Quantitative Proteomics of All 14 Renal Tubule Segments in Rat

BASIC RESEARCH www.jasn.org

Kavee Limbutara, Chung-Lin Chou, and Mark A. Knepper

Epithelial Systems Biology Laboratory, Systems Biology Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland

ABSTRACT Background Previous research has used RNA sequencing in microdissected kidney tubules or single cells isolated from the kidney to profile gene expression in each type of kidney tubule epithelial cell. However, because proteins, not mRNA molecules, mediate most cellular functions, it is desirable to know the iden- tity and amounts of each protein species to understand function. Recent improvements in the sensitivity of mass spectrometers offered us the ability to quantify the proteins expressed in each of 14 different renal tubule segments from rat. Methods We manually dissected kidney tubules from rat kidneys and subjected samples to protein mass spectrometry. We used the “proteomic ruler” technique to estimate the number of molecules of each protein per cell. Results Over the 44 samples analyzed, the average number of quantified proteins per segment was 4234, accounting for at least 99% of protein molecules in each cell. We have made the data publicly available online at the Kidney Tubule Expression Atlas website (https://esbl.nhlbi.nih.gov/KTEA/). Protein abundance along the renal tubule for many commonly studied water and solute transport proteins and metabolic enzymes matched expectations from prior localization studies, demonstrating the overall reliability of the data. The site features a “correlated protein” function, which we used to identify cell type–specific transcription factors expressed along the renal tubule. Conclusions We identified and quantified proteins expressed in each of the 14 segments of rat kidney tubules and used the proteomic data that we obtained to create an online information resource, the Kidney Tubule Expression Atlas. This resource will allow users throughout the world to browse segment-specific protein expression data and download them for their own research.

JASN 31: ccc–ccc, 2020. doi: https://doi.org/10.1681/ASN.2020010071

The introduction of RNA sequencing (RNA-Seq) has can be independently regulated by processes that con- provided an infusion of new information about gene trol protein stability and translation.12,13 expression in the kidney. The method is extremely Consequently, there is a strong need for quanti- sensitive, allowing transcriptomic proﬁling of indi- tative proteomic methods with sensitivity that vidual renal tubules1 and single cells isolated from kidney.2–5 RNA-Seq data are very valuable in helping researchers identify hypotheses for further study, sup- Received January 17, 2020. Accepted March 9, 2020. plying what amounts to “instant preliminary data” Published online ahead of print. Publication date available at when provided as online resources. Yet, there is a ma- www.jasn.org. jor limitation in the sense that proteins, not mRNA Correspondence: Dr. Mark A. Knepper, National Heart, Lung, molecules, are responsible for most biologic func- and Blood Institute, National Institutes of Health, Building 10, tions in the cell. Several studies have demonstrated Room 6N307, 10 Center Drive, MSC-1603, Bethesda, MD 20892- that protein abundances are often not predictable 1603. Email: [email protected] – from mRNA levels6 11 because protein abundances Copyright © 2020 by the American Society of Nephrology

JASN 31: ccc–ccc,2020 ISSN : 1046-6673/3106-ccc 1 BASIC RESEARCH www.jasn.org rivals that of transcriptomics. The problem has been that, Significance Statement although RNA-Seq benefits from PCR amplification, similar amplification is not possible for proteins. Instead, increased The renal tubule’s 14 distinct segments consist of epithelial cells sensitivity for mass spectrometry–based proteomics de- with different transport and metabolic functions. Identifying the pends on improvements in mass spectrometer sensitivity. proteins mediating each function is crucial to gaining an overall understanding of kidney physiology and pathophysiology. New 14 Largely because of such progress, Rinschen and colleagues developments in protein mass spectrometry have resulted in a have recently shown that it is possible to obtain deep pro- marked increase in sensitivity of protein detection and quantifica- teomes from microdissected renal tubules. Here, we use tion. In this study, the authors manually microdissected kidney tu- similar techniques to identify proteomes of 14 distinct renal bules from rat kidneys and leveraged the advances in protein mass tubule segments, working with microdissected tubules spectrometry to identify and quantify the proteins expressed in each of the 14 tubule segments. They used these data to create an from rats. online information resource, the Kidney Tubule Expression Atlas, to allow researchers throughout the world to browse segment- specific protein expression data and download them for their METHODS own investigations.

Microdissection for 30 minutes. The modified single-pot, solid phase–enhanced We followed the previously published standard protocol for sample preparation protocol17,18 was used to clean and digest 1,15 rat kidney tubule segment microdissection. Concisely, proteins into peptides for mass spectrometry analysis. The re- – – male Sprague Dawley rats age 4 8 weeks (Animal Study Pro- sulting peptide mixtures were then fractionated using micro- tocol No. H-0110R4; approved by the Animal Care and Use scale basic reverse-phase liquid chromatography19 into eight Committee, National Heart, Lung, and Blood Institute) were fractions (elution buffers: 5%, 7.5%, 10%, 13%, 16%, 20%, euthanized by decapitation, and kidneys were perfused via 25%, and 30% acetonitrile in 10 mM triethylammonium bi- aorta with 10 ml of buffer solution (120 mM NaCl, 5 mM carbonate). Peptide mixture fractions were concatenated (frac- KCl, 2.5 mM Na HPO , 5 mM HEPES, 1.2 mM MgSO , 2 4 4 tion 1 with 5, 2 with 6, 3 with 7, and 4 with 8), resulting in four 2mMCaCl , 5 mM sodium acetate, 5.5 mM glucose, adjusted 2 fractions per sample (except one cortical collecting duct sample to pH 7.4 by NaOH, bubbled with 100% oxygen) to remove that was not concatenated). Fractionated samples were then the blood. The kidneys were then further perfused with 10 ml analyzed with LC-MS/MS using a Dionex UltiMate 3000 digestion solution containing the same buffer plus either nano HPLC system coupled with Orbitrap Fusion Lumos 1 mg/ml of collagenase B (Roche) for cortex or 3 mg/ml for (Thermo Scientific). Peptides were introduced into a nanotrap medulla. (Separate rats were used for cortical and medullary column at a flow rate of 300 nl/min and then separated on a dissections.) For medullary tissue, 1 mg/ml (outer medulla) or m 3 3 mg/ml (inner medulla) of hyaluronidase (Worthington Bio- reverse-phase EASY-Spray PepMap column (C18, 75 m 50 chemical Corporation) was also added to the digestion solu- cm) using a nonlinear gradient from 2% to 28% acetonitrile in tion. Kidneys were removed and cut into thin slices, and then, 0.1% formic acid (runtime 120 minutes). Data-dependent ac- they were incubated with the same digestion solution at 37°C quisition was performed with MS1 resolution of 120,000 and for 30 minutes (cortex), 40 minutes (outer medulla), or MS2 resolution of 15,000/30,000 at cycle time of 3 seconds. fi 90 minutes (inner medulla). After the digestion, kidney tubule All mass spectrum raw les were searched against a rat microdissection was performed under a Wild M8 stereomi- UniProt reference proteome (release 2019_10) using Max- 20 fi croscope. Each tubule segment was distinguished by its char- Quant 1.6.10.43. Parameters for amino acid modi cation fi acteristics as previously described.1 A short description of the including xed carbamidomethyl (C) and variable Oxidation recognition criteria is given as Supplemental Table 1. Tubule (M), Acetyl (Protein N-term). Match between run option fi length was measured.16 Several dissected tubules were pooled was enabled. Trypsin/P was con gured as digestion enzyme. together and transferred with 2 ml to a clean petri dish con- Default settings were used for other parameters. taining ice-cold PBS. Tubules were washed several times To estimate protein abundance in each sample, we applied with PBS and then lysed in 15 mlof1.5%SDS/100mM the proteomic ruler approach21 using an in-house Python triethylammonium bicarbonate/13 Halt protease and script. Briefly, protein intensities were summed for each sam- phosphatase inhibitor by pipetting up and down under a ple and used to normalize differences in total protein amount. stereomicroscope. Lysed samples were sonicated using a Molecular weight and number of theoretical peptides (tryptic cup horn probe (Misonix Sonicator 3000) for 5 minutes digested peptides with length 7–30 amino acids) were used to andkeptfrozenat280°C until further processed. correct for differences in signal intensity caused by protein size and sequence. On the basis of the assumption that total Mass Spectrometry–Based Proteomics amount of histones is approximately equal to amount of For each sample, several tubules were pooled together. Protein DNA,21 total normalized signal intensity of histones in each lysates were reduced with 10 mM dithiothreitol at 37°C for sample was used to estimate copy number per cell for every 30 minutes followed by alkylation using 10 mM iodoacetamide protein. Plotting the total histone signal against the estimated

