Front. Mol. Biosci. Frontiers in Molecular Biosciences Front. Mol. Biosci. 2296-889X Frontiers Media S.A. 654465 10.3389/fmolb.2021.654465 Molecular Biosciences Original Research Alteration of N6-Methyladenosine RNA Profiles in Cisplatin-Induced Acute Kidney Injury in Mice Li et al. m6a Profiles in AKI Li Can-Ming † Li Ming † Zhao Wen-Bo Ye Zeng-Chun * Peng Hui * Department of Nephrology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China

Edited by: Xiao-ming Meng, Anhui Medical University, China

Reviewed by: Xiajing Che, Shanghai JiaoTong University, China

Ming Liang, Guangzhou First People’s Hospital, China

 *Correspondence: Zeng-Chun Ye, yzengch@mail.sysu.edu.cn; Hui Peng, pengh@mail.sysu.edu.cn

These authors have contributed equally to this work

This article was submitted to Protein and RNA Networks, a section of the journal Frontiers in Molecular Biosciences

 09 07 2021 2021 8 654465 19 01 2021 14 06 2021 Copyright © 2021 Li, Li, Zhao, Ye and Peng. 2021 Li, Li, Zhao, Ye and Peng

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Aim: To identify the alterations of N6-methyladenosine (m6A) RNA profiles in cisplatin-induced acute kidney injury (Cis-AKI) in mice.

Materials and Methods: The total level of m6A and the expression of methyltransferases and demethylases in the kidneys were measured. The profiles of methylated RNAs were determined by the microarray method. Bioinformatics analysis was performed to predict the functions.

Results: Global m6A levels were increased after cisplatin treatment, accompanied by the alterations of Mettl3, Mettl14, Wtap, Fto, and Alkbh5. A total of 618 mRNAs and 98 lncRNAs were significantly differentially methylated in response to cisplatin treatment. Bioinformatics analysis indicated that the methylated mRNAs predominantly acted on the metabolic process.

Conclusion: M6A epitranscriptome might be significantly altered in Cis-AKI, which is potentially implicated in the development of nephrotoxicity.

 acute kidney injury N6-methyladenosine (m6A) RNA cisplatin microarray Background

Acute kidney injury (AKI), characterized by the abrupt loss of renal function, is a common and severe disorder in hospitalized patients (Susantitaphong et al., 2013). AKI has become a major public health concern due to its high morbidity, mortality, and healthcare costs (Lameire et al., 2013; Mehta et al., 2015; Mehta et al., 2016). The etiology of AKI is usually multifactorial and complex. Among them, renal hypoperfusion, sepsis, and nephrotoxin exposure are often the three leading causes (Ronco et al., 2019). Nephrotoxic medications have been reported to be responsible for approximately one-quarter of AKI cases and remain a critical and increasing cause of AKI both in patients who are hospitalized and in the community, especially those with cancer (Bonventre et al., 2010; Loghman-Adham et al., 2012; Rosner and Perazella, 2017; Ronco et al., 2019; Tanase et al., 2019).

Cisplatin is a chemotherapy medication that is widely used in the treatment of multiple malignant tumors (Linkermann et al., 2014; Tanase et al., 2019). Due to the pharmacokinetic characteristics of cisplatin, its metabolite concentrations within the kidney are fivefold higher than in blood, suggesting an active accumulation of drugs by intrinsic renal cells, especially in kidney tubular epithelial cells (Bajorin et al., 1986; Miller et al., 2010; Xiang et al., 2019). An increased concentration of cisplatin in cells causes damage to nuclear and mitochondrial DNA, generates reactive oxygen species (ROS), which activated pathways of apoptosis and necrosis, and consequently contributes to an episode of nephrotoxicity (Miller et al., 2010). Therefore, the dose of cisplatin is greatly limited, thus leading to impaired therapeutic efficacy in patients with cancer (Dos Santos et al., 2012; Perazella, 2012; Tanase et al., 2019; Xiang et al., 2019). Although considerable progress has been made in the last few decades on the treatment of cisplatin-induced AKI (Cis-AKI), there are still no established pharmacotherapies that are available, mostly owing to the unclear molecular mechanisms of this disease (Agarwal et al., 2016; Ronco et al., 2019; Uber and Sutherland, 2019).

Recently, accumulating evidence suggest that epigenetic regulation plays a crucial role in a myriad of kidney diseases, including renal cell carcinoma, chronic kidney disease (CKD), and AKI (Guo et al., 2019; Kato and Natarajan, 2019; Linehan and Ricketts, 2019; Ruiz-Ortega et al., 2020). Epigenetic modifications, defined as stable and heritable alterations of gene expression without changing the primary DNA sequence, are essential for a variety of physiological processes, including DNA transcription, gene expression, cellular differentiation, cell cycle, and apoptosis (Quintanilha et al., 2019). Other than DNA methylation, histone modification, and noncoding RNAs, reversible modifications of RNAs have only recently emerged as an additional regulatory layer contributing to the complexity of epigenetic regulation (Vu et al., 2019). To date, at least 170 chemical modifications have been identified in various types of RNAs in all living organisms (Boccaletto et al., 2018; Huang et al., 2020). Notably, N 6 -methyladenosine (m6A), first identified in the 1970s following the discovery of the polyadenosinic acid (Poly A) structure of messenger RNA (mRNA), has been considered as the most prevalent and abundant posttranscriptional modification within eukaryotic mRNAs, microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs) (Desrosiers et al., 1974; Perry and Kelley, 1974; Rottman et al., 1974; Yang et al., 2017; Chen et al., 2019). m6A modifications, which fall within a consensus motif RRACH (R = G or A; H = A, C, or U; A = adenine and C = cytosine), are mainly enriched in the 3′-untranslated regions (UTRs) around the stop codons of mRNAs and play a critical role in mRNA processing events, such as splicing, nuclear export, degradation, and translation (Dominissini et al., 2012; Chen et al., 2019; Livneh et al., 2020). The biological effects of m6A modifications are collaboratively controlled by “writer,” “eraser,” and “reader” proteins (Vu et al., 2019). Methyltransferase like 3 (Mettl3) (Schumann et al., 2016), methyltransferase like 14 (Mettl14) (Liu et al., 2014), and Wilms’ tumor 1– associating protein (Wtap) (Ping et al., 2014) are essential components of the core writer complex, which efficiently catalyzes methyl group transfer to the N6 site of adenine (Wang X. et al., 2016). The m6A mark can then be recognized by reader proteins, such as YT521-B homology (YTH) N 6 -methyladenosine RNA-binding proteins (YTHDF), IGF2 mRNA-binding proteins (IGF2BPs), eukaryotic translation initiation factor 3 (eIF3), and heterogeneous nuclear ribonucleoprotein (HNRNP) protein families, and erased by RNA demethylases, including fat mass and obesity-associated protein (Fto) and AlkB homolog 5 (ALKHB5) (Jia et al., 2011; Zheng et al., 2013; Chen et al., 2019). Recent evidence suggests that abnormal mRNA m6A modification is linked to many diseases such as obesity, infertility, and cancer (Wei et al., 2017).

In the field of kidney diseases, it has been observed that Fto, the first-identified RNA demethylase, is abundant in the kidney and regulates the fibrogenic process through the TGF-β signaling pathway in obstructive nephropathy (Jia et al., 2011; Wang C. Y. et al., 2016). Another recent study indicated that Mettl14 played a detrimental role in renal ischemia-reperfusion injury (IRI) via suppressing YAP1-TEAD signaling (Xu Y. et al., 2020). In addition, data from Li X et al. found a strong relationship between m6A modification and the severity of renal interstitial fibrosis induced by unilateral ureteral obstruction (Li X. et al., 2020). Furthermore, recent evidence suggested that the m6A site of MALAT1 was methylated by Mettl3 and, thus, promoted the TGF-β1–induced epithelial–mesenchymal transition (EMT) in HK2 cells (Liu P. et al., 2020). Therefore, it is reasonable to believe that the m6A modification might be involved in the process of kidney injury. However, much less is known about the functional role and regulatory mechanism of the m6A modification in Cis-AKI. To fulfill this end, we explore the relationship between m6A modification of RNAs and Cis-AKI by the microarray technique in this study.

 Methods Animals

129 male mice aged about 10 weeks and weighing approximately 20–25 g were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. (China). All mice were maintained in a temperature-controlled room under a 12 h light–dark schedule and received food and water ad libitum. The mice in the Cis-AKI group (four mice per group) were injected intraperitoneal with a single dose of cisplatin (20 mg/kg body weight; Selleck Chemicals, TX, United States) that was dissolved in saline as described previously (Deng et al., 2019; Li et al., 2019; Li M. et al., 2020). Control mice (four mice per group) received saline only. The animals were euthanized with chloral hydrate (400 mg/kg) at 3 days after administration of cisplatin, and blood and kidney tissue with adherent fat and connective tissue removed were collected for the subsequent detections. All protocols had received prior approval from the Animal Care Committee of Sun Yat-sen University.

 Renal Function Assessment

Renal function was evaluated by performing serum creatinine and blood urea nitrogen (BUN) assays with an automatic biochemical analyzer according to the manufacturer’s instructions (Chemray-240, Rayto Life and Analytical Sciences Co., Ltd, China).

 Histopathology

Kidney tissues were fixed in 4% paraformaldehyde, embedded in paraffin wax, and cut into 4-μm–thick tissue sections. The kidney sections were deparaffinized, rehydrated, and stained with periodic acid–Schiff (PAS) by treating with periodic acid for 5 min and covering with Schiff’s reagent for 15 min at room temperature. The average percentage of cellular casts and necrosis in at least 20 random fields (×40) was examined and used as an indicator of tubular injury. The histopathological changes were scored in a single-blind manner.

 Apoptosis Analysis

Apoptotic cell death in kidney sections was determined by the terminal deoxynucleotidyl transferase–mediated dUTP nick-end labeling (TUNEL) method with an in situ Cell Death Detection Kit (Roche Molecular Biochemicals, Germany) according to the manufacturer’s protocol. Positive staining was detected in the nucleus by using a fluorescence microscope (Nikon, Japan). The average number of TUNEL-positive cells was calculated in 20 randomly selected regions by a blinded investigator.

