Epigenetic modifications in the murine liver upon depletion of transcriptional coregulator host cell factor 1

Abstract

Background

Transcriptional co-regulators fine-tune gene expression by modulating transcription factor activity and chromatin dynamics. HCF-1 (Host Cell Factor 1), a conserved transcriptional co-regulator, has been implicated in cell cycle progression, liver metabolism, and regeneration. Loss of hepatocyte-specific HCF-1 in mice leads to spontaneous NAFLD, which rapidly exacerbates to NASH and compromises liver regeneration. While its role in transcriptional regulation is well-established, the impact of HCF-1 on epigenetic modifications remains relatively unexplored.

Methods

To investigate the consequences of HCF-1 depletion, we performed histological and biochemical analyses of murine livers, assessing liver injury, lipid accumulation, and hepatocyte proliferation upon 2/3 partial hepatectomy (PH). Additionally, we conducted RNA sequencing (RNA-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) for H3K4me3 and RNA polymerase II (POL2) to examine the epigenetic and transcriptional alterations associated with HCF-1 loss.

Results

Loss of HCF-1 results in severe liver injury, causing hallmark features of NAFLD, including steatosis, inflammation, fibrosis, and mitochondrial dysfunction. Following injury, hepatocytes typically re-enter the cell cycle to replenish lost cells. However, in the absence of HCF-1, hepatocytes fail to proliferate leading to a progressive decline in liver function. Even upon 2/3 PH, HCF-1-deficient hepatocytes remain arrested in the cell cycle, further exacerbating disease severity and preventing tissue regeneration. RNA-seq analyses revealed significant downregulation of genes involved in cell cycle progression, metabolism, and mitochondrial structure and function including those regulating oxidative phosphorylation. ChIP-seq data showed altered H3K4me3 patterns at promoter and enhancer regions of key hepatic genes. These findings indicate that HCF-1 is essential for maintaining transcriptional and epigenetic landscapes necessary for hepatocyte proliferation and regeneration.

Conclusions

Our study establishes HCF-1 as a critical regulator of hepatic homeostasis, with roles extending beyond transcriptional control to epigenetic regulation of liver function and repair. Loss of HCF-1 not only induces liver injury and NAFLD but also prevents hepatocyte proliferation, impairing regeneration and accelerating disease progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-025-11786-5.

Background

The liver is a major organ found in vertebrates and is responsible for performing many essential biological processes. It plays a critical and indispensable role in the biotransformation of xenobiotics, the processing of metabolites as well as regulation of glucose and lipid metabolism [1]. It is a remarkable organ with the capacity for regeneration upon various injuries, where all types of mature liver cells participate in its execution [2, 3]. Due to its multidimensional functionality, however, liver is also prone to many diseases. Non-alcoholic fatty liver disease (NAFLD) is one such disease. Characterized by excessive lipid accumulation within hepatocytes, NAFLD emerges as a dynamic interplay between metabolic deregulation and cellular responses. It is a multifaceted condition that has recently gathered significant attention due to its rising global prevalence and its potential progression to more severe stages, such as non-alcoholic steatohepatitis (NASH), fibrosis, and eventually cirrhosis. In line with this, HCF-1 (Host cell factor 1) is one of the epigenetic coregulators that has recently been shown to be necessary for both healthy liver homeostasis and proper regeneration [4, 5].

HCF-1 is a conserved metazoan transcriptional co-regulator that was first identified as a host-cell factor for herpes simplex virus infection [6]. In mice, HCF-1 is encoded by the Hcfc1 gene located on the X chromosome [7]. The precursor protein consisting of 2045 amino acids is predominantly cleaved by site-specific proteolysis with the help of O-linked β-N-acetylglucosamine transferase (OGT) [8–13]. HCF-1 is known to bind to the transcriptional start sites (TSS) of many genes and physically link sequence-specific DNA-binding transcription factors with chromatin-modifying enzymes such as histone demethylases (KDM1A [14, 15] and PHF8 [16]), Set1 histone H3 lysine 4 methyltransferases, mixed-lineage leukemia (MLL) [17–19], histone acetyltransferase (KAT8 MOF) [20, 21], ubiquitin hydrolase RNF2 (BAP-1) [22–24], histone deacetylase (SIN3A) [25], glycosyl transferase OGT [24, 26], and phosphatase PPA1 [27]. This regulatory protein is implicated in several significant and varied processes, including development, differentiation, and embryonic stem cell pluripotency [27–31]. Moreover, HCF-1 has been shown to serve a vital role for cell proliferation in cell culture and in mice during both embryogenesis and liver regeneration [4, 32–35]. Particularly, in the context of liver regeneration, it has been shown that quiescent HCF-1 negative hepatocytes fail to re-enter the cell cycle post-2/3rd partial hepatectomy (PH) and, hence, cannot contribute to restoration of lost liver mass [4].

