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. 2026 Feb 5;49(1):84. doi: 10.1007/s10753-025-02410-5

TM9SF1 Aggravates Liver Ischemia–Reperfusion Injury by Promoting Autophagy

Tongtong Wu 1,2,3,#, Wendong Li 1,2,3,#, Ying Zhu 1,2,3, Xudong Liu 1,2,3, Haocheng Yu 1,2,3, Hao Li 1,2,3, Jiakai Zhang 1,2,3, Hongwei Tang 1,2,3, Mingjie Ding 1,2,3, Wenzhi Guo 1,2,3,✉
PMCID: PMC12920375  PMID: 41642418

Abstract

Liver transplantation (LT) remains the only effective treatment for end-stage liver disease. Autophagy critically regulates liver ischemia–reperfusion (I/R) injury. Transmembrane 9 superfamily member 1 (TM9SF1) is a transmembrane protein associated with the elevation of autophagy. However, the role and mechanism of this protein in liver I/R injury have not been explored. We observed upregulated TM9SF1 expression in liver I/R mice models and AML12 cells subjected to hypoxia-reoxygenation (H/R). Using TM9SF1 adeno-associated virus (AAV) to generate overexpression and knockdown (KD) mice with liver I/R injury, we found that TM9SF1-overexpressing mice exhibited exacerbated liver damage, inflammation, and autophagy, whereas KD-TM9SF1 mice showed opposite results. Mechanistically, we found that TM9SF1 and Annexin A2 (ANXA2) interacted and jointly promoted the expression of autophagy levels during liver I/R injury. Virtual screening of FDA-approved compounds identified lomitapide as an inhibitor that selectively suppresses TM9SF1 expression, thereby attenuating I/R injury. In general, our findings indicated that TM9SF1 and ANXA2 interact with each other, promoting autophagy levels through activating the mitogen-activated protein kinase (MAPK) pathway, thereby aggravating liver I/R injury. Targeting TM9SF1-ANXA2 may be a potential therapeutic strategy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10753-025-02410-5.

Keywords: TM9SF1, Liver Ischemia–Reperfusion Injury, Autophagy, ANXA2

Introduction

Liver transplantation remains the only curative treatment for end-stage liver disease. However, the ischemia and reperfusion injury experiences by the liver during liver transplantation may lead to postoperative complications such as liver failure and graft non-function. More serious liver ischemia–reperfusion (I/R) injury can induce systemic diseases such as multiple organ failure, systemic inflammatory response syndrome, and even death [1]. Current organ-level interventions to mitigate I/R injury include improved preservation techniques like hypothermic oxygenated perfusion (HOP) [2] and experimental surgical strategies like ischemia-free liver transplantation (IFLT), which have seen limited clinical application [3]. However, molecular targeted strategies for liver I/R injury are still in short supply in clinical practice.

The mechanism of liver I/R injury is extremely complex, involving not only changes in cell metabolism caused by hypoxia, but also inflammatory responses [4], cell apoptosis, and abnormal activation of intracellular signal transduction pathways [5]. During ischemic, hepatocytes transition to anaerobic metabolism, accumulating oxygen free radicals and disrupting calcium homeostasis. These changes trigger abnormal activation of intracellular signaling pathways, such as activation of phospholipase C and protein kinase C [6], which in turn induce cell apoptosis and the release of inflammatory factors [7]. During the reperfusion phase, metabolic disorders are exacerbated. Even an inflammatory cascade reaction is formed, leading to severe damage to hepatocytes and organ dysfunction [8].

Autophagy is the process by which misfolded, damaged, and aging proteins and organelles are engulfed and encapsulated into vesicles, which are then transported to lysosomes for degradation [9]. The process of liver I/R injury involves oxidative stress [10], mitochondrial dysfunction [11], and cascading inflammatory responses, all of which can serve as activating factors for autophagy [12]. In turn, the activation of autophagy can modulate these pathological processes. In the early stages of liver ischemia, there is mitochondrial dysfunction and a significant generation of reactive oxygen species (ROS), during which autophagy clears damaged mitochondria [13]. Conversely, sustained autophagic activation during reperfusion exacerbates hepatocyte injury. Thus, the role of autophagy in liver I/R injury is dual [14], with the outcomes of autophagy activation potentially differing depending on the biological processes involved.

Transmembrane 9 superfamily member 1 (TM9SF1) regulates autophagy [15] and inflammation. Studies have shown that TM9SF1 is a biomarker associated with autophagy, and overexpression of TM9SF1 elevates the expression of the autophagy marker protein Microtubule-associated protein 1 light chain 3B-II/I (LC3B-II/I) [16], but the specific regulatory mechanism is still unknown. In addition, TM9SF1 is associated with inflammation and immunity. In the lipopolysaccharide (LPS)-induced acute lung injury mouse model, TM9SF1 expression is upregulated, and silencing of the protein is manifested as a significant reduction in inflammatory cell infiltration [17]. Clinically, the expression level of TM9SF1 is highly correlated with the activity of the disease in rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) patients [18]. In recent years, TM9SF1 has been studied more in diseases such as gastric cancer [19], bladder cancer [20], and autoimmune diseases, but its specific mechanism of action in liver I/R injury has not yet been explored.

In this study, we found that TM9SF1 was significantly elevated during liver I/R injury. TM9SF1 overexpression exacerbated inflammatory responses, liver damage, and autophagy levels both in vivo and in vitro. Mechanistically, TM9SF1 and Annexin A2 (ANXA2) interact to increase the level of autophagy by promoting the activation of the MAPK pathway, thereby increasing liver I/R injury. In addition, lomitapide reduced the expression of TM9SF1, thereby alleviating liver I/R injury. Therefore, the TM9SF1-ANXA2 axis plays a key role in liver I/R injury, and targeting this axis may be a potential intervention.

