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. 2025 Nov 18;17:192. doi: 10.1186/s13148-025-02000-0

HMGA1 drives EMT in obliterative bronchiolitis through epigenetic regulation of chromatin accessibility in pulmonary epithelial cells

Tian Xia 1, Zhaoyao Hou 1, Sihua Wang 2, Jingyao Sun 1, Hui Yang 1, Peng Miao 1, Chang Liu 1, Wantong Zheng 1, Li Wei 1,✉
PMCID: PMC12625754  PMID: 41254723

Abstract

Background

Post-transplant obliterative bronchiolitis (OB) is a major cause of lung graft dysfunction and failure, with the epithelial–mesenchymal transition (EMT) process playing a pivotal role in driving extracellular matrix (ECM) deposition and fibrosis.

Methods

A mouse heterotopic tracheal allograft model was established to replicate the clinical manifestations of post-transplant OB. Histopathological alterations of tracheal grafts were assessed using Hematoxylin and Eosin (HE) staining. Gene expression was quantified through enzyme-linked immunosorbent assay (ELISA), immunofluorescence (IF), immunohistochemistry (IHC), reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and Western blot assays. Differentially expressed genes (DEGs) in heterotopic tracheal grafts were identified by RNA sequencing (RNA-Seq). Chromatin accessibility was evaluated using assay for transposase-accessible chromatin with sequencing (ATAC-Seq).

Results

Histological analysis revealed progressive luminal occlusion (7–14 days), with significant inflammatory infiltration at day 7 and ECM deposition at day 14. Elevated IL-1β/IL-6 levels and reduced IL-10 confirmed immune activation. High mobility group at-hook 1 (HMGA1) was upregulated in allografts and mediated TGF-β1-driven EMT in vitro. Integration of ATAC-seq and RT-qPCR in pulmonary epithelial cells demonstrated that HMGA1 orchestrates extensive chromatin remodeling during OB pathogenesis. HMGA1 directly enhanced chromatin accessibility at EMT-promoting loci, including specificity protein 1 (SP1), dedicator of cytokinesis 4 (DOCK4), serum response factor (SRF), and anillin (ANLN). Epigenetic reprogramming of these regulatory regions induced TGF-β1-mediated EMT.

Conclusions

HMGA1 promotes EMT in OB by facilitating chromatin accessibility at EMT-associated loci, highlighting its potential as a therapeutic target for post-transplant intervention.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-025-02000-0.

Keywords: Lung transplantation, Obliterative bronchiolitis, Epithelial–mesenchymal transition, TGF-β1, HMGA1, Chromatin accessibility

Introduction

Lung transplantation remains the only viable treatment for individuals with end-stage lung disease [1]. Despite advancements in managing acute rejection post-transplant, chronic allograft dysfunction (CAD) continues to significantly hinder long-term survival of transplant recipients [2]. Data from the Organ Procurement and Transplantation Network (2019) reveals that approximately 10% of lung allografts exhibit functional deterioration within the first year, with more than half of recipients losing graft function within 5 years. Understanding the molecular mechanisms underlying CAD is therefore essential for enhancing clinical outcomes.

Post-transplant obliterative bronchiolitis (OB), the primary cause of CAD [3], is characterized by inflammatory and fibroproliferative changes in the small airways of transplanted lungs. Often considered a form of chronic rejection [4], OB involves early epithelial injury, subepithelial inflammation, and extracellular matrix (ECM) deposition, leading to airway fibrosis and luminal occlusion [5].

Although orthotopic lung transplantation in mice closely mimics clinical lung transplantation, its use in OB research is limited by technical challenges and poor reproducibility of lesions [6]. In 1993, Hertz et al. developed a heterotopic tracheal transplantation model, wherein tracheal grafts are implanted into the subcutaneous neck pockets of recipient mice [7]. This model replicates key OB pathological features, including epithelial damage, inflammatory infiltration, and fibrotic remodeling, while offering greater technical simplicity and reproducibility. In this study, we employed this model to investigate the molecular mechanisms driving OB progression.

Using the heterotopic tracheal allograft model, we simulated the early-stage pathological changes of post-transplant OB. Through RNA sequencing (RNA-Seq) and assay for transposase-accessible chromatin using sequencing (ATAC-Seq), we identified high mobility group at-hook 1 (HMGA1) as a pivotal epigenetic regulator of epithelial–mesenchymal transition (EMT), providing new insights into OB pathogenesis and potential therapeutic targets.

Materials and methods

Mouse heterotopic tracheal allograft model

The mouse model was established to replicate the pathophysiology of OB [8]. BALB/c (H-2d haplotype, donor) and C57/BL6 (H-2b haplotype, recipient) mice were chosen to create an MHC-mismatched allograft model. This strain combination mimics clinical immune rejection following lung transplantation by inducing T-cell-mediated alloimmunity, thereby reproducing OB pathogenesis. The heterotopic subcutaneous transplantation technique minimizes surgical complexity while preserving critical pathological features such as airway epithelial injury, inflammatory infiltration, and ECM deposition. The animal study adhered to the principles of Laboratory Animal Care, and the experimental protocol was approved by the Ethics Committee of Huazhong University of Science and Technology. BALB/c and C57/BL6 mice were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China). In the isograft model, tracheas from donor BALB/c mice were heterotopically transplanted into the subcutaneous space of recipient BALB/c mice (control group). In the allograft model, tracheas from donor BALB/c mice were heterotopically transplanted into the subcutaneous space of recipient C57/BL6 mice (experimental group). Mice were anesthetized with intraperitoneal ketamine injection (100 mg/kg). A midline incision was made in the neck to expose the tracheas, which were then resected, rinsed, and stored in cold sterile saline. A dorsal skin incision was made, followed by dissection of a subcutaneous tunnel. The tracheas were then embedded, the incision was sutured, and the skin was disinfected. The operation took approximately 10 min, with no mortality observed. Post-operative care showed no infection or abnormal feeding behavior, and the survival rate was 100%. At 7 and 14 days after transplantation, heterotopic tracheas were harvested for histopathological analysis, RNA-Seq, and cytokine profiling (IL-1β, IL-6, and IL-10) via ELISA.