Additionally, human clinical trials of X-linked disorders, such as mental impairment and cobalamin dysfunction, have linked the Hcfc1 gene to non-proliferative functions [36–39] It has also been demonstrated that HCF-1 stabilization increases the synthesis of glucose in hepatocytes, and that HCF-1 knockdown improves glucose homeostasis in diabetic mice [24]. Additionally, hepatocyte-specific disruption of HCF-1 function results in NAFLD and NASH in mice [5]. Despite these findings, the precise molecular mechanisms by which HCF-1 coordinates hepatocyte proliferation, metabolic function, and epigenetic regulation remain unclear.

In this study, we have assessed the effect of HCF-1 depletion in mouse liver regeneration in terms of RNA polymerase II (POL2) activity and histone H3 lysine 4 tri-methylation (H3K4me3) modification in the genome in non-regenerating liver. Using RNA-seq and ChIP-seq analyses, we identified key gene regulatory pathways affected by HCF-1 loss. Our findings highlight HCF-1 as a critical epigenetic regulator essential for hepatic function, linking metabolic homeostasis, gene expression, and liver regeneration.

Materials and methods

Mice

All experimental studies have been performed in compliance with EU and national legislation rules, as advised by the Lemanique Animal Facility Network (Resal), concerning ethical considerations of transportation, housing, strain maintenance, breeding, and experimental use of animals. The animals used in this study were obtained from and housed within the authorized animal facility at the University of Lausanne. For all experiments, mice were housed four or five per cage at 23 °C, with a 12-h light and 12-h dark cycle and ad libitum access to food and water, unless specifically mentioned. For regeneration experiments, all mice were subjected to 12-h light and 12-h dark cycles for a duration of two weeks, followed by 12-h cycles of light and fasting and 12-h cycles of darkness and feeding. Mice were anesthetized with isoflurane and euthanized by cervical dislocation before the surgical procedure. Tamoxifen treatment and all tissue collections post-surgery were done between Zeitgeber Time ZT2 to ZT3, where ZT0 is the start of the light cycle. For all experiments with Hcfc1^hepKO/Y (KO) males, Hcfc1^lox/Y male mice were chosen as controls, whereas for Hcfc1^hepKO/+ (HET) females, Hcfc1^lox/+ female mice were used. No significant differences were observed between the phenotypes of the Hcfc1^lox/Y male and Hcfc1^lox/+ female mice.

DNA isolation and genotyping

Genomic DNA isolated from the ear tags of postnatal mice were used for genotyping. The DNA so isolated was used for PCR amplification using the KAPA2G Fast Hot Start Genotyping PCR mix (cat. # KK5621). The primer sets used for the genotyping reactions are mentioned in the Table 1 below.

Table 1.

Primers for genotyping

Sample	Sequence	Annealing	Extension
p1 for HCF-1 genotyping	5’GGAGGAACATGAGCTTTAGG3’	62 °C for 15 s	72 °C for 10 s
p2 for HCF-1 genotyping	5’CAATAGGCGAGTACCATCACAC3’
p3 for HCF-1 genotyping	5’GGGAAAGTAGACCCACTCTG3’
p1 for AlbCre genotyping	5’ATCATTTCTTTGTTTTCAGG3’	53 °C for 1 min	72 °C for 1 min
p2 for AlbCre genotyping	5’GGAACCCAAACTGATGACCA3’
p3 for AlbCre genotyping	5’TTAAACAAGCAAAACCAAAT3’

The PCR product of 229 bp generated by combination of p1 and p2 primers was used to detect the wild-type AlbCre allele. While the 444 bp PCR product generated by p2 and p3 primers sets detected the Cre allele [4].

