Methylmalonic Acid as a Ferroptosis-Derived Danger Signal: Activation of the PI3K–NF-κB Pathway Drives M1 Macrophage Polarization in Renal Ischemia–Reperfusion Injury

Methylmalonic Acid as a Ferroptosis-Derived Danger Signal: Activation of the PI3K–NF-κB Pathway Drives M1 Macrophage Polarization in Renal Ischemia–Reperfusion Injury | 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 Methylmalonic Acid as a Ferroptosis-Derived Danger Signal: Activation of the PI3K–NF-κB Pathway Drives M1 Macrophage Polarization in Renal Ischemia–Reperfusion Injury huimeng wang, jiajia Sun, Xiaohu Li, yongsheng Luo, hongxuan Ma, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9256951/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 7 You are reading this latest preprint version Abstract Background Ferroptosis and macrophage activation are key contributors to the development of acute kidney injury (AKI). Ferroptosis is accompanied by metabolic reprogramming and the release of soluble mediators, including metabolites, cytokines, and extracellular signals, which can propagate tissue damage and modulate immune responses. However, the metabolic profile of ferroptotic tubular epithelial cells and its impact on the immune microenvironment during ischemia–reperfusion injury (IRI) remains largely unexplored. Methods Using untargeted metabolomics, we found that ferroptotic cells secreted abnormally elevated levels of methylmalonic acid (MMA), and investigated the physiological role of MMA in acute kidney injury in mice. Furthermore, through transcriptomics and Western blotting, we explored the mechanism by which the ferroptosis-associated metabolite MMA promotes macrophage polarization. Results Here, untargeted metabolomics revealed a distinct metabolic secretome of ferroptotic tubular epithelial cells, with the level of MMA markedly elevated after IRI. Mechanistic studies demonstrated that MMA activated the PI3K/AKT/NF-κB pathway in macrophages, driving M1 polarization and increasing the secretion of proinflammatory cytokines such as IL-6 and TNF-α, ultimately exacerbating acute kidney injury. Conclusion These findings reveal the mechanism of metabolite–immune crosstalk in AKI, and suggest that targeting the ferroptosis–macrophage axis may represent a therapeutic strategy to disrupt the vicious cycle of inflammation and tissue injury. ferroptosis macrophage methylmalonic acid ischemia–reperfusion injury Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Ischemia–reperfusion injury (IRI) is a leading cause of acute kidney injury (AKI) following procedures such as kidney transplantation and cardiac surgery[ 1 – 3 ]. Renal tubular cell death during IRI was initially attributed mainly to apoptosis, and later studies highlighted necroptosis as a major contributor[ 4 ]. Recently, ferroptosis—a distinct form of regulated cell death characterized by iron-dependent lipid peroxidation—has emerged as a critical mechanism of tubular cell death in IRI[ 5 , 6 ]. Ferroptosis was first defined in 2012 and involves the collapse of cellular antioxidant defenses (notably glutathione peroxidase 4, GPX4) and the unchecked accumulation of lipid reactive oxygen species (ROS)[ 7 – 9 ]. Morphologically and biochemically, ferroptosis is nonapoptotic and often associated with mitochondrial shrinkage and loss of membrane integrity, which can trigger inflammation[ 10 , 11 ]. In various AKI models, ferroptosis has been shown to drive tissue damage; for example, pharmacological ferroptosis inhibitors such as ferrostatin-1 significantly alleviate renal dysfunction and histological injury in IRI[ 5 , 6 ] and other forms of AKI[ 11 ]. These findings underscore ferroptosis as a pivotal early event in IRI pathogenesis. While the direct cytotoxic role of ferroptosis in tissue injury has been established, its potential to influence the microenvironment via released signaling molecules remains poorly understood. Cells undergoing regulated death are being increasingly recognized not as inert entities but as active communicators. A landmark study demonstrated that apoptotic cells, despite maintaining plasma membrane integrity, release a suite of specific metabolites that act as “find-me” signals, thereby modulating neighboring cell behavior[ 12 ]. This apoptotic metabolite secretome is not a passive leakage of cellular contents but rather a caspase dependent, regulated process mediated by pannexin 1 (PANX1) channels[ 12 ]. In contrast, little is known about whether ferroptotic cells similarly emit metabolite signals and, if so, whether these signals contribute to the proinflammatory milieu of IRI. Recent evidence, however, indicates that ferroptotic cells may have a more complex secretory profile. In particular, Yapici and colleagues generated an atlas of ferroptosis-induced secretomes, demonstrating that ferroptotic cells release not only DAMPs but also a broad spectrum of proteins, lipids, and metabolites capable of shaping immune responses and intercellular communication. These findings suggest that ferroptosis is not merely destructive but may also convey context-dependent signals to the tissue microenvironment. Macrophages are central mediators of inflammation and repair in AKI. Classically activated M1 macrophages secrete proinflammatory cytokines and accelerate acute tissue damage[ 13 , 14 ], whereas alternatively activated M2 macrophages are anti-inflammatory and support tissue repair[ 15 ]. Macrophage polarization is known to be influenced by metabolic cues in the microenvironment. For example, succinate that accumulates during inflammatory macrophage activation can stabilize HIF-1α and drive a proinflammatory phenotype, in part by enhancing glycolysis and ROS production[ 16 , 17 ]. Conversely, metabolites such as itaconate or α-ketoglutarate can skew macrophages toward anti-inflammatory, reparative states[ 18 , 19 ]. Such findings highlight a paradigm wherein metabolites act as messengers that shape immune cell function. We therefore hypothesized that metabolites released by ferroptotic tubular cells may skew infiltrating macrophages toward an M1 proinflammatory phenotype, thereby linking tubular cell death to immune-mediated injury in IRI. To test these hypotheses, we induced ferroptosis in human proximal tubule HK-2 cells using two complementary inducers—RSL3 (a direct GPX4 inhibitor) and erastin (a system Xc– cystine transporter inhibitor)—and performed untargeted metabolomics on cell culture supernatants. We identified methylmalonic acid (MMA) as a markedly and consistently elevated metabolite specifically released during ferroptotic cell death. Notably, the level of MMA was not elevated in the supernatants of cells undergoing apoptosis or necroptosis, suggesting that MMA is a ferroptosis-associated secreted metabolite. Our experiments revealed that serum and kidney tissue MMA levels increase significantly after IRI and that this increase is blunted by the ferroptosis inhibitor Fer-1, suggesting that ferroptosis is linked to MMA accumulation in ischemic AKI. Furthermore, we found that MMA exposure polarizes macrophages toward the M1 phenotype and exacerbates kidney injury by amplifying inflammation. Mechanistically, we observed that MMA activates the PI3K/Akt/NF-κB signaling pathway in macrophages, providing a molecular basis for its proinflammatory activity. In summary, our study reveals a novel ferroptosis-triggered metabolic signal (MMA) that mediates crosstalk between dying tubular cells and immune cells. These findings shed new light on AKI pathogenesis and suggest potential therapeutic targets (such as metabolic modulation or ferroptosis inhibition) to mitigate IRI-induced kidney damage. Methods Antibodies The following antibodies were purchased from commercial vendors: rabbit anti-GPX4 (1;2000, Abways, CY6959), rabbit anti-SLC7A11 (1;1000, Abways, CY7046), rabbit anti-GAPDH (1;5000, Proteintech, 60004-1-Ig), rabbit anti-MUT (1;2000, Proteintech, 17034-1-AP), rabbit anti-NGAL (1;5000, Proteintech, 26991-1-AP), rabbit anti-IL6 (1;1000. Proteintech, 21865-1-AP), rabbit anti-TNF-α (1;1000, Proteintech, 17590-1-AP), rabbit anti-NF-κB p65 (1;2000, Abways, AB3449), rabbit anti-phospho-NF-κB p65 (ser536) (1;100, Abways, CY5095), rabbit anti-PI3K (1;500, Abways, CY3406), rabbit anti-phospho-PI3K p85 alpha (Tyr607) (1;1000, Affinity, AF3241), rabbit anti-phospho-Akt (Ser473) (1;1000, Abways, CY6569), and rabbit anti-Akt (1;1000, Abways, CY5561). Patients This study included 18 recipients who developed DGF after kidney transplantation from DCDs at the Department of Kidney Transplantation, The First Affiliated Hospital of Zhengzhou University, as the study group. Additionally, 20 recipients with stable graft function (ST) after kidney transplantation during the same period were randomly selected as controls. Zero-time biopsy samples of donor kidneys were obtained, and clinical history and follow-up data were collected. This clinical study involving clinical specimens was approved by the Institutional Review Board of the First Affiliated Hospital of Zhengzhou University in Zhengzhou, China (Approval Number: 2025-KY-0462-001) and complied with the ethical principles outlined in the 1975 Declaration of Helsinki. Animals Male C57BL/6 mice (6–8 weeks old) were purchased from Weitong Lihua Laboratory Animal Technology Co., Ltd. (Beijing, China). All the animals were maintained at constant humidity and temperature in standard facilities under specific pathogen-free conditions with free access to food and water. All operations were carried out in accordance with the National Institutes of Health (NIH) guidelines for the Care and Use of Laboratory Animals and were approved by the Ethics Committee of The First Affiliated Hospital of Zhengzhou University (Ethics Approval No. ZZU-LAC20210521[07]). Animal model Renal ischemia/reperfusion model Our study examined male mice because male animals exhibit less phenotypic variability. It is unknown whether the findings are relevant for female mice. Renal IRI was induced by occluding the left renal artery with a microaneurysm clamp for 30 min, followed by 24 h of reperfusion. Immediately after left renal artery clamping, a right nephrectomy was performed to preclude compensatory renal function. Throughout the procedure, the mice were maintained on a warming pad to stabilize their core body temperature at 36.5–37.0°C. Ferrostatin-1 (Fer-1, 5 mg/kg, ip.) and MMA (400 mg/kg, ip.), was intraperitoneally injected 15 min before IRI induction in C57BL/6 mice. Macrophage depletion in a mouse model The macrophages were depleted by the application of clodronate liposomes (CLOP, 200 µl, i.p.). In the control group, empty liposomes (200 µl, iP) were administered. The efficiency of macrophage depletion was evaluated using F4-80 antibody and CD11b by flow cytometry. Bone Marrow Cell Isolation and Differentiation into Mature BMDMs The mice were euthanized, and their femur and tibia bones were immediately isolated, cleaned with alcohol, and placed in PBS supplemented with 2% fetal bovine serum (FBS). The ends of the bones were cut off and flushed with PBS-FBS until they were cleared of all the bone marrow. The contents were filtered through a 40-µm cell strainer to obtain a single-cell suspension. ACK treatment was performed to lyse red blood cells, after which the cells were resuspended in BMDM (ISCove’s modified Dulbecco’s medium + 10% FBS + 10 ng/mL M-CSF). Bone marrow cells were seeded in 100-mm dishes at a density of 2 × 10 6 cells/mL and cultured for 7 days in BMDM. The medium of fresh BMDM was changed on Day 3. Cells were analyzed by flow cytometry for the expression of the markers CD11b and F4/80 to ensure that they had differentiated into mature BMDMs. Once the maturation of these macrophages was confirmed, they were treated with MMA (5 µM) or vehicle (PBS) as a control for 6 h in fresh media while still attached to the culture plate. The BMDMs were harvested and counted using a TC20 automated cell counter (Bio-Rad) and resuspended in PBS for injection into mice. Adoptive Transfer of Macrophages Mature BMDMs obtained from the culture, either untreated or treated with MMA, were injected into the mice through the tail vein at a concentration of 4 × 10 6 cells in 200 µL of PBS. Cell culture and treatment HK-2 cells and RAW264.7 cells were obtained from Procell Life Science & Technology Co., Ltd. The HK-2 cells were maintained in Dulbecco's modified Eagle’s medium/nutrient mixture F-12 (DMEM/F12; Gibco, USA) supplemented with 10% fetal bovine serum (FBS; Clark, USA) and 1% penicillin/streptomycin antibiotics (NCM; China) and incubated at 37°C with 5% CO 2 . To investigate the early secretory profile associated with ferroptosis, HK-2 cells were exposed to different concentrations of RSL3 (MCE, USA) or erastin (MCE, USA), and both cell and culture supernatants were collected 8 h after treatment for subsequent assays. RAW264.7 cells were treated with MMA (5 µM for 6 h; MCE, USA), LPS (100 ng/mL for 6 h; MCE, USA), or MMA followed by LPS (5 µM MMA for 6 h, subsequently exposed to 100 ng/mL LPS for an additional 6 h). For PI3K inhibition, cells were pretreated with LY294002 (10 µM; MCE, USA) for 12 h prior to the indicated treatments. Renal function Renal function was assessed by measuring serum creatinine (Scr) and blood urea nitrogen (BUN) levels. Commercially available kits (#C013-2-1 for BUN, #C011-2-1 for Scr; Nanjing Jiancheng, China) were used in accordance with the manufacturer’s instructions. Histology Renal tissues were embedded in paraffin, sectioned (4 µm thick), and stained with hematoxylin & eosin (H&E) and periodic acid–Schiff for histopathological evaluation. Tubular injury was diagnostically defined as cytolysis, brush border loss, or intraluminal cast formation. A blinded semiquantitative scoring system (grades 0–4) was used to categorize injury severity by the percentage of affected tubules per field: 0, no damage; 1, 80%. For each sample, 10 randomly selected cortical fields (200× magnification) were independently evaluated by two investigators, with final scores calculated as the mean value across all the fields to ensure statistical robustness. RT‒qPCR Total RNA was isolated from cell and tissue samples using a FastPure Cell/Tissue Total RNA Isolation Kit V2 (Vazyme Biotech Co., Ltd.). Reverse transcription was subsequently performed using Hifair III 1st Strand cDNA Synthesis SuperMix for qPCR (YEASEN, China) to synthesize complementary DNA. To assess mRNA expression levels, real-time quantitative PCR was carried out using Hieff qPCR SYBR Green Master Mix (YEASEN, China). For data normalization, GAPDH mRNA expression was used as the endogenous control. The relative quantification of target gene expression was determined through comparative threshold cycle analysis using the 2 −ΔΔCt method. The sequences of the mRNAs used for qPCR are provided in Table 1 . Western blot Total protein was extracted from cells and tissues by lysis in RIPA lysis buffer (Beyotime, China) supplemented with protease inhibitor (Beyotime, China). Protein concentrations were quantified using a BCA assay kit. For Western blot analysis, proteins were separated by SDS‒PAGE using an Omni-Easy™ One-Step PAGE Gel Fast Preparation Kit (Epizyme, Shanghai) and transferred onto PVDF membranes using a wet transfer system. The membranes were blocked with 5% skim milk for 2 h at room temperature and then incubated with primary antibodies at 4°C overnight. After being washed with TBST (3×10 min), the membranes were probed with HRP-conjugated secondary antibodies for 1 h. After intensive washing with TBST (5×5 min), the protein signals were visualized using enhanced chemiluminescence (ECL) reagent. All experimental reagents, including electrophoresis buffer, transfer buffer, TBST, and related solutions, were obtained from Yeasen Biotech (Shanghai). Flow cytometry analysis After the different treatments were administered, BMDMs, RAW264.7 cells, and kidney tissue cells were collected using cold PBS. For surface staining, the BMDMs and RAW264.7 cells were stained with Brilliant Violet 421™ anti-mouse CD11b (1:200, M1/70 clone, 101251, Biolegend) and FITC anti-mouse F4/80 (1:200, BM7 clone, 123108, Biolegend) antibodies for 30 min at 4°C. Kidney tissue cells were stained with Brilliant Violet 421™ anti-mouse CD11b (1:200, M1/70 clone, 101251, Biolegend) and FITC anti-mouse F4/80 (1:200, BM7 clone, 123108, Biolegend), for 30 min at 4°C. For intracellular cytokine staining, RAW264.7 cells were stained with PE anti-mouse TNF-α (1:200, MP6-XT22 clone, 506306, Biolegend) after surface staining. The stained cells were then washed twice with cold PBS and immediately analyzed by flow cytometry. Cellular subsets were sorted through CytoFLEX (Beckman, USA). Data were analyzed utilizing FlowJo Version 10.2 (FlowJo LLC, USA). Multiplex immunofluorescence (multi-IF) Paraffin-embedded kidney tissue sections were deparaffinized in xylene and then rehydrated sequentially in 100%, 95%, 70% ethanol, and PBS buffer. For IF, the sections were blocked with 5% goat serum in PBS buffer, incubated overnight with a GPX4 antibody (1:200; Abways, CY6959) at 4°C and incubated with the corresponding HRP-conjugated secondary antibody for 1 h at room temperature. The sections were incubated with tyramide signal amplification (TSA) (Servicebio Technology) for 10 min at room temperature, after which antigen repair and sealing were performed again. The MUT antibody (1:200; Proteintech, 17034-1-AP), corresponding HRP-labeled antibody, and TSA were sequentially added and incubated. For colocalization analysis of MUT with the proximal tubular marker Lotus tetragonolobus lecti, renal sections previously stained for MUT were coincubated with fluorescein-conjugated Lotus tetragonolobus lectin (LTL; Vector Laboratories, FL-1321) at room temperature (RT) for 1 h. Finally, the nuclei were stained with DAPI, and the images were scanned after the slices were sealed. Multiplex immunofluorescence staining of renal macrophages was performed as described above using antibodies against F4/80 (1:200; Proteintech, 29414-1-AP) and CD86 (1:200; Thermo Fisher, 14-0862-82). TUNEL assay The number of apoptotic cells was determined by TUNEL staining using a One Step TUNEL Apoptosis Assay Kit (Beyotime, Jiangsu, China), and the nuclei were stained with DAPI. Images were captured using a fluorescence microscope. FerroOrange and lipid oxidation species (LOS) detection FerroOrange (Dojindo, F347, Japan) is a fluorescent probe that enables live-cell imaging of intracellular Fe 2+ . For the assay, the cells were incubated with HBSS buffer containing 1 µmol/L FerroOrange for 1 h at 37°C. After incubation, the intracellular Fe 2+ levels were visualized by fluorescence microscopy, and the fluorescence intensity was quantified using ImageJ software (NIH, USA). Lipid