2 JASN JASN 31: ccc–ccc,2020 www.jasn.org BASIC RESEARCH number of cells from each sample gave a strong correlation in the IMCD. Expression levels were quantified as copies per (Supplemental Figure 1). The total cells per sample were esti- cell (cpc) using the Proteomic Ruler technique.21 Values were mated for segments other than thin descending limbs from successfully quantified over six orders of magnitude, a feat data for cells per unit length curated by Clark et al.22 and unachievable with immunochemical methods. The full data- multiplied by the total length of tubules in each sample. set can be interrogated at the publicly accessible Kidney Tubule Expression Atlas (KTEA) website (https://esbl.nhlbi.nih.gov/ Data Availability KTEA/), and cpc values for all replicates can be downloaded The mass spectrometry proteomics data have been deposited to from a link at the bottom of the “Data Table” tab. The KTEA the ProteomeXchange Consortium (http://proteomecentral. website has several options for data display and interroga- proteomexchange.org) via the PRIDE partner repository23 tion. In general, data are reproducible across all replicates with the dataset identifier PXD016958. with median coefficients of variation (SD/mean) for log10- transformed cpc values of ,0.14 in all segments (Table 1). Our calculations indicate that the proteome depth obtained RESULTS in this study is likely to account for at least 99% of the total protein mass in the cell (Supplemental Table 2). Among all Fourteen renal tubule segments were profiled with at least proteins quantified, about 25% are “housekeeping proteins,” three replicates each. Mass spectra have been archived at defined here as being expressed in all 14 tubule segments.1 PRIDE (Project accession: PXD016958). The terminology Here, we focus on those with various degrees of renal tubule used is on the basis of Chen et al.24 and is summarized in specificity. Table 1. Over the 44 samples, pooled from 90 rats, the average number of quantified proteins was 4234. Average total tubule Transporters length per sample ranged from 16 mm in the S3 proximal The various renal tubule segments are distinguished in part tubule to 91 mm in the inner medullary thin descending functionally by differences in transport. Figure 1 shows the limb (DTL3). Using measurements of total protein per unit distribution of well studied water and solute transport pro- length from Vandewalle et al.,16 the average protein mass per teins among the 14 renal tubule segments. In general, the lo- sample ranged from about 1.7 mg in the DTL2 to about 4.8 mg cations and relative abundances of these transport proteins

Table 1. Microdissected segments studied Short No. of Length per No. of Proteins Median CV of Full Name Origin a a b Name Replicates Sample (mm) Quantified log10 (cpc) S1 First segment of proximal tubule Cortical labyrinth 3 16.462.47 27346103 0.033 S2 Second segment of proximal Cortical medullary 318.364.78 47506415 0.053 tubule ray S3 Third segment of proximal Outer stripe of 315.864.94 35086287 0.033 tubule outer medulla DTL1 Descending thin limb type 1 Inner stripe of outer 371.561.0 4228619 0.02 (short-looped nephron) medulla DTL2 Descending thin limb type 2 Inner stripe of outer 344.968.54 33626312 0.067 (long-looped nephron) medulla DTL3 Descending thin limb type 3 Inner medulla 3 91.169.0 4426650.9 0.024 (long-looped nephron) ATL Ascending thin limb Inner medulla 3 69.7610.1 3285661.5 0.028 mTAL Medullary thick ascending limb Inner stripe of outer 422.567.5 34946413 0.093 medulla cTAL Cortical thick ascending limb Cortical medullary 336.9610.4 476261228 0.137 ray DCT Distal convoluted tubule Cortical labyrinth 3 27.263.6 48546808 0.083 CNT Connecting tubule Cortical labyrinth 3 17.564.1 51206286 0.035 CCD Cortical collecting duct Cortical medullary 432.7610.2 52656744 0.068 ray OMCD Outer medullary collecting duct Inner stripe of outer 318.261.2 39776216 0.039 medulla IMCD Inner medullary collecting duct Inner medulla 3 38.068.3 5421695.1 0.034 CV, coefficient of variation. aValues are mean 6 SD. bMedian CV (SD/mean) of the base 10 logarithm of cpc across all quantified proteins.

JASN 31: ccc–ccc,2020 Proteomics of Renal Tubule Segments 3 BASIC RESEARCH www.jasn.org

