Name: supervised machine learning for semi-quantification of extracellular dna in glomerulonephritis
Uploaded: 2020-06-18T14:00:00.000+00:00
Duration: 9 min 16 s
Description: Watch this Scientific Journal Video about Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis at JoVE.com

We acknowledge Monash Micro Imaging for the use of Nikon C1 upright confocal laser scanning microscope and the Monash Histology Platform for the processing of kidney tissue.

<ol>
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Nothing to disclose.

Multiple protocols exist that measure proinflammatory markers in the serum and urine of both patients and mouse models of glomerulonephritis. This described protocol allows analysis of the products of cell death (ecDNA, NETs and ecMPO) within the glomerulus directly. The most crucial steps in this protocol is the tissue preparation and imaging. The major restricting element of using a fluorescent staining method for analysis is the tissue autofluorescence. Formalin fixed paraffin tissue is subject to autofluorescence that can obscure specific fluorescent staining. The final step in the staining method where slides are immersed in Sudan black, attenuates autofluorescence of the tissue, and allows the illumination of the antibody specific staining through reduction in signal to noise ratio19. The imaging of the tissue must be performed with at least 40x oil magnification to be able to detect smaller fragments of ecDNA and MPO. When imaging is acquired, it is crucial that it is done in a line sequential manner to ensure no bleed through of fluorescence of one marker to another.
An advantage of the protocol for analysis is that it is available in open access through ImageJ for anyone to access16. We have demonstrated herein that the method can be easily adapted to measure different fluorescent markers within kidney tissue. Once the model in trainable Weka segmentation has been determined it can be applied to subsequent images with no bias and in the exact same manner each image has been analyzed. The supervised nature of the analysis allows any error in segmentation to be adjusted through the additional steps of thresholding the &#34;trained&#34; images, or retraining the program and adding more classifiers. The advantage of this program is that two different users will get similar result using the same model, provided they accurately delineate the glomerular tuft. The biggest inaccuracy in reproducibility by two different end users is created by the different manner in which people trace around the glomerular tuft. For example, if one person draws a rough circle around the glomerular tuft and another user carefully draws around the outermost capillary loops the area being examined will differ (as demonstrated in the results). Therefore, it is essential that both users are trained to identify the glomerular tuft in an identical manner. The practical application of this program would be for two users to design the model together on multiple images to build a robust model to be applied to further data sets. The more images that are used to train the classifiers the more accurate the model will be.
Limitations of this protocol would be measurement of fragments of ecDNA smaller than what the confocal microscope can detect. This could be overcome with the use of capturing images using super resolution microscopy methods and applying the trainable Weka segmentation to those images. The supervised component of the machine learning adds extra steps and reduces the ability to batch process large sets of images. However, as we demonstrated within the results unsupervised models have reduced accuracy and introducing the supervised component reduced inaccuracy significantly.
We have previously published that in addition to neutrophils producing extracellular traps, monocytes/macrophages were also observed to produce extracellular traps (termed METs) in human ANCA vasculitis, but in smaller proportions1. The current methods described herein do not distinguish, between extracellular traps produced by neutrophils or monocytes/macrophages. This is difficult to achieve as most confocal microscopes are limited by the number of lasers. Identification of NETs requires 4 different lasers therefore limiting the number of cell markers able to be processed via standard confocal imaging. If the MPO positive cell of origin is required a second serial section can be stained with either a neutrophil or macrophage/monocyte marker, to identify the cell type producing the extracellular trap.
Pathological features of MPO-ANCA vasculitis include the deposition of ecDNA, NETS and ecMPO within the glomeruli of the kidney20. Therapeutically targeting DNA within NETs and ecMPO as well as measuring them in human biopsies as markers of disease has been the subject of recent studies1,20,21,22. The significance of these methods in this field is accurately determining the relative proportion of ecDNA, NETs and ecMPO within the target organ, in a reproducible, less time-consuming manner. In conclusion we have demonstrated a supervised machine learning tool trainable Weka segmentation to semi automate the analysis of large data sets of acquired images for ecDNA, NETs and ecMPO. The use of this tool will reduce image analysis time considerably and the techniques can be easily adapted to other stains in other organs.

