IL-34 ameliorates MASLD by regulating the synthesis of gut microbiota-derived metabolites LPS and IMP

IL-34 ameliorates MASLD by regulating the synthesis of gut microbiota-derived metabolites LPS and IMP | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article IL-34 ameliorates MASLD by regulating the synthesis of gut microbiota-derived metabolites LPS and IMP Yicun Liu, Linling Ju, Lingling Shi, Lixian Wei, Jingjing Wang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8820945/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Previous studies have established that metabolic dysfunction-associated steatotic liver disease (MASLD) disrupts the intestinal barrier, allowing harmful microbial metabolites such as lipopolysaccharide (LPS) to translocate to the liver via the gut-liver axis and accelerate disease progression. While the conventional view holds that IL-34 plays a pro-inflammatory role in various diseases, our findings using IL-34 knockout mice under a high-fat diet (HFD) challenge this assumption, Contrary to expectations, IL-34 deficiency exacerbated both hepatic lipid accumulation and intestinal barrier damage compared to wild-type controls. Furthermore, IL-34 knockout led to a significant reduction in gut microbial diversity and an altered ratio of detrimental to beneficial bacterial populations. Notably, antibiotic intervention ameliorated the aggravated MASLD phenotype in IL-34-deficient mice, a protective effect not observed with macrophage depletion. Metabolomic analysis of portal vein serum revealed a significant increase in imidazole propionate (IMP), a microbiota-derived metabolite, following IL-34 ablation. Functional assays demonstrated that IMP directly promotes free fatty acid-induced lipid accumulation in AML12 and HepG2 hepatocyte cell lines. To our knowledge, this study is the first to elucidate that elevated serum IL-34 plays a protective role in MASLD by modulating the gut microbiota and preserving intestinal barrier integrity, thereby limiting the portal influx of deleterious gut microbial metabolites such as IMP and LPS. These findings uncover a previously unrecognized mechanism by which IL-34 regulates MASLD progression through the gut microbial metabolic network, highlighting its potential as a therapeutic target for metabolic liver diseases. Interleukin-34 MASLD Gut-liver axis Imidazole propionate Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Metabolic dysfunction-associated steatotic liver disease (MASLD) is a long-lasting liver condition caused by excessive fat building up in the liver. As the most prevalent chronic liver disease worldwide [ 1 , 2 ] , MASLD affects approximately 34% of the global population [ 2 ] . MASLD is not only highly prevalent in adults but also increasingly common among children and adolescents [ 3 , 4 ] . The pathogenesis of MASLD is multifactorial, encompassing hepatic steatosis, insulin resistance, oxidative stress, hepatocyte injury, and immune-mediated inflammatory responses. However, its precise pathophysiological mechanisms remain incompletely defined [ 5 , 6 ] . Current diagnostic tools of MASLD lack sufficient sensitivity for early-stage detection, while liver biopsy remains the gold standard, it is invasive and carries clinical limitations. In addition, specific therapeutic options for MASLD remain limited, primarily relying on lifestyle interventions and management of underlying comorbidities [ 7 ] . However, poor patient adherence poses a major constraint on long-term prognosis. Consequently, in-depth research into it underlying mechanisms is crucial for developing effective intervention strategies and improving patient outcomes. The gut-liver axis plays a critical role in the pathogenesis of inflammatory liver diseases [ 8 ] . This bidirectional communication system comprises several key components, including the gut microbiota, intestinal barrier integrity, microbial metabolites, and host-immune regulation, that collectively modulate hepatic metabolism, inflammatory cascades, and fibrogenesis [ 9 , 10 ] . It is well established that MASLD can disrupt gut microbiota by increasing the abundance of γ-proteobacteria, which further contributes to intestinal barrier disruption, increased intestinal permeability, and subsequent systemic inflammation. The compromised barrier function facilitates the translocation of gut-derived lipopolysaccharide (LPS) to the liver via the portal circulation. Once in the liver, Gut-derived LPS activates pro-inflammatory signaling pathways, triggering hepatic inflammation and exacerbating disease progression of MASLD [ 11 ] . Therefore, targeting the gut-liver axis represents a promising therapeutic strategy to prevent MASLD onset and halt its progression, providing various potential interventions [ 12 ] . Recently, through an epigenomic analysis of the methionine-choline deficient (MCD)-induced mouse model, Zeng et al. identified IL-34 as a potential regulator in the lipid metabolism and immune-inflammatory pathways in MASLD [ 13 ] . Shoji H and colleagues were the first to report elevated serum IL-34 levels in patients with MASLD [ 14 ] . IL-34 is a pleiotropic cytokine secreted by various cell populations, including macrophages, fibroblasts, and epithelial cells, and exerts its biological functions primarily by binding to the colony-stimulating factor-1 receptor (CSF-1R), thereby playing key roles in regulating inflammation, tissue repair, and immune responses [ 12 , 15 , 16 ] . Emerging evidence also suggests the involvement of other receptors, such as protein-tyrosine phosphatase zeta (PTPζ), CD138 (Syndecan-1), and the triggering receptor expressed on myeloid cells 2 (TREM2) in IL-34 signaling [ 17 ] . Notably, new evidence indicates a potential bidirectional link between IL-34 expression and the composition of the gut microbiota [ 18 , 19 ] . These findings highlight the emerging role of IL-34 in MASLD pathogenesis, providing fresh perspectives on disease mechanisms and potential treatments. We initially validated the previously reported serum findings of Shoji H et al. at both the mRNA and protein levels in liver tissues from MASLD patients, confirming significantly elevated IL-34 expression. Intriguingly, our results revealed that the elevated IL-34 is not a pathogenic factor in MASLD. Contrary to expectations, IL-34 knockout did not alleviate hepatic steatosis but instead exacerbated hepatic lipid accumulation in a HFD-induced mouse model. Concurrently, IL-34 deficiency was associated with impaired intestinal barrier function and dysbiosis of the gut microbiota. Crucially, subsequent antibiotic intervention effectively rescued the aggravated MASLD phenotype induced by IL-34 deficiency. Furthermore, we observed significantly increased levels of detrimental gut microbial metabolites, specifically LPS and imidazole propionate (IMP), in portal vein serum. In summary, our study establishes IL-34 as a pivotal protective regulator that mitigates MASLD progression through modulation of the microbiota-metabolite axis, highlighting its potential as a therapeutic target. Materials and methods Collection and Storage of Liver Specimens The study included a total of 6 healthy individuals and 5 patients with MASLD. Liver tissue samples were obtained from patients who underwent liver biopsies at the Third People's Hospital of Nantong University. After separation from the human body, the samples were immediately frozen in liquid nitrogen and stored at -80°C until use. This study was approved by the Ethics Committee of the Third People's Hospital of Nantong, and informed consent was obtained from each participant. High-fat diet (HFD) mouse model A total of 10 male C57BL/6 wild-type (WT) and IL-34 knockout (IL-34 −/− ) mice, aged 6 weeks, were randomly divided into WT/IL-34 −/− group and WT/IL-34 −/− + HFD group. The WT/IL-34 −/− group was fed a regular diet, while the WT/IL-34 −/− + HFD group was fed a high-fat diet (Research Diet, USA). Mice were weighed weekly, and after 12 weeks, they were sacrificed to collect peripheral blood, liver, and intestinal tissues for subsequent experiments. Body Weight Index (BWI) = (Weight Gain / Baseline Weight) × 100%, Liver Index = (Liver Weight / Body Weight) × 100%, Fatty Index = (Fat Weight / Body Weight) × 100% Antibiotic mouse model At the start of the HFD modeling, the antibiotic (BIO) group was provided with a mixture of four non-absorbable broad-spectrum antibiotics in their drinking water (1g/L ampicillin, 160 mg/L gentamicin, 1g/L metronidazole and 1g/L vancomycin), while the control group received distilled water. Mice were sacrificed after 12 weeks/4 weeks. Serum transaminase assay Mouse peripheral blood, centrifuge at 4°C, 8000 rpm for 10 minutes, then collect the supernatant (stored at -80°C). Perform the transaminase assay on a biochemical analyzer according to the instructions of the transaminase reagent kit (Nanjing Jiancheng Bioengineering Institute, Nanjing, China). Blood glucose and glucose tolerance test After fasting for 12h, mice were intraperitoneally injected with 20% high glucose (1.5ml/kg). Blood samples were collected at 0 min, 30 min, 60 min, 90 min, and 120 min to measure blood glucose levels, and the area under the insulin curve (AUC) was calculated to assess insulin resistance and glucose tolerance. The AUC calculation formulas are as follows: AUC1 = (BG0 min + 2 * BG15 min + BG30 min) * 7.5, AUC2 = (BG30 min + 2 * BG60 min + BG90 min) * 7, AUC = AUC1 + AUC2. Oil Red O staining Fresh frozen liver tissue was prepared into 8 µm thick sections. The sections were stained with Oil Red O in the dark for 30 minutes, followed by dehydration with 60% isopropanol. Hematoxylin counterstaining was done for 20–30 seconds, and the sections were rinsed with running water for 10 minutes. Observation and photography were performed under a microscope, with at least 5 fields of view taken for each slide. Hematoxylin & Eosin Staining (H&E) After fixation in formalin solution, mouse liver tissue was embedded in paraffin and sliced into 4µm sections. The paraffin sections were dewaxed, hydrated, and subjected to antigen retrieval. They were then stained with hematoxylin for 2 minutes, followed by rinsing and decolorization with 95% ethanol, and counterstained with 0.5% eosin for 2 minutes. After applying 1–2 drops of resin for mounting, the slides were observed under a microscope, and images were captured. Liver pathological sections were evaluated according to the MASLD Activity Score (NAS) established by the American Association for the Study of Liver Diseases in 2005. NAS > 4 indicates a diagnosis of MASLD, while a NAS 33%, MASLD can be confirmed; if steatosis is < 33%, it is classified as hepatic steatosis. Immunohistochemical Staining After deparaffinization, hydration, and antigen retrieval of the paraffin sections, the slides were incubated overnight in a humid chamber at 4°C with the primary antibody dilution. Following PBS washes, a secondary antibody dilution was added, and the slides were incubated at room temperature for 30 minutes. DAB chromogenic solution (Tongling Biomedicine Technology Co., Ltd., Xiamen, China) was prepared according to the manufacturer's instructions, and 100µL of the chromogenic solution was applied to the slides, adjusting for optimal staining time. Finally, after staining with hematoxylin for 30 seconds, the slides were mounted, and all tissue sections were assessed blindly under an optical microscope. Total Cholesterol, Triglycerides, and Non-Esterified Fatty Acids Measurement For mouse liver tissue, add a homogenization medium (for high-fat samples, use anhydrous ethanol for extraction; for non-high-fat samples, use phosphate-buffered saline (0.1 mol/L, pH 7.4) or saline for extraction). After mechanical homogenization, take the supernatant for measurement. Follow the instructions of the total cholesterol (TC), triglycerides (TG), and non-esterified fatty acids (NEFA) test kits provided by Nanjing Jiancheng Bioengineering Institute for detection. The calculation formulas are as follows: TC content in tissue (mmol/g protein) = (Sample OD value - blank OD value) / (Calibration OD value - blank OD value) * Calibration concentration (5.17 mmol/L) / Sample protein concentration (g protein/L). TG content in tissue (mmol/g protein) = (Sample OD value - blank OD value) / (Calibration OD value - blank OD value) * Calibration concentration (2.26 mmol/L) / Sample protein concentration (g protein/L). NEFA content in tissue (µmol/g protein) = (Measured sample OD value - blank tube OD value) / (Standard tube OD value - blank tube OD value) * Standard concentration (1000 µmol/L) / Sample protein concentration (g protein/L). Assessment of Intestinal Mucosal Permeability using the FITC-Dextran Method C57BL/6 (n = 7) and IL-34 −/− (n = 5) mice were fasted for 8 h and then orally administered 0.2 mL of fluorescein isothiocyanate–labeled dextran (FITC-dextran; 60 mg/100 g body weight; Sigma, Germany). After 4 h, the mice were euthanized, and serum samples were collected. Fluorescence intensity was measured using a fluorescence spectrophotometer (excitation wavelength: 480 nm; emission wavelength: 520 nm). The serum FITC-dextran concentration was calculated by extrapolating the fluorescence values to a standard curve of FITC-dextran. 