Single glomerular proteomics: A novel tool for translational glomerular cell biology

ARTICLE IN PRESS

Single glomerular proteomics: A novel tool for translational glomerular cell biology Markus M. Rinschen* The Scripps Research Institute, Center for Mass Spectrometry and Metabolomics, San Diego, CA, United States Department of Internal Medicine II and Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany *Corresponding author: e-mail address: [email protected]

Chapter outline 1 Introduction..........................................................................................................2 1.1 The glomerular apparatus forms the kidney filtration barrier........................2 1.2 Glomerular heterogeneity is a hallmark of many kidney diseases..................3 2 An overview of a single glomerular proteomics experiment.......................................4 3 Isolation of native glomeruli by glomerular preparation............................................4 3.1 Microdissection of single glomeruli from the cortex....................................4 3.2 Glomerular preparations..........................................................................5 3.2.1 Preparation of mouse glomeruli............................................................5 3.2.2 Preparation of rat glomeruli..................................................................6 3.2.3 Preparation of human glomeruli...........................................................6 3.3 Isolation of native glomeruli by laser capture microdissection......................6 4 Preparation of single glomerular proteomes for proteomic analysis...........................7 4.1 Lysis, reduction and alkylation of single glomeruli.....................................7 4.2 Purification of single glomeruli peptides via single pot solid phase sample preparation (SP3)...................................................................................8 5 Proteomic analysis of single glomeruli...................................................................8 5.1 Nano-liquid chromatography....................................................................9 5.2 Mass spectrometry acquisition.................................................................9 5.2.1 Data-dependent acquisition and raw data analysis................................9 5.2.2 Peptide and protein identification.......................................................10 5.2.3 Protein quantification........................................................................10

Methods in Cell Biology, ISSN 0091-679X, https://doi.org/10.1016/bs.mcb.2019.03.010 © 2019 Elsevier Inc. All rights reserved.

1

ARTICLE IN PRESS 2

Single glomerular proteomics

6 Bioinformatics analysis of single glomerular data..................................................10 6.1 Targeted data quantification..................................................................10 6.2 Further bioinformatics analysis..............................................................11 7 Limitations.........................................................................................................11 8 Conclusion.........................................................................................................12 References..............................................................................................................12

Abstract The glomerulus harbors the renal filtration barrier and needs to be precisely maintained. In this chapter, the concept of single glomerular proteomics is described. Single glomerular proteomics has recently been enabled by advances in glomerular isolation, ultrasensitive peptide sample preparation and mass spectrometry based technology and acquisition strategies. It generates protein content information on a single glomerulus that can be overlaid with morphological and other multi-layered omics analyses. The novel method consists of four essential steps: preparation of single glomeruli—by microdissection, glomerular preparation, or laser microdissection—followed by proteomic sample preparation, mass spectrometry analysis and bioinformatics analysis. It enables for the first time the generation of sub-biopsy level proteomics data. In perspective, comprehensive data from individual glomeruli could be used in order to pinpoint novel druggable targets in animal models of kidney disease or in patients with proteinuria and glomerular disease.

1 Introduction 1.1 The glomerular apparatus forms the kidney filtration barrier Loss of glomerular filtration rate is a key clinical parameter that defines chronic kidney disease (CKD). CKD is a condition affecting at least 1 out of 10 adults in the United States of America or in Europe (Chronic Kidney Disease (CKD) Surveillance Project, n.d.). An intact blood-urine barrier function is of outmost importance for maintaining a physiological renal glomerular filtration function over time. An early sign of glomerular disease is albuminuria (Brinkkoetter, Ising, & Benzing, 2013). The filtration barrier and the renal filtration surface are localized in the glomeruli. A human kidney contains approximately more than 1 million glomeruli, whereas a rat kidney contains approximately 35,000 (Heilmann et al., 2012) and a mouse kidney contains approximately 20,000 glomeruli (Bonvalet et al., 1977). The glomerulus consists of three major cell types: The endothelium that lines the renal capillaries, the mesangial cells, and the podocytes. In addition to these cell types, immune cells and blood cells regularly can be found within a glomerulus. Podocytes and also endothelial cells form the renal basement membrane, an important constituent of the filtration barrier. Podocytes are postmitotic cells that do not regenerate well. They are morphologically unique

ARTICLE IN PRESS 1 Introduction

cells that form interdigitating foot processes that form the ultimate part of the filtration barrier. Through this renal filtration barrier about 180 L of primary urine are generated every day in human, and the primary urine that is generated is usually almost protein free. Glomerular diseases are caused by injury to any of these components. For instance, podocyte injury by chemical, genetic, mechanical or inflammatory cues results in focal segmental glomerulosclerosis (Fogo, 2015). As a result, podocytes detach from the basement membrane, and the remaining glomerular cells, including podocytes and parietal epithelial cells react to these stimuli and induce the formation of scar tissue. Sclerosis of more and more capillary loops ultimately leads to loss of filtration function, nephron loss, chronic kidney disease and need for dialysis or transplantation.