Tamoxifen treatment

10–14 week-old control (Hcfc1^lox/Y) and test (Alb-Cre-ERT2^tg; Hcfc1^lox/Y) male mice were intraperitoneally injected with 1 mg/mouse tamoxifen [100 μl of 10 mg/ml (1:10 ethanol:corn oil)] (Sigma-Aldrich CAS#10,540–29-1) twice at intervals of every 24 h from day 0 to day 2. RNA sequencing analysis showed that tamoxifen treatment caused splicing of exon 1 to exon 4 of the Hcfc1 gene leading to rapid conversion of Hcfc1^lox/Y to Hcfc1^hepKO [5].

Immunohistochemistry

Immunohistochemistry was performed on 4 μm thick paraffin embedded liver tissue sections. The sections were first deparaffinized in xylene, followed by rehydration with graded ethanol washes. The tissue sections were then rinsed twice with 1X PBS. For antigen retrieval, the sections were heated in a 10 mM citrate buffer (pH 6) for about 10 min or until boiling in a 750 W microwave. The set-up was then cooled to 4℃ followed by two 1X PBS washes. Blocking was performed for 30 min at room temperature with 2% NGS (Normal Goat Serum, Sigma-Aldrich cat. # G9023) prepared in 1X PBS. Individual sections were then incubated with specific primary antibodies (dilutions prepared in 2% NGS) overnight at 4℃. Following the primary antibody incubation, the sections were washed thrice with 1 × PBS. Secondary antibody incubation was then performed in the dark at room temperature for 30 min. After this, the sections were again rinsed in 1X PBS and then counter stained with DAPI (4',6-diamidino-2-phenylindole, Sigma-Aldrich, CAS # 28,718–90-3) for 5 min. The DAPI stain was then washed away by PBS rinsing. The section was then mounted in mowiol mounting medium (Sigma-Aldrich, CAS # 9002–89-5).

The primary antibodies used were rabbit anti-HCF-1 (1:1000, H12), anti-HNF4α (1:100, R&D Systems cat. # 5 PP-H1415-00), rat anti-Ki67 (1:60, eBioscience cat. # 41–5698), mouse anti-PCNA (1:50, BD Transduction Laboratories cat. # 610,665), rabbit anti-Histone H3 phosphoSerine 10 (1:100, Abcam cat. # ab5176), rat anti-F4/80 (1:800, Abcam cat. # ab6640), anti-SMA (1:400, Abcam cat. # ab5694), mouse anti-OXPHOS (1:100, Abcam cat. # ab110413), mouse anti-MTCO1 (1:200, Abcam cat. # ab14705), mouse anti-ATP5α (1:400, Abcam cat. # ab14748), rabbit anti-TGFβ (1:100, Abcam cat. # ab 313,730), mouse anti-PCNA (1:50, BD Transduction Laboratories cat. # 610,665) and rat anti-CD31 (1:20, Dianova GmbH cat. # DIA-310-M).

Secondary antibodies used were goat anti-rabbit Alexa 488 (1:400, Molecular Probes cat. # A11034), goat anti-mouse Alexa 568 (1:500, Molecular Probes cat. # A11019), goat anti-rabbit Alexa 568 (1:1000, Molecular Probes cat. # A21069), goat anti-mouse Alexa 488 (1:400, Molecular Probes cat. # A11029), donkey anti-mouse Alexa 594 (1:500, Molecular Probes cat. # A11005), and goat anti-mouse Alexa 635 (1:300, Molecular Probes cat. # A31575).

Tunel assay

Terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling (TUNEL) was performed on paraffin-embedded liver sections using the In Situ Cell Death Detection Kit (Roche Applied Science, Cat. #11,684,795,910), following the manufacturer’s instructions.

Electron microscopy

Small liver tissue fragments (2 mm³) were initially fixed in a 2.5% glutaraldehyde solution (EMS, Hatfield, PA, USA) prepared in 0.1 M phosphate buffer (PB, pH 7.4) (Sigma, St. Louis, MO, USA) for 2 h at room temperature (RT). Following primary fixation, the samples underwent post-fixation in 1% osmium tetroxide (EMS, Hatfield, PA, USA) in the same phosphate buffer for an additional 2 h at RT. Subsequently, the samples were rinsed twice with distilled water and dehydrated using a graded acetone series (30% for 30 min, 70% for 30 min, and 100% for two cycles of 1 h each) (Sigma, St. Louis, MO, USA). The dehydrated samples were then gradually infiltrated with epoxy resin (Sigma, St. Louis, MO, USA) at increasing concentrations: Epon 1:3 acetone for 1 h, Epon 3:1 acetone for 1 h, Epon 1:1 for 2 h, and finally Epon 1:1 for 12 h. The resin-infiltrated tissue pieces were embedded in molds filled with resin and polymerized at 60 °C for 48 h. Ultrathin Sects. (50 nm) were obtained using a Leica Ultracut ultramicrotome (Leica Mikrosysteme GmbH, Vienna, Austria) and mounted on copper slot grids (2 × 1 mm) (EMS, Hatfield, PA, USA) coated with a polystyrene film (Sigma, St. Louis, MO, USA). Transmission electron microscopy (TEM) imaging was performed using a Philips CM100 TEM (FEI, Eindhoven, The Netherlands) operating at 80 kV, and micrographs were captured with a TVIPS TemCam-F416 digital camera (TVIPS GmbH, Gauting, Germany).