Materials and Methods

Animals

Male C57BL/6 J mice aged 6–8 weeks were obtained for the experiment (Huaxin Experimental Animal Co., Ltd, Zhengzhou, China). The mice were housed in SPF-level animal facilities with a controlled ambient temperature of 23 ± 2 ℃, a 12-h light/dark cycle, and ad libitum access to food and water. To establish knockdown and overexpression mouse models, a dose of 1 × 10^12 viral genomes (200μL per mouse) was administered via tail vein injection, targeting the liver. The viral vector system was used AAV2/8, containing green fluorescent protein (GFP) scramble control, GFP-tagged TM9SF1 for constitutive overexpression; shRNA targeting TM9SF1 (KD-TM9SF1); shRNA targeting ANXA2 (KD-ANXA2). (designed and synthesized by OBiO Technology Corp., Ltd., Shanghai, China). Six mice were assigned randomly per group. Mice received compassionate treatment in accordance with the "Principles for the Welfare and Utilization of Research Animals" (National Institutes of Health) established by the United States National Academy of Sciences. All mice were randomly assigned before treatment. This study adhered to ARRIVE guidelines. The procedures involving animal subjects were authorized by the Ethics Committee of The First Affiliated Hospital of Zhengzhou University (2023-KY-0761–002).

Liver I/R Injury Model Construction

A warm liver I/R model with 70% liver ischemia was established following established protocols [21]. Mice were anesthetized with 1% pentobarbital sodium (50 mg/kg) and subjected to midline laparotomy, with the blood vessels around the liver carefully separated. In the I/R group, a microvascular clamp was used to block blood flow to the left and middle liver lobes, while no such intervention was performed in the sham-operated group. The liver vessels were clamped with a vascular clamp to make the liver warm ischemia time 1 h, and then the vascular clamp was loosened to form the reperfusion process of liver blood flow. The mice were divided into the following groups: Sham group (Sham), 6 h after reperfusion group (I/R 6 h), 12 h after reperfusion group (I/R 12 h), and 24 h after reperfusion group (I/R 24 h), with six mice in each group. All mice were randomly assigned before treatment. At the time of sampling, blood and liver tissue samples were collected for subsequent analysis.

Measurements of Liver Injury

Serum concentrations of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were measured according to the manufacturer's instructions (C009-2–1, C010-2–1, Jiancheng, Nanjing, China).

Measurement of Inflammatory Factor Levels

Serum concentrations of pro-inflammatory cytokines IL-1β, IL-6, and TNF-α were quantified using commercially available ELISA kits according to the manufacturer's protocol (Proteintech, Wuhan, China).

Hematoxylin–Eosin (HE) and Immunohistochemical (IHC) Staining

Liver tissues were embedded in paraffin and sectioned into 5 μm slices after fixing the tissue with 10% neutral formalin. Sections were stained using the HE staining kit (Solarbio, Beijing, China). Images were captured by using a light microscope. IHC staining were performed on formalin-fixed liver tissue specimens as described previously using the TM9SF1 antibody (1:200; YN2876, ImmunoWay Biotechnology Company, Plano, TX, USA) and LC3B-II/I (1:100; GB11124-100, Servicebio, Wuhan China), then following by rabbit-specific IHC detection reagents (1:100; SPN-9001/SPN-9002, Beijing Zhongshan Golden Bridge Biotechnology Co., Ltd.).

Immunofluorescence (IF) Staining

Liver sections were stained with lymphocyte antigen 6 complex locus G6D (Ly6G) antibody (Proteintech,1:200) and fluorescent secondary antibody (Proteintech,1:500) following established protocols [22]. AML12 cells were fixed in 4% paraformaldehyde followed by permeabilization with 0.5% Triton X-100 (5 min). After blocking in 5% BSA (30 min, 37 °C), samples were exposed to primary antibodies against TM9SF1 (1:200) and ANXA2 (1:200) overnight at 4 °C and secondary fluorescent antibody for 1 h at 37 °C. Nuclei were subsequently counterstained with DAPI (10 min). Images were acquired by fluorescence microscopy and analyzed with ImageJ.

Drug Screening Based on the DrugBank Database

We performed virtual screening using the marketed compound library (2,452 molecules) from the DrugBank database. The predicted structure of the TM9SF1 protein retrieved from the AlphaFold Database (https://alphafold.ebi.ac.uk/) served as the structural basis. The Protein Preparation Wizard module in the Maestro 13.0 software package was used for the preparation of the protein, including adding bond order and charge to the impurities, removing all water molecules, adding hydrogen atoms to the protein system and optimizing the orientation of hydrogen atoms, predicting the protonation of amino acids at pH 7.4, and minimizing the energy of the entire structure under the OPLS4 force field. Then, the virtual screening process primarily utilized Glide docking algorithms of different precisions for gradient screening. Finally, we calculated the final binding energy using the MMGBSA method and compounds were further selected based on the binding energy.

Molecular Docking-Based Virtual Screening

TM9SF1 and ANXA2 structure was retrieved from AlphaFold. TM9SF1-ANXA2 binding was predicted using ZDOCK 3.0.2. Subsequently, they were processed using PyMol2.5.3, including removing the structural regions with incorrect predictions. The docking study was performed with the default configuration of ZDOCK 3.0.2, and global rigid docking was performed. After docking, AMBER18 was used to minimize the energy under the ff14SB force field. Finally, the minimized complexes were evaluated for binding affinity via PRODIGY. The optimal binding pose was visualized using PyMol2.5.3.

Terminal Deoxynucleotidyl Transferase dUTP Nick end Labeling (TUNEL) Staining

Liver tissue sections were subjected to staining using the TUNEL Apoptosis Detection Kit (Solarbio, Beijing, China). The stained liver tissue sections were examined under a fluorescence microscope, with red fluorescence indicating TUNEL-positive cells. Subsequently, cell death was assessed by fluorescence microscopy.

Hoechst 33,342/Propidium Iodide (PI) Dual Staining Assay

The cell death rate of AML12 was assessed using Hoechst 33,342/PI dual staining (Beyotime, Shanghai, China). After completing 12 h of hypoxia followed by 6 h of reoxygenation, the AML12 cells were exposed to cell staining buffer, Hoechst staining solution, and PI staining solution at 4 ℃ in the absence of light for 30 min, as per the manufacturer's guidelines. Subsequent to PBS rinsing, the cells were imaged under a fluorescence microscope.

