m6A Modification Destabilizes Prss8 and Activates Hepatic Stellate Cells via TLR4-Mediated Inflammatory Responses

Abstract

The 6-methyladenine (m6A) modification plays a major role in various diseases. Serine protease 8 (Prss8) contributes to the initiation and progression of liver fibrosis (LF). However, the mechanism by which the m6A modification of Prss8 induces hepatic stellate cells (HSCs) activation in the LF is unclear. This study focused on exploring the contribution of Prss8 m6A modification to the pathogenesis of LF. First, primary hepatic parenchymal cells (hepatocytes) and HSCs were isolated from a mouse model of LF, and a coculture of these two types of cells was used as the object of study. Then, real-time fluorescence quantitative PCR, methylated RNA immunoprecipitation, and Western blotting were used to test the expression levels of Prss8 mRNA and protein, Prss8 m6A modification, Collagen I, α-SMA, and TLR4. Finally, the expression levels of inflammatory markers were measured via an enzyme-linked immunosorbent assay. Compared with the control group, the model group presented significantly lower Prss8 mRNA and protein levels in hepatocytes but greater levels of Prss8 m6A modification; moreover, the expression of HSC activation markers and the TLR4, IL-1β, and IL-18 proteins was significantly elevated. Mutation of the Prss8 m6A modification site led to upregulation of Prss8 mRNA and protein and decreased levels of m6A modification, TLR4, IL-1β, and IL-18. Furthermore, mutation of the Prss8 m6A modification site increased the stability of Prss8 mRNA. Rescue experiments confirmed the regulatory link between Prss8 m6A modification and TLR4. Overall, Prss8 m6A modification decreases the stability of its mRNA, promoting TLR4-mediated inflammatory cascades and leading to excessive activation of HSCs. Targeting Prss8 m6A modification is a promising therapeutic strategy for LF.

Introduction

Liver fibrosis (LF) is a compensatory response during chronic and persistent liver inflammation or tissue repair after injury caused by a variety of pathogenic factors (Liu et al., 2023). Both parenchymal and nonparenchymal cells are present in the liver, with hepatic stellate cells (HSCs) being crucial among nonparenchymal cells (Bian et al, 2015; Liu et al, 2006). The activation of HSCs by inflammatory cytokines represents a central event in the pathogenesis of LF (Fan et al., 2023; Liu et al., 2022). Timely and effective anti-hepatic fibrosis treatment is necessary to prevent the transformation of chronic liver disease into end-stage liver disease (Zhou et al., 2021). However, the specific pathogenesis of LF is not yet completely clear. Thus, investigating the molecular mechanisms underlying LF pathogenesis holds significant theoretical and clinical importance.

The 6-methyladenine (m6A) modification refers to a dynamic and reversible methylation process that occurs on the sixth N atom of base A. Among eukaryotes, m6A is a widely occurring modification of RNA after transcription (Zhang et al., 2022). The m6A modification can affect various aspects of mRNAs, including transcription, splicing, localization, translation, stability, and posttranscriptional regulation at the RNA level (Wu et al., 2022). An increasing amount of evidence suggests that m6A modification may mediate the occurrence of LF. For example, ATG9A was shown to promote HSC autophagy and activation in an FTO-mediated m6A-dependent manner, thereby alleviating LF (Huang et al., 2025). Another study showed that WTAP-mediated m6A modification can reduce the mRNA stability of AP-2α, promote the secretion of inflammatory factors by macrophages to stimulate hepatic cells, and thus promote hepatic steatosis and fibrosis (Li et al., 2025). Thus, the m6A modification provides new research perspectives into LF for its pathogenesis, diagnosis, and treatment.

We have shown in previous research via comprehensive analysis of m6A-Seq and RNA-Seq data that the m6A modification level and mRNA expression of serine protease 8 (Prss8), a key pathogenic gene of LF, were significantly changed (Fan et al., 2021). Prss8 is a membrane-anchored serine protease reportedly involved in fibrosis-related cell migration and invasion (Gao et al., 2022). Moreover, the literature indicates that Prss8 proteolytically cleaves TLR4 at extracellular arginine and lysine residues, downregulating its expression (Uchimura et al., 2014). A study has shown that the inflammatory cascade reaction induced by TLR4 activation can stimulate the proliferation of HSCs and promote the occurrence and development of LF (Demel et al., 2022). However, the mechanism by which Prss8 mediates the pathogenesis of LF remains unclear.

