Single-Nucleus Transcriptional Profiling of Chronic Kidney Disease after Cisplatin Nephrotoxicity

Abstract

Cisplatin induces both acute and chronic nephrotoxicity during chemotherapy in patients with cancer. Presented here is the first study of single-nucleus RNA sequencing (snRNA-seq) of cisplatin-induced nephrotoxicity. Repeated low-dose cisplatin treatment (RLDC) led to decreases in renal function and kidney weight in mice at 9 weeks. The kidneys of these mice showed tubular degeneration and dilation. snRNA-seq identified 16 cell types and 17 cell clusters in these kidneys. Cluster-by-cluster comparison demonstrated cell type–specific changes in gene expression and identified a unique proximal tubule (PT) injury/repair cluster that co-expressed the injury marker kidney injury molecule-1 (Kim1) and the proliferation marker Ki-67. Compared with control, post-RLDC kidneys had 424 differentially expressed genes in PT cells, including tubular transporters and cytochrome P450 enzymes involved in lipid metabolism. snRNA-seq also revealed transcriptional changes in potential PT injury markers (Krt222, Eda2r, Ltbp2, and Masp1) and repair marker (Bex4). RLDC induced inflammation and proinflammatory cytokines (RelB, TNF-α, Il7, Ccl2, and Cxcl2) and the expression of fibrosis markers (fibronectin, collagen I, connective tissue growth factor, vimentin, and α-smooth muscle actin). Together, these results provide new insights into RLDC-induced transcriptional changes at the single-cell level that may contribute to the development of chronic kidney problems in patients with cancer after cisplatin chemotherapy.

Single-cell or single-nucleus RNA sequencing (snRNA-seq) is a powerful, unbiased technology for comprehensive analysis of cell subtypes, cell-specific gene expression, and their changes in physiological and pathologic conditions. Using this technology, recent studies have begun to unveil the single-cell transcriptional profiles in kidneys under physiological and disease conditions,1, 2, 3, 4 including kidney development,5, 6, 7 diabetic kidney disease,8, 9, 10 kidney transplantation,11, 12, 13 ischemic and endotoxic acute kidney injury,¹⁴ and maladaptive kidney repair and renal fibrosis.^15,16

Cisplatin is a potent and widely used chemotherapy drug for cancer treatment, but is notorious for adverse effects in normal tissues and organs, especially in the kidneys. Over a quarter of patients with cancer develop kidney problems during or after cisplatin chemotherapy. Acute nephrotoxicity of cisplatin has the typical feature of acute kidney injury (AKI), characterized by abrupt loss of renal function and damage to renal tubules. Chronic kidney problems after cisplatin exposure exhibit some key features of chronic kidney disease (CKD), including a gradual decline of renal function and tubule-interstitial histopathologies, such as tubular atrophy, atubular glomeruli, and tubulointerstitial fibrosis. Although cisplatin-induced AKI was a focus of research for years, recent studies have turned interest to chronic kidney problems after cisplatin exposure. This is facilitated by the establishment of the animal and cellular models of repeated low-dose cisplatin treatment (RLDC), which permits the investigation of the chronic changes in kidneys after cisplatin exposure.17, 18, 19, 20, 21, 22, 23

The present study was designed to analyze the changes of gene transcriptional profile at the single-cell resolution during the development of chronic kidney problems after RLDC treatment. Specifically, the kidney tissues were analyzed in a well-characterized mouse model of RLDC by snRNA-seq. The analysis led to the identification of a unique proximal tubule (PT) cell population co-expressing the cell proliferation marker Ki-67 and the PT injury marker Kim1. In addition, keratin 222 (Krt222), ectodysplasin A2 receptor (Eda2r), latent transforming growth factor beta binding protein 2 (Ltbp2), and MBL associated serine protease 1 (Masp1) were identified as the potential new markers of PT injury, whereas brain expressed, X-linked 4 (Bex4) was identified as a potential PT repair marker in the RLDC model. RLDC also induced PT-specific transcription changes in genes important for transport, inflammation, and fibrosis. Together, these results provide new insights into RLDC-induced transcriptional changes at the single-cell level that may contribute to the development of chronic kidney problems in patients with cancer after cisplatin chemotherapy.

Materials and Methods

Animals and RLDC Treatment

The Charlie Norwood VA Medical Center reviewed and approved all animal procedures used in this study. Male C57BL/6 mice were from Jackson Laboratory (Bar Harbor, ME) and housed in a pathogen-free animal facility of Charlie Norwood VA Medical Center under a 12/12-hour light/dark pattern with free access to food and water. Mice were given four consecutive weekly injections of 8 mg/kg cisplatin. Kidney tissues were collected at 4 or 9 weeks after the first injection for renal function and renal pathology analysis. Blood urea nitrogen levels and estimated glomerular filtration rate were determined to indicate renal function. Blood urea nitrogen was measured using the commercial kit from EKF Diagnostics USA (Stanbio Laboratory) (Boerne, TX).

Transcutaneous Measurement of Glomerular Filtration Rate

Estimated glomerular filtration rate was measured in mice by transcutaneously monitoring the clearance of fluorescein isothiocyanate–labeled sinistrin using the devices from MediBeacon (Mannheim, Germany), as previously described.¹⁹ Briefly, mice were anesthetized with isoflurane inhalation, shaved, and depilated 1 day before the measurement. The transdermal glomerular filtration rate monitors were adhered to the skin using a double-sided adhesive patch and mounted on the mouse using silk tape. Fluorescein isothiocyanate–sinistrin at 75 mg/kg body weight (15 mg/mL dissolved in 0.9% sterile saline) was injected via a tail vein. Estimated glomerular filtration rate was monitored for 1 hour, and data were analyzed using the elimination kinetics curve of fluorescein isothiocyanate–sinistrin.