Real-Time Polymerase Chain Reaction (PCR) Analyses

The total RNA was extracted using the VeZol Reagent (Vazyme, Nanjing, China), followed by cDNA synthesis with the Reverse Transcription Kit (Vazyme, Nanjing, China). The mRNA expression levels of the target genes were assessed using the 2 ^(−ΔΔCt) method with the SYBR PCR Master Mix Kit (Vazyme, Nanjing, China). β-actin served as the internal reference gene. Primer sequences employed in real-time PCR assays see Supplement-Table 1.

Western Blotting

Following protein extraction with RIPA lysis buffer, the supernatant underwent centrifugation for protein quantification. Post-electrophoresis, the protein samples were transferred onto PVDF membranes. These membranes were incubated with a specific primary antibody solution, appropriately diluted, followed by a 1-h incubation with the corresponding secondary antibody. Protein chemiluminescence was visualized using an enhanced chemiluminescence (ECL) kit on an imaging system (Bio-Rad). Protein expression levels were analyzed using ImageJ software. Antibody information employed in this study is detailed in Supplement-Table 2.

Oxidative Stress Analysis

The extraction solution was added to the liver tissue at a ratio of weight (g): volume (mL) = 1:9, and the liver tissue was homogenized using an ultrasonic disintegrator. Subsequently, the homogenate was centrifuged at 8000 g for 10 min at 4 °C, and the supernatant was collected for protein concentration measurement. Levels of superoxide dismutase (SOD), glutathione (GSH), and malondialdehyde (MDA) were determined in accordance with the protocols outlined in three kits (BC0025, BC0170, and BC1175, Solarbio, Beijing, China). Dihydroethidium (DHE; Servicebio, Wuhan, China) was utilized as an indicator of ROS content to evaluate tissue ROS levels. Additionally, dichlorodihydrofluorescein diacetate (DCFH-DA; 10 μM; Beyotime, Shanghai, China), served as an indicator of ROS content for assessing cell ROS levels. Images were captured by fluorescence microscopy.

Transmission Electron Microscopy (TEM)

Liver tissue was sectioned into 1 mm3 pieces. Subsequently, the liver tissue and AML12 cells were immersed in 4% glutaraldehyde (Servicebio, Wuhan, China) at 4 °C for 2 h. They were then rinsed with 0.1 mol L-1phosphate buffer and fixed in 1% osmium tetroxide. Following dehydration in a gradient of acetone and the processes of infiltration, embedding, and polymerization, the specimens were sliced into ultrathin sections approximately 70 nm thick. These sections were double stained with uranium lead and examined under a transmission electron microscope.

Construction of Plasmids and Stable Cell Lines

The TM9SF1 overexpression (TM9SF1), shRNA-TM9SF1(Sh-TM9SF1) plasmids (Public Protein/Plasmid Library, Nanjing, China) and siRNA-ANXA2(si-ANXA2) were synthesized. To establish stable cell lines with TM9SF1 knockdown and overexpression, a TM9SF1 lentiviral plasmid and packaging plasmids were introduced into HEK 293 T cells to produce lentiviral particles. Subsequently, these particles were transfected into AML12 cells, which were then subjected to selection using medium containing 2 μg/mL puromycin (Gibco, Carlsbad, CA, USA) for 7 days. The plasmid sequence information for TM9SF1 knockdown lentivirus employed in this study is detailed in Supplement-Table 3.

Cell Culture and Hypoxia-Reoxygenation (H/R) Experiments

In this study, experiments were conducted using AML12 cells (ProCell Life Sciences & Technology, Wuhan, China). The cells were cultured in DMEM/F12 medium (Solarbio, Beijing, China), supplemented with 10% fetal bovine serum (Biowest, USA), 40 ng/ml dexamethasone (Beyotime, China), and 1 × ITS-G (BasaIMedia, China). The cell culture incubator was maintained at a constant temperature of 37 °C with a 5% CO2 concentration. To mimic the ischemic conditions, cells were exposed in a three-gas incubator (1% O2, 5% CO2, 94% N2) at 37 °C for 12 h using DMEM/F12 medium (Solarbio, Beijing, China), then reoxygenated for 6 h.

RNA Sequencing and Analysis

We extracted total RNA from cells and assessed RNA purity and concentration using a NanoDrop2000 spectrophotometer, with RNA integrity verified by Agilent2100 Bioanalyzer/LabChip GX. After passing RNA quality control, cDNA libraries were constructed according to the manufacturer's instructions. Quality-validated libraries underwent paired-end 150 bp (PE150) sequencing on a high-throughput platform, followed by comprehensive analysis of sequencing data. Subsequently, differentially expressed genes (DEGs) were identified using DESeq2 (v1.38.3) with an adjusted p-value threshold of < 0.05 (FDR correction), and visualized via volcano plots. Heatmaps displaying DEG expression patterns were generated using the heatmap.2 function from the gplots package (v3.1.3) in R. Gene sets were defined as known Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways or Gene Ontology (GO) biological process terms. Gene Set Enrichment Analysis (GSEA v3.0) was executed using the Signal2Noise metric to evaluate enrichment based on differential gene expression patterns. Statistically significant sets met both thresholds: *p* < 0.05 and FDR < 0.25. Separately, Fisher's exact test was employed for KEGG pathway enrichment analysis of DEGs. Pathway annotations were retrieved directly from the KEGG database, with *p* < 0.05 defining statistical significance.

Data Analysis

For data processing and statistical analysis, SPSS software version 22.0 was employed. The data were expressed as mean ± standard deviation (SD). The Student’s t-test was utilized to evaluate differences between two groups, while the one-way ANOVA was employed to assess differences among multiple groups. A p-value less than 0.05 was considered statistically significant.

