Neutrophil Extracellular Traps Drive Kidney Stone Formation

Kidney stones, also known as urolithiasis or nephrolithiasis, are mineral deposits that form in the kidney and have four types: calcium, uric acid, struvite and cystine, which is a very common urological disease that affects approximately more than 10% of the global population [1]. Kidney stones may cause severe pain on the lower back, blood urine, fever, and chills and have afflicted mankind for centuries. Importantly, it has been noted that kidney stones are related to an increased risk of severe medical conditions such as cardiovascular disorders [2] and chronic kidney diseases [3]. The treatment for kidney stones, such as nephrolithotripsy, shockwave lithotripsy and percutaneous nephrolithotomy, has made a great progress [4]. However, it is still a serious problem to prevent the recurrence of kidney stones [5]. Therefore, a better understanding of the mechanisms underlying the formation and development of kidney stones is of great importance to the prevention and management of kidney stones.

Neutrophil extracellular traps (NETs) are networks of extracellular chromatin fibers consisting of DNA, histones, and granular proteins [6]. NETs extruded by stimulated neutrophils can entrap and kill invading microbes [7]. In addition, emerging evidence has revealed that NETs are crucial contributors to various diseases [8]. For instance, Yang et al. [9] found that NET formation was increased in the liver metastases of colon and breast cancer patients, and NETs attracted tumor cells to promote cancer metastasis through CCDC25. Nakazawa and colleagues reported that NETs exacerbated renal injury and remote organ dysfunction by releasing histones and cytokines [10]. NETs contribute to gallstone formation [11], but the involvement of NETs in kidney stones remains unknown. A previous study found that neutrophil infiltration and NETs were increased in brushite kidney stones that might promote inflammation in patients [12], suggesting its implication in kidney stones.

Neutrophil elastase (NE), a serine protease enriched in neutrophils, functions as a destructive elastase to destroy the extracellular matrix and regulate inflammation and tissue remodeling [13]. NE degrades histones after its translocation to the nucleus and promotes chromatin decondensation required for NET formation [14]. NE has been linked to inflammatory diseases and chronic kidney and lung disorders [15‒17], whereas the role of NET-associated NE in kidney stones has not been reported.

Therefore, the relationship between NETs and kidney stone formation is a mystery. Uncovering the mechanisms by which NETs are involved in kidney stones deepens the understanding of the pathogenesis of kidney stones. Here, we demonstrated that NETs were abundant in patients and rats with kidney stones, and blockade of NETs suppressed the formation and development of kidney stones. Our findings provide novel insights into kidney stone pathogenesis and suggest that targeting NETs may be beneficial to prevent and treat kidney stones.

Patients were divided into kidney stone and control groups. In the kidney stone group, 20 patients were diagnosed with kidney stones at Xiangya hospital and received percutaneous nephrolithotomy. In the control group, 20 patients suffered a trauma and received nephrectomy. Control patients did not have medical history of kidney stones, and no urinary tract stone was detected through plain radiography of the kidneys, ureters, and bladder and ultrasonography. Patients with renal failure, chronic diarrhea, urarthritis, medullary sponge kidney, renal tubular acidosis, hypercalcemia, hyperuricemia, hyperparathyroidism, hydronephrosis, urinary system infection, and cancers were excluded from this study. General characteristics of kidney stone and control patients were collected, and no significant difference was observed in general characteristics such as sex ratio and age. Peripheral blood and renal papillary tip tissues were collected from kidney stone and control patients. Blood was centrifugated at 2,000 g for 10 min at 4°C for plasma preparation. Renal tissues were fixed in 4% paraformaldehyde solution overnight and processed for paraffin embedding and sectioning at 5 µm. Patients were informed and provided written informed consent. Our study was approved by the Ethics Committee of Xiangya hospital (Approval No. 20210045).

We downloaded GSE73680 datasets including papillary tissues from kidney stone patients (n = 56) and patients without kidney stones (n = 6) and from control patients without any kidney stone from Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/) and analyzed it as previously described. Differentially expressed genes including 270 upregulated genes and 133 downregulated genes were identified using the limma package in R software, and the volcano plot of these genes was generated. Gene ontology (GO) enrichment analysis of differentially expressed genes was conducted using the clusterProfiler package in R software. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis was performed using Reactome Pathway Database. The protein-protein interaction network of differentially expressed genes was reconstructed through STRING, and top 10 hub genes, including CAV1, TGFB3, FBN1, COL4A2, COL6A1, SERPINH1, SPARC, MMP1, NID1, and FN1, were identified according to the degree score calculated by the cytoHubba plug-in.

