Name: automated image-based quantification of neutrophil extracellular traps using netquant
Uploaded: 2019-11-27T12:00:00.000+00:00
Duration: 7 min 33 s
Description: Watch this Scientific Journal Video about Automated Image-Based Quantification of Neutrophil Extracellular Traps Using NETQUANT at JoVE.com

The work was funded by the Crafoord Foundation (TM and PN), Swedish Government Research grant (PN, TM), Swedish research council (PN) and Groschinsky Foundation (TM, PN).

The ethics committee of Lund University approved the collection of venous blood from healthy volunteers in accordance with the Declaration of Helsinki (2013/728). All volunteers provided their written informed consent.
1. Isolation of Peripheral Blood Neutrophils using Density-Gradient Centrifugation
<ol>
	<li>Collect human venous blood in tubes containing heparin and allow the tubes to reach room temperature. 
	Note: A minimum of 16 mL of blood from a healthy donor is required to yield a sufficiently large cell pellet.</li>
	<li>Mix the blood with one volume of 2% dextran in saline (0.9% NaCl) and allow to sediment at room temperature for 30 min in a sterile 50 mL conical centrifuge tube.</li>
	<li>Aspirate the supernatant into a sterile 50 mL conical centrifuge tube and centrifuge at 200 x g for 10 min at 4 &#176;C.</li>
	<li>From this step onwards continue isolation at 4 &#176;C or on ice.</li>
	<li>Resuspend the pellet in 5 mL of ice cold saline and layer on top of 5 mL of leukocyte isolation gradient (9.1% sodium diatrizoate with 5.7% dextran, w/v) in a sterile 15 mL conical centrifuge tube.</li>
	<li>Centrifuge for 30 min at 400 x g at 4 &#176;C.</li>
	<li>Aspirate the supernatant and discard it.</li>
	<li>Lyse red blood cells by resuspending the pellet in 3 mL of ice-cold water for 30 s. Immediately add 1 mL of 3.6% NaCl and then fill up with 10 mL of ice cold saline.</li>
	<li>Centrifuge the cell suspension for 10 min at 350 x g.</li>
	<li>Remove the supernatant, collect the cell pellet and resuspend it in 1 mL of saline. Set aside 10 &#181;L in a microcentrifuge tube for assessment of the cell number and viability using trypan blue in a B&#252;rker chamber.</li>
	<li>Add 10 &#181;L of cell suspension to 90 &#181;L of 0.4% trypan blue solution. Take 10 &#181;L of the cell suspension in a B&#252;rker chamber. Count the cells in the 4 squares bound by 3 lines at each corner of the chamber. Cells that appear dark blue to the uptake of dye are non-viable, exclude them from the total cell number.</li>
	<li>Express the cell number as cells/mL as defined by the equation below. 
	<img alt="Equation" src="/files/ftp_upload/58528/58528eq1.jpg" /> 
	Note: Here chamber factor was 10,000, dilution factor was 10 and the total number of squares was 4.</li>
	<li>Dilute the remaining cell suspension to 10 mL for a final washing step.</li>
	<li>Centrifuge for 5 min at 200 x g.</li>
	<li>Resuspend the neutrophils in RPMI-1640 with 2 mg/mL heat-inactivated human serum albumin (HSA) at a concentration of 5 x 105 cells/mL.</li>
</ol>
2. Preparation of Coverslips and Stimulation of Neutrophils
<ol>
	<li>Place one coverslip (10 mm, #1) in each well of a 12-well plate and coat the coverslip by adding 200 &#181;L of 0.01% poly-L-lysine solution and leave it at 37 &#176;C overnight.</li>
	<li>Wash coverslips with 300 &#181;L phosphate buffer saline (PBS) once and leave to dry.</li>
	<li>Add 400 &#181;L of 5 x 105 neutrophils/mL to each well and incubate at room temperature for 15 min.</li>
	<li>Move the plate containing neutrophils to an incubator at 37 &#176;C with 5% CO2 for 15 min.</li>
	<li>Remove the supernatant. Add 400 &#181;L of prewarmed RPMI-1640 medium with 2 mg/mL HSA to controls. Add 300 &#181;L pre-warmed RPMI with 20 nM phorbol 12-myristate 13-acetate (PMA) for stimulation.</li>
	<li>Stimulate neutrophils for 150 min at 37 &#176;C with 5% CO2.</li>
</ol>
3. Visualization of NETs
<ol>
	<li>Remove the supernatant and wash the samples 2x with 200 &#181;L of PBS.</li>
	<li>Fix samples by adding 200 &#181;L of 4% paraformaldehyde (PFA) in PBS for 20 min at 37 &#176;C. 
	Note: PFA is toxic and must be handled with care.</li>
	<li>Wash samples 3x with 200 &#181;L of PBS.</li>
	<li>Permeabilize the samples by adding 50 &#181;L of 0.5% Triton X-100 for 30 s.</li>
	<li>Wash the samples 3x with 200 &#181;L of PBS.</li>
	<li>Block the samples with 5% goat serum in PBS for 1 h at 37 &#176;C.</li>
	<li>Add 300 &#181;L of primary rabbit anti-human neutrophil elastase in blocking solution at a dilution of 1:500 for 90 min at 37 &#176;C.</li>
	<li>Wash the samples 3x with 300 &#181;L of PBS.</li>
	<li>Add 300 &#181;L of secondary goat anti-rabbit fluorescent antibody at a dilution of 1:1000 for 90 min at 37 &#176;C.</li>
	<li>Wash the coverslips 3x with 300 &#181;L of PBS.</li>
	<li>Remove the coverslips from the wells and mount the coverslip with 10 &#181;L mounting medium containing DAPI. Store overnight at room temperature in the dark to dry the samples. 
	Note: The staining of DNA with DAPI is certainly a critical step in the method. The users can also troubleshoot by adding exogenous DAPI solution at a final concentration range of 0.1&#8210;0.5 &#181;g/mL for 2&#8210;3 min, followed by 3 washing steps with 300 &#181;L PBS.</li>
	<li>Acquire images with a wide-field fluorescence microscope using a 20X objective.</li>
</ol>
4. Analysis and Quantification of NETs using NETQUANT
Note: NETQUANT can be downloaded by clicking the installation file found on the Zenodo Github archive or the Nordenfelt Lab website (<a href="https://nordlab.med.lu.se/?page_id=34" target="_blank">https://nordlab.med.lu.se/?page_id=34</a>).
<ol>
	<li>Importing datasets for analysis, naming of channels and conversion of images
	<ol>
		<li>Open the Setup tab in NETQUANT.</li>
		<li>Choose the source folder for analysis by clicking the Get path option in the source menu and select the folder containing the image sequences to be analyzed.</li>
		<li>Click on the Get Path option in the target menu and select the folder for saving the data following the image analysis.</li>
		<li>Name the channels so that "DNA channel" corresponds with the DNA staining (e.g, DNA or DAPI) and "NET-channel" depicts the NET-bound protein staining (e.g, NET, neutrophil elastase) in the images. For the smooth functioning of the software, (recommended) name the folder containing the control image files as "control". 
		Note: The NET channel refers to the NET-bound granule protein marker staining only.</li>
		<li>Feed the image metadata into the software by clicking the Load image information button on the Image information sub-menu.</li>
		<li>Select the correct channel order contained in the images in the Channel order sub-menu. This option has been included as a fail-safe to prevent accidental mismatches.</li>
		<li>Acquire primary image properties from the raw data and convert the images by clicking the Prepare data button. The converted images appear in the Sample type sub-menu. Click on the Sample type menu for displaying and selecting all datasets acquired for analysis.</li>
		<li>Select an image from the Sample type sub menu and click on the Display image data button to display the images split into the DNA and NET channel respectively.</li>
	</ol>
	</li>
	<li>Segmentation of Cells in the DNA channel and the NET channel
	<ol>
		<li>Select the segmentation method by clicking on the Method sub menu in both the DNA channel and the NET channel. 
		Note: The default method of segmentation is set to adaptive and is the recommended setting. Other options are also available including global, edge and Chan-Vese. A watershed option is also included to help distinguish between closely placed cells or NETs.</li>
		<li>Enter the Segmentation tab to segment control cells first in both channels by clicking on the Segment control samples option.</li>