 Western Blot Analysis

The frozen kidney tissue specimens were weighted, cut into small pieces, homogenized by using a Dounce glass tissue homogenizer in ice-cold radioimmunoprecipitation assay (RIPA) buffer (Thermo Fisher, MA, United States), and supplemented with protease inhibitors (Thermo Fisher, MA, United States). Total protein was extracted from the kidney homogenate by centrifugation at 14,000 g for 15 min at 4°C and quantified with the BCA Protein Assay Kit (Beyotime biotechnology, China). Protein samples were boiled in 1× NuPAGE LDS Sample Buffer (Thermo Fisher, MA, United States) and electrophoresed in 10% SDS-PAGE gels. The proteins in the gel were then transferred to polyvinylidene difluoride (PVDF) membranes (Roche, United States) via a wet blotting apparatus (Bio-Rad, CA, United States). These membranes were blocked in a skim milk solution at room temperature for 60 min to eliminate most of the nonspecific hybridizations. The membranes were subsequently immersed in 5% bovine serum albumin (BSA) in the presence of the polyclonal rabbit anti-cleaved caspase-3 antibody (1:1000, Cell Signaling Technology, MA, United States), the monoclonal rabbit anti-Mettl14 antibody (1:1000, Cell Signaling Technology, MA, United States), the polyclonal rabbit anti-Mettl3 antibody (1:1000, Proteintech Group, Inc, IL, United States), the monoclonal mouse anti-Wtap antibody (1:1000, Proteintech Group, Inc, IL, United States) or the monoclonal mouse anti-Fto antibody (1:1000, Abcam, United Kingdom), the monoclonal rabbit anti-Alkbh5 antibody (1:1000, Abcam, United Kingdom), and the monoclonal mouse anti-GAPDH antibody (1:10000, CoWin Biosciences, China) overnight at 4°C and hybridized with a horseradish peroxidase (HRP)–labeled goat anti-rabbit/-mouse antibody (1:8000; TransGen Biotech, China) at room temperature for 1 h. The blots were washed with TBST and then visualized by enhanced chemiluminescence (ECL; Millipore, MA, United States) through a luminescent imaging workstation (Tanon, China). The amount of protein was proportional to the optical density (OD) intensity measured by the ImageJ software (National Institutes of Health, MD, United States).

 RNA Preparation and Quality Control

Total RNA was extracted from the kidney specimens using the TRIzol reagent (Invitrogen, MA, United States) following the manufacturer’s instructions. The quantity and quality of the total RNA were assessed by using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, DE, United States). The RNA integrity was determined by denatured agarose gel electrophoresis.

 m<sup>6</sup>A RNA Methylation Quantification

The total level of m6A in kidney tissue was determined by using the EpiQuik m6A RNA Methylation Quantification Kit (Epigentek, NY, United States) according to the manufacturer’s instructions. Briefly, 200 ng RNA isolated from kidney tissue was added to strip wells and incubated with the capture antibody and detection antibody in sequence. After treatment with enhancer solutions, the m6A content was quantified colorimetrically using a microplate spectrophotometer at 450 nm and calculated based on the formula provided by the manufacturer.

 Quantitative Real-Time PCR

The differential expression levels of the m6A-related genes Mettl3, Mettl14, Fto, Wtap, and Alkbh5 were evaluated by quantitative real-time PCR (qPCR) in control and Cis-AKI mice. In brief, total RNA derived from kidney tissues was reverse transcribed into cDNA with SuperScript™ III Reverse Transcriptase (Invitrogen, MA, United States) according to the manufacturer’s protocol. The amplification reactions were then carried out on a QuantStudio™ 5 System (Applied Biosystems, MA, United States) with a 2X PCR master mix (Arraystar, MD, United States), which contained a 2× Master Mix (Arraystar, MD, United States), 10 μmol/L forward primer, 10 μmol/L reverse primer, and 2 μl cDNA. The reaction condition was as follows: 95°C for 10 min, followed by 40 cycles of 95°C for 10 s and 60°C for 60 s. The Ct values obtained against known concentrations of serially diluted PCR products of mRNAs were used to construct a standard curve. The concentration of the targeted mRNAs in each sample was calculated according to the standard curve. The mRNA expression levels were normalized using GAPDH as the internal reference, and the fold change between the two groups was then calculated. To confirm the validity of the microarray data, qPCR combined with methylated RNA immunoprecipitation was conducted to determine the expression level of ten selected RNAs, including mRNAs (Fosl1, Krt20, Cdkn1a, Psme2, Slc35f3, and Cndp1) and lncRNAs (RP24-267E6.2, RP23-478H15.3, RP23-149A5.3, and RP23-257O9.1). The immunoprecipitated RNA and input RNA were both converted to cDNA and subjected to an amplification process as described previously (Wang Y. et al., 2019). The sequences of the primers used in the qPCR experiments are listed in Table 1.

Sequences of primers used for qPCR and MeRIP-qPCR analysis.

Name Sequence Product size (bp)
GAPDH F:5′ CAC​TGA​GCA​AGA​GAG​GCC​CTA​T 3′ 144
R:5′ GCA​GCG​AAC​TTT​ATT​GAT​GGT​ATT 3′
Mettl3 F:5′ GGT​TCG​TTC​CAC​CAG​TCA​TA 3′ 155
R:5′ CTA​GTA​GGT​GTA​TCC​CAT​CCA​G 3′
Mettl14 F:5′ TGC​GAA​AGT​GGG​GTT​ACA​GAA 3′ 172
R:5′ ATG​AAG​TCC​CCG​TCT​GTG​CT 3′
Fto F:5′ CTT​CAC​CAG​GGA​GAC​TGC​TAT 3′ 96
R:5′ AGT​GGA​ACT​AAA​CCG​AGG​CT 3′
Wtap F:5′ AAA​GGT​CCG​ACT​GAG​TGA​AAC 3′ 243
R:5′ CAC​TCT​TGC​ATC​TCC​TGC​TCT 3′
Alkbh5 F:5′ CGG​TCA​TCA​TTC​TCA​GGA​AGA​CA 3′ 259
R:5′ GAG​CTA​AAA​CTC​CCC​CTC​CG 3′
Fosl1 F:5′ TGCCAAGCATCGACAGCA 3′ 302
R:5′ CAA​TTT​GTC​GGT​CTC​CGC​C 3′
Krt20 F:5′ GCA​ATC​CAA​TTC​CAG​ACT​TGA 3′ 172
R:5′ CTT​AGC​ATT​GTC​AAT​TCG​CAG​G 3′
Cdkn1a F:5′ TAC​CGT​GGG​TGT​CAA​AGC​A 3′ 171
R:5′ GTG​CTG​TCC​CTT​CTC​GTG​A 3′
Cxcl10 F:5′ TCT​CTC​CAT​CAC​TCC​CCT​TTA 3′ 151
R:5′ GCT​TCG​GCA​GTT​ACT​TTT​GTC 3′
Cxcl1 F:5′ AAA​AGA​AGT​GCA​GAG​AGA​TAG​AGT 3′ 234
R:5′ GAG​ACC​AGG​AGA​AAC​AGG​GTT 3′
Lrmda F:5′ GCG​ACT​TGT​ACA​GAT​AAG​GAC​C 3′ 156
R:5′ TAA​GAC​GCA​GCC​AGT​GGA​G 3′
Psme2 F:5′ TAC​TAC​TCA​CGG​TGG​ATG​TCT​T 3′ 170
R:5′ TGG​GAT​AGG​GAT​GTC​CAG​AG 3′
Slc22a27 F:5′ AGC​TGT​AGG​AGT​CAT​TGG​GTT 3′ 270
R:5′ CCA​GGA​GTT​CCT​TAA​AAC​CTC 3′
Slc35f3 F:5′ AGCGCCTGCAACAGTCCG 3′ 178
R:5′ CCA​CAC​CCC​AGA​AGA​CCT​TCT 3′
Cndp1 F:5′ CCA​GGC​TAT​CAC​ACA​AAA​GAG​T 3′ 194
R:5′ TGC​CCG​TGG​ATC​AGT​AGA​CA 3′
RP24-267E6.2 F:5′ CGT​CTG​TGG​TTC​AAA​CCA​ATC​A 3′ 74
R:5′ GGA​GCA​TCG​GGA​GTG​TAA​AG 3′
RP23-478H15.3 F:5′ TCA​CTC​ATC​GCT​GTA​TTC​CC 3′ 144
R:5′ CAC​ACC​CTT​TAA​TAG​TGC​CAG​T 3′
RP23-149A5.3 F:5′ CAC​CTG​CCT​GCT​ACC​ATA​CTT​C 3′ 69
R:5′ GAC​CCA​GTT​CCA​CAG​GGA​TAG 3′
RP23-257O9.1 F:5′ ATA​GTT​AGG​GCA​CTA​ACT​TGC​C 3′ 67
R:5′ TGT​TCT​TGA​CCA​CTG​AGC​GT 3′
m<sup>6</sup>A Immunoprecipitation

Total RNA (3 μg) mixed with the m6A spike-in control reagent (Arraystar, MD, United States) was incubated with anti-m6A rabbit polyclonal antibody (Synaptic Systems, Germany) in an immunoprecipitation (IP) reaction system (50 mM Tris-HCl, 7.4 pH , 150 mM NaCl, 0.1% NP40, and 40 U/μl RNase Inhibitor (Enzymatics, MA, United States)) at 4°C for 2 h. Dynabeads™ M-280 Sheep Anti-Rabbit IgG (Invitrogen, MA, United States) was blocked with 0.5% bovine serum albumin (BSA) and then tumbled with the total RNA-antibody mixture prepared above. After binding to the total RNA, the beads were washed with IP buffer and Wash buffer (50 mM Tris-HCl, 7.4 pH , 50 mM NaCl, 0.1% NP40, and 40 U/μl RNase Inhibitor) several times. Finally, the enriched RNA was separated from the beads in Elution buffer (10 mM Tris-HCl, pH7.4, 1 mM EDTA, 0.05% SDS, and 40 U Proteinase K) and purified via acid phenol–chloroform extraction and the ethanol precipitation method.

 m<sup>6</sup>A RNA Microarray

The immunoprecipitated RNAs and RNAs in the supernatant were amplified separately as complementary RNAs (cRNAs) and labeled with Cy5 and Cy3 fluorescent dye using an Arraystar Super RNA Labeling Kit (Arraystar, MD, United States). The Cy3 and Cy5 marked cRNAs were mixed and purified by using an RNeasy Mini Kit (Qiagen GmbH, Germany). Following fragmentation by adding the blocking agent and fragmentation buffer, the cRNA mixture was combined with the hybridization buffer and then loaded onto the m6A-mRNA and lncRNA Epitranscriptomic Microarray slide (KangChen Bio-tech, China) for hybridization in an Agilent Hybridization Oven at 65°C for 17 h. The hybridized microarray slides were washed and scanned with the Agilent Scanner G2505C (Agilent Technologies, CA, United States).