Experimental kidney stones were established as previously described [18]. Male Sprague Dawley rats (8-10-week-old; 200–250 g) were provided by Slake Jingda Laboratory Animal Technology Company (Changsha, Hunan, China) and maintained in a specialized animal facility, which were randomly divided into various groups. In Figures 3 and 4, rats were divided into control and model groups, and rats were divided into PBS, model + PBS and model + Sivelestat (SIVE) groups in Figures 5 and 6. For model groups, to induce kidney stones, rats were administrated with 2 mL of ammonium chloride (1%) and ethylene glycol (1%) through gavage for 4 weeks. Control rats received 2 mL of drinking water. At 0 week (w), 1 w and 4 w, peripheral blood was collected, and rats were sacrificed, and the kidneys were excised for examination of superoxide dismutase (SOD) and malondialdehyde (MDA) and paraffin embedding. Animal procedures were approved by the Ethics Committee of Xiangya hospital (Approval No. 2022020236).

The level of cell-free DNA (cf-DNA) in the plasma was determined using Quant-iT™ PicoGreen™ dsDNA Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA) following the manual. Plasma levels of NE, H3Cit, and DNase I were examined using following enzyme-linked immunosorbent assay (ELISA) kits: Rat NE ELISA Kit (Cusabio, Houston, TX, USA), Human NE ELISA Kit (Cusabio), EpiQuik™ Circulating Histone H3 Citrullination ELISA Kit (Epigentek, Farmingdale, NY, USA), Rat DNase I ELISA Kit (LSBio, Seattle, WA, USA), and Human DNase I ELISA Kit (LSBio) according to the manufacturers’ recommendations.

The myeloperoxidase (MPO)-DNA complex in the plasma was quantified through ELISA as previous described [19]. Briefly, 96-well plates with high protein binding capacity (Thermo Fisher Scientific) were pre-coated with a myeloperoxidase polyclonal antibody (Thermo Fisher Scientific) at 5 µg/mL overnight at 4°C. Plates were gently washed, and 100 µL of 2% BSA/PBS solution was added for blocking. The plasma was diluted at 1:10, added into wells and incubated for 2 h. After wash, an anti-DNA HRP antibody (ZYMO RESEARCH, Irvine, CA, USA) was added at 5 µg/mL and incubated for 1 h. TMB substrate (Beyotime, Shanghai, China) was added and incubated for 10 min. The reaction was stopped, and the absorbance at 450 nm was measured.

Paraffin sections were deparaffinized in xylene, rehydrated and processed for heat-induced antigen retrieval in sodium citrate buffer (10 mm; pH 6.0) for 15 min. After natural cooling, sections were washed in water, and sections were permeabilized in 0.5% Triton X-100 solution for 15 min. Then, sections were immersed in 5% normal goat serum for 1 h and incubated with an anti-MPO antibody (1 µg/mL, Abcam, Cambridge, UK), anti-H3Cit antibody (1:20,000, Novus Biologicals, Centennial, CO, USA), or anti-NE antibody (10 µg/mL, Thermo Fisher Scientific) overnight. Subsequently, sections were washed and incubated with an Alexa Fluor 594 or 488-conjugated secondary antibody for 1 h. DAPI (Beyotime) was added to stain nuclei, and sections were mounted and imaged. Images were analyzed and H3Cit+ NE+ positive area was quantified and analyzed using Image J software.

Paraffin sections were immersed in xylene for dewaxing and rehydrated in gradient concentrations of ethanol and then in water. Subsequently, sections were immersed in hematoxylin solution (beyotime) for 5 min and rinsed in water. Sections were then successively immersed in 95% ethanol for 5 s and in eosin solution for 45 s. After dehydration, sections were cleared in xylene and mounted for observation. Kidney injury was scored: no tubular injury (0), <10% tubular injury (1), <10–25% tubular injury (2), <26–50% tubular injury (3), <51–74% tubular injury (4), and >75% tubular injury (5).