oxidation species (LOS) were assessed using the Lipid Peroxidation Probe BDP 581/591 C11 (Dojindo, L267, Japan) according to the manufacturer’s instructions. The fluorescence signal was captured by fluorescence microscopy, and the intensity was quantified using ImageJ software (NIH, USA). Calcein/PI staining of HK-2 cells To assess cell viability and cytotoxicity, a Calcein/PI Live/Dead Viability/Cytotoxicity Assay Kit (Beyotime Biotechnology) was used. HK-2 cells treated with different concentrations of erastin or RSL3 were cultivated after 24 h. After the incubation was complete, the cells were stained using a calcein/PI kit. The culture medium was aspirated, and the cells were gently washed once with PBS. Afterward, according to the kit’s instructions, the calcein/PI detection working solution was prepared and added to each well. The cells were incubated at 37°C in the dark for 30 min. After incubation, cell viability and cytotoxicity were assessed by observing fluorescence under a fluorescence microscope (NIH, USA). CCK-8 assay The macrophage cultured under the relevant conditions for 24 were treated by 10 µL CCK-8 solution (Solarbio Technology, Beijing, China) for 2 h at 37°C. Then the optical density (OD) values of wells were monitored by a microplate reader (Spark, Tecan Group Ltd., Switzerland). Three repetitive wells were set up for each group. ELISA The concentrations of methylmalonic acid (MMA) and inflammatory cytokines in the plasma and cell culture supernatant were determined using enzyme-linked immunosorbent assay (ELISA) kits. Blood samples and cell supernatants were collected and centrifuged at 1,000 × g for 10 min. For renal MMA measurement, kidney tissues were rinsed with ice-cold 1× PBS to remove residual blood, homogenized in 10% ice-cold 1× PBS, and stored overnight at ≤ − 20°C. Following two freeze–thaw cycles to disrupt the cell membranes, the homogenates were centrifuged at 5,000 × g for 5 min. According to the manufacturers’ instructions, ELISA kits were used to quantify MMA (EIAab, China), interleukin-6 (IL-6; Mlbio, China), and tumor necrosis factor-α (TNF-α; Mlbio, China) levels in mouse peripheral serum, cell supernatants, and kidney homogenates. The absorbance was measured at 450 nm, and the concentrations were subsequently calculated. Statistics Statistical analyses were conducted using GraphPad Prism 9.0 or SPSS 24.0. The data are expressed as the mean ± standard error of the mean (SEM). The Shapiro‒Wilk test was used to assess data normality, and the Brown‒Forsythe test was used to evaluate the homogeneity of variance. For comparisons between two groups, an unpaired two-tailed Student’s t test was applied when the data followed a normal distribution with equal variance. When variances were unequal, Welch’s t test was used. Nonnormally distributed data were analyzed using the Mann–Whitney U test. For comparisons among three or more groups, one-way ANOVA followed by Bonferroni post hoc correction was used for normally distributed data, whereas the Kruskal–Wallis test with Dunn’s multiple comparisons test was used for nonnormally distributed data. For multifactorial comparisons, two-way ANOVA followed by Bonferroni post hoc correction was applied for normally distributed datasets, whereas multiple Mann–Whitney U tests were used for nonparametric data. A P value < 0.05 was considered to indicate statistical significance. Results 1. Ferroptosis induces the selective secretion of methylmalonic acid in HK-2 cells To establish a robust in vitro system for studying ferroptosis-associated metabolite release, we used HK-2 human proximal tubular epithelial cells, which are highly susceptible to ferroptotic death. Two mechanistically distinct ferroptosis inducers were applied: RSL3, an irreversible covalent inhibitor of glutathione peroxidase 4 (GPX4), and erastin, which blocks cystine import via system Xc⁻ and thus depletes intracellular glutathione. By using both agents, we aimed to capture ferroptosis triggered by endogenous antioxidant failure as well as by disruption of cystine metabolism. Western blot analysis demonstrated clear and dose-dependent downregulation of the expression of the ferroptosis regulators GPX4 and SLC7A11 (Fig. 1 A, B). With increasing concentrations of RSL3 (2–10 µM), GPX4 protein levels progressively decreased, becoming almost undetectable at 8 µM, while SLC7A11 was reduced by more than 60%. Similarly, treatment with erastin (5–80 µM) suppressed GPX4 expression in a dose-dependent manner, with maximal inhibition at 80 µM and a concomitant reduction in SLC7A11 expression. Densitometric quantification across three independent experiments revealed that GPX4 expression decreased by approximately 65% in response to 2 µM RSL3 and by approximately 55% in response to 5 µM erastin compared with that in response to no treatment. These findings validated the successful induction of ferroptosis in HK-2 cells. To ensure that subsequent metabolomic profiling reflected regulated secretion rather than nonspecific leakage, we next assessed plasma membrane integrity. Propidium iodide staining revealed that > 80% of the cells retained intact membranes after treatment with 2 µM RSL3 or 5 µM erastin (Fig. 1 D). These concentrations were therefore selected for further experiments, as they effectively triggered ferroptosis while minimizing the confounding effects of widespread cell rupture. To further confirm ferroptosis, we assessed two hallmark readouts: intracellular ferrous iron (Fe²⁺) accumulation and lipid peroxidation. FerroOrange staining demonstrated a significant increase in cytosolic Fe²⁺ following both RSL3 and erastin exposure. Concurrently, BODIPY-C11 staining revealed a nearly twofold increase in lipid reactive oxygen species (ROS) intensity relative to that in the controls, which was consistent with ferroptotic lipid damage (Fig. 1 C). We then performed untargeted metabolomics on the conditioned media of ferroptotic and control cells. Principal component analysis demonstrated distinct clustering of ferroptosis-induced metabolomes compared with those of the untreated controls, confirming the broad reprogramming of extracellular metabolite release (Fig. 1 E-H). Specifically, 45 metabolites were significantly upregulated after RSL3 treatment, whereas 139 metabolites were enriched following erastin exposure. Venn diagram analysis revealed 19 metabolites that were commonly increased under both ferroptotic stimuli (Fig. 1 I). Among these, methylmalonic acid (MMA) emerged as the most consistently and robustly elevated metabolite. (Fig. 1 J, K). To determine whether MMA release was unique to ferroptosis or a general feature of cell death, we compared supernatants from apoptotic and necroptotic HK-2 cells. Neither apoptosis induction with TNF-α + SM-164 nor necroptotic induction with TNF-α + SM-164 + Z-VAD-FMK resulted in detectable increases in extracellular MMA (Fig. S1C). This result strongly indicated that MMA secretion is not a universal byproduct of cell death but is instead specifically associated with ferroptosis. 2. MUT suppression links ferroptosis to MMA accumulation in vivo To investigate whether the ferroptosis-associated release of MMA observed in vitro also occurs in vivo, we used a murine model of renal ischemia–reperfusion injury (Fig. 2 A), a clinically relevant setting in which ferroptosis has been shown to play a major role in tubular cell death. As expected, immunofluorescence staining confirmed a marked reduction in GPX4 protein expression in renal tissues collected 24 hours after reperfusion (Fig. 2 N), which was consistent with ferroptotic activation. Serum creatinine levels and blood urea nitrogen (BUN) levels were significantly elevated in both groups compared with those in the sham-operated control group (Fig. 2 B, C), while the expression of NGAL, a sensitive marker of tubular injury, markedly increased (Fig. 2 D). Histological analyses revealed extensive tubular epithelial cell detachment, denudation of basement membranes, tubular dilatation, cast formation, and infiltration of inflammatory cells (Fig. 2 E, F). Administration of the ferroptosis inhibitor ferrostatin-1 (Fer-1) significantly improved renal outcomes. Compared with untreated IRI mice, treated mice exhibited approximately 40% lower serum creatinine and BUN levels (Fig. 2 B, C), as well as reduced NGAL expression and attenuated histological damage (Fig. 2 D-F). These findings support the conclusion that ferroptosis is a central driver of kidney injury in this model. We next quantified MMA levels in serum and kidney tissues by ELISA. Consistent with our in vitro findings, IRI led to a significant increase in MMA concentrations both systemically and locally within the kidney (Fig. 2 G, H). Notably, Fer-1 treatment reversed these increases, reducing MMA levels. These findings suggest that ferroptosis directly contributes to MMA accumulation in vivo. Given that intracellular MMA catabolism requires the mitochondrial enzyme methylmalonyl-CoA mutase (MUT) (Fig. 2 I), we assessed MUT expression under ferroptotic conditions. In HK-2 cells, both RSL3 and erastin markedly reduced MUT transcript abundance and protein levels (Fig. 2 J, K). In the IRI model, renal MUT expression significantly decreased after ischemia–reperfusion but was preserved when ferroptosis was pharmacologically inhibited by Fer-1 (Fig. 2 L, M). To define the spatial relationship between ferroptosis and MUT suppression, we performed dual immunofluorescence staining. MUT was found to be predominantly expressed in proximal tubular epithelial cells, as identified by Lotus tetragonolobus lectin (LTL) labeling. Under basal conditions, MUT exhibited strong mitochondrial punctate signals along the proximal tubules. However, after IRI, the fluorescence intensity of the MUT was markedly reduced, particularly in areas where GPX4 expression was lost (Fig. 2 N, O). Colocalization analyses demonstrated that regions of GPX4 depletion coincided with diminished MUT staining, indicating that MUT suppression occurs specifically in ferroptotic tubular cells. 3. Ferroptosis-derived MMA exacerbates renal ischemia–reperfusion injury To directly evaluate the pathogenic potential of MMA during renal ischemia–reperfusion injury (IRI), we established an exogenous supplementation model in which MMA was administered intraperitoneally to mice immediately following reperfusion (Fig. 3 A). Biochemical and histological assessments were performed 24 hours after injury. Compared with mice with IRI alone, MMA-treated mice exhibited significantly worse renal function. Serum creatinine levels were elevated by approximately 25%, while BUN levels increased by approximately 35% compared with those in the IRI controls (Fig. 3 B, C). Western blotting and immunohistochemistry demonstrated that NGAL expression was further upregulated in MMA-treated kidneys (Fig. 3 D). These biochemical findings were corroborated by histopathological analysis. Hematoxylin–eosin and PAS staining revealed more extensive epithelial detachment from the basement membrane, widespread tubular dilatation, denudation of tubular structures, and abundant intraluminal cast formation in MMA-treated animals (Fig. 3 E). Semiquantitative scoring confirmed that overall tubular injury scores nearly 1.5-fold higher in the MMA + IRI group compared with those in the IRI alone group. To assess cell death more specifically, we performed TUNEL staining. The proportion of TUNEL-positive tubular cells was nearly twofold greater in MMA-treated kidneys, with extensive clusters of apoptotic and necrotic cells visible throughout the cortex and outer medulla (Fig. 3 F). These data indicate that MMA exposure directly enhances tubular epithelial cell vulnerability during reperfusion. Given that macrophages are critical mediators of post-IRI inflammation, we next assessed immune cell infiltration. Flow cytometry revealed a substantial increase in renal F4/80⁺CD86⁺ M1 macrophages in IRI kidneys compared with those in sham controls, and this effect was further augmented by MMA treatment (Fig. 3 G). The frequency of M1 macrophages increased by approximately 80% in response to MMA treatment compared to IRI alone. In parallel, Western blotting demonstrated increased expression of IL-6 and TNF-α in kidney tissues, and ELISA confirmed the increased systemic release of these cytokines into the circulation (Fig. 3 H-J). Together, these results suggest that MMA not only exacerbates epithelial injury but also amplifies inflammatory macrophage responses in the postischemic kidney. 4. MMA directly drives M1 macrophage polarization in vitro To explore whether MMA can directly modulate the macrophage phenotype independent of tubular injury, we designed an in vitro coculture system using the murine macrophage line RAW264.7 (Fig. S2A). Initial experiments using conditioned media from ferroptotic HK-2 cells demonstrated that compared with media from viable HK-2 cells, ferroptotic supernatants alone were sufficient to promote a shift toward M1 polarization, as evidenced by increased proportions of F4/80⁺TNF-α⁺ macrophages (Fig. S2B). These observations prompted us to examine whether MMA, identified as a prominent ferroptosis-associated metabolite, could directly account for this effect. RAW264.7 macrophages were pretreated with MMA (5 µM) for 6 hours and subsequently stimulated with or without lipopolysaccharide (LPS) to mimic inflammation. Flow cytometric analysis revealed that compared with no treatment, MMA alone markedly increased the fraction of F4/80⁺TNF-α⁺ macrophages by approximately 5-fold relative to untreated controls. (Fig. 4 A). When combined with LPS, MMA acted synergistically, further expanding the M1 population by approximately 60% beyond LPS stimulation alone. At the transcriptional level, qPCR analysis confirmed the robust induction of classical M1-associated genes. The iNOS and IL-6 mRNA level increased more than 10-fold after MMA treatment, whereas the levels of the TNF-α transcripts increased approximately 20-fold (Fig. 4 B). These transcriptional changes translated into functional protein responses. Western blotting revealed increased expression of iNOS, IL-6, and TNF-α in MMA-treated cells (Fig. 4 C). ELISAs corroborated these findings, revealing significantly increased secretion of IL-6 and TNF-α into the culture supernatants, with MMA + LPS-treated macrophages producing the greatest amounts (Fig. 4 D, E). Importantly, MMA did not affect the viability of RAW264.7 cells at the concentrations used, as confirmed by CCK-8 assays (Fig. 4 F), excluding nonspecific cytotoxicity as a confounder. These results indicated that MMA acts as a bona fide signaling metabolite capable of directly reprogramming macrophage functional states. 5. Macrophage depletion abrogates MMA-induced renal injury To determine whether macrophages are indispensable mediators of MMA-driven renal injury, we performed selective macrophage depletion in mice using clodronate liposomes (CLOPs) (Fig. S3A). The intravenous administration of CLOP effectively reduced renal macrophage populations, as confirmed by flow cytometry (Fig. S3B). More than 70% of the F4/80⁺ CD11b + cells were eliminated within 24 hours of treatment, confirming successful depletion. In IRI alone, macrophage depletion significantly ameliorated renal dysfunction, with serum creatinine and BUN levels reduced by approximately 25% compared with those in untreated IRI controls (Fig. 5 A, B). Importantly, in MMA-supplemented IRI mice, macrophage depletion completely reversed the exacerbated renal injury phenotype. Serum creatinine and BUN levels in the MMA+CLOP group were indistinguishable from those in the IRI+CLOP group, demonstrating that the detrimental effects of MMA were fully dependent on the presence of macrophages. Western blot analysis revealed that NGAL expression, which was strongly induced in IRI kidneys and further upregulated by MMA treatment, was significantly reduced after macrophage depletion (Fig. 5 C). Histological analysis corroborated these findings: while MMA + IRI kidneys exhibited extensive tubular epithelial detachment, cast formation, and inflammatory infiltration, these pathological features were markedly alleviated in the MMA+CLOP group (Fig. 5 D). Semiquantitative injury scoring confirmed a nearly 25% reduction in injury severity upon macrophage removal. To further assess cell death, we performed TUNEL staining. In MMA-treated IRI kidneys, the proportion of TUNEL-positive tubular epithelial cells was significantly greater than that in kidneys with IRI alone, but this effect was effectively reversed after macrophage depletion (Fig. 5 E). Similarly, Western blot and ELISA revealed that the increased expression and systemic release of IL-6 and TNF-α induced by MMA were abrogated by CLOP treatment (Fig. 5 F-H). These results highlight the central role of macrophages in mediating MMA-driven inflammatory injury. These results also provide direct causal evidence linking ferroptosis-derived metabolites to immune effector cells as critical mediators of tissue damage. 