Tissue histology

Various stainings were performed either on paraffin embedded liver sections (4 μm) or cryosections (8 μm).

Hematoxylin and eosin staining

Tissue organization was examined using hematoxylin and eosin staining [40]. Hematoxylin stains the nucleus while eosin stains the cytoplasm of the cell. The paraffin sections were initially dewaxed by heating and xylene treatment. This was followed by rehydration with repeated ethanol washes of decreasing percentages. Following this, the sections were rehydrated with ultrapure water and then stained with hematoxylin. Excess stain was washed in water followed by acid-alcohol wash for 2 min. The sections were then washed well in water before counterstaining with 0.25% eosin for 90 s. The sections were then dehydrated with higher percentage ethanol washes. Finally, the sections were washed in xylene and then mounted for imaging.

Sirius red staining

This azo dye is used to stain collagen fibers and can help assess hepatic fibrogenesis. For this, paraffin sections are washed in 0.2% phosphomolybdic acid for 5 min following rehydration. The sections are then stained with 0.1% sirius red staining solution (90 min) and counterstained with Mayer’s hematoxylin (for 1 min).

Oil red O

Oil Red O stain selectively stains neutral lipids. For this, 8 μm thick liver cryosections are first air dried followed by fixation with 4% PAF for 10 min at room temperature. Following fixation, the sections are quickly washed with distilled water, rinsed with 60% isopropanol for 1 min and then stained with Oil Red O stain (Sigma Cat #0625) for 10 min. The sections are then subjected to quick washes with 60% isopropanol and distilled water followed by co-staining with hematoxylin for 45 s. Subsequently the sections are washed well with water and mounted. In this staining, lipids and nuclei are seen in red and blue colours respectively.

Immunoblotting

100 mg of control Hcfc1^lox/Y liver tissue were collected at every point (0 h, 1 h, 10 h, 24 h, 36 h, 48 h, 72 h, 1 week) and homogenized well using RIPA buffer containing protease inhibitor (components of RIPA buffer listed in the Table 2). 10–20 μg samples were then mixed with a 1X loading buffer and heated at 95℃ for 5 min. Following transfer to nitrocellulose membrane, blocking was performed for 1 h with 5 mL of LI-COR blocking buffer. The membrane was then incubated overnight with primary antibody (1:1000 dilution of anti-HCF-1 antibody, Bethyl Laboratories; 1:1000 dilution of anti-OXPHOS antibody) (prepared in 1:1 blocking buffer:1 × PBST) at 4℃. The following day, the membrane was washed thrice and incubated with 1:10,000 dilution of secondary antibody at room temperature for 30 min. The membrane was then washed well and developed.

Table 2.

Components of RIPA buffer

Components	Final concentration
Tris–HCl pH7.4	50 mM
NaCl	150 mM
EDTA	1 mM
Sodium deoxycholate	0.2%
DTT	1 mM
PMSF	1 mM
Triton X	1%

ChIP-seq analysis

Chromatin isolation, immunoprecipitation, and preparation of high throughput sequencing

Chromatin was isolated from the liver of individual male Alb-Cre-ERT2^tg; Hcfc1^lox/Y mice at 0, 4 and 7 days after Hcfc1^hepKO allele induction by tamoxifen administration as described in Methods. Chromatin was immunoprecipitated and prepared for high-throughput sequencing as described [41] using the anti-HCF-1 (Bethyl Laboratories, A301-400A; RRID: AB_961015) H12, anti-RPB2 (Santa Cruz Biotechnology, sc-673–18), and anti-H3K4me3 (Abcam, ab8580) [8, 26].