Von Kossa Stain Kit provided by Abcam was used to stain calcium deposits in paraffin sections. Paraffin sections were dewaxed and rehydrated in distilled water. Sections were immersed in 5% Silver Nitrate Solution and exposed to ultraviolet light for 45 min. After wash, sections were incubated in 5% sodium thiosulfate solution for 2 min and washed in water. Then, sections were stained in nuclear fast red solution for 5 min, washed and dehydrated. Sections were cleared and mounted for observation. The crystal deposition area (black area) was quantified using image J software. For periodic acid-Schiff (PAS) staining, after dewaxing and rehydration, slides were immersed in periodic acid solution for 10 min, washed in water and stained in Schiff’s solution for 30 min. After wash, sections were stained with Hematoxylin for 2 min, washed and applied with Bluing reagent for 30 s. Subsequently, slides were incubated with light green solution for 2 min, washed, dehydrated, cleared, and mounted for imaging. PAS stain kit was provided by Abcam. No damage, ≤10%, 11–25%, 26–45%, 46–75%, and ≥76% damage, were represented by grades 0 to 5.

Cell apoptosis in renal tissues was detected by terminal deoxynucleotidyl transferase (TdT) dUTP nick-end labeling (TUNEL) assay using TUNEL assay Kit-HRP-DAB (Abcam) following the manual. Briefly, after dewaxing and rehydration, sections were treated with proteinase K solution for 20 min and washed, and endogenous peroxidases were quenched through incubation in 3% H₂O₂ for 5 min. Sections were washed and equilibrated in TdT Equilibration Buffer for 30 min. Subsequently, TdT labeling reaction mix was applied onto sections, and sections were incubated for 90 min at room temperature. Sections were washed, and the reaction was stopped by adding stop buffer. After 5 min, sections were washed, blocked in blocking buffer and incubated in 1 × conjugate for 30 min. DAB working solution was prepared and applied to sections followed by hematoxylin staining. Five areas surrounding the injury site were randomly selected, and TUNEL-positive cells were quantified and analyzed using Image J software.

Total RNA was extracted from renal tissues using high pure RNA tissue kit (Sigma-Aldrich, St. Louis, MO, USA) following the manufacturer’s recommendation. RNA quality was examined through electrophoresis and reversely transcribed into cDNA using iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). The relative expression of CAV1, TGFB3, FBN1, COL4A2, COL6A1, SERPINH1, SPARC, MMP1, NID1, and FN1 was determined by real-time quantitative PCR. GAPDH was used as a normalization control, and the 2^−∆∆Ct method was applied for calculation. Primers are shown in Table 1.

SOD activity and MDA content were applied to determine kidney oxidative stress. Rat renal tissues were homogenized in chilled Tris/HCl (0.1 m) containing PMSF (0.1 mg/mL), β-mercaptoethanol (5 mm) and Triton X-100 (0.5%), and tissue extracts were collected after centrifugation at 12,000 g for 10 min. SOD activity and MDA content were measured using superoxide dismutase activity assay kit (Sigma-Aldrich) and lipid peroxidation (MDA) assay kit (Sigma-Aldrich) according to the manufacturer’s instructions. Plasma levels of creatinine (Cr), blood urea nitrogen (BUN), and calcium were determined with creatinine assay kit (Sigma-Aldrich), urea nitrogen (BUN) colorimetric detection kit (Thermo Fisher Scientific) and calcium assay kit (Abcam), respectively.

Experiment results were from at least three independent assays and presented as mean ± standard deviation. The unpaired t test and one-way analysis of variance were applied to analyze the variance of two and multiple groups. p < 0.05 was statistically significant.

To explore potential regulators in kidney stones, we analyzed the microarray data from GSE73680, and 403 differentially expressed genes including 270 upregulated and 133 downregulated genes were identified between renal papillary tissues with Randall’s plaque and normal papillary tissues (Fig. 1a). Moreover, GO enrichment analysis for biological process terms and KEGG pathway analysis revealed that these differentially expressed genes were tightly associated with olfactory signaling pathway, G alpha (S) signaling events, degradation of the extracellular matrix, extracellular matrix organization, signaling by GPCR, GPCR downstream signaling, ECM proteoglycans and collagen degradation (Fig. 1b, c). Furthermore, we submitted these differentially expressed genes for reconstructing protein-protein interaction network through STRING (Fig. 1d), and top 10 hub genes, including CAV1, TGFB3, FBN1, COL4A2, COL6A1, SERPINH1, SPARC, MMP1, NID1, and FN1, were identified according to the degree score calculated by the cytoHubba plug-in (Fig. 1e).

