Short Chain Fatty Acids Prevent Glyoxylate-Induced Calcium Oxalate Stones by GPR43-Dependent Immunomodulatory Mechanism

Calcium oxalate (CaOx) stones are the most common type of kidney stones and are associated with high recurrence, short chain fatty acids (SCFAs), and inflammation. However, it remains uncertain whether SCFAs affect the formation of CaOx stones through immunomodulation. We first performed mass cytometry (CyTOF) and RNA sequencing on kidney immune cells with glyoxylate-induced CaOx crystals (to elucidate the landscape of the associated immune cell population) and explored the role of SCFAs in renal CaOx stone formation through immunomodulation. We identified 29 distinct immune cell subtypes in kidneys with CaOx crystals, where CX3CR1+CD24- macrophages significantly decreased and GR1+ neutrophils significantly increased. In accordance with the CyTOF data, RNA sequencing showed that most genes involved were related to monocytes and neutrophils. SCFAs reduced kidney CaOx crystals by increasing the frequency of CX3CR1+CD24- macrophages and decreasing GR1+ neutrophil infiltration in kidneys with CaOx crystals, which was dependent on the gut microbiota. GPR43 knockdown by transduction with adeno-associated virus inhibited the alleviation of crystal formation and immunomodulatory effects in the kidney, due to SCFAs. Moreover, CX3CR1+CD24- macrophages regulated GR1+ neutrophils via GPR43. Our results demonstrated a unique trilateral relationship among SCFAs, immune cells, and the kidneys during CaOx formation. These findings suggest that future immunotherapies may be used to prevent kidney stones using SCFAs.


Experimental Animal Studies
C57BL/6J mice were procured from Chengdu Dossy Experimental Animals Co., Ltd. The mice were housed in individual ventilated cages with unlimited access to sterilized food and water. The animal studies were approved by the Animal Research Ethics Committee of the West China Hospital in Sichuan University (2017105A).

Adeno-Associated Virus (AAV) Infection
To knockdown GPR43 expression in vivo, mice were transduced with an AAV serotype 9 vector encoding a green fluorescent protein reporter together with either short hairpin RNAs (shRNAs) targeting GPR43 in the kidney (AAV-shGPR43) or an empty vector (AAV-null). The shRNA sequences targeting the mouse GPR43 gene were cloned into the AAV by Shanghai GeneChem Co., Ltd. (Shanghai, China). Mice were injected with either AAV-shGPR43 or AAV-null via the tail vein (1 × 10 11 viral particles/mouse), followed by an additional 4 weeks of glyoxylate injection. The mice were randomly divided into five groups and treated with the AAV-null vector (AAV-null group), the AAV-shGPR43 vector and glyoxylate injection (AAV-shGPR43 group), the AAV-shGPR43 vector with C2 in the drinking water (AAV-shGPR43+C2 group), the AAV-shGPR43 vector with C3 in the drinking water (AAV-shGPR43+C3 group), or AAV-shGPR43 vector with C4 in the drinking water (AAV-shGPR43+C4 group).

CyTOF and Data Analysis
A panel of CyTOF antibodies combined with 42 metal isotopetagged antibodies (Supplemental Table 1, Fluidigm, San Francisco, USA) was used to detect immune cell populations in mouse kidneys. The kidneys were placed in Dulbecco's modified Eagles' medium and cut into pieces with collagenase IV (1 mg/mL; Merck, Shanghai, China) and DNase I (100 mg/ mL, Merck) at 37°C for 30 min (27). The digested kidney cells were resuspended in phosphate-buffered saline (Thermo Scientific, Shanghai, China) containing 0.02% NaN 3 and 0.5% bovine serum albumin and stained for viability with 194Pt (Fluidigm) for 5 min on ice. The cells were then blocked using Fc receptors, followed by cell-surface staining with metal-labeled monoclonal antibodies (mAbs) for 30 min. The cells were incubated overnight at 4°C with DNA Intercalator-Ir (Fluidigm) to discriminate singly nucleated cells from doublets. After fixation and permeabilization, the cells were intracellularly stained with metal-labeled mAbs for another 30 min. The cells were washed and prepared for data acquisition. The Helios system (Fluidigm Sciences) was used to acquire CyTOF data at ≤500 events/s. All CyTOF files were analyzed using FlowJo software, version 10.5.3. (TreeStar, Ashland, OR, USA). The CD45-positive populations were clustered using the X-shift algorithm (28), which automatically pools cells to identify underlying immune cell subpopulations. The normalized expression levels of markers were visualized with a heatmap. Cell frequencies were calculated by dividing the total number of CD45 + cells events by the number of assigned cell events. The R software package was used to perform dimension reduction, based on t-distributed stochastic neighbor embedding (t-SNE) (29).