Myeloperoxidase anti neutrophil cytoplasmic antibody associated vasculitis (MPO-AAV) is an autoimmune disease that results in renal failure from pathological glomerular injury with considerable cell death and release of deoxyribonucleic acid (DNA)1,2. DNA can activate the immune system by acting as a danger signal. Under normal healthy conditions, the nuclear location of DNA offers protection from exposure to the immune system. Self-DNA that is released extracellularly during either pathogenic processes or autoimmunity is seen by the immune system as a potent proinflammatory damage associated molecular self-protein (DAMP)3. Extra cellular DNA (ecDNA) is released from dying cells through several distinct mechanisms that are governed by distinct biochemical pathways, such as apoptosis, necroptosis neutrophil extracellular trap formation (NETs), necrosis or pyroptosis4,5,6,7,8.
We describe herein methods to stain and measure ecDNA released from dying cells in sections of formalin fixed paraffin embedded (FFPE) kidneys from experimental anti-MPO GN and kidney biopsies from patients with MPO-AAV9,10. Multiple methods exist for the detection of circulating double stranded DNA (dsDNA) and DNA complexes from both serum and urine and from in vitro assays11,12. These methods, although accurate in determining the amount of ecDNA, do not determine where the ecDNA is released anatomically. There are methods that describe specific measurement of ecDNA such as tunel for apoptosis and measurement of cell debris13,14. There is no method that describes measuring ecDNA culminated from all forms of cell death in FFPE kidneys where the pathological damage occurs. This is important to determine if experimental therapeutic treatments are clearing the ecDNA from the sites of pathological injury in the actual target organ.
The acquisition of multiple images from kidney samples creates a high volume of data that is analyzed commonly by one single user. This is labor intensive, time consuming and can be subject to unreliable reproducibility by other users, due to user bias. Trainable Weka segmentation is an open-source software plugin for ImageJ that uses cutting edge bioinformatic tools to classify pixels using machine learning algorithms15,16. This method is &#34;trainable&#34; whereby it learns from the user&#39;s classification of segments of pixels and applies the new learnt classification to other images. This method relies on common analysis tools within the ImageJ program that are used to &#34;classify&#34; each pixel in a segment as belonging to a specific &#34;class&#34;. Once the program learns the &#34;classifiers&#34;, they can be used to identify other similar classified segments within the same image. This model is then saved and applied to other sets of images within the same experiment.
Current obstacles to determining ecDNA in situ in kidney sections is the endogenous autofluorescence from fixation in formalin and the labor-intensive analysis of the images. We describe here how to quench this autofluorescence, detect ecDNA, and use supervised machine learning for high throughput measurement of ecDNA. We have previously published the measurement of NETs and extracellular MPO (ecMPO) using a macro in ImageJ, we now demonstrate semi automation of these methods using supervised machine learning1. We demonstrate the adaptability of the machine learning tool, to classify an alternative stain for NETs and ecMPO within the same image. These staining methods described here for detecting ecDNA, NETs and ecMPO can be translated to other solid organs and diseases where ecDNA, NETS and ecMPO plays a role in perpetuating disease such as rheumatoid arthritis and lupus17,18.