		<li>Select PMA from the sample type sub-menu and click on the Batch option (recommended) to begin segmentation of all images included in the data set. Select the images in the sample type menu and click on the Display image data button to visualize and validate the binary image masks (DNA mask and NET mask) generated post-segmentation.</li>
	</ol>
	</li>
	<li>Single-cell Analysis of Identifiable Properties
	<ol>
		<li>Enter the analysis tab and analyze the control samples by clicking on the Determine threshold button.</li>
		<li>Change the sample type to PMA and click on the Get cell properties button to complete the analysis of stimulated samples.</li>
		<li>Select an image from the Sample type sub-menu and click on the Display image data button to display the overlay and the number of cells and NET forming cells in the image.</li>
	</ol>
	</li>
	<li>Comparison of Cell properties to Identify NET-forming Cells
	<ol>
		<li>Select sample from the sample type sub-menu and click on the Analyze NETs button to complete the analysis. Individual images can be selected from the sample type sub-menu for analysis or the entire batch of images can be analyzed by selecting the batch option (recommended).</li>
		<li>Adjust NET criteria manually to yield optimal results for a given sample. Compare identified NETs with the original images to assess the quality of identification. 
		Note: The NET criteria can then be used across all images in the data set. Any changes in the NET-criteria are applied simultaneously across all control samples. This limits the possibility of any potential differences that may arise due to over-fitting of the NET parameters. The settings in the NET criteria can be adjusted according to the user&#39;s requirements. The relationship between false discovery rates and NETQUANT has been explored previously13. Typical ranges for area increase are 2&#8210;4, circularity to be 0.7&#8210;0.9 and the DNA/NET ratio to be 0.6&#8211;2.0.</li>
		<li>Inspect the data summary in the Cell data sub-menu where the number of images, cell count per image and percentage of NETs per image are displayed. 
		Note: The total percentage of NETs in the entire dataset is displayed by the "NET-gauge". The total image count, cell count, percentage of NETs in the sample (NETs%) and NETs% in the control sample are displayed in the summary statistics table below the NET-gauge. We recommend that the control data are reported alongside the data obtained from stimulated samples.</li>
	</ol>
	</li>
	<li>Result Outputs
	<ol>
		<li>Enter the Output tab to select and view result outputs.</li>
		<li>Explore and compare the various data outputs generated from the analysis of control and PMA by selecting the form of the output and clicking on the Output results button. 
		Note: All data generated post-analysis for both controls and stimulations is saved in the analysis folder as chosen in the target sub-menu. Data are saved in either .csv or .pdf formats.</li>
		<li>Launch the Method file to obtain the version of the software and NET-criteria used for the analysis (to be included in methods section for publication purposes).</li>
		<li>Click on the Results data table to visualize the individual data points in a given sample.</li>
		<li>Visualize the NET area distribution and DNA:NET ratio in the samples. The red line indicates the threshold value in the graphs.</li>
		<li>Determine the NET area versus shape of DNA by clicking on the Bivariate distribution file.</li>
	</ol>
	</li>
	<li>Loading Previous Analysis and Batch All Steps
	<ol>
		<li>Load previously successful analysis settings into NETQUANT using the Load previous analysis button.</li>
		<li>Use the Batch all steps button included in the Setup menu to run steps 5&#8210;12 (Figure 1, Figure 2, Figure 3, Figure 4, Figure 5) directly to obtain the final output.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Nauseef, W. M., Borregaard, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neutrophils+at+work.">Neutrophils at work.</a> Nature Immunology. 15 (7), 602-611 (2014).</li><li>Borregaard, N., Cowland, J. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Granules+of+the+human+neutrophilic+polymorphonuclear+leukocyte.">Granules of the human neutrophilic polymorphonuclear leukocyte.</a> Blood. 89 (10), 3503-3521 (1997).</li><li>Nordenfelt, P., Tapper, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phagosome+dynamics+during+phagocytosis+by+neutrophils.">Phagosome dynamics during phagocytosis by neutrophils.</a> Journal of Leukocyte Biology. 90 (2), 271-284 (2011).</li><li>Brinkmann, V., 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=Neutrophil+extracellular+traps+kill+bacteria.">Neutrophil extracellular traps kill bacteria.</a> Science. 303 (5663), 1532-1535 (2004).</li><li>Sorensen, O. E., Borregaard, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neutrophil+extracellular+traps+-+the+dark+side+of+neutrophils.">Neutrophil extracellular traps - the dark side of neutrophils.</a> Journal of Clinical Investigation. 126 (5), 1612-1620 (2016).</li><li>Yipp, B. G., Kubes, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=NETosis:+how+vital+is+it?.">NETosis: how vital is it?.</a> Blood. 122 (16), 2784-2794 (2013).</li><li>Jorch, S. K., Kubes, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+emerging+role+for+neutrophil+extracellular+traps+in+noninfectious+disease.">An emerging role for neutrophil extracellular traps in noninfectious disease.</a> Nature Medicine. 23 (3), 279-287 (2017).</li><li>Fuchs, T. 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=Novel+cell+death+program+leads+to+neutrophil+extracellular+traps.">Novel cell death program leads to neutrophil extracellular traps.</a> J Cell Biol. 176 (2), 231-241 (2007).</li><li>Mohanty, T., 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=A+novel+mechanism+for+NETosis+provides+antimicrobial+defense+at+the+oral+mucosa.">A novel mechanism for NETosis provides antimicrobial defense at the oral mucosa.</a> Blood. 126 (18), 2128-2137 (2015).</li><li>Hakkim, 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=Activation+of+the+Raf-MEK-ERK+pathway+is+required+for+neutrophil+extracellular+trap+formation.">Activation of the Raf-MEK-ERK pathway is required for neutrophil extracellular trap formation.</a> Nature Chemical Biology. 7 (2), 75-77 (2011).</li><li>Brinkmann, V., Goosmann, C., Kuhn, L. I., Zychlinsky, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automatic+quantification+of+in+vitro+NET+formation.">Automatic quantification of in vitro NET formation.</a> Frontiers in Immunology. 3, 413 (2012).</li><li>Coelho, L. P., 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=Automatic+determination+of+NET+(neutrophil+extracellular+traps)+coverage+in+fluorescent+microscopy+images.">Automatic determination of NET (neutrophil extracellular traps) coverage in fluorescent microscopy images.</a> Bioinformatics. 31 (14), 2364-2370 (2015).</li><li>Mohanty, T., Sorensen, O. E., Nordenfelt, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=NETQUANT:+Automated+Quantification+of+Neutrophil+Extracellular+Traps.">NETQUANT: Automated Quantification of Neutrophil Extracellular Traps.</a> Frontiers in Immunology. 8, 1999 (2017).</li><li>Kaplan, M. J., Radic, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neutrophil+extracellular+traps:+double-edged+swords+of+innate+immunity.">Neutrophil extracellular traps: double-edged swords of innate immunity.</a> Journal of Immunology. 189 (6), 2689-2695 (2012).</li><li>Cedervall, J., Olsson, A. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immunity+Gone+Astray+-+NETs+in+Cancer.">Immunity Gone Astray - NETs in Cancer.</a> Trends in Cancer. 2 (11), 633-634 (2016).</li><li>Ginley, B. G., 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=Computational+detection+and+quantification+of+human+and+mouse+neutrophil+extracellular+traps+in+flow+cytometry+and+confocal+microscopy.">Computational detection and quantification of human and mouse neutrophil extracellular traps in flow cytometry and confocal microscopy.</a> Scientific Reports. 7 (1), 17755 (2017).</li></ol>