HE staining assay

The tissue morphology and histopathological changes of the tracheal grafts from recipient mice were analyzed using HE staining. The tracheal grafts were fixed in 4% paraformaldehyde, embedded in paraffin, and sectioned at 4 μm. After hematoxylin and eosin staining, tracheal structure and the extent of inflammatory infiltration were evaluated under a light microscope at 200× magnification.

ELISA

Tracheal grafts collected at 7 and 14 days post-transplantation were homogenized in PBS, and the supernatants were used to measure IL-1β, IL-6, IL-10, and TGF-β1 levels using the Mouse IL-1β High Sensitivity ELISA Kit (Cat No. EK201BHS; Multi Sciences, Shanghai, China), Mouse IL-6 ELISA Kit (Cat No. EK206; Multi Sciences), Mouse IL-10 ELISA Kit (Cat No. EK210; Multi Sciences), and TGF-β1 ELISA Kit (Cat No. EK981-96; Multi Sciences), following the manufacturers' instructions.

RNA-seq analysis

Total RNA was extracted from tracheal grafts of both experimental and control groups at 7 and 14 days post-transplantation. RNA-Seq analysis was performed by Oebiotech Company (Shanghai, China). RNA extraction was carried out using Trizol reagent (Invitrogen, Carlsbad, CA, USA), and RNA integrity was assessed with an Agilent 2100 Bioanalyzer (Agilent Technologies, USA) (RIN > 8.0 for all samples). Libraries were constructed using the NEBNext Ultra RNA Library Prep Kit and sequenced on the Illumina HiSeq 2500 platform, generating 150-bp paired-end reads. The sequencing depth averaged 45 million reads per sample. Raw reads were quality-controlled using FastQC (v0.11.9), and adapter sequences/low-quality bases (Q < 20) were trimmed with fastp (v0.20.1) using the parameters: –length_required 50 –cut_right_window_size 4 –cut_right_mean_quality 20. Cleaned reads were aligned to the mouse reference genome (GRCm39) using HISAT2 (v2.1.0) with parameters: –rna-strandness RF –fr. The alignment statistics revealed a > 96% mapping rate for all samples (96.61–97.79%, Sup. Table 1). Gene expression quantification was performed using featureCounts (v2.0.1) with GENCODE M27 annotations. Gene expression profiles were obtained through FPKM normalization. Differential expression analysis was performed using DESeq2 (v1.22.2) with negative binomial generalized linear models. Genes with |log2FC|> 1 and an adjusted p-value (q-value) < 0.05 were defined as differentially expressed genes (DEGs) (Sup. Tables 2–3). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted using the DAVID database (https://david.ncifcrf.gov/) for DEG annotation.

Cell culture and transfection

BEAS-2B cells were purchased from Procell Life Science & Technology (Wuhan, China) and were cultured in BEBM medium (LONZA, Basel, Switzerland) supplemented with growth factors at 37 °C with 5% CO2. BEAS-2B cells were transfected with either scrambled shRNA (sh-NC) or HMGA1-targeting shRNA (sh-HMGA1; target sequence: 5′-GAGTCGAGCTCGAAGTCCA-3′) using Lipofectamine 2000 (Thermo Fisher Scientific).

IF assay

Immunofluorescence (IF) assays were employed to quantify protein levels in tissue specimens or cells. To measure the protein abundance of TGF-β1 and MMP2 in graft specimens, tracheal grafts were fixed, permeabilized, blocked, and incubated with TGF-β1 antibody (Cat No. 21898-1-AP; 1:500; Proteintech, Wuhan, China) or MMP2 antibody (Cat No. GB11130; 1:1000; Servicebio, Wuhan, China). The tissue specimens were then incubated with the appropriate secondary antibody. The cell nuclei were stained using DAPI reagent (Servicebio). Fluorescence intensity was evaluated using a confocal microscope at 20× magnification. Additionally, the abundance of E-cadherin, Vimentin, α-SMA, and fibronectin (FN) in cells was assessed via IF assay using anti-E-cadherin (Cat No. 20874-1-AP; 1:500; Proteintech), anti-Vimentin (Cat No. 10366-1-AP; 1:300; Proteintech), anti-α-SMA (Cat No. 14395-1-AP; 1:1000; Proteintech), and anti-FN (Cat No. 15613-1-AP; 1:300; Proteintech). Images were captured using a Zeiss LSM 900 confocal microscope.