Results

TM9SF1 Expression is Significantly Upregulated during Liver I/R Injury

In order to verify whether TM9SF1 plays a role in liver I/R injury, we first constructed a mouse 70% liver I/R injury model and divided the models into groups according to the reperfusion time to verify the expression of TM9SF1 after ischemia and reperfusion. Compared to the Sham group, I/R groups exhibited significantly enlarged areas of injury in HE-stained sections. However, the injury area peaked at 6 h post-reperfusion, followed by progressive reductions at 12 h and 24 h time points (Fig. 1A, 1). Similar trends were observed in ALT and AST levels (Fig. 1C). This observation confirmed the partially reversible nature of I/R-induced hepatic damage [23, 24]. Consequently, we hypothesized that TM9SF1 expression dynamically changed across reperfusion phases, prompting quantification of TM9SF1 at both mRNA and protein levels at multiple timepoints. Results demonstrated that TM9SF1 expression increased following liver I/R injury, with the most significant upregulation observed at 6 h post-reperfusion. While TM9SF1 expression remained elevated at 12 h post-reperfusion compared to the Sham group, the magnitude of increase was attenuated. By 24 h post-reperfusion, TM9SF1 expression levels returned to baseline (Fig. 1D-F). Therefore, we identified 6 h post-reperfusion as the critical time point of maximal TM9SF1 functional impact in this model. We performed immunohistochemistry on the liver after 6 h of reperfusion. Compared with the sham group, results showed a significant increase in TM9SF1 (Fig. 1J, 1). Furthermore, AML12 cells treated with H/R showed a significant increase in TM9SF1 mRNA and protein levels compared to the negative control (NC) group (Fig. 1G-I).

Fig. 1.

Fig. 1

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TM9SF1 expression was significantly increased in liver I/R injury. (A) Representative HE staining of liver tissues of mice at 6, 12, and 24 h after reperfusion or sham treatment (n = 6). Scale bar, 50 μm; (B) Statistical analysis of liver injury severity in HE staining; (C) Serum ALT/AST levels at 6, 12, and 24 h after reperfusion or sham treatment (n = 6); (D) TM9SF1 mRNA expression in liver tissues at 6, 12, and 24 h after reperfusion or sham treatment (n = 6); (E, F) TM9SF1 protein expression and statistical analysis in liver tissues at 6, 12, and 24 h after reperfusion or sham treatment (n = 6); (G) TM9SF1 mRNA expression in AML12 cells after H/R challenge (n = 3); (H,I) TM9SF1 protein expression and statistical analysis in AML12 cells after H/R challenge (n = 3); (J,K) TM9SF1 immunohistochemical staining and quantification of TM9SF1 expression of liver tissues at 6 h after reperfusion or sham treatment (n = 6). Scale bar, 50 μm; All data are presented as the mean ± SD. Levels of statistical significance are indicated as **p < 0.01, ***p < 0.001 and n.s. = not significant

TM9SF1 Aggravates I/R Injury-Related Liver Injury, Inflammation, Oxidative Stress

Some studies have reported that the inflammatory response caused by the liver I/R and the accumulation of oxygen free radicals are the molecular processes that involved in the damage [25]. Therefore, we further explored the role of TM9SF1 in liver I/R from three aspects: liver injury, inflammation, and oxidative stress. We constructed knockdown mice by AAV tail vein injection (Fig. 2A). The western blot results validated the knockdown of TM9SF1 in the liver (Fig. 2B-D). Following I/R injury in WT mice, there was a notable rise in serum transaminase (AST and ALT) levels. Remarkably, KD-TM9SF1 mice exhibited a more pronounced reduction (Fig. 2E). Additionally, consistent with the ALT/AST results, HE staining showed that liver necrosis was significantly decreased after I/R injury in the liver of KD-TM9SF1 mice (Fig. 2F, G). Next, we explored the validation of inflammation levels in knockdown mice. Within expectations, inflammatory cytokine levels (IL-1β, IL-6, and TNF-α) were markedly reduced in the livers of KD-TM9SF1mice compared to WT mice (Fig. 2H, Fig.S2 B). Correspondingly, a significant decline in Ly6g-positive inflammatory cells was observed in KD-TM9SF1 mice following I/R treatment compared to WT mice (Fig. 2I, J). Analysis through TUNEL staining revealed a lower incidence of hepatocellular death in KD-TM9SF1 mice post-I/R administration compared to WT mice (Fig. 2K, L). Moreover, oxidative stress decreased in KD-TM9SF1 mice compared to the WT mice after I/R administration (Fig. 2M, N). Measurements of serum SOD, GSH, and MDA demonstrated the same findings (Fig. S1 B). Similarly, we constructed overexpression mice of TM9SF1 and verified its efficiency (Fig. 3A-D). Interestingly, liver overexpression of TM9SF1 using AAV notably increased the liver damage response to I/R (Fig. 3E-G). Consistent with this, we observed significantly elevated levels of inflammatory factors in TM9SF1 mice (Fig. 3H-J, Fig.S2 A). In contrast to the results in KD-TM9SF1 mice, the TM9SF1 mice displayed a significant increase in hepatocellular death (Fig. 3K, 3). Similarly, oxidative stress levels showed a consistent elevated pattern (Fig. 3M, 3, Fig.S1 A). In conclusion, TM9SF1 significantly aggravated liver injury, inflammation levels, and oxidative stress levels during liver I/R injury.

Fig. 2.

Fig. 2

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TM9SF1 deletion alleviates liver I/R-related liver injury, inflammation, oxidative stress. (A) Diagram of the method for constructing AAV-knockdown (KD-TM9SF1) mice; (B-D) TM9SF1 mRNA and protein expression in liver tissues of WT and KD-TM9SF1 mice (n = 6); (E) Serum ALT/AST levels in WT and KD-TM9SF1 mice after reperfusion for 6 h (n = 6); (F) Representative HE staining of liver tissues from mice described in (E) (n = 6). Scale bar, 50 μm; (G) Statistical analysis of necrotic area of HE staining; (H) Serum levels of inflammatory cytokines IL-1β, IL-6, and TNF-α in mice described in (E) (n = 6); (I,J) Ly6g immunofluorescence staining and relative quantification analysis of liver tissues from mice described in (E) (n = 6); (K,L) TUNEL staining and quantification analysis of liver tissues from mice described in (E) (n = 6). Scale bar, 50 μm; (M, N) DHE staining and quantification analysis of liver tissues from mice described in (E). Scale bar, 50 μm. *p < 0.05, **p < 0.01, ***p < 0.001 and ns = not significant

Fig. 3.