Proximal Tubules Thin limbs Thick limbs DCT Collecting duct

S1 S2 S3 DTL1 DTL2 DTL3 ATL mTAL cTAL DCT CNT CCD OMCD IMCD

Aqp2 0 0 0 0 0 0 0.01 0 0 0.01 0.19 0.23 0.52 1 water Aqp4 0 0 0 0 0 0 0 0 0 0 0.07 0.07 0.1 1 water Aqp6 0 0 0 0 0 0 0 0 0 0 0.16 0.25 1 0 Cl– Atp6v1b1 0.05 0.03 0 0 0 0 0 0 0.06 0.11 0.66 1 0.29 0.01 H+ Atp6v1c2 0 0 0 0 0 0 0 0 0 0.08 1 0.94 0.56 0 H+ Atp6v1g3 0 0 0 0 0 0 0 0 0 0.03 0.52 1 0.27 0 H+ Clcnka 0 0 0 0 0 0.03 1 0.07 0 0 0 0 0 0.01 Cl– Clcnkb 0 0 0 0 0 0 0 0.01 0.94 0.88 1 0.58 0.25 0 Cl– Kcnj1 0 0 0 0 0 0 0 1 0.92 0.28 0.12 0.09 0 0 K+ Kcnj10 0 0 0 0 0 0 0 0 0.01 1 0.13 0.11 0 0 K+ Kcnj16 0 0.08 0 0 0 0 0 0.07 0.16 1 0.04 0 0 0 K+ + Rhbg 0 0 0 0 0 0 0 0 0 0.01 1 0.9 0.85 0.03 NH3/NH4 + Rhcg 0 0 0.09 0 0 0 0 0 0 0.39 0.85 0.83 1 0 NH3/NH4 Scnn1a 0 0 0 0 0 0 0 0 0 0 1 0.79 0 0 Na+ Scnn1g 0 0 0 0 0 0 0 0 0 0 1 0.94 0.34 0 Na+ Slc12a1 0 0 0 0.01 0.01 0.01 0.01 0.4 1 0.05 0 0 0 0 Na+/K+/CI– Slc12a3 0 0 0 0 0 0 0 0 0 1 0 0 0 0 Na+/CI– Slc14a2 0 0 0 0.09 0 0 0 0 0 0 0 0 0 1 urea Slc16a1 1 0.15 0 0 0.02 0.01 0 0.04 0.08 0.04 0 0 0 0.02 lactate Slc22a12 0 1 0.79 0.01 0 0 0 0 0 0 0 0 0 0 urate/CI– Slc22a6 0.03 1 0 0 0 0 0 0 0 0.01 0 0 0 0 organic anions – – Slc26a4 0 0 0 0 0 0 0 0 0 0 1 0.56 0 0 CI /HCO3 – – Slc26a7 0 0 0 0 0 0 0 0 0 0.01 0 0 1 0 CI /HCO3 Slc34a1 0.11 1 0.03 0 0 0 0 0 0 0 0 0 0 0 Na+/phosphate Slc34a3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 Na+/phosphate – – Slc4a1 0 0 0 0 0 0 0 0 0 0.03 0.3 0.58 1 0 CI /HCO3 + – Slc4a4 0.49 1 0 0 0 0 0 0 0.02 0 0 0 0 0 Na /HCO3 + – Slc4a9 0 0 0 0 0 0 0 0 0 0 1 0.77 0 0 Na /HCO3 Slc5a1 0 1 0.97 0 0 0 0 0 0.08 0 0 0 0 0 Na+/glucose Slc5a2 1 0.02 0 0 0 0 0 0 0.02 0.02 0 0 0 0 Na+/glucose Slc6a18 0 0.55 1 0 0 0 0 0 0 0 0 0 0 0 amino acids Trpm7 0 0 0 0 0 0 0 0 0.04 1 0 0 0 0 Mg2+

Figure 1. Relative protein expression levels of commonly studied renal transporters and channels in 14 microdissected renal tubule segments. Copy number values are normalized to maximum value for each protein along the renal tubule. Yellow shading is included to provide a facile means of identifying patterns of expression from proximal S1 to IMCD. See the Data Table tab of the KTEA website to download full data for all replicates. (Low values in some segments [e.g., AQP2 in ATL and DCT or Slc12a1 in thin limb segments] could either be due to low levels of ectopic expression or a small amount of contamination from ambient mRNA.) match knowledge from the literature, supporting the validity Slc12a1 (bumetanide-sensitive Na-K-2Cl cotransporter) in of the measurements. Examples include Slc5a2 (SGLT2) in S1 mTAL and cTAL29; Slc12a3 (thiazide-sensitive Na-Cl cotrans- proximal tubule25; Slc5a1 (SGLT1) in S2 and S3 proximal tu- porter) in DCT30; and Aqp2 (aquaporin-2) in CNT through bule26; Clcnka (CLC-Ka chloride channel) in ATL27;Clcnkb IMCD.31 Also, intercalated cell markers like Slc26a4 (CLC-Kb chloride channel in cTAL through OMCD)28; (pendrin)32 and Slc4a1 (bicarbonate-chloride exchanger 1)33

4 JASN JASN 31: ccc–ccc,2020 www.jasn.org BASIC RESEARCH were found only in the CNT, CCD, and OMCD (i.e.,inthe In general, the expression patterns shown match prior knowl- segments that contain intercalated cells). edge about the distribution of metabolic functions along the nephron,34 including (1) absence of glucose utilization Metabolic Enzymes (glycolysis) by proximal tubule cells with ATP generation by There are also important differences among renal tubule seg- fatty acid oxidation and amino acid oxidation; (2) selective ments in terms of metabolic function. Figure 2 summarizes roles of proximal tubule cells in gluconeogenesis, arginine the distributions of important (generally rate-limiting) non- production, fructose conversion to glucose, and uric acid pro- housekeeping metabolic enzymes along the renal tubule. duction; (3) selective production of the osmoprotective

Proximal Tubules Thin limbs Thick limbs DCT Collecting duct

S1 S2 S3 DTL1 DTL2 DTL3 ATL mTAL cTAL DCT CNT CCD OMCD IMCD

Idh3a 0.7 1 0.57 0.07 0.29 0.05 0.09 0.75 0.94 0.79 0.62 0.71 0.37 0.05 TCA cycle

Hk1 0 0 0.04 0.12 0.4 0.14 0.17 1 0.94 0.95 0.84 0.48 0.53 0.22 Glycolysis

Pfkp 0.04 0.07 0.21 0.12 0.22 0.07 0.2 0.79 1 0.81 0.68 0.7 0.65 0.38 Glycolysis

Pkm 0 0.02 0.1 0.05 0.08 0.06 0.08 0.09 0.11 0.17 0.27 0.45 0.28 1 Glycolysis

Ldha 0.1 0.12 0.16 0.03 0.09 0.06 0.06 0.16 0.21 0.22 0.61 0.88 0.8 1 Lactate metabolism

Ldhb 0.71 0.29 0.02 0.02 0.06 0.02 0.01 0.52 0.77 1 0.33 0.19 0.09 0.02 Lactate metabolism

Fbp1 0.47 1 0.67 0.01 0.01 0 0 0 0.02 0.02 0 0.01 0 0 Gluconeogenesis

Pck1 0.8 1 0.15 0 0.01 0 0 0 0 0 0 0 0 0 Gluconeogenesis

Gys1 0 0 0 0 0.03 0 0 0.39 0.74 1 0.59 1 0.27 0.11 Glycogen synthesis

Khk 0.17 0.71 1 0.01 0.01 0 0 0 0.01 0.01 0 0 0 0 Fructose conversion

Akr1b1 0 0 0 0.01 0.01 0.2 1 0 0 0 0 0.01 0 0.56 Sorbitol synthesis

Acads 0.06 0.84 1 0.01 0.02 0.01 0.01 0 0.07 0.07 0.14 0.19 0.06 0.07 Fatty acid oxidation

Acadl 0.29 1 0.49 0.02 0.04 0.01 0.03 0.15 0.09 0.1 0.04 0.05 0.02 0.01 Fatty acid oxidation

Cpt2 0.21 1 0.31 0.03 0.08 0.02 0.03 0.22 0.46 0.76 0.37 0.35 0.15 0.05 Fatty acid oxidation

Cpt1a 0.22 0.59 0.45 0.03 0.05 0.05 0.11 0.59 1 0.91 0.25 0.33 0.07 0.12 Fatty acid oxidation