Processing of the sequencing data

Raw data were cleaned using Trim Galore (v0.6.4) [42] and were checked for quality using FastQC (v0.11.8) [43]. STAR aligner (v2.7.9a) was deployed to align the reads to the mouse reference genome (mm10) once they had passed quality control [44]. Random, chimeric and uncharacterised reads were removed. Regions from the ENCODE blacklisted list were discarded for further analysis [45]. Only the fragments with 255 (unique mapping) and 3 (maps to 2 locations in the target) and 1 (maps to more than 2 locations in the target) MAPQ score were considered. All the fragments bigger than 2 kb were discarded. The module “callpeak” in MACS2 (Model-based Analysis for ChIP Sequencing v2.0) was used to identify regions of ChIP-seq enrichment over the background in an unbiased manner [46]. The parameters were adjusted according to different markers, HCF-1 and POL2 in narrow peak mode, H3K4me3 in broad peak mode, with q-value of 0.1. Further, differential peaks were identified using HOMER (v4.11) and intersect function in BEDTools (v2.30.0) [47, 48]. Motifs enrichment in peak regions were searched using the findMotifsGenome.pl script in the HOMER suite of tools. For biological interpretation of the results from the ChIP-Seq experiments, gene ontology and pathway analysis was implemented using web-based tool DAVID (The Database for Annotation, Visualization and Integrated Discovery) [49].

Statistical analysis

All the experiments were performed for a minimum of three biological replicates. Immunohistochemistry data were analyzed and quantified using ImageJ software. The percentage of positively stained cells was determined using the formula:

Data have been represented as mean ± SEM and p-values have been calculated using two-tailed Student’s t-test using GraphPad Prism Software, wherein p < 0.05 is statistically significant.

Results

Loss of HCF-1 leads to severe liver injury

We began by investigating the effect of hepatocyte-specific loss of HCF-1 on overall liver health and morphology. To achieve the liver specific deletion of HCF-1, we administered tamoxifen treatment to 10–14-week-old Albumin-Cre-ERT2^tg; Hcfc1^lox/Y and Albumin-Cre-ERT2^tg; Hcfc1^lox/+ male and female mice. As previously demonstrated [4, 5], in the aforementioned strains, the Albumin-Cre-ERT2^tg allele ensures a hepatocyte-specific knockout of the Hcfc1 gene upon tamoxifen activation. Since Hcfc1 gene is X-linked, this conversion results in generation of Hcfc1^hepKO/Y allele in male mice (completely lacking HCF-1 expression) and Hcfc1^hepKO/+ allele in female mice (exhibiting heterogeneous gene expression) [4, 5]. Before tamoxifen treatment, all HNF4α-positive hepatocytes consistently displayed HCF-1 expression (indicated by red arrows in Fig. 1A). However, within 7 days of tamoxifen induction, a noticeable hepatocyte-specific reduction in HCF-1 levels was observed in both Albumin-Cre-ERT2^tg; Hcfc1^KO/+ (HET) heterozygous female (Fig. 1B) and Albumin-Cre-ERT2^tg; Hcfc1^KO/Y (KO) knockout male (Fig. 1C) mice. Female mice showed heterogenous expression of the X-linked hcfc1 gene upon tamoxifen treatment by virtue of random X-chromosome inactivation. Some clusters of hepatocytes (HNF4α-positive) were found to be HCF-1 positive (red arrows in Fig. 1B), while others were HCF-1 negative (white arrows in Fig. 1B), in the female mice, dependent on the location of the Hcfc1^KO allele on the active or inactive X-chromosome, thus generating a 50/50 mix of HCF-1 positive and negative hepatocytes. Non-hepatocytes (HNF4α-negative) remained positive for HCF-1 (yellow arrows in Fig. 1B). In contrast, Hcfc1^KO/Y male mice displayed complete loss of hepatocyte-specific HCF-1 expression upon tamoxifen activation (white arrows in Fig. 1C), although non-hepatocytes remained positive for HCF-1 (yellow arrows in Fig. 1C). Upon quantification we observe, a significant decrease in the number of hepatocytes expressing HCF-1 in Hcfc1^KO/+ (HET) heterozygous female mice and Hcfc1^KO/Y (KO) knockout male mice as compared to Hcfc1^lox/+ control mice (Fig. 1D).

Fig. 1.