Fig. 3

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TM9SF1 overexpression aggravates liver I/R-related liver injury inflammation, oxidative stress. (A) Diagram of the method for constructing AAV-overexpression (TM9SF1) mice; (B-D) TM9SF1 mRNA and protein expression in livers tissues of WT and TM9SF1 mice (n = 6); (E) Serum ALT/AST levels in WT and TM9SF1 mice after reperfusion for 6 h (n = 6); (F) Representative HE staining of liver tissues from mice described in (E) (n = 6). Scale bar, 50 μm; (G) Statistical analysis of necrotic area of HE staining (n = 6); (H) Serum levels of inflammatory cytokines IL-1β, IL-6, and TNF-α in mice described in (E) (n = 6); (I,J) Ly6g immunofluorescence staining and relative quantification analysis of liver tissues from mice described in (E) (n = 6); (K,L) TUNEL staining and quantification analysis of liver tissues from mice described in (E) (n = 6).Scale bar, 50 μm; (M,N) DHE staining and quantification analysis of liver tissues from mice described in (E) (n = 6).Scale bar, 50 μm. *p < 0.05, **p < 0.01, ***p < 0.001 and ns = not significant

TM9SF1 Exacerbates Cell Death, Inflammatory Responses and ROS Level in AML12 Challenged by H/R

To further investigate the impact of TM9SF1 on liver I/R injury at the cellular level, we established an in vitro model of H/R to mimic liver I/R injury using AML12 cells. We established stable cell lines with target gene overexpression or knockdown, and confirmed efficiency of genetic manipulation at both mRNA and protein levels (Fig. 4A-F). We performed PI staining on the H/R-treated cell lines to explore the impact of TM9SF1 on cell death. Results showed that the PI-positive cell proportion increased in the overexpression (OE)-TM9SF1 cell line, but decreased in the Sh-TM9SF1 cell line (Fig. 4I, 4). Consistent with our in vivo findings, the overexpression of TM9SF1 in AML12 led to elevated mRNA levels of inflammatory factors (IL-1β, IL-6, and TNF-α) following H/R treatment (Fig. 4G). Additionally, In the OE-TM9SF1 cell line, further increased ROS fluorescence intensity indicated that TM9SF1 could exacerbate oxidative stress level of cells (Fig. 4K, 4). Consistent with the above conclusions, the opposite phenomenon was shown in the Sh-TM9SF1 cell line (Fig. 4H, 4, 4). These results indicate that TM9SF1 in AML12 cells is a vital mediator of cell death, inflammatory responses and ROS levels during liver I/R injury.

Fig. 4.

Fig. 4

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TM9SF1 overexpression aggravates cell damage, inflammatory responses and ROS level in AML12 challenged by H/R. (A-C) TM9SF1 mRNA and protein expression in AML12 transfected with three shRNA plasmids with different sequences(n = 6); (D-F) TM9SF1 mRNA and protein expression in AML12 transfected with overexpression plasmid(n = 6); (G) The mRNA expression of IL-1β, IL-6, and TNF-α in vector and TM9SF1 AML12 cells subjected to 12 h hypoxia and 6 h of reoxygenation(n = 6); (H) The mRNA expression of IL-1β, IL-6, and TNF-α in Sh-NC and Sh-TM9SF1 AML12 cells subjected to 12 h hypoxia and 6 h of reoxygenation(n = 6); (I,J,M,O) Representative Hoechst/PI staining and quantification analysis in NC, Sh-TM9SF1, TM9SF1 AML12 cells(n = 6).Scale bar, 20 μm; (K,L,N,P) ROS staining and quantification analysis in NC, Sh-TM9SF1, TM9SF1 AML12 cells(n = 6).Scale bar, 20 μm. *p < 0.05, **p < 0.01, ***p < 0.001 and ns = not significant

TM9SF1 Aggravates Autophagy in Vivo And in Vitro Models

Considering TM9SF1's role in autophagy regulation, we aimed to determine if the increased TM9SF1 expression promotes autophagy observed in liver tissues after I/R and AML12 cells treated with H/R. We assessed the expression levels of three autophagy-related proteins, LC3B-II/I and p62. We observed increased LC3B-II/I ratio and decreasedp62 levels in WT mice following liver I/R. Notably, mice with TM9SF1 overexpression exhibited a more pronounced increase in autophagy levels (Fig. 5A, 5). In contrast, autophagy levels were significantly diminished in the KD-TM9SF1 group compared to the WT group (Fig. 5C, 5). Similarly, we found that compared with the NC group, the autophagy level in the TM9SF1 overexpression group increased after H/R (Fig. 5E, 5), while the Sh-TM9SF1 group showed the opposite outcome (Fig. 5G, 5). Immunohistochemical analysis of TM9SF1 and KD-TM9SF1 mouse liver were consistent with above western blot findings (Fig. 5I, 5). Transmission electron microscope analysis revealed livers of TM9SF1 mice had significantly more autophagosomes than WT mice livers (Fig. 5K). To ascertain whether increased LC3B-II/I resulted from heightened autophagic vesicle formation or diminished autophagolysosomal degradation, we employed an autophagic flux inhibitor, Bafilomycin A1 (Baf-A1). The addition of Baf-A1 heightened the expressions of LC3B-II/I and p62, increasing autophagosome accumulation (Fig. 5L, 5). Subsequently, we performed electron microscopy observations on TM9SF1-overexpressing cells treated with Baf-A1. Our analysis demonstrated that AML12 overexpressing TM9SF1 exhibited a significant increase in autophagosome formation. Following additional treatment with Baf-A1, a further accumulation of autophagosomes was observed, consistent with the expected inhibitory effect on autophagosome-lysosome fusion (Fig. 5N). In conclusion, our investigation confirmed alterations in autophagy markers from various angles, consistently indicating that TM9SF1 expression fosters autophagy during liver I/R injury.

Fig. 5.