1.2 Glomerular heterogeneity is a hallmark of many kidney diseases Kidney diseases occur when the tissue is damaged. As a result of immunological, genetic, inflammatory, chemical or mechanical damage, the function and the morphology of the kidney tissue is altered. Many kidney diseases, such as inflammatory diseases such as lupus nephritis and ANCA vasculitis, focal segmental glomerulosclerosis, transplant nephropathy, and diabetic nephropathy are histologically heterogeneous (Hoyer, Dittrich, Bartram, & Rinschen, 2019). This is related to the chronic degenerative nature of most kidney diseases. Every nephron, the unit of the kidney tissue, is therefore affected to different extent. Therefore, it can be hypothesized that all glomeruli are affected to different extent, and that the individual glomeruli are in different stages of disease. The fact that kidney diseases are heterogeneous is used for pathological classification and clinical stratification of renal diseases. Renal pathologists have developed various scores that look at each glomerulus individually and classify various kidney diseases, including ANCA-vasculitis, Lupus nephritis, and many more (Brix et al., 2018; Loupy et al., 2017; Weening et al., 2004). Typically, various morphological parameters are analyzed, involving, for example, the number of complete sclerosis in glomeruli, the morphology of segmental lesions, and many more. It can be anticipated that adding a molecular layer to these histomorphological criterions can be useful to advance knowledge on disease-associated processes (Loupy et al., 2017). Distinct proteomic changes may actually proceed the development of proteinuria, even when no morphological changes are observable, as recently demonstrated for a rat animal model of puromycin-aminonucleoside induced nephrosis (Rinschen et al., 2017). At the same time, biopsies only contain very small protein amount and often times contain only 1–20 glomeruli can be examined. A physiologist, on the other hand, may be more interested in the heterogeneity of a glomerular population in order to understand and target specific disease processes in podocytes. Therefore, a workflow to analyze the proteome of an individual glomerulus may be of importance to advance the molecular interrogation of renal biopsies and to discover and understand novel concepts in glomerular biology.

3

ARTICLE IN PRESS 4

Single glomerular proteomics

2 An overview of a single glomerular proteomics experiment A single glomerular proteomics experiment consists of several steps. Essentially, it requires the isolation of glomeruli for which different techniques are available. Then, the glomerulus is lysed. Next, the denatured proteins need to be reduced, alkylated and subjected to ultrasensitive sample preparation. Sample preparation involves a tryptic digestion step. Then, proteomics analysis is performed on a nano-LC mass spectrometer that is able to determine sequence information as well as unique mass to charge ratios for every individual peptide, enabling peptide and protein quantification. Finally, bioinformatics analysis and quality controls need to be performed in order to assess variability, the determinants of biological differences, and to understand the biological and physiological meaning of every dataset. One of the first single glomerular proteomics experiment has been recently described (H€ ohne et al., 2018). This study went from isolation from mouse glomeruli to the discovery of novel protein modules that drive the disease. Part of this study was a significant improvement in sample preparation using an ultrasensitive sample preparation method. As a result, disease-driving protein coexpression modules in mouse models of glomerular disease could be identified that could be subsequently targeted using genetic intervention in mouse models. In addition, disease-causing alterations in single human glomeruli were identified. Currently, approximately 2000 proteins could be identified from a single human glomerulus. However, with increase in sensitivity of proteomics technology, there is further room for improvement in depth of the studies.

3 Isolation of native glomeruli by glomerular preparation A large number of individual glomeruli are advantageous to find enough replicates to enhance statistical confidence of quantitative differences. Three major options exist how to isolate glomeruli for subsequent processing: microdissection, glomerular preparations and laser capture microdissection. All of them are compatible with the further downstream applications. They are reviewed in the following three paragraphs. A general consideration for all three protocols is purity of preparation, and protein contamination of carrier substances (e.g., contents of buffers such as albumin, collagenases), contamination with tissue debris, and contamination with external proteins such as skin keratins. All of these can be avoided if the preparation is done accurately, rapidly and under clean conditions.

3.1 Microdissection of single glomeruli from the cortex Experienced researchers can stereoscopically microdissected glomeruli directly from the cortex. Here, the microstructure of the kidney is dissected using manual manipulation, and the anatomical structures of interests are manually isolated, often with the help of a mild collagenase digestion solution (Bankir & Rouffignac, 1976). This procedure is tedious and yields several glomeruli, depending on the experience

ARTICLE IN PRESS 3 Isolation of native glomeruli by glomerular preparation

of the experimenter. Therefore, also due to the time the tissue is incubated ex vivo, this protocol may not be the most suitable for isolation of larger populations of glomeruli. The advantage is that Bowman’s capsule can be retained using microdissection, allowing functional characterizations also of this part (Bankir & Rouffignac, 1976).