Tamoxifen induction leads to rapid loss of hepatocyte-specific HCF-1 expression in Hcfc1^hepKO/+ female and Hcfc1^hepKO/Y male livers. Immunofluorescence analysis of HCF-1 and hepatocyte specific marker (HNF4α) of 10-week old control (0d Ctrl WT; panels A), heterozygous Alb-Cre-ERT2^tg; Hcfc1^hepKO/+ female (7d HET; panel B) and knockout Alb-Cre-ERT2^tg; Hcfc1^hepKO/Y male livers (7d KO; panel C) 7 days post-tamoxifen treatment. The paraffin-embedded sections of livers (panels A, B, and C) were stained with DAPI (blue), anti-HNF4a (red), anti-HCF-1 (green). In panels A, and B the red arrows point to HCF-1-positive and HNF4α-positive hepatocytes. White arrows in panels B and C point to HCF-1-negative and HNF4α-positive hepatocytes. Yellow arrows in panel C point towards HCF-1-positive and HNF4α-negative non-hepatocytes. The indented circles in B reflect some of the visible HCF-1-positive and negative hepatocyte clusters. Percentages of HCF-1 positive hepatocytes (panel D, n = 4) were calculated for 0 d Ctrl WT, heterozygous Alb-Cre-ERT2^tg; Hcfc1^hepKO/+ female and and knockout Alb-Cre-ERT2^tg; Hcfc1.^hepKO/Y male mice livers. Students’ T test was used to calculate the significance. (**, p ≤ 0.001;***, p ≤ 0.0001; n.s., p > 0.05)

Assessment of liver damage upon loss of HCF-1 expression was examined by checking for AST levels, a liver injury marker (Additional Fig. 1). Histological assessments of liver tissue sections from both male and female Hcfc1^hepKO/Y and Hcfc1^hepKO/+ mice showed increased steatosis, identified by Oil Red O staining, (Fig. 2A) and infiltration of macrophages, labelled with F4/80 inflammatory marker, (Fig. 2B) by 7 days post-tamoxifen induction. Infiltration of macrophages (F4/80 staining) was also examined at 18 days post tamoxifen treatment in both Hcfc1^hepKO/+ female and Hcfc1^hepKO/Y male mice (Additional Fig. 2). Hepatic steatosis levels appeared to be more prominent in Hcfc1^hepKO/Y male mice, which completely lacked hepatocyte-specific HCF-1 expression compared to the heterozygous female mice that still retained patches of HCF-1-positive hepatocytes. Hcfc1^hepKO/Y male mice also showed appearance of ballooned hepatocytes indicating extensive liver injury (Additional Fig. 3). Further signs of liver injury emerged, such as accumulation of fibrotic fibres (Fig. 2C) together with the activation of hepatic stellate cells by the 18th day, as evidenced by the presence of smooth muscle α-actin (SMA) positive cells (Fig. 3A). Increased cell death in liver paraffin sections of Hcfc1-depleted mice was also observed at the 18th day, indicated by TUNEL staining where apoptotic cells were stained green (Fig. 3B). TUNEL staining was also performed at various time points post tamoxifen treatment for Hcfc1^hepKO/Y knockout male mice which showed significant cell death upon loss of HCF-1 (Additional Fig. 4). We also observed significant increased expression of cleaved-caspase 3 staining (Fig. 3C) and appearance of CD31-positive cells (Fig. 3D) at 18th day indicating increased cell death and increased angiogenesis upon loss of HCF-1. We also observed increased expression of another inflammatory marker TGF-β in Hcfc1^hepKO/Y knockout male mice compared to control and both Hcfc1^hepKO/+ heterozygous females (Additional Fig. 5).

Fig. 2.