Fig. 5

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TM9SF1 overexpression aggravates autophagy in both in vivo and in vitro models. (A,B) Autophagy-related protein (LC3B-II/I and p62) levels of liver tissues in WT and TM9SF1 mice after reperfusion for 6 h(n = 6); (C,D) Autophagy-related protein levels of liver tissues in WT and KD-TM9SF1 mice after reperfusion for 6 h(n = 6); (E,F) Autophagy-related molecules protein levels of vector and TM9SF1 AML12 cells subjected to 12 h hypoxia and 6 h of reoxygenation(n = 6); (G,H) Autophagy-related protein levels of Sh-NC and Sh-TM9SF1 AML12 cells with H/R treatment(n = 6); (I) LC3B immunohistochemical staining of liver tissues described in (A) (n = 6). Scale bar, 50 μm; (J) LC3B immunohistochemical staining of liver tissues described in (C) (n = 6). Scale bar, 50 μm; (K) Ultrastructure showing autophagosomes in liver tissues described in (A), Scale bar, 1 μm; (L,M) Autophagy-related protein levels of vector and TM9SF1 AML12 cells subjected to H/R and Baf-A1(n = 6); (N) Ultrastructure showing autophagosomes in cells described in (L), Scale bar, 1 μm. *p < 0.05, **p < 0.01, ***p < 0.001 and ns = not significant

TM9SF1 Activates MAPK Signaling during Liver I/R Injury

To elucidate the mechanism underlying the regulatory activity of TM9SF1 on liver I/R injury, we conducted RNA sequencing (RNA-Seq) on samples from Sh-NC and Sh-TM9SF1 cell lines treated with H/R. Pearson correlation and heatmap identified the key factors contributing to the distinctions between Sh-NC and Sh-TM9SF1 cell samples (Fig. 6A, 6). The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that the MAPK signaling pathway was significantly enriched in TM9SF1-mediated liver I/R injury (Fig. 6C). Subsequently, we investigated whether the MAPK pathway plays a crucial role in modulating TM9SF1 functions during liver I/R injury. Notably, the overexpression of TM9SF1 in liver tissues led to the activation of ERK, JNK, and P38 phosphorylation (Fig. 6E, 6). Conversely, a reduction in the phosphorylation levels of ERK, JNK, and P38 was noted in KD-TM9SF1 mice experiencing liver I/R injury (Fig. 6G, 6). These findings were further validated in the TM9SF1and Sh-TM9SF1 cell lines under H/R conditions (Fig. 6I-L). Taken together, these findings demonstrate that during liver I/R injury, the overexpression of TM9SF1 triggers the activation of the MAPK pathway.

Fig. 6.

Fig. 6

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TM9SF1 overexpression activates MAPK signaling during liver I/R injury. (A) Pearson correlation analysis between Sh-NC and Sh-TM9SF1 AML12 cells with H/R treatment; (B) Heatmap analysis between Sh-NC and Sh-TM9SF1 AML12 cells with H/R treatment; (C) KEGG Enrichment Scatter Plot analysis between Sh-NC and Sh-TM9SF1 AML12 cells with H/R treatment; (D) Volcano plot between Sh-NC and Sh-TM9SF1 AML12 cells with H/R treatment; (E,F) Protein levels of total and phosphorylated ERK, JNK, and P38 in the liver of WT and TM9SF1 mice after liver I/R injury (n = 6); (G,H) Protein levels of total and phosphorylated ERK, JNK, and P38 in the liver of WT and KD-TM9SF1 mice after liver I/R injury (n = 6); (I,J) Protein levels of total and phosphorylated ERK, JNK, and P38 in the vector and TM9SF1 AML12 cells with H/R treatment(n = 6); (K,L) Protein levels of total and phosphorylated ERK, JNK, and P38 in the Sh-NC and Sh-TM9SF1 AML12 cells with H/R treatment(n = 6); All data are presented as the mean ± SD. *p < 0.05, **p < 0.01, ***p < 0.001 and n.s. = not significant

TM9SF1 and ANXA2 Interaction Exacerbates Liver I/R Injury

The aforementioned content highlights TM9SF1's ability to enhance the activation of the MAPK pathway. Given the pathway’s critical role in cell proliferation and survival, understanding its interaction with TM9SF1 may reveal new disease mechanisms. To explore this interplay, we performed mass spectrometry on TM9SF1-overexpressing cells. The findings revealed ANXA2 as the potential partner that interacted with TM9SF1, reported to activate MAPK pathway and autophagy [26]. Molecular docking analysis revealed that TM9SF1 can bind to ANXA2(Fig. 7A). In addition, co-IP analysis also validated the interaction between TM9SF1 and ANXA2(Fig. 7B, 7). Subsequently, we investigated the subcellular localization of TM9SF1 and ANXA2 using the AML12 cell line. We observed significant overlap in their subcellular localization patterns (Fig. 7D). Subsequently, to investigate the involvement of TM9SF1 in liver I/R injury through its interaction with ANXA2, we administered AAV-mediated ANXA2 knockdown based on TM9SF1 mice and also created ANXA2 disruption in TM9SF1 stably transfected cell lines (Fig. S4 B). In comparison to the TM9SF1 mice, the KD-ANXA2 mice exhibited a notable decrease in serum ALT/AST levels (Fig. 7E). Consistent results confirmed this from HE and TUNEL staining (Fig. 7F-I). Subsequently, we assessed DHE levels along with serum SOD, GSH, and MDA levels in KD-ANXA2 mice. The results were remarkably consistent, showing decreased oxidative stress levels following ANXA2 knockdown (Fig. 7J, 7, Fig.S1 C). In summary, the downregulation of ANXA2 effectively attenuated TM9SF1-induced injury. Moreover, we validated the expression levels of MAPK pathway and autophagy proteins in ANXA2-interfered mice and cells. Consistently, in contrast to the overexpressed mice and cells, interference with ANXA2 suppressed activation of the MAPK pathway (Fig. 7L, 7, Fig.S4 C, D). Furthermore, Western blot results demonstrated a decrease in the LC3B-II/I ratio and an increase in P62 expression, suggesting a significant inhibition of autophagy activation (Fig. 7M, 7, Fig. S4 E, F). Furthermore, based on molecular docking results and binding energy analysis, we introduced site-directed mutations in the region of ANXA2 predicted to tightly bind with TM9SF1. We found that the mutated ANXA2 lost its ability to bind TM9SF1 (Fig. S5 A). Moreover, transfection with this binding-deficient ANXA2 mutant plasmid significantly attenuated TM9SF1-mediated activation of the MAPK pathway and its promotive effect on autophagy (Fig. S5 B-E).

Fig. 7.