TM and PN have a patent pending related to the algorithms used in NETQUANT.

NET formation is a relatively recent addition to the diverse neutrophil armamentarium4 and there has been a noticeable surge of interest to study the implication of NETs in a wide array of research areas5,7,14,15. Acquisition of images using Immunofluorescence microscopy and subsequent image-based quantification is a widely used method to quantify NETs. This approach has the advantage of being able to detect cells forming NETs at a single-cell level and can therefore better reduce the background signal. Manual methods of quantification can be exhaustive, slow and subject to user bias. A few semi-automatic options exist that have provided users with reliable analysis11,12. However, they might require significant technical skill for operation or may require several manual steps for quantification. This is challenging especially to previously non-experienced users. In a recent publication, a fully automatic computational method has been used to quantify NET formation using flow cytometry-based imaging as well as thin tissue sections. However, it can only be applied to specific scenarios and also requires a significant knowledge of programming for operation16. Presently, fully automated image quantification software dedicated towards general NET quantification that is easy to use and possesses single-cell resolution capacity is unavailable to researchers.
Here we present NETQUANT, a fully automated NET quantification software that is freely available. This software has been developed specifically to quantify NET formation with high stringency using immunofluorescence microscopy images, and with the ability to perform single-cell analysis and quantification. Apart from considering the increase in the area of staining under NETs, NETQUANT also takes into account nuclear deformation due to chromatin decondensation and an increase in the DNA/NET-marker protein co-localization to define NET formation in a given sample. This allows for distinguishing cells that have only undergone nuclear decondensation from cells that have undergone complete NET formation. The NET definition criteria included in the NETQUANT algorithm allows for higher stringency in quantification in comparison to many earlier quantification approaches that rely solely upon an increase in the area of NET staining.
The GUI is aimed to be user-friendly and simple to use. Each step of the analysis is numbered to ensure that users can follow the workflow. One of the key features provided in the software is the segmentation tool/tab that allows NETQUANT to perform single-cell analysis in images, which is the highest possible sensitivity that can be achieved. This makes NETQUANT one of the few available options that can perform single-cell quantification to quantitate NET formation. In addition, Mohanty et al. have demonstrated that the software can also adapt to image variations and acquisition parameters13. Due to the flexibility offered in the segmentation and NET-definition criteria, donor and plate variations can be accommodated. NETQUANT can handle large data sets adequately and can be used for reliable high-throughput image analysis13.
Although we found the workflow to yield robust results from multiple donors, we recommend that the user should decide on the appropriate values based on the individual samples. In theory, the data generated post-analysis could also be influenced by high cell density. Also, excessive aggregation of NETs can result in the reduction of the number of NETs detected. This is because the segmentation algorithm cannot distinguish entangled NETs into separate events. A similar problem with segmentation may also arise when unstimulated neutrophils are trapped within the NETs. The use of images acquired at 20X and 40X is currently recommended as NETQUANT&#39;s performance has not been tested at other magnification levels. Still, as long as the pixel size is set correctly (either manually or from metadata in the load image info section) the software should adapt area calculations accurately to higher or lower magnifications. Proper staining of the DNA and the granule marker is a critical factor. Poor staining or poor image quality in either channel will result in suboptimal results. Therefore, it is recommended that the user should determine a suitable cell number, staining procedure and antibody titer to yield optimal results.
NETQUANT has only been tested on NETs derived from human neutrophils in vitro. NETs from other species can also quantified with proper corrections in the criteria. NET quantification can be performed on fixed samples in chamber slides or multi-well glass bottom plates. High quality images of samples stained for DNA and granule protein markers are critical. NETQUANT can also be adapted to quantify other forms of extracellular traps (ET)-osis, e.g., as exhibited by eosinophils. Quantifying ETs in non-granulocytes such as monocytes is currently not possible as cytoplasmic granule staining area is required for the segmentation algorithm.
In conclusion, NETQUANT is a simple, automatic and rapid tool for accurately identifying NET formation that allows for single-cell analysis and quantification. We believe this software may lower the barrier for performing automatic NET quantification and that the research community will benefit from this freely available app.