Given that the above analysis showed that the organization and degradation of the extracellular matrix were involved in kidney stones, and NE, one of the important components of NETs, functions as a destructive elastase to destroy the extracellular matrix [13], our study focused on exploring the role of NETs in kidney stones. NETs consist of NE, MPO, cf-DNA, and histones such as H3Cit, and it is the primary source of circulating cf-DNA [20]. Thus, to identify NETs, we examined levels of cf-DNA, DNase I, MPO-DNA, H3Cit, and NE in the plasma from patients with kidney stones and control patients who suffered a trauma and needed nephrectomy. Increased concentrations of cf-DNA, MPO-DNA, H3Cit, and NE and decreased DNase I level were observed in the plasma from patients with kidney stones compared to control patients (Fig. 2a–e). Moreover, renal papillary tip tissues from patients with kidney stones showed increased abundance of MPO and H3Cit (Fig. 2f). Hematoxylin and eosin (H&E) staining showed significant pathological renal changes including epithelial cell necrosis, tubular dilation, and mononuclear cell infiltration in patients with kidney stones (Fig. 2g). These results suggested that NET formation was enhanced and might be implicated in kidney stones.

To evaluate the contribution of NETs to kidney stone formation and development, we established a rat model of kidney stones via gavage administration of ethylene glycol and ammonium chloride. Obvious pathological changes such as tubular dilation and necrosis were observed in the kidneys from experimental rats (Fig. 3a). Von Kossa and TUNEL staining exhibited a significant increase of calcium deposits and cell apoptosis in the kidneys (Fig. 3b, c). In addition, experimental kidney stone rats showed decreased SOD activity and increased MDA content in kidney lysates, and levels of blood Cr, BUN and calcium were increased (Fig. 3d), indicating impaired renal function in kidney stone rats. The top 10 genes identified in Figure 1e were confirmed to be upregulated in the kidneys from kidney stone rats compared to control rats (Fig. 3e). Collectively, these observations demonstrated that the rat model of kidney stones was successfully established. Importantly, we found that levels of cf-DNA, MPO-DNA, H3Cit, and NE were raised and DNase I was reduced in the plasma as kidney stones developed in rats (Fig. 4a–e). In addition, increased abundance of H3Cit and NE revealed that NET formation was enhanced in the kidney with the development of kidney stone in rats (Fig. 4f). As kidney stones developed, tubular injury and cell apoptosis in the kidney were significantly enhanced determined by PAS and TUNEL staining (Fig. 4g, h). Thus, our findings demonstrated the increased presence of NETs in the kidney from experimental kidney stone rats.

Furthermore, NETs were suppressed in kidney stone rats via intraperitoneal injection of the NE inhibitor Sivelestat (SIVE) to evaluate whether suppression of NETs regulates kidney stone development. Rats were divided into three groups: PBS, model + PBS and model + SIVE. Elevated levels of cf-DNA, MPO-DNA, H3Cit, and NE and decreased DNase I level were reversed by SIVE administration (Fig. 5a–e). Moreover, increased expression of H3Cit and NE in the kidney from kidney stone rats were inhibited by SIVE (Fig. 5f). These data confirmed that SIVE administration suppressed NET formation in kidney stone rats. H&E staining showed that renal injury was detected in the kidney from rats in the model + PBS group compared to the PBS group, and SIVE obviously reduced renal injury (Fig. 6a). Besides, increased calcium deposits, apoptotic cells, and tubular injury in kidney stone rats were ameliorated by SIVE administration (Fig. 6b–d). SIVE also raised SOD activity and reduced levels of MDA, Cr, BUN, and calcium in kidney stone rats (Fig. 6e), thus improving renal function. In conclusion, suppression of NETs via SIVE could repress the progression of kidney stones.

