All animal experiments were performed under the guidance of the Institutional Animal Care and Use Committee (IACUC) of the Korea Institute of Toxicology (Daejeon, China). Sprague-Dawley rats (24 males, 8 weeks old, 240–260 g) were purchased from Orient Bio, Inc. (Seongnam, Korea) and acclimated for 1 week prior to the experiment. All rats were housed under standard laboratory conditions on a 12-h light/dark cycle, under controlled temperature (23±3°C) and humidity (50±20%). The rats were divided into groups of eight and were fed standard food pellets and water ad libitum. The CMS was purchased from Samchundang Pharm (Seoul, Korea), diluted with 0.9% saline (Dai Han Pharm, Co., Ansan, Korea), and administered at concentrations of 0, 25, and 50 mg/kg body weight. Each rat was injected with 0.9% saline (a vehicle control) or CMS via intraperitoneal injection daily for 7 days. Prior to sacrifice, all rats were fasted overnight and anesthetized by isoflurane inhalation. All experiments were approved by the IACUC of the Korea Institute of Toxicology (approval no. 1404-0120) and conducted in accordance with the Association of Assessment and Accreditation of Laboratory Animal Care International guidelines.

The total body weight and weights of the right and left kidneys were measured, and the relative organ weight ratio was calculated. Blood samples of ~1.5 ml were drawn from the inferior vena cava and serum samples were separated by centrifugation at 2,000 × g for 10 min at room temperature. The serum chemistry parameters were measured using a Toshiba 120 FR chemistry analyzer (Toshiba Corporation, Tokyo, Japan). For histopathological evaluation, the tissues were fixed in paraformaldehyde (4%) and embedded in paraffin. The paraffin blocks were sectioned at 4 µm thickness using a microtome. The sectioned tissues were stained with hematoxylin and eosin. All histopathological results were reviewed by pathology experts at Korea Institute of Toxicology in a blinded-manner.

Following animal sacrifice, the whole right kidneys were extracted and frozen immediately in liquid nitrogen. The frozen samples were homogenized with a TissueLyser (Qiagen GmbH, Hilden, Germany) and total RNA was purified using an RNeasy^® Mini kit (Qiagen GmbH) according to the manufacturer's protocol. The concentration and quality of total RNA were determined using a NanoDrop™ spectrophotometer (NanoDrop Technologies; Thermo Fisher Scientific, Inc., Waltham, MA, USA) and the RNA integrity was measured using a 2100 Bioanalyzer (Agilent Technologies, Inc., Santa Clara, CA, USA).

The Affymetrix GeneChip Rat 230 2.0 (Affymetrix; Thermo Fisher Scientific, Inc.) was used for microarray analysis. Three rats were randomly selected from each CMS-treated group (0, 25, and 50 mg/kg). Microarray analysis was conducted according to the GeneChip^® 3′ expression array user guide (Affymetrix; Thermo Fisher Scientific, Inc.). cDNA synthesis, cRNA synthesis, biotin labeling, cRNA purification and fragmentation were performed according to the manufacturer's protocols (Affymetrix; Thermo Fisher Scientific, Inc.). The microarrays were hybridized at 45°C at 60 rpm for 16 h. The microarrays were stained and washed using a Fluidics Station 450 system (Affymetrix; Thermo Fisher Scientific, Inc.). A GeneChip^® Scanner 3000 (Affymetrix; Thermo Fisher Scientific, Inc.) was used to scan the microarrays. The reproducibility of the microarray experiments was confirmed using well-defined quality control criteria according to the manufacturer's protocol. The micro-array data was deposited into the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/; no. GSE121792).

To perform the preprocessing and statistical analysis of the microarray data, GeneSpring GX v.13.0 analysis software was used (Agilent Technologies, Inc.). Normalization was performed using robust multichip average quantile median normalization. To determine significance, one-way analysis of variance was used (P≤0.05) followed by Tukey's honest significant difference (HSD) post hoc test, and the Benjamini-Hochberg false discovery rate (FDR; P≤0.05) multiple testing correction was performed. The DEGs were selected based on a 1.3-fold-change compared with the control samples, as described previously (23). Venn diagram analysis was used to determine the expressed genes that were common among groups. Functional enrichment of the DEGs was analyzed using Ingenuity Pathway Analysis (IPA) software v.9.0 (Ingenuity Systems, Redwood City, CA, USA) (24). The enriched canonical pathways were generated through the Ingenuity Systems Knowledge Base and calculated using a right-tailed Fisher's exact test. Upstream regulators were selected via IPA causal analysis. Cytoscape software iRegulon v.3.2 (www.cytoscape.org) (25) was used to select the transcription factors, as described previously (26).