Neutrophils are crucial mediators of innate host defense responses against a wide variety of microbial pathogens1. They execute their antimicrobial functions by releasing their granules containing a wide array of antimicrobial proteins2, producing reactive oxygen species (ROS) and hypochlorite1, and through phagocytosis3. In addition, Brinkmann et al.4 described neutrophil extracellular traps (NETs) as a novel mechanism by which neutrophils trap and eliminate invading pathogens. Since their discovery a little over a decade ago4, NETs have been implicated in a wide variety of infectious5,6 and non-infectious7 morbidities. NET formation is an active process and results in the extrusion of chromatin DNA coated with granule-derived antimicrobial proteins8. Some of the key changes in cellular and nuclear morphology associated with NET formation include the loss of nuclear morphology, chromatin decondensation, mobilization of granule proteins from cytoplasm to the nucleus and an increase in the nuclear and cellular diameter8,9.
The web-like NETs, which may appear as diffuse structures slightly larger than the cell or as structures several times larger than a single neutrophil are considered as indicators of NETosis5,10. Using fluorescence microscopy, NETs can be detected by probing DNA with a fluorescent probe such as 4&#39;,6-diamidino-2-phenylindole (DAPI) and by immunofluorescence staining against NET-bound proteins such as neutrophil elastase. Quantification of overlapping areas of staining for DNA and NET-bound proteins determines the total area under NETs in an image11.
A number of image analysis options are available to perform fluorescence image-based quantification of NETs11,12. But these software options present limitations in not being user-friendly and/or fully automated. In this article, we demonstrate the operation of NETQUANT13, a freely available app that can perform unbiased fully automated immunofluorescence microscopy image-based NET quantification. The app has a user friendly graphical interface (GUI) and can perform single-cell analysis. The software quantifies NETosis in an image by detecting the morphological changes in the area of DNA-NET-bound marker, chromatin decondensation associated deformation of the nucleus and increase in the DNA:NET-bound protein ratio. Taken together, the multiple NET definition criteria allows for stringent NET quantification across several data sets in an unbiased fashion.

<table><tbody><tr><td>BD Vacutainer Heparinised plastic tubes</td><td>BD Biosciences</td><td>367885</td><td></td></tr><tr><td>Lymphoprep</td><td>Axis-Shield</td><td>114547</td><td></td></tr><tr><td>RPMI-1640 with L-Glutamine</td><td>Gibco</td><td>11835-030</td><td></td></tr><tr><td>50mL conical flasks</td><td>Sarstedt</td><td>62.547.004</td><td></td></tr><tr><td>15mL conical flasks</td><td>Sarstedt</td><td>62.554.002</td><td></td></tr><tr><td>12-well Tissue culture plates</td><td>Falcon</td><td>10626491</td><td></td></tr><tr><td>#1 Coverslips 10mm</td><td>Menzel Glaser</td><td>CS10100</td><td></td></tr><tr><td>Glass slides</td><td>Menzel Glaser</td><td>631-0098</td><td></td></tr><tr><td>Primary anti-human elastase</td><td>DAKO</td><td>DAKO rabbit 1373, contract immunization</td><td></td></tr><tr><td>Secondary fluorophore conjugated goat anti-rabbit</td><td>Life technologies</td><td>A-11072, A-11070</td><td></td></tr><tr><td>PROLONG-Gold Antifade reagent with DAPI</td><td>Life technologies</td><td>P36930</td><td>Mounting medium</td></tr><tr><td>Goat serum</td><td>Sigma-Aldrich</td><td>G9023</td><td></td></tr><tr><td>Phorbol 12-myristate 13-acetate (PMA)</td><td>Sigma-Aldrich</td><td>79346</td><td></td></tr><tr><td>Paraformaldehyde</td><td>Sigma-Aldrich</td><td>158127</td><td></td></tr><tr><td>Triton X-100</td><td>Sigma-Aldrich</td><td>T8787</td><td></td></tr><tr><td>Nikon Ti-E Epifluorescence microscope</td><td>Nikon</td><td></td><td></td></tr><tr><td>CCD camera</td><td>Andor Zyla</td><td></td><td></td></tr><tr><td>Plan Apochromat 20x, 40x objectives</td><td>Nikon</td><td></td><td></td></tr><tr><td>Windows 10</td><td>Microsoft</td><td></td><td>Operating system</td></tr><tr><td>macOS Sierra 10.12</td><td>Apple</td><td></td><td>Operating system</td></tr><tr><td>MATLAB</td><td>Mathworks</td><td></td><td></td></tr></tbody></table>

automated image-based quantification of neutrophil extracellular traps using netquant

Neutrophil extracellular traps (NETs) are web-like antimicrobial structures consisting of DNA and granule derived antimicrobial proteins. Immunofluorescence microscopy and image-based quantification methods remain important tools to quantitate neutrophil extracellular trap formation. However, there are key limitations to the immunofluorescence-based methods that are currently available for quantifying NETs. Manual methods of image-based NET quantification are often subjective, prone to error and tedious for users, especially non-experienced users. Also, presently available software options for quantification are either semi-automatic or require training prior to operation. Here, we demonstrate the implementation of an automated immunofluorescence-based image quantification method to evaluate NET formation called NETQUANT. The software is easy to use and has a user-friendly graphical user interface (GUI). It considers biologically relevant parameters such as an increase in the surface area and DNA:NET marker protein ratio, and nuclear deformation to define NET formation. Furthermore, this tool is built as a freely available app, and allows for single-cell resolution quantification and analysis.