3.2 Glomerular preparations In order to analyze multiple glomeruli, a preparation of native glomeruli is advantageous. This preparation is usually a suspension of glomeruli at a purity of 80–99%. Single glomeruli can then be manually picked from this suspension. The isolation method is based on the different morphology of glomeruli compared to the rest of the kidney, the tubules. The main two methods are perfusion of the glomeruli with magnetic beads, or sieving methods. Both methods are very compatible with proteomics analysis (reviewed in Rinschen, Benzing, Limbutara, & Pisitkun, 2015). A downside of glomerular preparations is that they typically lack the Bowmans capsule.

3.2.1 Preparation of mouse glomeruli Mouse glomeruli can be rapidly isolated using the magnetic bead perfusion protocol originally put forward by Takemoto et al. (2002). The kidneys are perfused with a suspension of Hanks Balanced Salt Solution (HBSS) and magnetic beads through the renal artery. The principle of this protocol is that magnetic beads get stuck within the first capillary loop of the glomerulus. After partial digestion of the major collagen in the kidney interstitium, these glomeruli can be isolated using a magnet and subsequent washing steps using HBSS. Notably, the delicate podocyte architecture, the interdigitating foot processes, is maintained when using this protocol (H€ohne et al., 2013). In this protocol, both kidneys are perfused via the renal arterial system with approximately 1 mL of ice-cold buffer (i.e., HBSS) containing tosylactivated magnetic beads of a 4.5 μm diameter (e.g., Dynabeads M-450, Tosylactivated, Thermo). To this end, kidney packages including aorta, retroperitoneal fat tissue, and kidneys are excised as a bulk. Then the dorsal retroperitoneal fat and muscle tissue is removed and the artery is prepared under stereomicroscopic control. Then the aorta is cut open form the dorsal side using a longitudinal cut. The kidneys are perfused through the renal arteries using a 27 or 30 gauge, depending on the size of the lumen. Protease inhibitors (e.g., Roche cOmplete Protease Inhibitor Cocktail tablets, Sigma) can be added if necessary. It is important to achieve a complete perfusion. The kidney is then excised, and remaining fat tissue and capsule is removed. Kidney tissue is minced in 1 mm3 sized pieces. Then, a mild collagenase digestion is performed. We use 1 mg/mL collagenase A, 100 U/mL DNAse I in HBSS, both from Sigma at 37 °C for 15 min with gentle agitation. Then subsequent sieving with tissue strainers (mesh size 100 μm) can be used to reduce larger pieces of extracellular matrix and other parts of the kidney that are not very well digested. Then, the suspension is spun down by a small centrifugation step (5 min, 1000g at 4 degrees). Then, the

5

ARTICLE IN PRESS 6

Single glomerular proteomics

supernatant is removed and the pellet is extracted. Using magnetic extraction using a portable magnetic separator (e.g., DynaMag, Thermo Fisher), glomeruli with beads inside can be isolated in very high purities since they stick to the wall of the tube and can be easily washed to remove the remnant, non-magnetic tubules. One or two beads per glomerulus are usually enough for magnetic isolation. A typical protein yield of glomeruli from a single mouse is 50–100 μg protein after lysis, depending on the purity of the preparation and the lysis buffer used. Very pure preparations require more wash steps, which leads to a loss of glomeruli. At most, purities of 97–99% can be obtained. Sieving can in principle also be used to at least partially enrich glomeruli from the mouse. However, in our hands, these protocols do not yield a very pure preparation of glomeruli.

3.2.2 Preparation of rat glomeruli The rat is an excellent model organism for glomerular diseases since it is closer to human physiology as compared to mice (Iannaccone & Jacob, 2009). The advantage of rats as a model organism is also that glomeruli can be obtained using a fast and highly effective sieving protocol. In a typical sieving protocol experiment, the entire kidneys are mechanically pressed through metal sieves with the mesh sizes of 150, 100 and 50 μm (Rinschen et al., 2015). These can be either woven sieves or metal mesh sieves (e.g., Stainless Steel Sieve Mesh, Endecotts). On the third sieve, with mesh size of 50 μm, the glomeruli are collected, because the tubules pass freely through the meshes. The procedures have been recently described with slight variations of the mesh size in a recent publication (Rush, Small, Stolz, & Tan, 2018). The protocol requires constant washing of the glomeruli, and the glomeruli can be washed of the membrane using a HBSS buffer. The glomeruli can be finally collected using a mild centrifugation step. It should be noted that magnetic bead perfusion for the rat have also been described (Katsuya, Yaoita, Yoshida, Yamamoto, & Yamamoto, 2006). However, this approach is less common due to the high purity commonly obtained using the sieving approaches.

3.2.3 Preparation of human glomeruli Human glomeruli can be isolated using sieving approaches. Most of the times, this is being done analogous to the approach in rat glomeruli. Human glomeruli can be pressed through sieves using the following mesh sizes: 425, 180, and 120 μm (Thongboonkerd, 2009). The glomeruli can be collected on the final sieve. Microscopy is used to confirm the purity of the preparation. Glomeruli can then be transferred into a washing solution (e.g., HBSS) and the glomeruli can be spun down in a table-top centrifuge at 3000 rpm.