<table><tbody><tr><td>Bovine Serum Albumin</td><td>SIGMA</td><td>A2153</td><td>5% and 1% solutions are made up in PBS, can be made in bulk and frozen- discard once thawed.</td></tr><tr><td>Chicken anti Goat IgG (H+L) cross absorbed antibody Alexa Fluor 594</td><td>ThermoFisher Scientific</td><td>A-21468</td><td>Spin in mini centrifuge for 1 minute prior to use to avoid any free conjugate in your antibody cocktail</td></tr><tr><td>Chicken anti mouse IgG (H+L) cross absorbed antibody, Alex Fluor 647</td><td>ThermoFisher Scientific</td><td>A-121468</td><td>Spin in mini centrifuge for 1 minute prior to use to avoid any free conjugate in your antibody cocktail</td></tr><tr><td>Chicken anti rabbit IgG (H+L) Cross absorbed antibody Alexa Fluor 488</td><td>ThermoFisher Scientific</td><td>A-21441</td><td>Spin in mini centrifuge for 1 minute prior to use to avoid any free conjugate in your antibody cocktail</td></tr><tr><td>Chicken sera</td><td>SIGMA</td><td>C5405</td><td>Made up in 1%BSA/PBS</td></tr><tr><td>Coverslips 24 x60 mm</td><td>Azerscientific</td><td>ES0107222</td><td>#1.5 This is not standard thickness- designed for use in confocal microscopy</td></tr><tr><td>EDTA 10mM</td><td>SIGMA</td><td>E6758</td><td>Add TRIS and EDTA together in distilled water and pH to 9, for antigen retrieval, can be made up in a 10x Solution</td></tr><tr><td>Ethanol 30%, 70% and 100%</td><td>Chem Supply</td><td>UN1170</td><td>Supplied as 100% undenatured ethanol- dilute to 30% and 70% using distilled water</td></tr><tr><td>Formaldehyde, 4% (10% Neutral buffered Formalin)</td><td>TRAJAN</td><td>NBF-500</td><td>Kidney is put into a 5ml tube containing 3ml of formalin for 16 hours at RT, formalin should be used in a fume hood</td></tr><tr><td>Glass histology slides- Ultra Super Frost, Menzel Glaze, 25x75 x1.0mm</td><td>TRAJAN</td><td>J3800AM4</td><td>Using positive charged coated slides is essential. We do not recommend using poly-L-lysine for coating slides as tissue dislodges from slides during the antigen retrieval step</td></tr><tr><td>Goat anti human/mouse MPO antibody</td><td>R&amp;amp;D</td><td>AF3667</td><td>Aliquot and freeze at minus 80 degrees upon arrival</td></tr><tr><td>Histosol</td><td>Clini Pure</td><td>CPL HISTOSOL 08</td><td>Used neat, in 200ml staining rack containers, use in a fume hood</td></tr><tr><td>Hydrophobic pen</td><td>VECTOR Labs</td><td>H-400</td><td>Use to draw circle around kidney tissue</td></tr><tr><td>Mouse anti human/mouse Peptidyl arginase 4 (PAD4)</td><td>ABCAM</td><td>ab128086</td><td>Aliquot and freeze at minus 80 degrees upon arrival</td></tr><tr><td>Nikon C1 confocal scanning laser head attached to Nikon Ti-E inverted Microscope</td><td>Coherent Scientific</td><td></td><td>Aliquot and freeze at minus 80 degrees upon arrival</td></tr><tr><td>Phosphate Buffered Saline</td><td>SIGMA</td><td>P38135</td><td>0.01M PB/0.09% NaCl Make up 5L at a time</td></tr><tr><td>Pressure Cooker 6L Tefal secure 5 Neo stainless</td><td>Tefal</td><td>GSA-P2530738</td><td>Purchased at local homeware store</td></tr><tr><td>Prolong Gold DAPI</td><td>Life Technologies</td><td>P36962</td><td>Apply drops directly to coverslip</td></tr><tr><td>Rabbit anti human/mouse Beta Actin antibody</td><td>ABCAM</td><td>ab8227</td><td>Aliquot and freeze at minus 80 degrees upon arrival</td></tr><tr><td>Rabbit anti human/mouse H3Cit antibody</td><td>ABCAM</td><td>ab5103</td><td>Aliquot and freeze at minus 80 degrees upon arrival</td></tr><tr><td>Staining rack 24 slides</td><td>ProScitech</td><td>H4465</td><td>Staining rack chosen has to be able to withstand boiling under pressure and incubation in 60 degree oven</td></tr><tr><td>Sudan Black B</td><td>SIGMA</td><td>199664</td><td>0.3% Add 3g to a 1L bottle in 70% Ethanol, filter and protect from the light- stable for 6 months at room temperature</td></tr><tr><td>Tris 10mM</td><td>SIGMA</td><td>T4661</td><td>Add TRIS and EDTA together in distilled water and pH to 9, for antigen retrieval, can be made up in a 10x solution</td></tr><tr><td>Xylene</td><td>Trajan</td><td>XL005/20</td><td>Must be use used in a fume hood</td></tr></tbody></table>

supervised machine learning for semi-quantification of extracellular dna in glomerulonephritis

Glomerular cell death is a pathological feature of myeloperoxidase anti neutrophil cytoplasmic antibody associated vasculitis (MPO-AAV). Extracellular deoxyribonucleic acid (ecDNA) is released during different forms of cell death including apoptosis, necrosis, necroptosis, neutrophil extracellular traps (NETs) and pyroptosis. Measurement of this cell death is time consuming with several different biomarkers required to identify the different biochemical forms of cell death. Measurement of ecDNA is generally conducted in serum and urine as a surrogate for renal damage, not in the actual target organ where the pathological injury occurs. The current difficulty in investigating ecDNA in the kidney is the lack of methods for formalin fixed paraffin embedded tissue (FFPE) both experimentally and in archived human kidney biopsies. This protocol provides a summary of the steps required to stain for ecDNA in FFPE tissue (both human and murine), quench autofluorescence and measure the ecDNA in the resulting images using a machine learning tool from the publicly available open source ImageJ plugin trainable Weka segmentation. Trainable Weka segmentation is applied to ecDNA within the glomeruli where the program learns to classify ecDNA. This classifier is applied to subsequent acquired kidney images, reducing the need for manual annotations of each individual image. The adaptability of the trainable Weka segmentation is demonstrated further in kidney tissue from experimental murine anti-MPO glomerulonephritis (GN), to identify NETs and ecMPO, common pathological contributors to anti-MPO GN. This method provides objective analysis of ecDNA in kidney tissue that demonstrates clearly the efficacy in which the trainable Weka segmentation program can distinguish ecDNA between healthy normal kidney tissue and diseased kidney tissue. This protocol can easily be adapted to identify ecDNA, NETs and ecMPO in other organs.