As a common urinary system disorder, kidney stones severely impact patients’ health and living quality globally. Kidney stones may lead to severe pain, renal infection, impaired kidney function and hydronephrosis [21, 22], and kidney stone-caused colic is a frequent medical emergency that brings a great burden to the emergency department [23]. The prevalence of kidney stones is steadily growing worldwide, for instance, from 5.95% to 10.63% in the past 30 years in mainland China [24]. Thanks to the development of modern therapies, kidney stones can be treated effectively. Unfortunately, its recurrence rate is extremely high. Almost half of patients relapse in 5–10 years, and the relapse rate in 20 years is approximately 75% [25]. No effective medications are available to prevent its recurrence. Kidney stones are one of the oldest disorders known to medicine, but the mechanisms underlying the formation and development of stones remain largely unknown, even though various factors such as uric acid, renal tubular cell injury and apoptosis, oxidative stress and macromolecules have been found to be important contributors in multiple processes of kidney stone formation [1]. In addition, NETs may induce oxidative stress [26, 27], which may in turn lead to accumulation of extracellular matrix proteins [28], suggesting the implication of oxidative stress in kidney stones. Thus, further exploration of the pathogenesis of renal stone formation is vital for the development of novel management and prevention approaches. In the present study, we discovered NETs as a novel mechanism contributing to kidney stones. Specially, we confirmed elevated NET formation in patients with kidney stones, and blockade of NETs restrained experimental kidney stone formation and development in rats, providing the evidence that targeting NETs might be a potential approach for preventing and treating kidney stones.

NETs were firstly uncovered as a mesh-like structure released by hyperactivated neutrophils capable of engulfing and killing invading bacteria in 2004 [7]. Subsequent studies further demonstrated NETs as a key contributor to host defense [29]. Bianchi et al. [30] reported that a specific gene therapy for patients with chronic granulomatous disease endowed antifungal activity and controlled aspergillosis via rebuilding NET formation [30]. On the other hand, emerging evidence has demonstrated that aberrant NETs also show deleterious activities in various pathological conditions. NETs contribute to thrombosis by providing a scaffold and stimulus, linking inflammation and thrombosis [31]. Wong and colleagues found that diabetes enhanced NET formation, and subsequently NETs impaired wound healing in diabetes [32]. In addition, NETs may facilitate tumor metastasis, growth and progression [33]. Moreover, NETs are implicated in various kidney diseases such as lupus nephritis and acute kidney injury [34]. However, its roles in kidney stones have not been reported. Here, we observed increased NET formation in patients with kidney stones and experimental renal stone rats, suggesting a linkage between NETs and the formation and development of kidney stones.

Targeting NETs have shown great potential in treatment of diseases. For instance, suppression of NETs through thrombomodulin could prevent liver metastasis in pancreatic cancer [35]. Adrover et al. [36] discovered that disulfiram mitigated acute lung injury and protected SARS-CoV-2 infection by inhibiting the formation of NETs in rodents. SIVE administration could ameliorate lung damage and endotoxic shock and prevent malaria-related acute lung injury in mice by suppressing NET formation [37, 38]. Therefore, we treated kidney stone rats with SIVE and confirmed that administration of SIVE effectively reduced NET markers, suggesting that SIVE could repress the formation of NETs in rats. Importantly, we demonstrated that blockade of NETs reduced CaOx crystal deposition, apoptotic cells and tubular injury and improved kidney function. Collectively, SIVE-mediated suppression of NETs repressed kidney stones, suggesting that SIVE might be used as an inhibitor of NET for the prevention and treatment of kidney stones.

In summary, we demonstrated that NETs were associated with the processes of kidney stone formation and identified NETs as a vital regulator contributing to the progression of kidney stones. Suppression of NETs via SIVE administration could significantly alleviate kidney stones in rats. Hence, NETs may potentially serve as a therapeutic target, and NET inhibitors such as SIVE and disulfiram may be used for the management of kidney stones. However, the mechanisms by which blockade of NETs restrains kidney stone formation need to be uncovered in future studies.

Patients were informed and provided written informed consent. Our study was approved by the Ethics Committee of Xiangya hospital (Approval No. 20210045). Animal procedures were approved by the Ethics Committee of Xiangya hospital (Approval No. 2022020236).

The authors declare that there is no competing interest.

This study was supported by National Natural Science Foundation of China (No.82200854).

Guarantor of integrity of the entire study: X.B.Z.; study design: X.B.Z., Z.M.Y., X.C., and J.G.; literature research: G.N.Q. and X.C.; experimental studies: Z.M.Y., X.B.Z., G.N.Q., X.C., and Z.L.; data analysis and manuscript review: Z.M.Y. and X.B.Z.; statistical analysis: Z.M.Y.; manuscript editing: Z.M.Y. All authors have read and agreed to the published version of the manuscript.

The datasets used or analyzed during this study can be made available from the corresponding author upon reasonable request. The data that support the findings of this study are not publicly available due to their containing information that could compromise the privacy of research participants but are available from X.B.Z.