3.3 Isolation of native glomeruli by laser capture microdissection A novel option to readily isolate single glomeruli for proteomic analysis is to apply laser capture microdissection (LCM). The method is also known as LMD (laser microdissection). These devices are available from several vendors. The principle of this analysis is that defined regions of a tissue can be microscopically dissected.

ARTICLE IN PRESS 4 Preparation of single glomerular proteomes for proteomic analysis

Optically defined specimens are precisely cut out of a membrane on which the tissue section has been mounted. Kidney tissue is mounted on a thermoplastic membrane that is then melted by a laser beam. On the membrane, one can mount both paraffinembedded tissue (also known as FFPE—Formalin Fixed Paraffin Embedded tissue), or frozen sections of kidneys, e.g., in OCT-medium (optimal cutting temperature medium, so-called cryosections). To increase the amount of protein, a thicker section (5–10 μm) is generally advised. Historically, this approach has been first used to analyze proteomes of cancer tissue. Macroscopic criterions can be used to identify a glomerulus. Glomeruli can be directly captured and lysed in 5% SDS buffer containing Tris (H€ohne et al., 2018). Notably, the method is compatible with routine staining protocols such as hematoxylin–eosin and PAS (periodic acid Schiff ) staining. This allows comparison of proteomic profiles with morphological features, for example, if consecutive tissue sections are obtained. However, some changes in the podocyte ultrastructure— effacement of podocyte foot processes—are not visible in light microscopy, but only in electron microscopy. Thus, LCM is suitable for glomeruli with a distinct morphological abnormality, and has been largely used for analysis of kidney tissue from biopsies.

4 Preparation of single glomerular proteomes for proteomic analysis Because of the low amount of protein in a single glomerulus (only 200 cells in a mouse glomerulus), a very accurate sample preparation is key to a successful single glomerular proteomics experiment. The amount of proteins in a single glomerulus is usually beyond the detectable limit of commercial protein determination assays such as the BCA (bicinchoninic acid) assay. Spectral photometric assays (e.g., Nanodropassay, Thermo) could give a rough estimation of the protein amount depending on the sensitivity. After the proteins are lysed, the proteins need to be prepared for proteomics. A standard bottom up approach involving protein digestion is chosen. Essentially, the following paragraphs explain the application of the Single Pot Solid Phase Sample Preparation (SP3) protocol for single glomerular proteomics. The SP3 protocol has been first developed by Hughes et al. (2014). It has been applied to a variety of very small sample amounts, including human oocytes as a single cell proteomics approach (Virant-Klun, Leicht, Hughes, & Krijgsveld, 2016). For a detailed protocol of the technology, the reader is diverted to a recent excellent hands-on description of the SP3 protocol (Hughes et al., 2019).

4.1 Lysis, reduction and alkylation of single glomeruli The following steps are almost identical to standard proteomics workflows and include lysis, denaturation, reduction and alkylation: A single glomerulus is transferred into 20–40 μL of a lysis buffer containing 5% SDS in 10 mM Tris-Base, further

7

ARTICLE IN PRESS 8

Single glomerular proteomics

adjustment of pH is not necessary. The sample containing the glomerulus is heated to 95 degrees for 5 min in a PCR cycler in order to completely denature the proteins. For degradation and shredding of DNA and chromatin, benzonase can be added (25 Units for 500,000 cells). Dithiothreitol (DTT) is then added to a final amount of 5 mM, and the solution is incubated 30 min at 37 °C. This step leads to a reduction of cysteine residues. Finally, iodoacetamide (IAA) at a final amount of 40 mM, is added and the sample is incubated 30 min at room temperature in the dark. This step leads to alkylation of cysteine residues. The process can be interrupted any time and the protein lysates can be stored at 80 degrees Celsius.

4.2 Purification of single glomeruli peptides via single pot solid phase sample preparation (SP3) The following paragraphs give a short overview on the procedures for purification of peptides using SP3. 2 μL of hydrophilic and hydrophobic carboxylated functionalized magnetic beads are added to the sample (SeraMag). Acetonitrile in 0.1% formic acid (FA) is added to the mixture, and the sample is incubated on ice. During this time, the positively charged proteins will be precipitated on the magnetic beads. Subsequently, the beads containing the proteins are washed with ethanol. A magnet is used to keep the beads—including the proteins precipitated on the beads—in the tube during the washes. Acetonitrile washes follow and finally, the beads are air-dried. Then, proteins are digested on the beads. This is done using a digestion buffer containing, e.g., 10 mM ammonium bicarbonate, and the proteases LysC and Trypsin (e.g., Trypsin Gold mass spectrometry grade, Promega) in a 1:50 ratio, respectively. Both enzymes are commonly used proteases that cleave proteins C-terminal from arginine (Trypsin) and lysine (Trypsin, LysC) residues. The solution can be digested overnight (12–16 h) at 37 degrees in a PCR cycler. The next day, the peptides are washed again and finally eluted in Dimethylsulfoxide, using sonication in a water bath. After acidification with 1% formic acid, the peptides are amenable to proteomics analysis. No further sample cleanup and desalting, such as stop-and-go extraction-tips, is necessary (Rappsilber, Ishihama, & Mann, 2003). Samples can be stored at 20 or at 4 degrees until measurement.