Fig. 7

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TM9SF1 and ANXA2 interaction exacerbates liver I/R injury. (A) Molecular docking analysis of TM9SF1 and ANXA2; (B, C) Flag-tagged TM9SF1 and HA-tagged ANXA2 plasmids were co-transfected into AML12 cells. Anti-Flag and Anti-HA antibodies was used for immunoprecipitation; (D) Immunofluorescence co-localization of TM9SF1 and ANXA2 in AML12 cells; (E) Serum ALT/AST levels in TM9SF1 mice and KD-ANXA2 mice after liver I/R injury (n = 6); (F) Representative HE staining of liver tissues from mice described in (E) (n = 6). Scale bar, 50 μm; (G) Statistical analysis of necrotic area of HE staining(n = 6); (H, I) TUNEL staining and quantification analysis of liver tissues from mice described in (E) (n = 6). Scale bar, 50 μm; (J, K) DHE staining and quantification analysis of liver tissues from mice described in (E) (n = 6). Scale bar, 50 μm; (L) Protein levels of total and phosphorylated ERK, JNK, and P38 in the liver from mice described in (E) (n = 6); (M) Autophagy-related protein (LC3B and p62) levels of liver from mice described in (E) (n = 6); (N) Protein levels of total and phosphorylated ERK, JNK, and P38 in TM9SF1 and si-ANXA2 AML12 cells with H/R treatment(n = 6); (O) Autophagy-related molecules (LC3B and p62) protein levels of TM9SF1 and si-ANXA2 AML12 cells with H/R treatment(n = 6); All data are presented as the mean ± SD. *p < 0.05, **p < 0.01, ***p < 0.001 and ns = not significant

Our previous findings demonstrated that TM9SF1 promotes autophagy and activates the MAPK pathway. Given that MAPK-mediated regulation of autophagy has been well established in multiple studies [27–30], we sought to determine whether TM9SF1 enhances autophagic activity specifically through MAPK activation. Thus, we treated OE-TM9SF1 AML12 cells with the MAPK inhibitor SP600125 and observed a marked reduction in autophagy levels (Fig. S3).

In conclusion, these findings suggest that ANXA2 interference can ameliorate liver damage, reduce oxidative stress levels, inhibit MAPK pathway activation, and suppress autophagy induction triggered by TM9SF1 in liver I/R injury. Additionally, these results underscore the involvement of TM9SF1 in liver I/R injury through the regulation of the MAPK pathway and autophagy via its interaction with ANXA2.

Pharmacological Inhibition of TM9SF1 Attenuates Liver I/R Injury

To investigate the therapeutic potential of a TM9SF1 inhibitor in liver I/R injury, we screened molecules in the molecular library in DrugBank database (2452 molecules) capable of interacting with TM9SF1 using virtual screening. Following docking analysis, ten compounds with lowest MMGBSA scores were selected, and their impact on TM9SF1 expression was subsequently evaluated (Fig. 8A). Western blotting demonstrated that lomitapide most potently inhibited on the expression of TM9SF1(Fig. 8B). Analysis from molecular docking indicated the potential binding of lomitapide to TM9SF1(Fig. 8C). Furthermore, at the atomic level, the molecular dynamics simulation validated stability and dynamics of the complex formed by TM9SF1 and lomitapide (Fig. 8D-G). Subsequently, we corroborated the impact of lomitapide on liver I/R injury. Interestingly, following I/R treatment, the serum ALT/AST levels in the treated group decreased significantly compared to the untreated group, with a more pronounced reduction observed in the high-concentration treated group (Fig. 8H). HE and TUNEL staining similarly showed lomitapide has the potential to mitigate necrosis and hepatocellular death in liver tissue samples (Fig. 8I-L). DHE staining along with measurement of serum SOD, GSH, and MDA levels also revealed that lomitapide inhibited I/R-induced oxidative stress (Fig. 8M, 8, Fig. S1 D). Collectively, these results identify lomitapide as a promising therapeutic candidate that attenuates liver I/R injury by reducing TM9SF1 expression.

Fig. 8.

Fig. 8

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Pharmacological inhibition of TM9SF1 attenuates liver I/R injury. (A)Docking results of potential compounds withTM9SF1. (B) Protein levels of TM9SF1 in liver tissues with different drug treatments; (C) Molecular docking analysis of TM9SF1 and lomitapide; (D) Root mean square deviation (RMSD) change curve of TM9SF1_Lomitapide complex system during simulation; (E) RMSD change curve of TM9SF1_Lomitapide complex system during simulation; (F) Changes in the number of hydrogen bonds between lomitapide and TM9SF1 protein during molecular dynamics simulation; (G) Top 10 amino acids contributing to small molecule and protein binding(ΔGbind: binding free energy); (H) Serum ALT/AST levels in the lomitapide-treated group and the control group(n = 6); (I) HE staining of liver tissues from the lomitapide-treated group and the control group(n = 6). Scale bar, 50 μm; (J) Statistical analysis of necrotic area of HE staining(n = 6); (K, L) TUNEL staining and quantification analysis of liver tissue from the lomitapide-treated group and the control group(n = 6). Scale bar, 50 μm; (M, N) DHE staining and quantification analysis of liver tissue from the lomitapide-treated group and the control group (n = 6). Scale bar, 50 μm. **p < 0.01, ***p < 0.001 and ns = not significant

Discussion

While TM9SF1's role in inflammation and autophagy is known [17, 18], its specific involvement in liver ischemia–reperfusion injury remains unexplored. We found significant upregulation of TM9SF1 in liver I/R injury mice and in AML12 cells undergoing H/R. TM9SF1 was upregulated in mice after liver I/R and in AML12 cells undergoing H/R. Furthermore, gain- and loss-of-function experiments showed that TM9SF1 exacerbates liver I/R injury via autophagy induction [31]. TM9SF1 activates the phosphorylation of the MAPK pathway by binding ANXA2, promoting excessive autophagy and liver I/R injury. Additionally, we discovered that lomitapide alleviated liver I/R injury by inhibiting the expression of TM9SF1. Findings establish the TM9SF1-ANXA2 axis as a potential therapeutic target for liver I/R injury treatment.