The protein-protein interactions (PPIs) of the common expressed genes were analyzed using STRING software v.10 (http://string-db.org) (27). The medium confidence score (0.400) was used to select the network of PPIs of the DEGs (25 mg/kg). This score is the approximate probability that a predicted link exists between two proteins in the same Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway (www.genome.jp/kegg/) (28). The PPI network was also selected using a high confidence score (0.700) in the DEGs (50 mg/kg-treated group) due to the high number of DEGs.

The DEGs were validated by RT-qPCR analysis. The primers were purchased from Bioneer Corporation (Daejeon, Korea). Total RNA (2 µg) was reverse transcribed with SuperScript™ II (Invitrogen; Thermo Fisher Scientific, Inc.) using an oligo-dT primer according to the manufacturer's protocol. The cDNA samples were stored at −20°C until use. The RT-qPCR procedure was performed using a 20-µl reaction volume containing 2 µl (5 pM) forward- and reverse-specific primers, 10 µL of SYBR^®-Green Master mix (Applied Biosystems; Thermo Fisher Scientific, Inc.), 2 µl of cDNA and 6 µl of nuclease-free water. The cDNA was amplified using a StepOne™ and StepOnePlus™ Real-Time PCR system (Applied Biosystems; Thermo Fisher Scientific, Inc.) according to the manufacturer's protocol. The following amplification protocol was used: Denaturation program (10 min at 95°C for 10 min, 60°C for 10 sec, 72°C for 60 sec), melting curve program (60–95°C with a heating rate of 0.1 per second and a continuous fluorescence measurement) and a final cooling step to 40°C. The sequences of the primers used were as follow: DnaJ heat shock protein family (Hsp40) member B1 (Dnajb1; Hsp40), forward 5′-GTCCCTGTCAACTACTGCCT-3′ and reverse 5′-TGAGTCGAATGGTCAGAGCA′; heat shock protein (Hsp)h1, forward 5′-CCAAGATCGCAGCAGACTTC-3′ and reverse 5′-TCATCCACTCCATCACCTCG-3′; Hsp90aa1, forward 5′-GCCAGTTTGGTGTTGGTTTT-3′ and reverse 5′-ACCCATTGGTTCACCTGTGT-3′; glutathione peroxidase 2 (Gpx2) forward 5′-ATATTGTCCCCTTGCCTTCC-3′ and reverse 5′-CAGACTTAGAGCCCCCAGTG-3′; glutathione-disulfide reductase (Gsr), forward 5′-CAACATCCCTACCGTGGTCT-3′ and reverse 5′-TGAAGGCGGTCGAGTAGATT-3′; glutathione S-transferase (Gst)a3, forward 5′-GGAGGCCAACACGTTTTCTA-3′ and reverse 5′-CCAAATAGCATCCCAGCAAT-3′; Gstm2, forward 5′-CACAAGATCACCCAGAGCAA-3′ and reverse 5′-AAACGTCCACACGAATCCTC-3′; Gstt2, forward 5′-TTTTCTGGCTCCTTTTCTGG-3′ and reverse 5′-GGGTCTCCTATTGGTTGTGC-3′; superoxide dismutase 1 (Sod1), forward 5′-ATTGGCCGTACTATGGTGGT-3′ and reverse 5′-CCAATCACACCACAAGCCAA-3′; β-actin, forward 5′-GTCGTACCACTGGCATTGTG-3′ and reverse 5′-CTCTCAGCTGTGGTGGTGAA-3′. The β-actin primers were used as an internal control and fold changes in expression were calculated according to the 2−^ΔΔCq method (29).