Single-Nucleus RNA Sequencing

Nuclei were isolated from kidney tissues, as previously described.¹⁰ Briefly, kidney samples of cortex with outer medulla were cut into <8-mm³ pieces and homogenized in 2 mL of ice-cold Nuclei EZ Lysis buffer (NUC101; Sigma, St. Louis, MO) with protease inhibitor (5892791001; Roche, Indianapolis, IN) and RNase inhibitor [N2615 (Promega, Madison, WI); AM2696 (Life Technologies, Carlsbad, CA)] using a Dounce homogenizer (885302-0002; Kimble Chase, Rockwood, TN). The homogenate was further incubated on ice for 5 minutes with an additional 2 mL of lysis buffer. Then, the homogenate was filtered through a 40-μm cell strainer (43-50040-51; pluriSelect, El Cajon, CA) followed by centrifugation at 500 × g for 5 minutes at 4°C. The pellet was resuspended and washed with 4 mL of the buffer and incubated on ice for another 5 minutes. After another centrifugation, the pellet was resuspended in Nuclei Suspension Buffer (1× phosphate-buffered saline, 1% bovine serum albumin, and 0.1% RNase inhibitor) and filtered through a 5-μm cell strainer (43-50005; pluriSelect). The quality and quantity of nuclei were examined under a microscope. Nuclei were processed using Chromium Single Cell Controller and Chromium Next GEM Single Cell 3′ Reagent kit version 3.1 (10x Genomics, Pleasanton, CA), according to the manufacturer's protocol. Briefly, 5000 to 6000 nuclei were loaded onto the Chromium Controller to generate single-cell gel beads in emulsion (GEMs) coated with unique 10× cell barcodes, unique molecular identifiers, and poly dT oligos. RNA molecules from single nuclei were reverse transcribed within droplets to generate barcoded cDNAs. After break emulsion, cDNA molecules were pre-amplified, fragmented, ligated to an adaptor, and amplified with sample indexes, followed by a double-sided size selection using SPRI beads (Beckman Coulter, Brea, CA). The final libraries were assessed by Bioanalyzer 2100 (Agilent, Colorado Springs, CO) and Qubit HS DNA (Thermo Fisher Scientific, Waltham, MA) and pooled. The pooled library was quantified by real-time quantitative PCR and calibrated with a control sequencing library. The libraries were sequenced on NextSeq 500 (Illumina, San Diego, CA) using NextSeq 500 Mid Output version 2.5, 150 cycles kit (Illumina) with 28 bp (read 1), 8 bp (indexing run), and 91 bp (RNA read 2), followed by the primary analysis on the single-nuclei RNA sequencing. Reads from the raw FASTQ files demultiplexed were mapped to the RNA regions from mm10 Mouse Genome reference by Star aligner linked with Cell Ranger 5.0.1 pipeline (10X Genomics, Pleasanton, CA) with the intron-include flag to output clusters representing the cell populations and the corresponding up-regulated genes annotated as the cell surface markers in each cell population, followed by visualizing and organizing output with a loupe cell browser. As a result, it generated 22,000 to 25,000 reads/nucleus with 97 to 101 million reads/sample at a target of 3.8 to 4.5 × 10³ cells identified as >86.6% in bases with a quality score of 30 or higher (Q30 bases) in RNA read as well as >92.7% genome mapping rates in a range of 1100 to 1900 median genes per nucleus.

Immunoblot Analysis

The kidney cortex and outer medulla were lysed in 2% SDS buffer with protease inhibitor cocktail (Sigma) and Benzonase nuclease (EMD Millipore, Burlington, MA). Protein concentration was determined by the Pierce BCA protein assay kit (Thermo Fisher Scientific). Equal amounts of protein were loaded in each lane and separated by SDS-PAGE. The blots were incubated with blocking buffer after being transferred onto polyvinylidene difluoride membranes. The blots were incubated with primary antibodies at 4°C overnight and with secondary antibodies for 1 hour at room temperature. Antigens on the blots were revealed by an enhanced chemiluminescence kit (Thermo Scientific). Primary antibodies were from the following sources: anti–vascular cell adhesion molecule 1 (Vcam1; ab134047), anti–α-smooth muscle actin (ab5694), anti-fibronectin (ab2413), and anti–cyclophilin B (ab16045) from Abcam (Cambridge, UK); anti–connective tissue growth factor (CTGF; NBP2-16025) and anti–collagen I (NBP1-30054) from Novus Biologicals (Littleton, CO); and anti-vimentin (number 3932) from Cell Signaling (Danvers, MA). Secondary antibodies for immunoblot analysis were from Jackson ImmunoResearch Laboratories (West Grove, PA).

RNA Extraction and Real-Time PCR

Kidney cortical and outer medulla samples were dissected and freshly frozen in liquid N₂ and kept at –80°C until use. Total RNA was extracted with a mirVana miRNA Isolation Kit (Life Technologies, Thermo Fisher Scientific). For tumor necrosis factor (TNF)-α mRNA detection, reverse transcription was performed using the high-capacity cDNA reverse transcription kit from ThermoFisher Scientific, and PCR was performed using TaqMan Universal PCR Master Mix from ThermoFisher Scientific. TNF-α and glyceraldehyde-3-phosphate dehydrogenase real-time quantitative PCR (qPCR) probe assays were purchased from Integrated DNA Technologies, Inc. (Coralville, IA). For other real-time quantitative PCR, 1 μg RNA was reverse transcribed using a cDNA Transcription Kit (Bio-Rad, Hercules, CA), and real-time quantitative PCR was performed using SYBR Green PCR Master Mix (Bio-Rad). Glyceraldehyde-3-phosphate dehydrogenase was used for normalization. The sequence of the primers for the qPCR is listed in Table 1.

Table 1.

PCR Primers

Target genes	Forward sequence	Reverse sequence
Krt222	5′-CACGGATGAGGGCTGTTTAG-3′	5′-GGGTTTGATGGAGGGAATACTG-3′
Eda2r	5′-GAAGGCCAACTGCACAAATAC-3′	5′-GTACACTGAACCTCGGAAGAAG-3′
Masp1	5′-GCAAGGAGAGGGAAGATGAAG-3′	5′-GTTGTCTGTGTGGAGGATGTAG-3′
Ltbp2	5′-CCCAGGATGGACAACATCAA-3′	5′-AAGCCAGAACGGCAGATAC-3′
Kcnh8	5′-ACAGACTAGGGTGAGTTGGA-3′	5‘-CAGATACCAGAGGCGACATTAC-3′
Bex4	5′-CTAACTTTCTCTGGGCCATACC-3′	5′-TAAAGGCAAGTTCCGAGAAGG-3′
RelB	5′-TGCCGAATCAACAAGGAGAG-3′	5′-TGCTGAACACCACGGATATG-3′
IL7	5′-TTGCCCGAATAATGAACCAAAC-3′	5′-TGCGAGCAGCACGATTTA-3′
Ccl2	5′-CATCCACGTGTTGGCTCA-3′	5′-GATCATCTTGCTGGTGAATGAGT-3′
Cxcl2	5′-GACAGAAGTCATAGCCACTCTC-3′	5′-GCCTTGCCTTTGTTCAGTATC-3′
KLF6	5′-CTTCCGAAAGCATACCGGTG-3′	5′-GCCTGGAAGCCTCTTTTAGC-3′
Spp1	5′-CTTTCACTCCAATCGTCCCTAC-3′	5′-CAGAAACCTGGAAACTCCTAGAC-3′
Runx1	5′-CTCTGACCATCACCGTCTTTAC-3′	5′-CATCTAGTTTCTGCCGATGTCT-3′
Gapdh	5′-AATGGTGAAGGTCGGTGTG-3′	5′-GTGGAGTCATACTGGAACATGTAG-3′