16S rRNA Sequencing of Fecal Samples and Untargeted Metabolomics of Portal Vein Serum Fecal samples from C57BL/6 (n = 6) and IL-34 −/− (n = 6) mice were subjected to 16S rRNA sequencing, and untargeted metabolomics analysis was performed on portal vein serum samples. These analyses were conducted by AZENTA Life Sciences (Suzhou, China). RNA extraction and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) Total RNA from human and mouse liver was extracted using TRIzol® Reagent (Thermo Fisher Scientific, Shanghai, China). Following the instructions of the PrimeScript RT Master Mix (Takara, Japan), the RNA was reverse transcribed into cDNA. Subsequently, gene amplification was performed using TB Green Premix Ex Taq II (Takara). Finally, detection was carried out on a CFX Connect real-time PCR instrument (BIO-RAD, USA). Western Blot Tissue samples were ground and suspended in an appropriate amount of RIPA lysis buffer (Jiangsu Biyuntian Company, Jiangsu, China) for cell lysis. The supernatant was collected and stored at -80°C for future use. The protein concentration was adjusted to an appropriate level (20–50 µg per well). The samples were mixed with loading buffer and boiled for 5 minutes to denature the proteins. The samples were loaded onto SDS-PAGE gels (typically 10–15% polyacrylamide gel) and subjected to electrophoresis at 120V for protein separation. After electrophoresis, the gel was transferred to a nitrocellulose membrane at 100V for 1 hour to transfer the proteins from the gel to the membrane. Blocking was performed using blocking buffer from Biyuntian Company, incubating at room temperature for 1 hour. The primary antibody was diluted according to the manufacturer's instructions (Kang Cheng Biotechnology Company, Shanghai, China) and incubated overnight at 4°C. After washing the membrane three times, an appropriate dilution of the secondary antibody (Kang Cheng Biotechnology Company) was added, and incubation was performed at room temperature for 1 hour. Following the wash steps, an adequate amount of ECL developing solution was added, and imaging was performed using the Tenen Chemical Imaging System (Shanghai, China). Cell Lines and Culture Conditions The human colorectal cancer cell line Caco-2, hepatocellular carcinoma cell line HepG2, and human/mouse hepatocyte cell line AML12 were purchased from the Stem Cell Bank of the Chinese Academy of Sciences (Shanghai, China). All cells were cultured in a humidified incubator at 37°C with 5% CO₂ (model CO2-311, Thermo Fisher Scientific). MEM medium (Gibco, Waltham, USA) and DMEM/12 (Zhongqiao Xinzhou, Shanghai, China) were used for culturing human Caco-2/HepG2 cells and murine AML12 cells, respectively. Free Fatty Acid (FFA) Solution Preparation and Cell Modeling A free fatty acids (FFAs) solution was prepared by mixing oleic acid (OA; Sigma, Germany) and palmitic acid (PA; Sigma, Germany) at a molar ratio of 2:1 (0.5 mM OA : 0.25 mM PA). The mixture was thoroughly blended at 60°C and then combined with an equal volume of 10% BSA (Leagene Biotechnology, Beijing, China) to form the FFAs working solution. When HepG2 and AML12 cells reached 70–80% confluence, they were first treated with Imidazole propionate (IMP; Sigma, Germany). One hour after IMP administration, the cells were co-stimulated with the FFAs solution for 24 hours. When Caco-2 cells reached 70–80% confluence, they were treated with varying concentrations of exogenous IL-34 (MedChemExpress, Shanghai, China), CSF-1 (MedChemExpress, Shanghai, China), GW2580 (MedChemExpress, Shanghai, China), or SCH772984 (MedChemExpress, Shanghai, China). Cells were subsequently harvested at different time points. Cells Oil Red O Staining After 24 hours of FFAs stimulation, HepG2 and AML12 cells were washed with PBS and fixed with 1 mL of cell fixation solution. The cells were then stained with Oil Red O (Sigma, Germany) in the dark for 12 minutes, followed by destaining with 60% isopropanol for 5 minutes. Finally, the cells were counterstained with hematoxylin (Beyotime Biotechnology, Jiangsu, China) for 2 minutes. The area of Oil Red O staining was quantified from five random fields of view using an inverted light microscope (Olympus, Japan). Isolation of Intestinal Crypts and Organoid Culture Intestinal crypts were isolated from the mouse small intestine as previously described with minor modifications [ 20 ] . Briefly, the IL-34 −/− /WT mice small intestine was dissected, opened longitudinally, and washed thoroughly in cold phosphate-buffered saline (PBS) to remove intestinal contents. The tissue was then fragmented and incubated in 2 mM EDTA in PBS for 30 minutes on ice with gentle agitation. Crypts were released by vigorous shaking in PBS. The suspension was filtered through a 70-µm cell strainer to remove debris and large villus fragments. The crypts were collected by centrifugation at 150×g for 5 minutes at 4°C. The isolated crypts were resuspended in reduced-growth-factor Matrigel (KeyGEN BioTECH, USA) and plated as 20µL droplets in the center of a pre-warmed 24-well plate. The plate was inverted and incubated at 37°C for 15 minutes to allow the Matrigel to polymerize. Each well was then overlaid with 500µL of complete Intestinal Organoid Growth Medium. The organoid culture medium was changed every 2–3 days. Statistical analysis This study used SPSS 26.0 and GraphPad Prism 9.0 software for data analysis and statistical result visualization. Chi-square tests were employed for correlation analysis, while independent samples t-tests were used for intergroup difference analysis. In cases of non-normal distribution, non-parametric rank-sum tests were applied. All statistical results were considered significant at P < 0.05. Results Upregulation of IL-34 Expression in MASLD We collected liver biopsy samples from 5 patients with MASLD and 6 healthy controls (HC). H&E staining was performed on all liver biopsy specimens to validate hepatic steatosis in MASLD patients (Fig. 1 A). The expression of IL-34 in these tissues was then evaluated using qPCR and the results demonstrated significantly elevated IL-34 mRNA levels in liver tissues of MASLD patients compared to HCs (Fig. 1 B). To validate this finding at the protein level, we obtained additional liver biopsy specimens from 10 HCs and 21 MASLD patients for immunohistochemical (IHC) staining analysis. Under 200× and 400× magnification, marked increases in brown-stained areas, indicative of IL-34 expression, were observed in liver tissues from the MASLD group (Fig. 1 C, left). Semi-quantitative scoring confirmed significantly higher IL-34 protein levels in MASLD patient livers (Fig. 1 C, right). To further corroborate IL-34 upregulation in MASLD, we established a high-fat diet (HFD) mouse model by feeding C57BL/6 mice with a diet containing 60% of calories from fat for 12 weeks (Fig. 1 D). Compared to the control mice (n = 5), HFD-fed mice (n = 10) exhibited significantly greater body weight gain (Fig. 1 E). The effectiveness of the HFD-induced model was further confirmed by H&E staining, which showed extensive lipid accumulation in hepatocytes (Fig. 1 F). Following successful establishment of the HFD model, we assessed IL-34 expression in mouse liver tissues using qPCR (Fig. 1 G) and IHC staining (Fig. 1 H). To verify changes in IL-34 protein levels in HFD mouse livers, we performed Western blot analysis, which demonstrated a significant upregulation of IL-34 in the livers of HFD mice compared with the controls (Fig. 1 I). IL-34 Deficiency Exacerbates High-Fat Diet-Induced Hepatic fat accumulation in MASLD through Lipid Metabolic Dysregulation Given the significant upregulation of IL-34 in both serum [ 14 ] and liver tissues of MASLD subjects, we generated IL-34 knockout mice to investigate its biological role in the development and progression of MASLD. C57BL/6 wild-type (WT) and IL-34 knockout (IL-34 −/− ) mice were fed with a 60% high-fat diet (HFD) for 12 weeks to establish an HFD-induced MALSD model (Fig. 2 A). Compared to the WT group, IL-34 −/− HFD mice exhibited increased body size (Fig. 2 B), accelerated weight gain (Fig. 2 C), and a higher liver index (Fig. 2 D&E). To further explore the effects of IL-34 −/− on liver function and lipid metabolism, we measured serum triglycerides (TG), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) levels. The results showed that IL-34 knockout led to higher serum TG levels (Fig. 2 F) and elevated liver transaminase levels (Fig. 2 G&H) in HFD mice. Histological analysis using H&E (Fig. 2 I-J) and Oil Red O (Fig. 2 K-L) staining revealed markedly enhanced hepatic lipid accumulation in IL-34 −/− mice compared to WT controls. To investigate the role of IL-34 in adipose tissue pathology, we collected and weighed visceral fat from both groups of mice. The results indicated that IL-34 −/− mice had increased visceral fat accumulation (Fig. 2 M). H&E staining of adipose tissue demonstrated enlarged adipocyte size in IL-34 −/− mice relative to controls (Fig. 2 N&O). Further metabolic characterization demonstrated that IL-34 deficiency significantly disrupted systemic energy metabolism. Glucose metabolism tests showed pronounced glucose intolerance (Fig. 2 P&Q), and insulin resistance (Fig. 2 R&S) in IL-34 −/− +HFD mice. IL-34 enhances intestinal mucosal barrier function by promoting the expression of tight junction proteins First, we cultured colonic organoids from IL-34 −/− and WT mice respectively and found that IL-34 knockout slowed the proliferation of colonic cells and reduced the budding rate in mice (Fig. 3 A). To assess intestinal permeability, serum FITC-dextran concentration was measured following oral administration. We found that IL-34 knockout mice exhibited significantly increased intestinal permeability compared to controls (Fig. 3 B). Serum LPS levels were also elevated in IL-34 knockout mice, with a pronounced increase in serum subjected to HFD modeling (Fig. 3 C), indicating exacerbated endotoxemia. Using the HFD animal model, we observed that compared with the control group, IL-34 deficiency aggravated the HFD-induced intestinal pathological changes in mice, including increased mucosal thickness and inflammatory cell infiltration (Fig. 3 D). Given that IL-34 deficiency alters intestinal mucosal permeability in mice, we validated the expression of intestinal tight junction proteins, ZO-1 and Occludin, using qPCR and immunohistochemistry. Both analyses demonstrated that both IL-34 knockout and HFD independently led to decreased expression of intestinal tight junction proteins, and their combination resulted in an additive suppression (Fig. 3 E-H). Additionally, we examined the expression of four IL-34 receptors in intestinal tissues following HFD treatment through immunohistochemical staining and found that the expression of CSF-1 was downregulated in IL-34 knockout mice, whereas other three receptors remained unaffected. Upon HFD treatment, CSF-1R levels were significantly reduced in intestinal tissues of WT mice. However, in IL-34 knockout mice, HFD did not further suppress CSF-1R expression. These results suggest a role for IL-34 in maintaining CSF-1R expression, potentially contributing to the regulation of IL-34-mediated downstream biological processes (Supplementary Fig. S2). In vitro studies using human NCM460 colonic epithelial cells demonstrated that treatment with recombinant IL-34, but not CSF-1, dose-dependently upregulated the expression of ZO-1 and Occludin (Fig. 3 I-K). Mechanistic investigations revealed that pharmacological inhibition of ERK signaling with SCH772984 significantly attenuated IL-34-mediated upregulation of these proteins (Fig. 3 L). However, the addition of the CSF-1R inhibitor GW2580 did not affect the action of IL-34 on tight junction proteins.These findings provide compelling evidence that IL-34 enhances intestinal epithelial barrier function through activation of the ERK signaling axis, leading to increased expression of tight junction proteins ZO-1 and Occludin. IL-34 may impact energy metabolism through modulation of the gut microbiota Since IL-34 can improve intestinal mucosal permeability, we further investigated its effect on the gut microbial community in mice using 16S ribosomal RNA gene-based amplicon sequencing. The unweighted UniFrac heatmap, where color intensity reflects the degree of dissimilarity between sample pairs, with lighter colors indicating lower dissimilarity, revealed minimal variation within both WT and IL-34 −/− groups (Fig. 4 A). Principal Coordinate Analysis (PCoA), in which shorter distances between samples represents greater similarity in microbial communities, indicated that the microbial community structures of the two groups were largely similar (Fig. 4 B). However, rarefaction curves (Fig. 4 C) and OTU-based Venn diagram (Fig. 4 D) showed that after IL-34 knockout, the richness of the gut microbiota in mice decreased compared to the control group. Further analysis using the Chao1 index (commonly used in ecology to estimate richness of species; where higher Chao1 index indicates greater number of OTUs) and Shannon index (commonly used to estimate microbial diversity in a sample; a higher Shannon index indicates higher community diversity) revealed that both the species richness (Fig. 4 E) and diversity (Fig. 4 F) of the gut microbiota were significantly reduced in IL-34 knockout mice. Furthermore, Linear Discriminant Analysis Effect Size (LEfSe) results identified Sutterellaceae, Burkholderiales, and Gammaproteobacteria as the most differentially enriched microbial taxa in the IL-34 −/− group, whereas In the WT group, the top taxa were Oscillospirales, Akkermansia, and Eubacterium_coprostanoligenes_group were enriched in the WT group, indicating distinct microbial profiles between the two groups (Fig. 4 G). Figures 4 H and 4 I present bar charts at the species level for each sample. The top five taxa exhibiting the greatest differential abundance between the two groups were Coriobacteriaceae_UCG-002, Rikenella, Parasutterella, Ruminiclostridium, and Muribaculum. Among these, Coriobacteriaceae_UCG-002 and Rikenella were significantly enriched in IL-34 −/− mice compared to the control group, while Parasutterella, Ruminiclostridium, and Muribaculum were markedly reduced. To explore functional implications, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed on the differentially abundant taxa. The top ten most significantly altered pathways are shown in Fig. 4 J. The enriched pathways were primarily related to energy metabolism, including the TCA cycle and glucose degradation, purine and pyrimidine ribonucleotide synthesis and degradation, tRNA processing, LPS metabolism-related pathways such as the superpathway of UDP-glucose-derived O-antigen building block biosynthesis, and biosynthesis pathways for key cofactors such as tetrahydrofolate, pyridoxal 5'-phosphate, and heme. Compared to controls, the IL-34 −/− group exhibited a decrease in the energy metabolism-related pathways, particularly the TCA cycle, alongside a significant increase in LPS metabolism-related pathways. Antibiotic-Mediated Gut Microbiota Modulation Reverses IL-34 Deficiency-Induced Liver Injury in MASLD Mice Based on our findings above, which demonstrate that IL-34 regulates the gut microbiota and that IL-34 knockout exacerbates hepatic steatosis in HFD-fed mice, we administered broad-spectrum antibiotics in the drinking water to the experimental group following HFD modeling (Fig. 5 A). This intervention aimed to determine whether depletion of the gut microbiota could ameliorate the aggravated disease phenotype induced by IL-34 knockout under HFD conditions. In the HFD model, antibiotic treatment normalized the elevated body weight index in IL-34 −/− +HFD mice (Fig. 5 B&C) and restored the increased liver index to levels comparable to controls (Fig. 5 D&E), with no significant effect observed in WT + HFD animals. Histopathological analysis revealed that antibiotics effectively ameliorated hepatic steatosis, inflammatory cell infiltration, and hepatocellular ballooning in IL-34 −/− +HFD mice (Fig. 5 F). The NAS confirmed a significant improvement in overall liver pathology in antibiotic-treated IL-34-deficient mice (Fig. 5 G). Liver Oil Red O staining revealed that antibiotic treatment significantly rescued the exacerbated hepatic lipid accumulation in HFD-fed mice caused by IL-34 deficiency (Fig. 5 H & I). Serum biochemical analysis demonstrated that antibiotic intervention markedly reduced the elevated levels of TG (Fig. 5 J), nonesterified fatty acids (NEFA, Fig. 5 K), ALT (Fig. 5 L), and AST (Fig. 5 M) caused by IL-34 deficiency. Furthermore, antibiotics also ameliorated the aggravated visceral fat accumulation caused by IL-34 deficiency in the HFD mouse model (Fig. 5 N-P). IL-34 deficiency led to increased production of gut microbiota-derived metabolites, particularly LPS and Imidazole propionate (IMP). Based on our experimental findings of increased LPS levels in mouse serum and KEGG pathway enrichment analysis of 16S rRNA sequencing data revealing enhanced enrichment of LPS metabolism-related pathways in IL-34 −/− mice compared to controls, we performed non-targeted metabolomic profiling of mouse portal vein serum. This approach was employed to identify metabolites entering the systemic circulation following alterations in intestinal mucosal permeability. The reliability of the metabolomic data was confirmed by a high correlation coefficient (~ 0.997) among quality control (QC) samples (Fig. 6 A). Principal component analysis (PCA) in three-dimensional score plots revealed distinct clustering between WT and IL-34 −/− groups, with strong intra-group reproducibility (Fig. 6 B). A total of 1,558 metabolites were identified across both groups (Fig. 6 C), heatmap visualization demonstrated a substantial number of differentially abundant metabolites in portal vein serum between WT and IL-34 −/− mice (Fig. 6 D). KEGG pathway enrichment analysis of all detected metabolites identified the top five enriched pathways as: Citric Acid Cycle (TCA cycle), short-chain fatty acid metabolism, fatty acid metabolism, thiamine metabolism, and glucose and glucose-1-phosphate degradation (Fig. 6 E). Further analysis showed significant reduction in the enrichment of pathways relevant to fatty liver disease—specifically the TCA cycle and linoleic acid metabolism—in the IL-34 −/− group compared to controls (Fig. 6 F). These KEGG enrichment analysis results indicate that IL-34 deficiency leads to abnormalities in energy metabolism and certain fatty acid metabolic pathways. Based on fold-change criteria, the top 10 upregulated and downregulated metabolites in portal vein serum were selected for generating heatmap and volcano plot visualizations (Fig. 6 G&H). Among these, p-Cresol glucuronide exhibited the greatest increase in the IL-34 −/− mice, whereas propionic acid showed the most pronounced downregulation. Since p-Cresol glucuronide has been previously reported to lack significant impacts on insulin resistance or fatty liver metabolism [ 21 ] , we focused subsequent analysis on the second most altered metabolite, imidazole propionate (IMP). The relative fold-changes of propionic acid and IMP are displayed in Fig. 6 I and 6 J, respectively. We intersected the two sets of differentially abundant bacterial flora with the IMP-associated gut microbiota reported in the study by Koh A et al [ 22 ] , identifying 15 overlapping species, including: Streptococcus, Ruminiclostridium, Corynebacterium, Staphylococcus, Alloprevotella, Erysipelatoclostridium, Blautia, Lachnoclostridium, Odoribacter, Bacteroides, Parabacteroides, Ruminococcus, Alistipes, Butyricimonas, and Desulfovibrio (Fig. 6 K). Among these, eight species (Streptococcus, Ruminiclostridium, Blautia, Lachnoclostridium, Odoribacter, Parabacteroides, Alistipes, and Desulfovibrio) showed increased abundance following IL-34 knockout. With the exception of Blautia, the differences in the remaining seven species were statistically significant (Fig. S3A). Seven other species exhibited decreased abundance, among which only Corynebacterium and Butyricimonas showed statistically significant differences between the two groups (Fig. S3B). Imidazole propionate ameliorates free fatty acid-induced hepatic steatosis in hepatocyte cultures Previous studies have demonstrated that IMP exacerbates insulin resistance and impairs glucose tolerance in diabetic models [ 22 ] . Furthermore, IMP has been shown to promote the accumulation of bone marrow adipocytes in vivo [ 23 ] . However, whether IMP exerts a direct impact on hepatic steatosis in hepatocytes has not been evaluated. To address this question, we treated AML12 and HepG2 hepatocyte cell lines with a free fat [ 24 ] ty acids (FFAs) mixture (oleic acid: palmitic acid = 2:1) to establish a cellular model of hepatic steatosis. Our results demonstrated a dose-dependent aggravation of FFAs-induced lipid accumulation in both AML12 (Fig. 7 A&B) and HepG2 (Fig. 7 C&D) cells following IMP treatment, as assessed by Oil red O staining. Discussion As the most common chronic liver disease worldwide, MASLD imposes a significant and growing global health burden due to its increasing prevalence and strong associations with multiple chronic conditions. Despite substantial research efforts and resources investment in recent years, no FDA-approved targeted therapies are currently available [ 23 , 24 ] . Lifestyle interventions, the most widely recommended clinical approach for MASLD, are limited by poor patience compliance, while conventional pharmacological treatments offer only modest efficacy and carry potential side effects [ 7 , 25 ] . Moreover, the marked heterogeneity of MASLD hinders the development of personalized treatment [ 26 ] . These challenges collectively highlight the urgent need for novel and effective therapeutic targets. Although gut microbiota dysbiosis has emerged as a key pathogenic driver in MASLD, its translation into targeted therapeutic interventions remains largely exploratory [ 5 , 27 ] . Our study addresses this unmet need by elucidating a previously unrecognized regulatory role for IL-34 in maintaining gut-liver axis homeostasis, providing compelling evidence for its protective function in MASLD. Our study provides the first evidence demonstrating upregulation of IL-34 in the livers of both MASLD patients and HFD-fed mice. While IL-34 has traditionally been associated with pro-inflammatory functions in various pathological contexts [ 28 ] , our findings reveal a contrasting, tissue-protective role in MASLD. Intriguingly, IL-34 knockout mice fed an HFD exhibited exacerbated hepatic steatosis and impaired intestinal barrier integrity. Collectively, our data establish IL-34 as a protective factor that attenuates the progression of MASLD. Mechanistically, our findings elucidate that IL-34 confers hepatoprotective effects through two distinct pathways. Firstly, we have uncovered a novel role for IL-34 in modulating gut microbial metabolism, wherein it suppresses IMP production, thereby mitigating insulin resistance and hepatic lipid accumulation. This discovery provides fresh insight into the regulatory network of the gut-liver axis in MASLD. Secondly, exogenous IL-34 activates the CSF-1R/ERK signaling axis, leading to enhanced expression of intestinal tight junction proteins. This action strengthens the intestinal barrier and restricts the translocation of gut microbial metabolites, notably IMP and LPS, into the portal vein circulation. While current evidence indicates that IL-34 primarily mediates pro-inflammatory effects by modulating monocytes/macrophage survival and function via its receptor CSF-1R [ 28 , 29 ] , our study yields a striking observation: macrophage depletion failed to rescue liver injury induced by IL-34 deficiency (Figure S1 ), whereas antibiotic intervention conferred significant protection. This compelling finding strongly suggests that the beneficial effects of IL-34 are predominantly microbiota-dependent rather than macrophage-mediated. Following IL-34 knockout, gut microbial diversity was significantly reduced, accompanied by a disrupted balance between beneficial and harmful bacterial populations. Therefore, we conclude that high levels of serum IL-34 in MASLD patients exert protective effects in the gut by modulating the composition of gut microbiota, enhancing intestinal barrier integrity, and reducing the entry of detrimental microbial metabolites, such as LPS and IMP, into the portal circulation, ultimately attenuating disease pathogenesis (Fig. 8 ). The gut microbial metabolite IMP initially gained attention for its established role in diabetes, particularly following the work of Koh A et al., which demonstrated its capacity to aggravate insulin resistance and impair glucose tolerance [ 22 ] . Further investigation revealed that IMP impairs the glucose-lowering efficacy of metformin by inhibiting AMPK phosphorylation at Threonine 172 [ 24 ] . Furthermore, IMP has been shown to promote bone marrow adiposity [ 23 , 24 ] . Collectively, these findings establish IMP as a critical mediator of insulin resistance and lipid accumulation, underscoring its significance in metabolic dysregulation. Our study is the first to demonstrate that IL-34 alleviates hepatic steatosis by modulating the gut microbiota to reduce IMP synthesis, thereby improving insulin resistance and glucose tolerance. Furthermore, we directly demonstrate that exogenous IMP exacerbates free fatty acid-induced lipid accumulation in hepatocytes. These results not only confirm the critical role of IMP in MASLD progression but also open new avenues for therapeutic strategies targeting its synthesis. Several limitations warrant consideration when interpreting these findings. First, while our study clearly demonstrates the importance of IL-34 in murine models of MASLD, additional clinical studies are needed to validate these observations in human patients. Second, the precise molecular mechanisms by which IMP exacerbates lipid accumulation in the liver remain incompletely understood and warrant further investigation. Additionally, the specific pathways through which IL-34 modulates the abundance of gut microbiota, as well as the identification of the affected microbial taxa, require further validation through high-throughput sequencing and functional experiments. Despite these limitations, our study carries important translational implications. The identification of IL-34 as a regulator of gut-liver communication unveils novel therapeutic opportunities for MASLD, including potential approaches such as IL-34 supplementation, CSF-1R agonists, or targeted modulation of IMP-producing bacteria. Future studies should explore these possibilities and evaluate whether circulating IL-34 levels could serve as prognostic biomarkers for MASLD progression. Conclusion In summary, this study is the first to elucidate that IL-34 alleviates insulin resistance and hepatic steatosis in MASLD by modulating the gut microbiota to reduce the entry of LPS and IMP into the portal circulation. Our work thereby provides robust evidence for the involvement of gut microbiota in MASLD pathogenesis and establishes a foundational rationale for developing microbiota-targeted therapeutic interventions. Declarations Declarations and ethics statements All study procedures involving animal and people experiments were consistent with the requirements of the Lab Animal Ethical Committee of Nantong University and the Medical Ethics Committee of Third People’s Hospital of Nantong, respectively. Ethical approval The animal experiment part of this article has been approved by the Laboratory Animal Center of Nantong University. Furthermore, this experiment has been approved by the Medical Ethics Committee of Third People’s Hospital of Nantong, and the Ethics Committee reference number is EK2024100. Informed consent from participants All patients involved in the article were informed and signed informed consent. Availability of data and materials All the data are reliable, and all the reagents and devices designed in the article are commercially available. Please contact the corresponding author for the data if required. Consent to publish statement/form All the authors of this article have consented to publication. Competing interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding This study was supported by grants from the Science and Technology Bureau (MS22018007 and MSZ2024117), Six Peak Talents in Jiangsu Province (YY-177), Project of Jiangsu Province Youth Medical Talent Development (QNRC2016400), Project of Nantong Youth Medical Talent Development (No.05), Youth Fund of Natural Science Foundation of Jiangsu Province (BK20200965), Scientific Research Fund of Nantong Health Commission (MB2020037), Nantong University Clinical Medicine Special Research Fund Project (2024JZ020), Health Bureau of Nantong City (grant No. MB2021057), the National Natural Science Foundation of China (32270919 and 32470927), and Jiangsu Innovative and Entrepreneurial Research Team Program (JSSCTD202348). However, the funding sources had no involvement in the study design, collection, analysis, interpretation of data, writing of the report, or the decision to submit the paper for publication. Author contributions Yicun Liu performed the main part of the study and wrote the original draft. Linling Ju performed the main part of the study. Lingling Shi, Lixian Wei, Jingjing Wang provided technical support and analyzed the data. Zhouming Shen, Lin Chen and Jianguo Shao contributed to part of the experiments. Liming Mao and Zhaolian Bian designed the study, performed the main part, and guided the manuscript writing. Acknowledgments We thank the Animal Center of Nantong University and the Institute of Liver Diseases of Nantong Third People’s Hospital for providing the experimental platform . Thanks for Figdraw. References Miao L, Targher G, Byrne CD et al (2024) Current status and future trends of the global burden of MASLD[J]. Trends Endocrinol Metab 35(8):697–707 Chan WK, Chuah KH, Rajaram RB et al (2023) Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD): A State-of-the-Art Review[J]. 