Immunohistochemistry (IHC) assay

The protein levels of Col I, Col III, and HMGA1 in tracheal graft specimens were analyzed via IHC. Primary antibodies against Col I (Cat No. GB11022-3; 1:800; Servicebio), Col III (Cat No. GB111629; 1:400; Servicebio), and HMGA1 (Cat No. 29895-1-AP; 1:400; Proteintech) were utilized. Briefly, tracheal graft specimens were fixed with 4% formalin for 24 h, followed by paraffin embedding and sectioning into 4 μm-thick slices. A VECTASTAIN Elite ABC kit (Vector Laboratories, Burlingame, CA, USA) was used for signal detection, and slides were imaged under a light microscope at 40× magnification.

Western blot assay

Tracheal graft tissues and BEAS-2B cells were lysed on ice in RIPA buffer (Beyotime, Shanghai, China) containing protease inhibitors (EDTA-free cocktail, Cat No. 78430, Thermo Fisher). Protein concentration was measured using a commercial BCA kit (Cat No. 23227, Thermo Fisher). Proteins (30 μg per loading well) were separated by SDS-PAGE and transferred onto PVDF membranes (Millipore, Billerica, MA, USA). After blocking with 5% skimmed milk, the membranes were incubated overnight with primary antibodies: anti-HMGA1 (Cat No. 29895-1-AP; 1:10,000; Proteintech), anti-E-cadherin (Cat No. 20874-1-AP; 1:20,000; Proteintech), anti-Vimentin (Cat No. 10366-1-AP; 1:5000; Proteintech), or anti-α-SMA (Cat No. 14395-1-AP; 1:5000; Proteintech). The membranes were then incubated with the corresponding secondary antibodies. Immunoreactivity was detected using commercial chemiluminescence reagents (Thermo Fisher Scientific), and protein intensity was quantified using ImageJ (NIH, Bethesda, MD, USA). ACTB or β-Tubulin served as the internal reference.

RT-qPCR

Total RNA from BEAS-2B cells was extracted using Trizol reagent (Invitrogen, Carlsbad, CA, USA). RNA concentration was measured using a commercial UV spectrophotometer (Thermo Fisher Scientific). RNA was reverse-transcribed into cDNA using the SweScript RT II First Strand cDNA Synthesis Kit (Servicebio, Wuhan, China). qPCR was performed using Fast SYBR Green Master Mix (Cat No. 4385612; Thermo Fisher Scientific) on an Applied Biosystems PCR instrument (Foster City, CA, USA). The thermocycling conditions were 95 °C for 10 min, followed by 40 cycles of 95 °C for 15 s and 60 °C for 1 min. Gene expression was normalized to GAPDH and calculated using the 2–ΔΔCt method. Primer sequences used in the qPCR assay are listed below:

Human HMGA1, F: 5′-GAAAAGGACGGCACTGAGAA-3′.

Human HMGA1, R: 5′-TTTCCTTCCTGGAGTTGTGG-3′.

Human specificity protein 1 (SP1), F: 5′-ATGGACAGGTCAGTTGGCAG-3′.

Human SP1, R: 5′-AGGCAATGGGTGTGAGAGTG-3′.

Human dedicator of cytokinesis 4 (DOCK4), F: 5′-TGGATACCTACGGAGCACGA-3′.

Human DOCK4, R: 5′-ACCAGCCATCACACTTCTCC-3′.

Human serum response factor (SRF), F: 5′-GATCGGTATGGTGGTCGGTG-3′.

Human SRF, R: 5′-TGATGCCCGTCTTCCTCTTG-3′.

Human anillin actin binding protein (ANLN), F: 5′-TGCACCATTGGCACAAACAG-3′.

Human ANLN, R: 5′-CCAGATTCAGCTCGAGGGAC-3′.

Human GAPDH, F: 5′-GTCAAGGCTGAGAACGGGAA-3′.

Human GAPDH, R: 5′-AAATGAGCCCCAGCCTTCTC-3′.

ATAC-seq

ATAC-Seq was performed on BEAS-2B cells treated with TGF-β1 (10 ng/mL, 24 h) and transfected with sh-HMGA1 or sh-NC. ATAC-Seq analysis was conducted by Novogene Biotechnology (Beijing, China). Libraries were constructed using the NEBNext Ultra DNA Library Prep Kit and sequenced on the Illumina NovaSeq 6000 platform, generating 150-bp paired-end reads. The sequencing depth averaged 50 million reads per sample (range: 22–44 million). Raw reads were quality-controlled using FastQC (v0.11.9), and adapter sequences/low-quality bases (Q < 20) were trimmed with skewer (v0.2.2) using the parameters: –window-size 4 –mean-quality 20 –min-length 18. Cleaned reads were aligned to the human reference genome (GRCh38) using BWA (v0.7.12-r1039) with parameters -T 25 -k 18.

Alignment statistics showed > 96% mapping rate to non-mitochondrial regions (96.61–97.79%), with mitochondrial reads (0.35–1.31%) filtered out. Peak calling was performed using MACS2 (v2.1.2) with parameters: –nomodel –shift –100 –extsize 200 –keep-dup all –qvalue 0.05 –call-summits. Peak characteristics for all samples are cataloged in Sup. Table 4. Open chromatin regions were quantified using FRiP (Fraction of Reads in Peaks), ranging from 24.89 to 56.43% across samples. Motif enrichment analysis was performed via HOMER (v4.9.1) with parameters: findMotifsGenome.pl -size 500 -len 8,10,12,14. Peak annotation to genomic features was conducted using ChIPseeker (v1.28.3), and GO and KEGG enrichment analyses were performed with clusterProfiler (v4.0) with an adjusted p-value < 0.05. Differential chromatin accessibility analysis was performed using DiffBind (v3.0.15) with DESeq2 normalization, defining regions with |log2FC|> 1 and FDR < 0.05 as differential peaks. Key quality control and alignment statistics for ATAC-Seq analysis are provided in Sup. Table 5.