These images represent the multiple steps required to successfully use trainable Weka segmentation to minimize the labor-intensive manual measurement of ecDNA in fluorescently stained FFPE kidney tissue from a mouse with induced anti-MPO GN. These steps are summarized in Figure 1 and Figure 2 with images taken directly from the Weka segmentation program, outlining every step in the analysis process. Measurements from this analysis is then shown in Figure 3 demonstrating the ability of the program to determine the different amounts of ecDNA deposited in the glomerulus, in control tissue, without induced anti MPO GN. Figure 4 demonstrates that the model for ecDNA can be adapted to identify ecDNA in kidney biopsy specimens from a control patient (Minimal Change Disease patients have minimal glomerular damage evident at a histological level) and compared to that of a kidney biopsy from a patient with MPO-AAV. Figure 5 demonstrates the translational capacity of this program to other stains within kidney tissue. We have used a representative sample from a mouse kidney with induced experimental anti-MPO GN to stain for NETs and ecMPO. The trainable Weka segmentation program is then used to identify both NETS and ecMPO within the same image. Figure 6 demonstrates there is no significant difference in the outcome of results in the amount of ecDNA quantification on the same data set analyzed by two independent users creating 2 different models designed to semi-quantitate ecDNA.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61180/61180fig1.jpg" /> 
Figure 1: Images illustrating classification of nuclei, background and extracellular DNA within mouse kidney glomeruli from experimental MPO-ANCA GN using trainable Weka segmentation. (A) Demonstrates single channel images of DAPI to stain DNA (blue), &#946; actin (green) to delineate glomerular area, and the composite file with a region of interest (ROI) indicating the glomerular area to be measured. (B) Classification of intact nuclei to develop the model (pink) and unclassified nuclei (blue). (C) Classification of what is considered to be background (green). (D) Classification of what is considered to be ecDNA (purple). (E) The model generated by trainable Weka segmentation showing nuclei in red, background in green and ecDNA area in purple. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61180/61180fig1large.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/61180/61180fig2.jpg" /> 
Figure 2: Images demonstrating the supervised component of the model to reduce the inaccuracy. The Weka model generates the probability of recognizing each classifier in unclassified components. (A) Model generated classification of what intact nuclei is. (B) Model generated classification of what is considered background. (C) Model generation of what ecDNA is considered. (D) Illustrates the image of classified ecDNA unthresholded. (E) Shows the adjustment of the threshold to rule out any errors in what has been identified as ecDNA, identified ecDNA shown in red. (F) Threshold is applied to image and made into a binary image for particle analysis. (G) The glomerular ROI is superimposed on the image so only glomerular ecDNA is analyzed. (H) Shows the summary of results generated from the analysis. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61180/61180fig2large.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/61180/61180fig3.jpg" /> 
Figure 3: Images illustrating classification of nuclei, background and extracellular DNA within mouse kidney glomeruli from a control mouse without induced experimental MPO-ANCA GN using trainable Weka segmentation. (A) Shows the original merged image with the glomerular region to be analyzed, the training and the trained model result (background green, nuclei red and ecDNA identified in purple. (B) Shows the model probabilities of identifying, nuclei, background and ecDNA. (C) Results of what the model classified and identified as ecDNA, displayed in arbitrary units. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61180/61180fig3large.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/61180/61180fig4.jpg" /> 
Figure 4: Image illustrating trainable Weka segmentation is adaptable for the analysis of ecDNA in human kidney biopsies from a patient with minimal change disease and a patient with MPO-ANCA vasculitis. (A) Illustrates that minimal ecDNA is detected using trainable Weka segmentation intact nuclei (red), background (green) and ecDNA (purple). (B) Demonstrates considerable quantities of ecDNA in a patient kidney biopsy from a patient with MPO-ANCA vasculitis intact nuclei (red), background (green) and ecDNA purple. Results demonstrate that 8 particles of ecDNA were found within the glomerular region of a patient with MCD compared to a patient with active MPO ANCA vasculitis (180 particles). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61180/61180fig4large.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/61180/61180fig5.jpg" /> 
Figure 5: Trainable Weka segmentation can used to identify NETS and ecMPO within the same image and model analysis, in mouse kidney tissue from experimental MPO-ANCA GN. (A) Demonstrates a glomerulus with NETs [co-localization of green (Citrullinate histone 3), red (MPO) DAPI (nuclei) and PAD4 (white)]. ecMPO is considered to be cell free. (B) Training for identification of the classifiers, Red (Intact nuclei), Green (background), Purple (NETs) and yellow (ecDNA)]. (C) The model trainable Weka segmentation uses to classify NETs and ecMPO, Red (Intact nuclei), Green (background), Purple (NETs) and yellow (ecDNA). (D) Particle analysis of what the model determined to be NETs. (E) Particle analysis of what the model determined to be ecMPO. (F) Results sheet from the particle analysis for both NETs and ecDNA. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61180/61180fig5large.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/61180/61180fig6.jpg" /> 
Figure 6: Comparison of 2 independent users in designing a model for the detection of ecDNA. (A) Original image showing the DAPI, Beta Actin and Merged images to be analyzed. (B) Comparison of training model, classifiers, thresholding and glomerular ROI between 2 independent users. The yellow arrow indicates that User 2 had to retrain the model to remove background. (C) Results generated showing the comparison of ecDNA count, total area, % area and perimeter, between 2 users. (D) Graph of results showing no significant difference between the number of ecDNA detected within glomeruli and % area from two independent investigators. Statistical analysis performed using Mann-Whitney U test with significance set at &#60;0.05. Sample size is n=6. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/61180/61180fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis at JoVE.com

Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis

Extracellular DNA (ecDNA) released during cell death is proinflammatory and contributes to inflammation. Measurement of ecDNA at the site of injury can determine the efficacy of therapeutic treatment in the target organ. This protocol describes the use of a machine learning tool to automate measurement of ecDNA in kidney tissue.

Glomerular cell death is a pathological feature of myeloperoxidase anti neutrophil cytoplasmic antibody associated vasculitis (MPO-AAV). Extracellular ...

supervised-machine-learning-for-semi-quantification-extracellular-dna

Nanyang Technological University

Research

JoVE Journal

Immunology and Infection

6.7K Views.  Monash University. Glomerulonephritis veroorzaakt pathologische glomerulaire verwondingen met aanzienlijke celdood en extracellulaire DNA-afgifte. Dit protocol maakt de visualisatie van extracellulair DNA op de plaats van afgifte tijdens pathologisch letsel mogelijk. Het voordeel van deze techniek is dat het extracellulair DNA van celdood in de nier meet.In tegenstelling tot serum of urine is extracellulaire DNA-meting een surrogaatmarker voor pathologische schade. Het belang van deze methode is dat zowe...

Video: Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis

Isolation of Glomeruli and In Vivo Labeling of Glomerular Cell Surface Proteins

Proteinuria results from the disruption of the glomerular filter that is composed of the fenestrated endothelium, glomerular basement membrane, and podocytes with their slit diaphragms. The delicate structure of the glomerular filter, especially the slit diaphragm, relies on the interplay of diverse cell surface proteins. Studying these cell surface proteins has so far been limited to in vitro studies or histologic analysis. Here, we present a murine in vivo biotinylation labeling method, which enables the study of glomerular cell surface proteins under physiologic and pathophysiologic conditions. This protocol contains information on how to perfuse mouse kidneys, isolate glomeruli, and perform endogenous immunoprecipitation of a protein of interest. Semi-quantitation of glomerular cell surface abundance is readily available with this novel method, and all proteins accessible to biotin perfusion and immunoprecipitation can be studied. In addition, isolation of glomeruli with or without biotinylation enables further analysis of glomerular RNA and protein as well as primary glomerular cell culture (i.e., primary podocyte cell culture).

Isolation of Glomeruli and In Vivo Labeling of Glomerular Cell Surface Proteins

Here we present a protocol for murine in vivo labeling of glomerular cell surface proteins with biotin. This protocol contains information on how to perfuse mouse kidneys, isolate glomeruli, and perform endogenous immunoprecipitation of the protein of interest.

Proteinuria results from the disruption of the glomerular filter that is composed of the fenestrated endothelium, glomerular basement membrane, and ...