5 Proteomic analysis of single glomeruli A multitude of platforms can be used to analyze the single glomeruli using proteomics. We describe here a bottom-up approach. In general, the setup consists of an nLC-part and a mass spectrometry. For quantitative untargeted proteomics, an instrument with high sensitivity, high resolution and high mass accuracy is chosen. For instance, Quadrupole-Orbitrap or a Quadrupole-Time of Flight tandem mass spectrometers are current state of the art instrumentations to obtain peptide sequence information from very small sample amounts.

ARTICLE IN PRESS 5 Proteomic analysis of single glomeruli

5.1 Nano-liquid chromatography In tandem mass spectrometry based proteomics analysis, separation using a nanoliquid chromatography is commonly used to reduce the complexity of peptides that are being sprayed into the mass spectrometer. Notably, standard approaches of LC are compatible with the described SP3 sample preparation. For this, a solvent gradient of different mobile phases is used to separate peptide mixture with a column that contains C18 material. A standard setup of a nano-LC chromatography is described in a recent publications (H€ ohne et al., 2018). Column length and material should be chosen according to enable accurate chromatography, for instance 2.7 μm size (Poroshell, 120EC-C18). Then, a gradient is used to separate the peptides. Solvent A contains a high fraction of water (i.e., 5% Acetonitrile, 95% water, 0.1% formic acid), and solvent B a high fraction of organic phase such as Acetonitrile (i.e., 95% Acetonitrile, 5% water, 0.1% formic acid). Application of a solvent gradient enables a sufficient separation of peptides along a gradient. A gradient can be formed, e.g., from 5% to 25% solvent B within 43 min, 25% to 37% solvent B within 4 min, and finally up to 85% solvent B within 10 min, followed by 5% post-run equilibration (Gradient information in H€ ohne et al., 2018). Gradients can be adjusted according to the sample and the total ion chromatogram.

5.2 Mass spectrometry acquisition 5.2.1 Data-dependent acquisition and raw data analysis The chosen data acquisition technique can lead to dramatically different results in magnitude, depth, and overall reproducibility of peptide identifications and quantification (Rinschen, Limbutara, Knepper, Payne, & Pisitkun, 2018). Major data acquisition techniques are data-dependent acquisition (DDA), dataindependent acquisition (DIA), and targeted proteomics. The DDA strategy is typically used in discovery proteomics studies. In this case, selection of ions for fragmentation is dependent on previously established rules (e.g., the 10 most intensive peaks). The advantage of DDA is that the data analysis pipeline is straightforward, and its instrumentation is easy to set up. However, the data-dependent nature of this approach decreases the reproducibility of peptide identification. This means that not every precursor ion present in the sample is selected for fragmentation and identification run in each run, nor are the same precursor ions consistently selected for fragmentation between different runs. In the work by H€ohne et al., a full scan from 300 to 1750 mass-to-charge was acquired at a resolution of 70,000 (automated gain control target 3e6; maximum injection time, 20 ms), and this was followed by MS/MS of the top 10 peptides. Peptides were isolated using an isolation window of 2.1 Th. The automatic gain control target for MS/MS was set at 500,000 at a maximum injection time of 60ms. The resolution at the MS/MS level was set at 17,500 (H€ ohne et al., 2018).

9

ARTICLE IN PRESS 10

Single glomerular proteomics

5.2.2 Peptide and protein identification The single glomerular proteomics data is usually obtained in a “bottom up” approach and can thus be analyzed using a variety of software packages and algorithms. The first step usually involves a search against a sequence database. A commonly used platform is the MaxQuant (Cox & Mann, 2008; Cox et al., 2011) platform, but many other search algorithms exist such as Sequest, Mascot and many others.

5.2.3 Protein quantification Essentially, label-free and label-based protein quantification approaches need to be distinguished. Label-free quantification algorithms (e.g., Cox et al., 2014) are usually the most straightforward approaches because they do not need additional upstream processes. Yet, they come at the expense of accuracy of quantification. An introduction for a kidney researcher is given elsewhere (Rinschen, Limbutara, et al., 2018). Depending on the experimental design, label-free, metabolic or chemical labeling can be used in order to obtain peptide quantification. The result of quantification is an expression matrix that contains samples (columns) as well as proteins as rows. For statistical determination of altered proteins, a variety of tests can be used, including t-tests with an appropriate correction for multiple testing.