Histologic Analysis

Kidney tissues were fixed with 4% paraformaldehyde in phosphate-buffered saline, embedded in paraffin, and sectioned at 5 μmol/L. Sirius red staining was performed according to a standard protocol from the manufacturer (Chondrex Inc., Woodinville, WA). Periodic acid–Schiff staining was performed according to a standard protocol from Sigma. For immunohistochemical staining, tissue sections were heated in the antigen retrieval buffer. Then, the sections were incubated with 3% H₂O₂ and then blocking buffer. The slides were then exposed to the primary antibody at 4°C overnight. After washing, the slides were incubated with ImmPRESS HRP Horse Anti-Rabbit IgG (MP-7401) or ImmPRESS-AP Horse Anti-Goat IgG (MP-5405) (both from Vector Laboratories, Burlingame, CA) for 1 hour at room temperature. After washing, color was developed with a DAB kit ImmPACT DAB Substrate, Peroxidase (HRP) (SK-4105) and ImmPACT Vector Red Substrate, Alkaline Phosphatase (SK-5105) (both from Vector Laboratories). The primary antibodies for immunostaining included anti–Ki-67 (9129; Cell Signaling), anti-Kim1 (AF1817; R&D Systems, Minneapolis, MN), anti-Vcam1 (ab134047; Abcam), and anti-Krt20 (provided by Dr. Venkatachalam at the University of Texas Health Science Center at San Antonio as a gift from NeoBiotechnologies, Union City, CA).

Statistical Analysis and Software

Quantitative data were expressed as means ± SEM. Statistical analysis was conducted using the GraphPad Prism software 9.2.0 (332) (GraphPad Software, La Jolla, CA). Statistical differences between the two groups were determined by a two-tailed unpaired t-test. P < 0.05 was considered significantly different. Functional enrichment analysis [gene ontology (GO) term analysis] was performed using DAVID Bioinformatics Resources 6.8 (https://david.ncifcrf.gov, last accessed January 3, 2022). Heat maps, enrichment bar charts, volcano plots, and bubble plots were constructed using the OmicShare tools (https://www.omicshare.com/tools, last accessed December 30, 2021).

Results

Chronic Kidney Injury and Renal Function Decline in Post-RLDC Mice

For RLDC treatment, male C57BL/6 mice were given four consecutive weekly injections of 8 mg/kg cisplatin, and blood samples and kidney tissues were collected for analysis (Figure 1A). Blood urea nitrogen was increased after RLDC at 4 weeks (Figure 1B). At 9 weeks after RLDC, mice showed a moderate increase in blood urea nitrogen (Figure 1C) and a notable decrease in estimated glomerular filtration rate (Figure 1D). In addition, there was an obvious loss of kidney weight (Figure 1E). In histology, RLDC induced tubular degeneration and dilation, cast formation, tubular atrophy, inflammatory cell infiltration, and interstitial fibrosis (Figure 1F), some of the typical pathologic features of CKD. Moreover, many kidney tubules in RLDC-treated mice were positive for Kim1 staining (Figure 1G). These results verify that RLDC induced chronic kidney pathologies and functional decline in mice, providing the basis for subsequent snRNA-seq analysis.

Figure 1.

Chronic kidney injury and renal function decline in post–repeated low-dose cisplatin (RLDC) mice. Male C57BL/6 mice were given four consecutive weekly injections of 8 mg/kg cisplatin. Blood and kidney samples were collected at 4 or 9 weeks after the first cisplatin injection for analysis. A: Timeline of cisplatin treatment in the RLDC model. B and C: Blood urea nitrogen (BUN). D: Estimated glomerular filtration rate (eGFR). E: Kidney weight/body weight (KW/BW) ratio. F: Periodic acid–Schiff staining of renal histology. G: Immunohistochemical staining of Kim1. Quantitative data are expressed as means ± SEM (B–E). n ≥ 5 (B–E). ∗P < 0.05, ∗∗P < 0.01, and ∗∗∗P < 0.001. Scale bar = 0.05 mm (F and G). CT, control.

Cell Types and Clusters Identified by snRNA-seq in Kidney Tissues

After RLDC treatment, the main histopathologic changes occur in the kidney cortex and outer medulla (Figure 1F). Therefore, kidneys from control or post-RLDC mice were collected to dissect these anatomic regions for the isolation of cell nuclei, which were subjected to snRNA-seq using the 10x Genomics platform. A total of 10,196 nuclei were analyzed, and the mean reads per nucleus were 26,146. snRNA-seq identified transcripts corresponding to about 20,000 genes. Cell populations were defined using canonical markers of kidney cell populations derived from published literature.^1,24 The analysis revealed 16 cell types and 17 cell clusters (Figure 2A). Unbiased hierarchical clustering showed a kidney cell landscape with each color representing a different cell population (Figure 2A). The markers for 16 cell types and 17 cell clusters were detected and shown in Figure 2B. As expected, the proximal tubule (PT) populations were enriched for PT markers (Slc34a1, Lrp2, Slc5a2, Slc13a3, and Slc7a13), thick ascending limb cells were enriched for Slc12a1, distal convoluted tubule, and connecting tubule enriched for Slc12a3 and Slc8a1, endothelial cells enriched for Flt1, immune cells enriched for Adgre1, Ptprc and Arhgap45, and Cd247, intercalated cells (type A intercalated cells of collecting duct/type B intercalated cells of collecting duct) enriched for Kit and Slc26a4, and podocytes for Nphs1. In the mixed-1 and mixed-2 cell clusters, the study detected the transcriptional features of mesangial cells (Fhl2), fibroblast (Col1a1, Acta2, Cfh, Pdgfra, and Pdgfrb), pericyte (Myh11), and some other cells. Therefore, the fibroblasts were distributed into two clusters, mixed-1 and mixed-2.

Figure 2.