Data analysis

All experiments were performed in triplicate unless otherwise mentioned. GraphPad Prism 8.0 software (GraphPad Prism, La Jolla, CA, USA) was utilized for data processing and analysis, and the data were represented as the form of mean ± SD. The differences were assessed by Student’s t‑test or one-way ANOVA. P < 0.05 denoted the statistically significant differences.

Results

The mouse heterotopic tracheal allograft model is successfully established

The heterotopic tracheal allograft model was established in mice to replicate the early stages of post-transplant OB [8]. Histological analysis by HE staining revealed significant abnormalities in the transplanted trachea of the experimental group at both 7 and 14 days, including inflammatory cell infiltration and luminal occlusion (Fig. 1A), mirroring the histological features observed in clinical OB. Moreover, the extent of luminal occlusion increased with prolonged transplantation time (Fig. 1A). IL-1β, IL-6, and IL-10 are critical cytokines involved in the early post-transplant inflammatory response [9, 10]. Our data demonstrated a marked increase in the release of pro-inflammatory cytokines (IL-1β and IL-6) in the experimental group at day 7 compared to the control group (Fig. 1B, C). Furthermore, the concentrations of these cytokines were lower at day 14 than at day 7 in both groups (Fig. 1B, C). Additionally, the production of the anti-inflammatory cytokine IL-10 was significantly reduced at day 7 in the experimental group (Fig. 1D), with concentrations higher at day 14 than at day 7 in both groups (Fig. 1D). These results confirm the successful establishment of the model.

Fig. 1.

Fig. 1

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Mouse heterotopic tracheal allograft model recapitulates post-transplant OB pathology. BALB/c donor tracheas were heterotopically transplanted into the subcutaneous space of BALB/c recipient mice (control group) or C57/BL6 recipient mice (experimental group). The BALB/c-to-C57/BL6 strain combination ensured MHC mismatch-driven immune rejection, enabling high-fidelity simulation of OB progression. Subcutaneous implantation simplifies surgical procedures while preserving luminal occlusion and inflammatory-fibrotic transitions characteristic of clinical OB. At 7 d and 14 d after transplantation, the heterotopic tracheas were dissected for further analysis. A Representative HE staining images of heterotopically transplanted tracheas in control (isograft) and experimental (allograft) groups at 7 d and 14 d post-transplantation. The experimental group exhibited progressive luminal occlusion and inflammatory cell infiltration compared to intact epithelial structure in controls. Unpaired Student’s t-test was utilized in this study. B–D ELISA was employed to evaluate the concentrations of pro-inflammatory cytokines (IL-1β, IL-6) and anti-inflammatory IL-10 in tracheal grafts. The experimental group showed elevated IL-1β and IL-6 at 7 d and 14 d with reduced IL-10 at 7 d. Unpaired Student’s t-test was utilized in this study. *P < 0.05, **P < 0.01, ***P < 0.001

The TGF-β1-mediated ECM deposition may be a leading contributor to OB development

The RNA expression profiles of tracheal tissues from three biological replicates across four groups were determined through RNA-Seq analysis. The reproducibility and reliability of the RNA-Seq results were validated (Sup. Figure 1A, B). DEGs were identified using the thresholds: q < 0.05, |Log2FC|> 1 (7 d: Sup. Table 1; 14 d: Sup. Table 2). Volcano plots displayed the distribution of DEGs in the two groups at 7 and 14 days based on these criteria (Fig. 2A). Histopathological analysis revealed bronchial epithelial damage, inflammatory infiltration, and fibrotic remodeling in the allografts (Fig. 1A). GO and KEGG analyses highlighted significant enrichment in the “inflammation” and “immune response” pathways (Fig. 2B, C), suggesting active inflammatory processes during early-stage tracheal transplantation. By 14 days, ECM-related pathways were prominently enriched (indicated by the red boxes; Fig. 2B, C). RNA-seq also revealed differential expression of ECM-related factors between groups at both time points (Fig. 2D). To minimize potential noise, RNA-seq data were reanalyzed using stricter thresholds (q-value < 0.05 and |Log2FC| > 2.0). While this approach reduced the number of DEGs, core functional pathways and hub genes, particularly those related to adhesion and inflammation, remained statistically significant and consistent with the initial findings (Sup. Fig. 2A, B).

Fig. 2.

Fig. 2

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ECM-related pathways are enriched during OB development. Heterotopic tracheal specimens in four groups were utilized to carry out RNA-Seq. A Volcano plot of DEGs between the control and the experimental groups at 7 d and 14 d (q-value < 0.05 and |Log2FC|> 1). B and C GO and KEGG analyses were employed for gene annotation of up-regulated DEGs. Red boxes highlight ECM-related terms enriched at 14 d. D Heatmap of ECM-related gene expression (Col1a1, Col3a1, Mmp2) showing significant upregulation in the experimental group at 14 d. Hierarchical clustering based on FPKM values

Numerous studies have highlighted TGF-β1, a key profibrotic factor, as a regulator of ECM synthesis, remodeling, and degradation, contributing to fibrosis progression [11–13]. In the present study, TGF-β1 abundance in transplanted tracheas was assessed by IF, revealing a significant upregulation in the experimental group compared to the control group at both 7 and 14 days (Fig. 3A). ELISA assays confirmed that TGF-β1 secretion was markedly enhanced in the experimental group at both time points (Fig. 3B). Since TGF-β1 modulates ECM remodeling by regulating ECM-associated molecules such as Col I, Col III, and MMP2 [14, 15], their expression was further evaluated by IHC and IF. The data showed significantly elevated levels of Col I, Col III, and MMP2 in the experimental group at 14 days (Fig. 3C–E), suggesting that TGF-β1-induced ECM remodeling may play a major role in OB progression.