RNA Sequencing and Analysis
Kidney digestion is the same as described above. Renal cells were surface-stained with fluorophore-conjugated antibodies against the mouse CD45 antigen (FITC, BioLegend, San Diego, CA, USA), then renal CD45 + cells were sorted by Flow cytometry. The RNeasy Mini Kit (Qiagen, Germany) was used to extract total RNA from renal CD45 + cells following the manufacturer's instructions. One microgram total RNA was used to prepare an RNA-seq transcriptome library using the TruSeq ™ RNA Sample Preparation Kit (Illumina, San Diego, CA). Then, complementary DNA target fragments (200-300 base pairs) were selected, followed by polymerase chain reaction-based amplification with Phusion DNA polymerase (Thermo Scientific, Shanghai, China). An Illumina HiSeq X instrument was used for sequencing.
The raw data were trimmed and qualified using the SeqPrep and Sickle tools. Then, the clean data were aligned to the reference genome using TopHat software (version 2.0.0) (30), and the mapped reads were assembled using StringTie.
Transcript expression levels were calculated using the transcripts per million reads method to identify differentially expressed genes (DEGs) between groups. The RSEM (31) and EdgeR (32) software programs were utilized to quantify gene abundances and for differential expression analysis, respectively. Furthermore, Gene Ontology (GO) functional-enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on DEGs with a Bonferroni-corrected P-value of ≤ 0.05.

Cytokine Analyses
Mouse sera were collected, and IL-1b, IL-6, and TNF-a levels were measured using enzyme-linked immunosorbent assays (Invitrogen, Shanghai, China), according to the manufacturer's recommendations.
The raw 16S rRNA sequence data were demultiplexed, quality-filtered, and merged using fastp software (version 0.20.0) (33) and FLASH software (version 1.2.7) (34). All sequences were clustered into different operational taxonomic units (OTUs) at 97% similarity using UPARSE software (version 7.1) (35) by removing the chimeric sequences. The taxonomy of the 16S rRNA amplicon sequences was analyzed using the RDP Classifier software (version 2.2) (36) against the Silva v138 database with a confidence threshold of 0.7.
Alpha diversity and coverage indices were calculated. Principal coordinates analysis (PCoA) and the Adonis test were used to evaluate beta diversity among the groups. Linear discriminant analysis effect size (LEfSe) analysis was used to identify differentially abundant bacteria among the three groups with a cutoff threshold of 3.0. KEGG metabolic pathways were predicted using the PICRUSt software package.
CD45 + F4/80 + CD11b + CX3CR1 + CD24macrophages and CD45 + CD11b + GR1 + neutrophils were sorted by flow cytometry. Macrophages (with or without GPR43-antagonist treatment for 24 h) were cocultured with neutrophils for another 24 h. GPR43 expression was detected by immunofluorescence. Using a Transwell system, macrophages were cultured in the upper chamber with or without a GPR43 antagonist for 24 h. Treated macrophages were added to another upper chamber of a 24-well plate with neutrophils, and TCMK-1 cells were treated with LPS and CaOx crystals seeded in the lower chamber for 24 h. Neutrophil migration and GPR43 expression were also observed.

Statistics
Statistical analyses were performed using SPSS. Data are shown as mean ± standard deviation (SD). All data were analyzed by oneway analysis of variance for multiple groups, and Student's t-test was applied for comparisons between two groups. Statistically significant differences are shown as *p < 0.05 or **p < 0.01.