Cell types and clusters identified by single-nucleus RNA sequencing (snRNA-seq) in kidney tissues. Male C57BL/6 mice were given four consecutive weekly injections of 8 mg/kg cisplatin. Kidney tissues were collected at 9 weeks after the first cisplatin injection for snRNA-seq. A: t-Distributed stochastic neighbor embedding (t-SNE) plot showing main cell clusters or populations. Control and repeated low-dose cisplatin (RLDC)–treated samples were integrated into a single data set and clustered using Loupe Browser. B: Cell clusters were identified by kidney cell lineage-specific marker expression. C: Bar plot showing the compositions of cell clusters in control and post-RLDC kidneys. CNT, connecting tubule; DCT, distal convoluted tubule; EC, endothelial cell; FC, fold change; IC-A, type A intercalated cells of collecting duct; IC-B, type B intercalated cells of collecting duct; Mixed, mixed cell types; PC, principal cell; PT-injury/repair, proximal tubule cells expressing kidney injury and repair marker genes; PT-S1, the S1 segment of proximal tubule; PT-S2, the S2 segment of proximal tubule; PT-S3, the S3 segment of proximal tubule; TAL, thick ascending limb of the loop of Henle.

The percentages of the identified cell populations were further analyzed to check whether they change after RLDC treatment (Figure 2C). The percentage of total PT (S1 + S2 + S3) cells decreased slightly from 58% in control to 53% after RLDC treatment, suggesting PT cell death or degeneration. Notably, a unique subset of PT cells expressed both injury (Kim1) and proliferation (Ki-67) markers, which increased significantly from approximately 1.9% in control to approximately 5.1% in post-RLDC kidneys. This subpopulation was named PT-injury/repair cells. Remarkably, the immune cells increased from approximately 1.2% in control to 3.5% in RLDC kidneys. These observations support the critical roles played by proximal tubules and immune cells in maladaptive kidney repair after cisplatin nephrotoxicity.

Identification of the PT-Injury/Repair Cell Cluster in Post-RLDC Kidneys

The proximal tubule is the main injury site in AKI and the main kidney repair site. Therefore, the gene transcription profiles were analyzed and compared in specific PT cell clusters (Figure 3A). Anatomically, the proximal tubule is divided into the S1 segment that is the first part of the proximal convoluted tubule next to the glomerulus; the S2 segment, or the second part of the proximal convoluted tubule; and the S3 segment of the proximal straight tubule. Consistently, this snRNA-seq identified S1, S2, and S3 PT cells according to their transcriptional characteristics. Interestingly, a unique cluster of PT cells showed a decreased expression of Slc34a1 and Lrp2 indicating dedifferentiation, but an increased expression of the well-known PT injury markers Kim1²⁵ and recently identified PT injury markers, Krt18, Krt19, and Krt20^26,27 (Figure 3A). This PT-injury/repair cluster also had higher expression of Vcam1, Dcdc2a, Cxcl2, Ccl2, and Cd44 (Figure 3A), indicative of severe injury.^16,28 In addition, this cell population demonstrated higher expression of cell cycle markers, such as Mki67, Cdk1, and Top2a (Figure 3A), indicating cell proliferation. The increase of Kim1 and Ki-67 was verified by immunohistochemical staining (Figure 3B). Control kidneys only had a few Ki-67–positive tubular cells and no Kim1-positive tubules, whereas there were more Ki-67–positive cells and some Kim1-positive tubules in the RLDC-treated kidneys, suggesting the increase of both injured and proliferative tubular cells. Remarkably, some tubules co-expressed Kim1 and Ki-67, suggesting these tubules were injured but undergoing proliferation or repair. Furthermore, the increase of Krt20 and Vcam1 in post-RLDC kidneys was verified by immunohistochemical staining and/or immunoblotting analysis. As shown in Figure 4, A and B, RLDC increased the expression of Krt20 in injured tubules at 4 and 9 weeks relative to untreated controls, and the number of Krt20-positive kidney tubules decreased at 9 weeks compared with 4 weeks, indicating tubular repair after RLDC. Meanwhile, immunoblot analysis detected higher Vcam1 expression in post-RLDC kidneys than in control (Figure 4C). In immunohistochemical staining, control kidneys only had positive Vcam1 signal in the interstitium and endothelial cells, and there were no Vcam1-positive tubules. However, in post-RLDC kidneys, atrophic proximal tubules showed heavy Vcam1 staining (Figure 4D). These results, together with the observation of Dcdc2a, Sema5a, and Ccl2 (Figure 3A), indicate the existence of proinflammatory failed-repair proximal tubules, as demonstrated in maladaptive kidney repair after renal ischemia-reperfusion injury (IRI).¹⁶

Figure 3.

Identification of the proximal tubule (PT)-injury/repair cell cluster in post–repeated low-dose cisplatin (RLDC) kidneys. Male C57BL/6 mice were given four consecutive weekly injections of 8 mg/kg cisplatin. Kidney tissues were collected at 9 weeks after the first cisplatin injection for analysis. A: Differentially expressed genes involved in renal injury and repair are shown in the single-nucleus RNA sequencing. B: Co-immunostaining of Ki-67 and Kim1. The bottom panels are magnified from the boxed areas in the top panels. Arrows point to renal tubules with Ki-67 and Kim1 costaining. Scale bar = 0.05 mm (B). CT, control; FC, fold change.

Figure 4.

Verification of Krt20 and vascular cell adhesion molecule 1 (Vcam1) expression in proximal tubules in post–repeated low-dose cisplatin (RLDC) kidneys. Male C57BL/6 mice were given four consecutive weekly injections of 8 mg/kg cisplatin to collect kidneys at 4 and 9 weeks after the first cisplatin injection. A and B: Immunohistochemical (IHC) staining to verify the renal tubular expression of Krt20 at 4 weeks (A) and 9 weeks (B). C: Immunoblots verifying Vcam1 expression at 9 weeks post-RLDC mouse kidneys. D: IHC staining to verify the renal tubular expression of Vcam1 at 9 weeks. Scale bar = 0.05 mm (A, B, and D). CT, control; Cyclo.B, cyclophilin B.

The PT-injury/repair cluster also had increased expression of Sema5a and Sema3c, two genes with important roles in kidney development.²⁹ The increase of Sema5a was detected in PT cells after renal IRI,¹⁶ but there was no report about Sema3c in kidney injury or repair.