 Microarray Data Analysis

Raw data were obtained with Agilent Feature Extraction software (version 11.0.1.1) by analyzing the scanned array images. After normalization of raw intensities of immunoprecipitated RNAs (Cy5-labeled) and RNAs in the supernatant (Cy3-labeled) with an average intensity of spike-in RNA, the probe signals flagged as present (P) or marginal (M) in at least four out of eight samples were retained for further analysis. The m6A-methylated RNAs having |fold changes| (|FC|) ≥2 and p values ≤ 0.05 between the control and Cis-AKI groups were identified as of the significantly differential expression. The false discovery rate (FDR) approach was used to correct the p value. Gene ontology (GO) is a bioinformatic method for annotating genes, gene products, and sequences to the underlying biological activities (Gene Ontology Consortium, 2006). The ontology can be divided into three nonoverlapping domains: the biological process (BP), cellular component (CC), and molecular function (MF). The potential functions of the differentially expressed m6A-methylated RNAs were predicted according to the functional annotation of the host genes. Enrichment analysis for GO terms was performed using the topGO package in R software for statistical computing. The pathway analysis based on Kyoto Encyclopedia of Genes and Genomes (KEGG) was utilized to identify the pathways significantly enriched in the parental genes of the differentially expressed m6A-methylated RNAs. The enrichment p value of the pathway analysis was calculated by Fisher’s exact test.

 Statistical Analysis

All data are expressed as the means ± SEM of three or more independent experiments. Student’s t-tests were used to determine the differences between the two groups. A p value ≤ 0.05 was defined as statistically significant. SPSS 20.0 software (SPSS Inc., IL, United States) was used to analyze the data.

 Result Cisplatin-Induced AKI and Renal Tubular Epithelial Cell Apoptosis

The blood urea nitrogen (BUN) and serum creatinine (Scr) were measured to evaluate the renal function of the mice. After 72 h of treatment with cisplatin, a significant increase of BUN and Scr was observed (Figures 1A,B). Pathologic analysis also showed more severe tubular injury after cisplatin exposure, as demonstrated by the acute and progressive tubular dilation, proteinaceous cast formation, and necrosis (Figures 1C,D). Consistent with these results, the expression level of cleaved caspase-3 and the number of apoptotic tubular cells were markedly increased in the cisplatin-treated mice compared with the controls (Figures 1E–H). Overall, these results demonstrated that a mouse model of AKI was established successfully.

Cisplatin-induced AKI in mice. 129 male mice were treated with vehicle or cisplatin (20 mg/kg, intraperitoneal) and sacrificed on day 3 after cisplatin injection. (A) The histogram showing the level of blood urea nitrogen (BUN) in each group. *p < 0.05 vs. control group, n = 4 per group. (B) The histogram showing the level of creatinine in each group. *p < 0.05 vs. control group, n = 4 per group. (C) Periodic acid–Schiff (PAS) staining showing the histopathologic changes in the kidneys. Original magnification ×200; bar = 100 μm. (D) The histogram showing the number of necrotic tubules in the kidneys. Data are the mean ± SD of 20 random fields obtained in each kidney slice. *p < 0.05 vs. control group, n = 4 per group. (E) Representative immunostaining images showing cleaved caspase-3 expression in kidney tissues. GAPDH was used as a loading control for normalizing changes in specific gene expressions. (F) The histogram showing the level of cleaved caspase-3 protein expression that was calculated by densitometric analysis. *p < 0.05 vs. control group, n = 4 per group. (G) Representative micrographs showing the terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining among different groups. Original magnification ×200; bar = 100 μm; green: TUNEL; blue: DAPI. (H) Quantitative analysis of TUNEL staining positive cells among different groups. Data are the mean ± SEM of 20 random fields obtained in each kidney slice. *p < 0.05 vs. control group, n = 4 per group.

 Cisplatin Increased the Total m<sup>6</sup>A Level and Modulated the m<sup>6</sup>A-Related Genes in the Mouse Kidneys

The m6A RNA methylation level in mice treated with cisplatin was quantified using a colorimetric method. The results indicated that the RNA m6A content in kidney tissues treated with cisplatin was higher than those derived from control groups (Figure 2A). The mRNA expression levels of five major enzymes involved in m6A methylation including Mettl3, Mettl14, Wtap, Fto, and Alkbh5 were assessed by qPCR. Compared with that in the control group, the expression of Mettl3 and Alkbh5 was increased in the mice with cisplatin-induced AKI, whereas the expression of Fto was decreased (Figures 2B,E,F). The mRNA levels of Mettl14 and Wtap were similar in the control and AKI groups (Figures 2C,D). In addition, the expressions of the abovementioned five genes were further tested by western blot. The results demonstrated that the protein expressions of Mellt3, Wtap, and Alkbh5 were increased in response to cisplatin treatment, whereas the expressions of Mettl14 and Fto were decreased (Figures 2G–P).

Cisplatin increased the total m6A level and modulated the m6A-related genes in the mouse kidneys. (A) Quantification of m6A abundance in total RNA isolated from the kidneys of male mice treated with vehicle or cisplatin. The histogram showing the levels of Mettl3 (B), Mettl14 (C), Wtap (D), Fto (E), and Alkbh5. (F) mRNA expression was quantified by qPCR analysis. GAPDH was used as a housekeeping gene for normalizing changes in specific gene expressions. *p < 0.05 vs. control group, n = 4 per group. Representative immunostaining images and densitometric analysis were performed to assess the protein expression of m6A-related enzymes: Mettl3 (G and H), Mettl14 (I and J), Wtap (K and L), Fto (M and N), and Alkbh5 (O and P) in kidneys of Cis-AKI groups compared with control groups. GAPDH was used as an internal control. Data were expressed as mean ± SEM and analyzed using Student’s t-test to determine the differences between the two groups. *p < 0.05 vs. control group, n = 4 per group.

 Cisplatin Altered m<sup>6</sup>A Modification Profiles in the Kidney

To clarify the transcript-specific m6A modifications induced by cisplatin, we characterized the immunoprecipitated m6A methylated RNAs derived from the kidneys of Cis-AKI mice and their littermate controls. Principal component analysis (PCA) is a ubiquitous technique for data analysis and dimensionality reduction. The three-dimensional PCA clustering results calculated from the methylation data revealed distinct clustering and segregation between the individual samples of control and AKI groups (Figure 3A). The percentage of variance associated with PC1, PC2, and PC3 is 51.29, 47.58, and 1.13%, respectively (Figure 3A). These results indicated that the microarray profiles of the methylated RNA samples were rigor and reproducible. An RNA spike-in, designed to hybridize with a specific control probe on the target array, was used to measure sensitivity, accuracy, and biases in our microarray experiments for internal technology assessments (Jiang et al., 2011). As shown in Figure 3B, we observed that there was a similar change in the m6A enrichment of positive and negative spike-in controls between control and AKI groups, hence implying a rigorous analysis process. A total of 31,455 transcripts were identified in the four pairs of samples, including 26,550 mRNAs, 3,246 lncRNAs, and 1,659 small RNAs (pri-mRNA, pre-mRNA, snoRNA, and snRNA). The alteration in methylated RNAs with statistical significance between health and AKI mice was demonstrated by a volcano plot (Figures 3C–E). Based on the fold change of differentially methylated RNAs, hierarchical clustering was employed to show the distinguishable expression pattern of methylated transcripts between the two groups (Figures 3F–H). In response to cisplatin, a total of 618 mRNAs were observed to be differentially methylated by fold change ≥2.0 and p < 0.05, including 322 upregulated and 296 downregulated. In addition, 98 lncRNAs were detected to be differentially methylated by fold change ≥2.0 and p < 0.05 in cisplatin-treated mice compared with saline control animals, with 60 upregulated and 38 downregulated. It is noteworthy that the magnitude of change in methylation in mRNAs was larger than that in lncRNAs. Furthermore, 14 small RNAs were found to be differentially hypermethylated by fold change ≥2.0 and p < 0.05 in cisplatin-treated mice compared with control mice, with 14 upregulated and none downregulated. The top 20 altered methylated mRNAs, lncRNAs, and small RNAs are listed in Tables 2–4. The distributions of altered methylated transcripts in mice revealed that the differentially modified mRNAs were transcribed from all chromosomes, while the lncRNAs and small RNAs with differential methylation were transcribed from all chromosomes except chromosome Y (Figures 3I,J).