The structure of an AOP is composed of MIEs, measurable KEs, KE relationships (KERs) and adverse outcomes (AOs). The MIE initiates toxicity through the interaction between a chemical initiator and a molecular target within cells. The KEs are initiated by the MIE and connected by KERs, which are sequentially effected from cells to tissues. Therefore, the KEs are individual cellular toxicity response pathways that connect the MIE with the AO. The KEs and the KERs were selected using pathway analysis. An AOP is basically composed of an MIE, KEs, an AO and KERs, and this framework is a modular system in which multiple AOPs share a network. The -omics data together with biochemical and histopathological results were used to build the AOP framework. Relevant data from the literature were also used to support and connect this model.

Organ weights, and the concentrations and activity levels of substrates and proteins in the serum were analyzed using one-way analysis of variance following by Dunnet's post hoc test for multiple comparison analysis. Statistical analyses were performed with SAS 9.4 (SAS institute, Cary, NC, USA; 8 replicates per group). P<0.05 indicated a statistically significant difference.

In clinical studies, it is recommended that CMS is administrated to patients at ~6.67–13.3 mg/kg/day (2.5–5 mg/kg/day colistin base activity) in 2–4 intravenous doses (5). Based on pharmacokinetics, CMS at 9 mg/kg/24 h in humans is equivalent to 30 mg/kg/12 h in the rat via jugular vein (6). A previous clinical study reported that intravenous injection of 2.5–5 mg/kg/day CMS for 14 days induced renal injury in a patient (8). An animal study showed that intraperitoneal injection of 16 mg/kg/day CMS for 15 days induced nephrotoxicity in a murine model, and that there was no significant difference in toxicity between intraperitoneal and intravenous injection (15). Therefore, the dosage and duration of CMS for the Sprague-Dawley rats were determined from preliminary studies that showed nephrotoxicity. In the present study, the dosages for inducing initial and moderate damage were selected for analysis of the initial molecular events causing nephrotoxicity. The respective doses of CMS were set to 25 and 50 mg/kg via intraperitoneal injection, and each rat was injected with a vehicle control or CMS via intra-peritoneal injection daily for 7 days. The total body weights were decreased and the relative kidney ratio was increased in the 50 mg/kg CMS-treated group, with no significant change detected in the 25 mg/kg CMS-treated group (Table I). As shown in Fig. 1, serum biochemical analysis indicated that total cholesterol, blood urea nitrogen (BUN), serum creatinine (CREA), and blood calcium were significantly increased in the 50 mg/kg CMS-treated rats. BUN and CREA are representative serum markers of nephrotoxicity, and it is known that calcium increases following kidney dysfunction. Histopathological analysis revealed that there were no significant lesions in the liver, but renal toxicity was observed in the CMS-treated rats (Table II). In the 25 mg/kg CMS-treated group, tubular basophilia and dilated tubules were observed. Renal tubular cell necrosis, tubular degeneration/dilatation and eosinophilic casts were observed in the 50 mg/kg CMS-treated group. In the 25 mg/kg CMS-treated group, calcium levels were significantly increased, although no histopathological renal toxicity was observed. In the 50 mg/kg CMS-treated group, the BUN, CREA and calcium levels were increased, and renal lesions were observed in the histopathological analyses.

Overall, severe renal injury occurred in the 50 mg/kg CMS-treated rats, and renal injury was initiated by subacute treatment of 25 mg/kg CMS. Colistin has been shown to increase serum CREA levels in previous clinical and animal studies (8,16). The biochemical and histopathological observations following CMS treatment in the present study are consistent with those of previous studies (6,11). These results suggest that nephrotoxicity was induced by CMS treatment (25 and 50 mg/kg) in the rat kidneys.