5 x 105 neutrophils/mL were seeded onto coverslips placed in a 12-well plate and stimulated with either 20 nM PMA or left unstimulated for 150 min. The samples were then stained using primary rabbit anti-human neutrophil elastase antibodies, secondary goat anti-rabbit fluorophore conjugated antibodies and DAPI - a fluorescently labelled dye that stains DNA (See the Table of Materials for details). A minimum of 5 images were then acquired using an epifluorescence microscope and a 20X (NA = 0.75) objective. Sample data used for the test analysis in the manuscript can be downloaded by following the link <a href="https://nordlab.med.lu.se/?page_id=34" target="_blank">https://nordlab.med.lu.se/?page_id=34</a> and clicking on the sample dataset icon.
Here we describe the ability of the NETQUANT workflow (Figure 1) to quantify NET formation in a given sample. The software tool can be installed as an app in MATLAB and can be used without any previous knowledge of this interface. The GUI of NETQUANT was used to analyze the datasets as described above. All images used for analysis by NETQUANT are always left unaltered in the parent directory. The GUI is divided into 4 tabs &#8212; setup tab, segmentation tab, analysis tab and results output tab. The samples were prepared for analysis in the setup tab (Figure 2). The file paths (1), naming conventions (2), image information (3) and channel orders (4) are defined by the user. The prepare data option (5) ensures that the conversion and organization in a standardized fashion throughout the experiment. The segmentation parameters were the set in the segmentation tab (Figure 3) to identify individual cells in the samples (6). The control samples are always segmented first (7) prior to the segmentation of stimulated samples (8). All recommended values for segmentation are indicated in the software tab. The properties that define unstimulated control cells are first acquired (9) and then compared to PMA stimulated cells (10) (Figure 4). NETs are then analyzed in the samples based upon the NET criteria (11) and displayed with total image counts, cell counts and corresponding NETs% in the control samples. The final data outputs from the analysis were selected and then visualized (Figure 5). An option for loading and using a previously successful analysis, and a batch-all option to process groups of steps 5-12 (Figure 1, Figure 2, Figure 3, Figure 4, Figure 5) have also been included in the setup tab.
During the analysis, a total of 2619 cells were analyzed in the experiment. The PMA stimulated neutrophils were able to generate 90.59% NETs (NETs%) in contrast to 25.87 NETs% in the control samples (Figure 6). The image analysis was completed within 10 min of initiating the workflow on the software. In summary, NETQUANT provides a rapid and convenient option to quantify NET formation in images that have been acquired using immunofluorescence microscopy.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/58528/58528fig1.jpg" /> 
Figure 1: Overview of the NETQUANT workflow. Fluorescent micrographs of human neutrophils double stained with anti-elastase and DAPI (DNA) are first processed and converted. The images are then segmented, followed by analysis of cell properties, detection of NETs and result outputs. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58528/58528fig1large.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/58528/58528fig2.jpg" /> 
Figure 2: Setup tab options in NETQUANT. File paths for the datasets to be analyzed and data output folders are entered in the setup tab first (1). The naming conventions are then filled in to define channel names and the control folder name (2). The image information is then acquired (3) followed by naming the correct channel order (4). The proper setup of all fields is recommended prior to the processing of the datasets (5) for standardized image conversion. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58528/58528fig2large.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/58528/58528fig3.jpg" /> 
Figure 3: Segmentation tab parameters in NETQUANT. The parameters used for segmentation of both DNA channel and NET-protein marker include method, sensitivity, iterations, minimum area and watershed (6). The use of an adaptive segmentation method and watershed is recommended. Also, other settings provided as presets in the software can be used without modification for most purposes. Control samples are first segmented (7) and then the stimulated samples are segmented (8). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58528/58528fig3large.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/58528/58528fig4.jpg" /> 
Figure 4: Detection of NETs in the analysis tab. The cell properties defining unstimulated cells are analyzed and acquired from control samples (9). This is followed by the analysis of cell properties in the experimental samples (10). The NET-definition criteria (fold increase in cellular area, nuclear deformation (values 0 to 1) and DNA staining area/NET-marker staining area) are applied to both control and stimulated samples to define NET formation (11). The quantity of NETs, total cell count and number of images in both samples is displayed in the summary statistics section. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58528/58528fig4large.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/58528/58528fig5.jpg" /> 
Figure 5: Visualization of result output files in NETQUANT. Results obtained post-analysis can be selected by the individual user. The result outputs that can be generated with NETQUANT includes a .csv file containing data points from individual cells. Also, histograms depicting distribution of cells undergoing increase in NET (cellular) area, deformation of nucleus due to chromatin decondensation and DNA:NET-marker ratio, and a 3D graph of NET area versus nuclear deformation are also generated in the analysis. All outputs are automatically saved in the analysis folder chosen in the setup tab as .csv, .pdf and .txt files. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58528/58528fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/58528/58528fig6.jpg" /> 
Figure 6: Analysis of NET formation. (A) The NETs%, total cell count and number of images from the test data set as observed in the summary statistics for controls and PMA-stimulated (20 nM) neutrophils. (B) A side-by-side comparison of histograms depicting increase in the area, nuclear deformation (values 0 to 1) and DNA/NET ratio in control and PMA-stimulated samples. The red line in the histograms threshold values for the NET-definition criteria. (C) Comparison of 3D graph of NET area versus nuclear deformation generated by NETQUANT analysis of control and PMA-stimulated samples. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58528/58528fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Automated Image-Based Quantification of Neutrophil Extracellular Traps Using NETQUANT at JoVE.com

Automated Image-Based Quantification of Neutrophil Extracellular Traps Using NETQUANT

Here, we present a protocol for generating neutrophil extracellular traps (NETs) and operating NETQUANT, a fully automatic software option for quantification of NETs in immunofluorescence images.

Neutrophil extracellular traps (NETs) are web-like antimicrobial structures consisting of DNA and granule derived antimicrobial proteins. ...

automated-image-based-quantification-neutrophil-extracellular-traps

Nanyang Technological University

Research

JoVE Journal

Immunology and Infection

6.7K Views.  Lund University. Here, we present a protocol for generating neutrophil extracellular traps (NETs) and operating NETQUANT, a fully automatic software option for quantification of NETs in immunofluorescence images.