6. MMA-primed BMDMs aggravate IRI through enhanced M1 polarization To further validate that MMA directly reprograms macrophages toward a pathogenic phenotype in vivo, we conducted adoptive transfer experiments using bone marrow–derived macrophages (BMDMs) (Fig. S4A). BMDMs were generated from C57BL/6 mice and confirmed by flow cytometry to express the macrophage lineage markers F4/80 and CD11b at high purity (> 90%) (Fig. S4B). To enable in vivo tracking, BMDMs were labeled with the fluorescent dye PKH-26 prior to transfer (Fig. S4C). Recipient mice subjected to renal IRI were intravenously infused with either untreated BMDMs or BMDMs preconditioned in vitro with MMA (5 µM, 24 h). Fluorescence microscopy confirmed that the transferred PKH-26–labeled BMDMs efficiently homed to injured kidneys, where they were localized predominantly in the cortical and outer medullary regions (Fig. S4D). Adoptive transfer of naïve BMDMs alone was sufficient to increase the frequency of renal F4/80⁺CD86⁺ M1 macrophages following IRI, suggesting that the injury microenvironment promotes proinflammatory polarization (Fig. 6 A). Notably, compared with unprimed BMDM transfer, the transfer of MMA-primed BMDMs resulted in an even greater expansion of the M1 subset, with M1 macrophage proportions being elevated by an additional 35%. Consistent with these findings, the results of the ELISA and Western blot analyses demonstrated that kidneys that received MMA-primed BMDMs expressed significantly higher levels of IL-6 and TNF-α than controls did (Fig. 6 B) and that the serum levels of these cytokines were also elevated (Fig. 6 C, D). At the functional level, renal injury was exacerbated in mice that received MMA-primed BMDMs, as evidenced by an approximately 25% increase in serum creatinine and BUN levels (Fig. 6 E, F), more severe histological damage with extensive tubular epithelial cell detachment and cast formation (Fig. 6 G, H), and a greater proportion of TUNEL-positive tubular cells (Fig. 6 I). These results demonstrate that MMA induces macrophages to adopt a more aggressive proinflammatory phenotype in vivo, thereby amplifying renal injury after IRI. 7. MMA promotes M1 polarization via PI3K/Akt/NF-κB signaling To elucidate the molecular mechanisms through which MMA drives macrophage polarization, we performed transcriptomic profiling of RAW264.7 cells treated with MMA for 12 hours. RNA-seq revealed 235 significantly differentially expressed genes (DEGs) compared with those in the untreated controls (Fig. 7 A, B). Among these genes, numerous genes involved in immune activation, cytokine production, and cell survival were upregulated. KEGG pathway enrichment analysis revealed that the PI3K/Akt signaling pathway was among the most significantly enriched pathways (Fig. 7 C, D), suggesting its potential role as a mediator of MMA-driven macrophage responses. Closer inspection of the RNA-seq dataset revealed increased expression of several regulators closely linked to PI3K/Akt activation, including PIK3AP1, Vegfa, and Mcl-1 (Fig. 7 E, F). qPCR validation confirmed that the expression of PIK3AP1, Vegfa, and Mcl-1 increased approximately 3-fold, approximately 2-fold, and approximately 2.5-fold, respectively, after MMA treatment (Fig. 7 F). These genes are known to increase PI3K activity, promote survival signaling, and facilitate proinflammatory programming in macrophages[ 20 – 22 ]. At the protein level, Western blot analysis demonstrated that MMA stimulation robustly increased the phosphorylation of PI3K, Akt, and NF-κB p65 (Fig. 7 G). Compared with those of the untreated controls, phosphorylated PI3K increased by approximately 2-fold, phosphorylated Akt by approximately 1.5-fold, and phosphorylated p65 by approximately 2.5-fold, while total protein levels remained unchanged. These findings indicated the activation of the canonical PI3K/Akt/NF-κB signaling cascade. To test whether PI3K/Akt signaling is functionally required for MMA-induced polarization, we pretreated macrophages with LY294002, a selective PI3K inhibitor. LY294002 markedly suppressed MMA-induced transcription of iNOS, IL-6, and TNF-α (Fig. 7 H), reduced the frequency of F4/80⁺CD86⁺ M1 macrophages, as determined by flow cytometry (Fig. 7 K), and significantly decreased the secretion of IL-6 and TNF-α into the culture supernatant (Fig. 7 I, J). Notably, LY294002 alone had minimal effects on basal macrophage polarization, underscoring the specific dependence of MMA-mediated effects on PI3K/Akt activation. 8. Downregulation of donor kidney MUT is correlated with aggravated acute kidney injury To extend our mechanistic findings to a clinically relevant setting, we examined methylmalonyl-CoA mutase (MUT) expression in human renal allografts subjected to ischemia–reperfusion during transplantation. Biopsy samples were collected from two groups of recipients: those who developed delayed graft function (DGF), defined as the need for dialysis within the first week post-transplant, and those with stable function (ST). Immunohistochemical staining and Western blotting demonstrated that MUT expression was markedly lower in donor kidneys from the DGF group than in those from the ST group (Fig. 8 A). Quantitative densitometry revealed an average reduction in MUT protein levels in DGF samples. Morphological analysis further revealed that MUT staining, which is normally strong in proximal tubules, was faint or patchy in DGF biopsies, particularly in regions showing structural injury. Clinical correlations supported the functional importance of MUT downregulation. Patients receiving grafts with low MUT expression exhibited significantly worse renal function recovery during the first postoperative week, as indicated by persistently elevated serum creatinine levels and blood urea nitrogen (Fig. 8 B, C). Moreover, the incidence of DGF was substantially greater in the low-MUT group (Fig. 8 D). Receiver operating characteristic (ROC) curve analysis revealed that MUT expression in donor kidneys had predictive value for DGF occurrence, with an area under the curve (AUC) of 0.78 (Fig. 8 E). These findings suggest that MUT could serve as a biomarker of donor kidney quality. Discussion In this study, we identified methylmalonic acid (MMA) as a novel ferroptosis-associated metabolite that mediates crosstalk between dying tubular epithelial cells and immune cells, thereby exacerbating AKI in the context of IRI. Our findings demonstrate that ferroptotic renal tubular cells actively release MMA and that this metabolite acts as a paracrine “danger signal” to promote proinflammatory macrophage activation. This discovery expands the emerging paradigm of cell death-induced metabolite signaling and provides new insights into how ferroptosis contributes to tissue injury beyond cell autonomous effects. One of the key results of our work is the specific upregulation of MMA in the extracellular milieu of ferroptotic cells. Using two distinct ferroptosis inducers (RSL3 and erastin) in HK-2 tubular cells, we observed marked decreases in GPX4 and SLC7A11 expression (confirming ferroptosis induction) accompanied by significant MMA accumulation in culture supernatants. Importantly, this effect was not replicated in cells undergoing apoptosis or necroptosis—neither of those cell death modalities led to elevated MMA release. Thus, MMA appears to be uniquely associated with ferroptotic cell death. To ensure that MMA release was not merely due to nonspecific membrane rupture, we carefully titrated the concentrations of RSL3 and erastin to induce ferroptosis while keeping > 80% of the cell membranes intact (preventing widespread necrotic leakage). Under these sublytic conditions, the levels of intracellular Fe^2 + and lipid peroxides (hallmarks of ferroptosis) were significantly elevated, yet the cells largely maintained membrane integrity, suggesting that MMA release is a regulated event rather than merely a consequence of membrane destruction. This observation is in agreement with prior reports on apoptotic cells, where metabolites are released through specific channels instead of random leakage[ 11 ]. Similarly, our data suggest that ferroptotic cells may possess a “metabolite secretome” of their own. Indeed, a previous study in a renal IRI model revealed that the pannexin 1 channel is involved in ferroptosis execution[ 15 ], suggesting that PANX1 or other conduits could be involved in the release of small metabolites such as MMA during ferroptosis. MMA itself is a well-known metabolic intermediate, and its accumulation is most prominently recognized in inherited methylmalonic acidemia caused by deficiency of the mitochondrial enzyme methylmalonyl-CoA mutase (MUT) or its cofactor vitamin B_12[ 23 ]. In those genetic or nutritional disorders, elevated MMA leads to systemic complications, including renal failure and immune dysfunction[ 24 ]. Our results reveal a previously unappreciated acute scenario of MMA accumulation: an IRI setting in which ferroptosis leads to transient functional MUT impairment. We found that both RSL3 treatment and erastin treatment markedly downregulated MUT expression in tubular cells in vitro, and similarly, renal MUT expression was suppressed after IRI in vivo. Notably, administering the ferroptosis inhibitor Fer-1 preserved MUT expression and prevented the increase in MMA levels post-IRI. These findings suggest that ferroptotic stress interferes with methylmalonate metabolism, likely through inactivation or downregulation of MUT, leading to acute MMA accumulation. The mechanism by which ferroptosis affects MUT could involve oxidative damage to the enzyme or broader metabolic reprogramming—an intriguing area for future investigation. Nevertheless, it is clear that ferroptotic cell death creates a metabolic byproduct (MMA) that is normally tightly regulated, thereby enriching the extracellular space with a potentially bioactive metabolite. Functionally, we discovered that MMA release is not a benign bystander event but rather has significant pathophysiological effects. An increase in MMA levels in the context of IRI translated to worse kidney injury outcomes. Compared with control mice, mice administered exogenous MMA prior to IRI presented higher peak serum creatinine levels and blood urea nitrogen levels, indicating aggravated acute kidney dysfunction. Histologically, compared with controls with the same IRI insult, MMA-treated mice had more severe tubular damage, including greater tubular epithelial cell loss, denuded basement membranes, tubular dilation, and cast formation. Additionally, the expression of NGAL (a sensitive injury marker) in the kidney was further increased by MMA. These data establish that MMA can potentiate IRI-induced AKI. Mechanistically, our results suggest that the immune system, particularly macrophages, is the primary mediator of the detrimental effects of MMA. We observed that MMA administration led to a significant increase in proinflammatory M1 macrophage infiltration in post-IRI kidneys, along with elevated local and systemic levels of IL-6 and TNF-α. To directly test the role of macrophages, we used clodronate liposome to deplete macrophages in vivo. Strikingly, macrophage depletion almost completely abrogated the additional injury caused by MMA; compared with control mice, MMA-treated, macrophage-depleted mice no longer showed worsened renal function or heightened NGAL expression, and the exacerbation of tubular cell death and inflammation induced by MMA was largely reversed. These results clearly indicate that MMA aggravates AKI predominantly by acting on macrophages and enhancing inflammatory responses. Our in vitro and adoptive transfer experiments provide further evidence for the role of MMA in modulating the macrophage phenotype. In cultured RAW264.7 macrophages, MMA exposure alone was sufficient to skew polarization toward an M1-like state, as evidenced by increased expression of M1 markers (inducible nitric oxide synthase (iNOS), TNF-α, and IL-6) and increased secretion of IL-6 and TNF-α. When MMA treatment was combined with a low-dose LPS stimulus, the effect was synergistic: MMA preconditioning significantly increased LPS-induced M1 polarization. These findings suggest that MMA not only directly drives macrophage activation but also “prime” macrophages to respond more vigorously to other inflammatory cues. Consistently, in vivo adoptive transfer of bone marrow-derived macrophages (BMDMs) demonstrated that MMA-treated BMDMs acquired a pronounced proinflammatory phenotype. In IRI mice, MMA-pretreated BMDMs preferentially homed to the injured kidney and significantly increased the proportion of F4/80^+CD86^+ M1 macrophages in the tissue. Compared with mice that received naive BMDMs, those that received MMA-exposed BMDMs had higher renal IL-6 and TNF-α levels and greater kidney damage and cell death. Together, these results establish a cause-and-effect link: MMA is capable of reprogramming macrophages toward the M1 phenotype, and these MMA-primed macrophages, in turn, intensify tissue injury in IRI. At the molecular level, we identified the PI3K/Akt/NF-κB pathway as a critical signaling axis through which MMA exerts its proinflammatory effect on macrophages. Transcriptomic analysis of MMA-stimulated macrophages revealed enrichment of pathways related to PI3K-Akt signaling. We confirmed that MMA stimulation led to robust phosphorylation of PI3K, Akt, and the NF-κB p65 subunit in macrophages, indicating the activation of this pathway. The PI3K/Akt pathway is well known to regulate macrophage survival, proliferation, and polarization[ 25 , 26 ], in part by activating NF-κB, which drives the transcription of numerous inflammatory genes[ 25 , 27 – 29 ]. In our study, pharmacologic inhibition of PI3K/Akt signaling with LY294002 significantly attenuated MMA-induced M1 polarization; LY294002-treated macrophages showed blunted upregulation of TNF , IL6 , and iNOS transcripts and secreted markedly lower levels of TNF-α and IL-6 in response to MMA. These findings confirm that the proinflammatory effects of MMA on macrophages are largely mediated by PI3K/Akt and its downstream target NF-κB. Notably, NF-κB is a central hub for M1 macrophage activation[ 30 ], and our data suggest that MMA is an upstream trigger of this hub. How MMA activates PI3K/Akt remains unclear. We hypothesize that MMA accumulation could perturb cellular metabolism, perhaps through the accumulation of methylmalonyl-CoA and related metabolites that interfere with normal TCA cycle flux, leading to secondary signals (such as altered AMP/ATP ratios or ROS generation) that engage PI3K/Akt. Alternatively, cell-surface receptors or sensors for MMA may exist. Although no dedicated MMA receptor is known, it is interesting to consider parallels with succinate, another metabolic acid. Succinate can signal via its G-protein coupled receptor SUCNR1 (GPR91) on immune cells to promote inflammation and macrophage chemotaxis[ 31 , 32 ]. Some studies have shown that succinate-SUCNR1 interactions exacerbate inflammatory responses in tissues[ 33 , 34 ]. It remains to be seen whether MMA may be detected by a similar pattern recognition mechanism or if it primarily acts intracellularly once it is taken up by macrophages. Our observation that MMA increases intracellular ROS and inflammatory cytokines in macrophages (akin to effects observed in neural cells[ 35 – 37 ]) suggests an interplay between metabolic redox stress and classical inflammatory signaling. Further work is warranted to elucidate the precise sensing mechanism of MMA in immune cells. Our findings contribute to a broader understanding of the “metabolic language” of cell death. Our findings align with and extend the concept introduced by Medina et al. that dying cells release metabolites to influence their environment[ 12 ]. However, there is a striking contrast in outcomes: whereas apoptotic cells predominantly emit anti-inflammatory, proresolving metabolites to facilitate orderly tissue turnover[ 38 ], ferroptotic cells (as exemplified by MMA release) appear to do the opposite—they create a metabolic milieu that amplifies inflammation and tissue injury. This dichotomy likely reflects the distinct physiological roles of these death processes. Apoptosis occurs during homeostatic turnover and development, where it is advantageous for quelling inflammation[ 38 ]. Ferroptosis, on the other hand, is often associated with pathological stress (e.g., severe oxidative injury) and may serve as a trigger for immune activity. In evolutionary terms, inflammatory signals from ferroptosis may help recruit immune cells to sites of damage or infection. Unfortunately, sterile injury, such as IRI, can lead to collateral tissue damage. Our work provides direct evidence of such a mechanism in that a metabolite produced from disrupted metabolism in ferroptotic cells can act as an alarm signal that drives maladaptive inflammation. Clinical implications The clinical implications of our study are noteworthy. The severity of donor kidney acute injury is strongly associated with the incidence of delayed graft function (DGF) after transplantation. Grafts with more severe AKI are less capable of functional recovery, thereby increasing the risk of DGF. In kidney transplantation, IRI is an unavoidable event, especially in donations after circulatory death (DCD). DCD donor kidneys experience prolonged warm ischemia and are at high risk of delayed graft function (DGF). Indeed, the DGF incidence in DCD kidney transplants is approximately double that of standard-criteria brain-dead donors (approximately 38–49% vs. approximately 20%)[ 39 ]. Our analysis of transplant biopsy samples revealed that compared with those with immediate graft function, donor kidneys that continued on to develop DGF had significantly lower MUT expression. These findings suggest that an impaired capacity to metabolize MMA (reflected by low MUT levels) may predispose grafts to worsened ischemic injury and delayed recovery. In other words, robust metabolic handling of methylmalonyl-CoA could be a protective factor, whereas its deficiency exacerbates injury, which is consistent with our experimental data. Moreover, we found that MUT downregulation in donor kidneys correlated with poorer early posttransplant renal function and a greater likelihood of DGF. Preliminary ROC analysis indicated that the donor MUT expression level has prognostic value for DGF, suggesting that it could be developed as a biomarker. While these clinical observations need validation in larger cohorts, they underscore the relevance of the ferroptosis-MUT-MMA axis in real-world IRI scenarios. It also prompts speculation on potential therapeutic interventions. For example, supplementation of vitamin B12 (to maximize MUT activity) or other metabolic therapies may reduce IRI severity. Moreover, whether ferroptosis inhibitors or specific MMA scavengers administered during organ preservation or immediately after reperfusion could improve outcomes in DCD transplants remains unknown. These are exciting questions for future translational research. In our study, the administration of vitamin B₁₂ or L-carnitine, two agents clinically used to reduce MMA levels in patients with methylmalonic acidemia by enhancing MUT activity, failed to achieve significant therapeutic benefits in a murine IRI model. This lack of efficacy may reflect model-specific differences and species-related variability between mice and humans. Nevertheless, these findings underscore the potential value of developing pharmacological strategies directly targeting MUT to lower MMA levels, which may represent a promising therapeutic approach for IRI. In summary, our study provides the first evidence that ferroptotic cells can release a metabolite signal (MMA) that actively modulates the immune response in AKI. We demonstrated that ferroptosis-induced MMA release drives macrophages toward an M1 proinflammatory phenotype via the PI3K/Akt/NF-κB pathway, thereby exacerbating kidney injury. These findings reveal that ferroptosis is not only a cell-intrinsic death mechanism but also an activator of intercellular signaling and inflammation. From a therapeutic standpoint, our work suggests multiple potential targets—from blocking ferroptosis itself to intercepting the activity or production of MMA or modulating macrophage responses. Given the urgent clinical need in AKI and transplant IRI (where no specific therapies exist to prevent DGF other than general ischemic mitigation), targeting the ferroptotic metabolite axis could be a novel strategy to improve patient