Cisplatin altered m6A modification profiles in the kidney. (A) Principal component analysis (PCA) was performed to categorize the differentially m6A modified transcripts between Cis-AKI and control groups (A: Cis-AKI; C: control; n = 4 per group). (B) The histogram showing the expression level of positive (Pos) and negative (Neg) spike-in RNA controls that were quantified by qPCR analysis (n = 4 per group); the volcano plots of mRNAs (C), lncRNAs (D), and small RNAs (E) expressions between Cis-AKI groups and control groups are shown. The spots represent upregulated (red) and downregulated (green) expressions of RNAs between the two groups. The heatmaps of the differentially m6A modified mRNAs (F), lncRNAs (G), and small RNAs (H) in Cis-AKI groups and control groups are shown. The distributions of altered mRNAs (I), lncRNAs (J), and small RNAs (K) among mouse chromosomes are shown.

Top 20 differently methylated mRNAs in the kidneys after cisplatin treatment.

Transcript_ID Log2 (fold change) Regulation Chromosome RNA length Transcript_type Gene symbol p value FDR
ENSMUST00000025850 10.90171777 Up chr19 1,707 protein_coding Fosl1 5.04959E-07 0.000893777
ENSMUST00000017743 10.58235631 Up chr11 1,927 protein_coding Krt20 1.01209E-05 0.003049634
ENSMUST00000023829 6.950454632 Up chr17 1,910 protein_coding Cdkn1a 8.37413E-06 0.002850425
ENSMUST00000044687 6.784580325 Up chr12 1,093 protein_coding Ifi27l2b 1.75887E-05 0.004967059
ENSMUST00000092426 6.533305034 Up chr9 1,087 protein_coding Ccdc153 7.2375E-06 0.003512516
ENSMUST00000127683 6.501754033 Up chr2 445 protein_coding RP23-430H1.2 2.02934E-05 0.002668828
ENSMUST00000100700 6.031748629 Up chr5 1,233 protein_coding Gm10382 1.56582E-05 0.003616034
ENSMUST00000038816 5.920444897 Up chr5 1,094 protein_coding Cxcl10 4.99512E-05 0.003415904
ENSMUST00000049209 5.776601971 Up chr5 1,801 protein_coding Gc 0.000105077 0.0062421
ENSMUST00000086370 5.681891497 Up chr2 812 protein_coding RP23-430H1.2 4.81714E-07 0.000893777
ENSMUST00000180430 −5.4136623 Down chr5 13,125 protein_coding Ksr2 8.83534E-07 0.001234623
ENSMUST00000029632 −4.51302473 Down chr3 5,351 protein_coding Lrat 0.000365844 0.010950184
ENSMUST00000159777 −4.09666987 Down chr14 761 protein_coding Lrmda 6.71672E-06 0.002511676
NM_001253358 −3.95059022 Down chr14 5,063 protein_coding Kcnma1 0.000196399 0.008396774
ENSMUST00000159687 −3.89483022 Down chr14 564 protein_coding Psme2 0.000109443 0.006316784
uc007suc.1 −3.88318978 Down chr14 3,041 protein_coding Erc2 1.5033E-07 0.000498909
ENSMUST00000162484 −3.87351184 Down chr9 3,606 protein_coding Cntn5 4.67443E-07 0.000893777
ENSMUST00000029833 −3.78628815 Down chr3 2,652 protein_coding Lrriq3 8.61405E-05 0.005739289
ENSMUST00000182102 −3.75097078 Down chr19 1,801 protein_coding Slc22a27 0.000532007 0.013078513
ENSMUST00000098441 −3.73934763 Down chr9 8,781 protein_coding Col6a6 4.69398E-05 0.004865821

Top 20 differently methylated lncRNAs in the kidneys after cisplatin treatment.

Transcript_ID Log2 (fold change) Regulation Chromosome RNA length Transcript_type Gene symbol p value FDR
ENSMUST00000189460 7.550857116 Up chr1 548 lncRNA RP24-267E6.2 1.4627E-06 0.000787674
ENSMUST00000136927 7.244660674 Up chr11 876 lncRNA RP23-478H15.3 3.82383E-06 0.001034346
ENSMUST00000150329 5.639433808 Up chr11 4,063 lncRNA Egfros 5.06678E-06 0.00117477
ENSMUST00000132010 4.596570731 Up chr4 5,432 lncRNA Trp53inp1 0.000192292 0.007285261
ENSMUST00000192285 4.299689008 Up chr1 2,763 lncRNA RP23-349L18.2 1.1406E-06 0.000740479
ENSMUST00000131854 4.190638957 Up chr1 517 lncRNA Atf3 0.000850584 0.016146176
ENSMUST00000159701 4.187198822 Up chr1 915 lncRNA AC139673.3 3.41929E-08 0.00011099
ENSMUST00000216917 3.901038923 Up chr9 3,485 lncRNA RP23-110E20.5 3.38838E-06 0.001034346
ENSMUST00000189987 3.817308354 Up chr10 1,095 lncRNA Sobp 7.55471E-05 0.005004612
ENSMUST00000134701 3.730540579 Up chr3 1,581 lncRNA Dnajb4 0.0001113 0.005943006
ENSMUST00000189802 −4.73050701 Down chr1 871 lncRNA RP23-149A5.3 2.07759E-05 0.002325468
ENSMUST00000219854 −4.43488047 Down chr10 1,718 lncRNA RP23-417F2.1 1.41542E-05 0.001875077
ENSMUST00000218333 −3.69175411 Down chr10 2,231 lncRNA RP23-257O9.1 0.002985554 0.035662156
ENSMUST00000209842 −3.68939357 Down chr7 688 lncRNA RP23-114A6.4 1.44414E-05 0.001875077
ENSMUST00000181623 −3.39644228 Down chr19 2,054 lncRNA C330002G04Rik 2.31177E-05 0.00236634
ENSMUST00000195137 −3.33047484 Down chr3 2,713 lncRNA RP23-227A12.5 0.002907356 0.035367798
ENSMUST00000218833 −3.24928997 Down chr10 628 lncRNA RP24-377N13.1 0.001323028 0.022299215
ENSMUST00000138767 −3.20394732 Down chr6 1,996 lncRNA RP23-99G18.2 7.83749E-05 0.005088098
ENSMUST00000187223 −2.98711362 Down chr6 3,096 lncRNA Pik3c2g 7.49369E-05 0.005004612
ENSMUST00000175787 −2.864803 Down chr4 1,693 lncRNA RP23-365O6.3 0.002115895 0.029477237

Top 20 differently methylated smallRNAs in the kidneys after cisplatin treatment.

Transcript_ID Log2 (fold change) Regulation Chromosome RNA length Transcript_type Gene symbol p value FDR
MI0021886-pri-5 3.082208595 Up chr18 100 pri-miRNA pri-5-mmu-mir-6358 0.000179897 0.010532486
ENSMUST00000183609 2.761690244 Up chr11 215 snoRNA Gm24949 0.002669786 0.036156425
ENSMUST00000083278 2.706661683 Up chr6 159 snRNA Gm26264 0.000100255 0.010395193
ENSMUST00000157083 2.640817688 Up chrX 139 snRNA Gm23000 4.06993E-05 0.007782031
ENSMUST00000083033 2.581393655 Up chr1 167 snRNA Gm24405 4.00991E-05 0.007782031
ENSMUST00000083111 2.565886571 Up chr3 165 snRNA Gm24046 0.000740094 0.017293193
ENSMUST00000083224 2.50485157 Up chr13 227 snoRNA Gm25483 0.000691744 0.016851184
MI0000562-pri-3 2.476254101 Up chr13 100 pri-miRNA pri-3-mmu-let-7f-1 0.000576182 0.016672703
MI0026036 2.433478337 Up chr1 147 pre-miRNA mmu-mir-3535 0.000815825 0.018540472
ENSMUST00000104215 2.191764197 Up chr4 191 snoRNA Gm25419 0.004983237 0.052157759
MI0022927-pri-3 −1.82022939 Down chr8 100 pri-miRNA pri-3-mmu-mir-7077 4.22172E-05 0.007782031
MI0000400-pri-3 −1.6397752 Down chr12 100 pri-miRNA pri-3-mmu-mir-300 0.007064005 0.065853371
MI0026022 −1.63115661 Down chr16 129 pre-miRNA mmu-mir-8095 0.01101019 0.085457802
MI0022781-pri-3 −1.3878493 Down chr11 100 pri-miRNA pri-3-mmu-mir-6934 0.00092536 0.01920793
MI0004686 −1.26916795 Down chr5 109 pre-miRNA mmu-mir-702 0.004460451 0.048464681
ENSMUST00000157160 −1.0470791 Down chr2 124 snoRNA Gm23172 9.25779E-05 0.010254389
MI0022901-pri-3 −1.04504735 Down chr7 100 pri-miRNA pri-3-mmu-mir-7052 0.000700863 0.016851184
MI0022869-pri-3 −1.03746499 Down chr4 100 pri-miRNA pri-3-mmu-mir-7020 0.004550455 0.048939999
ENSMUST00000122791 −0.97593288 Down chr1 104 snRNA Gm25294 0.002930654 0.038283107
ENSMUST00000175481 −0.94951247 Down chr14 107 snRNA Gm25464 0.008336336 0.073656993
GO and Pathway Analyses of the Host Genes of Differentially m<sup>6</sup>A Modified RNA

To depict the physiological and pathological significance of m6A methylation in Cis-AKI, the host genes of the differentially methylated mRNA were investigated using GO and KEGG pathway analysis. GO analysis indicated that the upregulated methylated transcripts were enriched in the cellular metabolic process (ontology: biological process), intracellular process (ontology: cellular component), and binding (ontology: molecular function; Figure 4A). The downregulated methylated mRNAs were significantly associated with the small molecule metabolic process (ontology: biological process), cell part (ontology: cellular component), and catalytic activity (ontology: molecular function; Figure 4B). KEGG pathway analysis revealed 85 pathways related to hypermethylated genes, including spliceosome, Epstein–Barr virus infection, and RNA transport, and 78 pathways involved in hypomethylated genes, including valine, leucine, and isoleucine degradation, glyoxylate and dicarboxylate metabolism, and propanoate metabolism (Figures 4C,D).