Acaca 0 0 0 0 0 0 0 0.06 1 0.86 0.51 0.96 0 0.87 Fatty acid synthesis

Acacb 0 0.03 0 0.01 0 0 0 0.47 1 0.57 0.04 0 0.03 0.01 Fatty acid synthesis

Arg2 0 0.16 1 0.02 0.02 0.03 0.03 0 0 0 0.12 0.38 0.2 0.26 Arginine catabolism

Asl 1 0.16 0.04 0.01 0.01 0.01 0 0.02 0.08 0.05 0.05 0.05 0.02 0.04 Arginine synthesis

Ass1 1 0.49 0.41 0.01 0.01 0 0 0 0.02 0.03 0 0.01 0 0 Arginine synthesis

Gls 0.42 0.18 0.08 0.07 0.15 0.18 0.11 0.25 1 0.55 0.4 0.52 0.21 0.31 Glutamine metabolism

Glud1 0.17 0.76 1 0.02 0.04 0.03 0.02 0.08 0.13 0.09 0.06 0.08 0.03 0.02 Glutamate metabolism

Got2 0.54 1 0.42 0.03 0.09 0.05 0.07 0.34 0.51 0.6 0.31 0.31 0.16 0.08 Amino acid metabolism

Xdh 1 0.52 0.09 0 0 0 0 0 0 0.02 0 0 0 0.03 Uric acid synthesis

Ckb 0 0.01 0 0.01 0 0.01 0.03 0.05 0.01 0.05 0.26 1 0.13 0.15 High enery phosphate buffer

Ckmt1 0 0 0 0.02 0.05 0.01 0.01 0.45 0.83 1 0.82 0.82 0.29 0 High enery phosphate buffer

Figure 2. Relative protein expression levels of differentially expressed metabolic enzymes in 14 microdissected rat renal tubule segments. Copy number values are normalized to maximum value for each protein along the renal tubule. Yellow shading is included to provide a facile means of identifying patterns of expression along the renal tubule. See the Data Table tab of the KTEA website to download full data for all replicates.

JASN 31: ccc–ccc,2020 Proteomics of Renal Tubule Segments 5 BASIC RESEARCH www.jasn.org enzyme aldose reductase in inner medullary segments; (4) distribution to prior knowledge further supports the validity selective expression of rate-limiting enzymes for ammonia- of the measurements. genesis (Pck1 and Glud1) in proximal tubule cells; and (5) maximum abundance of creatine kinase (important for Transcription Factors high-energy phosphate buffering) in segments with the high- The high degree of ﬁdelity to prior knowledge regarding the est rates of sodium reabsorption (mTAL, cTAL, DCT) or distribution of transport and metabolic functions demon- transport against a large Na gradient (CNT, CCD). As with strated in Figures 1 and 2 suggests that the data can be used transporters, the ﬁdelity of the match of metabolic enzyme to identify novel hypotheses about other types of function. An

Proximal Tubules Thin limbs Thick limbs DCT Collecting duct

S1 S2 S3 DTL1 DTL2 DTL3 ATL mTAL cTAL DCT CNT CCD OMCD IMCD

Elf1 0 0 0 0.34 0 0 0 0 0.04 0.03 0.03 0 1 0.38 ETS

Elf5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 ETS

Esrrg 0 0 0 0 0 0 0 0.52 1 0.43 0.4 0.13 0.01 0 Nuclear receptor

Foxc1 0 0 0.01 1 0.52 0.65 0.05 0 0 0 0 0 0 0 Forkhead

Foxi1 0 0 0 0 0 0 0 0 0 0 0.49 1 0.22 0 Forkhead

Gata3 0 0 0 0 0 0 0 0 0 0 0.03 0.66 1 0.82 zf−GATA

Hnf1a 0.43 1 0.07 0 0 0 0 0 0 0 0 0 0 0 Homeobox

Hnf1b 0 0.88 1 0.75 0.21 0.29 0.08 0 0.7 0.09 0.11 0.19 0.15 0.01 Homeobox

Hnf4a 0 1 0.09 0 0 0 0 0 0 0 0 0 0 0 Nuclear receptor

Hoxb6 0 0 0 0 0 0.04 0 0 0 0 0 0.01 0 1 Homeobox

Hoxb7 0 0 0 0 0 0.36 0 0 0.02 0.23 0 0.2 0.87 1 Homeobox

Hoxd8 0 0 0 0.05 0 0 0 0.12 0.77 1 0.47 0.72 0.74 0.11 Homeobox

Hoxd9 0 0 0 0 0 0 0 0 0 0 1 0.66 0 0 Homeobox

Irf3 0.03 0.02 0 0 0 0.16 0 0 0 0 0 0 0 1 IRF

Irf9 0 0 0 0.09 0 0.06 0 0 0 0 0.17 0.14 0.14 1 IRF

Nfat5 0 0 0 0.18 0.73 1 0.58 0 0 0 0.03 0 0.06 0.41 RHD

Nr2f2 0 0 0 0.23 0.02 0.34 0 0.09 1 0.03 0 0 0 0 COUP

Pax2 0 0 0 0.31 0 0.8 0.47 0 0 0 0 0 0 1 PAX

Stat2 0 0.06 0 0.07 0.03 0.13 0 0.03 0.09 0.12 0.25 0.29 0.48 1 STAT

Tfap2b 0 0 0 0 0 0 0 0 1 0 0.9 0 0 0 AP−2

Tfcp2l1 0 0 0 0 0 0 0 0 0.02 0.02 1 0.86 0.25 0 GRH/CP2

Vdr 0 0 0 0 0 0 0 0 0.04 1 0.38 0 0 0 Nuclear receptor

Zfp503 0 0 0 0 0 0 0 0 0 1 0 0 0 0 Elbow/Noc

Figure 3. Relative protein expression levels of differentially expressed transcription factors in 14 microdissected rat renal tubule segments. Copy number values are normalized to maximum value for each protein along the renal tubule. Yellow shading is included to provide a facile means of identifying patterns of expression along the renal tubule. See the Data Table tab of the KTEA website to download full data for all replicates.