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CNS Neurosci Ther 30(4):e14657 Nian Z, Dou Y, Shen Y et al (2024) Interleukin-34-orchestrated tumor-associated macrophage reprogramming is required for tumor immune escape driven by p53 inactivation[J]. Immunity 57(10):2344–2361e7 Supplementary Files Supplementarydocument.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Minor Revision 12 Apr, 2026 Reviewers agreed at journal 23 Feb, 2026 Reviewers invited by journal 20 Feb, 2026 Editor assigned by journal 09 Feb, 2026 First submitted to journal 08 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8820945","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":594338810,"identity":"651dca92-2ddb-4fd7-a97e-b85f06fc75aa","order_by":0,"name":"Yicun Liu","email":"","orcid":"","institution":"Nantong Third Hospital Affiliated to Nantong University Department of Gastroenterology: The Third People's Hospital of Nantong Department of 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Gastroenterology","correspondingAuthor":true,"prefix":"","firstName":"Zhaolian","middleName":"","lastName":"Bian","suffix":""}],"badges":[],"createdAt":"2026-02-08 10:46:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8820945/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8820945/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103353907,"identity":"b44d461b-237c-4bad-ac67-a23a563281b4","added_by":"auto","created_at":"2026-02-24 17:50:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":11087125,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eUpregulation of IL-34 Expression in MASLD\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e(A) H\u0026amp;E staining and NRS scores in the livers of normal control (HC, n=6) and MASLD patients (n=5); (B) The qPCR analysis results showed that compared with the HC(n=6) group, the expression level of IL34 in the liver of MASLD patients (n=5); (C) Immunohistochemical analysis of liver tissues revealed a higher expression level of IL-34 in MASLD (n=5) patients compared to the HC (n=6) group.; (D) HFD model was established by feeding C57BL/6 mice with a 60% high-fat diet for 12 weeks; (E) Line graph of body weight changes in WT (n=5) and WT+HFD (n=10) mice; (F) H\u0026amp;E staining and NAS scores in the livers of WT and WT+HFD mice; (G) qPCR analysis of IL-34 expression levels in the livers of WT and WT+HFD mice; (H) Immunohistochemical analysis of IL-34 expression in the livers of WT and WT+HFD mice and positive rate statistics; (I) Western blot analysis of IL-34 expression in the livers of WT and WT+HFD mice (n=4). Data were presented as mean ± SD. *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001, ns: not significant.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8820945/v1/0baa3e1b8541f3e9825a4a2a.png"},{"id":103353906,"identity":"943441b0-dbc5-40d8-b1a5-bf50c8973158","added_by":"auto","created_at":"2026-02-24 17:50:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":7610193,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIL-34 Deficiency Exacerbates High-Fat Diet-Induced Hepatic fat accumulation in MASLD through Lipid Metabolic Dysregulation\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e(A) High-fat diet (HFD) model was established by feeding C57BL/6 (WT) and IL-34\u003csup\u003e-/-\u003c/sup\u003e mice with a 60% high-fat diet for 12 weeks; (B) Representative photographs showing body size differences between WT+HFD and IL-34\u003csup\u003e-/-\u003c/sup\u003e+HFD mice; (C) Body weight changes in WT+HFD and IL-34\u003csup\u003e-/-\u003c/sup\u003e+HFD mice presented as a line graph; (D-E) Liver size and weight measurements in WT+HFD and IL-34\u003csup\u003e-/-\u003c/sup\u003e+HFD mice; (F) Serum TG levels in WT+HFD and IL-34\u003csup\u003e-/-\u003c/sup\u003e+HFD mice; (G) Serum ALT levels in WT+HFD and IL-34\u003csup\u003e-/-\u003c/sup\u003e+HFD mice; (H) Serum AST levels in WT+HFD and IL-34\u003csup\u003e-/-\u003c/sup\u003e+HFD mice; (I-J) H\u0026amp;E staining of liver tissues and corresponding NAS scores in WT+HFD and IL-34\u003csup\u003e-/-\u003c/sup\u003e+HFD mice; (K-L) H\u0026amp;E staining of liver tissues and quantification of positively stained areas in WT+HFD and IL-34\u003csup\u003e-/-\u003c/sup\u003e+HFD mice; (M) Visceral adipose tissue weight comparison between WT+HFD and IL-34\u003csup\u003e-/-\u003c/sup\u003e+HFD mice; (N-O) H\u0026amp;E staining of visceral adipose tissues and adipocyte counting in WT+HFD and IL-34\u003csup\u003e-/-\u003c/sup\u003e+HFD mice; (P-Q) Glucose tolerance test (GTT) performed at 10 weeks in WT+HFD and IL-34\u003csup\u003e-/-\u003c/sup\u003e+HFD mice; (R-S) Insulin tolerance test (ITT) performed at 12 weeks in WT+HFD and IL-34\u003csup\u003e-/-\u003c/sup\u003e+HFD HFD mice. Statistical significance was determined by unpaired two-tailed Student's t-test (*p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8820945/v1/8ca765f73c89b44d74351e4e.png"},{"id":103506624,"identity":"928a288e-38ce-490c-ab34-135c0da78891","added_by":"auto","created_at":"2026-02-26 13:38:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":12003145,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIL-34 enhances intestinal mucosal barrier function by promoting the expression of tight junction proteins\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e(A) Colon organoids were isolated and cultured from WT and IL-34\u003csup\u003e-/-\u003c/sup\u003e mice, showing that IL-34 knockout inhibited budding in colon organoids. (B) Intestinal mucosal permeability was assessed in WT and IL-34\u003csup\u003e-/- \u003c/sup\u003emice using the fluorescein isothiocyanate–dextran (FITC-dextran) assay; (B) Serum lipopolysaccharide (LPS) levels were measured with an endotoxin detection kit; (C) Representative colon H\u0026amp;E staining and histological scores from the four experimental groups (WT, IL-34\u003csup\u003e-/- \u003c/sup\u003e, WT+HFD, IL-34\u003csup\u003e-/- \u003c/sup\u003e+HFD); (D-E) mRNA expression levels of ZO-1 and Occludin in colon tissues of the four groups were determined by qPCR; (F-G) Protein expression of ZO-1 and Occludin in colon tissues of the four groups was evaluated by immunohistochemical staining; (H) Caco-2 cells treated with increasing concentrations of exogenous IL-34 showed progressively elevated expression of ZO-1 and Occludin; (I) Time-dependent increase in ZO-1 and Occludin expression was observed in Caco-2 cells following treatment with 100 μg/ml exogenous IL-34 at 0, 6, 12, 24, and 48 hours; (J) Exogenous IL-34, but not CSF-1, enhanced ZO-1 and Occludin expression in Caco-2 cells; (K) The CSF-1R inhibitor GW2580 did not affect ZO-1 and Occludin expression, whereas the ERK inhibitor SCH772984 significantly attenuated the IL-34-induced upregulation of ZO-1 and Occludin in Caco-2 cells.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8820945/v1/3526c7e5d254ff771f9dab74.png"},{"id":103353914,"identity":"3fd912bc-251d-4aa7-afd5-7c5213af8f82","added_by":"auto","created_at":"2026-02-24 17:50:29","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3946321,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIL-34 may impact energy metabolism through modulation of the gut microbiota\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e(A) Unweighted Unifrac heatmap displays the dissimilarity coefficients between samples from WT and IL-34\u003csup\u003e-/- \u003c/sup\u003egroups; (B) Principal Coordinate Analysis represents the similarity of microbial communities between the two groups of samples; (C) Rarefaction curve results show changes in the number of gut microbiota with increasing sample size in each group; (D) Venn diagram based on OTUs of WT and IL-34\u003csup\u003e-/- \u003c/sup\u003egroups represents the diversity of gut microbiota in the two groups of mice; (E) Chao1 index plot of the total species richness of gut microbiota; (F) Shannon index plot of gut microbiota diversity; (G) LDA Effect Size (LEfSe) plot displays the gut microbiota playing significant roles in WT and IL-34\u003csup\u003e-/- \u003c/sup\u003emice; (H-I) Species distribution bar chart at the species level for samples from WT and IL-34\u003csup\u003e-/- \u003c/sup\u003egroups; (J) Kyoto Encyclopedia of Genes and Genomes enrichment analysis was performed on the differential microbiota between the two groups, and the top ten pathways with the most significant differences were visualized in a dendrogram. Data are presented as mean ± SD from three independent experiments. *p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.001, ****p\u0026lt;0.0001 by unpaired two-tailed Student's t-test. ns: not significant.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8820945/v1/890c7e0ebb9d2fdb177b58a7.png"},{"id":103506870,"identity":"5847cf6d-a092-4f30-acc7-3bdaef44f942","added_by":"auto","created_at":"2026-02-26 13:39:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":11034148,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAntibiotic-Mediated Gut Microbiota Modulation Reverses IL-34 Deficiency-Induced Liver Injury in MASLD Mice\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;(A) C57BL/6 (WT) and IL-34\u003csup\u003e-/- \u003c/sup\u003emice were fed a 60% high-fat diet with or without broad-spectrum antibiotics (BIO; 1 g/L ampicillin, 160 mg/L gentamicin, 1 g/L metronidazole, and 1 g/L vancomycin) in drinking water for 12 weeks to establish an HFD + antibiotic model. The mice were divided into four groups: WT + HFD, WT + HFD+BIO, IL-34\u003csup\u003e-/- \u003c/sup\u003e+ HFD and IL-34\u003csup\u003e-/-\u003c/sup\u003e+ HFD + BIO; (B) Representative photographs showing body size differences among the four HFD-fed groups; (C) Body weight changes of the four HFD mouse groups presented in a line chart; (D-E) Statistical graphs of liver volume and weight in the four HFD mouse groups; (F-G) Liver H\u0026amp;E staining and NAS scores for the four HFD mouse groups; (H-I) Liver H\u0026amp;E staining and statistical analysis of positive area in the four HFD mouse groups; (J) Serum TG levels in the four HFD mouse groups; (K) Serum non-esterified fatty acid (NEFA) levels in the four mouse groups; (L) Serum ALT levels in the four HFD mouse groups; (M) Serum AST levels in the four mouse groups; (N) Comparison of visceral fat weight in the four HFD mouse groups; (O-P) Visceral fat H\u0026amp;E staining and adipocyte count statistics in the four HFD mouse groups.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-8820945/v1/a8a986f169843889c2885805.png"},{"id":103353909,"identity":"90dd56d5-7e95-49fc-8396-45f9d648d37b","added_by":"auto","created_at":"2026-02-24 17:50:29","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":4472896,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIL-34 deficiency led to increased production of gut microbiota-derived metabolites, particularly LPS and Imidazole propionate (IMP)\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e(A) QC sample correlation plot; (B) PCA 3D score scatter plot; (C) Circular chart of metabolite classification; (D) Metabolite heatmap showing numerous differentially expressed metabolites in the two groups of portal vein serum; (E) KEGG enrichment analysis plot; (F) KEGG heatmap; (G) Differential metabolite heatmap; (H) Differential metabolite volcano plot; (I) Box plot of Propionic acid differential expression; (J) Box plot of Imidazole propionate differential expression; (K) Venn diagram of differential microbiota between the two groups and IMP-producing gut microbiota. Data are presented as mean ± SD. *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ns: not significant.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-8820945/v1/8caacfadae367b851a5c2499.png"},{"id":103353911,"identity":"f566e720-c3e8-4847-9bcc-6258d956c8d9","added_by":"auto","created_at":"2026-02-24 17:50:29","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":11700949,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eImidazole propionate ameliorates free fatty acid-induced hepatic steatosis in hepatocyte cultures\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e(A-B) Oil Red O staining and positive area quantification of AML12 hepatic steatosis models induced by FFAs and stimulated with varying IMP concentrations (0, 25, 50, 100, 200 μmol/ml); (C-D) Oil Red O staining and positive area quantification of HepG2 hepatic steatosis models induced by FFAs and stimulated with varying IMP concentrations. Data were presented as mean ± SD. *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001, ns: not significant.