Biochemistry

Quantifying Glomerular Permeability of Fluorescent Macromolecules Using 2-Photon Microscopy in Munich Wistar Rats

Kidney diseases involving urinary loss of large essential macromolecules, such as serum albumin, have long been thought to be caused by alterations in the permeability barrier comprised of podocytes, vascular endothelial cells, and a basement membrane working in unison. Data from our laboratory using intravital 2-photon microscopy revealed a more permeable glomerular filtration barrier (GFB) than previously thought under physiologic conditions, with retrieval of filtered albumin occurring in an early subset of cells called proximal tubule cells (PTC)1,2,3.
Previous techniques used to study renal filtration and establishing the characteristic of the filtration barrier involved micropuncture of the lumen of these early tubular segments with sampling of the fluid content and analysis4. These studies determined albumin concentration in the luminal fluid to be virtually non-existent; corresponding closely to what is normally detected in the urine. However, characterization of dextran polymers with defined sizes by this technique revealed those of a size similar to serum albumin had higher levels in the tubular lumen and urine; suggesting increased permeability5.
Herein is a detailed outline of the technique used to directly visualize and quantify glomerular fluorescent albumin permeability in vivo. This method allows for detection of filtered albumin across the filtration barrier into Bowman's space (the initial chamber of urinary filtration); and also allows quantification of albumin reabsorption by proximal tubules and visualization of subsequent albumin transcytosis6. The absence of fluorescent albumin along later tubular segments en route to the bladder highlights the efficiency of the retrieval pathway in the earlier proximal tubule segments. Moreover, when this technique was applied to determine permeability of dextrans having a similar size to albumin virtually identical permeability values were reported2. These observations directly support the need to expand the focus of many proteinuric renal diseases to included alterations in proximal tubule cell reclamation.

A technique utilizing high resolution intavital 2-photon microscopy to directly visualize and quantify gloemrular filtration in surface glomeruli. This method allows for direct determination of permeability characteristics of macromolecules in both normal and diseased states.

Kidney  diseases involving urinary loss of large essential macromolecules, such as  serum albumin, have long been thought to be caused by alterations in ...

Medicine

Assessment of Kidney Function in Mouse Models of Glomerular Disease

The use of murine models to mimic human kidney disease is becoming increasingly common. Our research is focused on the assessment of glomerular function in diabetic nephropathy and podocyte-specific VEGF-A knock-out mice; therefore, this protocol describes the full kidney work-up used in our lab to assess these mouse models of glomerular disease, enabling a vast amount of information regarding kidney and glomerular function to be obtained from a single mouse. In comparison to alternative methods presented in the literature to assess glomerular function, the use of the method outlined in this paper enables the glomerular phenotype to be fully evaluated from multiple aspects. By using this method, the researcher can determine the kidney phenotype of the model and assess the mechanism as to why the phenotype develops. This vital information on the mechanism of disease is required when examining potential therapeutic avenues in these models. The methods allow for detailed functional assessment of the glomerular filtration barrier through measurement of the urinary albumin creatinine ratio and individual glomerular water permeability, as well as both structural and ultra-structural examination using the Periodic Acid Schiff stain and electron microscopy. Furthermore, analysis of the genes dysregulated at the mRNA and protein level enables mechanistic analysis of glomerular function. This protocol outlines the generic but adaptable methods that can be applied to all mouse models of glomerular disease.

This protocol describes a full kidney work-up that should be carried out in mouse models of glomerular disease. The methods allow for detailed functional, structural, and mechanistic analysis of glomerular function, which can be applied to all mouse models of glomerular disease.

The use of murine models to mimic human kidney disease is becoming increasingly common. Our research is focused on the assessment of glomerular function ...

An Efficient Sieving Method to Isolate Intact Glomeruli from Adult Rat Kidney

Preservation of glomerular structure and function is pivotal in the prevention of glomerulonephritis, a category of kidney disease characterized by proteinuria which can eventually lead to chronic and end-stage renal disease. The glomerulus is a complex apparatus responsible for the filtration of plasma from the body. In disease, structural integrity is lost and allows for the abnormal leakage of plasma contents into the urine. A method to isolate and examine glomeruli in culture is critical for the study of these diseases. In this protocol, an efficient method of retrieving intact glomeruli from adult rat kidneys while conserving structural and morphological characteristics is described. This process is capable of generating high yields of glomeruli per kidney with minimal contamination from other nephron segments. With these glomeruli, injury conditions can be mimicked by incubating them with a variety of chemical toxins, including protamine sulfate, which causes foot process effacement and proteinuria in animal models. Degree of injury can be assessed using transmission electron microscopy, immunofluorescence staining, and western blotting. Nephrin and Wilms Tumor 1 (WT1) levels can also be assessed from these cultures. Due to the ease and flexibility of this protocol, the isolated glomeruli can be utilized as described or in a way that best suits the needs of the researcher to help better study glomerular health and structure in diseased states.

The main focus of this protocol is to efficiently isolate viable primary glomeruli cultures with minimal contaminants for use in a variety of downstream applications. The isolated glomeruli retain structural relationships between component cell types and can be cultured ex vivo for a short time.