Fig. 3.

Fig. 3

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The TGF-β1-mediated ECM deposition may be a leading contributor for OB development. A IF staining (red) revealed increased TGF-β1 protein in the experimental group at 7 d and 14 d. Nuclei: DAPI (blue). Unpaired Student’s t-test was utilized in this study. B ELISA confirmed elevated TGF-β1 secretion in the experimental group at both time points. Unpaired Student’s t-test was utilized in this study. C and D IHC staining demonstrated upregulated Col I and Col III deposition in experimental group at 14 d. Unpaired Student’s t-test was utilized in this study. E IF staining (red) showed increased MMP2 expression in experimental group at 7 d and 14 d. Unpaired Student’s t-test was utilized in this study. *P < 0.05, **P < 0.01, ***P < 0.001

HMGA1 abundance is aberrantly up-regulated in heterotopic tracheal specimens

RNA-seq analysis (Fig. 2) not only identified ECM-related pathways but also revealed a notable upregulation of HMGA1 (Fig. 4A), a chromatin remodeler with established roles in fibrosis and epigenetic regulation [16]. HMGA1 has been strongly associated with inflammation [17] and fibrosis [18, 19]. RNA-seq demonstrated significant upregulation of HMGA1 in the experimental group at both 7 and 14 days (Fig. 4A). Consistent with RNA-seq data, both Western blot and IHC assays confirmed a significant increase in HMGA1 expression in the experimental group compared to the control group at 7 and 14 days (Fig. 4B, C), suggesting its potential involvement in OB pathogenesis..

Fig. 4.

Fig. 4

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HMGA1 abundance is aberrantly up-regulated in heterotopic tracheal specimens. A RNA-Seq analysis (FPKM values) showed significant HMGA1 upregulation in experimental group at 7 d and 14 d. Unpaired Student’s t-test was utilized in this study. B Western blot confirmed elevated HMGA1 protein levels in experimental group. ACTB: loading control. Unpaired Student’s t-test was utilized in this study. C IHC staining revealed increased HMGA1 nuclear localization (brown) in experimental group at 7 d and 14 d. Unpaired Student’s t-test was utilized in this study. *P < 0.05, **P < 0.01, ***P < 0.001

HMGA1 is a key player in TGF-β1-mediated EMT

To examine whether TGF-β1 regulates ECM remodeling via HMGA1, HMGA1 abundance was measured upon TGF-β1 exposure. TGF-β1 significantly increased both HMGA1 mRNA and protein levels (Fig. 5A, B). The high efficiency of HMGA1 silencing by sh-HMGA1 was validated through Western blot analysis (Fig. 5B). To assess HMGA1's involvement in EMT, we evaluated the expression of various EMT markers. TGF-β1 stimulation reduced E-cadherin expression and increased Vimentin/α-SMA levels in BEAS-2B cells, an effect that was largely reversed by HMGA1 silencing (Fig. 5C), suggesting that HMGA1 knockdown partially counteracts TGF-β1-induced EMT. IF assays further confirmed the TGF-β1-induced loss of E-cadherin and gain of mesenchymal markers (Vimentin, α-SMA, FN), which were attenuated by sh-HMGA1 (Fig. 5D–G), reinforcing the critical role of HMGA1 in TGF-β1-mediated EMT. These results validate HMGA1’s key function in the TGF-β1-induced EMT model in vitro.

Fig. 5.

Fig. 5

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HMGA1 mediates TGF-β1-induced EMT in pulmonary epithelial cells. A RT-qPCR showed TGF-β1 (10 ng/mL, 24 h) upregulated HMGA1 mRNA in BEAS-2B cells. Unpaired Student’s t-test was utilized in this study. B Western blot confirmed HMGA1 protein induction by TGF-β1 and efficient knockdown by sh-HMGA1. One-way ANOVA was utilized in this study. C Western blot of EMT markers. TGF-β1 reduced E-cadherin and increased Vimentin/α-SMA, reversed by HMGA1 silencing. One-way ANOVA was utilized in this study. D–G IF staining showed TGF-β1-induced loss of E-cadherin (green) and gain of Vimentin (green), α-SMA (green), and fibronectin (FN, green), mitigated by sh-HMGA1. Nuclei: DAPI (blue). One-way ANOVA was utilized in this study. *P < 0.05, **P < 0.01, ***P < 0.001

HMGA1 modulates global chromatin accessibility landscapes

To explore HMGA1’s epigenetic regulation of EMT, ATAC-Seq analysis was conducted in TGF-β1-stimulated BEAS-2B cells with or without HMGA1 knockdown. Figure 6A shows the concentration of ATAC-Seq signals near transcription start sites (TSS ± 3 kb), consistent with regulatory regions. MACS2 analysis identified 52,347 and 58,055 accessible regions in control sh-NC replicates (Fig. 6B). TGF-β1 stimulation significantly reduced global chromatin accessibility, resulting in 36,242 and 25,747 accessible regions in sh-NC + TGF-β1 groups, although selective accessibility gains were observed at pro-EMT loci. HMGA1 knockdown partially restored overall chromatin accessibility, with 40,009 and 37,141 accessible regions in the sh-HMGA1 + TGF-β1 groups (Fig. 6B).