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-8820945/v1/83d2b24d2bc47f718f10bb1b.png"},{"id":103353912,"identity":"20fd1fac-d842-4c25-a275-fb5951b5c978","added_by":"auto","created_at":"2026-02-24 17:50:29","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":195577,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIL-34 ameliorates MASLD by regulating the synthesis of gut microbiota-derived metabolites LPS and IMP\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHigh levels of serum IL-34 in MASLD patients exert protective effects in the gut by modulating the composition of gut microbiota, enhancing intestinal barrier integrity, and reducing the entry of detrimental microbial metabolites, such as LPS and IMP, into the portal circulation, ultimately attenuating disease pathogenesis.\u003c/p\u003e\n\u003cp\u003eAbbreviations: MASLD: Metabolic dysfunction-associated steatotic liver disease; LPS: Lipopolysaccharide; IMP: imidazole propionate. AntibioticL: 1g/L ampicillin, 160 mg/L gentamicin, 1g/L metronidazole and 1g/L vancomycin.\u003c/p\u003e","description":"","filename":"OnlineFigure8.png","url":"https://assets-eu.researchsquare.com/files/rs-8820945/v1/854a9354017c59b739b8607a.png"},{"id":103509925,"identity":"42ef79f1-0654-42ae-b253-c5b1f10bcea0","added_by":"auto","created_at":"2026-02-26 14:02:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":57549418,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8820945/v1/d3ee3174-625b-445a-9a5f-1a4bac7992ab.pdf"},{"id":103353913,"identity":"08929601-1ac1-44ae-be41-768446f5b3c5","added_by":"auto","created_at":"2026-02-24 17:50:29","extension":"docx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":1529361,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarydocument.docx","url":"https://assets-eu.researchsquare.com/files/rs-8820945/v1/1cb9929561b5ec16b9063893.docx"}],"financialInterests":"","formattedTitle":"IL-34 ameliorates MASLD by regulating the synthesis of gut microbiota-derived metabolites LPS and IMP","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMetabolic dysfunction-associated steatotic liver disease (MASLD) is a long-lasting liver condition caused by excessive fat building up in the liver. As the most prevalent chronic liver disease worldwide\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e, MASLD affects approximately 34% of the global population\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. MASLD is not only highly prevalent in adults but also increasingly common among children and adolescents\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. The pathogenesis of MASLD is multifactorial, encompassing hepatic steatosis, insulin resistance, oxidative stress, hepatocyte injury, and immune-mediated inflammatory responses. However, its precise pathophysiological mechanisms remain incompletely defined\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Current diagnostic tools of MASLD lack sufficient sensitivity for early-stage detection, while liver biopsy remains the gold standard, it is invasive and carries clinical limitations. In addition, specific therapeutic options for MASLD remain limited, primarily relying on lifestyle interventions and management of underlying comorbidities\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. However, poor patient adherence poses a major constraint on long-term prognosis. Consequently, in-depth research into it underlying mechanisms is crucial for developing effective intervention strategies and improving patient outcomes.\u003c/p\u003e \u003cp\u003eThe gut-liver axis plays a critical role in the pathogenesis of inflammatory liver diseases\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. This bidirectional communication system comprises several key components, including the gut microbiota, intestinal barrier integrity, microbial metabolites, and host-immune regulation, that collectively modulate hepatic metabolism, inflammatory cascades, and fibrogenesis\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. It is well established that MASLD can disrupt gut microbiota by increasing the abundance of γ-proteobacteria, which further contributes to intestinal barrier disruption, increased intestinal permeability, and subsequent systemic inflammation. The compromised barrier function facilitates the translocation of gut-derived lipopolysaccharide (LPS) to the liver via the portal circulation. Once in the liver, Gut-derived LPS activates pro-inflammatory signaling pathways, triggering hepatic inflammation and exacerbating disease progression of MASLD\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Therefore, targeting the gut-liver axis represents a promising therapeutic strategy to prevent MASLD onset and halt its progression, providing various potential interventions\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRecently, through an epigenomic analysis of the methionine-choline deficient (MCD)-induced mouse model, Zeng et al. identified IL-34 as a potential regulator in the lipid metabolism and immune-inflammatory pathways in MASLD\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Shoji H and colleagues were the first to report elevated serum IL-34 levels in patients with MASLD\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. IL-34 is a pleiotropic cytokine secreted by various cell populations, including macrophages, fibroblasts, and epithelial cells, and exerts its biological functions primarily by binding to the colony-stimulating factor-1 receptor (CSF-1R), thereby playing key roles in regulating inflammation, tissue repair, and immune responses \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. Emerging evidence also suggests the involvement of other receptors, such as protein-tyrosine phosphatase zeta (PTPζ), CD138 (Syndecan-1), and the triggering receptor expressed on myeloid cells 2 (TREM2) in IL-34 signaling \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Notably, new evidence indicates a potential bidirectional link between IL-34 expression and the composition of the gut microbiota\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. These findings highlight the emerging role of IL-34 in MASLD pathogenesis, providing fresh perspectives on disease mechanisms and potential treatments.\u003c/p\u003e \u003cp\u003eWe initially validated the previously reported serum findings of Shoji H et al. at both the mRNA and protein levels in liver tissues from MASLD patients, confirming significantly elevated IL-34 expression. Intriguingly, our results revealed that the elevated IL-34 is not a pathogenic factor in MASLD. Contrary to expectations, IL-34 knockout did not alleviate hepatic steatosis but instead exacerbated hepatic lipid accumulation in a HFD-induced mouse model. Concurrently, IL-34 deficiency was associated with impaired intestinal barrier function and dysbiosis of the gut microbiota. Crucially, subsequent antibiotic intervention effectively rescued the aggravated MASLD phenotype induced by IL-34 deficiency. Furthermore, we observed significantly increased levels of detrimental gut microbial metabolites, specifically LPS and imidazole propionate (IMP), in portal vein serum. In summary, our study establishes IL-34 as a pivotal protective regulator that mitigates MASLD progression through modulation of the microbiota-metabolite axis, highlighting its potential as a therapeutic target.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCollection and Storage of Liver Specimens\u003c/h2\u003e \u003cp\u003eThe study included a total of 6 healthy individuals and 5 patients with MASLD. Liver tissue samples were obtained from patients who underwent liver biopsies at the Third People's Hospital of Nantong University. After separation from the human body, the samples were immediately frozen in liquid nitrogen and stored at -80\u0026deg;C until use. This study was approved by the Ethics Committee of the Third People's Hospital of Nantong, and informed consent was obtained from each participant.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHigh-fat diet (HFD) mouse model\u003c/h3\u003e\n\u003cp\u003eA total of 10 male C57BL/6 wild-type (WT) and IL-34 knockout (IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e) mice, aged 6 weeks, were randomly divided into WT/IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e group and WT/IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e + HFD group. The WT/IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e group was fed a regular diet, while the WT/IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e + HFD group was fed a high-fat diet (Research Diet, USA). Mice were weighed weekly, and after 12 weeks, they were sacrificed to collect peripheral blood, liver, and intestinal tissues for subsequent experiments. Body Weight Index (BWI) = (Weight Gain / Baseline Weight) \u0026times; 100%, Liver Index = (Liver Weight / Body Weight) \u0026times; 100%, Fatty Index = (Fat Weight / Body Weight) \u0026times; 100%\u003c/p\u003e\n\u003ch3\u003eAntibiotic mouse model\u003c/h3\u003e\n\u003cp\u003eAt the start of the HFD modeling, the antibiotic (BIO) group was provided with a mixture of four non-absorbable broad-spectrum antibiotics in their drinking water (1g/L ampicillin, 160 mg/L gentamicin, 1g/L metronidazole and 1g/L vancomycin), while the control group received distilled water. Mice were sacrificed after 12 weeks/4 weeks.\u003c/p\u003e\n\u003ch3\u003eSerum transaminase assay\u003c/h3\u003e\n\u003cp\u003eMouse peripheral blood, centrifuge at 4\u0026deg;C, 8000 rpm for 10 minutes, then collect the supernatant (stored at -80\u0026deg;C). Perform the transaminase assay on a biochemical analyzer according to the instructions of the transaminase reagent kit (Nanjing Jiancheng Bioengineering Institute, Nanjing, China).\u003c/p\u003e\n\u003ch3\u003eBlood glucose and glucose tolerance test\u003c/h3\u003e\n\u003cp\u003eAfter fasting for 12h, mice were intraperitoneally injected with 20% high glucose (1.5ml/kg). Blood samples were collected at 0 min, 30 min, 60 min, 90 min, and 120 min to measure blood glucose levels, and the area under the insulin curve (AUC) was calculated to assess insulin resistance and glucose tolerance. The AUC calculation formulas are as follows: AUC1 = (BG0 min\u0026thinsp;+\u0026thinsp;2 * BG15 min\u0026thinsp;+\u0026thinsp;BG30 min) * 7.5, AUC2 = (BG30 min\u0026thinsp;+\u0026thinsp;2 * BG60 min\u0026thinsp;+\u0026thinsp;BG90 min) * 7, AUC\u0026thinsp;=\u0026thinsp;AUC1\u0026thinsp;+\u0026thinsp;AUC2.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eOil Red O staining\u003c/h2\u003e \u003cp\u003eFresh frozen liver tissue was prepared into 8 \u0026micro;m thick sections. The sections were stained with Oil Red O in the dark for 30 minutes, followed by dehydration with 60% isopropanol. Hematoxylin counterstaining was done for 20\u0026ndash;30 seconds, and the sections were rinsed with running water for 10 minutes. Observation and photography were performed under a microscope, with at least 5 fields of view taken for each slide.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHematoxylin \u0026 Eosin Staining (H\u0026E)\u003c/h3\u003e\n\u003cp\u003eAfter fixation in formalin solution, mouse liver tissue was embedded in paraffin and sliced into 4\u0026micro;m sections. The paraffin sections were dewaxed, hydrated, and subjected to antigen retrieval. They were then stained with hematoxylin for 2 minutes, followed by rinsing and decolorization with 95% ethanol, and counterstained with 0.5% eosin for 2 minutes. After applying 1\u0026ndash;2 drops of resin for mounting, the slides were observed under a microscope, and images were captured. Liver pathological sections were evaluated according to the MASLD Activity Score (NAS) established by the American Association for the Study of Liver Diseases in 2005. NAS\u0026thinsp;\u0026gt;\u0026thinsp;4 indicates a diagnosis of MASLD, while a NAS\u0026thinsp;\u0026lt;\u0026thinsp;3 excludes the possibility of MASLD. When there is no ballooning degeneration, lobular inflammation, or fibrosis, but steatosis is \u0026gt;\u0026thinsp;33%, MASLD can be confirmed; if steatosis is \u0026lt;\u0026thinsp;33%, it is classified as hepatic steatosis.\u003c/p\u003e\n\u003ch3\u003eImmunohistochemical Staining\u003c/h3\u003e\n\u003cp\u003eAfter deparaffinization, hydration, and antigen retrieval of the paraffin sections, the slides were incubated overnight in a humid chamber at 4\u0026deg;C with the primary antibody dilution. Following PBS washes, a secondary antibody dilution was added, and the slides were incubated at room temperature for 30 minutes. DAB chromogenic solution (Tongling Biomedicine Technology Co., Ltd., Xiamen, China) was prepared according to the manufacturer's instructions, and 100\u0026micro;L of the chromogenic solution was applied to the slides, adjusting for optimal staining time. Finally, after staining with hematoxylin for 30 seconds, the slides were mounted, and all tissue sections were assessed blindly under an optical microscope.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTotal Cholesterol, Triglycerides, and Non-Esterified Fatty Acids Measurement\u003c/h2\u003e \u003cp\u003eFor mouse liver tissue, add a homogenization medium (for high-fat samples, use anhydrous ethanol for extraction; for non-high-fat samples, use phosphate-buffered saline (0.1 mol/L, pH 7.4) or saline for extraction). After mechanical homogenization, take the supernatant for measurement. Follow the instructions of the total cholesterol (TC), triglycerides (TG), and non-esterified fatty acids (NEFA) test kits provided by Nanjing Jiancheng Bioengineering Institute for detection. The calculation formulas are as follows: TC content in tissue (mmol/g protein) = (Sample OD value - blank OD value) / (Calibration OD value - blank OD value) * Calibration concentration (5.17 mmol/L) / Sample protein concentration (g protein/L). TG content in tissue (mmol/g protein) = (Sample OD value - blank OD value) / (Calibration OD value - blank OD value) * Calibration concentration (2.26 mmol/L) / Sample protein concentration (g protein/L). NEFA content in tissue (\u0026micro;mol/g protein) = (Measured sample OD value - blank tube OD value) / (Standard tube OD value - blank tube OD value) * Standard concentration (1000 \u0026micro;mol/L) / Sample protein concentration (g protein/L).