Based on the preliminary sequencing results and literature, we propose that the Prss8 m6A modification decreases the stability of Prss8 mRNA, promotes TLR4 expression, mediates inflammation, and activates HSCs. The aim of this study was to identify the underlying mechanism of Prss8 m6A modification in LF pathogenesis, which could serve as a therapeutic strategy for LF.

Materials and Methods

Animal experiments

Animals

Male Specific Pathogen Free (SPF)-grade C57BL/6 mice weighing 20 ± 2 g and aged 6–8 weeks were purchased from Hangzhou Ziyuan Experimental Animal Technology Co., Ltd. The mice were acclimatized for 1 week, then divided into model and control groups. The number of mice in each group was determined based on the amount of primary cells required for the experiment. The model group received a single subcutaneous injection of 20% CCl₄ (0.1 mL/10 g; CCl₄ diluted in olive oil, v/v = 1:4) twice a week for 12 weeks (Jiang et al., 2017). The control group received no treatment. Liver samples from the mice were used to isolate hepatocytes and HSCs via in situ liver perfusion. The experiments employed a coculture cell model of hepatocytes and HSCs. After the cells were lysed with lysis buffer, proteins and RNA were extracted. Protein quantification was performed via the Bicinchoninic Acid Assay (BCA) assay, and RNA quantification was carried out with an ultramicro spectrophotometer. The protocols approved by the Ethics Committee of Anhui University of Traditional Chinese Medicine were followed during the animal experiments (AHUCM-mouse-2023085).

Cell coculture and plasmid transfection

Primary hepatocytes and HSCs were isolated from the control and model groups via in situ liver perfusion and served as the control and model groups, respectively (Fan et al., 2021). Plasmid-transfected cells were then added to the model group. Briefly, the cells were digested with 0.05% collagenase, and the hepatocytes and HSCs were seeded into six-well plates and cultured overnight. After transfection with the corresponding plasmids or siRNAs, the cocultured hepatocytes and HSCs were collected for subsequent experiments. The plasmid vector and control plasmid empty vector were constructed by General Biotech (Anhui) Co., Ltd, and the type of vector used was pcDN3.1, with a size of 1698 bp. Prss8 and TLR4 were transfected according to the instructions.

Real-time fluorescence quantitative PCR

Total RNA extraction was performed via TRIzol (Invitrogen), and complementary DNA (cDNA) synthesis was carried out via the PrimeScript^TM RT reagent kit (TaKaRa, RR047A). RT-PCR utilized this cDNA as a template to quantify fluorescence with the following reaction conditions: initial denaturation at 95°C for 30 s, followed by 40 cycles of 95°C for 40 s and 60°C for 30 s. The results were analyzed via the relative quantification method and the 2^−ΔΔCt calculation method to determine gene expression. The primer sequences are shown in Table 1.

Table 1.

The Primer Sequence

Gene	Amplicon size (bp)	Primer (5′−3′)
Prss8	126	Forward: CTGCAGAGAGACTAAAGGGGC Reverse: CGACTGGAGCAATCCGAGAA
TLR4	170	Forward: AAGTGGCCCTACCAAGTCTC Reverse: TCGGATACTTCAGCGTCAGGA
α-SMA	102	Forward: GTCCCAGACATCAGGGAGTAA
		Reverse: TCGGATACTTCAGCGTCAGGA
Collagen I	88	Forward: AACTGGTACATCAGCCCGAA
		Reverse: TTCCGTACTCGAACGGGAAT
β-actin	120	Forward: AGTGTGACGTTGACATCCGTReverse: TGCTAGGAGCCAGAGCAGTA

Western blot

Using Radioimmunoprecipitation Assay (RIPA) buffer, the cells were lysed and centrifuged to obtain total protein. After separation by Sodium Dodecyl Sulfate – Polyacrylamide Gel Electrophoresis (SDS–PAGE), the proteins were transferred onto a PVDF membrane. After blocking with 5% skim milk for 2 h, the Polyvinylidene difluoride (PVDF) membranes were incubated with primary anti-β-actin (Zs-BIO, TA-09, 1:1000), collagen I (Affinity, AF7001, 1:500), Prss8 (Affinity, DF12224, 1:500), TLR4 (Affinity, AF7017, 1:500), and α-Smooth Muscle Actin (α-SMA) (Affinity, AF1032, 1:500) antibodies and incubated overnight. The membrane was washed with Phosphate Buffered Saline with Tween (PBST) and then incubated with the appropriate secondary antibodies (1:10,000) for 2 h at room temperature. The proteins were identified through an automatic exposure device and imaged via an enhanced chemiluminescence reagent. The grayscale values of the protein bands were analyzed via ImageJ software, which calculates the ratio of the target protein to the grayscale value of β-actin.