6 Bioinformatics analysis of single glomerular data 6.1 Targeted data quantification Targeted proteomics offers many advantages for data acquisition because it allows reducing the stochastic detection of high-abundant proteins in data-dependent acquisitions. Essentially, mass spectrometry quantification is performed on the MS2 level, meaning that fragment ions of a specific peptide are being analyzed. Robustness of targeted proteomics assays is one of the most important criterions for designing an assay. For targeted proteomics data, various guidelines regarding the design have been written. Currently, the guidelines classifying targeted proteomics assays in the CPTAC consortium are standard for design and reporting of targeted proteomics assay (Carr et al., 2014). Therefore, several parameters during acquisition need to be balanced. For targeted quantification, a parallel reaction monitoring PRM assay was set up (H€ ohne et al., 2018). Forty-one peptides were selected for scheduled PRM analysis. MS2 resolution was set at 140 k. The AGC target was set at 1,000,000 at a rather long maximum injection time of 500 ms. Peptides were isolated using an isolation window of 1.0 Th and fragmented with normalized collision energy of 27. For data analysis, several platforms are available for quantification including skyline (MacLean et al., 2010) and the OpenMS pipeline (Pfeuffer et al., 2017). It is important to optimize the collision energies, and to evaluate elution profiles and chromatograms, and observe that different peptide fragments have similar contributions to the overall quantification value. For recent overviews of the field of

ARTICLE IN PRESS 7 Limitations

targeted proteomics and references for successful assay development, the reader is directed to recent reviews (Ebhardt, Root, Sander, & Aebersold, 2015; Schubert, R€ ost, Collins, Rosenberger, & Aebersold, 2017).

6.2 Further bioinformatics analysis The most challenging part of any experiment is always the annotation and the statistical analysis to deduct biological meaning from the data. Different considerations have to be used in order to fully take advantage of the data. One of the first challenges is to deconvolute the data, e.g., by analyzing the relative contributions of cell populations (e.g., podocyte loss) to the overall proteome. To this end, deep proteomic dataset of isolated podocytes have been published (Rinschen, G€odel, et al., 2018) that can be used a resource for biological interpretation of differentially altered signals within single glomerular proteomic datasets. Signaling networks can also be contextualized by several glomerular phosphoproteomic datasets that have been recently been acquired. To address the connection of various measured parameters among each other, simple correlative approaches can be used. Differential quantitative data can be used for this, e.g., the protein quantitative expression values for every protein. Correlation coefficients can be clustered and defined as modules. The importance of modules to the different diseases and their morphological correlates are currently being investigated and cross-model or -biopsy correlations can be used to find common and distinct signatures across various patients or in different animal models of disease. Further impactful analyses are multivariate analyses, such as principal component analyses and others. Multivariate analysis can be used to detect inherent patterns in the data by transforming multidimensional data into a set of values of linear variables called principal components. Other multivariate analyses exist. If multiple observations of a large number of glomeruli are being made, clustering analyses such as t-Distributed Stochastic Neighbor Embedding (t-SNE) (van der Maaten & Hinton, 2008) can be used. Other algorithms have been developed for single cell data, such as RPhenograph and others (Levine et al., 2015). These can—in principle—also be applied to the single glomerular data to identify mathematical related glomerular proteomics datapoints. To conclude, statistical means to assess stoichiometry as well as variability of single glomeruli are currently under development and will require the acquisition of larger numbers of individual glomeruli. It is anticipated that this process is accelerated by developments in the single cell transcriptomics field.

7 Limitations There are limitations of the described workflow that are defined by the limitations of mass-spectrometry-based proteomics methods in general. Detection of proteins is biased toward high abundant proteins. In addition, the analysis of posttranslational protein modifications is not yet possible with this method.

11

ARTICLE IN PRESS 12

Single glomerular proteomics

8 Conclusion Single glomerular proteomics has recently been enabled by advances in glomerular isolation, ultrasensitive sample preparation and mass spectrometry-based technology and acquisition strategies. It enables to generate information on a single glomerulus that can be potentially overlaid with morphological criterions. The novel method consists of four essential steps: preparation of single glomeruli—by microdissection, glomerular preparation, or laser microdissection—followed by sample preparation, mass spectrometry analysis and bioinformatics analysis. This novel method enables the generation of sub-biopsy level proteomics data and will be useful for the interrogation of kidney biopsies or animal models of glomerular disease. In perspective, comprehensive data from individual glomeruli can be used in order to pinpoint novel targets in animal models of kidney disease or in patients with proteinuria and glomerular disease.