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of Intestinal Mucosal Permeability using the FITC-Dextran Method\u003c/h2\u003e \u003cp\u003eC57BL/6 (n\u0026thinsp;=\u0026thinsp;7) and IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e (n\u0026thinsp;=\u0026thinsp;5) mice were fasted for 8 h and then orally administered 0.2 mL of fluorescein isothiocyanate\u0026ndash;labeled dextran (FITC-dextran; 60 mg/100 g body weight; Sigma, Germany). After 4 h, the mice were euthanized, and serum samples were collected. Fluorescence intensity was measured using a fluorescence spectrophotometer (excitation wavelength: 480 nm; emission wavelength: 520 nm). The serum FITC-dextran concentration was calculated by extrapolating the fluorescence values to a standard curve of FITC-dextran.\u003c/p\u003e \u003cp\u003e \u003cb\u003e16S rRNA Sequencing of Fecal Samples and Untargeted Metabolomics of Portal Vein Serum\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFecal samples from C57BL/6 (n\u0026thinsp;=\u0026thinsp;6) and IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e (n\u0026thinsp;=\u0026thinsp;6) mice were subjected to 16S rRNA sequencing, and untargeted metabolomics analysis was performed on portal vein serum samples. These analyses were conducted by AZENTA Life Sciences (Suzhou, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRNA extraction and quantitative reverse transcription-polymerase chain reaction (qRT-PCR)\u003c/h2\u003e \u003cp\u003eTotal RNA from human and mouse liver was extracted using TRIzol\u0026reg; Reagent (Thermo Fisher Scientific, Shanghai, China). Following the instructions of the PrimeScript RT Master Mix (Takara, Japan), the RNA was reverse transcribed into cDNA. Subsequently, gene amplification was performed using TB Green Premix Ex Taq II (Takara). Finally, detection was carried out on a CFX Connect real-time PCR instrument (BIO-RAD, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eWestern Blot\u003c/h2\u003e \u003cp\u003eTissue samples were ground and suspended in an appropriate amount of RIPA lysis buffer (Jiangsu Biyuntian Company, Jiangsu, China) for cell lysis. The supernatant was collected and stored at -80\u0026deg;C for future use. The protein concentration was adjusted to an appropriate level (20\u0026ndash;50 \u0026micro;g per well). The samples were mixed with loading buffer and boiled for 5 minutes to denature the proteins. The samples were loaded onto SDS-PAGE gels (typically 10\u0026ndash;15% polyacrylamide gel) and subjected to electrophoresis at 120V for protein separation. After electrophoresis, the gel was transferred to a nitrocellulose membrane at 100V for 1 hour to transfer the proteins from the gel to the membrane. Blocking was performed using blocking buffer from Biyuntian Company, incubating at room temperature for 1 hour. The primary antibody was diluted according to the manufacturer's instructions (Kang Cheng Biotechnology Company, Shanghai, China) and incubated overnight at 4\u0026deg;C. After washing the membrane three times, an appropriate dilution of the secondary antibody (Kang Cheng Biotechnology Company) was added, and incubation was performed at room temperature for 1 hour. Following the wash steps, an adequate amount of ECL developing solution was added, and imaging was performed using the Tenen Chemical Imaging System (Shanghai, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCell Lines and Culture Conditions\u003c/h2\u003e \u003cp\u003eThe human colorectal cancer cell line Caco-2, hepatocellular carcinoma cell line HepG2, and human/mouse hepatocyte cell line AML12 were purchased from the Stem Cell Bank of the Chinese Academy of Sciences (Shanghai, China). All cells were cultured in a humidified incubator at 37\u0026deg;C with 5% CO₂ (model CO2-311, Thermo Fisher Scientific). MEM medium (Gibco, Waltham, USA) and DMEM/12 (Zhongqiao Xinzhou, Shanghai, China) were used for culturing human Caco-2/HepG2 cells and murine AML12 cells, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eFree Fatty Acid (FFA) Solution Preparation and Cell Modeling\u003c/h2\u003e \u003cp\u003eA free fatty acids (FFAs) solution was prepared by mixing oleic acid (OA; Sigma, Germany) and palmitic acid (PA; Sigma, Germany) at a molar ratio of 2:1 (0.5 mM OA : 0.25 mM PA). The mixture was thoroughly blended at 60\u0026deg;C and then combined with an equal volume of 10% BSA (Leagene Biotechnology, Beijing, China) to form the FFAs working solution. When HepG2 and AML12 cells reached 70\u0026ndash;80% confluence, they were first treated with Imidazole propionate (IMP; Sigma, Germany). One hour after IMP administration, the cells were co-stimulated with the FFAs solution for 24 hours. When Caco-2 cells reached 70\u0026ndash;80% confluence, they were treated with varying concentrations of exogenous IL-34 (MedChemExpress, Shanghai, China), CSF-1 (MedChemExpress, Shanghai, China), GW2580 (MedChemExpress, Shanghai, China), or SCH772984 (MedChemExpress, Shanghai, China). Cells were subsequently harvested at different time points.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eCells Oil Red O Staining\u003c/h2\u003e \u003cp\u003eAfter 24 hours of FFAs stimulation, HepG2 and AML12 cells were washed with PBS and fixed with 1 mL of cell fixation solution. The cells were then stained with Oil Red O (Sigma, Germany) in the dark for 12 minutes, followed by destaining with 60% isopropanol for 5 minutes. Finally, the cells were counterstained with hematoxylin (Beyotime Biotechnology, Jiangsu, China) for 2 minutes. The area of Oil Red O staining was quantified from five random fields of view using an inverted light microscope (Olympus, Japan).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eIsolation of Intestinal Crypts and Organoid Culture\u003c/h2\u003e \u003cp\u003eIntestinal crypts were isolated from the mouse small intestine as previously described with minor modifications\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Briefly, the IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e/WT mice small intestine was dissected, opened longitudinally, and washed thoroughly in cold phosphate-buffered saline (PBS) to remove intestinal contents. The tissue was then fragmented and incubated in 2 mM EDTA in PBS for 30 minutes on ice with gentle agitation. Crypts were released by vigorous shaking in PBS. The suspension was filtered through a 70-\u0026micro;m cell strainer to remove debris and large villus fragments. The crypts were collected by centrifugation at 150\u0026times;g for 5 minutes at 4\u0026deg;C. The isolated crypts were resuspended in reduced-growth-factor Matrigel (KeyGEN BioTECH, USA) and plated as 20\u0026micro;L droplets in the center of a pre-warmed 24-well plate. The plate was inverted and incubated at 37\u0026deg;C for 15 minutes to allow the Matrigel to polymerize. Each well was then overlaid with 500\u0026micro;L of complete Intestinal Organoid Growth Medium. The organoid culture medium was changed every 2\u0026ndash;3 days.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThis study used SPSS 26.0 and GraphPad Prism 9.0 software for data analysis and statistical result visualization. Chi-square tests were employed for correlation analysis, while independent samples t-tests were used for intergroup difference analysis. In cases of non-normal distribution, non-parametric rank-sum tests were applied. All statistical results were considered significant at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eUpregulation of IL-34 Expression in MASLD\u003c/h2\u003e \u003cp\u003eWe collected liver biopsy samples from 5 patients with MASLD and 6 healthy controls (HC). H\u0026amp;E staining was performed on all liver biopsy specimens to validate hepatic steatosis in MASLD patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The expression of IL-34 in these tissues was then evaluated using qPCR and the results demonstrated significantly elevated IL-34 mRNA levels in liver tissues of MASLD patients compared to HCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). To validate this finding at the protein level, we obtained additional liver biopsy specimens from 10 HCs and 21 MASLD patients for immunohistochemical (IHC) staining analysis. Under 200\u0026times; and 400\u0026times; magnification, marked increases in brown-stained areas, indicative of IL-34 expression, were observed in liver tissues from the MASLD group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, left). Semi-quantitative scoring confirmed significantly higher IL-34 protein levels in MASLD patient livers (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, right).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo further corroborate IL-34 upregulation in MASLD, we established a high-fat diet (HFD) mouse model by feeding C57BL/6 mice with a diet containing 60% of calories from fat for 12 weeks (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Compared to the control mice (n\u0026thinsp;=\u0026thinsp;5), HFD-fed mice (n\u0026thinsp;=\u0026thinsp;10) exhibited significantly greater body weight gain (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). The effectiveness of the HFD-induced model was further confirmed by H\u0026amp;E staining, which showed extensive lipid accumulation in hepatocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). Following successful establishment of the HFD model, we assessed IL-34 expression in mouse liver tissues using qPCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG) and IHC staining (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH). To verify changes in IL-34 protein levels in HFD mouse livers, we performed Western blot analysis, which demonstrated a significant upregulation of IL-34 in the livers of HFD mice compared with the controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eIL-34 Deficiency Exacerbates High-Fat Diet-Induced Hepatic fat accumulation in MASLD through Lipid Metabolic Dysregulation\u003c/h2\u003e \u003cp\u003eGiven the significant upregulation of IL-34 in both serum\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e and liver tissues of MASLD subjects, we generated IL-34 knockout mice to investigate its biological role in the development and progression of MASLD. C57BL/6 wild-type (WT) and IL-34 knockout (IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e) mice were fed with a 60% high-fat diet (HFD) for 12 weeks to establish an HFD-induced MALSD model (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Compared to the WT group, IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e HFD mice exhibited increased body size (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), accelerated weight gain (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC), and a higher liver index (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD\u0026amp;E). To further explore the effects of IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e on liver function and lipid metabolism, we measured serum triglycerides (TG), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) levels. The results showed that IL-34 knockout led to higher serum TG levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF) and elevated liver transaminase levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG\u0026amp;H) in HFD mice. Histological analysis using H\u0026amp;E (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eI-J) and Oil Red O (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eK-L) staining revealed markedly enhanced hepatic lipid accumulation in IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice compared to WT controls. To investigate the role of IL-34 in adipose tissue pathology, we collected and weighed visceral fat from both groups of mice. The results indicated that IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice had increased visceral fat accumulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eM). H\u0026amp;E staining of adipose tissue demonstrated enlarged adipocyte size in IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice relative to controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eN\u0026amp;O). Further metabolic characterization demonstrated that IL-34 deficiency significantly disrupted systemic energy metabolism. Glucose metabolism tests showed pronounced glucose intolerance (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eP\u0026amp;Q), and insulin resistance (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eR\u0026amp;S) in IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e+HFD mice.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eIL-34 enhances intestinal mucosal barrier function by promoting the expression of tight junction proteins\u003c/h2\u003e \u003cp\u003eFirst, we cultured colonic organoids from IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e and WT mice respectively and found that IL-34 knockout slowed the proliferation of colonic cells and reduced the budding rate in mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). To assess intestinal permeability, serum FITC-dextran concentration was measured following oral administration. We found that IL-34 knockout mice exhibited significantly increased intestinal permeability compared to controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Serum LPS levels were also elevated in IL-34 knockout mice, with a pronounced increase in serum subjected to HFD modeling (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC), indicating exacerbated endotoxemia. Using the HFD animal model, we observed that compared with the control group, IL-34 deficiency aggravated the HFD-induced intestinal pathological changes in mice, including increased mucosal thickness and inflammatory cell infiltration (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Given that IL-34 deficiency alters intestinal mucosal permeability in mice, we validated the expression of intestinal tight junction proteins, ZO-1 and Occludin, using qPCR and immunohistochemistry. Both analyses demonstrated that both IL-34 knockout and HFD independently led to decreased expression of intestinal tight junction proteins, and their combination resulted in an additive suppression (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE-H). Additionally, we examined the expression of four IL-34 receptors in intestinal tissues following HFD treatment through immunohistochemical staining and found that the expression of CSF-1 was downregulated in IL-34 knockout mice, whereas other three receptors remained unaffected. Upon HFD treatment, CSF-1R levels were significantly reduced in intestinal tissues of WT mice. However, in IL-34 knockout mice, HFD did not further suppress CSF-1R expression. These results suggest a role for IL-34 in maintaining CSF-1R expression, potentially contributing to the regulation of IL-34-mediated downstream biological processes (Supplementary Fig. S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn vitro studies using human NCM460 colonic epithelial cells demonstrated that treatment with recombinant IL-34, but not CSF-1, dose-dependently upregulated the expression of ZO-1 and Occludin (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI-K). Mechanistic investigations revealed that pharmacological inhibition of ERK signaling with SCH772984 significantly attenuated IL-34-mediated upregulation of these proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eL). However, the addition of the CSF-1R inhibitor GW2580 did not affect the action of IL-34 on tight junction proteins.These findings provide compelling evidence that IL-34 enhances intestinal epithelial barrier function through activation of the ERK signaling axis, leading to increased expression of tight junction proteins ZO-1 and Occludin.