GO and pathway analyses of the host genes of differentially m6A modified RNAs. GO analysis on parental genes of the m6A hypermethylated (A) and hypomethylated (B) mRNA transcripts is shown. The vertical axis demonstrates the annotated functions of the target genes. The horizontal axis demonstrates the enrichment score (−log10 transformed p value) of each cluster. KEGG analysis on parental genes of the m6A hypermethylated (C) and hypomethylated (D) mRNA transcripts is shown. The horizontal axis shows the enrichment score (−log10 transformed p value). Node size: gene count; node color: p value.

 MeRIP-qPCR Verification of Differentially Methylated RNA Expression

To validate the results of our microarray data, we performed m6A immunoprecipitation qPCR (MeRIP-qPCR) assays for six mRNAs and four lncRNAs in the Cis-AKI group and control group, respectively. The m6A methylation manifested a significant increase in Fosl1, Krt20, Cdkn1a, lncRNA RP24-267E6.2, and lncRNA RP23-478H15.3 in the kidney tissues exposed to cisplatin compared with those treated with saline (Figure 5A), whereas the m6A methylation levels of Psme2, Slc35f3, Cndp1, lncRNA RP23-149A5.3, and lncRNA RP23-257O9.1 were significantly decreased (Figure 5A). The abovementioned results exhibited a similar tendency of m6A methylation changes between microarray data and qPCR analysis (Figure 5B).

MeRIP-qPCR verification of differentially methylated RNA expression. (A) The m6A enrichment of selected mRNAs and lncRNAs was detected by the MeRIP-qPCR method. *p < 0.05, vs. control group, n = 4 per group. (B) The comparison between microarray data and MeRIP-qPCR results.

 Discussion

Nephrotoxicity is the most important and dose-limiting adverse event associated with the use of cisplatin that restricts its chemotherapeutic application. Although extensive research has suggested potential mechanisms that may be responsible for acute kidney injury induced by cisplatin, the molecular details are not yet fully understood (Agarwal et al., 2016; Ronco et al., 2019; Uber and Sutherland, 2019). m6A modifications in RNAs are recently recognized as functional regulators in a wide range of diseases, including neurological disorders, cancers, diabetes mellitus, leukemia, and coronary heart disease (Jonkhout et al., 2017; Vu et al., 2017; Kadumuri and Janga, 2018; Wang Y. et al., 2019; Mathiyalagan et al., 2019). However, much less is known about the role of m6A methylation in Cis-AKI. In the current study, we found that the m6A expression pattern is altered in the mouse kidneys after cisplatin treatment with the help of microarray technology. First, the m6A level in the kidney tissue was found to be higher in Cis-AKI mice than in littermate controls. Consistent with this result, the protein level of Mettl3 and Wtap was increased, and the protein level of Fto was decreased. Interestingly, the protein levels of Mettl14 and Alkbh5 exhibited an inverse trend compared with the change in total m6A levels. Furthermore, a total of 618 mRNAs and 98 lncRNAs were significantly differentially regulated and might be implicated in multiple biological processes and pathways. These findings provided an important opportunity to advance the understanding of the role of the m6A RNA modification in Cis-AKI.

An accumulating body of evidence suggests that the m6A modification is involved in the initiation and progression of kidney injury and repair. A recent study showed that the m6A level was elevated in renal tubular epithelial cells after TGF-β1 treatment, suggesting that m6A participated in the process of renal fibrosis (Liu P. et al., 2020). In addition, the m6A methylated RNA was also increased significantly in a mouse model of renal IRI (Xu Y. et al., 2020). Furthermore, the kidney biopsies from patients with AKI had remarkably higher m6A methylated RNA levels than those of patients with non-AKI (Xu Y. et al., 2020). Moreover, the m6A level was positively correlated with serum creatinine levels in these patients (Xu Y. et al., 2020). However, in an animal model of AKI induced by unilateral ureteral obstruction (UUO) operation, m6A methylation in adult mouse kidneys was found to decrease and showed a similar change of the expressions of Mettl3 and Mettl14 (Li X. et al., 2020). Taken together, these studies support the notion that m6A methylation had different regulatory functions in different types of AKI. In the current study, m6A methylated levels in total RNA were increased in the kidney tissues after cisplatin treatment. We further revealed that the expression patterns of m6A-modified RNAs changed significantly in response to cisplatin. Similar to our results, a recent study also found differences in the expression profile of m6A methylation in the kidney tissues after cisplatin treatment (Shen J. et al., 2020). The parent genes of the differentially expressed m6A methylated mRNAs, such as Krt20, Ccdc85b, and Serpina3n were found to be upregulated in both studies, while Ctnna2, Afm, Pzp, and Dgkg were downregulated. Due to the differences in the methods (microarray vs. RNA sequencing) and experimental animal species (129 vs. C57BL/6), the expression patterns of m6A-modified mRNAs in the two studies were not entirely consistent. However, the conclusions of the two studies are consistent, suggesting that m6A methylation may play a crucial role in the pathophysiologic process of Cis-AKI.

M6A is a dynamic and reversible modification that is modulated by the adenosine methyltransferases complex, including Mettl3, Mettl14, and Wtap, and m6A demethylases, such as Fto and Alkbh5 (Vu et al., 2019). In the present study, Mettl3 and Wtap were found to be upregulated in response to cisplatin. These alterations were correlated with the increased m6A modification. By contrast, the protein level of Mettl14 was decreased after cisplatin treatment, which was inconsistent with the trend of changes of the total m6A levels. Similarly, a recent study demonstrated that the abundance of m6A is partially correlated with the expression level of their writers and erasers (Liu J. et al., 2020). The authors found that the expressions of Mettl3 and Wtap, but not Mettl14, showed positive correlations with the m6A signal variation in human tissues (Liu J. et al., 2020). Thus, our unanticipated results suggested that the synthetic activity of the METLL3 and Wtap may exceed the effect of the downregulation of Mettl14, thus collectively contributing to the elevation of m6A modification in Cis-AKI. Nevertheless, the underlying mechanisms are still under scrutiny. The recent work by Panneerdoss S et al. revealed that Alkbh5/Mettl14 affected each other’s expression and restrained the translational stability of m6A reader YTHDF3, which, in turn, inhibited RNA demethylase activity and determined the m6A abundance of target genes (Panneerdoss et al., 2018). Therefore, this study outlines a critical role for Alkbh5 in the regulation of Mettl14 expression, which might be a potential mechanism for the inconsistency in the expression levels of Mettl3/Wtap and Mettl14, and ultimately leads to the total abundance of m6A upregulation.

Previous research has established that the adenosine methyltransferase complex is involved in a variety of biological processes, including cell cycle, cell proliferation, cell apoptosis, inflammation response, and metabolism (Liu S. et al., 2020). In mouse renal tubular epithelial cells, Mettl3 overexpression alleviated the colistin-induced renal injury by reducing apoptosis and enhancing the ability of antioxidative stress by the regulation of Nrf2, HO-1, and Keap1 (Wang J. et al., 2019). These results reflect those of Fanhang Meng et al. who also found that suppressing Mettl3 could lead to the decreased expression of cleaved caspase-3, resulting in the reduction of NRK-52E cell apoptosis (Meng et al., 2020). On the contrary, knocking down the expression of Mettl3 could inhibit the viability, proliferation, and migration potential of HK2 cells and, thus, attenuate the TGF-β1–induced epithelial–mesenchymal transition (EMT), suggesting that Mettl3 might play a detrimental role in the process of renal fibrosis (Liu P. et al., 2020). In addition to Mettl3, the expression of Mettl14 was found to consistently increase in the kidney biopsies from patients with AKI, compared with those from patients with non-AKI (Xu Y. et al., 2020). Moreover, loss of function of Mettl14 could mitigate the IRI-induced kidney injury through enhancing YAP1-TEAD signaling (Meng et al., 2020). Consistently, overexpression of Mettl14 was reported to significantly increase the expression of cleaved caspase-3 and promote apoptosis in HK2 cells with cisplatin treatment (Zhou P. et al., 2019). Therefore, the key members of the m6A writers, Mettl3 and Mettl14, might play a critical role in the development of AKI.

Fto, identified as the first obesity-susceptibility gene, has been repeatedly linked to obesity traits, insulin resistance, and type 2 diabetes (Dina et al., 2007; Frayling et al., 2007; Spoto et al., 2012; Loos and Yeo, 2014). Variants in this gene were subsequently reported to associate with the risk of chronic kidney disease (CKD), reduced estimated glomerular filtration rate (eGFR) in type 2 diabetes patients, and all-cause mortality in predialysis and dialysis patients (Franceschini et al., 2012; Hubacek et al., 2012; Spoto et al., 2012; Chen et al., 2013). This gene codes for an enzyme that selectively removes the methyl group from target RNAs, and by this mechanism, it may regulate epigenetic modifications of relevant genes to determine the cell fate. For example, a recent study showed that Fto-dependent m6A demethylation enhanced the expression of antiapoptotic genes and subsequently led to cell survival (Yan et al., 2018). Another study demonstrated that inhibition of Fto would increase m6A levels and aggravate the renal damages through p53-mediated apoptosis pathways (Zhou P. et al., 2019). On the contrary, several reports found that Fto was increased after ureteral obstruction and renal fibrosis (Wang C. Y. et al., 2016; Li X. et al., 2020). Furthermore, deficiency of the Fto gene attenuated the fibrogenic responses induced by ureteral obstruction in the kidney (Wang C. Y. et al., 2016). Moreover, recent evidence showed that Fto affected mitochondrial content and fat metabolism by modulating m6A levels in hepatocytes (Kang et al., 2018). Similarly, Changshui Zhuang and colleagues found that Fto influenced mitochondria integrity through regulating mitochondrial fusion, fission, and biogenesis (Zhuang et al., 2019). Furthermore, extensive research has revealed that improvement of mitochondrial function could alleviate cisplatin-induced nephrotoxicity (Li M. et al., 2020; Yu et al., 2020). In the present study, Fto was found to decrease in kidney tissue after cisplatin treatment and correlate with increased m6A modification. Therefore, Fto and the subsequent m6A modification might be involved in the pathological process of AKI.