Fig. 6.

Fig. 6

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HMGA1 modulates chromatin accessibility at EMT-related loci. BEAS-2B cells were divided into sh-NC, sh-NC + TGF-β1, and sh-HMGA1 + TGF-β1 groups before being subjected to ATAC-Seq. A ATAC-Seq signal distribution near transcription start sites (TSS ± 3 kb). TGF-β1 reduced chromatin accessibility near TSS, while HMGA1 knockdown partially restored it. B Peak calling was conducted using MACS2 software to identify the number of peak in each sample. TGF-β1 decreased total peaks (sh-NC + TGF-β1 1: 36,242 vs. sh-NC 1: 52,347), reversed by HMGA1 silencing (sh-HMGA1 + TGF-β1 1: 40,009). C The enrichment of motif and the known transcription factor motif was analyzed. TGF-β1 suppressed transcription factor motif enrichment (e.g., Jun B, Jun-AP1), attenuated by HMGA1 knockdown. D Peak distribution in functional areas in each sample was identified using ChIPseeker software. TGF-β1 reduced promoter-associated peaks (sh-NC + TGF-β1 1: 28.92% vs. sh-NC 1: 33.72%), rescued by sh-HMGA1 (38.46%). E GO terms enriched for genes near peaks upregulated by TGF-β1 (left) and downregulated by HMGA1 silencing (right). Functional enrichment analyses revealed TGF-β1 upregulated peaks were enriched for “cell–cell adherens junction”, while HMGA1 knockdown downregulated peaks associated with “cell–cell adherens junction”, “extracellular matrix” and “cell junction” terms. F KEGG pathways enriched for differential chromatin accessibility regions. KEGG analysis implicated “focal adhesion” pathways between sh-NC and sh-NC + TGF-β1 and between sh-HMGA1 + TGF-β1 and sh-NC + TGF-β1

Motif enrichment analysis of significant accessible regions (q < 0.05) revealed that TGF-β1 downregulated binding sites for EMT-inhibiting transcription factors Bach2 and Atf3 (Fig. 6C). HMGA1 knockdown specifically restored accessibility at these regulatory sites. Figure 6D illustrates that TGF-β1 reduced promoter-associated accessibility from 32.51% to 25.86%, which was restored to 37.23% following HMGA1 knockdown.

Functional annotation revealed that TGF-β1-induced accessible regions were enriched for the “cell–cell adherens junction” term (ranked 4th among all enriched terms, 21 genes, P = 0.0039; Fig. 6E, left panel). Although terms such as “neuro part” and “neuron projection” showed stronger enrichment, “cell–cell adherens junction” was specifically highlighted due to its direct relevance to EMT initiation. HMGA1 knockdown reduced the accessible regions associated with “cell–cell adherens junction” (44 genes, P = 0.0029), “ECM” (107 genes, P = 0.0056), and “cell junction” (338 genes, P = 0.0074) (Fig. 6E, right panel). KEGG analysis consistently enriched the “focal adhesion” pathway (Fig. 6F).

HMGA1-dependent regulation of EMT-promoting genes identified through integrated chromatin accessibility screening

To identify direct transcriptional targets of HMGA1-mediated remodeling that contribute to EMT, genes within differentially accessible regions were cross-referenced with established EMT drivers in the literature. Differentially accessible regions were defined by TGF-β1-induced upregulation (log2FC > 0.58, P < 0.05) and HMGA1-knockdown-induced downregulation (log2FC < − 0.58, P < 0.05). From this overlap, SP1 [20–25], DOCK4 [26, 27], SRF [28, 29], and ANLN [30] were selected based on their known roles in promoting EMT and metastasis (Fig. 7A–D). Functional RT-qPCR validation confirmed that while SRF expression remained unaffected by these interventions, SP1, DOCK4, and ANLN demonstrated consistent TGF-β1-induced upregulation and HMGA1-knockdown-mediated suppression (Fig. 7E–H). Notably, DOCK4 exhibited the most significant response (P < 0.001 for both TGF-β1 induction and HMGA1-knockdown reversal) and showed a strong correlation between epigenetic and transcriptional regulation. The accessibility changes of DOCK4 in ATAC-seq were strongly aligned with significant mRNA upregulation in murine allografts at both 7 days (log2FC = 0.867, P = 1.30 × 10−31) and 14 days (log2FC = 0.854, P = 3.28 × 10−42). This dual-system validation, coupled with emerging evidence that DOCK4 drives EMT through Rap1 signaling activation [27] and β-catenin axis regulation [26], confirms its role as a key effector in HMGA1-mediated OB pathogenesis. Collectively, these results suggest that HMGA1 regulates EMT by modulating the chromatin accessibility of key EMT-associated genes, particularly DOCK4.

Fig. 7.