outcomes. Future studies should explore the generality of our findings (e.g., whether other ferroptotic contexts or cell types release different metabolites that affect immune cells) and further dissect how MMA is sensed at the molecular level. Nevertheless, the present work provides a foundation for considering metabolic interventions in conjunction with cell death modulation as a means to curtail tissue damage in ischemic and inflammatory diseases. Abbreviations AKI acute kidney injury IRI ischemia–reperfusion injury MMA methylmalonic acid GPX4 glutathione peroxidase 4 ROS reactive oxygen species PANX1 pannexin 1 Fer-1 Ferrostatin-1 LTL Lotus tetragonolobus lectin TNF-α tumor necrosis factor-α BUN blood urea nitrogen MUT methylmalonyl-CoA mutase BMDMs bone marrow–derived macrophages DGF delayed graft function ROC Receiver operating characteristic. Declarations Data availability The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Acknowledgements Not applicable. Funding This work was supported by the National Natural Science Foundation of China (Nos. 82070771, Nos.82300858, Nos82500926), Key Project of Natural Science Foundation of Henan Province (252300421264) and Funding for Scientiffc Research and Innovation Team of The First Afffliated Hospital of Zhengzhou University (QNCXTD2023020). Author information Huimeng Wang, Jiajia Sun, Xiaohu Li contributed equally to this work. Authors and Affiliations Department of Kidney Transplantation, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China. Huimeng Wang, Jiajia Sun, Xiaohu Li, Hongxuan Ma, Yongsheng Luo, Minghui Qin, Hao Zhang, Haodong Bian, Jinfeng Li Contributions Huimeng Wang: Investigation, Methodology, Resources, Software, Writing – original draft, Writing – review & editing. Xiaohu Li: Data curation, Formal analysis, Writing – original draft. Hongxuan Ma: Data curation, Formal analysis, Methodology. Jiajia Sun: Project administration, Formal analysis, Funding acquisition, Writing – original draft. Yongsheng Luo: Investigation, Methodology, Funding acquisition. Minghui Qin: Methodology, Software. Hao Zhang: Formal analysis. Haodong Bian: Formal analysis. Jinfeng Li: Conceptualization, Funding acquisition, Methodology, Supervision. Corresponding authors Correspondence to Jinfeng Li. Ethics declarations Conflict of interest The authors declare no competing interests. Ethics approval and consent to participate This study was approved by The First Affiliated Hospital of Zhengzhou University (Ethics Approval No. ZZU-LAC20210521[07]). Our experimental methods are performed in accordance with ethical standards of the responsible committee on human experimentation with the Helsinki Declaration of 1975. Informed written consent was obtained from either participants or their legal guardians. Consent for publication Not applicable. References Ni L, Yuan C, Wu X. Targeting ferroptosis in acute kidney injury. Cell Death Dis. 2022; 13: 182. Newton K, Dugger DL, Maltzman A, Greve JM, Hedehus M, Martin-McNulty B, et al. RIPK3 deficiency or catalytically inactive RIPK1 provides greater benefit than MLKL deficiency in mouse models of inflammation and tissue injury. Cell Death Differ. 2016; 23: 1565-76. Linkermann A, Bräsen JH, Darding M, Jin MK, Sanz AB, Heller JO, et al. Two independent pathways of regulated necrosis mediate ischemia-reperfusion injury. 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Locke JE, Segev DL, Warren DS, Dominici F, Simpkins CE, Montgomery RA. Outcomes of Kidneys from Donors After Cardiac Death: Implications for Allocation and Preservation. American Journal of Transplantation. 2007; 7: 1797-807. Table 1 Table1 Primers Primer sequence iNOS2-F CACCAAGCTGAACTTGAGCG iNOS2-R CGTGGCTTTGGGCTCCTC TNFα-F CTTCTGTCTACTGAACTTCGGG TNFα-R CAGGCTTGTCACTCGAATTTTG IL-6-F CAAAGCCAGAGTCCTTCAGAG IL-6-R MUT-F MUT-R GTCCTTAGCCACTCCTTCTG ACCCAGAGGACCTTATATGGC CTTCGGGTAAGTCCAGAGTATCT MCL-1-F MCL-1-R Vegfa-F Vegfa-R PIK3AP1-F PIK3AP1-R AAAGGCGGCTGCATAAGTC TGGCGGTATAGGTCGTCCTC CTGCCGTCCGATTGAGACC CCCCTCCTTGTACCACTGTC GTCCCGGATGCCTCTTTCTC CACAAGTCATTTCCTGCCAGT Additional Declarations No competing interests reported. Supplementary Files supplementaryfigures.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 11 May, 2026 Reviews received at journal 29 Apr, 2026 Reviewers agreed at journal 19 Apr, 2026 Reviewers invited by journal 15 Apr, 2026 Editor assigned by journal 01 Apr, 2026 Submission checks completed at journal 01 Apr, 2026 First submitted to journal 29 Mar, 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-9256951","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626497886,"identity":"eb0a3562-e224-416e-8fd0-867b2078a81b","order_by":0,"name":"huimeng wang","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"huimeng","middleName":"","lastName":"wang","suffix":""},{"id":626497892,"identity":"99976a26-6bed-45e8-b094-463e316c1245","order_by":1,"name":"jiajia Sun","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"jiajia","middleName":"","lastName":"Sun","suffix":""},{"id":626497896,"identity":"a0ade268-e209-4837-8aa9-debe7176ff8c","order_by":2,"name":"Xiaohu Li","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Xiaohu","middleName":"","lastName":"Li","suffix":""},{"id":626497897,"identity":"e7ae84df-8aae-4068-a046-db6139b3f5d3","order_by":3,"name":"yongsheng Luo","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"yongsheng","middleName":"","lastName":"Luo","suffix":""},{"id":626497898,"identity":"a7298707-f9dd-439d-9cf8-33273bbef6f8","order_by":4,"name":"hongxuan Ma","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"hongxuan","middleName":"","lastName":"Ma","suffix":""},{"id":626497899,"identity":"10c698b4-e59e-42b4-a32e-2013c9e9394e","order_by":5,"name":"minghui Qin","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"minghui","middleName":"","lastName":"Qin","suffix":""},{"id":626497903,"identity":"46024bb4-d500-4d56-a7d3-dce74fb2dc0b","order_by":6,"name":"hao Zhang","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"hao","middleName":"","lastName":"Zhang","suffix":""},{"id":626497906,"identity":"47d8a7a3-fa2c-4c67-b7c1-c65b2f1103fe","order_by":7,"name":"haodong Bian","email":"","orcid":"","institution":"Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"haodong","middleName":"","lastName":"Bian","suffix":""},{"id":626497907,"identity":"c40e768a-0561-44bc-af19-ee8dd77171b0","order_by":8,"name":"jingfeng Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyElEQVRIiWNgGAWjYBAC9gYGxgMJPHJyEC4bEVp4DjAwALUYG5OohYHBOLGBeC3shx8ceCBjkD6//4wBw4eywwz8sxsIaOFJMwA6zCC3seGMAeOMc4cZJO4cwK/FXoIH5Jc/uc2MPQbMvG2HGQwkEgjYAtFikM7GzGPA/JcULQk8bEAtjERpgfrFcAYPW8HBnnPpPBI3CGlhP/zw4c8eA3n5/sMbH/wos5bjn0FACxgw9kDoAyAziFAPAj+IVDcKRsEoGAUjEwAAHCA8KoeYcZgAAAAASUVORK5CYII=","orcid":"","institution":"Zhengzhou University","correspondingAuthor":true,"prefix":"","firstName":"jingfeng","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2026-03-29 07:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9256951/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9256951/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107637146,"identity":"a49aadca-e0da-4c44-b411-f8699fcc6379","added_by":"auto","created_at":"2026-04-23 12:41:20","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1522295,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFerroptosis induces the selective secretion of methylmalonic acid in HK-2 cells. \u003c/strong\u003e(A and B) Western blot analysis of GPX4 and SLC7A11 expression in HK-2 cells treated with two different concentrations of the ferroptosis inducers RSL3 and erastin. (C) Lipid ROS and intracellular Fe²⁺ levels in HK-2 cells treated with 5 μM erastinand 2 μM RSL3 were analyzed using the Liperfluo fluorescent probe and FerroOrange assay. Lipid ROS are shown in green, and Fe²⁺ is shown in red. Scale bar: 50 μm. Quantification of fluorescence intensity revealedsignificantly increased lipid ROS and intracellular Fe²⁺ levels compared with those in the vehicle control group. (D) Calcein/PI staining of HK-2 cells treated with 5 μM erastinand 2 μM RSL3. Calcein (green) indicates live cells, and PI (red) indicates dead cells. Scale bar: 50 μm. (E-H) Heatmap and volcano plot showing differentially altered metabolites in the supernatant of HK-2 cells treated with 5 μM erastinand 2 μM RSL3, and volcano plot of differentially abundant metabolites in POS mode. The x-axis represents the log₂ fold change in metabolite abundance relative to that of the control, and the y-axis represents the -log₁₀ P value from the t test. Dashed vertical lines indicate the screening threshold for differentially abundant metabolites. Red dots represent upregulated metabolites (VIP ≥ 1 and p \u0026lt; 0.05, FC \u0026gt; 1.2), and green dots represent downregulated metabolites (VIP ≥ 1 and p \u0026lt; 0.05, FC \u0026lt; -0.83). (I) Venn diagram showing overlapping secreted metabolites increased in the two ferroptosis induction models. (J, K) Heatmap of the increased levels of secreted metabolites in the two ferroptosis models, ranked according to fold change. The dataare presented as the mean ± SD;n = 3 for all the groups. ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, *\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9256951/v1/a73117debe82a345f29f431c.jpeg"},{"id":107637148,"identity":"27ae7f63-31e5-4f4b-b52b-a0c93b668b8d","added_by":"auto","created_at":"2026-04-23 12:41:21","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1656410,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMUT suppression links ferroptosis to MMA accumulation in vivo. \u003c/strong\u003e(A) Schematic diagram of the experimental groups. (B and C) Serum creatinine and blood urea nitrogen (BUN) levels across different groups (n = 5). (D) Western blot analysis and quantification of NGAL expression in renal tissues (n = 3). (E and F) Representative H\u0026amp;E and PAS staining of kidney sections and tubular injury scores (scale bar, 100 μm; n = 3). (G and H) ELISA analysis of MMA levels in mouse serum and kidney tissues. Each group contained five mice, and each sample was assayed in triplicate wells. (n = 5). (I) Schematic illustration of the metabolic pathway of MMA.(J and K) Western blot and qPCR analysesof MUT expression in two distinct ferroptosis models (n = 3). (L and M) Western blot and qPCR analysis of MUT expression in a mouse renal ischemia‒reperfusion injury (IRI) model and in IRI mice following FER-1 treatment. (N and O) Representative immunofluorescence staining of MUT (red), LTL (green), GPX4 (white) and DAPI (blue) in mouse kidneys after renal IRI and IRI following FER-1 treatment. (scale bar: 50 μm; n = 3). The dataare presented as the mean ± SD. ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, *\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9256951/v1/e2c6b4a8dfabcbcbed510220.jpeg"},{"id":107637150,"identity":"d5227e20-fce8-440a-a36b-7c3f706feb28","added_by":"auto","created_at":"2026-04-23 12:41:21","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1101206,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFerroptosis-derived MMA exacerbates renal ischemia–reperfusion injury. \u003c/strong\u003e(A) Schematic diagram of the experimental groups. (B and C) Serum creatinine and blood urea nitrogen (BUN) levels across different groups (n = 5). (D) Western blot analysis of NGAL expression in renal tissues (n = 3). (E) Representative H\u0026amp;E and PAS staining of kidney sections and tubular injury scores (scale bar, 100 μm; n = 3). (F) TUNEL staining for cell death in kidney tissues from different groups after IRI. Quantification of TUNEL-positive cells is shown in the right panel (scale bar, 100 μm; n = 3). (G) Immunofluorescence staining of F4/80 (green), CD86 (red), and nuclei (DAPI, blue) in kidney tissues from IRI mice. Quantification of F4/80⁺CD86⁺ cells is shown in the right panel (scale bar, 100 µm;n = 3). (H) Western blot analysis of the expression of IL-6 and TNF-α in renal tissues (n = 3). (I and J) ELISA analysis of TNF-α and IL-6 levels in mouse serum. Each group contained five mice, and each sample was assayed in triplicate wells. The data are presented as the mean ± SD. The dataare presented as the mean ± SD. ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, *\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9256951/v1/6f3de868cf6bf2b45a88447c.jpeg"},{"id":107637179,"identity":"7665c415-fadf-4490-a967-910fa3ae6dd5","added_by":"auto","created_at":"2026-04-23 12:41:25","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":613821,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMMA directly drives M1 macrophage polarization in vitro. \u003c/strong\u003e(A) Flow cytometry analysis of M1 marker expression (F4/80 and TNF-α) in macrophages with or without MMA stimulation (n = 3). (B) qPCR analysis of iNOS, IL-6, and TNF-α gene expression in macrophages (n = 3). (C) Western blot analysis of IL-6 and TNF-α expression in macrophages (n = 3). (D and E) ELISA analysis of IL-6 and TNF-α levels in cell culture supernatants from each group (n = 3). (F) Cell viability of Raw264.7 cells treated with different concentrations of MMA (n = 3). The dataare presented as the mean ± SD. ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, **\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.01, *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9256951/v1/797d5e1560137cd3cf0e5467.jpeg"},{"id":107637176,"identity":"6e52f406-a228-4f90-8bf7-3b4516f45415","added_by":"auto","created_at":"2026-04-23 12:41:24","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1559249,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMacrophage depletion abrogates MMA-induced renal injury. \u003c/strong\u003e(A and B) Serum creatinine and blood urea nitrogen (BUN) levels across different groups (n = 5). (C) Western blot analysis of NGAL expression in renal tissues (n = 3). (D) Representative H\u0026amp;E and PAS staining of kidney sections and tubular injury scores (scale bar, 100 μm; n = 3). (E) TUNEL staining for cell death in kidney tissues from different groups after IRI. Quantification of TUNEL-positive cells is shown in the right panel (scale bar, 100 μm; n = 3). (F) Analysis of the expression of IL-6 and TNF-α in renal tissues (n = 3). (G and H) ELISA analysis of TNF-α and IL-6 levels in mouse serum. Each group contained five mice, and each sample was assayed in triplicate wells (n = 5). The data are presented as the mean ± SD. ****\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.0001, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9256951/v1/ba320ab019e3303d3a2e5598.jpeg"},{"id":107637046,"identity":"4bf726c6-a997-49bf-a45d-14d54e5d9c1c","added_by":"auto","created_at":"2026-04-23 12:41:14","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1600552,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMMA-primed BMDMs aggravate IRI through enhanced M1 polarization. \u003c/strong\u003e(A) Immunofluorescence staining of F4/80 (green), CD86 (red), and nuclei (DAPI, blue) in kidney tissues from IRI mice. Quantification of F4/80⁺CD86⁺ cells is shown in the right panel (scale bar, 100 µm; n = 3). (B) Western blot analysis of the expression of IL-6 and TNF-α in renal tissues (n = 3). (C and D) ELISA analysis of TNF-α and IL-6 levels in mouse serum (n = 5). (E and F) Serum creatinine and blood urea nitrogen (BUN) levels across different groups (n = 5). (G) Analysis of NGAL expression in renal tissues (n = 3). (H) Representative H\u0026amp;E and PAS staining of kidney sections and tubular injury scores (scale bar, 100 μm; n = 3). (I) TUNEL staining for cell death in kidney tissues from different groups after IRI. Quantification of TUNEL-positive cells is shown in the right panel (scale bar, 100 μm; n = 3). The dataare presented as the mean ± SD. ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, *\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9256951/v1/cd441aef7d473ad360389ce2.jpeg"},{"id":107637142,"identity":"6d7dbb04-276c-40c0-9b5a-20a20571cb1a","added_by":"auto","created_at":"2026-04-23 12:41:19","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":928924,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMMA promotes M1 polarization via PI3K/Akt/NF-κB signaling. \u003c/strong\u003e(A and B) Heatmap and volcano plot showing differentially expressed genes in RAW264.7 cells stimulated with LPS alone or with LPS plus MMA. (C and D) KEGG and GSEA of differentially expressed genes from the transcriptomic data. (E) Heatmap of differentially expressed genes enriched in the PI3K–AKT signaling pathway based on transcriptomic profiling, together with fold-change analysis of the indicated genes.(F) qPCR analysis of \u003cstrong\u003ePIK3AP1, Vegfa,\u003c/strong\u003eand\u003cstrong\u003e Mcl-1 \u003c/strong\u003eexpression in macrophages(n = 3). (G) Western blot analysis of PI3K (p-PI3K/PI3K), AKT (p-AKT/AKT) and P65 (p-P65/P65) phosphorylation levels in macrophagestreated with LPS with or without MMA pretreatment (n = 3). (H) qPCR analysis of iNOS, IL-6, and TNF-α gene expression in macrophages from different groups following treatment with the PI3K phosphorylation inhibitor LY294002 (n = 3). (I and J) ELISA analysis of IL-6 and TNF-α levels in cell culture supernatants from each group (n = 3). (K) Flow cytometry analysis of M1 marker expression (F4/80 and TNF-α) in macrophages with or without LY294002 pretreatment. Quantification of the mean fluorescence intensity (MFI) for F4/80 and TNF-α is shown in the right panel (n = 3). The dataare presented as the mean ± SD. ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, *\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9256951/v1/f057123464a7299bd040ae15.jpeg"},{"id":107637141,"identity":"5cee3fbc-bc85-4177-bab5-7a2620c81250","added_by":"auto","created_at":"2026-04-23 12:41:18","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":173993,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe downregulation of thedonor kidney MUT is correlated with delayed graft function\u003c/strong\u003e. (A and B) Representative immunofluorescence staining of MUT in donor kidneys from the DGF (n = 18) and ST (n = 20) groups (scale bars: 50 μm), with quantification based on MUT fluorescence intensity. (C and D) Spearman correlation between the MUT fluorescence intensity and recipient serum creatinine (Scr) and blood urea nitrogen (BUN) levels at postoperative week 1. (E) DGF incidence stratified by MUT expression levels in donor kidneys. (F) ROC curve analysis of the ability of donor USAG-1 expression to predictDGF. The dataare presented as the mean ± SD. ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, *\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9256951/v1/ef084f029824188f3214c0d7.jpeg"},{"id":107705975,"identity":"2b95fc2b-3b7a-4f0d-9a41-3b421c27b533","added_by":"auto","created_at":"2026-04-24 09:16:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9552088,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9256951/v1/2ff294dc-40db-4bf5-a75e-bcb2b596270a.pdf"},{"id":107637143,"identity":"a03bd208-1ce0-4de8-a707-ae6c096e819a","added_by":"auto","created_at":"2026-04-23 12:41:19","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":720016,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-9256951/v1/22f5854ec4210b3ac86d998d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Methylmalonic Acid as a Ferroptosis-Derived Danger Signal: Activation of the PI3K–NF-κB Pathway Drives M1 Macrophage Polarization in Renal Ischemia–Reperfusion Injury","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIschemia\u0026ndash;reperfusion injury (IRI) is a leading cause of acute kidney injury (AKI) following procedures such as kidney transplantation and cardiac surgery[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Renal tubular cell death during IRI was initially attributed mainly to apoptosis, and later studies highlighted necroptosis as a major contributor[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Recently, ferroptosis\u0026mdash;a distinct form of regulated cell death characterized by iron-dependent lipid peroxidation\u0026mdash;has emerged as a critical mechanism of tubular cell death in IRI[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Ferroptosis was first defined in 2012 and involves the collapse of cellular antioxidant defenses (notably glutathione peroxidase 4, GPX4) and the unchecked accumulation of lipid reactive oxygen species (ROS)[\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Morphologically and biochemically, ferroptosis is nonapoptotic and often associated with mitochondrial shrinkage and loss of membrane integrity, which can trigger inflammation[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In various AKI models, ferroptosis has been shown to drive tissue damage; for example, pharmacological ferroptosis inhibitors such as ferrostatin-1 significantly alleviate renal dysfunction and histological injury in IRI[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] and other forms of AKI[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. These findings underscore ferroptosis as a pivotal early event in IRI pathogenesis.\u003c/p\u003e \u003cp\u003eWhile the direct cytotoxic role of ferroptosis in tissue injury has been established, its potential to influence the microenvironment via released signaling molecules remains poorly understood. Cells undergoing regulated death are being increasingly recognized not as inert entities but as active communicators. A landmark study demonstrated that apoptotic cells, despite maintaining plasma membrane integrity, release a suite of specific metabolites that act as \u0026ldquo;find-me\u0026rdquo; signals, thereby modulating neighboring cell behavior[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This apoptotic metabolite secretome is not a passive leakage of cellular contents but rather a caspase dependent, regulated process mediated by pannexin 1 (PANX1) channels[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In contrast, little is known about whether ferroptotic cells similarly emit metabolite signals and, if so, whether these signals contribute to the proinflammatory milieu of IRI. Recent evidence, however, indicates that ferroptotic cells may have a more complex secretory profile. In particular, Yapici and colleagues generated an atlas of ferroptosis-induced secretomes, demonstrating that ferroptotic cells release not only DAMPs but also a broad spectrum of proteins, lipids, and metabolites capable of shaping immune responses and intercellular communication. These findings suggest that ferroptosis is not merely destructive but may also convey context-dependent signals to the tissue microenvironment.\u003c/p\u003e \u003cp\u003eMacrophages are central mediators of inflammation and repair in AKI. Classically activated M1 macrophages secrete proinflammatory cytokines and accelerate acute tissue damage[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], whereas alternatively activated M2 macrophages are anti-inflammatory and support tissue repair[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Macrophage polarization is known to be influenced by metabolic cues in the microenvironment. For example, succinate that accumulates during inflammatory macrophage activation can stabilize HIF-1α and drive a proinflammatory phenotype, in part by enhancing glycolysis and ROS production[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Conversely, metabolites such as itaconate or α-ketoglutarate can skew macrophages toward anti-inflammatory, reparative states[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Such findings highlight a paradigm wherein metabolites act as messengers that shape immune cell function. We therefore hypothesized that metabolites released by ferroptotic tubular cells may skew infiltrating macrophages toward an M1 proinflammatory phenotype, thereby linking tubular cell death to immune-mediated injury in IRI.\u003c/p\u003e \u003cp\u003eTo test these hypotheses, we induced ferroptosis in human proximal tubule HK-2 cells using two complementary inducers\u0026mdash;RSL3 (a direct GPX4 inhibitor) and erastin (a system Xc\u0026ndash; cystine transporter inhibitor)\u0026mdash;and performed untargeted metabolomics on cell culture supernatants. We identified methylmalonic acid (MMA) as a markedly and consistently elevated metabolite specifically released during ferroptotic cell death. Notably, the level of MMA was not elevated in the supernatants of cells undergoing apoptosis or necroptosis, suggesting that MMA is a ferroptosis-associated secreted metabolite. Our experiments revealed that serum and kidney tissue MMA levels increase significantly after IRI and that this increase is blunted by the ferroptosis inhibitor Fer-1, suggesting that ferroptosis is linked to MMA accumulation in ischemic AKI. Furthermore, we found that MMA exposure polarizes macrophages toward the M1 phenotype and exacerbates kidney injury by amplifying inflammation. Mechanistically, we observed that MMA activates the PI3K/Akt/NF-κB signaling pathway in macrophages, providing a molecular basis for its proinflammatory activity. In summary, our study reveals a novel ferroptosis-triggered metabolic signal (MMA) that mediates crosstalk between dying tubular cells and immune cells. These findings shed new light on AKI pathogenesis and suggest potential therapeutic targets (such as metabolic modulation or ferroptosis inhibition) to mitigate IRI-induced kidney damage.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAntibodies\u003c/h2\u003e \u003cp\u003eThe following antibodies were purchased from commercial vendors: rabbit anti-GPX4 (1;2000, Abways, CY6959), rabbit anti-SLC7A11 (1;1000, Abways, CY7046), rabbit anti-GAPDH (1;5000, Proteintech, 60004-1-Ig), rabbit anti-MUT (1;2000, Proteintech, 17034-1-AP), rabbit anti-NGAL (1;5000, Proteintech, 26991-1-AP), rabbit anti-IL6 (1;1000. Proteintech, 21865-1-AP), rabbit anti-TNF-α (1;1000, Proteintech, 17590-1-AP), rabbit anti-NF-κB p65 (1;2000, Abways, AB3449), rabbit anti-phospho-NF-κB p65 (ser536) (1;100, Abways, CY5095), rabbit anti-PI3K (1;500, Abways, CY3406), rabbit anti-phospho-PI3K p85 alpha (Tyr607) (1;1000, Affinity, AF3241), rabbit anti-phospho-Akt (Ser473) (1;1000, Abways, CY6569), and rabbit anti-Akt (1;1000, Abways, CY5561).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePatients\u003c/h3\u003e\n\u003cp\u003eThis study included 18 recipients who developed DGF after kidney transplantation from DCDs at the Department of Kidney Transplantation, The First Affiliated Hospital of Zhengzhou University, as the study group. Additionally, 20 recipients with stable graft function (ST) after kidney transplantation during the same period were randomly selected as controls. Zero-time biopsy samples of donor kidneys were obtained, and clinical history and follow-up data were collected. This clinical study involving clinical specimens was approved by the Institutional Review Board of the First Affiliated Hospital of Zhengzhou University in Zhengzhou, China (Approval Number: 2025-KY-0462-001) and complied with the ethical principles outlined in the 1975 Declaration of Helsinki.\u003c/p\u003e\n\u003ch3\u003eAnimals\u003c/h3\u003e\n\u003cp\u003eMale C57BL/6 mice (6\u0026ndash;8 weeks old) were purchased from Weitong Lihua Laboratory Animal Technology Co., Ltd. (Beijing, China). All the animals were maintained at constant humidity and temperature in standard facilities under specific pathogen-free conditions with free access to food and water.\u003c/p\u003e \u003cp\u003e All operations were carried out in accordance with the National Institutes of Health (NIH) guidelines for the Care and Use of Laboratory Animals and were approved by the Ethics Committee of The First Affiliated Hospital of Zhengzhou University (Ethics Approval No. ZZU-LAC20210521[07]).\u003c/p\u003e\n\u003ch3\u003eAnimal model\u003c/h3\u003e\n\u003cp\u003eRenal ischemia/reperfusion model\u003c/p\u003e \u003cp\u003eOur study examined male mice because male animals exhibit less phenotypic variability. It is unknown whether the findings are relevant for female mice. Renal IRI was induced by occluding the left renal artery with a microaneurysm clamp for 30 min, followed by 24 h of reperfusion. Immediately after left renal artery clamping, a right nephrectomy was performed to preclude compensatory renal function. Throughout the procedure, the mice were maintained on a warming pad to stabilize their core body temperature at 36.5\u0026ndash;37.0\u0026deg;C. Ferrostatin-1 (Fer-1, 5 mg/kg, ip.) and MMA (400 mg/kg, ip.), was intraperitoneally injected 15 min before IRI induction in C57BL/6 mice.\u003c/p\u003e \u003cp\u003eMacrophage depletion in a mouse model\u003c/p\u003e \u003cp\u003eThe macrophages were depleted by the application of clodronate liposomes (CLOP, 200 \u0026micro;l, i.p.). In the control group, empty liposomes (200 \u0026micro;l, iP) were administered. The efficiency of macrophage depletion was evaluated using F4-80 antibody and CD11b by flow cytometry.\u003c/p\u003e \u003cp\u003eBone Marrow Cell Isolation and Differentiation into Mature BMDMs\u003c/p\u003e \u003cp\u003eThe mice were euthanized, and their femur and tibia bones were immediately isolated, cleaned with alcohol, and placed in PBS supplemented with 2% fetal bovine serum (FBS). The ends of the bones were cut off and flushed with PBS-FBS until they were cleared of all the bone marrow. The contents were filtered through a 40-\u0026micro;m cell strainer to obtain a single-cell suspension. ACK treatment was performed to lyse red blood cells, after which the cells were resuspended in BMDM (ISCove\u0026rsquo;s modified Dulbecco\u0026rsquo;s medium\u0026thinsp;+\u0026thinsp;10% FBS\u0026thinsp;+\u0026thinsp;10 ng/mL M-CSF). Bone marrow cells were seeded in 100-mm dishes at a density of 2 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells/mL and cultured for 7 days in BMDM. The medium of fresh BMDM was changed on Day 3. Cells were analyzed by flow cytometry for the expression of the markers CD11b and F4/80 to ensure that they had differentiated into mature BMDMs. Once the maturation of these macrophages was confirmed, they were treated with MMA (5 \u0026micro;M) or vehicle (PBS) as a control for 6 h in fresh media while still attached to the culture plate. The BMDMs were harvested and counted using a TC20 automated cell counter (Bio-Rad) and resuspended in PBS for injection into mice.\u003c/p\u003e \u003cp\u003eAdoptive Transfer of Macrophages\u003c/p\u003e \u003cp\u003eMature BMDMs obtained from the culture, either untreated or treated with MMA, were injected into the mice through the tail vein at a concentration of 4 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells in 200 \u0026micro;L of PBS.\u003c/p\u003e\n\u003ch3\u003eCell culture and treatment\u003c/h3\u003e\n\u003cp\u003eHK-2 cells and RAW264.7 cells were obtained from Procell Life Science \u0026amp; Technology Co., Ltd. The HK-2 cells were maintained in Dulbecco's modified Eagle\u0026rsquo;s medium/nutrient mixture F-12 (DMEM/F12; Gibco, USA) supplemented with 10% fetal bovine serum (FBS; Clark, USA) and 1% penicillin/streptomycin antibiotics (NCM; China) and incubated at 37\u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e. To investigate the early secretory profile associated with ferroptosis, HK-2 cells were exposed to different concentrations of RSL3 (MCE, USA) or erastin (MCE, USA), and both cell and culture supernatants were collected 8 h after treatment for subsequent assays. RAW264.7 cells were treated with MMA (5 \u0026micro;M for 6 h; MCE, USA), LPS (100 ng/mL for 6 h; MCE, USA), or MMA followed by LPS (5 \u0026micro;M MMA for 6 h, subsequently exposed to 100 ng/mL LPS for an additional 6 h). For PI3K inhibition, cells were pretreated with LY294002 (10 \u0026micro;M; MCE, USA) for 12 h prior to the indicated treatments.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRenal function\u003c/h2\u003e \u003cp\u003eRenal function was assessed by measuring serum creatinine (Scr) and blood urea nitrogen (BUN) levels. Commercially available kits (#C013-2-1 for BUN, #C011-2-1 for Scr; Nanjing Jiancheng, China) were used in accordance with the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHistology\u003c/h3\u003e\n\u003cp\u003eRenal tissues were embedded in paraffin, sectioned (4 \u0026micro;m thick), and stained with hematoxylin \u0026amp; eosin (H\u0026amp;E) and periodic acid\u0026ndash;Schiff for histopathological evaluation. Tubular injury was diagnostically defined as cytolysis, brush border loss, or intraluminal cast formation. A blinded semiquantitative scoring system (grades 0\u0026ndash;4) was used to categorize injury severity by the percentage of affected tubules per field: 0, no damage; 1, \u0026lt; 20%; 2, 20\u0026ndash;40%; 3, 40\u0026ndash;60%; 4, 60\u0026ndash;80%; and 5, \u0026gt; 80%. For each sample, 10 randomly selected cortical fields (200\u0026times; magnification) were independently evaluated by two investigators, with final scores calculated as the mean value across all the fields to ensure statistical robustness.\u003c/p\u003e\n\u003ch3\u003eRT‒qPCR\u003c/h3\u003e\n\u003cp\u003eTotal RNA was isolated from cell and tissue samples using a FastPure Cell/Tissue Total RNA Isolation Kit V2 (Vazyme Biotech Co., Ltd.). Reverse transcription was subsequently performed using Hifair III 1st Strand cDNA Synthesis SuperMix for qPCR (YEASEN, China) to synthesize complementary DNA. To assess mRNA expression levels, real-time quantitative PCR was carried out using Hieff qPCR SYBR Green Master Mix (YEASEN, China). For data normalization, GAPDH mRNA expression was used as the endogenous control. The relative quantification of target gene expression was determined through comparative threshold cycle analysis using the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method. The sequences of the mRNAs used for qPCR are provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eWestern blot\u003c/h2\u003e \u003cp\u003eTotal protein was extracted from cells and tissues by lysis in RIPA lysis buffer (Beyotime, China) supplemented with protease inhibitor (Beyotime, China). Protein concentrations were quantified using a BCA assay kit. For Western blot analysis, proteins were separated by SDS‒PAGE using an Omni-Easy\u0026trade; One-Step PAGE Gel Fast Preparation Kit (Epizyme, Shanghai) and transferred onto PVDF membranes using a wet transfer system. The membranes were blocked with 5% skim milk for 2 h at room temperature and then incubated with primary antibodies at 4\u0026deg;C overnight. After being washed with TBST (3\u0026times;10 min), the membranes were probed with HRP-conjugated secondary antibodies for 1 h. After intensive washing with TBST (5\u0026times;5 min), the protein signals were visualized using enhanced chemiluminescence (ECL) reagent. All experimental reagents, including electrophoresis buffer, transfer buffer, TBST, and related solutions, were obtained from Yeasen Biotech (Shanghai).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFlow cytometry analysis\u003c/h2\u003e \u003cp\u003eAfter the different treatments were administered, BMDMs, RAW264.7 cells, and kidney tissue cells were collected using cold PBS. For surface staining, the BMDMs and RAW264.7 cells were stained with Brilliant Violet 421\u0026trade; anti-mouse CD11b (1:200, M1/70 clone, 101251, Biolegend) and FITC anti-mouse F4/80 (1:200, BM7 clone, 123108, Biolegend) antibodies for 30 min at 4\u0026deg;C. Kidney tissue cells were stained with Brilliant Violet 421\u0026trade; anti-mouse CD11b (1:200, M1/70 clone, 101251, Biolegend) and FITC anti-mouse F4/80 (1:200, BM7 clone, 123108, Biolegend), for 30 min at 4\u0026deg;C. For intracellular cytokine staining, RAW264.7 cells were stained with PE anti-mouse TNF-α (1:200,\u003c/p\u003e \u003cp\u003eMP6-XT22 clone, 506306, Biolegend) after surface staining. The stained cells were then washed twice with cold PBS and immediately analyzed by flow cytometry. Cellular subsets were sorted through CytoFLEX (Beckman, USA). Data were analyzed utilizing FlowJo Version 10.2 (FlowJo LLC, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMultiplex immunofluorescence (multi-IF)\u003c/h2\u003e \u003cp\u003eParaffin-embedded kidney tissue sections were deparaffinized in xylene and then rehydrated sequentially in 100%, 95%, 70% ethanol, and PBS buffer. For IF, the sections were blocked with 5% goat serum in PBS buffer, incubated overnight with a GPX4 antibody (1:200; Abways, CY6959) at 4\u0026deg;C and incubated with the corresponding HRP-conjugated secondary antibody for 1 h at room temperature. The sections were incubated with tyramide signal amplification (TSA) (Servicebio Technology) for 10 min at room temperature, after which antigen repair and sealing were performed again. The MUT antibody (1:200; Proteintech, 17034-1-AP), corresponding HRP-labeled antibody, and TSA were sequentially added and incubated. For colocalization analysis of MUT with the proximal tubular marker Lotus tetragonolobus lecti, renal sections previously stained for MUT were coincubated with fluorescein-conjugated Lotus tetragonolobus lectin (LTL; Vector Laboratories, FL-1321) at room temperature (RT) for 1 h. Finally, the nuclei were stained with DAPI, and the images were scanned after the slices were sealed. Multiplex immunofluorescence staining of renal macrophages was performed as described above using antibodies against F4/80 (1:200; Proteintech, 29414-1-AP) and CD86 (1:200; Thermo Fisher, 14-0862-82).