Concerning another primary m6A demethylase, Alkbh5, there are plenty of studies that described its pivotal functions in multiple pathophysiological processes, such as proliferation, apoptosis, and autophagy (Wang et al., 2020). Recently, investigators have demonstrated that Alkbh5 was involved in neuronal apoptosis by affecting neurons’ methylation (Xu K. et al., 2020). Contrary to expectations, this study found that the increasing trend of RNA m6A modification was in parallel with the paradoxical upregulated expression of Alkbh5 in the cerebral cortex of rats after cerebral IRI (Xu K. et al., 2020). In accordance with their results, we found that the increased total abundance of m6A was consecutive to the increase of Alkbh5 expression after cisplatin treatment. It is difficult to explain this result, but the authors believed that it might be related to the compensatory effect of oxidative stress on Alkbh5 (Xu K. et al., 2020). Moreover, a recent study indicated that an increase in Alkbh5 might be compensated for the loss of Fto in the failing hearts (Mathiyalagan et al., 2019). Another possible explanation for these unexpected results may be the involvement of m6A writers and readers. As mentioned above, there was crosstalk between Mettl14 and Alkbh5, which is manifested as that knocking down of Mettl14 resulted in significantly reduced levels of Alkbh5, while silencing of Alkbh5 decreased Mettl14 levels (Panneerdoss et al., 2018). In addition, the activity of Alkbh5 can be further regulated by YTHDF3, an m6A reader, which restrained the activity of RNA demethylase (Panneerdoss et al., 2018). Therefore, the inconsistency between m6A level and Alkbh5/Mettl14 expression in the present study might be due to the compensatory effect of oxidative stress and Fto, as well as the crosstalk between Alkbh5 and Mettl14.

It is now well established from a variety of studies that cisplatin-induced nephrotoxicity is mediated through reactive nitrogen species (ROS), induction of proapoptotic and inflammatory pathways, and metabolic disorders (Perazella and Moeckel, 2010; Perazella, 2012; Perazella and Izzedine, 2015; Perazella, 2019). ROS plays a direct detrimental role in DNA and protein synthesis, cellular structure maintenance, and cell repair mechanisms (Perazella, 2019). The GO analysis results indicated that the altered m6A methylated transcripts were mainly associated with intracellular, binding, and cell part, which were closely related to the adverse effect of ROS, implying that the m6A modification might be essential for the oxidative stress response in AKI. In addition, further analysis demonstrated that the parent genes of the top three altered methylated mRNAs (Fosl1, Krt20, and Cdkn1a) participated in regulating apoptotic pathways (Torgovnick et al., 2018; Shen S. et al., 2020). A study conducted by Shen J et al. also found that genes with elevated methylation of m6A sites were significantly enriched in the cell death processes, such as apoptotic processes (Shen J. et al., 2020). Since apoptosis in renal tubular epithelial cells is a major feature of AKI, we would predict that m6A methylation has a pivotal role in tubular cell death.

Besides ROS and apoptosis, the metabolic disorder was identified as a new mechanism that leads to kidney function decline. The tubular epithelial cell, the most susceptible cell type to cisplatin in the kidney, combusts fatty acids to generate adenosine triphosphate (ATP) through oxidative phosphorylation for the high transport and reabsorption activities (Tammaro et al., 2020). Tran and colleagues recently showed that nicotinamide adenine dinucleotide (NAD+), an essential cofactor for fatty acid oxidation (FAO) (Szeto, 2017), was decreased in the renal tubular cells with IRI treatment, and this reduction in NAD+ may develop marked fat accumulation and renal function impairment (Tran et al., 2016). Our previous study also demonstrated that the levels of ATP, adenosine diphosphate (ADP), NAD+, nicotinamide adenine dinucleotide phosphate (NADP+), flavin mononucleotide (FMN), and other tricarboxylic acid cycle (TCA) products were significantly declined in response to cisplatin (Li M. et al., 2020). We further found that FAO improvement can attenuate Cis-AKI in mice (Li M. et al., 2020). In addition to fatty acid metabolism, Zhou et al. found that inhibitory S-nitrosylation of pyruvate kinase M2 (PKM2), a key enzyme of glycolysis, shunted metabolic intermediates and shifted metabolic flux from glycolytic to antioxidant pathways, leading to significant protection against declining kidney function in mice (Zhou H. L. et al., 2019). Furthermore, Legouis and colleagues showed that glucose production was impaired during AKI and this reduction in renal glucose due to the disorder of gluconeogenesis in proximal tubule cells was strongly associated with mortality in ICU patients with AKI (Legouis et al., 2020). This study highlights an unappreciated systemic role of renal glucose metabolism in kidney damage (Legouis et al., 2020). In cisplatin-induced AKI, a recent study indicated that genes with differently altered methylation of m6A sites were highly enriched in metabolic processes (Shen J. et al., 2020). Regarding amino acid metabolism, the levels of phenylalanine, allantoic acid, methylcysteine, gamma-aminobutyric acid, beta-alanine, and aminoadipic acid in the renal cortex of Sprague Dawley rats were increased significantly after intraperitoneal injection of endotoxin lipopolysaccharide (LPS) (Ping et al., 2019). Metabolic pathway analysis revealed that taurine and hypotaurine metabolism, pantothenic acid and CoA biosynthesis, and phenylalanine metabolism were involved in the development of AKI in sepsis (Ping et al., 2019). In the present study, we found that the host genes of the differentially methylated mRNA were enriched in the metabolic process and amino acid degradation. Therefore, we concluded that m6A methylation might be essential for the development and progression of AKI, regarding the abovediscussed functions of metabolic process and amino acid metabolism during kidney damage.

 Conclusion

In conclusion, the current work identified the differential m6A methylome in the kidney in response to cisplatin treatment, indicating a potential relationship between m6A modification and the regulation of the pathophysiologic process in AKI. Mettl3, Mettl14, Wtap, Fto, and Alkbh5 might play a vital role in the epigenetic modification of transcripts in cisplatin-treated kidneys. Overall, the empirical findings in this study might provide novel therapeutic targets for AKI treatment by fine-tuning the m6A modification.

 Data Availability Statement

The original contributions presented in the study are publicly available. These data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE165100, accession number: GSE165100.

 Ethics Statement

The animal study was reviewed and approved by the Animal Care Committee of Sun Yat-sen University.

 Author Contributions

C-ML and ML performed the biological experiments. C-ML, ML, W-BZ, and Z-CY made the acquisition, analysis, or interpretation of data for the work. C-ML and HP drafted the manuscript. All the authors read and approved the final manuscript.

 Funding

This study was supported by the Science and Technology Program of Guangzhou, China (International Science and Technology Cooperation Program; Grant No. 201807010037 to HP), the National Natural Science Foundation of Guangdong, China (Grant No. 2017A030313714 to HP), and the National Natural Science Foundation of China (Grant No. 81470954). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

 Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

 References Agarwal A. Dong Z. Harris R. Murray P. Parikh S. M. Rosner M. H. (2016). Cellular and Molecular Mechanisms of AKI. Jasn 27 (5), 1288–1299. 10.1681/asn.2015070740 Bajorin D. F. Bosl G. J. Alcock N. W. Niedzwiecki D. Gallina E. Shurgot B. (1986). Pharmacokinetics of cis-Diamminedichloroplatinum(II) after Administration in Hypertonic saline. Cancer Res. 46 (11), 5969–5972. Boccaletto P. Machnicka M. A. Purta E. Piątkowski P. Bagiński B. Wirecki T. K. (2018). MODOMICS: a Database of RNA Modification Pathways. 2017 Update. Nucleic Acids Res. 46 (D1), D303–D307. 10.1093/nar/gkx1030 Bonventre J. V. Vaidya V. S. Schmouder R. Feig P. Dieterle F. (2010). Next-generation Biomarkers for Detecting Kidney Toxicity. Nat. Biotechnol. 28 (5), 436–440. 10.1038/nbt0510-436 Chen G. Xu Y. Lin Y. Lai X. Yao J. Huang B. (2013). Association Study of Genetic Variants of 17 Diabetes-Related Genes/loci and Cardiovascular Risk and Diabetic Nephropathy in the Chinese She Population. J. Diabetes 5 (2), 136–145. 10.1111/1753-0407.12025 Chen X. Y. Zhang J. Zhu J. S. (2019). The Role of M(6)A RNA Methylation in Human Cancer. Mol. Cancer 18 (1), 103. 10.1186/s12943-019-1033-z Deng F. Sharma I. Dai Y. Yang M. Kanwar Y. S. (2019). Myo-inositol Oxygenase Expression Profile Modulates Pathogenic Ferroptosis in the Renal Proximal Tubule. J. Clin. Invest. 129 (11), 5033–5049. 10.1172/jci129903 Desrosiers R. Friderici K. Rottman F. (1974). Identification of Methylated Nucleosides in Messenger RNA from Novikoff Hepatoma Cells. Proc. Natl. Acad. Sci. 71 (10), 3971–3975. 10.1073/pnas.71.10.3971 Dina C. Meyre D. Gallina S. Durand E. Körner A. Jacobson P. (2007). Variation in FTO Contributes to Childhood Obesity and Severe Adult Obesity. Nat. Genet. 39 (6), 724–726. 10.1038/ng2048 Dominissini D. Moshitch-Moshkovitz S. Schwartz S. Salmon-Divon M. Ungar L. Osenberg S. (2012). Topology of the Human and Mouse m6A RNA Methylomes Revealed by m6A-Seq. Nature 485 (7397), 201–206. 10.1038/nature11112 Dos Santos N. A. G. Carvalho Rodrigues M. A. Martins N. M. Dos Santos A. C. (2012). Cisplatin-induced Nephrotoxicity and Targets of Nephroprotection: an Update. Arch. Toxicol. 86 (8), 1233–1250. 10.1007/s00204-012-0821-7 Franceschini N. Shara N. M. Wang H. Voruganti V. S. Laston S. Haack K. (2012). The Association of Genetic Variants of Type 2 Diabetes with Kidney Function. Kidney Int. 82 (2), 220–225. 10.1038/ki.2012.107 Frayling T. M. Timpson N. J. Weedon M. N. Zeggini E. Freathy R. M. Lindgren C. M. (2007). A Common Variant in the FTO Gene Is Associated with Body Mass index and Predisposes to Childhood and Adult Obesity. Science 316 (5826), 889–894. 10.1126/science.1141634 Gene Ontology Consortium (2006). The Gene Ontology (GO) Project in 2006. Nucleic Acids Res. 34 (Database issue), D322–D326. 10.1093/nar/gkj021 Guo C. Dong G. Liang X. Dong Z. (2019). Epigenetic Regulation in AKI and Kidney Repair: Mechanisms and Therapeutic Implications. Nat. Rev. Nephrol. 15 (4), 220–239. 10.1038/s41581-018-0103-6 Huang H. Weng H. Chen J. (2020). The Biogenesis and Precise Control of RNA m6A Methylation. Trends Genet. 36 (1), 44–52. 10.1016/j.tig.2019.10.011 Hubacek J. A. Viklicky O. Dlouha D. Bloudickova S. Kubinova R. Peasey A. (2012). The FTO Gene Polymorphism Is Associated with End-Stage Renal Disease: Two Large Independent Case-Control Studies in a General Population. Nephrol. Dial. Transplant. 27 (3), 1030–1035. 10.1093/ndt/gfr418 Jia G. Fu Y. Zhao X. Dai Q. Zheng G. Yang Y. (2011). N6-methyladenosine in Nuclear RNA Is a Major Substrate of the Obesity-Associated FTO. Nat. Chem. Biol. 7 (12), 885–887. 10.1038/nchembio.687 Jiang L. Schlesinger F. Davis C. A. Zhang Y. Li R. Salit M. (2011). Synthetic Spike-In Standards for RNA-Seq Experiments. Genome Res. 21 (9), 1543–1551. 10.1101/gr.121095.111 Jonkhout N. Tran J. Smith M. A. Schonrock N. Mattick J. S. Novoa E. M. (2017). The RNA Modification Landscape in Human Disease. RNA 23 (12), 1754–1769. 10.1261/rna.063503.117 Kadumuri R. V. Janga S. C. (2018). Epitranscriptomic Code and its Alterations in Human Disease. Trends Mol. Med. 24 (10), 886–903. 10.1016/j.molmed.2018.07.010 Kang H. Zhang Z. Yu L. Li Y. Liang M. Zhou L. (2018). FTO Reduces Mitochondria and Promotes Hepatic Fat Accumulation through RNA Demethylation. J. Cell. Biochem. 119 (7), 5676–5685. 10.1002/jcb.26746 Kato M. Natarajan R. (2019). Epigenetics and Epigenomics in Diabetic Kidney Disease and Metabolic Memory. Nat. Rev. Nephrol. 15 (6), 327–345. 10.1038/s41581-019-0135-6 Lameire N. H. Bagga A. Cruz D. De Maeseneer J. Endre Z. Kellum J. A. (2013). Acute Kidney Injury: an Increasing Global Concern. The Lancet 382 (9887), 170–179. 10.1016/s0140-6736(13)60647-9 Legouis D. Ricksten S.-E. Faivre A. Verissimo T. Gariani K. Verney C. (2020). Altered Proximal Tubular Cell Glucose Metabolism during Acute Kidney Injury Is Associated with Mortality. Nat. Metab. 2 (8), 732–743. 10.1038/s42255-020-0238-1 Li C.-M. Li M. Ye Z.-C. Huang J.-Y. Li Y. Yao Z.-Y. (2019). Circular RNA Expression Profiles in Cisplatin-Induced Acute Kidney Injury in Mice. Epigenomics 11 (10), 1191–1207. 10.2217/epi-2018-0167 Li M. M. Li C. m. Ye Z. c. Huang J. Li Y. Lai W. (2020). Sirt3 Modulates Fatty Acid Oxidation and Attenuates Cisplatin‐induced AKI in Mice. J. Cell Mol Med 24, 5109–5121. 10.1111/jcmm.15148 Li X. Fan X. Yin X. Liu H. Yang Y. (2020). Alteration of N6-Methyladenosine Epitranscriptome Profile in Unilateral Ureteral Obstructive Nephropathy. Epigenomics 12, 1157–1173. 10.2217/epi-2020-0126 Linehan W. M. Ricketts C. J. (2019). The Cancer Genome Atlas of Renal Cell Carcinoma: Findings and Clinical Implications. Nat. Rev. Urol. 16 (9), 539–552. 10.1038/s41585-019-0211-5 Linkermann A. Chen G. Dong G. Kunzendorf U. Krautwald S. Dong Z. (2014). Regulated Cell Death in AKI. Jasn 25 (12), 2689–2701. 10.1681/asn.2014030262 Liu J. Li K. Cai J. Zhang M. Zhang X. Xiong X. (2020). Landscape and Regulation of m6A and m6Am Methylome across Human and Mouse Tissues. Mol. Cell 77 (2), 426–440.e6. 10.1016/j.molcel.2019.09.032 Liu J. Yue Y. Han D. Wang X. Fu Y. Zhang L. (2014). A METTL3-METTL14 Complex Mediates Mammalian Nuclear RNA N6-Adenosine Methylation. Nat. Chem. Biol. 10 (2), 93–95. 10.1038/nchembio.1432 Liu P. Zhang B. Chen Z. He Y. Du Y. Liu Y. (2020). m6A-induced lncRNA MALAT1 Aggravates Renal Fibrogenesis in Obstructive Nephropathy through the miR-145/FAK pathwayA-Induced lncRNA MALAT1 Aggravates Renal Fibrogenesis in Obstructive Nephropathy through the miR-145/FAK Pathway. Aging 12 (6), 5280–5299. 10.18632/aging.102950 Liu S. Zhuo L. Wang J. Zhang Q. Li Q. Li G. (2020). METTL3 Plays Multiple Functions in Biological Processes. Am. J. Cancer Res. 10 (6), 1631–1646. Livneh I. Moshitch-Moshkovitz S. Amariglio N. Rechavi G. Dominissini D. (2020). The m6A Epitranscriptome: Transcriptome Plasticity in Brain Development and Function. Nat. Rev. Neurosci. 21 (1), 36–51. 10.1038/s41583-019-0244-z Loghman-Adham D. M. Kiu Weber D. C. I. Ciorciaro D. C. Mann D. J. Meier D. M. (2012). Detection and Management of Nephrotoxicity during Drug Development. Expert Opin. Drug Saf. 11 (4), 581–596. 10.1517/14740338.2012.691964 Loos R. J. F. Yeo G. S. H. (2014). The Bigger Picture of FTO-The First GWAS-Identified Obesity Gene. Nat. Rev. Endocrinol. 10 (1), 51–61. 10.1038/nrendo.2013.227 Mathiyalagan P. Adamiak M. Mayourian J. Sassi Y. Liang Y. Agarwal N. (2019). FTO-Dependent N 6 -Methyladenosine Regulates Cardiac Function During Remodeling and Repair. Circulation 139 (4), 518–532. 10.1161/circulationaha.118.033794 Mehta R. L. Burdmann E. A. Cerdá J. Feehally J. Finkelstein F. García-García G. (2016). Recognition and Management of Acute Kidney Injury in the International Society of Nephrology 0by25 Global Snapshot: a Multinational Cross-Sectional Study. The Lancet 387 (10032), 2017–2025. 10.1016/s0140-6736(16)30240-9 Mehta R. L. Cerdá J. Burdmann E. A. Tonelli M. García-García G. Jha V. (2015). International Society of Nephrology's 0by25 Initiative for Acute Kidney Injury (Zero Preventable Deaths by 2025): a Human Rights Case for Nephrology. The Lancet 385 (9987), 2616–2643. 10.1016/s0140-6736(15)60126-x Meng F. Liu Y. Chen Q. Ma Q. Gu S. Cui R. (2020). METTL3 Contributes to Renal Ischemia-Reperfusion Injury by Regulating Foxd1 Methylation. Am. J. Physiology-Renal Physiol. 319 (5), F839–F847. 