Gene Expression in Different PT Clusters after RLDC Treatment

RLDC-induced changes in the transcriptional profiles of different PT clusters were further analyzed. There were no significant differences in PT-S1 transcriptional profiles between control and RLDC-treated mice (data not shown). However, RLDC induced differential gene expression in PT-S2/S3, PT-S2, PT-S3, and PT-injury/repair clusters (Figure 5, A–D). Specifically, RLDC induced Serpine2, Cdh6, Eda2r, and Tshr in PT-S2/S3; Pappa, Eda2r, Cdh6, Erbb4, and Nrg1 in PT-S2; Hao2, Kcnk1, Dok6, and Scd1 in PT-S3-1; Tshr, Eda2r, Cdh6, Hao2, Myof, Klf6, Il7, Spp1, and Sema5a in PT-S3-2; and NGF, Kcnip4, Kcnh8, Havcr1, Vcam1, Ntm, Dock10, and Spaca7 transcription in PT-injury/repair cluster (Figure 5E). This result indicates differential gene expression in different PT clusters after RLDC treatment.

Figure 5.

Gene expression in different proximal tubule (PT) clusters after repeated low-dose cisplatin (RLDC) treatment. Male C57BL/6 mice were given four consecutive weekly injections of 8 mg/kg cisplatin or control vehicle solution to collect kidneys at 9 weeks after the first cisplatin injection for single-nucleus RNA sequencing. The transcriptional profiles in proximal tubule cell clusters from post-RLDC kidneys and control kidneys were compared. The genes with log2 fold change (FC) > 1 and P < 0.05 in different PT clusters were selected and presented in a bubble plot. A: PT-S2/S3. B: PT-S2. C: PT-S3-1. D: PT-S3-2. E: PT-injury/repair.

Overall Transcriptional Changes Induced by RLDC in PT Cells

The data sets of all PT clusters were combined into one to identify the overall transcriptional changes induced by RLDC. When P value was set to <0.05 and log2 fold change was set to >1 and <–1 for up-regulated and down-regulated genes, 424 differentially expressed genes were detected between the PTs of control and those of post-RLDC mice kidneys (Figure 6A). Of these differentially expressed genes, 200 genes were up-regulated and 224 genes were down-regulated after RLDC treatment (Figure 6B).

Figure 6.

Overall transcriptional changes induced by repeated low-dose cisplatin (RLDC) in proximal tubule (PT) cells. Male C57BL/6 mice were given four consecutive weekly injections of 8 mg/kg cisplatin to collect kidney tissues at 9 weeks for single-nucleus RNA sequencing (snRNA-seq). The snRNA-seq data sets of all PT clusters were combined into one to identify the overall transcriptional changes induced by RLDC. A: Volcano plot showing the distribution of differentially expressed genes in PT after RLDC treatment compared to control. Horizontal and vertical dashed black lines indicate the thresholds of x axis and y axis, respectively. The threshold of x axis is the threshold of log2 [fold change (FC)], and is set at –1 and 1. The threshold of y axis is the threshold of –log10 (P value) and is set at 0.05. The significant difference in gene expression between the control and RLDC groups is displayed by differently colored points. B: The number of up-regulated and down-regulated genes in post-RLDC PT compared with control (CT). C: Heat map showing the down-regulated genes of tubular transporters and cytochrome P450 enzymes involved in lipid metabolism in post-RLDC PT compared with control. D: Heat map showing the top 50 up-regulated genes in post-RLDC PT compared with control.

Interestingly, multiple tubular transporters and cytochrome P450 enzymes involved in lipid metabolism were down-regulated by RLDC in PT cells. As shown in Figure 6C, RLDC decreased the expression of Slc7a13 (l-amino acid transmembrane transporter) and Slc22a30 and Slc22a28 (organic anion transporters), Slc18a1 and Slc22a7 (biogenic monoamines transporters), Slco3a1 [Na (+)-independent organic anion transporter], and Slco1a6 (sodium-independent organic ion transporter). RLDC decreased the expression of Cyp4b1, Cyp2d9, Cyp2e1, Cyp2d12, Cyp2a4, Cyp4a32, and Cyp7b1, which encode cytochrome P450 enzymes involved in lipid metabolism (Figure 6C). RLDC also decreased the expression of Atp11a, a catalytic component of the P4-ATPase flippase complex that catalyzes the hydrolysis of ATP coupled to the transport of aminophospholipids, phosphatidylserines, and phosphatidylethanolamines and contributes to the maintenance of membrane lipid asymmetry. These changes are expected to reduce the transport and lipid metabolism activity in PT cells after RLDC treatment. The top 50 up-regulated genes, including a few PT injury and repair markers, are displayed in Figure 6D.

Induction of Kidney Injury and Repair Genes in Post-RLDC Kidneys

As expected, RLDC treatment induced gene expression enriched for cellular response to injuries, such as cellular response to extracellular stimulus, regulation of the apoptotic process, cell death, apoptotic signaling pathway, and response to hypoxia (Figure 7A). Moreover, gene expression enriched for base-excision repair, plasma membrane repair, regulation of cell proliferation, cellular component organization, wound healing, cell motility, positive regulation of stem cell proliferation, cell cycle, and regulation of cell differentiation, was demonstrated by GO analysis (Figure 7B), indicating the repair and recovery process after RLDC treatment.

Figure 7.

Induction of kidney injury and repair genes in post–repeated low-dose cisplatin (RLDC) kidneys. Male C57BL/6 mice were given four consecutive weekly injections of 8 mg/kg cisplatin to collect kidney tissues at 9 weeks for single-nucleus RNA sequencing. Gene set enrichment was analyzed using DAVID Bioinformatics and mapped to gene ontology (GO) terms. A: GO terms involved in injury after RLDC treatment. B: GO terms involved in repair after RLDC treatment.

Kcnh8, Havcr1, Vcam1, Masp1, Spaca7, Adhl1a2, NGF, Ltbp2, Trim71, Krt20, Dock10, Sorcs1, Sh3rf3, Ntm, Trp53cor1, Ugt1a10, Top2a, Inca2, and Eda2r were the top 20 up-regulated genes in RLDC-treated PT compared with controls (Figure 6D). Among them, Havcr1 (Kim1), Vcam1, and Krt20 have been used or reported as PT injury markers.^16,27 Besides Krt20, elevated expression of Krt222 was observed in RLDC-treated PT (Figure 8, A and B). Krt222 expression correlated with overall survival of patients with kidney renal clear cell carcinoma³⁰ and had not previously been associated with kidney injury and repair. Meanwhile, RLDC induced Eda2r, Masp1, Ltbp2, and Kcnh8 expression, which was validated by qPCR analysis (Figure 8, C–F). Eda2r encodes ectodysplasin A2 receptor, a member of the large family of tumor necrosis factor receptors that lacks a discernible death domain. Ectodysplasin A2 receptor was shown to increase in high glucose milieu to mediate podocyte apoptosis and dedifferentiation.³¹ Masp1 encodes a protein in the lectin complement pathway, and MASP1 increase in tubular interstitium was closely associated with the degree of damage of tubular interstitium in diabetic nephropathy.³² Latent transforming growth factor binding protein-2 (Ltbp2), encoded by Ltbp2, may be useful as a biomarker for major adverse kidney events.³³ In contrast, potassium voltage-gated channel subfamily H member 8 (Kcnh8) was shown to be primarily expressed in the nervous and venous systems.^34,35 The up-regulation of Krt222, Eda2r, Ltbp2, and Masp1 in post-RLDC kidneys suggests their possible involvement in maladaptive kidney repair.