Microarray analysis of the three groups (0, 25, and 50 mg/kg CMS) revealed 358 genes and 4,126 gene probe sets as DEGs by fold-change (≥1.3, P<0.05) from each group (25 and 50 mg/kg) compared with the vehicle control. To remove false-positive genes, 27 and 886 significantly regulated genes were selected in the 25 and 50 mg/kg CMS-treated groups, respectively, following correction for multiple comparisons (FDR, P<0.05) and Tukey's HSD post hoc test. A total of 14 genes were selected as common genes in the two CMS treatment groups (Table III). Among the common genes, the expression levels of cold-inducible RNA binding protein (Cirbp), kinesin family member 18B (Kif18b), inhibin β-B (Inhbb) and bloom syndrome, RecQ helicase-like (Blm) were increased, whereas those of eukaryotic translation initiation factor 5 (Eif5), ethanolamine kinase 1 (Etnk1), calcyclin binding protein(Cacybp), arginine vasopressin receptor 1A (Avpr1a), Hsp90aa1, bone morphogenetic protein receptor, type II (Bmpr2) and Hsph1 were decreased in the two CMS-treated groups. A total of 8 probe IDs for B-cell lymphoma (Bcl-2)-associated transcription factor 1 (Bclaf1), Dnajb (Hsp40) and zinc finger protein 423 (Zfp423) were differentially expressed in the 25 mg/kg CMS-treated group only. Dnajb1 (Hsp40), Hsp90aa1 and Hsph1 are members of the Hsp family that protect the cell from proteotoxic and oxidative stress (30,31), and these were downregulated by CMS. Dnajb1 (Hsp40) interacts with Hsp70 and is induced by proteotoxic stress (32), Hsp90aa1 is expressed following proteotoxic stress and other conditions of cellular stress (32), and Hsph1 encodes heat shock 105/110 protein 1 and is induced by oxidative and proteotoxic stress (33).

The significant DEGs with the most marked changes in the 50 mg/kg CMS-treated group were selected (Table IV). Hepatitis A virus cellular receptor 1 (Havcr1), lipocalin 2 (Lcn2) and secreted phosphoprotein 1 (Spp1) are known to be representative nephrotoxicity biomarkers, and these genes showed high expression following CMS treatment. Kallikrein 1-related peptidase C4 (Klk1c4), Klk1c9 and Klk1c7 were significantly downregulated; these genes are associated with the kinin-kallikrein system, which is important for renal function (34). Gpx2 and Gsta3 were significantly upregulated and downregulated, respectively; these antioxidant genes are regulated by oxidative stress (35). These results indicated that gene sets associated with nephrotoxicity were also regulated by CMS under these experimental conditions.

In the 25 mg/kg CMS group, IPA revealed the significant canonical pathways were transforming growth factor (TGF)-β, bone morphogenetic protein (BMP) and androgen signaling. The canonical pathways of the 50 mg/kg CMS group were shown to be significant in eIF2, regulation of eIF4/p70S6K, mammalian target of rapamycin (mTOR), and aryl hydrocarbon receptor signaling, in addition to cell cycle control of chromosomal replication (Table V). The fold-changes of the top-ranked genes belonging to TGF-β and eIF2 are also represented in Table VI. The canonical pathways associated with the upregulated and downregulated genes following 50 mg/kg CMS treatment were analyzed separately (Fig. 2A and B). Specifically, canonical pathways associated with protein translation, cell cycle control and apoptosis were predicted to be activated in the upregulated genes. In the canonical analysis of the downregulated genes, there was significance in pathways associated with amino acid metabolism and oxidative stress. The expression levels of genes involved in apoptosis and the cell cycle were upregulated, whereas the expression levels of genes involved in the protective response to oxidative stress were downregulated in the 50 mg/kg CMS-treated group.

Several investigations have reported that TGF-β and BMP signaling are significantly affected by nephrotoxic compounds, including tacrolimus and cyclosporine (36,37). TGF-β acts as a key mediator in renal disease given its functions in renal inflammation, apoptosis and differentiation (38). BMPs belong to the TGF-β family, and TGF-β/BMP signaling is important in kidney development and renal cell proliferation (39). This result demonstrated that TGF-β/BMP signalling may be activated to cause proliferation of kidney cells following the initial damage caused by CMS. eIF2, regulation of eIF4 and p70S6K, and the mTOR signalling pathway were significantly altered following CMS treatment. These pathways are activated for survival and recovery from cellular stresses, including oxidative or proteotoxic stress (40,41).

PPI analysis was performed with the DEGs from each group using STRING (v.10) software (Fig. 3). With the DEGs identified in the 25 mg/kg CMS treatment group, the protein interaction analysis showed connections among Hsph1, Hsp90aa1, Dnajb1, Jun proto-oncogene (Jun), Cacybp, Bmpr2 and Inhbb with a confidence score of 0.400 (Fig. 3A). In particular, strong associations were observed among Hsph1, Hsp90 and Dnajb1 (Hsp40), and the heat shock factor 1 (Hsf1) transcription factor is known to regulate the expression of these genes. The protein interaction analysis of the DEGs of the 50 mg/kg CMS treatment group, conducted with a confidence score of 0.700, is shown in Fig. 3B. The PPI pathways were primarily grouped into ribosome, cell cycle, and apoptosis categories using KEGG pathway enrichment. The PPI analysis indicated that Hsph1, Hsp90 and Dnajb1 function as key nodes in the gene regulatory network during initial nephrotoxicity induced by 25 mg/kg CMS treatment.