Phenotypic Heterogeneity Within the Kidney-Resident Immune Cell Population
After 7 consecutive days of intraperitoneal glyoxylate injection, CaOx crystal deposits were found in mouse kidneys with elevated serum creatinine and urea levels (Supplemental Figure 1). To explore the immunomodulatory role of SCFAs in CaOx stones, we first studied the phenotypic diversity of immune cell populations in kidneys with CaOx crystals by analyzing CD45 + cell populations clustered with the X-shift algorithm.
Unsupervised clustering of 383,985 single CD45 + kidney cells from six samples created a detailed t-SNE map of distinct cell populations ( Figure 1A). The clusters were classified into 29 distinct immune cell types ( Figures 1A, B), based on the expression levels of lineage markers. The normalized expression of clusters is shown in a heatmap ( Figure 1C). We identified the following major cell subsets: CD4 T cells, CD8 T cells, B cells, macrophages, DCs, natural killer cells, monocytes, ILCs, and neutrophils (Supplemental Table 2).
The frequencies of each cluster are shown in Fig. 2. The frequencies of clusters 12, 15, 17, 22, and 23 in CaOx crystals were significantly lower than those in control mice ( Figure 2A). Based on lineage and functional markers, the cells of cluster 17 were defined as DCs with high CD103 expression that also expressed CD24, MHC-II, BST2, CXCR3, CD69, CCR2, and CD68 ( Figure 2B). Clusters 22 and 23 were both defined as CX3CR1 + CD24macrophage populations, where CD11c expression differentiated cluster 22 from cluster 23 ( Figure 2B). Clusters 12 and 15 expressed low levels of CD45, and their cell types could not be determined ( Figure 2B).
When analyzing the above results, we did not find a significant difference in the frequencies of T cells and B cells. We then depleted CD3 + and CD19 + cells to an unsupervised cluster using the X-shift algorithm to identify more myeloid cell subsets. We observed 27 clustered immune cell populations, composed mainly of macrophages and DCs ( Figures 3A, B). Cluster 18 (defined as neutrophils) increased significantly in mice with CaOx crystals, and cluster 20 (defined as CX3CR1 + CD24macrophages) was significantly lower in mice with CaOx crystals than in control mice ( Figures 3C, D), indicating that macrophages and neutrophils were involved in CaOx crystal formation in the kidney.

Functional and Transcriptional Features of CD45 + Cells in the Kidneys of Mice With CaOx Crystals
Bulk RNA sequencing was applied to identify the functional and transcriptional characteristics of immune kidney cells in mice with CaOx crystals. We identified 172 DEGs in mice with CaOx crystals (adjusted P < 0.05; fold-change ≥ 2 or ≤ 0.5), including 89 upregulated and 83 downregulated mRNAs ( Figure 4A). GO analyses revealed DEGs associated with responses to external stimuli, extracellular regions, and other parameters ( Figure 4B). KEGG analyses showed that the DEGs were involved in circadian rhythms, the PPAR signaling pathway, complement and coagulation cascades, retinol metabolism, porphyrin and chlorophyll metabolism, and steroid hormone biosynthesis ( Figure 4C). To further identify the functional and transcriptional features of the more significant DEGs, we analyzed DEGs with 10-fold changes in expression. Interestingly, DEGs with 10-fold expression differences were enriched for GO terms related to acute inflammatory responses, neutrophil and granulocyte migration, and interleukin-6 and interleukin-8 secretion, among others ( Figure 4D). In addition, KEGG analysis showed that DEGs with 10-fold expression differences were linked to the IL-17 and TNF signaling pathway, and cytokinecytokine receptor interactions ( Figure 4E), where most genes were associated with CXCL2, CXCL1, and IFN-g ( Figure 4E). Previous findings showed that these genes were all expressed at sites of inflammation and were related to monocytes and neutrophils (37,38). The results are in accordance with our CyTOF results, suggesting that the formation of kidney stones was associated with inflammation promoted by neutrophil migration.

SCFAs Reduced the CaOx Crystal Deposition by Regulating Immune Cell Subpopulations and Inflammation
Previously, we found that SCFAs were associated with kidney stones (18), which play an important role in immunomodulation. Thus, we next administered SCFAs to mice with renal CaOx crystals to observe the effect of SCFAs on crystal formation through immunomodulation. The results showed that C2, C3, and C4 reduced CaOx crystal deposition ( Figure 5A), with decreased secretion of serum IL-6, TNF-a, and IL-1b ( Figure 5B) and decreased expression of NLRP3 (Supplemental Figure 2).
The frequencies of CD45 + F4/80 + CD11b + CX3CR1 + CD24m a c r o p h a g e s ( C X 3 C R 1 + C D 2 4m a c r o p h a g e s ) a n d CD45 + GR1 + CD11b + neutrophils (GR1 + neutrophils) in mice with CaOx crystals were detected by flow cytometry (Supplemental Figure 3). In mice with renal CaOx crystals, CX3CR1 + CD24macrophages decreased, and GR1 + neutrophils increased significantly (Figures 6A, B). Interestingly, we found that C2 and C3 administration significantly increased the frequencies of CX3CR1 + CD24macrophages ( Figure 6C). Administration of C2, C3, and C4 decreased the frequency of GR1 + neutrophils ( Figure 6C). These results suggest that SCFAs prevent renal CaOx crystal formation through immunomodulation.   Figure 7A). PCoA at the OTU level showed that the microbiota composition of the control mice, CaOx crystal mice, and CaOx crystal mice administered with C2, C3, and C4 were different, which was confirmed by the Adonis test (p < 0.01) ( Figure 7B). At the phylum level, Firmicutes was the most common bacteria in the gut microbiota, followed by Bacteroidetes and Actinobacteria ( Figure 7C). At the genus level, we found that the abundance of Jin et al.