10.1152/ajprenal.00222.2020 Miller R. P. Tadagavadi R. K. Ramesh G. Reeves W. B. (2010). Mechanisms of Cisplatin Nephrotoxicity. Toxins 2 (11), 2490–2518. 10.3390/toxins2112490 Panneerdoss S. Eedunuri V. K. Yadav P. Timilsina S. Rajamanickam S. Viswanadhapalli S. (2018). Cross-talk Among Writers, Readers, and Erasers of m6A Regulates Cancer Growth and Progression. Sci. Adv. 4 (10), eaar8263. 10.1126/sciadv.aar8263 Perazella M. A. (2012). Onco-nephrology: Renal Toxicities of Chemotherapeutic Agents. Cjasn 7 (10), 1713–1721. 10.2215/cjn.02780312 Perazella M. A. (2019). Drug-induced Acute Kidney Injury. Curr. Opin. Crit. Care 25 (6), 550–557. 10.1097/mcc.0000000000000653 Perazella M. A. Izzedine H. (2015). New Drug Toxicities in the Onco-Nephrology World. Kidney Int. 87 (5), 909–917. 10.1038/ki.2015.30 Perazella M. A. Moeckel G. W. (2010). Nephrotoxicity from Chemotherapeutic Agents: Clinical Manifestations, Pathobiology, and Prevention/therapy. Semin. Nephrol. 30 (6), 570–581. 10.1016/j.semnephrol.2010.09.005 Perry R. P. Kelley D. E. (1974). Existence of Methylated Messenger RNA in Mouse L Cells. Cell 1 (1), 37–42. 10.1016/0092-8674(74)90153-6 Ping F. Guo Y. Cao Y. Shang J. Yao S. Zhang J. (2019). Metabolomics Analysis of the Renal Cortex in Rats with Acute Kidney Injury Induced by Sepsis. Front. Mol. Biosci. 6, 152. 10.3389/fmolb.2019.00152 Ping X.-L. Sun B.-F. Wang L. Xiao W. Yang X. Wang W.-J. (2014). Mammalian WTAP Is a Regulatory Subunit of the RNA N6-Methyladenosine Methyltransferase. Cell Res 24 (2), 177–189. 10.1038/cr.2014.3 Quintanilha J. C. F. Saavedra K. F. Visacri M. B. Moriel P. Salazar L. A. (2019). Role of Epigenetic Mechanisms in Cisplatin-Induced Toxicity. Crit. Rev. Oncology/Hematology 137, 131–142. 10.1016/j.critrevonc.2019.03.004 Ronco C. Bellomo R. Kellum J. A. (2019). Acute Kidney Injury. The Lancet 394 (10212), 1949–1964. 10.1016/s0140-6736(19)32563-2 Rosner M. H. Perazella M. A. (2017). Acute Kidney Injury in Patients with Cancer. N. Engl. J. Med. 376 (18), 1770–1781. 10.1056/nejmra1613984 Rottman F. Shatkin A. J. Perry R. P. (1974). Sequences Containing Methylated Nucleotides at the 5′ Termini of Messenger RNAs: Possible Implications for Processing. Cell 3 (3), 197–199. 10.1016/0092-8674(74)90131-7 Ruiz-Ortega M. Rayego-Mateos S. Lamas S. Ortiz A. Rodrigues-Diez R. R. (2020). Targeting the Progression of Chronic Kidney Disease. Nat. Rev. Nephrol. 16, 269–288. 10.1038/s41581-019-0248-y Schumann U. Shafik A. Preiss T. (2016). METTL3 Gains R/W Access to the Epitranscriptome. Mol. Cell 62 (3), 323–324. 10.1016/j.molcel.2016.04.024 Shen J. Wang W. Shao X. Wu J. Li S. Che X. (2020). Integrated Analysis of m6A Methylome in Cisplatin-Induced Acute Kidney Injury and Berberine Alleviation in Mouse. Front. Genet. 11, 584460. 10.3389/fgene.2020.584460 Shen S. Li K. Liu Y. Liu X. Liu B. Ba Y. (2020). Silencing lncRNA AGAP2-AS1 Upregulates miR-195-5p to Repress Migration and Invasion of EC Cells via the Decrease of FOSL1 Expression. Mol. Ther. - Nucleic Acids 20, 331–344. 10.1016/j.omtn.2019.12.036 Spoto B. Mattace-Raso F. Sijbrands E. Mallamaci F. Leonardis D. Aucella F. (2012). The Fat-Mass and Obesity-Associated Gene (FTO) Predicts Mortality in Chronic Kidney Disease of Various Severity. Nephrol. Dial. Transpl. 27 (Suppl. 4), iv58–iv62. 10.1093/ndt/gfs550 Susantitaphong P. Cruz D. N. Cerda J. Abulfaraj M. Alqahtani F. Koulouridis I. (2013). World Incidence of AKI: a Meta-Analysis. Cjasn 8 (9), 1482–1493. 10.2215/cjn.00710113 Szeto H. H. (2017). Pharmacologic Approaches to Improve Mitochondrial Function in AKI and CKD. Jasn 28 (10), 2856–2865. 10.1681/asn.2017030247 Tammaro A. Kers J. Scantlebery A. M. L. Florquin S. (2020). Metabolic Flexibility and Innate Immunity in Renal Ischemia Reperfusion Injury: The Fine Balance between Adaptive Repair and Tissue Degeneration. Front. Immunol. 11, 1346. 10.3389/fimmu.2020.01346 Tanase D. M. Gosav E. M. Radu S. (2019). The Predictive Role of the Biomarker Kidney Molecule-1 (KIM-1) in Acute Kidney Injury (AKI) Cisplatin-Induced Nephrotoxicity. Int. J. Mol. Sci. 20 (20). 10.3390/ijms20205238 Torgovnick A. Heger J. M. Liaki V. Isensee J. Schmitt A. Knittel G. (2018). The Cdkn1aSUPER Mouse as a Tool to Study P53-Mediated Tumor Suppression. Cell Rep. 25 (4), 1027–1039 e1026. 10.1016/j.celrep.2018.09.079 Tran M. T. Zsengeller Z. K. Berg A. H. Khankin E. V. Bhasin M. K. Kim W. (2016). PGC1α Drives NAD Biosynthesis Linking Oxidative Metabolism to Renal protection. Nature 531 (7595), 528–532. 10.1038/nature17184 Uber A. M. Sutherland S. M. (2019). Nephrotoxins and Nephrotoxic Acute Kidney Injury. Pediatr. Nephrol. 35, 1825–1833. 10.1007/s00467-019-04397-2 Vu L. P. Cheng Y. Kharas M. G. (2019). The Biology of m6A RNA Methylation in Normal and Malignant Hematopoiesis. Cancer Discov. 9 (1), 25–33. 10.1158/2159-8290.cd-18-0959 Vu L. P. Pickering B. F. Cheng Y. Zaccara S. Nguyen D. Minuesa G. (2017). The N6-Methyladenosine (m6A)-Forming Enzyme METTL3 Controls Myeloid Differentiation of normal Hematopoietic and Leukemia Cells. Nat. Med. 23 (11), 1369–1376. 10.1038/nm.4416 Wang C. Y. Shie S. S. Tsai M. L. Yang C. H. Hung K. C. Wang C. C. (2016). FTO Modulates Fibrogenic Responses in Obstructive Nephropathy. Sci. Rep. 6, 18874. 10.1038/srep18874 Wang J. Ishfaq M. Xu L. Xia C. Chen C. Li J. (2019). METTL3/m(6)A/miRNA-873-5p Attenuated Oxidative Stress and Apoptosis in Colistin-Induced Kidney Injury by Modulating Keap1/Nrf2 Pathway. Front. Pharmacol. 10, 517. 10.3389/fphar.2019.00517 Wang J. Wang J. Gu Q. (2020). The Biological Function of m6A Demethylase ALKBH5 and its Role in Human Disease. Cancer Cell Int 20, 347. 10.1186/s12935-020-01450-1 Wang X. Feng J. Xue Y. Guan Z. Zhang D. Liu Z. (2016). Structural Basis of N6-Adenosine Methylation by the METTL3-METTL14 Complex. Nature 534 (7608), 575–578. 10.1038/nature18298 Wang Y. Mao J. Wang X. Lin Y. Hou G. Zhu J. (2019). Genome-wide Screening of Altered m6A-Tagged Transcript Profiles in the hippocampus after Traumatic Brain Injury in Mice. Epigenomics 11 (7), 805–819. 10.2217/epi-2019-0002 Wei W. Ji X. Guo X. Ji S. (2017). Regulatory Role of N6-Methyladenosine (m6A) Methylation in RNA Processing and Human Diseases. J. Cell. Biochem. 118 (9), 2534–2543. 10.1002/jcb.25967 Xiang X. Guo C. Tang C. Cai J. Dong Z. (2019). Epigenetic Regulation in Kidney Toxicity: Insights from Cisplatin Nephrotoxicity. Semin. Nephrol. 39 (2), 152–158. 10.1016/j.semnephrol.2018.12.005 Xu K. Mo Y. Li D. Yu Q. Wang L. Lin F. (2020). N(6)-methyladenosine Demethylases Alkbh5/Fto Regulate Cerebral Ischemia-Reperfusion Injury. Ther. Adv. Chronic Dis. 11, 2040622320916024. 10.1177/2040622320916024 Xu Y. Yuan X. D. Wu J. J. Chen R. Y. Xia L. Zhang M. (2020). The N6‐methyladenosine mRNA Methylase METTL14 Promotes Renal Ischemic Reperfusion Injury via Suppressing YAP1. J. Cell Biochem 121 (1), 524–533. 10.1002/jcb.29258 Yan F. Al-Kali A. Zhang Z. Liu J. Pang J. Zhao N. (2018). A Dynamic N6-Methyladenosine Methylome Regulates Intrinsic and Acquired Resistance to Tyrosine Kinase Inhibitors. Cell Res 28 (11), 1062–1076. 10.1038/s41422-018-0097-4 Yang Y. Fan X. Mao M. Song X. Wu P. Zhang Y. (2017). Extensive Translation of Circular RNAs Driven by N6-Methyladenosine. Cell Res 27 (5), 626–641. 10.1038/cr.2017.31 Yu X. Xu M. Meng X. Li S. Liu Q. Bai M. (2020). Nuclear Receptor PXR Targets AKR1B7 to Protect Mitochondrial Metabolism and Renal Function in AKI. Sci. Transl Med. 12 (543), eaay7591. 10.1126/scitranslmed.aay7591 Zheng G. Dahl J. A. Niu Y. Fedorcsak P. Huang C.-M. Li C. J. (2013). ALKBH5 Is a Mammalian RNA Demethylase that Impacts RNA Metabolism and Mouse Fertility. Mol. Cell 49 (1), 18–29. 10.1016/j.molcel.2012.10.015 Zhou H.-L. Zhang R. Anand P. Stomberski C. T. Qian Z. Hausladen A. (2019). Metabolic Reprogramming by the S-Nitroso-CoA Reductase System Protects against Kidney Injury. Nature 565 (7737), 96–100. 10.1038/s41586-018-0749-z Zhou P. Wu M. Ye C. Xu Q. Wang L. (2019). Meclofenamic Acid Promotes Cisplatin-Induced Acute Kidney Injury by Inhibiting Fat Mass and Obesity-Associated Protein-Mediated m6A Abrogation in RNA. J. Biol. Chem. 294 (45), 16908–16917. 10.1074/jbc.ra119.011009 Zhuang C. Zhuang C. Luo X. Huang X. Yao L. Li J. (2019). N6-methyladenosine demethylase FTO suppresses clear cell renal cell carcinoma through a novel FTO-PGC-1α signalling axis. J Cell Mol Med 23 (3), 2163–2173. 10.1111/jcmm.14128