of embryos, their accessibility due to external development, their optical transparency as well as the availability of a wide panoply of genetic/immunological tools and transgenic reporter line collections, contribute to the versatility of this model.&#160;In this respect, the present manuscript describes the use of zebrafish as an&#160;in vivo&#160;model system to investigate the chronology of Mycobacterium abscessus infection. This human pathogen can exist either as smooth (S) or rough (R) variants, depending on cell wall composition, and their respective virulence can be imaged and compared in zebrafish embryos and larvae. Micro-injection of either S or R fluorescent variants directly in the blood circulation via the caudal vein, leads to chronic or acute/lethal infections, respectively. This biological system allows high resolution visualization and analysis of the role of mycobacterial cording in promoting abscess formation. In addition, the use of fluorescent bacteria along with transgenic zebrafish lines harbouring fluorescent macrophages produces a unique opportunity for multi-color imaging of the host-pathogen interactions. This article describes detailed protocols for the preparation of homogenous M. abscessus inoculum and for intravenous injection of zebrafish embryos for subsequent fluorescence imaging of the interaction with macrophages. These techniques open the avenue to future investigations involving mutants defective in cord formation and are dedicated to understand how this impacts on M. abscessus pathogenicity in a whole vertebrate.

Deciphering and Imaging Pathogenesis and Cording of Mycobacterium abscessus in Zebrafish Embryos

Optically transparent zebrafish embryos are widely used to study and visualize in real time the interactions between pathogenic microorganisms and the innate immune cells. Micro-injection of Mycobacterium abscessus, combined with fluorescence imaging, is used to scrutinize essential pathogenic features such as cord formation in zebrafish embryos.

Zebrafish (Danio rerio) embryos are increasingly used as an infection model to study the function of the vertebrate innate immune system in host-pathogen ...

An Endothelial Planar Cell Model for Imaging Immunological Synapse Dynamics

Adaptive immunity is regulated by dynamic interactions between T cells and antigen presenting cells (&#39;APCs&#39;) referred to as &#39;immunological synapses&#39;. Within these intimate cell-cell interfaces discrete sub-cellular clusters of MHC/Ag-TCR, F-actin, adhesion and signaling molecules form and remodel rapidly. These dynamics are thought to be critical determinants of both the efficiency and quality of the immune responses that develop and therefore of protective versus pathologic immunity. Current understanding of immunological synapses with physiologic APCs is limited by the inadequacy of the obtainable imaging resolution. Though artificial substrate models (e.g., planar lipid bilayers) offer excellent resolution and have been extremely valuable tools, they are inherently non-physiologic and oversimplified. Vascular and lymphatic endothelial cells have emerged as an important peripheral tissue (or stromal) compartment of &#39;semi-professional APCs&#39;. These APCs (which express most of the molecular machinery of professional APCs) have the unique feature of forming virtually planar cell surface and are readily transfectable (e.g., with fluorescent protein reporters). Herein a basic approach to implement endothelial cells as a novel and physiologic &#39;planar cellular APC model&#39; for improved imaging and interrogation of fundamental antigenic signaling processes will be described.

Adaptive immunity is controlled by dynamic 'immunological synapses' formed between T cells and antigen presenting cells. This protocol describes methods for investigating endothelial cells both as understudied physiologic APCs and as a novel type of 'planar cellular APC model'.

Adaptive immunity is regulated by dynamic interactions between T cells and antigen presenting cells (&#39;APCs&#39;) referred to as &#39;immunological ...

Live Imaging and Characterization of Microglia Dynamics in the Zebrafish Embryo

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Chapters in this video

In vivo Imaging of Transgenic Leishmania Parasites in a Live Host

Use of an Optical Trap for Study of Host-Pathogen Interactions for Dynamic Live Cell Imaging

Non-invasive Imaging of Disseminated Candidiasis in Zebrafish Larvae

Real-time Live Imaging of T-cell Signaling Complex Formation

Culturing Microglia from the Neonatal and Adult Central Nervous System

Live Cell Imaging of Alphaherpes Virus Anterograde Transport and Spread

The Mesenteric Lymph Duct Cannulated Rat Model: Application to the Assessment of Intestinal Lymphatic Drug Transport

Non-invasive Imaging of the Innate Immune Response in a Zebrafish Larval Model of Streptococcus iniae Infection

Deciphering and Imaging Pathogenesis and Cording of Mycobacterium abscessus in Zebrafish Embryos

An Endothelial Planar Cell Model for Imaging Immunological Synapse Dynamics