Fig. 7

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HMGA1-dependent chromatin accessibility and transcriptional regulation of EMT-promoting genes. A–D Chromatin accessibility profiles at loci of SP1 (A), DOCK4 (B), SRF (C), and ANLN (D) measured by ATAC-seq. E–H BEAS-2B cells were treated as follows: control, TGF-β1, TGF-β1 + sh-NC, and TGF-β1 + sh-HMGA1. The mRNA expression levels of SP1 (E), DOCK4 (F), SRF (G), and ANLN (H) quantified by RT-qPCR. *P < 0.05, **P < 0.01, ***P < 0.001

Discussion

Post-transplant OB remains the leading cause of lung allograft dysfunction and mortality in transplant recipients [31]. This condition is marked by fibrotic changes that begin with bronchial epithelial injury, progress through acute inflammation, and ultimately result in airway fibrosis and luminal occlusion [31]. The heterotopic tracheal transplantation model used in this study effectively recapitulated these pathological stages, offering a robust platform for investigating the early progression of OB.

RNA-seq analysis was conducted to explore the underlying mechanisms of OB progression. GO and KEGG analyses of the RNA-seq data confirmed the involvement of inflammation and immune responses during OB progression in the mouse heterotopic tracheal allograft model. Notably, ECM-related functions and pathways were significantly enriched at 14 days, suggesting that ECM regulation plays a critical role at this time point post-transplantation. TGF-β1, a key regulator of ECM deposition, is strongly implicated in the pathogenesis of lung fibrosis [11–13]. Our findings suggest that TGF-β1-induced ECM remodeling may be a major contributor to OB progression.

Epigenetic modifications have been closely linked to the initiation and progression of various human disorders [32]. HMGA1, a member of the high-mobility group A (HMGA) protein family, lacks intrinsic transcriptional activity but can modulate gene expression by altering chromatin structure [33, 34]. Given the high expression of HMGA1 in the experimental group as revealed by RNA-seq data, coupled with its established association with inflammation [17] and fibrosis [18, 19], HMGA1 was selected for further investigation. In addition to the RNA-seq data, Western blot and IHC assays confirmed the elevated expression of HMGA1 in the experimental group compared to the control, suggesting its potential role in OB pathogenesis.

TGF-β1 induces the trans-differentiation of pulmonary epithelial cells into myofibroblasts via EMT, contributing to ECM synthesis, inhibiting ECM degradation, and ultimately leading to fibrosis [35]. Our data demonstrated that HMGA1 is a key downstream protein through which TGF-β1 mediates EMT in pulmonary epithelial cells. As a chromatin architectural protein, HMGA1 regulates transcriptional programs by altering DNA accessibility [36]. ATAC-seq analysis revealed that HMGA1-mediated chromatin remodeling selectively enhanced accessibility at loci encoding critical EMT regulators. Notably, the cytoskeletal regulator DOCK4 emerged as a pivotal effector, with its chromatin accessibility and transcriptional activation strongly associated with OB pathogenesis. This finding is further supported by the established role of DOCK4 in driving EMT via Rap1 signaling and cytoskeletal reorganization [26, 27]. SP1 (a transcription factor) and ANLN (a cytoskeletal organizer) were also validated as HMGA1 targets. Collectively, these findings highlight HMGA1’s role in regulating a functionally diverse EMT program.

This study provides the first evidence that HMGA1 drives EMT in OB by enhancing chromatin accessibility, as demonstrated through integrated ATAC-seq and RNA-seq analyses. The heterotopic tracheal transplantation model successfully recapitulated the dynamic pathological changes during OB progression, offering a robust platform for studying early fibrotic events. However, several limitations warrant consideration when interpreting these findings. The study employed a relatively small sample size, which may limit the statistical power to detect more subtle effects or interactions. Furthermore, the heterotopic transplantation microenvironment, characterized by factors such as hypoxia and mechanical stress inherent to the subcutaneous site, may not fully replicate the complex physiological conditions present in orthotopic lung transplantation. This potential discrepancy could influence the translational relevance of specific findings. Additionally, while HMGA1’s role in pulmonary epithelial cells was the primary focus, its potential contributions within other critical cell types involved in OB pathogenesis, such as fibroblasts, immune cells, or endothelial cells, remain unexamined. These limitations highlight the need for future studies to validate these findings in larger cohorts, explore HMGA1 function in orthotopic models or human tissue, and investigate its cell type-specific roles using approaches like conditional knockout models or single-cell analysis. Despite these limitations, the identification of HMGA1 as a key epigenetic regulator of EMT via chromatin remodeling provides significant new insights into OB pathogenesis.

HMGA1’s chromatin-modulating activity presents unique therapeutic opportunities. By binding to AT-rich DNA sequences, HMGA1 enhances chromatin accessibility at EMT-related loci, facilitating TGF-β1-driven transcriptional reprogramming. Pharmacological inhibition of HMGA1 with netropsin analogs [37] or siRNA-mediated knockdown has been shown to suppress osteoblast EMT in vitro and reduce fibrotic lesion severity in murine OB models [38].

HMGA1 represents a promising therapeutic target for OB, with precedents in other fibrotic and neoplastic diseases. In cardiac fibrosis, HMGA1 knockdown via RNA interference inhibited fibroblast activation, collagen synthesis, and alleviated fibrosis progression [19]. In esophageal squamous cell carcinoma, HMGA1 levels influenced sensitivity to mTOR inhibitors (rapamycin) by regulating the ETS1-FKBP12 axis [39], positioning HMGA1 as a potential predictive biomarker for targeted therapies. Our findings extend this concept to OB: HMGA1 knockdown reduced TGF-β1-induced EMT, suggesting that HMGA1 inhibitors could mitigate airway fibrosis. However, HMGA1’s functional redundancy with HMGA2 [40] and the potential off-target effects of chromatin-modulating agents highlight the need for careful optimization of therapeutic strategies.