Figure 8.

Verification of injury/repair-related gene transcription in post–repeated low-dose cisplatin (RLDC) kidneys. A–G: Male C57BL/6 mice were given four consecutive weekly injections of 8 mg/kg cisplatin. Kidney tissues were collected at 9 weeks for single-nucleus RNA sequencing (snRNA-seq; A) or real-time quantitative PCR (B–G). A: Heat map of snRNA-seq showing the up-regulated genes involved in kidney injury and repair in proximal tubule of post-RLDC kidneys. B–G: mRNA fold changes of indicated genes in post-RLDC kidneys relative to control. B–G: A two-tailed unpaired t-test was used. Quantitative data are expressed as means ± SEM (B–G). n = 3 to 5 (B–G). ∗P < 0.05, ∗∗∗P < 0.001, and ∗∗∗∗P < 0.0001. CT, control; FC, fold change.

Besides Mki67 and Top2a, RLDC induced several other genes that may regulate the cell cycle to promote kidney recovery after injury, including Sox4, Sox9, and Trim71 (Figure 7A). Tripartite motif containing 71 (Trim71) represses cyclin-dependent kinase inhibitor 1A (Cdkn1a) to facilitate the G₁-S cell cycle transition to promote rapid embryonic stem cell self-renewal.³⁶ SRY-box transcription factor 9 (Sox9) is protective in AKI and facilitates recovery of renal function after the onset of AKI.^37,38 Sox9 was detected in regenerative tubules,^28,39 and in renal tubules in fibrotic areas.²⁸ Of note, RLDC also induced the expression of Bex4 (Figure 8A), which contributes to α-tubulin acetylation for spindle formation during chromosome segregation in cell division.⁴⁰ BEX4 expression is altered in many cancers and promotes tumor cell proliferation,^41,42 but the dysregulation of BEX4 has not been reported in kidney diseases. The elevation of Bex4 expression was validated in RLDC-treated kidneys by qPCR (Figure 8G). The RLDC-induced transcriptional changes in Bex4 suggest this gene may promote kidney repair after RLDC treatment.

Induction of Inflammatory Genes in PT Cells in Post-RLDC Kidneys

Inflammation is crucially involved in kidney injury and post-injury fibrosis. The inflammatory response has also been demonstrated in post-RLDC kidneys.^18,19,43,44 Under this condition, proximal tubular cells are believed to play an important role in promoting inflammation by secreting chemokines and cytokines and recruiting immune cells to kidney tissues. GO-term analysis of the genes up-regulated in post-RLDC kidneys revealed a variety of inflammation-associated GO terms (Figure 9A). The up-regulated inflammatory molecules included Cxcl2, Cxcl1, Cxcl5, Cxcl16, Ccl2, Ccl7, Ccl9, Il7, Tnf-α, and Relb, which encode the proinflammatory chemokines and cytokines (Figure 9B). The up-regulation of Relb, Tnf-α, Il7, Ccl2, and Cxcl2 mRNA was validated in post-RLDC kidneys by qPCR (Figure 10, A and B). Moreover, Relb, Tnf-α, Il7, Ccl2, and Cxcl2 expression was also elevated at 4 weeks after RLDC treatment (Figure 10, A and B), indicating a continuous or chronic inflammation response during kidney repair after RLDC nephrotoxicity. Correspondingly, the immune cells showed enrichment of Ccr2, Ccr5, Ccr1, Ccr7, and Cxcr5, which encode the receptors of the above-mentioned chemokines (Figure 10C), supporting the role of proximal tubular cells in recruiting immune cells to post-injury kidneys and promoting chronic inflammation by secreting chemokines and cytokines.

Figure 9.

Induction of inflammatory genes in proximal tubule (PT) cells in post–repeated low-dose cisplatin (RLDC) kidneys. Male C57BL/6 mice were given four consecutive weekly injections of 8 mg/kg cisplatin to collect kidney tissues at 9 weeks for single-nucleus RNA sequencing. A: Gene ontology (GO) terms involved in inflammation. Gene set enrichment was analyzed using DAVID Bioinformatics and mapped to gene ontology terms. B: Induction of inflammatory cytokines and chemokines in PT cells of post-RLDC kidneys. CT, control; FC, fold change.

Figure 10.

Verification of inflammatory gene transcription in proximal tubule cells in post–repeated low-dose cisplatin (RLDC) kidneys. A–C: Male C57BL/6 mice were given four consecutive weekly injections of 8 mg/kg cisplatin to collect kidney tissues at 4 or 9 weeks for real-time quantitative PCR (qPCR) analysis (A and B) or at 9 weeks for single-nucleus RNA sequencing (C). A: Validation of the induction of RelB, TNF-α, Il7, Ccl2, and Cxcl2 mRNA expression at 9 weeks after cisplatin treatment by qPCR. B: Validation of the induction of RelB, TNFα, Il7, Ccl2, and Cxcl2 mRNA expression at 4 weeks after cisplatin treatment by qPCR. C: Bubble plot showing the induction of chemokine receptors in immune cell cluster. C: A two-tailed unpaired t-test was used. Quantitative data are expressed as means ± SEM (A and B). n = 3 to 4 (A and B).∗P < 0.05, ∗∗P < 0.01, and ∗∗∗P < 0.001. CT, control; FC, fold change.

Induction of Fibrotic Genes in PT Cells in Post-RLDC Kidneys

Renal fibrosis is a major pathologic feature and the common pathway to CKD. The control and post-RLDC PT samples were compared for their expression of fibrosis-associated genes in snRNA-seq. As shown in Figure 11A, RLDC significantly induced the expression of Fn1, Col1a1, and Vim, suggesting the direct contribution of PT cells to kidney fibrosis. In addition, Tgfb1, Tgfb2, Ccn2, and Pdgfd expression was up-regulated by RLDC treatment (Figure 11A), indicating a paracrine function of PT cells in stimulating fibroblast proliferation and activation by secreting profibrotic growth factors. Consistent with these results, immunoblot analysis detected the expression of fibronectin, collagen I, CTGF, α-smooth muscle actin (α-SMA), and vimentin in post-RLDC kidneys (Figure 11B). Sirius-red staining further showed increased collagen deposition in kidney tissues after RLDC treatment (Figure 11C).