Liver I/R injury comprises two distinct phases: ischemia and reperfusion. During ischemia, the body activates the antioxidant system to maintain oxidative stress homeostasis. However, progressive ischemic damage compromises ROS clearance capacity, leading to ROS accumulation. This imbalance leads to progressive accumulation of oxidative stress, causing cellular damage [32]. During reperfusion, blood flow restoration increases inflammation [33], oxidative stress [34], autophagy activation [35], and mitochondrial dysfunction [36], exacerbating the injury. Thus, inflammation and ROS are key pathophysiological processes of liver I/R injury. Though controversial, autophagy is critical pathophysiological process of liver I/R injury [37]. While moderate autophagy could clear damaged organelles and safeguard against I/R injury [38], excessive autophagy may cause cell death [39]. Haojie Wang et al. suggest in liver diseases, autophagy regulation varies across pathways [40]. Hence, regulatory mechanisms differ, which suggests distinct autophagy regulation. The mechanisms and effects of different molecules and pathways involved in autophagy may be different, which may also imply the uniqueness of autophagy regulation and potential targeted therapeutic value. Our study revealed that TM9SF1 exacerbates liver injury by amplifying inflammatory responses, oxidative stress responses, and autophagic flux. Given the complexity of liver I/R injury pathogenesis, identifying molecular targets represents a promising therapeutic strategy. GivenTM9SF1's regulatory role in autophagy, TM9SF1 is a novel target for modulating autophagic activity in liver I/R injury.

The MAPK pathway is involved in liver I/R injury, and its inhibition ameliorates liver damage [21][41]. MAPK-regulated autophagy occurs in multiple diseases [42][43]. Pan-MAPK modulators may dysregulate metabolism Consequently, identifying upstream regulatory targets governing the MAPK axis is critically imperative. TM9SF1 was found to activate MAPK phosphorylation Mass spectrometry of TM9SF1-overexpressing cells identified ANXA2 as an interactor. Annexin A2(ANXA2) is a calcium-dependent phospholipid-binding protein [44]. Possessing multifunctional characteristics, ANXA2 can engage with a range of ligands, influencing a variety of cellular processes [45]. ANXA2 is associated with multiple pathological mechanisms such as cellular immune inflammation, pyroptosis [46], apoptosis, ferroptosis [47], and cancer metastasis [48]. Moreover, Kaili Fu et al. revealed that the surface protein TMPC of S. anginosus can enhance the phosphorylation activation of the MAPK pathway by binding to ANXA2 on gastric epithelial cells, thereby fostering gastric cancer progression [26]. Subhadip Mukhopadhyay et al. highlighted ANXA2's involvement in modulating fluctuations in autophagy [49], while Minsoo Koh et al. demonstrated ANXA2's role in promoting autophagy in triple-negative breast cancer (TNBC) [50]. ANXA2 is highly expressed in hepatocytes [46, 51–53]. We confirmed that TM9SF1 and ANXA2 physically interact enabling TM9SF1 to activate MAPK, thereby exacerbating liver I/R injury. Thus, the TM9SF1-ANXA2 axis is a promising therapeutic target for liver I/R injury. Through virtual screening of FDA-approved drugs targeting TM9SF1, followed by molecular dynamics simulations and experimental validation, we have established the translational feasibility of modulating this pathway.

A limitation of this study is that the experimental design primarily centered on the interaction between TM9SF1 and ANXA2, without delving deeper into TM9SF1's effect on ANXA2 expression or binding mechanism. Further validation is required. In addition, our study focused specifically on the role of TM9SF1 in liver I/R injury via ANXA2 binding. Whether TM9SF1 functions via alternative pathways requires further investigation and validation. The use of AAV-shRNA-mediated knockdown, though effective for whole-organ gene suppression, inherently lacks both temporal control and cell-type resolution—critical advantages of inducible conditional knockout models that enable targeted ablation in specific cell populations at defined timepoints. Additionally, a notable limitation of our study is using only animal and cellular models, lacking human validation. Consequently, clinical translation of these promising findings requires rigorous validation in human tissues prior to therapeutic application.

In conclusion, we showed that TM9SF1 mediates liver I/R injury by regulating autophagy levels. Our findings suggest that TM9SF1 may promote MAPK pathway phosphorylation through its interaction with ANXA2, promoting autophagy induction and exacerbating injury. Thus, targeting of the TM9SF1-ANXA2 axis could represent a promising strategy for mitigating liver I/R injury.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 121 KB) (120.6KB, pdf)
Supplementary file2 (PDF 699 KB) (698.8KB, pdf)
Supplementary file3 (PDF 1830 KB) (1.8MB, pdf)

Acknowledgements

The mechanism diagrams in this article were partially drawn by the biorender online site, thanks to the biorender site for their help with this article (https://app.biorender.com/).

Author contributions

Tongtong Wu: Conceptualization, Investigation, Writing the original draft; Wendong Li: Investigation, Validation; Ying Zhu, Xudong Liu, Haocheng Yu, Hao Li: Investigations, Methods; Jiakai Zhang, Hongwei Tang: Project management; Mingjie Ding: Data curation, Review; Wenzhi Guo: Supervision, Validation.

Funding

This work was supported by grants from the National Natural Science Foundation of China (82170648, 82370646), Science and technology innovation team in Henan Higher Education Institutions (24IRTSTHN038), funding for Scientific Research and Innovation Team of The First Affiliated Hospital of Zhengzhou University (ZYCXTD2023007), Postdoctoral Fellowship Program of CPSF under Grant Number (GZC20232405) and Gandanxiangzhao (HKP2023004).

Data Availability

The accession number for the RNA-Seq data reported in this paper is GSE300727 and is publicly accessible at [https://www.ncbi.nlm.nih.gov/geo/].

Declarations

Ethical Approval and Consent to Participate

This study was conducted in accordance with the Declaration of Helsinki and was approved by the Clinical Research Ethics Committee of the First Affiliated Hospital of Zhengzhou University (2023-KY-0761–002).

Clinical trial number

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Tongtong Wu and Wendong Li contributed to the work eqully and should be regarded as co-first authors.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary file1 (PDF 121 KB) (120.6KB, pdf)
Supplementary file2 (PDF 699 KB) (698.8KB, pdf)
Supplementary file3 (PDF 1830 KB) (1.8MB, pdf)

Data Availability Statement

The accession number for the RNA-Seq data reported in this paper is GSE300727 and is publicly accessible at [https://www.ncbi.nlm.nih.gov/geo/].

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