References Bankir, L., & Rouffignac, C. (1976). Anatomical and functional heterogeneity of nephrons € in the rabbit: Microdissection studies and SNGFR measurements. Pflugers Archiv— European Journal of Physiology, 366(1), 89–93. Bonvalet, J. P., Champion, M., Courtalon, A., Farman, N., Vandewalle, A., & Wanstok, F. (1977). Number of glomeruli in normal and hypertrophied kidneys of mice and guineapigs. The Journal of Physiology, 269(3), 627–641. Brinkkoetter, P. T., Ising, C., & Benzing, T. (2013). The role of the podocyte in albumin filtration. Nature Reviews. Nephrology, 9(6), 328–336. https://doi.org/10.1038/nrneph. 2013.78. Brix, S. R., Noriega, M., Tennstedt, P., Vettorazzi, E., Busch, M., Nitschke, M., et al. (2018). Development and validation of a renal risk score in ANCA-associated glomerulonephritis. Kidney International, 94(6), 1177–1188. https://doi.org/10.1016/j.kint.2018.07.020. Carr, S. A., Abbatiello, S. E., Ackermann, B. L., Borchers, C., Domon, B., Deutsch, E. W., et al. (2014). Targeted peptide measurements in biology and medicine: Best practices for mass spectrometry-based assay development using a fit-for-purpose approach. Molecular & Cellular Proteomics, 13(3), 907–917. https://doi.org/10.1074/mcp.M113.036095. Chronic Kidney Disease (CKD) Surveillance Project. (n.d.). Retrieved October 24, 2017, from https://nccd.cdc.gov/CKD/. Cox, J., Hein, M. Y., Luber, C. A., Paron, I., Nagaraj, N., & Mann, M. (2014). Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Molecular & Cellular Proteomics: MCP, 13(9), 2513–2526. https://doi.org/10.1074/mcp.M113.031591. Cox, J., & Mann, M. (2008). MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nature Biotechnology, 26(12), 1367–1372. https://doi.org/10.1038/nbt.1511. Cox, J., Neuhauser, N., Michalski, A., Scheltema, R. A., Olsen, J. V., & Mann, M. (2011). Andromeda: A peptide search engine integrated into the MaxQuant environment. Journal of Proteome Research, 10(4), 1794–1805. https://doi.org/10.1021/pr101065j.

ARTICLE IN PRESS References

Ebhardt, H. A., Root, A., Sander, C., & Aebersold, R. (2015). Applications of targeted proteomics in systems biology and translational medicine. Proteomics, 15(18), 3193–3208. https://doi.org/10.1002/pmic.201500004. Fogo, A. B. (2015). Causes and pathogenesis of focal segmental glomerulosclerosis. Nature Reviews. Nephrology, 11(2), 76–87. https://doi.org/10.1038/nrneph.2014.216. Heilmann, M., Neudecker, S., Wolf, I., Gubhaju, L., Sticht, C., Schock-Kusch, D., et al. (2012). Quantification of glomerular number and size distribution in normal rat kidneys using magnetic resonance imaging. Nephrology, Dialysis, Transplantation: Official Publication of the European Dialysis and Transplant Association—European Renal Association, 27(1), 100–107. https://doi.org/10.1093/ndt/gfr273. H€ohne, M., Frese, C. K., Grahammer, F., Dafinger, C., Ciarimboli, G., Butt, L., et al. (2018). Single-nephron proteomes connect morphology and function in proteinuric kidney disease. Kidney International, 93(6), 1308–1319. https://doi.org/10.1016/ j.kint.2017.12.012. H€ohne, M., Ising, C., Hagmann, H., V€olker, L. A., Br€ahler, S., Schermer, B., et al. (2013). Light microscopic visualization of podocyte ultrastructure demonstrates oscillating glomerular contractions. The American Journal of Pathology, 182(2), 332–338. https://doi. org/10.1016/j.ajpath.2012.11.002. Hoyer, K. J. R., Dittrich, S., Bartram, M. P., & Rinschen, M. M. (2019). Quantification of molecular heterogeneity in kidney tissue by targeted proteomics. Journal of Proteomics, 193, 85–92. https://doi.org/10.1016/j.jprot.2018.03.001. Hughes, C. S., Foehr, S., Garfield, D. A., Furlong, E. E., Steinmetz, L. M., & Krijgsveld, J. (2014). Ultrasensitive proteome analysis using paramagnetic bead technology. Molecular Systems Biology, 10, 757. https://doi.org/10.15252/msb.20145625. Hughes, C. S., Moggridge, S., M€uller, T., Sorensen, P. H., Morin, G. B., & Krijgsveld, J. (2019). Single-pot, solid-phase-enhanced sample preparation for proteomics experiments. Nature Protocols, 14(1), 68–85. https://doi.org/10.1038/s41596-018-0082-x. Iannaccone, P. M., & Jacob, H. J. (2009). Rats!. Disease Models & Mechanisms, 2(5–6), 206–210. https://doi.org/10.1242/dmm.002733. Katsuya, K., Yaoita, E., Yoshida, Y., Yamamoto, Y., & Yamamoto, T. (2006). An improved method for primary culture of rat podocytes. Kidney International, 69(11), 2101–2106. https://doi.org/10.1038/sj.ki.5000398. Levine, J. H., Simonds, E. F., Bendall, S. C., Davis, K. L., Amir, E. D., Tadmor, M. D., et al. (2015). Data-driven phenotypic dissection of AML reveals progenitor-like cells that correlate with prognosis. Cell, 162(1), 184–197. https://doi.org/10.1016/j. cell.2015.05.047. Loupy, A., Haas, M., Solez, K., Racusen, L., Glotz, D., Seron, D., et al. (2017). The Banff 2015 kidney meeting report: Current challenges in rejection classification and prospects for adopting molecular pathology. American Journal of Transplantation: Official Journal of the American Society of Transplantation and the American Society of Transplant Surgeons, 17(1), 28–41. https://doi.org/10.1111/ajt.14107. MacLean, B., Tomazela, D. M., Shulman, N., Chambers, M., Finney, G. L., Frewen, B., et al. (2010). Skyline: An open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics, 26(7), 966–968. https://doi.org/10.1093/bioinformat ics/btq054. Pfeuffer, J., Sachsenberg, T., Alka, O., Walzer, M., Fillbrunn, A., Nilse, L., et al. (2017). OpenMS—A platform for reproducible analysis of mass spectrometry data. Journal of Biotechnology, 261, 142–148. https://doi.org/10.1016/j.jbiotec.2017.05.016.