6 JASN JASN 31: ccc–ccc,2020 www.jasn.org BASIC RESEARCH

z−score example is mapping of tubule segment–speciﬁctranscrip- −10123 tion factors (Figure 3). Here, we used the Correlated Pro-

Tmem40 Rac3 teins function of our R Shiny-based KTEA website (https:// Rab9b Mx1 Gpha2 esbl.nhlbi.nih.gov/KTEA/) to identify transcription factors Anxa8 Crabp2 Gpx2 with distributions similar to those of each of the transporters Nxpe4 Lpin3 in Figure 1. This analysis identified some transcription fac- Aqp4 Rhcg Fkbp10 tors that have been well characterized with respect to roles in Slc26a7 Ldhc 35 36 Aqp6 renal tubule–selective gene expression (e.g.,Elf5, Gata3, Ddx43 Dbndd2 37,38 39 40 41,42 43 Fuom Hoxb7, Foxi1, Nfat5, Pax2, and Tfcp2l1 )as Dynlt3 CNT/CD Mt3 Isoc2 well as some for which there is little or no prior knowledge. Mrpl52 Cox6a1 fi fi Med22 Many transcription factors were con ned to speci c regions B3gnt2 Calb1 Stradb of the renal tubule: proximal tubule (Hnf1a and Hnf4a), Atp6v1f Atp6v0d2 ’ Slc26a4 thin limbs of Henle s loop (Foxc1), distal convoluted tubule Atp6v1c2 Atp6v1g3 Pgam2 (Vdr and Zfp503), general collecting duct (Gata3 and Stat2), Rab3d Dpm3 Capn6 non-IMCD collecting duct segments (Foxi1 and Tfcp2l1), Urad Nudt10 Tsc22d1 and IMCD (Elf5, Hoxb6, Irf3, and Irf9). Others have broader

Ly6b DCT Tmem52b ﬁ Slc8a1 distributions that may be related to speci c functions. For ex- Slc12a3 Gcgr Cldn16 ample, two transcription factors associated with osmotic reg- Casr Cyp2s1 40 41 Dusp9 ulation (Nfat5 and Pax2 ) were found selectively in inner Ptgs2 Fxyd1 Cldn19 medullary thin limbs and inner medullary collecting ducts Kcnt1 Ndrg4 LOC108348190 TAL where osmotic regulation is most important. In addition, this Prom2 Ptger3 analysis identiﬁed two transcription factor proteins involved in Umod RT1−Ba Tmem72 innate immunity (Irf3 and Irf9) that are selectively expressed in Ppp1r1a Cldn10 Ppp1r1b the IMCD segment, providing novel hypotheses about the de- Wnt5a Sh3gl3 Plcxd3 fense against retrograde introduction of viruses and bacteria Padi2 LOC100909474

Cldn11 ATL into the renal tubules from the pelvic space. A full analysis of Lypd2 Nrgn fi fi Psca IMCD-speci c proteins identi ed several additional proteins Nrip3 Parm1 Nradd involved in innate immunity (Gene Ontology Biologic Process Fgf2 Chn2 “ ” Slc16a14 term innate immune response ), namely Mx1, Mx2, Oasl, Sncg Akap11 S100a4 Oas1a, Sting1, and Trim21. Slc14a1 Slc4a11 Fst The Hox family of transcription factors, associated with Tmem79 Cntf Sdc2 segmentation of structures in a variety of developmental Slc6a6 Sfrp1 Smoc2 model systems, is represented by Hoxb6, Hoxb7, Hoxd8, Cldn23 Mgarp fi Gprc5a Descending limb and Hoxd9 (Figure 3). Hoxd9 and Hoxb6 are con ned to Spp1 Plet1 Gpc3 the early and late parts of the collecting duct system, respec- S100a6 Klrb1a Fstl1 tively. In contrast, Hoxd8 spans the boundary between meta- Slc14a2 Cavin3 – Arrb2 nephric mesenchyme derived structures and ureteric Tmem35a Cyp4b1 – Etnppl bud derived structures. Hoxb7, generally considered a col- Anks4b Slco4c1 lecting duct marker, is most strongly expressed in the Slco1a3 Slco1a1 Slc7a13 OMCD and IMCD but is not expressed in the CNT, consistent Aldh1b1 Mphosph8 Flvcr2 with the finding that the Hoxb7 promoter does not drive Cre Aqp7 Acbd4 44 Cyp2e1 recombinase expression in the CNT. Aadac Slc13a3 Slc34a1 Gpm6a Slc17a3 Sorbs1 The Seven-Membrane Spanning Receptors Pxmp2 Ugt2b15

Slc5a8 Proximal Tubules The analysis also provides a mapping of the most important Ambp Igfbp4 Prodh2 seven-membrane spanning receptors, which include both G Apoa1 Dpt Apoa4 Folh1 Ccl9 Rbp4 Ang2 Spink1l Smim24 The top 12 proteins of each segment with at least four times greater

S1 S2 S3 . ATL DCT CNT

CCD abundance than the average of all other segments (log ratio 2) cTAL 2 DTL1 DTL2 DTL3 IMCD mTAL OMCD and adjusted P value ,0.01 are shown in the heat map. Copy Figure 4. Heat map of the most highly differentially expressed numbers were standardized with z score. Some well known marker proteins along the renal tubule. For each tubule segment, log2- proteins are shown, including Slc34a1 (proximal tubule), Spp1 transformed protein copy numbers were used to compare (descending limb), Umod (TAL), Slc12a3 (DCT), Calb1 (CNT), and between the segment and the average of all other segments. Aqp4 (collecting duct).

JASN 31: ccc–ccc,2020 Proteomics of Renal Tubule Segments 7 BASIC RESEARCH www.jasn.org

S1 S2 S3

10 r=0.46 r=0.52 r=0.51 p−value<1e−35 p−value<1e−35 p−value<1e−35 0

DTL1 DTL2 DTL3

10 r=0.39 r=0.43 r=0.45 p−value<1e−35 p−value<1e−35 p−value<1e−35 0

ATL mTAL cTAL

10 r=0.44 r=0.47 r=0.45 (Protein copy per cell+1)

2 p−value<1e−35 p−value<1e−35 p−value<1e−35 0 Log

DCT CNT CCD

10 r=0.46 r=0.48 r=0.51 p−value<1e−35 p−value<1e−35 p−value<1e−35 0 0 5 10 15 OMCD IMCD

10 r=0.44 r=0.54 p−value<1e−35 p−value<1e−35 0 0 5 10 15 0 5 10 15

Log2 (TPM+1)

Figure 5. Protein:transcript correlations for all proteins quantified in each renal tubule segment. Overall, the median correlation coefficient among all segments was 0.46. These values are consistent with the conclusion that mRNA level is an important determinant of protein level but that other factors, such as translational efficiency and protein half-life, also are important determinants of protein expression level. TPM, transcripts per million.