Figure 11.

Induction of fibrotic genes in proximal tubule (PT) cells in post–repeated low-dose cisplatin (RLDC) kidneys. A–C: Male C57BL/6 mice were given four consecutive weekly injections of 8 mg/kg cisplatin to collect kidney tissues at 9 weeks for single-nucleus RNA sequencing (snRNA-seq; A), immunoblotting (B), or fibrosis staining (C). A: Heat map of snRNA-seq showing up-regulated genes involved in renal fibrosis in PT cells in post-RLDC kidneys. B: Representative immunoblots of fibronectin (FN), collagen I (Col.I), connective tissue growth factor (CTGF), α-smooth muscle actin (α-SMA), vimentin, and cyclophilin B (Cyclo.B; loading control). C: Sirius red and fast green staining showed increased collagen deposition in post-RLDC kidneys. Scale bar = 0.05 mm (C). CT, control; FC, fold change.

Identification of Key Molecules Regulating Renal Inflammation and Fibrosis Progression in RLDC

Gene functional enrichment analysis of RLDC-treated PT versus control was performed to identify the key regulators controlling inflammation and fibrosis progression in RLDC. Genes were enriched in neutrophil chemotaxis, inflammatory response, fibroblast growth factor receptor signaling pathway, positive regulation of fibroblast proliferation, and cellular response to transforming growth factor-β stimulus. The induction of the key molecules involved in these terms was shown in Figure 12A. Particularly, RLDC elevated the expression of Creb5, Irf1, Irf4, Klf6, Spp1, and Runx1. The up-regulation of ruppel-like factor 6 (Klf6), RUNX family transcription factor 1 (Runx1), and secreted phosphoprotein 1 (Spp1) mRNA was validated by qPCR (Figure 12, B–D). KLF6 acted as a NF-κB co-activator to aggravate the renal IRI inflammatory response,⁴⁵ and Klf6 knockdown reduced the proinflammatory cytokine expression.^46,47 PT-specific Klf6 deletion was protective against AKI and kidney fibrosis in mice.⁴⁸ KLF6 also plays a role during the development of the renal collecting duct system.⁴⁷ Runx1 was associated with postischemia renal fibrosis,²⁷ and specific deletion of Runx1 in mouse renal tubular epithelial cells attenuated both unilateral ureteral obstruction (UUO) and folic acid–induced renal fibrosis.⁴⁹ In addition to playing an important role in mineralization and bone resorption, Spp1 is also involved in the regulation of immunity and inflammation.^50,51 Spp1 expression is elevated in acute and chronic kidney diseases, renal allograft dysfunction, and renal injury animal models.^50,52,53 In addition, down-regulation of Spp1 attenuated renal fibrosis in diabetic rats⁵⁴ and mice undergoing UUO,⁵⁵ indicating its regulatory role in renal fibrosis. The up-regulation of Runx1, Klf6, and Spp1 expression in post-RLDC kidneys suggests an important role of proximal tubules in RLDC-induced inflammation and renal fibrosis progression.

Figure 12.

Identification of key molecules regulating renal inflammation and fibrosis progression in repeated low-dose cisplatin (RLDC). A–D: Male C57BL/6 mice were given four consecutive weekly injections of 8 mg/kg cisplatin to collect kidney tissues at 9 weeks for single-nucleus RNA sequencing (A) or at 4 or 9 weeks for real-time quantitative PCR (qPCR) analysis (B–D). A: Heat map showing gene expression promoting renal inflammation and fibrosis in RLDC-treated proximal tubule. B–D: Validation of the induction of KLF6, Runx1, and Spp1 mRNA expression by qPCR. n = 3. ∗P < 0.05, ∗∗P < 0.01, and ∗∗∗∗P < 0.0001. CT, control; FC, fold change.

Discussion

In this study, snRNA-seq was used to analyze the changes of gene transcriptional profile at the single-cell level after cisplatin nephrotoxicity. A literature search indicates that this is the first snRNA-seq analysis of cisplatin nephrotoxicity. The mouse model of RLDC mimicking the chemotherapy regimen for cancer patients was examined. The single-cell transcriptional profiles were analyzed together with the examination of renal pathologies and the decline of renal function in post-RLDC kidneys. Particular attention was given to the transcriptional changes in PT cells, and the transcriptional changes relevant to inflammation and renal fibrosis.

In this RLDC model, mice had the worst kidney injury within the first 1 to 2 weeks after the completion of four weekly cisplatin injections, and thereafter, the mice started recovery, as indicated by regaining renal function and body weight (data not shown). This snRNA-seq analyzed the kidneys at 9 weeks after RLDC treatment of mice, a time point of kidney repair or recovery. The analysis identified a unique PT cell population in post-RLDC kidneys that co-expressed proliferation markers and PT injury markers, which was further validated by immunostaining of Ki-67 and Kim1 (Figures 2 and 3). These cells were injured but showed signs of the active cell cycle, indicating their significance in tubular repair and recovery after RLDC treatment. Especially, this PT-injury/repair cluster also contained some failed-repair and proinflammatory tubular cells that were characterized by the transcription of Vcam1, Dcdc2a, Sema5a, Cxcl2, and Ccl2 (Figure 3A) and a senescence-associated secretory phenotype, as previously reported in post-IRI kidneys.¹⁶

In addition to Kim1, this snRNA-seq demonstrated the induction of Krt20, Vcam1, and Cd44 in injured PT cells in post-RLDC kidneys (Figures 3 and 4). Recent studies reported the induction of these genes in renal IRI and diabetic nephropathy,^16,26,28,56, 57, 58 indicating they are common PT injury responsive genes or markers. This analysis also identified several new PT injury responsive genes in post-RLDC kidneys, including Krt222, Eda2r, Ltbp2, Masp1, and Kcnh8.

Proliferation or regeneration by surviving tubular epithelial cells is an important mechanism of kidney repair after injury.⁵⁹ In contrast to a plethora of kidney injury markers, limited information is known about molecular markers of kidney repair. In this regard, this snRNA-seq revealed the induction of Bex4 in post-RLDC kidneys. Bex4 encodes a protein that is localized at microtubules and spindle poles⁴⁰ and participates in cell proliferation and growth.⁴¹ The induction of Bex4 after RLDC treatment in this study suggests a potential role of Bex4 in promoting tubular cell proliferation for kidney repair.