To define the key regulators that trigger colistin-induced nephrotoxicity, transcriptional regulators of the DEGs following CMS treatment (25 mg/kg) were analyzed using IPA and Cytoscape software iRegulon. Hsf1 was selected as the primary gene based on the upstream and causal analysis of IPA. The IPA analysis revealed that Hsf1 regulates the expression of Hsp1, Hsp90aa1, Dnajb1 (Hsp40), Jun and Cirbp (Fig. 4A). Hsf1 is predicted to inhibit the expression of its target gene. Hsf1 was also selected as the top transcription factor in the iRegulon analysis (Fig. 4B). Collectively, Hsf1 was identified as a master transcription factor regulating gene expression in colistin-induced nephrotoxicity.

To validate the microarray data, RT-qPCR analysis was conducted (Fig. 5). Analysis of the expression of Hsf1 target genes and Nrf2-mediated oxidative stress genes by microarray and RT-qPCR analyses indicated that these methods produced similar results. The expression levels of Dnajb1, Hsph1 and Hsp90aa1 were inhibited by both doses of CMS (Fig. 5A). With 25 mg/kg CMS treatment, no significant changes were observed in the expression levels of Nrf2-mediated oxidative stress genes when analyzed by microarray and RT-qPCR analyses (data not shown). However, the expression of Nrf2-mediated oxidative stress genes were significantly altered in the 50 mg/kg CMS-treated group; these results were consistent in both analyses (Fig. 5B). The expression of Hsf1 target genes and Nrf2-mediated oxidative stress genes were confirmed by RT-qPCR analysis.

Hsf1 is a major transcriptional regulator that binds heat shock elements in the promoter of heat shock proteins (42) and triggers the activation of Hsp genes in response to environmental stresses (43). Hsf1 is critical in regulating physiological events during development and pathological conditions (43). It has been reported that nephrotoxic compounds induce the synthesis of Hsp proteins in the kidney prior to the increase in classical biochemical markers for nephrotoxicity becoming apparent (44). Cyclosporine, a nephrotoxic drug, induces a heat shock response (45) and Di (2-ethylhexyl) phthalate also induces nephrotoxicity by inhibiting the HSF-dependent heat shock response (46). In the present study, the activity of Hsf1 was predicted, and its target genes increased with CMS treatment. This finding demonstrated that Hsf1 may be a key regulator in defense against pathological lesions in the kidney through activation of the heat shock response.

A number of AOP frameworks associated with nephrotoxicity have been investigated as part of the OECD work plan (https://www.aopkb.oecd.org). Cyclooxygenase 1 and agonism of the estrogen receptor have been suggested as potential MIEs, although there is limited understanding of MIE and KE molecules. The present study suggested a putative framework for a nephrotoxicity AOP that integrates -omics data, blood biochemistry, histopathology and data from publications on colistin-induced nephrotoxicity, although further validation is necessary to build an AOP model with a sufficient weight of evidence. In the present study, serum and histological observations suggested that nephrotoxicity resulted from CMS, and key pathways and master regulatory were comprehensively analyzed based on phenotype-anchored gene expression profiles. The phenotype-anchored gene expression and observed high expression of well-known nephrotoxic biomarkers, including the Kim1 (hepatitis A virus cellular receptor 1), Lcn2, Spp1 and Klklc families, were analyzed in the group treated with 50 mg/kg CMS. The key pathways and master regulators associated with the nephrotoxicity induced by CMS were then analyzed. The gene expression of heat shock-related proteins was significantly inhibited in the low-dose group, and the inhibition of the heat shock response may be a potential MIE. In the master regulator gene analysis, it was found that Hsf1 significantly regulated the expression of those genes in the CMS-treated kidney (25 mg/kg). Proteotoxic stress is triggered by an imbalance of proteostasis, which is a biological pathway that maintains cellular homeostasis from cellular stress and is predominantly controlled by Hsf1 (47–49). To maintain proteostasis, the proteostasis network is regulated by ribosomes, chaper-ones and the proteasome (50). Chaperones, including HSPs, function to prevent protein misfolding and maintain protein homeostasis, and the transcription of these genes is regulated by HSFs (51,52).