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eTUNEL assay\u003c/h2\u003e \u003cp\u003eThe number of apoptotic cells was determined by TUNEL staining using a One Step TUNEL Apoptosis Assay Kit (Beyotime, Jiangsu, China), and the nuclei were stained with DAPI. Images were captured using a fluorescence microscope.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFerroOrange and lipid oxidation species (LOS) detection\u003c/h2\u003e \u003cp\u003eFerroOrange (Dojindo, F347, Japan) is a fluorescent probe that enables live-cell imaging of intracellular Fe\u003csup\u003e2+\u003c/sup\u003e. For the assay, the cells were incubated with HBSS buffer containing 1 \u0026micro;mol/L FerroOrange for 1 h at 37\u0026deg;C. After incubation, the intracellular Fe\u003csup\u003e2+\u003c/sup\u003e levels were visualized by fluorescence microscopy, and the fluorescence intensity was quantified using ImageJ software (NIH, USA).\u003c/p\u003e \u003cp\u003eLipid oxidation species (LOS) were assessed using the Lipid Peroxidation Probe BDP 581/591 C11 (Dojindo, L267, Japan) according to the manufacturer\u0026rsquo;s instructions. The fluorescence signal was captured by fluorescence microscopy, and the intensity was quantified using ImageJ software (NIH, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eCalcein/PI staining of HK-2 cells\u003c/h2\u003e \u003cp\u003eTo assess cell viability and cytotoxicity, a Calcein/PI Live/Dead Viability/Cytotoxicity Assay Kit (Beyotime Biotechnology) was used. HK-2 cells treated with different concentrations of erastin or RSL3 were cultivated after 24 h. After the incubation was complete, the cells were stained using a calcein/PI kit. The culture medium was aspirated, and the cells were gently washed once with PBS. Afterward, according to the kit\u0026rsquo;s instructions, the calcein/PI detection working solution was prepared and added to each well. The cells were incubated at 37\u0026deg;C in the dark for 30 min. After incubation, cell viability and cytotoxicity were assessed by observing fluorescence under a fluorescence microscope (NIH, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eCCK-8 assay\u003c/h2\u003e \u003cp\u003eThe macrophage cultured under the relevant conditions for 24 were treated by 10 \u0026micro;L CCK-8 solution (Solarbio Technology, Beijing, China) for 2 h at 37\u0026deg;C. Then the optical density (OD) values of wells were monitored by a microplate reader (Spark, Tecan Group Ltd., Switzerland). Three repetitive wells were set up for each group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eELISA\u003c/h2\u003e \u003cp\u003eThe concentrations of methylmalonic acid (MMA) and inflammatory cytokines in the plasma and cell culture supernatant were determined using enzyme-linked immunosorbent assay (ELISA) kits. Blood samples and cell supernatants were collected and centrifuged at 1,000 \u0026times; g for 10 min. For renal MMA measurement, kidney tissues were rinsed with ice-cold 1\u0026times; PBS to remove residual blood, homogenized in 10% ice-cold 1\u0026times; PBS, and stored overnight at \u0026le;\u0026thinsp;\u0026minus;\u0026thinsp;20\u0026deg;C. Following two freeze\u0026ndash;thaw cycles to disrupt the cell membranes, the homogenates were centrifuged at 5,000 \u0026times; g for 5 min. According to the manufacturers\u0026rsquo; instructions, ELISA kits were used to quantify MMA (EIAab, China), interleukin-6 (IL-6; Mlbio, China), and tumor necrosis factor-α (TNF-α; Mlbio, China) levels in mouse peripheral serum, cell supernatants, and kidney homogenates. The absorbance was measured at 450 nm, and the concentrations were subsequently calculated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eStatistics\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using GraphPad Prism 9.0 or SPSS 24.0. The data are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean (SEM). The Shapiro‒Wilk test was used to assess data normality, and the Brown‒Forsythe test was used to evaluate the homogeneity of variance. For comparisons between two groups, an unpaired two-tailed Student\u0026rsquo;s t test was applied when the data followed a normal distribution with equal variance. When variances were unequal, Welch\u0026rsquo;s t test was used. Nonnormally distributed data were analyzed using the Mann\u0026ndash;Whitney U test. For comparisons among three or more groups, one-way ANOVA followed by Bonferroni post hoc correction was used for normally distributed data, whereas the Kruskal\u0026ndash;Wallis test with Dunn\u0026rsquo;s multiple comparisons test was used for nonnormally distributed data. For multifactorial comparisons, two-way ANOVA followed by Bonferroni post hoc correction was applied for normally distributed datasets, whereas multiple Mann\u0026ndash;Whitney U tests were used for nonparametric data. A P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003e1. Ferroptosis induces the selective secretion of methylmalonic acid in HK-2 cells\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo establish a robust in vitro system for studying ferroptosis-associated metabolite release, we used HK-2 human proximal tubular epithelial cells, which are highly susceptible to ferroptotic death. Two mechanistically distinct ferroptosis inducers were applied: RSL3, an irreversible covalent inhibitor of glutathione peroxidase 4 (GPX4), and erastin, which blocks cystine import via system Xc⁻ and thus depletes intracellular glutathione. By using both agents, we aimed to capture ferroptosis triggered by endogenous antioxidant failure as well as by disruption of cystine metabolism.\u003c/p\u003e \u003cp\u003eWestern blot analysis demonstrated clear and dose-dependent downregulation of the expression of the ferroptosis regulators GPX4 and SLC7A11 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, B). With increasing concentrations of RSL3 (2\u0026ndash;10 \u0026micro;M), GPX4 protein levels progressively decreased, becoming almost undetectable at 8 \u0026micro;M, while SLC7A11 was reduced by more than 60%. Similarly, treatment with erastin (5\u0026ndash;80 \u0026micro;M) suppressed GPX4 expression in a dose-dependent manner, with maximal inhibition at 80 \u0026micro;M and a concomitant reduction in SLC7A11 expression. Densitometric quantification across three independent experiments revealed that GPX4 expression decreased by approximately 65% in response to 2 \u0026micro;M RSL3 and by approximately 55% in response to 5 \u0026micro;M erastin compared with that in response to no treatment. These findings validated the successful induction of ferroptosis in HK-2 cells.\u003c/p\u003e \u003cp\u003eTo ensure that subsequent metabolomic profiling reflected regulated secretion rather than nonspecific leakage, we next assessed plasma membrane integrity. Propidium iodide staining revealed that \u0026gt;\u0026thinsp;80% of the cells retained intact membranes after treatment with 2 \u0026micro;M RSL3 or 5 \u0026micro;M erastin (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). These concentrations were therefore selected for further experiments, as they effectively triggered ferroptosis while minimizing the confounding effects of widespread cell rupture. To further confirm ferroptosis, we assessed two hallmark readouts: intracellular ferrous iron (Fe\u0026sup2;⁺) accumulation and lipid peroxidation. FerroOrange staining demonstrated a significant increase in cytosolic Fe\u0026sup2;⁺ following both RSL3 and erastin exposure. Concurrently, BODIPY-C11 staining revealed a nearly twofold increase in lipid reactive oxygen species (ROS) intensity relative to that in the controls, which was consistent with ferroptotic lipid damage (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eWe then performed untargeted metabolomics on the conditioned media of ferroptotic and control cells. Principal component analysis demonstrated distinct clustering of ferroptosis-induced metabolomes compared with those of the untreated controls, confirming the broad reprogramming of extracellular metabolite release (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eE-H). Specifically, 45 metabolites were significantly upregulated after RSL3 treatment, whereas 139 metabolites were enriched following erastin exposure. Venn diagram analysis revealed 19 metabolites that were commonly increased under both ferroptotic stimuli (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eI). Among these, methylmalonic acid (MMA) emerged as the most consistently and robustly elevated metabolite. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ, K).\u003c/p\u003e \u003cp\u003eTo determine whether MMA release was unique to ferroptosis or a general feature of cell death, we compared supernatants from apoptotic and necroptotic HK-2 cells. Neither apoptosis induction with TNF-α\u0026thinsp;+\u0026thinsp;SM-164 nor necroptotic induction with TNF-α\u0026thinsp;+\u0026thinsp;SM-164\u0026thinsp;+\u0026thinsp;Z-VAD-FMK resulted in detectable increases in extracellular MMA (Fig. S1C). This result strongly indicated that MMA secretion is not a universal byproduct of cell death but is instead specifically associated with ferroptosis.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2. MUT suppression links ferroptosis to MMA accumulation in vivo\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo investigate whether the ferroptosis-associated release of MMA observed in vitro also occurs in vivo, we used a murine model of renal ischemia\u0026ndash;reperfusion injury (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), a clinically relevant setting in which ferroptosis has been shown to play a major role in tubular cell death. As expected, immunofluorescence staining confirmed a marked reduction in GPX4 protein expression in renal tissues collected 24 hours after reperfusion (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eN), which was consistent with ferroptotic activation. Serum creatinine levels and blood urea nitrogen (BUN) levels were significantly elevated in both groups compared with those in the sham-operated control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, C), while the expression of NGAL, a sensitive marker of tubular injury, markedly increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). Histological analyses revealed extensive tubular epithelial cell detachment, denudation of basement membranes, tubular dilatation, cast formation, and infiltration of inflammatory cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eE, F).\u003c/p\u003e \u003cp\u003eAdministration of the ferroptosis inhibitor ferrostatin-1 (Fer-1) significantly improved renal outcomes. Compared with untreated IRI mice, treated mice exhibited approximately 40% lower serum creatinine and BUN levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, C), as well as reduced NGAL expression and attenuated histological damage (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eD-F). These findings support the conclusion that ferroptosis is a central driver of kidney injury in this model.\u003c/p\u003e \u003cp\u003eWe next quantified MMA levels in serum and kidney tissues by ELISA. Consistent with our in vitro findings, IRI led to a significant increase in MMA concentrations both systemically and locally within the kidney (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eG, H). Notably, Fer-1 treatment reversed these increases, reducing MMA levels. These findings suggest that ferroptosis directly contributes to MMA accumulation in vivo.\u003c/p\u003e \u003cp\u003eGiven that intracellular MMA catabolism requires the mitochondrial enzyme methylmalonyl-CoA mutase (MUT) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eI), we assessed MUT expression under ferroptotic conditions. In HK-2 cells, both RSL3 and erastin markedly reduced MUT transcript abundance and protein levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eJ, K). In the IRI model, renal MUT expression significantly decreased after ischemia\u0026ndash;reperfusion but was preserved when ferroptosis was pharmacologically inhibited by Fer-1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eL, M).\u003c/p\u003e \u003cp\u003eTo define the spatial relationship between ferroptosis and MUT suppression, we performed dual immunofluorescence staining. MUT was found to be predominantly expressed in proximal tubular epithelial cells, as identified by Lotus tetragonolobus lectin (LTL) labeling. Under basal conditions, MUT exhibited strong mitochondrial punctate signals along the proximal tubules. However, after IRI, the fluorescence intensity of the MUT was markedly reduced, particularly in areas where GPX4 expression was lost (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eN, O). Colocalization analyses demonstrated that regions of GPX4 depletion coincided with diminished MUT staining, indicating that MUT suppression occurs specifically in ferroptotic tubular cells.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3. Ferroptosis-derived MMA exacerbates renal ischemia\u0026ndash;reperfusion injury\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo directly evaluate the pathogenic potential of MMA during renal ischemia\u0026ndash;reperfusion injury (IRI), we established an exogenous supplementation model in which MMA was administered intraperitoneally to mice immediately following reperfusion (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Biochemical and histological assessments were performed 24 hours after injury.\u003c/p\u003e \u003cp\u003eCompared with mice with IRI alone, MMA-treated mice exhibited significantly worse renal function. Serum creatinine levels were elevated by approximately 25%, while BUN levels increased by approximately 35% compared with those in the IRI controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, C). Western blotting and immunohistochemistry demonstrated that NGAL expression was further upregulated in MMA-treated kidneys (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). These biochemical findings were corroborated by histopathological analysis. Hematoxylin\u0026ndash;eosin and PAS staining revealed more extensive epithelial detachment from the basement membrane, widespread tubular dilatation, denudation of tubular structures, and abundant intraluminal cast formation in MMA-treated animals (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). Semiquantitative scoring confirmed that overall tubular injury scores nearly 1.5-fold higher in the MMA\u0026thinsp;+\u0026thinsp;IRI group compared with those in the IRI alone group.\u003c/p\u003e \u003cp\u003eTo assess cell death more specifically, we performed TUNEL staining. The proportion of TUNEL-positive tubular cells was nearly twofold greater in MMA-treated kidneys, with extensive clusters of apoptotic and necrotic cells visible throughout the cortex and outer medulla (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). These data indicate that MMA exposure directly enhances tubular epithelial cell vulnerability during reperfusion.\u003c/p\u003e \u003cp\u003eGiven that macrophages are critical mediators of post-IRI inflammation, we next assessed immune cell infiltration. Flow cytometry revealed a substantial increase in renal F4/80⁺CD86⁺ M1 macrophages in IRI kidneys compared with those in sham controls, and this effect was further augmented by MMA treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eG). The frequency of M1 macrophages increased by approximately 80% in response to MMA treatment compared to IRI alone. In parallel, Western blotting demonstrated increased expression of IL-6 and TNF-α in kidney tissues, and ELISA confirmed the increased systemic release of these cytokines into the circulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eH-J). Together, these results suggest that MMA not only exacerbates epithelial injury but also amplifies inflammatory macrophage responses in the postischemic kidney.\u003c/p\u003e \u003cp\u003e \u003cb\u003e4. MMA directly drives M1 macrophage polarization in vitro\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo explore whether MMA can directly modulate the macrophage phenotype independent of tubular injury, we designed an in vitro coculture system using the murine macrophage line RAW264.7 (Fig. S2A). Initial experiments using conditioned media from ferroptotic HK-2 cells demonstrated that compared with media from viable HK-2 cells, ferroptotic supernatants alone were sufficient to promote a shift toward M1 polarization, as evidenced by increased proportions of F4/80⁺TNF-α⁺ macrophages (Fig. S2B). These observations prompted us to examine whether MMA, identified as a prominent ferroptosis-associated metabolite, could directly account for this effect.\u003c/p\u003e \u003cp\u003eRAW264.7 macrophages were pretreated with MMA (5 \u0026micro;M) for 6 hours and subsequently stimulated with or without lipopolysaccharide (LPS) to mimic inflammation. Flow cytometric analysis revealed that compared with no treatment, MMA alone markedly increased the fraction of F4/80⁺TNF-α⁺ macrophages by approximately 5-fold relative to untreated controls. (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). When combined with LPS, MMA acted synergistically, further expanding the M1 population by approximately 60% beyond LPS stimulation alone.\u003c/p\u003e \u003cp\u003eAt the transcriptional level, qPCR analysis confirmed the robust induction of classical M1-associated genes. The iNOS and IL-6 mRNA level increased more than 10-fold after MMA treatment, whereas the levels of the TNF-α transcripts increased approximately 20-fold (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). These transcriptional changes translated into functional protein responses. Western blotting revealed increased expression of iNOS, IL-6, and TNF-α in MMA-treated cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). ELISAs corroborated these findings, revealing significantly increased secretion of IL-6 and TNF-α into the culture supernatants, with MMA\u0026thinsp;+\u0026thinsp;LPS-treated macrophages producing the greatest amounts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eD, E).\u003c/p\u003e \u003cp\u003eImportantly, MMA did not affect the viability of RAW264.7 cells at the concentrations used, as confirmed by CCK-8 assays (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eF), excluding nonspecific cytotoxicity as a confounder. These results indicated that MMA acts as a bona fide signaling metabolite capable of directly reprogramming macrophage functional states.\u003c/p\u003e \u003cp\u003e \u003cb\u003e5. Macrophage depletion abrogates MMA-induced renal injury\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo determine whether macrophages are indispensable mediators of MMA-driven renal injury, we performed selective macrophage depletion in mice using clodronate liposomes (CLOPs) (Fig. S3A). The intravenous administration of CLOP effectively reduced renal macrophage populations, as confirmed by flow cytometry (Fig. S3B). More than 70% of the F4/80⁺ CD11b\u003csup\u003e+\u003c/sup\u003e cells were eliminated within 24 hours of treatment, confirming successful depletion.