Future research should focus on three key translational priorities: (1) testing HMGA1-targeted agents (e.g., small-molecule inhibitors, epigenetic editors) in preclinical OB models to validate their antifibrotic efficacy; (2) elucidating the context-dependent roles of HMGA1 across various cell types (osteoblasts, fibroblasts, immune cells) through single-cell multiomics and conditional knockout models; and (3) prospective clinical validation of circulating HMGA1 levels for early OB detection and treatment monitoring in lung transplant recipients.

Conclusions

Here, we demonstrated the vital role of HMGA1 in the EMT of OB for the first time. HMGA1 was aberrantly up-regulated in mouse heterotopic tracheal allograft model, and the enhancement of chromatin accessibility of EMT-associated genes by HMGA1 contributed to the occurrence of EMT during OB, making HMGA1 a latent therapeutic target for post-transplant OB.

Supplementary Information

Supplementary Material 1. (10.3KB, xlsx)
Supplementary Material 2. (1.4MB, xlsx)
Supplementary Material 3. (1.2MB, xlsx)
Supplementary Material 4. (19.5MB, xlsx)
Supplementary Material 5. (10.4KB, xlsx)
13148_2025_2000_MOESM6_ESM.tif (2.4MB, tif)

Supplementary Material 6: Figure S1. Assessment of the reliability of RNA-seq data. (A) PCA suggested the tight clustering of three repetitions. (B) The correlations between RNA‐Seq samples indicated good intergroup repeatability of RNA-Seq results.

13148_2025_2000_MOESM7_ESM.tif (6.6MB, tif)

Supplementary Material 7: Figure S2. GO and KEGG analyses for gene annotation of up-regulated DEGs under the criteria of q-value <0.05 with |Log2FC|>2. (A) GO analysis for gene annotation of up-regulated DEGs between the control and the experimental groups at 7 d and 14 d under the criteria of q-value <0.05 with |Log2FC|>2. (B) KEGG pathway enrichment analysis for gene annotation of up-regulated DEGs between the control and the experimental groups at 7 d and 14 d under the criteria of q-value <0.05 with |Log2FC| > 2

Supplementary Material 8. (2.1MB, docx)

Acknowledgements

I would like to express my gratitude to all those who have helped me during the writing of this thesis. I gratefully acknowledge the help of Key Science and Technology Research Project in Henan Province (No. 222102310511) that funded this research. Also, I would like to thank Tian Xia, Zhaoyao Hou, Sihua Wang, Jingyao Sun, Hui Yang, Peng Miao, Chang Liu, Wantong Zheng, who contributed to the research work.

Abbreviations

OB

Obliterative bronchiolitis

ECM

Extracellular matrix

HMGA1

High mobility group AT-hook 1

CAD

Chronic allograft dysfunction

FN

Fibronectin

IHC

Immunohistochemistry

TSS

Transcription start site

Author contributions

Tian Xia: Conceptualization、Methodology、Writing-original draft; Zhaoyao Hou: Data curation, Investigation; Sihua Wang: Data curation、Methodology; Jingyao Sun：: Data curation、Formal analysis; Hui Yang: Investigation, Methodology; Peng Miao: Investigation, Methodology; Chang Liu: Data curation, Methodology; Wantong Zheng: Formal analysis, Investigation; Li Wei：Funding acquisition, Supervision, Writing-review & editing.

Funding

This research was supported by Key Science and Technology Research Project in Henan Province (No. 222102310511).

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethical approval and consent to participate

All animal experiments were performed with the approval of the Animal Ethics Committee of Huazhong University of Science and Technology and the procedures for Care and Use of Laboratory Animals in cancer research.

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.

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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 Material 1. (10.3KB, xlsx)
Supplementary Material 2. (1.4MB, xlsx)
Supplementary Material 3. (1.2MB, xlsx)
Supplementary Material 4. (19.5MB, xlsx)
Supplementary Material 5. (10.4KB, xlsx)
13148_2025_2000_MOESM6_ESM.tif (2.4MB, tif)

Supplementary Material 6: Figure S1. Assessment of the reliability of RNA-seq data. (A) PCA suggested the tight clustering of three repetitions. (B) The correlations between RNA‐Seq samples indicated good intergroup repeatability of RNA-Seq results.

13148_2025_2000_MOESM7_ESM.tif (6.6MB, tif)

Supplementary Material 7: Figure S2. GO and KEGG analyses for gene annotation of up-regulated DEGs under the criteria of q-value <0.05 with |Log2FC|>2. (A) GO analysis for gene annotation of up-regulated DEGs between the control and the experimental groups at 7 d and 14 d under the criteria of q-value <0.05 with |Log2FC|>2. (B) KEGG pathway enrichment analysis for gene annotation of up-regulated DEGs between the control and the experimental groups at 7 d and 14 d under the criteria of q-value <0.05 with |Log2FC| > 2

Supplementary Material 8. (2.1MB, docx)

Data Availability Statement

No datasets were generated or analysed during the current study.

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