8 JASN JASN 31: ccc–ccc,2020 www.jasn.org BASIC RESEARCH protein–coupled receptors and frizzled receptors (Supplemental protein levels may not be predictable from transcript levels Table 3). These proteins include some that are well studied, such owing to post-transcriptional regulation. We addressed this as the prostaglandin E2 receptor EP3 subtype (Ptger3) and the issue by looking for the correlation between mRNA abun- calcium-activated receptor (Casr) in the thick ascending limb as dance profiles along the rat renal tubule1 and protein abun- well as the V2 vasopressin-receptor (Avpr2) in collecting duct dance profilesfromthisstudy(Figure5).Therewasahighly segments. Others, such as the oxytocin receptor in the cortical significant correlation in all 14 renal tubule segments. thick ascending limb, have not been investigated. However, at any given transcript abundance level, there was a broad range of protein abundances, indicating Discovering Additional Segment-Specific Proteins that there are other determinants of protein abundance. The potential use of the data described in this paper for One such determinant is protein half-life. Indeed, when hypothesis discovery extends beyond transcription factors. we mapped protein half-life values from global half-life Figure 4 shows a general analysis of differentially expressed profiling studies in mpkCCD cells12,13 to protein-mRNA genes along the renal tubule independent of molecular function. abundance ratios in CCD measured in this study, there Although many of the proteins reported in this figure are well was a highly significant correlation (Figure 6). It is likely known segment-specificmarkers(e.g., Slc34a1 [Na-phosphate that variability in protein half-life is also in part due to cotransporter] in proximal tubule, Spp1 [osteopontin] in de- variable translation efficiency, although we do not have scending limb of Henle, Umod [uromodulin] and Casr [calcium data to test this hypothesis. receptor] in TAL, Slc12a3 [thiazide-sensitive Na-Cl cotrans- Another way to view correlation between mRNA levels porter] in DCT, Calb1 [calbindin] in CNT, and Aqp4 in col- and protein levels is in terms of congruence between mRNA lecting ducts), many are not well characterized with regard to and protein expression patterns along the renal tubule. their segment-specific functional roles and may form the ba- This can be gauged by regression analysis for each gene sis of future studies. A similar analysis reporting values selec- product, comparing mRNA and protein levels across the tive for particular regions of the kidney is shown in 14 renal tubule segments. Figure 7 shows the distribution Supplemental Figure 2. of correlation coefficients for all genes using Pearson regression analysis. Similar results were found for Spearman Correlation with Transcriptomic Data regression (Supplemental Figure 3). Here, high-magnitude As noted in the Introduction, the rationale for proteomic pro- positive values indicate a high degree of congruence, zero filing of the nephron versus transcriptomic profiling is that values indicate no congruence, and high-magnitude

r=0.30 p−value=2.1e−34 20 N=1610 1.2 Median: 0.37 N = 6030

10 0.8 Density

0 (Protein copy per cell+1/TPM+1)

2 0.4 Log

0255075100 0.0 Protein Half−life (hour) −1.0 −0.5 0.0 0.5 1.0 Figure 6. Relationship between protein half-lives and protein- Gene–wise protein−mRNA Pearson correlation transcript ratios in cortical collecting duct. There is a significant positive correlation between protein half-life and protein- Figure 7. Distribution of genewise regression coefficients (Pearson) transcript ratio (Pearson r 50.30). Protein half-life data were de- for correlations between protein (log2 copy number) and transcript rived from previously published data in mpkCCD cells (https:// (log2 TPM) abundance along the renal tubule. The median corre- hpcwebapps.cit.nih.gov/ESBL/Database/ProteinHalfLives/). TPM, lation coefficient was 0.37. Note that many genes had negative transcripts per million. correlation coefficients. TPM, transcripts per million.

JASN 31: ccc–ccc,2020 Proteomics of Renal Tubule Segments 9 BASIC RESEARCH www.jasn.org negative values indicate a mirror image relationship. Al- that protein abundance levels are not predictable from though there are many genes with a high degree of congru- transcript levels alone. ence, 50% had correlation coefﬁcients ,0.37 (median value), suggesting that determinants of protein abundance frequently vary along the renal tubule. Figure 8A shows DISCUSSION examples of commonly studied gene products with high congruence, whereas Figure 8B shows examples with low This paper reports a new web resource (the KTEA) for support congruence. Overall, the evidence supports the concept of investigations of renal physiology and pathophysiology on

A B Slc5a2 Maoa 2.5M Protein Protein 300.0K 2.0M 1.5M 200.0K 1.0M 500.0K 100.0K 0.0 value 300.0 value 60.0 RNA RNA 200.0 40.0 100.0 20.0 0.0 0.0 S1 S2 S3 S1 S2 S3 ATL ATL DCT CNT DCT CNT CCD CCD cTAL cTAL DTL3 DTL1 DTL2 DTL3 DTL1 DTL2 IMCD IMCD mTAL mTAL OMCD OMCD segment segment

Slc34a1 Maob Protein 4.0M Protein 150.0K 3.0M 100.0K 2.0M 1.0M 50.0K 0.0 0.0 0.0 value value RNA 4.0K RNA 0.0 3.0K 0.0 2.0K 0.0 1.0K 0.0 0.0 0.0 S3 S1 S2 S1 S2 S3 ATL ATL DCT CNT DCT CNT CCD CCD cTAL cTAL DTL1 DTL2 DTL3 DTL1 DTL2 DTL3 IMCD IMCD mTAL mTAL OMCD OMCD segment segment

Slc12a1 Calr 8.0M Protein Protein 8.0M 6.0M 6.0M 4.0M 4.0M 2.0M 2.0M 0.0

value 300.0 value RNA 2.0K RNA 1.5K 200.0 1.0K 500.0 100.0 0.0 S1 S2 S3 S1 S2 S3 ATL ATL DCT CNT DCT CNT CCD CCD cTAL cTAL DTL1 DTL2 DTL3 DTL2 DTL3 DTL1 IMCD IMCD mTAL mTAL OMCD OMCD segment segment

Slc12a3 Bsg Protein 1.0M Protein 8.0M 750.0K 6.0M 500.0K 4.0M 250.0K 2.0M 0.0 0.0 value

value 5.0K RNA 900.0 RNA 4.0K 600.0 3.0K 300.0 2.0K 0.0 1.0K S1 S2 S1 S3 S3 S2 ATL ATL DCT CNT DCT CNT CCD CCD cTAL cTAL DTL2 DTL1 DTL3 DTL1 DTL3 DTL2 IMCD IMCD mTAL mTAL OMCD OMCD segment segment

Aqp2 Abcb8

15.0M Protein 100.0K Protein 10.0M 5.0M 50.0K 0.0 0.0 value value

20.0K RNA RNA 15.0K 40.0 10.0K 20.0 5.0K 0.0 0.0 S1 S2 S3 S1 S2 S3 ATL DCT CNT ATL CCD cTAL DCT CNT DTL1 DTL2 DTL3 CCD IMCD cTAL mTAL DTL1 DTL2 DTL3 IMCD mTAL OMCD OMCD segment segment

Figure 8. Comparison of protein and mRNA abundance proﬁles along the renal tubule. Average protein copy numbers and average TPM values along the renal tubule are shown. (A) Examples of strongly correlated protein/mRNA. (B) Examples of proteins with different expression pattern from the mRNAs counterpart.