Video: Automated Image-Based Quantification of Neutrophil Extracellular Traps Using NETQUANT

Neutrophil Extracellular Traps: How to Generate and Visualize Them

Neutrophil granulocytes are the most abundant group of leukocytes in the peripheral blood. As professional phagocytes, they engulf bacteria and kill them intracellularly when their antimicrobial granules fuse with the phagosome. We found that neutrophils have an additional way of killing microorganisms: upon activation, they release granule proteins and chromatin that together form extracellular fibers that bind pathogens. These novel structures, or Neutrophil Extracellular Traps (NETs), degrade virulence factors and kill bacteria1, fungi2 and parasites3. The structural backbone of NETs is DNA, and they are quickly degraded in the presence of DNases. Thus, bacteria expressing DNases are more virulent4. Using correlative microscopy combining TEM, SEM, immunofluorescence and live cell imaging techniques, we could show that upon stimulation, the nuclei of neutrophils lose their shape and the eu- and heterochromatin homogenize. Later, the nuclear envelope and the granule membranes disintegrate allowing the mixing of NET components. Finally, the NETs are released as the cell membrane breaks. This cell death program (NETosis) is distinct from apoptosis and necrosis and depends on the generation of Reactive Oxygen Species by NADPH oxidase5. 
Neutrophil extracellular traps are abundant at sites of acute inflammation. NETs appear to be a form of innate immune response that bind microorganisms, prevent them from spreading, and ensure a high local concentration of antimicrobial agents to degrade virulence factors and kill pathogens thus allowing neutrophils to fulfill their antimicrobial function even beyond their life span. There is increasing evidence, however, that NETs are also involved in diseases that range from auto-immune syndromes to infertility6.
We describe methods to isolate Neutrophil Granulocytes from peripheral human blood7 and stimulate them to form NETs. Also we include protocols to visualize the NETs in light and electron microscopy.

Neutrophil Extracellular Traps (NETs) are an important innate immune mechanism to fight pathogenic bacteria, fungi and parasites. Here we describe methods to isolate neutrophil granulocytes from human blood and to activate them to form NETs. We present preparation techniques to visualize NETs in light and electron microscopy.

Neutrophil granulocytes are the most abundant group of leukocytes in the peripheral blood. As professional phagocytes, they engulf bacteria and kill them ...

A Simple Fluorescence Assay for Quantification of Canine Neutrophil Extracellular Trap Release

Neutrophil extracellular traps are networks of DNA, histones and neutrophil proteins released in response to infectious and inflammatory stimuli. Although a component of the innate immune response, NETs are implicated in a range of disease processes including autoimmunity and thrombosis. This protocol describes a simple method for canine neutrophil isolation and quantification of NETs using a microplate fluorescence assay. Blood is collected using conventional venipuncture techniques. Neutrophils are isolated using dextran sedimentation and a density gradient using conditions optimized for dog blood. After allowing time for attachment to the wells of a 96 well plate, neutrophils are treated with NET-inducing agonists such as phorbol-12-myristate-13-acetate or platelet activating factor. DNA release is measured by the fluorescence of a cell-impermeable nucleic acid dye. This assay is a simple, inexpensive method for quantifying NET release, but NET formation rather than other causes of cell death must be confirmed with alternative methods.

Neutrophil extracellular traps (NETs) are networks of DNA, histones and neutrophil proteins. Although a component of the innate immune response, NETs are implicated in autoimmunity and thrombosis. This protocol describes a simple method for canine neutrophil isolation and quantification of NETs using a microplate fluorescence assay.

Neutrophil extracellular traps are networks of DNA, histones and neutrophil proteins released in response to infectious and inflammatory stimuli. Although ...

In Vitro Canine Neutrophil Extracellular Trap Formation: Dynamic and Quantitative Analysis by Fluorescence Microscopy

In response to invading pathogens, neutrophils release neutrophil extracellular traps (NETs), which are extracellular networks of DNA decorated with histones and antimicrobial proteins. Excessive NET formation (NETosis) and citH3 release during sepsis is associated with multiple organ dysfunction and mortality in mice and humans but its implications in dogs are unknown. Herein, we describe a technique to isolate canine neutrophils from whole blood for observation and quantification of NETosis. Leukocyte-rich plasma, generated by dextran sedimentation, is separated by commercially available density gradient separation media and granulocytes collected for cell count and viability testing. To observe real-time NETosis in live neutrophils, cell permeant and cell impermeant fluorescent nucleic acid stains are added to neutrophils activated either by lipopolysaccharide (LPS) or phorbol 12-myristate 13-acetate (PMA). Changes in nuclear morphology and NET formation are observed over time by fluorescence microscopy. In vitro NETosis is further characterized by co-colocalization of cell-free DNA (cfDNA), myeloperoxidase (MPO) and citrullinated histone H3 (citH3) using a modified double-immunolabelling protocol. To objectively quantify NET formation and citH3 expression using fluorescence microscopy, NETs and citH3-positive cells are quantified in a blinded manner using available software. This technique is a specific assay to evaluate the in vitro capacity of canine neutrophils to undergo NETosis.

In Vitro Canine Neutrophil Extracellular Trap Formation: Dynamic and Quantitative Analysis by Fluorescence Microscopy

We describe methods to isolate canine neutrophils from whole blood and visualize NET formation in live neutrophils using fluorescence microscopy. Also described are protocols to quantify NET formation and citrullinated histone H3 (citH3) expression using immunofluorescence microscopy.

In response to invading pathogens, neutrophils release neutrophil extracellular traps (NETs), which are extracellular networks of DNA decorated with ...

A High-throughput Assay to Assess and Quantify Neutrophil Extracellular Trap Formation

Neutrophil extracellular traps (NETs) are immunogenic extracellular DNA structures that can be released by neutrophils upon a wide variety of triggers. NETs have been demonstrated to serve as an important host defense mechanism that traps and kills microorganisms. On the other hand, they have been implicated in diverse systemic autoimmune diseases. NETs are immunogenic and toxic structures that contain a pool of relevant autoantigens including anti-neutrophil cytoplasmic antibodies (ANCA)-associated vasculitis (AAV) and systemic lupus erythematosus (SLE). Different forms of NETs can be induced depending on the stimulus. The amount of NETs can be quantified using different techniques including measuring DNA release in supernatants, measuring DNA-complexed with NET-molecules like myeloperoxidase (MPO) or neutrophil elastase (NE), measuring the presence of citrullinated histones by fluorescence microscopy, or flow cytometric detection of NET-components which all have different features regarding their specificity, sensitivity, objectivity, and quantity. Here is a protocol to quantify ex vivo NET formation in a highly-sensitive, high-throughput manner by using three-dimensional immunofluorescence confocal microscopy. This protocol can be applied to address various research questions about NET formation and degradation in health and disease.