\u003c/p\u003e \u003cp\u003eIn IRI alone, macrophage depletion significantly ameliorated renal dysfunction, with serum creatinine and BUN levels reduced by approximately 25% compared with those in untreated IRI controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, B). Importantly, in MMA-supplemented IRI mice, macrophage depletion completely reversed the exacerbated renal injury phenotype. Serum creatinine and BUN levels in the MMA+CLOP group were indistinguishable from those in the IRI+CLOP group, demonstrating that the detrimental effects of MMA were fully dependent on the presence of macrophages.\u003c/p\u003e \u003cp\u003eWestern blot analysis revealed that NGAL expression, which was strongly induced in IRI kidneys and further upregulated by MMA treatment, was significantly reduced after macrophage depletion (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Histological analysis corroborated these findings: while MMA\u0026thinsp;+\u0026thinsp;IRI kidneys exhibited extensive tubular epithelial detachment, cast formation, and inflammatory infiltration, these pathological features were markedly alleviated in the MMA+CLOP group (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). Semiquantitative injury scoring confirmed a nearly 25% reduction in injury severity upon macrophage removal.\u003c/p\u003e \u003cp\u003eTo further assess cell death, we performed TUNEL staining. In MMA-treated IRI kidneys, the proportion of TUNEL-positive tubular epithelial cells was significantly greater than that in kidneys with IRI alone, but this effect was effectively reversed after macrophage depletion (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). Similarly, Western blot and ELISA revealed that the increased expression and systemic release of IL-6 and TNF-α induced by MMA were abrogated by CLOP treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eF-H). These results highlight the central role of macrophages in mediating MMA-driven inflammatory injury. These results also provide direct causal evidence linking ferroptosis-derived metabolites to immune effector cells as critical mediators of tissue damage.\u003c/p\u003e \u003cp\u003e \u003cb\u003e6. MMA-primed BMDMs aggravate IRI through enhanced M1 polarization\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo further validate that MMA directly reprograms macrophages toward a pathogenic phenotype in vivo, we conducted adoptive transfer experiments using bone marrow\u0026ndash;derived macrophages (BMDMs) (Fig. S4A). BMDMs were generated from C57BL/6 mice and confirmed by flow cytometry to express the macrophage lineage markers F4/80 and CD11b at high purity (\u0026gt;\u0026thinsp;90%) (Fig. S4B). To enable in vivo tracking, BMDMs were labeled with the fluorescent dye PKH-26 prior to transfer (Fig. S4C).\u003c/p\u003e \u003cp\u003eRecipient mice subjected to renal IRI were intravenously infused with either untreated BMDMs or BMDMs preconditioned in vitro with MMA (5 \u0026micro;M, 24 h). Fluorescence microscopy confirmed that the transferred PKH-26\u0026ndash;labeled BMDMs efficiently homed to injured kidneys, where they were localized predominantly in the cortical and outer medullary regions (Fig. S4D).\u003c/p\u003e \u003cp\u003eAdoptive transfer of na\u0026iuml;ve BMDMs alone was sufficient to increase the frequency of renal F4/80⁺CD86⁺ M1 macrophages following IRI, suggesting that the injury microenvironment promotes proinflammatory polarization (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Notably, compared with unprimed BMDM transfer, the transfer of MMA-primed BMDMs resulted in an even greater expansion of the M1 subset, with M1 macrophage proportions being elevated by an additional 35%.\u003c/p\u003e \u003cp\u003eConsistent with these findings, the results of the ELISA and Western blot analyses demonstrated that kidneys that received MMA-primed BMDMs expressed significantly higher levels of IL-6 and TNF-α than controls did (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eB) and that the serum levels of these cytokines were also elevated (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eC, D). At the functional level, renal injury was exacerbated in mice that received MMA-primed BMDMs, as evidenced by an approximately 25% increase in serum creatinine and BUN levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eE, F), more severe histological damage with extensive tubular epithelial cell detachment and cast formation (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eG, H), and a greater proportion of TUNEL-positive tubular cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eI). These results demonstrate that MMA induces macrophages to adopt a more aggressive proinflammatory phenotype in vivo, thereby amplifying renal injury after IRI.\u003c/p\u003e \u003cp\u003e \u003cb\u003e7. MMA promotes M1 polarization via PI3K/Akt/NF-κB signaling\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo elucidate the molecular mechanisms through which MMA drives macrophage polarization, we performed transcriptomic profiling of RAW264.7 cells treated with MMA for 12 hours. RNA-seq revealed 235 significantly differentially expressed genes (DEGs) compared with those in the untreated controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eA, B). Among these genes, numerous genes involved in immune activation, cytokine production, and cell survival were upregulated. KEGG pathway enrichment analysis revealed that the PI3K/Akt signaling pathway was among the most significantly enriched pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eC, D), suggesting its potential role as a mediator of MMA-driven macrophage responses.\u003c/p\u003e \u003cp\u003eCloser inspection of the RNA-seq dataset revealed increased expression of several regulators closely linked to PI3K/Akt activation, including PIK3AP1, Vegfa, and Mcl-1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eE, F). qPCR validation confirmed that the expression of PIK3AP1, Vegfa, and Mcl-1 increased approximately 3-fold, approximately 2-fold, and approximately 2.5-fold, respectively, after MMA treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eF). These genes are known to increase PI3K activity, promote survival signaling, and facilitate proinflammatory programming in macrophages[\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt the protein level, Western blot analysis demonstrated that MMA stimulation robustly increased the phosphorylation of PI3K, Akt, and NF-κB p65 (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eG). Compared with those of the untreated controls, phosphorylated PI3K increased by approximately 2-fold, phosphorylated Akt by approximately 1.5-fold, and phosphorylated p65 by approximately 2.5-fold, while total protein levels remained unchanged. These findings indicated the activation of the canonical PI3K/Akt/NF-κB signaling cascade.\u003c/p\u003e \u003cp\u003eTo test whether PI3K/Akt signaling is functionally required for MMA-induced polarization, we pretreated macrophages with LY294002, a selective PI3K inhibitor. LY294002 markedly suppressed MMA-induced transcription of iNOS, IL-6, and TNF-α (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eH), reduced the frequency of F4/80⁺CD86⁺ M1 macrophages, as determined by flow cytometry (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eK), and significantly decreased the secretion of IL-6 and TNF-α into the culture supernatant (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eI, J). Notably, LY294002 alone had minimal effects on basal macrophage polarization, underscoring the specific dependence of MMA-mediated effects on PI3K/Akt activation.\u003c/p\u003e \u003cp\u003e \u003cb\u003e8. Downregulation of donor kidney MUT is correlated with aggravated acute kidney injury\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo extend our mechanistic findings to a clinically relevant setting, we examined methylmalonyl-CoA mutase (MUT) expression in human renal allografts subjected to ischemia\u0026ndash;reperfusion during transplantation. Biopsy samples were collected from two groups of recipients: those who developed delayed graft function (DGF), defined as the need for dialysis within the first week post-transplant, and those with stable function (ST).\u003c/p\u003e \u003cp\u003eImmunohistochemical staining and Western blotting demonstrated that MUT expression was markedly lower in donor kidneys from the DGF group than in those from the ST group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e8\u003c/span\u003eA). Quantitative densitometry revealed an average reduction in MUT protein levels in DGF samples. Morphological analysis further revealed that MUT staining, which is normally strong in proximal tubules, was faint or patchy in DGF biopsies, particularly in regions showing structural injury.\u003c/p\u003e \u003cp\u003eClinical correlations supported the functional importance of MUT downregulation. Patients receiving grafts with low MUT expression exhibited significantly worse renal function recovery during the first postoperative week, as indicated by persistently elevated serum creatinine levels and blood urea nitrogen (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e8\u003c/span\u003eB, C). Moreover, the incidence of DGF was substantially greater in the low-MUT group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e8\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003eReceiver operating characteristic (ROC) curve analysis revealed that MUT expression in donor kidneys had predictive value for DGF occurrence, with an area under the curve (AUC) of 0.78 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e8\u003c/span\u003eE). These findings suggest that MUT could serve as a biomarker of donor kidney quality.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we identified methylmalonic acid (MMA) as a novel ferroptosis-associated metabolite that mediates crosstalk between dying tubular epithelial cells and immune cells, thereby exacerbating AKI in the context of IRI. Our findings demonstrate that ferroptotic renal tubular cells actively release MMA and that this metabolite acts as a paracrine \u0026ldquo;danger signal\u0026rdquo; to promote proinflammatory macrophage activation. This discovery expands the emerging paradigm of cell death-induced metabolite signaling and provides new insights into how ferroptosis contributes to tissue injury beyond cell autonomous effects.\u003c/p\u003e \u003cp\u003eOne of the key results of our work is the specific upregulation of MMA in the extracellular milieu of ferroptotic cells. Using two distinct ferroptosis inducers (RSL3 and erastin) in HK-2 tubular cells, we observed marked decreases in GPX4 and SLC7A11 expression (confirming ferroptosis induction) accompanied by significant MMA accumulation in culture supernatants. Importantly, this effect was not replicated in cells undergoing apoptosis or necroptosis\u0026mdash;neither of those cell death modalities led to elevated MMA release. Thus, MMA appears to be uniquely associated with ferroptotic cell death. To ensure that MMA release was not merely due to nonspecific membrane rupture, we carefully titrated the concentrations of RSL3 and erastin to induce ferroptosis while keeping\u0026thinsp;\u0026gt;\u0026thinsp;80% of the cell membranes intact (preventing widespread necrotic leakage). Under these sublytic conditions, the levels of intracellular Fe^2\u0026thinsp;+\u0026thinsp;and lipid peroxides (hallmarks of ferroptosis) were significantly elevated, yet the cells largely maintained membrane integrity, suggesting that MMA release is a regulated event rather than merely a consequence of membrane destruction. This observation is in agreement with prior reports on apoptotic cells, where metabolites are released through specific channels instead of random leakage[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Similarly, our data suggest that ferroptotic cells may possess a \u0026ldquo;metabolite secretome\u0026rdquo; of their own. Indeed, a previous study in a renal IRI model revealed that the pannexin 1 channel is involved in ferroptosis execution[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], suggesting that PANX1 or other conduits could be involved in the release of small metabolites such as MMA during ferroptosis.\u003c/p\u003e \u003cp\u003eMMA itself is a well-known metabolic intermediate, and its accumulation is most prominently recognized in inherited methylmalonic acidemia caused by deficiency of the mitochondrial enzyme methylmalonyl-CoA mutase (MUT) or its cofactor vitamin B_12[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In those genetic or nutritional disorders, elevated MMA leads to systemic complications, including renal failure and immune dysfunction[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Our results reveal a previously unappreciated acute scenario of MMA accumulation: an IRI setting in which ferroptosis leads to transient \u003cem\u003efunctional\u003c/em\u003e MUT impairment. We found that both RSL3 treatment and erastin treatment markedly downregulated MUT expression in tubular cells in vitro, and similarly, renal MUT expression was suppressed after IRI in vivo. Notably, administering the ferroptosis inhibitor Fer-1 preserved MUT expression and prevented the increase in MMA levels post-IRI. These findings suggest that ferroptotic stress interferes with methylmalonate metabolism, likely through inactivation or downregulation of MUT, leading to acute MMA accumulation. The mechanism by which ferroptosis affects MUT could involve oxidative damage to the enzyme or broader metabolic reprogramming\u0026mdash;an intriguing area for future investigation. Nevertheless, it is clear that ferroptotic cell death creates a metabolic byproduct (MMA) that is normally tightly regulated, thereby enriching the extracellular space with a potentially bioactive metabolite.\u003c/p\u003e \u003cp\u003eFunctionally, we discovered that MMA release is not a benign bystander event but rather has significant pathophysiological effects. An increase in MMA levels in the context of IRI translated to worse kidney injury outcomes. Compared with control mice, mice administered exogenous MMA prior to IRI presented higher peak serum creatinine levels and blood urea nitrogen levels, indicating aggravated acute kidney dysfunction. Histologically, compared with controls with the same IRI insult, MMA-treated mice had more severe tubular damage, including greater tubular epithelial cell loss, denuded basement membranes, tubular dilation, and cast formation. Additionally, the expression of NGAL (a sensitive injury marker) in the kidney was further increased by MMA. These data establish that MMA can potentiate IRI-induced AKI. Mechanistically, our results suggest that the immune system, particularly macrophages, is the primary mediator of the detrimental effects of MMA. We observed that MMA administration led to a significant increase in proinflammatory M1 macrophage infiltration in post-IRI kidneys, along with elevated local and systemic levels of IL-6 and TNF-α. To directly test the role of macrophages, we used clodronate liposome to deplete macrophages in vivo. Strikingly, macrophage depletion almost completely abrogated the additional injury caused by MMA; compared with control mice, MMA-treated, macrophage-depleted mice no longer showed worsened renal function or heightened NGAL expression, and the exacerbation of tubular cell death and inflammation induced by MMA was largely reversed. These results clearly indicate that MMA aggravates AKI predominantly by acting on macrophages and enhancing inflammatory responses.\u003c/p\u003e \u003cp\u003eOur in vitro and adoptive transfer experiments provide further evidence for the role of MMA in modulating the macrophage phenotype. In cultured RAW264.7 macrophages, MMA exposure alone was sufficient to skew polarization toward an M1-like state, as evidenced by increased expression of M1 markers (inducible nitric oxide synthase (iNOS), TNF-α, and IL-6) and increased secretion of IL-6 and TNF-α. When MMA treatment was combined with a low-dose LPS stimulus, the effect was synergistic: MMA preconditioning significantly increased LPS-induced M1 polarization. These findings suggest that MMA not only directly drives macrophage activation but also \u0026ldquo;prime\u0026rdquo; macrophages to respond more vigorously to other inflammatory cues. Consistently, in vivo adoptive transfer of bone marrow-derived macrophages (BMDMs) demonstrated that MMA-treated BMDMs acquired a pronounced proinflammatory phenotype. In IRI mice, MMA-pretreated BMDMs preferentially homed to the injured kidney and significantly increased the proportion of F4/80^+CD86^+ M1 macrophages in the tissue. Compared with mice that received naive BMDMs, those that received MMA-exposed BMDMs had higher renal IL-6 and TNF-α levels and greater kidney damage and cell death. Together, these results establish a cause-and-effect link: MMA is capable of reprogramming macrophages toward the M1 phenotype, and these MMA-primed macrophages, in turn, intensify tissue injury in IRI.