RNA methylation immunoprecipitation-qPCR

The extracted 15 µg of RNA and immune capture solution (Immuno Capture Buffer, 2 µL of m6A antibody, and Affinity Beads) were added to the PCR tube, which was incubated at ambient temperature for 90 min, and 150 µL of each reaction tube was washed three times with wash buffer and once with 150 µL of PDB. The purification and elution of the enriched RNA were then performed following the manufacturer’s instructions. RT-qPCR detection was subsequently performed. The response conditions were as follows: initial denaturation at 95°C for 1 min, followed by 40 cycles of 95°C for 20 s and 95°C for 45 s. The result analysis method was the relative quantification method, and the calculation method was the 2^−ΔΔCt method.

RNA stability measurement

The cells were treated with 4 µM actinomycin D for 0 h, 2 h, 4 h, or 8 h. The cells were collected at different time points, and each group of RNA was extracted and analyzed via real-time fluorescence quantitative PCR. Since the mRNA levels of GAPDH did not change after actinomycin D treatment, the GAPDH gene was used as a reference gene (Zeng et al., 2017). The 2^−ΔΔCt method was used to analyze the data. The sequences of primers used for detecting indicators are listed in Table 2.

Table 2.

The Primer Sequence

Gene	Amplicon size (bp)	Primer (5′−3′)
GAPDH	99	Forward: GGGTCCCAGCTTAGGTTCAT
		Reverse: CCAATACGGCCAAATCCGTT
Prss8	126	Forward: CTGCAGAGAGACTAAAGGGGC
		Reverse: CGACTGGAGCAATCCGAGAA

Cell counting kit-8

Cell counting kit-8 (CCK8; Servicebio, G4103) was used to measure the proliferative activity of HSCs and quantify cell proliferation following the manufacturer’s instructions. In brief, 1 × 10⁵ cells were seeded into each well of a 96-well plate, followed by the addition of 100 μL of complete medium. Subsequently, 10 μL of CCK-8 was added to each well, and the plate was incubated for 48 h. After incubation, the absorbance values of the wells were measured at 450 nm via an enzyme-linked immunoassay detector.

Flow cytometry

Flow cytometry was used to detect cycles of HSCs. The cells were first washed with PBS and fixed in 90% ethanol at 20°C for 1 h. Following three additional washes with PBS, the cells were resuspended in a staining solution containing 100 μL of RNase and incubated at 37°C for 30 min. Subsequently, 400 μL of Propidium Iodide (PI) staining solution was added to resuspend the cells, which were then stained for 3060 min at 4°C in the dark and analyzed within 24 h by flow cytometry for cell cycle detection.

Enzyme-linked immunosorbent assay

Enzyme-linked immunosorbent assay (ELISA) was used to measure the expression levels of the inflammatory markers IL-1β and IL-18. Supernatants were collected from cultures, and the IL-1β and IL-18 concentrations in the supernatants were evaluated via ELISA (Elabscience, China) following the manufacturer’s instructions.

Statistical analysis

All experiments were performed with at least three distinct replicates, and the results were statistically analyzed and graphed with Statistical Package for the Social Sciences (Version 23.0) software. The results are presented as the means ± standard deviations ( $\bar{x}$ ± s). Differences between the two groups were compared via a t test. Differences were compared between two or more groups via one-way analysis of variance. Statistical importance was indicated when p < 0.05.

Results

Low Prss8 expression is accompanied by an inflammatory response and HSC activation

To investigate the expression of Prss8 in LF we employed Western blotting (WB) and RT-qPCR and found that Prss8 expression was significantly reduced in hepatocytes (Fig. 1A–C). To investigate whether low Prss8 expression induced an inflammatory response and activated HSCs, we subsequently employed methods such as CCK8, flow cytometry, and WB to detect relevant inflammatory markers and HSC activation indicators. According to the CCK8 results, the cell activity of the HSCs in the model group was clearly greater than that in the control group (Fig. 1D). The flow cytometry results are shown in Figure 1E, F, and the number of HSCs in the G1 phase was significantly reduced. Changes in the expression levels of HSCs activation markers were detected via RT-qPCR and WB. As demonstrated in Figure 1G–L, there was a substantial increase in the expression of α-SMA and collagen I in the model group. In addition, ELISA was used to test the levels of inflammatory indicators in the supernatants of cocultured cells. The results revealed that the levels of the inflammatory indicators IL-1β and IL-18 were greatly increased (Fig. 1M, N).