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eIL-34 may impact energy metabolism through modulation of the gut microbiota\u003c/h2\u003e \u003cp\u003eSince IL-34 can improve intestinal mucosal permeability, we further investigated its effect on the gut microbial community in mice using 16S ribosomal RNA gene-based amplicon sequencing. The unweighted UniFrac heatmap, where color intensity reflects the degree of dissimilarity between sample pairs, with lighter colors indicating lower dissimilarity, revealed minimal variation within both WT and IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Principal Coordinate Analysis (PCoA), in which shorter distances between samples represents greater similarity in microbial communities, indicated that the microbial community structures of the two groups were largely similar (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). However, rarefaction curves (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC) and OTU-based Venn diagram (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD) showed that after IL-34 knockout, the richness of the gut microbiota in mice decreased compared to the control group. Further analysis using the Chao1 index (commonly used in ecology to estimate richness of species; where higher Chao1 index indicates greater number of OTUs) and Shannon index (commonly used to estimate microbial diversity in a sample; a higher Shannon index indicates higher community diversity) revealed that both the species richness (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE) and diversity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF) of the gut microbiota were significantly reduced in IL-34 knockout mice. Furthermore, Linear Discriminant Analysis Effect Size (LEfSe) results identified Sutterellaceae, Burkholderiales, and Gammaproteobacteria as the most differentially enriched microbial taxa in the IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e group, whereas In the WT group, the top taxa were Oscillospirales, Akkermansia, and Eubacterium_coprostanoligenes_group were enriched in the WT group, indicating distinct microbial profiles between the two groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigures \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI present bar charts at the species level for each sample. The top five taxa exhibiting the greatest differential abundance between the two groups were Coriobacteriaceae_UCG-002, Rikenella, Parasutterella, Ruminiclostridium, and Muribaculum. Among these, Coriobacteriaceae_UCG-002 and Rikenella were significantly enriched in IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice compared to the control group, while Parasutterella, Ruminiclostridium, and Muribaculum were markedly reduced. To explore functional implications, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed on the differentially abundant taxa. The top ten most significantly altered pathways are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eJ. The enriched pathways were primarily related to energy metabolism, including the TCA cycle and glucose degradation, purine and pyrimidine ribonucleotide synthesis and degradation, tRNA processing, LPS metabolism-related pathways such as the superpathway of UDP-glucose-derived O-antigen building block biosynthesis, and biosynthesis pathways for key cofactors such as tetrahydrofolate, pyridoxal 5'-phosphate, and heme. Compared to controls, the IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e group exhibited a decrease in the energy metabolism-related pathways, particularly the TCA cycle, alongside a significant increase in LPS metabolism-related pathways.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eAntibiotic-Mediated Gut Microbiota Modulation Reverses IL-34 Deficiency-Induced Liver Injury in MASLD Mice\u003c/h2\u003e \u003cp\u003eBased on our findings above, which demonstrate that IL-34 regulates the gut microbiota and that IL-34 knockout exacerbates hepatic steatosis in HFD-fed mice, we administered broad-spectrum antibiotics in the drinking water to the experimental group following HFD modeling (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). This intervention aimed to determine whether depletion of the gut microbiota could ameliorate the aggravated disease phenotype induced by IL-34 knockout under HFD conditions. In the HFD model, antibiotic treatment normalized the elevated body weight index in IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e+HFD mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB\u0026amp;C) and restored the increased liver index to levels comparable to controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD\u0026amp;E), with no significant effect observed in WT\u0026thinsp;+\u0026thinsp;HFD animals.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHistopathological analysis revealed that antibiotics effectively ameliorated hepatic steatosis, inflammatory cell infiltration, and hepatocellular ballooning in IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e+HFD mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). The NAS confirmed a significant improvement in overall liver pathology in antibiotic-treated IL-34-deficient mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG). Liver Oil Red O staining revealed that antibiotic treatment significantly rescued the exacerbated hepatic lipid accumulation in HFD-fed mice caused by IL-34 deficiency (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH \u0026amp; I). Serum biochemical analysis demonstrated that antibiotic intervention markedly reduced the elevated levels of TG (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eJ), nonesterified fatty acids (NEFA, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eK), ALT (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eL), and AST (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eM) caused by IL-34 deficiency. Furthermore, antibiotics also ameliorated the aggravated visceral fat accumulation caused by IL-34 deficiency in the HFD mouse model (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eN-P).\u003c/p\u003e \u003cp\u003e \u003cb\u003eIL-34 deficiency led to increased production of gut microbiota-derived metabolites, particularly LPS and Imidazole propionate (IMP).\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBased on our experimental findings of increased LPS levels in mouse serum and KEGG pathway enrichment analysis of 16S rRNA sequencing data revealing enhanced enrichment of LPS metabolism-related pathways in IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice compared to controls, we performed non-targeted metabolomic profiling of mouse portal vein serum. This approach was employed to identify metabolites entering the systemic circulation following alterations in intestinal mucosal permeability. The reliability of the metabolomic data was confirmed by a high correlation coefficient (~\u0026thinsp;0.997) among quality control (QC) samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Principal component analysis (PCA) in three-dimensional score plots revealed distinct clustering between WT and IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e groups, with strong intra-group reproducibility (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). A total of 1,558 metabolites were identified across both groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC), heatmap visualization demonstrated a substantial number of differentially abundant metabolites in portal vein serum between WT and IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKEGG pathway enrichment analysis of all detected metabolites identified the top five enriched pathways as: Citric Acid Cycle (TCA cycle), short-chain fatty acid metabolism, fatty acid metabolism, thiamine metabolism, and glucose and glucose-1-phosphate degradation (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). Further analysis showed significant reduction in the enrichment of pathways relevant to fatty liver disease\u0026mdash;specifically the TCA cycle and linoleic acid metabolism\u0026mdash;in the IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e group compared to controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). These KEGG enrichment analysis results indicate that IL-34 deficiency leads to abnormalities in energy metabolism and certain fatty acid metabolic pathways. Based on fold-change criteria, the top 10 upregulated and downregulated metabolites in portal vein serum were selected for generating heatmap and volcano plot visualizations (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG\u0026amp;H). Among these, p-Cresol glucuronide exhibited the greatest increase in the IL-34\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice, whereas propionic acid showed the most pronounced downregulation. Since p-Cresol glucuronide has been previously reported to lack significant impacts on insulin resistance or fatty liver metabolism\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e, we focused subsequent analysis on the second most altered metabolite, imidazole propionate (IMP). The relative fold-changes of propionic acid and IMP are displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eJ, respectively. We intersected the two sets of differentially abundant bacterial flora with the IMP-associated gut microbiota reported in the study by Koh A et al\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e, identifying 15 overlapping species, including: Streptococcus, Ruminiclostridium, Corynebacterium, Staphylococcus, Alloprevotella, Erysipelatoclostridium, Blautia, Lachnoclostridium, Odoribacter, Bacteroides, Parabacteroides, Ruminococcus, Alistipes, Butyricimonas, and Desulfovibrio (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eK). Among these, eight species (Streptococcus, Ruminiclostridium, Blautia, Lachnoclostridium, Odoribacter, Parabacteroides, Alistipes, and Desulfovibrio) showed increased abundance following IL-34 knockout. With the exception of Blautia, the differences in the remaining seven species were statistically significant (Fig. S3A). Seven other species exhibited decreased abundance, among which only Corynebacterium and Butyricimonas showed statistically significant differences between the two groups (Fig. S3B).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eImidazole propionate ameliorates free fatty acid-induced hepatic steatosis in hepatocyte cultures\u003c/h2\u003e \u003cp\u003ePrevious studies have demonstrated that IMP exacerbates insulin resistance and impairs glucose tolerance in diabetic models\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Furthermore, IMP has been shown to promote the accumulation of bone marrow adipocytes in vivo\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. However, whether IMP exerts a direct impact on hepatic steatosis in hepatocytes has not been evaluated. To address this question, we treated AML12 and HepG2 hepatocyte cell lines with a free fat\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003ety acids (FFAs) mixture (oleic acid: palmitic acid\u0026thinsp;=\u0026thinsp;2:1) to establish a cellular model of hepatic steatosis. Our results demonstrated a dose-dependent aggravation of FFAs-induced lipid accumulation in both AML12 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA\u0026amp;B) and HepG2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC\u0026amp;D) cells following IMP treatment, as assessed by Oil red O staining.