This protocol describes a highly sensitive and high throughput neutrophil extracellular trap (NET) assay for the semi-automated quantification of ex vivo NET formation by immunofluorescence three-dimensional confocal microscopy. This protocol can be used to evaluate NET formation and degradation after different stimuli and can be used to study potential NET-targeted therapies.

Neutrophil extracellular traps (NETs) are immunogenic extracellular DNA structures that can be released by neutrophils upon a wide variety of triggers. ...

Morphological and Compositional Analysis of Neutrophil Extracellular Traps Induced by Microbial and Chemical Stimuli

Neutrophils function as the first line of cellular defense in an innate immune response by employing diverse mechanisms, such as the formation of neutrophil extracellular traps (NETs). This study analyzes the morphological and compositional changes in NETs induced by microbial and chemical stimuli using standardized in vitro methodologies for NET induction and characterization with human cells. The procedures described here allow the analysis of NET morphology (lytic or non-lytic) and composition (DNA-protein structures and enzymatic activity), and the effect of soluble factors or cellular contact on such characteristics. Additionally, the techniques described here could be modified to evaluate the effect of exogenous soluble factors or cellular contact on NET composition.
The applied techniques include the purification of polymorphonuclear cells from human peripheral blood using a double density gradient (1.079-1.098 g/mL), guaranteeing optimal purity and viability (&#8805; 95%) as demonstrated by Wright's staining, trypan blue exclusion, and flow cytometry, including FSC versus SSC analysis and 7AAD staining. NET formation is induced with microbial (Pseudomonas aeruginosa, Staphylococcus aureus, and Candida albicans) and chemical (phorbol myristate acetate, HOCl) stimuli, and the NETs are characterized by DNA-DAPI staining, immunostaining for the antimicrobial peptide cathelicidin (LL37), and quantification of enzymatic activity (neutrophil elastase, cathepsin G, and myeloperoxidase). The images are acquired through fluorescence microscopy and analyzed with ImageJ.

Presented here is a protocol for the induction and analysis of in vitro neutrophil extracellular traps (NETs). Quantification of DNA, cathelicidin (LL37), and enzyme activity yielded data that show the variability in the composition and morphology of NETs induced by microbial and chemical stimuli under similar controlled conditions.

Neutrophils function as the first line of cellular defense in an innate immune response by employing diverse mechanisms, such as the formation of ...

Immunofluorescence Labelling of Human and Murine Neutrophil Extracellular Traps in Paraffin-Embedded Tissue

Neutrophil granulocytes, also called polymorphonuclear leukocytes (PMN) due to their lobulated nucleus, are the most abundant type of leukocytes. They mature in the bone marrow and are released into the peripheral blood, where they circulate for about 6&#8722;8 h; however, in tissue, they can survive for days. By diapedesis through the endothelium, they leave the blood stream, enter tissues, and migrate towards the site of an infection following chemotactic gradients.&#160;Neutrophils can combat invading microorganisms by phagocytosis,&#160;degranulation, and generation of neutrophil extracellular traps (NETs). This protocol will help to detect NETs in paraffin-embedded tissue. NETs are the result of a process called NETosis, which leads to the release of nuclear, granular, and cytoplasmic components either from living (vital NETosis) or dying (suicidal NETosis) neutrophils. In vitro, NETs form cloud-like structures, which occupy a space several times larger than that of the cells from which they descended. The backbone of NETs is chromatin, to which a selection of proteins and peptides originating from granules and cytoplasm are bound. Thereby, a high local concentration of toxic compounds is maintained so that NETs can capture and inactivate a variety of pathogens including bacteria, fungi, viruses, and parasites, while diffusion of the highly active NET components leading to damage in neighboring tissue is limited. Nevertheless, in recent years it has become apparent that NETs, if generated in abundance or cleared insufficiently, do have pathological potential ranging from autoimmune diseases to cancer. Thus, detection of NETs in tissue samples may have diagnostic significance, and the detection of NETs in diseased tissue can influence the treatment of patients. Since paraffin-embedded tissue samples are the standard specimen used for pathological analysis, it was sought to establish a protocol for fluorescent staining of NET components in paraffin-embedded tissue using commercially available antibodies.

Neutrophil extracellular traps (NETs) are three-dimensional structures generated by stimulated neutrophil granulocytes. It has become clear in recent years that NETs are involved in a wide variety of diseases. Detection of NETs in tissue may have diagnostic relevance, so standardized protocols for labelling NET components are required.

Neutrophil granulocytes, also called polymorphonuclear leukocytes (PMN) due to their lobulated nucleus, are the most abundant type of leukocytes. They ...

Medicine

Staining and Imaging to Visualize Neutrophil Extracellular Traps

Immunofluorescence Imaging of Neutrophil Extracellular Traps in Human and Mouse Tissues

Neutrophil extracellular traps (NETs) are released by neutrophils as a response to bacterial infection or traumatic tissue damage but also play a role in autoimmune diseases and sterile inflammation. They are web-like structures composed of double-stranded DNA filaments, histones, and antimicrobial proteins. Once released, NETs can trap and kill extracellular pathogens in blood and tissue. Furthermore, NETs participate in homeostatic regulation by stimulating platelet adhesion and coagulation. However, the dysregulated production of NETs has also been associated with various diseases, including sepsis or autoimmune disorders, which makes them a promising target for therapeutic intervention. Apart from electron microscopy, visualizing NETs using immunofluorescence imaging is currently one of the only known methods to demonstrate NET interactions in tissue. Therefore, various staining methods to visualize NETs have been utilized. In the literature, different staining protocols are described, and we identified four key components showing high variability between protocols: (1) the types of antibodies used, (2) the usage of autofluorescence-reducing agents, (3) antigen retrieval methods, and (4) permeabilization. Therefore, in vitro immunofluorescence staining protocols were systemically adapted and improved in this work to make them applicable for different species (mouse, human) and tissues (skin, intestine, lung, liver, heart, spinal disc). After fixation and paraffin-embedding, 3 &#181;m thick sections were mounted onto slides. These samples were stained with primary antibodies for myeloperoxidase (MPO), citrullinated histone H3 (H3cit), and neutrophil elastase (NE) according to a modified staining protocol. The slides were stained with secondary antibodies and examined using a widefield fluorescence microscope. The results were analyzed according to an evaluation sheet, and differences were recorded semi-quantitatively.
Here, we present an optimized NET staining protocol suitable for different tissues. We used a novel primary antibody to stain for H3cit and reduced non-specific staining with an autofluorescence-reducing agent. Furthermore, we demonstrated that NET staining requires a constant high temperature and careful handling of samples.