FIG. 1.

Low expression of Prss8 is accompanied by inflammatory response and activation of HSCs. (A): RT-qPCR detects the expression of Prss8 mRNA in hepatocytes. (B) and (C): WB detects the expression of Prss8 protein in hepatocytes. (D): CCK8 detects cell viability of HSCs. (E) and (F): Flow cytometry to test cell cycle. a: Control group; b: Model group. (G): RT-qPCR detects the expression of α-SMA mRNA. (H) and (I): WB detects the expression of α-SMA protein. (J): RT-qPCR detects the expression of Collagen I mRNA. (K) and (L): WB Detection of Collagen I protein expression. (M) and (N): ELISA detection The expression levels of IL-1β and IL-18. Compared with the control group, **p < 0.01. HSCs, hepatic stellate cells; real-time fluorescence quantitative PCR, RT-qPCR; WB, Western blotting; ELISA, Enzyme-linked immunosorbent assay

Prss8 m6A modification decreases the stability of Prss8 mRNA

The significant increase in Prss8 m6A expression in the model group was further confirmed via methylated RNA immunoprecipitation-qPCR (MeRIP-qPCR) (Fig. 2A). To investigate whether the m6A modification of Prss8 affected its expression, we examined the changes in Prss8 protein, mRNA, and stability after mutation of the m6A site of Prss8. The findings indicated a reduced level of Prss8 m6A modification in the mutant group (Fig. 2B). As shown in Figure 2C–E, there was a significant increase in Prss8 mRNA and protein levels in the mutant group relative to those in the Wild Type (WT) group. After the m6A modification site was mutated (MUT), the degradation rate of Prss8 mRNA in hepatocytes was significantly reduced (Fig. 2F). These findings indicate that Prss8 m6A modification can decrease Prss8 mRNA stability.

FIG. 2.

Prss8 m6A modification decrease the stability of Prss8 mRNA. (A): MeRIP-qPCR detects the expression of Prss8 m6A in hepatocytes. (B): MeRIP-qPCR detection of Prss8 m6A in hepatocytes after mutation expression. (C): RT-qPCR detects the expression of Prss8 mRNA. (D) and (E): WB detects expression of Prss8 protein. (F): Actinomycin D experiment to detect the stability of Prss8 mRNA. Compared with the control group, **p < 0.01, Compared with the WT group,^## p < 0.01; ^# p < 0.05. MeRIP-qPCR, methylated RNA immunoprecipitation-qPCR.

Prss8 m6A modification activates HSCs

Given that m6A methylation is the most widespread RNA modification, it plays an essential role in the regulation of gene performance and signaling pathways (Karthiya and Khandelia, 2020). As a result, we examined how Prss8 m6A modification affects the activation of HSCs. According to the CCK8 results, the activity of HSCs in the mutant group was significantly lower than that in the WT group (Fig. 3A). The flow cytometry results are shown in Figure 3B, C. The number of G1 phase HSCs in the mutant group was significantly greater than that in the WT group. The RT-qPCR and WB results are shown in Figure 3D–1. There was a significant decrease in the α-SMA and collagen I expression levels in the mutant group. In addition, the ELISA results are shown in Figure 3J, K. There was a clear decrease in the expression levels of the inflammatory markers IL-1β and IL-18 in the mutant group compared with those in the WT group.

FIG. 3.

Prss8 m6A modification activates HSCs. (A): CCK8 detects HSCs cell viability. (B) and (C): Flow cytometry to detect cell cycle. a: MUT group; b: WT group. (D): RT-qPCR detects the expression of α-SMA mRNA. (E) and (F): WB detects the expression of α-SMA protein. (G): RT-qPCR detects the expression of Collagen I mRNA. (H) and (I): WB detects the expression of Collagen I protein expression. (J) and (K): ELISA detects the expression levels of IL-1β and IL-18. Compared with the WT group, ^## p < 0.01; ^# p < 0.05.

Effects of mutant Prss8 m6A on TLR4 expression

Several reports suggest that Prss8 can regulate TLR4 (Sugitani et al., 2020; Uchimura et al., 2014). In LF, TLR4 is a pivotal mediator that facilitates the release of IL-1β and IL-18, leading to an increased inflammatory response (Nicotra et al., 2012). To assess the regulatory effect of Prss8 on TLR4, we conducted further analysis. The expression level of TLR4 in LF hepatocytes was significantly greater than that in control hepatocytes, as indicated by the RT-qPCR and WB results (Fig. 4A–C). In contrast, the Prss8 m6A mutant group presented a noticeably lower level of TLR4 expression than the WT group did (Fig. 4D–F).