Previous studies have shown that colistin binds to the N-domain of HSP90 and suppresses chaperone activity (53,54). Therefore, it is hypothesized that colistin binds to Hsp90 and inhibits the transcriptional activity of Hsf1. As a result, proteotoxicity is induced due to decreased protective function against stress. From these results, a potential MIE was predicted through a process in which hsp90 is bound to a drug and induces proteotoxicity.

The KEs and KERs were predicted by the canonical pathways of the DEGs and data from other publications. Based on the results of the pathway analysis, it was possible to identify KEs at the molecular level and develop the structure of the framework by linking the KERs with literature data. In the pathway analysis of the upregulated DEGs following 50 mg/kg CMS treatment, it was found that the important pathways were eIF2, regulation of eIF4/p70S6K, mTOR, apoptosis signaling, and cell cycle control. In the pathway analysis of the downregulated DEGs, the important pathways were amino acid degradation, Nrf2-mediated oxidative stress response and glutathione-mediated detoxification signaling. In addition, ribosomes, cell cycle arrest, and apoptosis pathways were selected as representative pathways in the PPI analysis.

Proteotoxic stress can be induced by the impairment of cellular function caused by protein misfolding (50). The signaling pathways associated with translation factors, including eIF2 and eIF4, are modulated for recovery from proteotoxic stress (41,55). mTOR signaling is related to responses to proteotoxic stress and is also related to HSF activation and synthesis of HSPs (40). The expression of antioxidant genes (Sod and Gpx) are downregulated by CMS, as observed in previous investigations (14). Nrf2-mediated oxidative stress signaling and glutathione signaling are known to be involved in oxidative stress, and the expression levels of these genes are downregulated by CMS treatment (56). This indicates that the antioxidant response is inhibited by colistin. Cell cycle arrest and apoptosis signaling via the mitochondrial, death receptor, and endoplasmic reticulum pathways have already been shown to be involved in colistin-induced nephrotoxicity (14,15). In the present study, genes related to p53 signaling were also significantly differentially regulated in the CMS-treated kidneys (Table VI). This suggested that these pathways are KEs of this AOP and that these KEs are related to each other.

The present study hypothesized that proteotoxic stress may occur through the suppression of HSPs and the antioxidant response. It was hypothesized that oxidative stress and ER stress are involved as KEs through the activation of eIF2 signaling and mTOR signaling. In addition, cell cycle arrest and apoptosis represents major events in cell death, and these major pathways may be elements of KEs. The binding of colistin to HSP90 inhibits chaperone activity and induces proteotoxic stress, which results in oxidative stress. ROS produced by oxidative stress induces ER stress, mitochondrial injury, cell cycle arrest and apoptosis, leading to cell death. These KEs have been confirmed in the results of previous publications (14). The AOP of renal toxicity can be explained by the biochemical and histopathological results in addition to analysis of previous literature (Fig. 6).

In the present study, a putative AOP for nephrotoxicity induced by colistin was suggested using global gene expression profiling. Omics approaches are considered suitable tools to provide information on putative AOPs. Gene expression changes can offer molecular insights regarding the initial events, but have limitations as they reflect a snapshot of a rapidly changing gene set in certain circumstances. Despite the limitations of microarray approaches, further information on MIE and KEs is required to develop the AOP networking model. However, AOPs ultimately aim to suggest qualitative or quantitative approaches to assess toxicity, and further validation is necessary to strengthen the weight of evidence for the putative AOP model.

In conclusion, gene expression analysis was performed in the present study to evaluate the mechanism of nephrotoxicity induced by colistin. It was found that the expression levels of HSF1 target genes, including Hsp90aa1, Hsph1 and Dnajb1 (Hsp40), were downregulated by colistin, and the expression levels of Nrf2-mediated oxidative stress genes were also down-regulated following treatment with a high dose of colistin. HSF1 and Nrf2 are known to be associated with protection against various forms of stress and to compensate for each other (57). Based on these results, a framework for an AOP of colistin-induced nephrotoxicity was constructed, which can facilitate an improved understanding of the mechanism of renal toxicity.