Author Spotlight: Neutrophil Extracellular Traps Imaging in Human and Mouse Tissues 

Neutrophil extracellular traps (NETs) are associated with various diseases, and immunofluorescence is often used for their visualization. However, there are various staining protocols, and, in many cases, only one type of tissue is examined. Here, we establish a generally applicable protocol for staining NETs in mouse and human tissue.

Neutrophil extracellular traps (NETs) are released by neutrophils as a response to bacterial infection or traumatic tissue damage but also play a role in ...

Quantifying NET Formation Using Dual-Dye Live Cell Analysis

Real-Time High Throughput Technique to Quantify Neutrophil Extracellular Traps Formation in Human Neutrophils

Neutrophils are myeloid-lineage cells that form a crucial part of the innate immune system. The past decade has revealed additional key roles that neutrophils play in the pathogenesis of cancer, autoimmune diseases, and various acute and chronic inflammatory conditions by contributing to the initiation and perpetuation of immune dysregulation through multiple mechanisms, including the formation of neutrophil extracellular traps (NETs), which are structures crucial in antimicrobial defense. Limitations in techniques to quantify NET formation in an unbiased, reproducible, and efficient way have restricted our ability to further understand the role of neutrophils in health and diseases. We describe an automated, real-time, high-throughput method to quantify neutrophils undergoing NET formation using a live cell imaging platform coupled with a membrane permeability-dependent dual-dye approach using two different DNA dyes to image intracellular and extracellular DNA. This methodology is able to help assess neutrophil physiology and test molecules that can target NET formation.

Author Spotlight: Quantifying Neutrophil Extracellular Traps in Disease and Drug Screening Using Dual-Color Live-Cell Imaging

We present an automated high-throughput method to quantify neutrophil extracellular traps (NETs) utilizing the live cell analysis system, coupled with a membrane permeability-dependent dual-dye approach.

Neutrophils are myeloid-lineage cells that form a crucial part of the innate immune system. The past decade has revealed additional key roles that ...

Real-Time Microscopy for Studying NETosis Kinetics and Screening Inhibitors

Real-Time, High-Throughput Microscopic Quantification of Human Neutrophil Extracellular Trap Release and Assessing the Pharmacology of Antagonists

Neutrophils play an important role in innate immune defense by using several strategies, including the release of neutrophil extracellular traps (NETs) in a process referred to as NETosis. However, in the past two decades, it has become clear that the accumulation of NETs in tissues contributes to the pathophysiology of multiple inflammatory and autoimmune diseases. Therefore, interest in the development of NETosis antagonists has risen. Variable and non-standardized methods to detect and analyze NETosis were developed concomitantly, each with its own advantages and limitations. Here, we describe a real-time microscopy method for the quantification of human NET release, allowing to study NETosis as well as NET inhibition in a high-throughput manner. The surface area-based semi-automated analysis recognizes NETs and distinguishes them from non-netting activated neutrophils. We demonstrate that the non-physiological NETosis inducers, calcium ionophore and phorbol-12-myristate-13-acetate (PMA), trigger the release of NETs with different characteristics and kinetics. Furthermore, we show that this approach allows studying NET release in response to disease-relevant stimuli, including immune complexes, N-Formylmethionine-leucyl-phenylalanine (fMLF), monosodium urate crystals, and calcium pyrophosphate crystals. To exemplify the utility of this method to study NETosis antagonists, we used CIT-013, a first-in-class monoclonal antibody inhibitor of NET release. CIT-013 targets citrullinated histone H2A and H4 and efficiently inhibits NET release with an IC50 of 4.6 nM. Other anti-histone antibodies tested lacked this NETosis-inhibitory capacity. Altogether, we demonstrate that this protocol enables specific, reliable, and reproducible high-throughput quantification of NETs, enhancing the study of NET release characteristics, kinetics, and pharmacology of NETosis antagonists.

This defined protocol describes a real-time high-throughput microscopy approach to visualize and quantify human neutrophil extracellular trap (NET) release in vitro. The reproducible method allows investigation of the characteristics and kinetics of NET release upon stimulation with distinct NETosis inducers and enables assessment of the pharmacology of NETosis antagonists.

Neutrophils play an important role in innate immune defense by using several strategies, including the release of neutrophil extracellular traps (NETs) in ...

Biology

Induction and Visualization of Neutrophil Extracellular Traps in Pre-Labeled Neutrophils

Source: Arends, E. J. et al., <a href="https://app-jove-com.remotexs.ntu.edu.sg/v/59150">A High-throughput Assay to Assess and Quantify Neutrophil Extracellular Trap Formation.</a>&#160;J. Vis. Exp.&#160;(2019)
This video demonstrates the induction and visualization of neutrophil extracellular traps or NETs in pre-labeled neutrophils using patient serum containing anti-neutrophil cytoplasmic antibodies. Furthermore, using an impermeable DNA dye and fluorescence microscopy enables the visualization of NETs.

All procedures involving human participants have been performed in compliance with the institutional, national, and international guidelines for human ...

Automated Image-Based Quantification of Neutrophil Extracellular Traps Using NETQUANT

Summary

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Chapters in this video

Neutrophil Extracellular Traps: How to Generate and Visualize Them

A Simple Fluorescence Assay for Quantification of Canine Neutrophil Extracellular Trap Release

In Vitro Canine Neutrophil Extracellular Trap Formation: Dynamic and Quantitative Analysis by Fluorescence Microscopy

A High-throughput Assay to Assess and Quantify Neutrophil Extracellular Trap Formation

Morphological and Compositional Analysis of Neutrophil Extracellular Traps Induced by Microbial and Chemical Stimuli

Immunofluorescence Labelling of Human and Murine Neutrophil Extracellular Traps in Paraffin-Embedded Tissue

Immunofluorescence Imaging of Neutrophil Extracellular Traps in Human and Mouse Tissues

Real-Time High Throughput Technique to Quantify Neutrophil Extracellular Traps Formation in Human Neutrophils

Real-Time, High-Throughput Microscopic Quantification of Human Neutrophil Extracellular Trap Release and Assessing the Pharmacology of Antagonists

Induction and Visualization of Neutrophil Extracellular Traps in Pre-Labeled Neutrophils