\u003c/p\u003e \u003cp\u003eAt the molecular level, we identified the PI3K/Akt/NF-κB pathway as a critical signaling axis through which MMA exerts its proinflammatory effect on macrophages. Transcriptomic analysis of MMA-stimulated macrophages revealed enrichment of pathways related to PI3K-Akt signaling. We confirmed that MMA stimulation led to robust phosphorylation of PI3K, Akt, and the NF-κB p65 subunit in macrophages, indicating the activation of this pathway. The PI3K/Akt pathway is well known to regulate macrophage survival, proliferation, and polarization[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], in part by activating NF-κB, which drives the transcription of numerous inflammatory genes[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In our study, pharmacologic inhibition of PI3K/Akt signaling with LY294002 significantly attenuated MMA-induced M1 polarization; LY294002-treated macrophages showed blunted upregulation of \u003cem\u003eTNF\u003c/em\u003e, \u003cem\u003eIL6\u003c/em\u003e, and \u003cem\u003eiNOS\u003c/em\u003e transcripts and secreted markedly lower levels of TNF-α and IL-6 in response to MMA. These findings confirm that the proinflammatory effects of MMA on macrophages are largely mediated by PI3K/Akt and its downstream target NF-κB. Notably, NF-κB is a central hub for M1 macrophage activation[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], and our data suggest that MMA is an upstream trigger of this hub. How MMA activates PI3K/Akt remains unclear. We hypothesize that MMA accumulation could perturb cellular metabolism, perhaps through the accumulation of methylmalonyl-CoA and related metabolites that interfere with normal TCA cycle flux, leading to secondary signals (such as altered AMP/ATP ratios or ROS generation) that engage PI3K/Akt. Alternatively, cell-surface receptors or sensors for MMA may exist. Although no dedicated MMA receptor is known, it is interesting to consider parallels with succinate, another metabolic acid. Succinate can signal via its G-protein coupled receptor SUCNR1 (GPR91) on immune cells to promote inflammation and macrophage chemotaxis[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Some studies have shown that succinate-SUCNR1 interactions exacerbate inflammatory responses in tissues[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. It remains to be seen whether MMA may be detected by a similar pattern recognition mechanism or if it primarily acts intracellularly once it is taken up by macrophages. Our observation that MMA increases intracellular ROS and inflammatory cytokines in macrophages (akin to effects observed in neural cells[\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]) suggests an interplay between metabolic redox stress and classical inflammatory signaling. Further work is warranted to elucidate the precise sensing mechanism of MMA in immune cells.\u003c/p\u003e \u003cp\u003eOur findings contribute to a broader understanding of the \u0026ldquo;metabolic language\u0026rdquo; of cell death. Our findings align with and extend the concept introduced by Medina et al. that dying cells release metabolites to influence their environment[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, there is a striking contrast in outcomes: whereas apoptotic cells predominantly emit anti-inflammatory, proresolving metabolites to facilitate orderly tissue turnover[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], ferroptotic cells (as exemplified by MMA release) appear to do the opposite\u0026mdash;they create a metabolic milieu that amplifies inflammation and tissue injury. This dichotomy likely reflects the distinct physiological roles of these death processes. Apoptosis occurs during homeostatic turnover and development, where it is advantageous for quelling inflammation[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Ferroptosis, on the other hand, is often associated with pathological stress (e.g., severe oxidative injury) and may serve as a trigger for immune activity. In evolutionary terms, inflammatory signals from ferroptosis may help recruit immune cells to sites of damage or infection. Unfortunately, sterile injury, such as IRI, can lead to collateral tissue damage. Our work provides direct evidence of such a mechanism in that a metabolite produced from disrupted metabolism in ferroptotic cells can act as an alarm signal that drives maladaptive inflammation.\u003c/p\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eClinical implications\u003c/h2\u003e \u003cp\u003eThe clinical implications of our study are noteworthy. The severity of donor kidney acute injury is strongly associated with the incidence of delayed graft function (DGF) after transplantation. Grafts with more severe AKI are less capable of functional recovery, thereby increasing the risk of DGF. In kidney transplantation, IRI is an unavoidable event, especially in donations after circulatory death (DCD). DCD donor kidneys experience prolonged warm ischemia and are at high risk of delayed graft function (DGF). Indeed, the DGF incidence in DCD kidney transplants is approximately double that of standard-criteria brain-dead donors (approximately 38\u0026ndash;49% vs. approximately 20%)[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Our analysis of transplant biopsy samples revealed that compared with those with immediate graft function, donor kidneys that continued on to develop DGF had significantly lower MUT expression. These findings suggest that an impaired capacity to metabolize MMA (reflected by low MUT levels) may predispose grafts to worsened ischemic injury and delayed recovery. In other words, robust metabolic handling of methylmalonyl-CoA could be a protective factor, whereas its deficiency exacerbates injury, which is consistent with our experimental data. Moreover, we found that MUT downregulation in donor kidneys correlated with poorer early posttransplant renal function and a greater likelihood of DGF. Preliminary ROC analysis indicated that the donor MUT expression level has prognostic value for DGF, suggesting that it could be developed as a biomarker. While these clinical observations need validation in larger cohorts, they underscore the relevance of the ferroptosis-MUT-MMA axis in real-world IRI scenarios. It also prompts speculation on potential therapeutic interventions. For example, supplementation of vitamin B12 (to maximize MUT activity) or other metabolic therapies may reduce IRI severity. Moreover, whether ferroptosis inhibitors or specific MMA scavengers administered during organ preservation or immediately after reperfusion could improve outcomes in DCD transplants remains unknown. These are exciting questions for future translational research. In our study, the administration of vitamin B₁₂ or L-carnitine, two agents clinically used to reduce MMA levels in patients with methylmalonic acidemia by enhancing MUT activity, failed to achieve significant therapeutic benefits in a murine IRI model. This lack of efficacy may reflect model-specific differences and species-related variability between mice and humans. Nevertheless, these findings underscore the potential value of developing pharmacological strategies directly targeting MUT to lower MMA levels, which may represent a promising therapeutic approach for IRI.\u003c/p\u003e \u003cp\u003eIn summary, our study provides the first evidence that ferroptotic cells can release a metabolite signal (MMA) that actively modulates the immune response in AKI. We demonstrated that ferroptosis-induced MMA release drives macrophages toward an M1 proinflammatory phenotype via the PI3K/Akt/NF-κB pathway, thereby exacerbating kidney injury. These findings reveal that ferroptosis is not only a cell-intrinsic death mechanism but also an activator of intercellular signaling and inflammation. From a therapeutic standpoint, our work suggests multiple potential targets\u0026mdash;from blocking ferroptosis itself to intercepting the activity or production of MMA or modulating macrophage responses. Given the urgent clinical need in AKI and transplant IRI (where no specific therapies exist to prevent DGF other than general ischemic mitigation), targeting the ferroptotic metabolite axis could be a novel strategy to improve patient outcomes. Future studies should explore the generality of our findings (e.g., whether other ferroptotic contexts or cell types release different metabolites that affect immune cells) and further dissect how MMA is sensed at the molecular level. Nevertheless, the present work provides a foundation for considering metabolic interventions in conjunction with cell death modulation as a means to curtail tissue damage in ischemic and inflammatory diseases.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAKI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eacute kidney injury\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIRI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eischemia\u0026ndash;reperfusion injury\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMMA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emethylmalonic acid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGPX4\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eglutathione peroxidase 4\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ereactive oxygen species\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePANX1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epannexin 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFer-1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFerrostatin-1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLTL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLotus tetragonolobus lectin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTNF-α\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etumor necrosis factor-α\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBUN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eblood urea nitrogen\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMUT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emethylmalonyl-CoA mutase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMDMs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebone marrow\u0026ndash;derived macrophages\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDGF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edelayed graft function\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver operating characteristic.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (Nos. 82070771, Nos.82300858, Nos82500926), Key Project of Natural Science Foundation of Henan Province (252300421264) and Funding for Scientiffc Research and Innovation Team of The First Afffliated Hospital of Zhengzhou University (QNCXTD2023020).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuimeng Wang,\u0026nbsp;Jiajia Sun, Xiaohu Li\u0026nbsp;contributed equally to this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Kidney Transplantation, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuimeng Wang, Jiajia Sun, Xiaohu Li, Hongxuan Ma, Yongsheng Luo, Minghui Qin, Hao Zhang, Haodong Bian, Jinfeng Li\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuimeng Wang: Investigation, Methodology, Resources, Software, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing. Xiaohu Li: Data curation, Formal analysis, Writing \u0026ndash; original draft. Hongxuan Ma: Data curation, Formal analysis, Methodology. Jiajia Sun: Project administration, Formal analysis, Funding acquisition, Writing \u0026ndash; original draft. Yongsheng Luo: Investigation, Methodology, Funding acquisition. Minghui Qin: Methodology, Software. Hao Zhang: Formal analysis. Haodong Bian: Formal analysis. Jinfeng Li: Conceptualization, Funding acquisition, Methodology, Supervision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding authors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to\u0026nbsp;Jinfeng Li.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by The First Affiliated Hospital of Zhengzhou University (Ethics Approval No. ZZU-LAC20210521[07]). Our experimental methods are performed in accordance with ethical standards of the responsible committee on human experimentation with the Helsinki Declaration of 1975. Informed written consent was obtained from either participants or their legal guardians.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNi L, Yuan C, Wu X. Targeting ferroptosis in acute kidney injury. Cell Death Dis. 2022; 13: 182.\u003c/li\u003e\n\u003cli\u003eNewton K, Dugger DL, Maltzman A, Greve JM, Hedehus M, Martin-McNulty B, et al. RIPK3 deficiency or catalytically inactive RIPK1 provides greater benefit than MLKL deficiency in mouse models of inflammation and tissue injury. Cell Death Differ. 2016; 23: 1565-76.\u003c/li\u003e\n\u003cli\u003eLinkermann A, Br\u0026auml;sen JH, Darding M, Jin MK, Sanz AB, Heller JO, et al. Two independent pathways of regulated necrosis mediate ischemia-reperfusion injury. 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Diabetologia. 2017; 60: 1304-13.\u003c/li\u003e\n\u003cli\u003eGabbi P, Ribeiro LR, Jessi\u0026eacute; Martins G, Cardoso AS, Haupental F, Rodrigues FS, et al. Methylmalonate Induces Inflammatory and Apoptotic Potential: A Link to Glial Activation and Neurological Dysfunction. J Neuropathol Exp Neurol. 2017; 76: 160-78.\u003c/li\u003e\n\u003cli\u003eViegas CM, Zanatta \u0026Acirc;, Grings M, Hickmann FH, Monteiro WO, Soares LE, et al. Disruption of redox homeostasis and brain damage caused in vivo by methylmalonic acid and ammonia in cerebral cortex and striatum of developing rats. Free Radic Res. 2014; 48: 659-69.\u003c/li\u003e\n\u003cli\u003eRibeiro LR, Della-Pace ID, de Oliveira Ferreira AP, Funck VR, Pinton S, Bobinski F, et al. Chronic administration of methylmalonate on young rats alters neuroinflammatory markers and spatial memory. Immunobiology. 2013; 218: 1175-83.\u003c/li\u003e\n\u003cli\u003eMcHugh J. Metabolic messengers of cell death. Nature Reviews Rheumatology. 2020; 16: 296-.\u003c/li\u003e\n\u003cli\u003eLocke JE, Segev DL, Warren DS, Dominici F, Simpkins CE, Montgomery RA. Outcomes of Kidneys from Donors After Cardiac Death: Implications for Allocation and Preservation. American Journal of Transplantation. 2007; 7: 1797-807.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003e\u003cstrong\u003eTable1\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003ePrimers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003ePrimer sequence\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eiNOS2-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eCACCAAGCTGAACTTGAGCG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eiNOS2-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eCGTGGCTTTGGGCTCCTC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eTNF\u0026alpha;-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eCTTCTGTCTACTGAACTTCGGG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eTNF\u0026alpha;-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eCAGGCTTGTCACTCGAATTTTG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eIL-6-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eCAAAGCCAGAGTCCTTCAGAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eIL-6-R\u003c/p\u003e\n \u003cp\u003eMUT-F\u003c/p\u003e\n \u003cp\u003eMUT-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eGTCCTTAGCCACTCCTTCTG\u003c/p\u003e\n \u003cp\u003eACCCAGAGGACCTTATATGGC\u003c/p\u003e\n \u003cp\u003eCTTCGGGTAAGTCCAGAGTATCT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eMCL-1-F\u003c/p\u003e\n \u003cp\u003eMCL-1-R\u003c/p\u003e\n \u003cp\u003eVegfa-F\u003c/p\u003e\n \u003cp\u003eVegfa-R\u003c/p\u003e\n \u003cp\u003ePIK3AP1-F\u003c/p\u003e\n \u003cp\u003ePIK3AP1-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 50px;\"\u003e\n \u003cp\u003eAAAGGCGGCTGCATAAGTC\u003c/p\u003e\n \u003cp\u003eTGGCGGTATAGGTCGTCCTC\u003c/p\u003e\n \u003cp\u003eCTGCCGTCCGATTGAGACC\u003c/p\u003e\n \u003cp\u003eCCCCTCCTTGTACCACTGTC\u003c/p\u003e\n \u003cp\u003eGTCCCGGATGCCTCTTTCTC\u003c/p\u003e\n \u003cp\u003eCACAAGTCATTTCCTGCCAGT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\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":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"inflammation-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"inre","sideBox":"Learn more about [Inflammation Research](http://link.springer.com/journal/11)","snPcode":"11","submissionUrl":"https://submission.nature.com/new-submission/11/3","title":"Inflammation Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"ferroptosis, macrophage, methylmalonic acid, ischemia–reperfusion injury","lastPublishedDoi":"10.21203/rs.3.rs-9256951/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9256951/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eFerroptosis and macrophage activation are key contributors to the development of acute kidney injury (AKI). Ferroptosis is accompanied by metabolic reprogramming and the release of soluble mediators, including metabolites, cytokines, and extracellular signals, which can propagate tissue damage and modulate immune responses. However, the metabolic profile of ferroptotic tubular epithelial cells and its impact on the immune microenvironment during ischemia\u0026ndash;reperfusion injury (IRI) remains largely unexplored.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eUsing untargeted metabolomics, we found that ferroptotic cells secreted abnormally elevated levels of methylmalonic acid (MMA), and investigated the physiological role of MMA in acute kidney injury in mice. Furthermore, through transcriptomics and Western blotting, we explored the mechanism by which the ferroptosis-associated metabolite MMA promotes macrophage polarization.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eHere, untargeted metabolomics revealed a distinct metabolic secretome of ferroptotic tubular epithelial cells, with the level of MMA markedly elevated after IRI. Mechanistic studies demonstrated that MMA activated the PI3K/AKT/NF-κB pathway in macrophages, driving M1 polarization and increasing the secretion of proinflammatory cytokines such as IL-6 and TNF-α, ultimately exacerbating acute kidney injury.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThese findings reveal the mechanism of metabolite\u0026ndash;immune crosstalk in AKI, and suggest that targeting the ferroptosis\u0026ndash;macrophage axis may represent a therapeutic strategy to disrupt the vicious cycle of inflammation and tissue injury.\u003c/p\u003e","manuscriptTitle":"Methylmalonic Acid as a Ferroptosis-Derived Danger Signal: Activation of the PI3K–NF-κB Pathway Drives M1 Macrophage Polarization in Renal Ischemia–Reperfusion Injury","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 12:40:10","doi":"10.21203/rs.3.rs-9256951/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-11T14:58:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-29T08:18:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"213967953020617243222129474813648392743","date":"2026-04-20T01:17:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-15T16:30:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-01T16:08:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-01T16:07:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Inflammation Research","date":"2026-03-29T06:57:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"inflammation-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"inre","sideBox":"Learn more about [Inflammation Research](http://link.springer.com/journal/11)","snPcode":"11","submissionUrl":"https://submission.nature.com/new-submission/11/3","title":"Inflammation Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"dea25305-e6a5-4fed-9ef1-c674bf3709c6","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-11T14:58:40+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T15:12:26+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 12:40:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9256951","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9256951","identity":"rs-9256951","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}