13

ARTICLE IN PRESS 14

Single glomerular proteomics

Rappsilber, J., Ishihama, Y., & Mann, M. (2003). Stop and go extraction tips for matrixassisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics. Analytical Chemistry, 75(3), 663–670. Rinschen, M. M., Benzing, T., Limbutara, K., & Pisitkun, T. (2015). Proteomic analysis of the kidney filtration barrier—Problems and perspectives. Proteomics. Clinical Applications, 9(11 12), 1053–1068. https://doi.org/10.1002/prca.201400201. Rinschen, M. M., G€odel, M., Grahammer, F., Zschiedrich, S., Helmst€adter, M., Kretz, O., et al. (2018). A multi-layered quantitative in vivo expression atlas of the podocyte unravels kidney disease candidate genes. Cell Reports, 23(8), 2495–2508. https://doi.org/10.1016/j. celrep.2018.04.059. Rinschen, M. M., Grahammer, F., Hoppe, A.-K., Kohli, P., Hagmann, H., Kretz, O., et al. (2017). YAP-mediated mechanotransduction determines the podocyte’s response to damage. Science Signaling, 10(474). https://doi.org/10.1126/scisignal.aaf8165. Rinschen, M. M., Limbutara, K., Knepper, M. A., Payne, D. M., & Pisitkun, T. (2018). From molecules to mechanisms: Functional proteomics and its application to renal tubule physiology. Physiological Reviews, 98(4), 2571–2606. https://doi.org/10.1152/ physrev.00057.2017. Rinschen, M. M., Pahmeyer, C., Pisitkun, T., Schnell, N., Wu, X., Maaß, M., et al. (2015). Comparative phosphoproteomic analysis of mammalian glomeruli reveals conserved podocin C-terminal phosphorylation as a determinant of slit diaphragm complex architecture. Proteomics, 15(7), 1326–1331. https://doi.org/10.1002/pmic.201400235. Rush, B. M., Small, S. A., Stolz, D. B., & Tan, R. J. (2018). An efficient sieving method to isolate intact glomeruli from adult rat kidney. Journal of Visualized Experiments: JoVE, 141. https://doi.org/10.3791/58162. Schubert, O. T., R€ost, H. L., Collins, B. C., Rosenberger, G., & Aebersold, R. (2017). Quantitative proteomics: Challenges and opportunities in basic and applied research. Nature Protocols, 12(7), 1289–1294. https://doi.org/10.1038/nprot.2017.040. Takemoto, M., Asker, N., Gerhardt, H., Lundkvist, A., Johansson, B. R., Saito, Y., et al. (2002). A new method for large scale isolation of kidney glomeruli from mice. The American Journal of Pathology, 161(3), 799–805. https://doi.org/10.1016/S0002-9440 (10)64239-3. Thongboonkerd, V. (2009). Renal and urinary proteomics: Methods and protocols. John Wiley & Sons. van der Maaten, L., & Hinton, G. (2008). Visualizing Data using t-SNE. Journal of Machine Learning Research, 9(Nov), 2579–2605. Virant-Klun, I., Leicht, S., Hughes, C., & Krijgsveld, J. (2016). Identification of maturationspecific proteins by single-cell proteomics of human oocytes. Molecular & Cellular Proteomics: MCP, 15(8), 2616–2627. https://doi.org/10.1074/mcp.M115.056887. Weening, J. J., D’Agati, V. D., Schwartz, M. M., Seshan, S. V., Alpers, C. E., Appel, G. B., et al. (2004). The classification of glomerulonephritis in systemic lupus erythematosus revisited. Journal of the American Society of Nephrology: JASN, 15(2), 241–250.