October 2021 | Volume 12 | Article 729382
Allobaculum was highest in mice with CaOx crystals, although the abundance decreased sharply in mice with CaOx crystals that were administered C2 and C3 (p < 0.01, Figure 7D). The abundances of Dubosiella, Candidatus, Saccharimonas, and Bifidobacterium significantly increased in mice with CaOx crystals administered C3 (p < 0.05, Figure 7D). Faecalibaculum was significantly increased in mice with CaOx crystals administered C4 ( Figure 7D). LEfSe analysis significantly different abundances (p < 0.05) for six, ten, three, six, and 18 bacterial genera in the gut microbiota of mice with CaOx crystals administered C2, C3, and C4; control mice; and CaOx crystal mice, respectively ( Figure 7E and Supplemental Table 3). The differentially abundant metabolic pathways are shown in Supplemental Table 4. PICRUSt analysis revealed that the abundance of 24 KEGG pathways differed significantly among the five groups, including those related to oxidative phosphorylation; fructose and mannose metabolism; glycerophospholipid metabolism; and valine, leucine, and isoleucine degradation (p < 0.05).
To determine whether SCFAs regulated the formation of CaOx crystals in a manner dependent on the gut microbiota, antibiotics were administered to deplete intestinal bacterial loads before SCFAs were used. Administering C2, C3, and C4 with The level of serum IL-1b, IL-6 and TNF-a. Data were shown as mean ± standard deviation. All data were analyzed by one-way ANOVA followed by Tukey's multiple comparisons test among multiple groups. Statistically signifificant was shown as *p < 0.05, **p < 0.01.
antibiotics reduced CaOx crystal deposition ( Figure 8A), without decreasing secretion of IL-6, TNF-a, and IL-1b ( Figure 8B). Interestingly, we found that administration of C2, C3, and C4 did not modulate the frequencies of CX3CR1 + CD24macrophages and GR1 + neutrophils ( Figure 9) after depletion of the intestinal bacterial load. These results suggest that SCFAs prevent renal CaOx crystal formation, although the immunomodulatory effects depend on the gut microbiota.