Preservation of glomerular structure and function is pivotal in the prevention of glomerulonephritis, a category of kidney disease characterized by ...

Analyses of Proteinuria, Renal Infiltration of Leukocytes, and Renal Deposition of Proteins in Lupus-prone MRL/lpr Mice

Systemic lupus erythematosus (SLE) is an autoimmune disorder with no known cure and is characterized by persistent inflammation in many organs, including the kidneys. Under such circumstances, the kidney loses its ability to clean waste from the blood and regulate salt and fluid concentrations, eventually leading to renal failure. Women, particularly those of childbearing age, are diagnosed nine times more often than men. Kidney disease is the leading cause of mortality in SLE patients. The present protocol describes a quick and simple method to measure excreted protein levels in collected urine, tracking lupus progression over time. In addition, an approach to isolate kidney mononuclear cells is provided based on size and density selection to investigate renal infiltration of leukocytes. Furthermore, an immunohistochemical method has been developed to characterize protein deposition in the glomeruli and leukocyte infiltration in the tubulointerstitial space. Together, these methods can help investigate the progression of chronic inflammation associated with the kidneys of lupus-prone MRL/lpr mice.

The present protocol describes a method to track lupus progression in mice. Two additional procedures are presented to characterize lupus nephritis based on cell infiltration and protein deposition in the kidneys.

Systemic lupus erythematosus (SLE) is an autoimmune disorder with no known cure and is characterized by persistent inflammation in many organs, including ...

Using 2-Photon Microscopy to Quantify the Effects of Chronic Unilateral Ureteral Obstruction on Glomerular Processes

Applying novel microscopy methods to suitable animal disease models to explore the dynamic physiology of the kidney remains a challenge. Rats with surface glomeruli provide a unique opportunity to investigate physiological and pathophysiological processes using intravital 2-photon microscopy. Quantification of glomerular capillary blood flow and vasoconstriction and dilatation in response to drugs, permeability, and inflammation are just some of the processes that can be studied. In addition, transgenic rats, i.e., podocytes labeled with fluorescent dyes and other molecular biomarker approaches, provide increased resolution to directly monitor and quantify protein-protein interactions and the effects of specific molecular alterations.
In mice, which lack surface glomeruli after four weeks of age, unilateral ureteral obstruction (UUO) for several weeks has been used to induce surface glomeruli. As this induction model does not allow for baseline studies, we quantified the effects of UUO on glomerular processes in the UUO model in Munich Wistar Fr&#246;mter (MWF) rats, which have surface glomeruli under physiologic conditions. The UUO model for five weeks or more induced significant alterations to gross renal morphology, the peritubular and glomerular microvasculature, as well as the structure and function of tubular epithelia. Glomerular and peritubular red blood cell (RBC) flow decreased significantly (p &#60; 0.01), probably due to the significant increase in the adherence of white blood cells (WBCs) within glomerular and peritubular capillaries. The glomerular sieving coefficient of albumin increased from 0.015 &#177; 0.002 in untreated MWFs to 0.045 &#177; 0.05 in 5-week-old UUO MWF rats. Twelve weeks of UUO resulted in further increases in surface glomerular density and glomerular sieving coefficient (GSC) for albumin. Fluorescent albumin filtered across the glomeruli was not reabsorbed by the proximal tubules. These data suggest that using UUO to induce surface glomeruli limits the ability to study and interpret normal glomerular processes and disease alterations.

Here, we present a protocol using 2-photon microscopy in Munich Wistar Fromter rats with surface glomeruli to quantifythe effects of prolonged ureteral obstruction on glomerular dynamics and function.

Applying novel microscopy methods to suitable animal disease models to explore the dynamic physiology of the kidney remains a challenge. Rats with surface ...

Application of Laser Microdissection to Uncover Regional Transcriptomics in Human Kidney Tissue

Gene expression analysis of human kidney tissue is an important tool to understand homeostasis and disease pathophysiology. Increasing the resolution and depth of this technology and extending it to the level of cells within the tissue is needed. Although the use of single nuclear and single cell RNA sequencing has become widespread, the expression signatures of cells obtained from tissue dissociation do not maintain spatial context. Laser microdissection (LMD) based on specific fluorescent markers would allow the isolation of specific structures and cell groups of interest with known localization, thereby enabling the acquisition of spatially-anchored transcriptomic signatures in kidney tissue. We have optimized an LMD methodology, guided by a rapid fluorescence-based stain, to isolate five distinct compartments within the human kidney and conduct subsequent RNA sequencing from valuable human kidney tissue specimens. We also present quality control parameters to enable the assessment of adequacy of the collected specimens. The workflow outlined in this manuscript shows the feasibility of this approach to isolate sub-segmental transcriptomic signatures with high confidence. The methodological approach presented here may also be applied to other tissue types with substitution of relevant antibody markers.