10 JASN JASN 31: ccc–ccc,2020 www.jasn.org BASIC RESEARCH the basis of comprehensive proteomic analysis of microdissec- Office of the NHLBI Division of Intramural Research for hosting the ted tubules from rats. Overall, relatively deep proteomes were Kidney Tubule Expression Atlas website. obtained in all 14 renal tubule segments, averaging 4234 quan- Dr. Knepper and Dr. Limbutara designed the study; Dr. Chou tified proteins per segment. The protein abundance profiles and Dr. Limbutara carried out experiments; Dr. Knepper and for transporter proteins and metabolic enzymes matched Dr. Limbutara analyzed the data; Dr. Knepper and Dr.Limbutara closely with prior data, supporting the validity of the measure- made the figures; Dr. Knepper and Dr. Limbutara drafted manuscript; ments. This match supports the idea that the dataset can be Dr. Limbutara made the website; and Dr. Chou, Dr. Knepper, and used to reliably identify new hypotheses about other biologic Dr. Limbutara approved the final version of the manuscript. processes in renal epithelial cells. For example, we used the data to identify differentially expressed transcription factors along the renal tubule, including many that have not yet been DISCLOSURES studied. The KTEA website, built on a Shiny45 platform, has several None. options for data display and analysis. One of them, the Cor- related Proteins function, is particularly useful in identifying proteins whose abundance profiles along the renal tubule are FUNDING similar. The Correlated Proteins function was used to generate fi Figure 3. Another function, Pro le, used to generate Figure 8 The work was primarily funded by the National Heart, Lung, and Blood allows users to compare the proteomic profile of a given pro- Institute (NHLBI) Division of Intramural Research projects ZIA-HL001285 tein with previously obtained profiles from RNA-Seq analysis (to Dr. Knepper) and ZIA-HL006129 (to Dr. Knepper). of microdissected tubules,1 useful in identifying sites of post- transcriptional regulation. Success with this study was made possible by recent in- SUPPLEMENTAL MATERIAL creases in sensitivity of commercial mass spectrometers.46 It depended also on strategies to capture proteins and to This article contains the following supplemental material online at scale down the biochemical procedures needed to prepare http://jasn.asnjournals.org/lookup/suppl/doi:10.1681/ASN.2020010071/-/ the samples for mass spectrometric analysis. The protocol DCSupplemental. here is similar to that developed for microdissected tubule Supplemental Figure 1. Scatter plot between estimated number of and single-glomerulus analysis by Rinschen and colleagues.14 cells and mass spectrometry signal intensity of histone proteins. It is conceivable that further technical development will allow Supplemental Figure 2. Heat map of the most differentially ex- quantification of even more proteins. However, our calcula- pressed proteins in selected regions of the kidney. tions indicate that the proteome depth obtained in this study is Supplemental Figure 3. Distribution of genewise Spearman cor- likely to account for at least 99% of the total protein mass in relations between protein and mRNA. each cell type. Supplemental Table 1. A short description of each renal tubule The proteomic ruler method provided a means of estimating segment. copy number per cell on the basis of the idea that DNA-cladding Supplemental Table 2. Estimation of percentage of total protein histones are expressed at relatively equal amounts in different detected. cell types for diploid cells.21 The results, therefore, provide an apt Supplemental Table 3. The seven-membrane spanning receptors means of determining relative protein abundance among renal expressed along the renal tubule. tubule cell types. This assumption seems to be validated by the resemblance of expression profilesofmanyabundantproteinsto corresponding profiles among transcripts (Figure 8A). The val- REFERENCES idity of total histones to provide an index of cell number is 1. Lee JW, Chou CL, Knepper MA: Deep sequencing in microdissected supported by Supplemental Figure 1, showing a strong correla- renal tubules identifies nephron segment-specific transcriptomes. JAm tion between cell number per sample and total histone signal. Soc Nephrol 26: 2669–2677, 2015 2. 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12 JASN JASN 31: ccc–ccc,2020 Supplemental Material

Table of Contents

- Supplemental Table 1: A short description of each renal tubule segment. - Supplemental Table 2: Estimation of percent of total protein detected. - Supplemental Table 3: 7-membrane spanning receptors expressed along the renal tubule. - Supplemental Figure 1: Scatter plot between estimated number of cell and mass spectrometry signal intensity of histone proteins. - Supplemental Figure 2: Heatmap of the most differentially expressed proteins in selected regions of the kidney. - Supplemental Figure 3: Distribution of gene-wise Spearman correlations between protein and mRNA.

Segment Region Full name Short description S1 Cortex S1 Proximal tubule Proximal tubule directly attached to the glomerulus. S2 Cortex S2 Proximal tubule Straight part of proximal tubule obtained from medullary ray. S3 Cortex S3 Proximal tubule Final portion of proximal tubule from outer medulla before transitioning into thin limb. DTL1 Outer medulla Short descending limb Thin descending limb from outer medulla characterized by attachment to S3, transitioning into ascending limb within outer medulla, and smaller diameter than DTL2. DTL2 Outer medulla Long descending limb, Thin descending limb from outer medulla, wider than DTL1 and continues outer medulla into inner medulla. DTL3 Inner medulla Long descending limb, Thin descending limb from inner medulla. inner medulla ATL Inner medulla Thin ascending limb Thin ascending limb from inner medulla characterized by transitioning into thick ascending limb. mTAL Outer medulla Medullary thick Thick ascending limb from outer medulla, bigger than thin limb and more ascending limb granular appearance. cTAL Cortex Cortical thick ascending Thick ascending limb from medullary ray with smaller diameter than S2 and limb CCD. DCT Cortex Distal convoluted tubule Convoluted tubule segment in the cortical labyrinth, having a smaller diameter than proximal tubule. The appearance of DCT is different from adjacent CNT segment which has cobblestone appearance. Only DCTs within around 0.5 mm from macula densa were collected. CNT Cortex Connecting tubule Branching tubules in the cortical labyrinth with cobblestone appearance. CCD Cortex Cortical collecting duct Tubule segments dissected from medullary rays of the cortex with cobblestone appearance. OMCD Outer medulla Outer medullary Tubule segments dissected from outer medulla with cobblestone collecting duct appearance. IMCD Inner medulla Inner medullary The largest tubule segment in the inner medulla. Multiple segments are collecting duct merging together as they descend deeper in the medulla.

Supplemental Table 1: A short description of each renal tubule segment.

Segment Sum copy Detection Number of Number of Estimated Percent per cell threshold quantified undetected undetected copy detected proteins proteins per cell S1 2.13E+09 3150 2952 5048 1.59E+07 99.26 S2 4.47E+09 444 5410 2590 1.15E+06 99.97 S3 4.49E+09 1378 3881 4119 5.67E+06 99.87 DTL1 7.20E+08 2560 4369 3631 9.29E+06 98.73 DTL2 9.01E+08 41 4089 3911 1.60E+05 99.98 DTL3 8.09E+08 1969 4596 3404 6.70E+06 99.18 ATL 8.80E+08 1870 3513 4487 8.39E+06 99.06 MTAL 1.26E+09 148 4229 3771 5.59E+05 99.96 CTAL 1.85E+09 211 5865 2135 4.50E+05 99.98 DCT 1.75E+09 259 5688 2312 5.98E+05 99.97 CNT 1.59E+09 627 5647 2353 1.48E+06 99.91 CCD 1.91E+09 12 6550 1450 1.67E+04 100 OMCD 1.14E+09 643 4395 3605 2.32E+06 99.8 IMCD 1.35E+09 2086 5621 2379 4.96E+06 99.63

Supplemental Table 2. Estimation of percent of total protein detected. For each tubule segment, the sum of average protein copy per cell was calculated. Because undetected proteins are likely to have low copy number, we used 20th percentile of copy number in each segment as estimate copy number for the missing proteins. Assuming that 8000 different proteins are expressed in each segment, the numbers of undetected proteins are calculated by subtracting number of quantified proteins from 8000. The total estimated copy per cell of all undetected proteins are then simply multiplication of number of undetected proteins and the corresponding detection threshold.