SCFAs Alleviated Crystal Formation and Adhesion to Kidney Cells by Regulating Immune Cells With GPR43
GPR43, known as SCFA receptors, is activated by SCFAs (39) and has been reported to be expressed on extensive types of immune cells, particularly neutrophils and monocytes (40,41).
To identify the role of GPR43 in SCFAs in regulating crystal formation through kidney immune cells, GPR43 was detected in A B C FIGURE 6 | Representative flow cytometric analysis of CD45 + F4/80 + CD11b + CX3CR1 + CD24macrophages and CD45 + GR1 + CD11b + neutrophil in CaOx crystal mice with or without administration of SCFAs. Gates were set on CD45 + cells, (A) macrophages then were gated on F4/80 + CD11b + cells followed by CX3CR1 + CD24 -, and (B) neutrophil were gated as GR1 + CD11b + in CD45 + cells. c Frequencies of CD45 + F4/80 + CD11b + CX3CR1 + CD24macrophages and CD45 + GR1 + CD11b + neutrophil in kidney with or without administration of SCFAs. (C) Frequencies of CD45 + F4/80 + CD11b + CX3CR1 + CD24macrophages and CD45 + GR1 + CD11b + neutrophil in kidney. Data were shown as mean ± standard deviation. Data were analyzed by one-way ANOVA followed by Tukey's multiple comparisons test among multiple groups. Statistically signifificant was shown as *p < 0.05. the kidneys of mice with or without SCFA administration. GPR43 expression on CX3CR1 + CD24macrophages in the kidneys of mice with CaOx crystals was lower than that in control mice ( Figure 10). C2, C3, and C4 administration increased the infiltration of CX3CR1 + CD24 -GPR43 + macrophages with GPR43 ( Figure 10). In contrast, GPR43 expression on GR1 + neutrophils in the kidney decreased after SCFA administration, compared to that in mice with CaOx crystals (Figure 11). Then, AAV carrying GPR43 shRNA was administered to mice with CaOx crystals, along with SCFAs. Renal GPR43 expression was knocked down by transduction with the AAV vector after four weeks ( Figure 12). GPR43 knockdown inhibited the alleviation of crystal formation in the kidney by SCFAs (Figure 12). We also found that GPR43 knockdown blocked the regulation of CX3CR1 + CD24macrophages and GR1 + neutrophils by SCFAs (Supplemental Figure 4).
adhesion to renal cells, but also play a role in regulating immune cells via GPR43. In addition, we found that CX3CR1 + CD24macrophages inhibited CaOx crystal adhesion to TCMK-1 cells induced by GR1 + neutrophils through GPR43 ( Figure 13). Next, we cocultured CX3CR1 + CD24macrophages and GR1 + neutrophils in a non-Transwell or a Transwell system, with or without TCMK-1 cells or CaOx crystals. CX3CR1 + CD24macrophages suppressed GPR43 expression on GR1 + neutrophils ( Figure 14A) and decreased the migration of GR1 + neutrophils ( Figure 14B). However, treating CX3CR1 + CD24macrophages with GPR43 antagonists restored GPR43 expression on neutrophils and the migration of GR1 + neutrophils ( Figure 14). The results indicate that the interaction between CX3CR1 + CD24macrophages and GR1 + neutrophils was mediated through GPR43.
In summary, we found multiple immune cell subpopulations in the kidney. We and also found that SCFAs reduced CaOx crystal formation in the kidney by decreasing the secretion of IL-1b, IL-6, and TNF-a by modulating CX3CR1 + CD24macrophages and GR1 + neutrophils in a manner that depended on the gut microbiota. Furthermore, SCFAs alleviated crystal formation and crystal adhesion in the kidney by regulating macrophages and neutrophils with GPR43. Additionally, our results revealed that CX3CR1 + CD24macrophages regulate GR1 + neutrophils through GPR43 ( Figure 15).