We describe a protocol for laser microdissection of sub-segments of the human kidney, including the glomerulus, proximal tubule, thick ascending limb, collecting duct and interstitium. The RNA is then isolated from the obtained compartments and RNA sequencing is carried out to determine changes in the transcriptomic signature within each sub-segment.

Gene expression analysis of human kidney tissue is an important tool to understand homeostasis and disease pathophysiology. Increasing the resolution and ...

Biology

Nuclei Isolation from Adult Mouse Kidney for Single-Nucleus RNA-Sequencing

The kidneys regulate diverse biological processes such as water, electrolyte, and acid-base homeostasis. Physiological functions of the kidney are executed by multiple cell types arranged in a complex architecture across the corticomedullary axis of the organ. Recent advances in single-cell transcriptomics have accelerated the understanding of cell type-specific gene expression in renal physiology and disease. However, enzyme-based tissue dissociation protocols, which are frequently utilized for single-cell RNA-sequencing (scRNA-seq), require mostly fresh (non-archived) tissue, introduce transcriptional stress responses, and favor the selection of abundant cell types of the kidney cortex resulting in an underrepresentation of cells of the medulla.
Here, we present a protocol that avoids these problems. The protocol is based on nuclei isolation at 4 &#176;C from frozen kidney tissue. Nuclei are isolated from a central piece of the mouse kidney comprised of the cortex, outer medulla, and inner medulla. This reduces the overrepresentation of cortical cells typical for whole-kidney samples for the benefit of medullary cells such that data will represent the entire corticomedullary axis at sufficient abundance. The protocol is simple, rapid, and adaptable and provides a step towards the standardization of single-nuclei transcriptomics in kidney research.

Here, we present a protocol to isolate high-quality nuclei from frozen mouse kidneys that improve the representation of medullary kidney cell types and avoids the gene expression artifacts from enzymatic tissue dissociation.

The kidneys regulate diverse biological processes such as water, electrolyte, and acid-base homeostasis. Physiological functions of the kidney are ...

Fluorescent Labeling of Glomeruli in Cleared Mouse Kidneys for Microscopy

An Efficient and Fast Method for Labeling and Analyzing Mouse Glomeruli

The glomeruli are fundamental units in the kidney; hence, studying the glomeruli is pivotal for understanding renal function and pathology. Biological imaging provides intuitive information; thus, it is of great significance to label and observe the glomeruli. However, the glomeruli observation methods currently in use require complicated operations, and the results may lose label details or three-dimensional (3D) information. The clear, unobstructed brain imaging cocktails and computational analysis (CUBIC) tissue clearing technology has been widely used in renal research, allowing for more accurate detection and deeper detection depth. We found that mouse glomeruli can be rapidly and effectively labeled by tail vein injection of medium molecular weight FITC-Dextran followed by the CUBIC clearing method. The cleared mouse kidney could be scanned by a light-sheet microscope (or a confocal microscope when sliced) to obtain three-dimensional image stacks of all the glomeruli in the entire kidney. Processed with appropriate software, the glomeruli signals could be easily digitized and further analyzed to measure the number, volume, and frequency of the glomeruli.

Author Spotlight: Aiding Research in Kidney Biology by Labeling Glomeruli in Cleared Tissues 

This study presents an easy-to-use, complete, and simple set of methods to label and analyze glomeruli from CUBIC-cleared mouse kidneys. Data such as glomerulus number and volume can be obtained easily and reliably using fluorescein isothiocyanate (FITC)-Dextran, light sheet fluorescence microscopy (LSFM), or common confocal microscopy and software such as Imaris.

The glomeruli are fundamental units in the kidney; hence, studying the glomeruli is pivotal for understanding renal function and pathology. Biological ...

Extracellular DNA Staining: A Method to Identify Extracellular DNA in FFPE Tissue Sections

Source: O&#39;Sullivan, K. M. et al. <a href="https://www-jove-com.remotexs.ntu.edu.sg/video/61180" target="_blank">Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis.</a> J. Vis. Exp. (2020)
This video describes the technique of staining extracellular DNA in FFPE tissue sections. The stained extracellular DNA can be quantitated to determine the efficacy of any therapeutic treatment that leads to the death of cancer cells.

Source: O&#39;Sullivan, K. M. et al. Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis. J. Vis. Exp. (2020)
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Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis

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