RANK S1 S2 S3 DTL1 DTL2 DTL3 ATL MTAL CTAL DCT CNT CCD OMCD IMCD

1 Gprc5c Gprc5c Gprc5c Gprc5a Gprc5a Gprc5c Gprc5c Ptger3 Casr Gprc5c Gprc5c Gprc5c Gprc5c Gprc5c (5.04) (5.69) (5.62) (5.14) (5.1) (5.22) (4.5) (4.36) (5.4) (4.61) (4.76) (4.68) (4.49) (4.96) 2 Adgrg1 Adgrg1 Adgrg1 Gprc5c Gprc5c Gprc5a Adgrg1 Gprc5c Gprc5c Casr Adgrf5 Adgrf5 Adgrf5 Avpr2 (4.32) (4.15) (1.18) (4.88) (4.95) (5.15) (3.87) (4.15) (4.45) (4.38) (4.18) (4.51) (4.34) (4.46) 3 Lpar3 Pth1r Adgrg1 Adgrg1 Ackr3 Gprc5a Casr Ptger3 Gpr39 Ackr3 Ackr3 Ackr3 Gprc5a (3.9) (3.84) (3.54) (3.67) (4.18) (3.68) (3.91) (4.12) (3.63) (3.8) (4.17) (3.97) (4.42) 4 Adgrl2 Adgrf5 Ackr3 Adgrf5 Adgrf5 Adgrg1 Gcgr Celsr2 Adgrg1 Gpr39 Gpr39 Gprc5b (2.04) (2.88) (1.4) (3.77) (3.47) (3.66) (3.98) (3.22) (3.56) (4) (3.67) (4.21) 5 Adgrf5 Celsr2 Adgrl2 Adgrg1 Adgrf5 Calcr Adgrl2 Celsr2 Adgrg1 Celsr2 Ackr3 (2) (2.82) (0.97) (3.74) (3.17) (2.84) (2.69) (3.55) (3.85) (3.35) (4.03) 6 Adgrl2 Adgrl2 Adgrl2 Ackr3 Gpr183 Casr Gprc5b Fzd6 (2.68) (2.26) (2.79) (2.51) (2.62) (3.57) (2.45) (3.89) 7 Celsr2 Adgrg1 Ptger3 Gpr39 Celsr2 Avpr2 Adgrg1 (2.45) (2.69) (2.43) (2.59) (3.35) (1.4) (3.79) 8 Calcrl Pth1r Adgrg1 Calcr Celsr1 Celsr1 Gpr39 (2.41) (2.43) (2.35) (2.54) (3.06) (0.84) (3.3) 9 Gpr39 Oxtr Adgrf5 Fzd1 Fzd6 Celsr1 (2.26) (2.33) (2.07) (2.06) (2.75) (3.17) 10 Celsr2 Celsr1 Celsr1 Avpr2 Fzd1 (2.24) (1.95) (2.01) (1.13) (2.82) 11 Adgrf5 Calcrl Grm6 Lpar1 Grm6 (2.11) (1.12) (2.01) (0.98) (2.42) 12 Celsr1 Gprc5b Fzd4 Celsr2 (1.87) (1.27) (0.96) (2.42) 13 Calcrl Casr Fzd1 Lpar5 (1.17) (1.1) (0.83) (1.13) 14 Calcr (0.82) 15 Grm6 (0.76)

Supplemental Table 3. 7-membrane spanning receptors expressed along the renal tubule. Numbers in parentheses represent average log10 copy number per cell in each tubule segment.

● S1 ● S3 ● mTAL ● DCT ● CCD ● IMCD segment ● S2 ● ATL ● cTAL ● CNT ● OMCD

p - value = 5.8e−05 11.0 Adjusted R2 = 0.38

● ● ) l ● ●

a ● ● ●

n ● ● g 10.5 i s ● e

n ● o ● ●

t ● s

i ● ● H

( ● 10.0 ●

10 ● ● ● ● ● g ●

o ●

L ●● ● ● ●

9.5 ● ●

●

5000 10000 15000 20000 Estimated number of cell

Supplemental figure 1. Scatter plot between estimated number of cell and mass spectrometry signal intensity of histone proteins. The number of cells in each sample was calculated by multiplying total tubule length per sample with estimated number of cells per length in the literature.1

z−score −1 0 1 2

Tmem79 Ncam1 Psca Eps8l1 Ptgs1 Ugt8 Fabp4 Ctnnal1 Them6 Akap12 Lgals1 Cryab Plet1 Medulla Tacstd2 Gprc5a Thy1 Plod2 Proser2 Slc6a12 S100a6 Ifi47 Arhgef37 Crybg1 Arl4d Rhbg Atp6v0d2 Degs2 Gata3 Btc Fam241a Itga2 Ptges Lgals3 Phactr2

Atp6v1c2 Collecting ducts Aqp2 Nxpe4 Ldhc Atp6v1g3 Aqp4 Arnt2 Slc7a5 RT1−Ba Smpx Ndufb1 Cldn19 Slc16a7 Mtmr7 Cldn16 Cldn10 Casr Slc12a1 Ptger3 Kcnt1 Cyp2s1 Ppp1r1b

Tmem72 Thick ascending limb LOC108348190 Umod Ppp1r1a Mettl7b Slc22a5 Ces2g Sult1b1 Gamt Sult1c2 Akr1d1 Lrrc19 Cltrn Neu1 RGD1562699 Slc47a1 Cdhr2 RGD1564865 Slc34a1

Anks4b Tubules Proximal A0JPQ1 Agmat Iyd Smim24 S1 S2 S3 ATL DCT CNT CCD cTAL DTL1 DTL2 DTL3 mTAL IMCD OMCD

Supplemental figure 2. Heatmap of the most differentially expressed proteins in selected regions of the kidney. Closely related tubule segments were grouped together, namely proximal tubule (S1, S2, S3), thick ascending limbs (mTAL, cTAL), collecting ducts (CCD, OMCD, IMCD), and renal medulla (DTL1, DTL2, DTL3, ATL, mTAL, OMCD, IMCD). The average values of log2- transformed protein copy numbers in each group were compared with the average of all other segments. Top twenty proteins of each group with at least 4 times more abundance (log2 ratio > 2) and adjusted p-value < 0.01 are shown in the heatmap. Copy numbers were standardized with z-score to help visualized multiple proteins in the heatmap. Median: 0.38 N = 6030 1.0 Density 0.5

0.0

−1.0 −0.5 0.0 0.5 1.0 Gene−wise protein−mRNA Spearman correlation

Supplemental figure 3. Distribution of gene-wise Spearman correlations between protein (log2 copy number) and transcript (log2 TPM) abundance along renal tubule. Around 85% of genes have a positive correlation with a median of 0.38. The distribution of Spearman correlations is almost identical to the distribution of Pearson correlation (See Figure 5).

Reference: 1. Clark JZ, Chen L, Chou CL, Jung HJ, Lee JW, Knepper MA: Representation and relative abundance of cell-type selective markers in whole-kidney RNA-Seq data. Kidney Int, 95: 787- 796, 2019