DISCUSSION
In this study, we first applied CyTOF and mRNA sequencing with kidney immune cells with CaOx crystals to elucidate the characteristics of immune populations in kidneys with CaOx crystals. We then explored the immunomodulatory role of SCFAs in the kidneys of mice with CaOx. Recently, several groups reported that macrophages play an important role in kidney stone disease. Sergei et al. found that macrophages removed and digested interstitial renal crystal deposits by releasing inflammatory cytokines (42). Further data shown that inflammatory macrophages (M1) were associated with stone formation and that anti-inflammatory macrophages (M2) were associated with the suppression of stone formation (42). In this study, five subsets of macrophages were identified in mouse kidneys, including SIRPa+ macrophages, CD11c+CX3CR1+ macrophages, CD11c-CX3CR1+ macrophages, and M2 and CD25+ macrophages. However, the abundances of CD11c +CX3CR1+ macrophages and CD11c-CX3CR1+ macrophages, but not M2 macrophages, were significantly reduced in kidneys with CaOx crystals. CX3CR1, a chemokine receptor for monocytes/macrophages, plays an important role in acute injury repair by regulating macrophage phagocytosis and cytokine production (43). Marelli et al. showed that macrophages expressing CX3CR1 contribute to maintaining the inflammatory response balance in the gut by secreting IL-10 (44). In this study, CX3CR1 + CD24macrophages were cocultured with TCMK-1 cells, and we found that CX3CR1 + CD24macrophages decreased the adhesion of CaOx crystals to TCMK-1 cells and inhibited CaOx crystal adhesion to TCMK-1 cells induced by neutrophils. These results suggest that CX3CR1 + CD24macrophages play an anti-inflammatory role in kidneys with CaOx crystals.
Neutrophils and neutrophil extracellular traps have been reported to be associated with calcium or cholesterol crystals and monosodium urate crystal-related diseases (45,46), but are limited in CaOx crystal disease. Makki et al. showed an increase in neutrophil infiltration in the papillae of patients with brushite versus CaOx (47). Conversely, we identified that CD45 + CD11b + GR1 + neutrophils, which aggravated crystal adhesion, were increased in the kidneys of CaOx mice. However, the mechanism of neutrophils in CaOx stone formation needs to be explored in further studies. SCFAs are metabolites resulting from gut bacteria fermentation that are composed of fatty acids with fewer than six carbons (such as acetic acid, propionic acid, and butyric acid), which account for over 90% of all SCFAs (48,49). SCFAs can regulate the functions of almost all immune cells by altering their differentiation, chemotaxis, and proliferation through SCFA receptors, including G protein-coupled receptors (48,50). GPR43, also known as free fatty acid receptor 2 (FFAR2), has been shown to be involved in immune responses and inflammation management (39). Recent data revealed that butyrate facilitates M2 macrophage polarization in vitro and in vivo (51). Nakajima et al. reported that GPR43 activation by SCFAs leads to TNF-a induction in anti-inflammatory M2 macrophages located within adipose tissue (52). Vieira et al. observed that acetate restored the responsiveness of macrophages to MSU crystals in a GPR43-dependent manner (53). Consistent with previous studies, our results demonstrated that SCFAs increased the frequency of CX3CR1 + CD24macrophages and suppressed crystal adhesion to TCMK-1 cells in a GPR43-dependent manner. However, Kamp et al. found that SCFA modulated neutrophil recruitment during inflammatory responses via GPR43, and more intravascular neutrophil rolling and adhesion was observed in GPR43-deficient mice in response to LPS (54). In this study, more GR1 + neutrophils infiltrated kidneys with CaOx crystals, but this process was inhibited by SCFAs; however, SCFAs could not modulate neutrophil FIGURE 12 | Representative images of Von Kossa staining and HE staining in kidney after administration of AAV carrying shRNA targeting GPR43. AAV-shGPR43 represent as groups of mice treated with AAV carrying shRNA targeting GPR43 and administration with SCFAs. Western Blot was used to detect GPR43 expression on protein level. Statistically significant was shown as **p < 0.01, ***p < 0.001. infiltration in GPR43 inhibitor-treated mice. These results indicate that SCFAs have an inhibitory effect on neutrophils. Consistent with the results of other studies showing that SCFAs reduced CXCR2 expression in neutrophils and CXCL-2 production by neutrophils, our current findings suggest that SCFAs exerted an inhibitory effect on neutrophils (55,56).
Neutrophils are recruited to sites of injury in response to dangerassociated molecular patterns in order to phagocytose and produce cytokines, which leads to inflammation (57,58). After neutrophils arrive at the site of injury, they can initiate neutrophil-macrophage crosstalk (59). Interestingly, we found neutrophil-macrophage crosstalk occurred via GPR43. CX3CR1 + CD24macrophages not FIGURE 13 | Adhesion of CaOx crystals on mouse renal tubular epithelial cells (TCMK-1 cells) when treated with SCFAs, macrophages, neutrophils and GPR43 antagonist. Statistically significant was shown as *p < 0.05, **p < 0.01. Macrophages were cocultured with neutrophils in non-transwell system with or without GPR43 antagonist. (B) Macrophages were cocultured with neutrophils in the upper chamber of transwell system with or without GPR43 antagonist. TCMK-1 cells were stimulated with CaOx crystals and LPS in the lower chamber of transwell system. 594 (GR1, red), and FITC (GPR43, green) fluorescence images and merged images with Hoechst staining (blue) of the same visual field are also shown. Statistically significant was shown as *p < 0.05, **p < 0.01. only regulated GPR43 expression in neutrophils, but also modulated neutrophil migration through GPR43.
In conclusion, 29 distinct immune cell types were identified in the kidneys of mice with CaOx crystals, in which CX3CR1 + CD24macrophages significantly decreased and GR1 + neutrophils significantly increased. SCFAs inhibited CaOx crystal formation in the kidney by modulating the functions of CX3CR1 + CD24macrophages and GR1 + neutrophils in a manner that depended on the microbiota and GPR43. These findings suggest that future immunotherapies may involve the use of SCFAs to prevent the formation of kidney stones.

DATA AVAILABILITY STATEMENT
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.

ETHICS STATEMENT
The animal study was reviewed and approved by the Animal Research Ethics Committee of the West China Hospital in Sichuan University.

AUTHOR CONTRIBUTIONS
XJ and ZJ conceived and designed the study, analyzed the data, and wrote the first draft of the manuscript. XC, YM, HM, and YL conducted animal experiments and collected samples. LG and LX conducted laboratory experiments. LX, SZ, and XS analyzed the data. SQ, HL, and KW participated in manuscript revision. KW designed the study and made the final draft. All authors contributed to the article and approved the submitted version.