Another remarkable transcriptional change in PT cells in post-RLDC kidneys is the induction of Slc7a12. Normally, Slc7a12 is expressed in PT-S3 cells only in female mice, whereas Cyp7b1 is expressed only in male PT-S3 cells.⁶⁰ However, in the present study, Slc7a12 was induced in PT-S2/S3, PT-S3-1, and PT-S3-2 clusters in male mice following RLDC treatment, along with the expression of Cyp7b1 (Figures 2B and 5, A, C, and D). Similar findings were reported during maladaptive kidney repair after renal IRI and obstructive nephropathy,^15,57 indicating that transactivation of Slc7a12 may be a common response to different renal stresses and injuries in male mice.

Injured PT cells also showed transcriptional features of dedifferentiation in post-RLDC kidneys, as illustrated by decreased expression of mature PT markers, the gaining of some mesenchymal cell properties, and the induction of renal development-associated genes (Figure 3A). Such transcriptional features of dedifferentiation were also observed during the development of renal fibrosis after IRI.²⁷ These observations support the notion that following injury, surviving PT cells dedifferentiate and proliferate to repopulate the tubule, followed by redifferentiation to restore the tubular integrity and function.^61,62 Of interest, compared with other PT cell clusters, Sema3c transcription was specifically induced in the PT-injury/repair cluster (Figure 3A). Sema3c contributes critically to kidney development by promoting ureteric bud and endothelial cell branching.²⁹ The induction of Sema3c in PT-injury/repair cells suggests the possible involvement of Sema3c in the repair and recovery of the injured tubules.

In addition to tubular injury, inflammation and renal fibrosis are important pathologic features of maladaptive kidney repair and its progression to CKD.62, 63, 64 In this study, an obvious inflammatory cell infiltration was observed in post-RLDC kidneys, as illustrated by periodic acid–Schiff staining and by snRNA-seq that revealed an increase in the percentage of immune cells in post-RLDC kidneys (Figure 2C). Moreover, 28 inflammation-associated GO terms were identified in the transcriptional profile of post-RLDC kidneys (Figure 9A). The snRNA-seq further revealed the induction of key inflammatory chemokine and cytokine genes in PT cells after RLDC treatment, including RelB, TNF-α, IL7, Cxcl2, Cxcl1, Cxcl5, Cxcl16, Ccl7, Ccl9, and Ccl2. Meanwhile, the immune cells in post-RLDC kidneys showed the enrichment of relevant chemokine receptors, including Ccr2, CCr5, Ccr1, Ccr7, and Cxcr5 (Figure 10C). These data suggest that inflammation is activated early by RLDC and persists in the development of chronic renal pathologies and CKD. During this process, PT-injury/repair cells produce chemokines and cytokines for the recruitment and activation of inflammatory cells.

For renal fibrosis, this snRNA-seq showed the transactivation of relevant genes in post-RLDC kidneys. Particularly, the transcription of several profibrotic growth factors was induced in PT cells after RLDC treatment, including TGF-β, CTGF (also named Ccn2), and PDGF (Figure 11A). The increased expression of CTGF protein was further verified by immunoblotting in RLDC-treated kidneys (Figure 11B). Along with these profibrotic factors, there was an induction of fibrotic marker genes, such as collagens and fibronectin (Figure 11, B and C). Despite these findings, renal fibroblasts were annotated in two cell clusters (mixed-1 and mixed-2), and a distinct cluster of fibroblasts/activated fibroblasts was not observed in post-RLDC kidneys (Figure 2). As a result, this snRNA-seq did not reveal a significant change or increase in the percentage of fibroblasts following RLDC nephrotoxicity. The failure in detecting a distinct fibroblast cluster might be caused by the limited number of cells/nuclei sequenced in this study. In addition, interstitial fibrosis in post-RLDC kidneys is less extensive than in other models, such as renal IRI, UUO, and aristolochic acid toxic nephropathy.^19,22,23,65

Tubular epithelial injury, interstitial inflammation, and fibrosis underlie AKI-to-CKD progression.⁶⁶ This snRNA-seq study identified some important factors involved in RLDC treatment, which are either proinflammatory and/or profibrotic factors, including Klf6, Runx1, and Spp1, providing important pathologic insights into RLDC-induced kidney inflammation and fibrosis. Notably, this study demonstrated a remarkable up-regulation of Spp1 (alias osteopontin) and its cell surface receptor CD44 (Figures 3A and 12A). Both CD44 and Spp1 were elevated in injured tubular areas in a murine model of tubulointerstitial nephritis.⁶⁷ CD44 was expressed in dilated tubules and the renal tubules of fibrotic areas in AKI in rats,²⁸ whereas Spp1 takes part in renal fibrosis in diabetes and UUO models.^54,55 Therefore, our results suggest the similar profibrotic and proinflammatory functions of Cd44 and Spp1 in post-RLDC kidneys. In addition to CD44, integrin is another type of Spp1 receptor. However, no remarkable increase in integrin expression was identified by snRNA-seq in this study, indicating that CD44 is the major receptor of Spp1 during RLDC treatment. Different from Klf6 and Spp1, which participate in the regulation of both renal inflammation and fibrosis progression under various pathologic circumstances, Runx1 mainly exerts its regulatory effects in renal fibrosis induced by a variety of kidney injury models, including ischemia, UUO, and folic acid.^27,49 The involvement of KLF6, Spp1, and RUNX1 in this study indicates that they may be common factors for renal inflammation and/or renal fibrosis under different conditions. Targeting KLF6, Spp1, and RUNX1 may help prevent the transition of AKI to CKD in patients with cisplatin treatment and the development of CKD caused by various injuries.

This study sequenced the samples of 9 weeks after RLDC treatment, but some transcriptional changes were verified by qPCR in samples collected at both 4 and 9 weeks. For instance, transcription levels of inflammatory factors RelB, TNFα, IL7, Ccl2, and Cxcl2 were all significantly induced by RLDC at 4 and 9 weeks, although the mRNA levels of RelB, TNFα, Il7, Ccl2, and Cxcl2 were all lower at 9 weeks when compared with those at 4 weeks (Figure 10, A and B). In addition, potential regulators of renal inflammation and renal fibrosis, including Klf6, Runx1, and Spp1, were all significantly induced at 4 and 9 weeks after RLDC treatment, although their mRNA levels at 9 weeks were lower than at 4 weeks (Figure 12, B–D). Thus, the changes of the transcriptional profile after RLDC were dynamic.