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAs the most common chronic liver disease worldwide, MASLD imposes a significant and growing global health burden due to its increasing prevalence and strong associations with multiple chronic conditions. Despite substantial research efforts and resources investment in recent years, no FDA-approved targeted therapies are currently available\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Lifestyle interventions, the most widely recommended clinical approach for MASLD, are limited by poor patience compliance, while conventional pharmacological treatments offer only modest efficacy and carry potential side effects\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Moreover, the marked heterogeneity of MASLD hinders the development of personalized treatment\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. These challenges collectively highlight the urgent need for novel and effective therapeutic targets. Although gut microbiota dysbiosis has emerged as a key pathogenic driver in MASLD, its translation into targeted therapeutic interventions remains largely exploratory\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Our study addresses this unmet need by elucidating a previously unrecognized regulatory role for IL-34 in maintaining gut-liver axis homeostasis, providing compelling evidence for its protective function in MASLD. Our study provides the first evidence demonstrating upregulation of IL-34 in the livers of both MASLD patients and HFD-fed mice. While IL-34 has traditionally been associated with pro-inflammatory functions in various pathological contexts\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e, our findings reveal a contrasting, tissue-protective role in MASLD. Intriguingly, IL-34 knockout mice fed an HFD exhibited exacerbated hepatic steatosis and impaired intestinal barrier integrity. Collectively, our data establish IL-34 as a protective factor that attenuates the progression of MASLD.\u003c/p\u003e \u003cp\u003eMechanistically, our findings elucidate that IL-34 confers hepatoprotective effects through two distinct pathways. Firstly, we have uncovered a novel role for IL-34 in modulating gut microbial metabolism, wherein it suppresses IMP production, thereby mitigating insulin resistance and hepatic lipid accumulation. This discovery provides fresh insight into the regulatory network of the gut-liver axis in MASLD. Secondly, exogenous IL-34 activates the CSF-1R/ERK signaling axis, leading to enhanced expression of intestinal tight junction proteins. This action strengthens the intestinal barrier and restricts the translocation of gut microbial metabolites, notably IMP and LPS, into the portal vein circulation. While current evidence indicates that IL-34 primarily mediates pro-inflammatory effects by modulating monocytes/macrophage survival and function via its receptor CSF-1R\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e, our study yields a striking observation: macrophage depletion failed to rescue liver injury induced by IL-34 deficiency (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), whereas antibiotic intervention conferred significant protection. This compelling finding strongly suggests that the beneficial effects of IL-34 are predominantly microbiota-dependent rather than macrophage-mediated. Following IL-34 knockout, gut microbial diversity was significantly reduced, accompanied by a disrupted balance between beneficial and harmful bacterial populations. Therefore, we conclude that high levels of serum IL-34 in MASLD patients exert protective effects in the gut by modulating the composition of gut microbiota, enhancing intestinal barrier integrity, and reducing the entry of detrimental microbial metabolites, such as LPS and IMP, into the portal circulation, ultimately attenuating disease pathogenesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe gut microbial metabolite IMP initially gained attention for its established role in diabetes, particularly following the work of Koh A et al., which demonstrated its capacity to aggravate insulin resistance and impair glucose tolerance\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Further investigation revealed that IMP impairs the glucose-lowering efficacy of metformin by inhibiting AMPK phosphorylation at Threonine 172\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Furthermore, IMP has been shown to promote bone marrow adiposity\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Collectively, these findings establish IMP as a critical mediator of insulin resistance and lipid accumulation, underscoring its significance in metabolic dysregulation. Our study is the first to demonstrate that IL-34 alleviates hepatic steatosis by modulating the gut microbiota to reduce IMP synthesis, thereby improving insulin resistance and glucose tolerance. Furthermore, we directly demonstrate that exogenous IMP exacerbates free fatty acid-induced lipid accumulation in hepatocytes. These results not only confirm the critical role of IMP in MASLD progression but also open new avenues for therapeutic strategies targeting its synthesis.\u003c/p\u003e \u003cp\u003eSeveral limitations warrant consideration when interpreting these findings. First, while our study clearly demonstrates the importance of IL-34 in murine models of MASLD, additional clinical studies are needed to validate these observations in human patients. Second, the precise molecular mechanisms by which IMP exacerbates lipid accumulation in the liver remain incompletely understood and warrant further investigation. Additionally, the specific pathways through which IL-34 modulates the abundance of gut microbiota, as well as the identification of the affected microbial taxa, require further validation through high-throughput sequencing and functional experiments. Despite these limitations, our study carries important translational implications. The identification of IL-34 as a regulator of gut-liver communication unveils novel therapeutic opportunities for MASLD, including potential approaches such as IL-34 supplementation, CSF-1R agonists, or targeted modulation of IMP-producing bacteria. Future studies should explore these possibilities and evaluate whether circulating IL-34 levels could serve as prognostic biomarkers for MASLD progression.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, this study is the first to elucidate that IL-34 alleviates insulin resistance and hepatic steatosis in MASLD by modulating the gut microbiota to reduce the entry of LPS and IMP into the portal circulation. Our work thereby provides robust evidence for the involvement of gut microbiota in MASLD pathogenesis and establishes a foundational rationale for developing microbiota-targeted therapeutic interventions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclarations and ethics statements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll study procedures involving animal and people experiments were consistent with the requirements of the Lab Animal Ethical Committee of Nantong University and the Medical Ethics Committee of Third People’s Hospital of Nantong, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe animal experiment part of this article has been approved by the Laboratory Animal Center of Nantong University. Furthermore, this experiment has been approved by the Medical Ethics Committee of Third People’s Hospital of Nantong, and the Ethics Committee reference number is EK2024100.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent from participants\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll patients involved in the article were informed and signed informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the data are reliable, and all the reagents and devices designed in the article are commercially available. Please contact the corresponding author for the data if required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish statement/form\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors of this article have consented to publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from the Science and Technology Bureau (MS22018007 and MSZ2024117), Six Peak Talents in Jiangsu Province (YY-177), Project of Jiangsu Province Youth Medical Talent Development (QNRC2016400), Project of Nantong Youth Medical Talent Development (No.05), Youth Fund of Natural Science Foundation of Jiangsu Province (BK20200965), Scientific Research Fund of Nantong Health Commission (MB2020037), Nantong University Clinical Medicine Special Research Fund Project (2024JZ020), Health Bureau of Nantong City (grant No. MB2021057), the National Natural Science Foundation of China (32270919 and 32470927), and Jiangsu Innovative and Entrepreneurial Research Team Program (JSSCTD202348). However, the funding sources had no involvement in the study design, collection, analysis, interpretation of data, writing of the report, or the decision to submit the paper for publication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYicun Liu performed the main part of the study and wrote the original draft. Linling Ju performed the main part of the study. Lingling Shi, Lixian Wei, Jingjing Wang provided technical support and analyzed the data. Zhouming Shen, Lin Chen and Jianguo Shao contributed to part of the experiments. Liming Mao and Zhaolian Bian designed the study, performed the main part, and guided the manuscript writing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the Animal Center of Nantong University and the Institute of Liver Diseases of Nantong Third People’s Hospital for providing the experimental platform . Thanks for Figdraw.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMiao L, Targher G, Byrne CD et al (2024) Current status and future trends of the global burden of MASLD[J]. Trends Endocrinol Metab 35(8):697\u0026ndash;707\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChan WK, Chuah KH, Rajaram RB et al (2023) Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD): A State-of-the-Art Review[J]. 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Front Immunol 16:1655560\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePepperberg IM, Neapolitan DM, 2ND, LANGUAGE-ACQUISITION - A FRAMEWORK FOR STUDYING, THE IMPORTANCE OF INPUT AND INTERACTION IN EXCEPTIONAL SONG ACQUISITION[J] (1988) Ethology 77(2):150\u0026ndash;168\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMin BH, Devi S, Kwon GH et al (2024) Gut microbiota-derived indole compounds attenuate metabolic dysfunction-associated steatotic liver disease by improving fat metabolism and inflammation[J]. Gut Microbes 16(1):2307568\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSi W, Chen Z, Bei J et al (2024) Stigmasterol alleviates neuropathic pain by reducing Schwann cell-macrophage cascade in DRG by modulating IL-34/CSF1R[J]. CNS Neurosci Ther 30(4):e14657\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNian Z, Dou Y, Shen Y et al (2024) Interleukin-34-orchestrated tumor-associated macrophage reprogramming is required for tumor immune escape driven by p53 inactivation[J]. Immunity 57(10):2344\u0026ndash;2361e7\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cellular-and-molecular-life-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"life","sideBox":"Learn more about [Cellular and Molecular Life Sciences](https://link.springer.com/journal/18)","snPcode":"18","submissionUrl":"https://www.editorialmanager.com/life/default2.aspx","title":"Cellular and Molecular Life Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Interleukin-34, MASLD, Gut-liver axis, Imidazole propionate","lastPublishedDoi":"10.21203/rs.3.rs-8820945/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8820945/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePrevious studies have established that metabolic dysfunction-associated steatotic liver disease (MASLD) disrupts the intestinal barrier, allowing harmful microbial metabolites such as lipopolysaccharide (LPS) to translocate to the liver via the gut-liver axis and accelerate disease progression. While the conventional view holds that IL-34 plays a pro-inflammatory role in various diseases, our findings using IL-34 knockout mice under a high-fat diet (HFD) challenge this assumption, Contrary to expectations, IL-34 deficiency exacerbated both hepatic lipid accumulation and intestinal barrier damage compared to wild-type controls. Furthermore, IL-34 knockout led to a significant reduction in gut microbial diversity and an altered ratio of detrimental to beneficial bacterial populations. Notably, antibiotic intervention ameliorated the aggravated MASLD phenotype in IL-34-deficient mice, a protective effect not observed with macrophage depletion. Metabolomic analysis of portal vein serum revealed a significant increase in imidazole propionate (IMP), a microbiota-derived metabolite, following IL-34 ablation. Functional assays demonstrated that IMP directly promotes free fatty acid-induced lipid accumulation in AML12 and HepG2 hepatocyte cell lines. To our knowledge, this study is the first to elucidate that elevated serum IL-34 plays a protective role in MASLD by modulating the gut microbiota and preserving intestinal barrier integrity, thereby limiting the portal influx of deleterious gut microbial metabolites such as IMP and LPS. These findings uncover a previously unrecognized mechanism by which IL-34 regulates MASLD progression through the gut microbial metabolic network, highlighting its potential as a therapeutic target for metabolic liver diseases.\u003c/p\u003e","manuscriptTitle":"IL-34 ameliorates MASLD by regulating the synthesis of gut microbiota-derived metabolites LPS and IMP","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-24 17:50:18","doi":"10.21203/rs.3.rs-8820945/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor Revision","date":"2026-04-13T03:35:39+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2026-02-24T00:11:10+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-20T09:17:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-09T13:25:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cellular and Molecular Life Sciences","date":"2026-02-08T05:46:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cellular-and-molecular-life-sciences","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"life","sideBox":"Learn more about [Cellular and Molecular Life Sciences](https://link.springer.com/journal/18)","snPcode":"18","submissionUrl":"https://www.editorialmanager.com/life/default2.aspx","title":"Cellular and Molecular Life Sciences","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"32749888-5892-46c0-9ca4-3e32546fe9a5","owner":[],"postedDate":"February 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-29T01:01:42+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-24 17:50:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8820945","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8820945","identity":"rs-8820945","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}