FIG. 4.

Effect of mutant Prss8 m6A on TLR4 expression. (A): RT-qPCR detects the expression of TLR4 mRNA. (B) and (C): WB detection of TLR4 protein expression. (D): RT-qPCR detects of TLR4 mRNA expression levels after Prss8 m6A mutation. (E) and (F): WB detection of TLR4 protein expression after Prss8 m6A mutation. Compared with the control group, **p < 0.01; Compared with the WT group, ^## p < 0.01.

Prss8 activates HSCs by regulating the expression of TLR4

To further study whether Prss8 m6A modification can affect the functional phenotype of HSCs through regulating TLR4, we subsequently conducted a recovery experiment. The results from the CCK-8 and flow cytometry assays indicated that TLR4 overexpression enhances HSC proliferation while simultaneously reducing the number of cells in the G1 phase (Fig. 5A–C). The RT-qPCR and WB results are shown in Figure 5D–1. Significant increases in α-SMA and collagen I expression were observed in the group with Prss8 m6A mutation and TLR4 upregulation. The ELISA results revealed that the levels of IL-1β and IL-18, which are indicators of inflammation, were significantly elevated in the cointervention group with Prss8 m6A modification site mutations and TLR4 overexpression (Fig. 5J, K). In summary, our results indicate that Prss8 can activate HSCs by regulating the expression of TLR4.

FIG. 5.

Prss8 activates HSCs by regulating high expression of TLR4. (A): CCK8 detects the cell viability of HSCs. (B–C): Flow cytometry to detect cell cycle; B: pink bar: The proportion of G1 phase (pre-DNA synthesis phase) cells in the total cell population; blue bar: The proportion of G2+S phase (late DNA synthesis phase) cells in the total cell population. (C): a: Control group: not treated; b: Model group: cells underwent model treatment; c: MUT group: transfected with the Prss8 m6A mut plasmid on the basis of the model; d: MUT+pc-TLR4 group: co-transfected with the Prss8 m6A mut plasmid and the TLR4 overexpression plasmid on the basis of the model; e: MUT+pc-NC group: co-transfected with the Prss8 m6A mut plasmid and the TLR4 negative control plasmid on the basis of the model. (D) and (E): RT-qPCR detects the mRNA expression of α-SMA and Collagen I. (F–I): WB detection the protein expression of α-SMA and Collagen I. (J) and (K): ELISA detects the expression levels of IL-1β and IL-18. Compared with the control group, **p < 0.01; compared with the model group, ^## p < 0.01, ^# p < 0.05; compared with the MUT group, ^&& p < 0.01.

Discussion

LF emerges as the inevitable result of numerous causes of chronic LF and is the last reversible step in the progression to cirrhosis and hepatocellular carcinoma (Hernandez-Gea and Friedman, 2011; Ni et al., 2017). Chronic inflammation plays an essential role in the pathogenesis of LF through the activation of HSCs (Li et al., 2019). In the liver, hepatocytes account for 80% of the total number of liver cells and play an essential role in LF (Mafanda et al., 2019). Numerous reports confirm that liver parenchymal cells can release IL-1β, IL-18, and other inflammatory factors, affecting HSCs activation (Charan et al., 2023; Xu et al., 2024; Zhang et al., 2018). In addition, activated HSCs themselves also produce inhibitory cytokines, which further promote LF (Liu et al., 2018; Tseng et al., 2019). Therefore, suppressing inflammation and improving the inflammatory microenvironment are key to treating LF. In our study, we found that the viability and activation indicators of HSCs were significantly increased and that the inflammatory factors IL-1β and IL-18 were highly expressed in the supernatant of cocultured cells.

We studied the molecular mechanism by which the m6A modification inhibits the activation of HSCs. This modification is closely related to the onset and development of LF (Sun et al., 2022; Wang et al., 2023). For example, it can regulate ferroptosis in HSCs and interact with immune infiltrating cells to affect the progression of LF (Alqahtani and Schattenberg, 2021; Zhao et al., 2022). Current studies on the impact of m6A methylation on liver cell biological functions emphasize gene and pathway regulatory mechanisms (Cao et al., 2021; Zhang et al., 2020). The m6A methylation-induced ablation of NR1D1 disrupts circadian rhythms and promotes LF in HSCs (Chen et al., 2023). An increasing body of evidence suggests that m6A modification may serve as a potential therapeutic target for LF. For example, Wei et al. reported that the administration of AcSDKP reduced the m6A modification of Ptch1 and inhibited HSC activation, thereby alleviating CCl₄-induced LF (Wei et al., 2022).

In the early stage, our research team used m6A-Seq and RNA-Seq sequencing to screen out the key differential Prss8 genes related to the onset of LF (Fan et al., 2021). Prss8 is also an oncogenic factor in the progression of hepatocellular cancer development, and its high expression significantly inhibits the proliferation and invasion of hepatocellular carcinoma cells (Zhang et al., 2016). However, the specific effects of Prss8 m6A on LF incidence and disease development are not yet known. Therefore, we chose to study the expression of Prss8 m6A in hepatocytes and observe the changes in HSCs after site mutation of Prss8 m6A. Research has shown that Prss8 m6A modification site mutation can reduce the viability of HSCs and the expression levels of HSCs activation indicators, which may decrease the occurrence and advancement of LF to a certain level.

TLR4 is a type I transmembrane protein that can initiate intracellular signal transduction through multiple pathways and is a crucial mediator of the proinflammatory response (Coutinho-Wolino et al., 2022). Studies have shown that TLR4 can regulate inflammatory responses, induce HSCs activation, and participate in the incidence and progression of LF (Li et al., 2024). Moreover, ample evidence suggests that TLR4 is important in many liver-related pathological states, ranging from hepatic steatosis to hepatic failure and inflammatory liver disease (Chen et al., 2018; Farrell et al., 2018). The activation of TLR4 triggers a series of complex cascade reactions. Under the stimulation of TLR4, the signal transduction of MyD88 induces the recruitment of IRAK1/4 and TRAF6, thereby activating the TAK1-IKK complex, which then activates NF‐κB and stimulates the production of IL-1β and IL-18, leading to inflammation (Li et al., 2022; Zhang et al., 2021). The inflammatory reaction stimulates the acceleration and multiplication of HSCs, triggers excessive production and synthesis of extracellular matrix(ECM), and promotes the onset and progression of LF (Dong et al., 2020; Flamini et al., 2021). Therefore, this study explored the role and potential mechanism of TLR4 in LF. The results were consistent with expectations, as TLR4 and its protein were highly expressed in LF.

Prss8 can exert anti-inflammatory effects by downregulating TLR4 signaling (Sugitani et al., 2020). Therefore, we explored the regulatory effect of Prss8 m6A modification on TLR4. Our results showed that mutation of the Prss8 m6A site can significantly downregulate the expression level of TLR4. In addition, rescue experiments further confirmed that overexpression of TLR4 can counteract the effects of point mutations in Prss8 m6A sites on hepatocyte inflammation and HSCs activation. These findings indicate that Prss8 m6A modification can regulate TLR4 signaling and thereby participate in the pathogenesis of LF.

Conclusion

This study revealed that Prss8 m6A modification decreased the stability of Prss8 mRNA, promoted downstream TLR4 expression, mediated inflammatory cascade reactions, and induced overactivation of HSCs. Therefore, targeting Prss8 m6A modification could be an innovative strategy for LF treatment.

Footnotes

Authors’ Contributions

H.C. and L.Z.: Writing—original draft. L.Z.: Data curation. T.L. and X.P.: Writing—review and editing. C.F.: Funding acquisition, supervision, writing—review and editing. H.J.: Funding acquisition, supervision, writing—review and editing, conceptualization.

Disclosure Statement

No conflict of interest exists in the submission of this article, which is approved by all authors for publication. On behalf of my coauthors, I would like to declare that the work described in the article was original research that has not been published previously or considered for publication elsewhere. All the authors listed in the article have approved the article.

Data Availability

Data will be made available on request.

Animal Subjects

The design of the experiment was approved by the Animal Ethics Committee of Anhui University of Chinese Medicine (Permit Number: AHUCM-mouse-2023085), and all methods were performed in accordance with the relevant guidelines and regulations.

Funding Information

The study was funded by National Natural Science Foundation of China (grant no. 82304995) and Natural Science Research Project of Anhui Educational Committee (grant no. 2022AH050530, 2023AH040115, and 2024AH040165). The authors thank all individuals who participated in or helped with this research.

Supplementary Material

Supplementary Data S1

Supplementary Data S2

Supplementary Data S3

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