Hcfc1 knock-out leads to severe liver injury. Comparison of cryosections (A) and paraffin-embedded sections (B and C) of control livers (0d; left), heterozygous Alb-Cre-ERT2tg; Hcfc1^hepKO/+ female (middle) and knockout Alb-Cre-ERT2tg; Hcfc1^hepKO/Y livers (right). A The presence of steatosis was estimated by Oil Red O staining of cryo-sections from control, heterozygous Alb-Cre-ERT2tg; Hcfc1^hepKO/+ female and knockout Alb-Cre-ERT2tg; Hcfc1^hepKO/Y livers. Scale bar 50 μm. Quantifications show significant increase in area of lipid droplets in heterozygous Alb-Cre-ERT2tg; Hcfc1^hepKO/+ female and Alb-Cre-ERT2tg; Hcfc1^hepKO/Y knockout male livers in comparison to control (n = 4, ***, p ≤ 0.0001; *, p ≤ 0.05,) (B) DAB immunostaining for macrophage marker F4/80 (brown). The sections were also stained with hematoxylin (blue). Scale bar 25 μm. Quantifications show significant increase in percentage area of F4/80 staining in heterozygous Alb-Cre-ERT2tg; Hcfc1^hepKO/+ female and Alb-Cre-ERT2tg; Hcfc1^hepKO/Y knockout male livers in comparison to control (n = 4, **, p ≤ 0.001; *, p ≤ 0.05,) (C) Sirius red staining of paraffin embedded sections. Scale bar 25 μm. Quantifications show significant increase in percentage area of sirius red staining in Alb-Cre-ERT2tg; Hcfc1^hepKO/Y knockout male livers in comparison to control, while non-significant increase in case of heterozygous Alb-Cre-ERT2tg; Hcfc1^hepKO/+ female in comparison to Control (n = 4, **, p ≤ 0.001; n.s., p > 0.05). Students’ T test was used to calculate the significance

Fig. 3.

Loss of Hcfc1 leads to rapid progression to NASH-like characteristics (A) Sections stained with DAPI (blue) and smooth-muscle -actin (SMA; green) antibody. Scale bar 50 μm. Quantifications show significant increase in intensity of SMA staining in Alb-Cre-ERT2tg; Hcfc1^hepKO/Y knockout male livers in comparison to control and non-significant increase in SMA staining intensity in heterozygous Alb-Cre-ERT2tg; Hcfc1^hepKO/+ female in comparison to control (n = 4, ****, p < 0.0001; n.s., p > 0.05) (B) TUNEL assay of apoptotic cells (green) co-stained with HCF-1 antibody (red). TUNEL-positive apoptotic cells are shown in green. Scale bar 50 μm. Quantifications show significant increase in cell death in heterozygous Alb-Cre-ERT2tg; Hcfc1^hepKO/+ female and Alb-Cre-ERT2tg; Hcfc1^hepKO/Y knockout male livers in comparison to control (n = 3, ****, p < 0.0001; *, p ≤ 0.05). C Sections co-stained with cleaved caspase 3 (red), SMA (green) antibody and DAPI (blue). Scale bar 50 μm. Quantifications show significant increase in intensity of cleaved-caspase3 staining in heterozygous Alb-Cre-ERT2tg; Hcfc1^hepKO/+ female and Alb-Cre-ERT2tg; Hcfc1^hepKO/Y knockout male livers in comparison to control (n = 4, **, p ≤ 0.001; *, p ≤ 0.05,). D Cryosections stained with DAPI (blue) and CD31 (green) antibody. Scale bar 100 μm. Quantifications show significant increase in intensity of CD31positive staining in Alb-Cre-ERT2tg; Hcfc1^hepKO/Y knockout male livers in comparison to control (n = 4, *, p ≤ 0.05; n.s., p > 0.05). Students’ T test was used to calculate the significance

Collectively, these findings suggest the development of chronic liver injury akin to advanced stages of NAFLD within approximately three weeks due to the spontaneous hepatocyte-specific deletion of the Hcfc1 gene in Hcfc1^hepKO/Y male mice. In contrast, Hcfc1^hepKO/+ female mice exhibit milder morphological defects compared to Hcfc1^hepKO/Y male mice. While Hcfc1^hepKO/Y male mice exhibit signs of rapid progression from NAFL to NASH in approximately three weeks, the Hcfc1^hepKO/+ female mice eventually begin to show signs of complete recovery over time. This recovery is likely driven by the proliferation of HCF-1 positive hepatocytes, as indicated by the restoration of HCF-1-positive cells one month after its induced loss (Additional Figures 6 and 7).

Hepatocytes are unable to proliferate upon loss of HCF-1

Hepatocyte-specific depletion of HCF-1 leads to increased cell death following extensive liver injury. Typically, the liver initiates a robust regenerative response to replace lost hepatocytes, with existing hepatocytes re-entering the cell cycle to restore liver mass. However, we sought to determine if this regenerative response is also activated following the loss of HCF-1, as significant hepatocyte death occurs under these conditions. We, therefore, utilized these Albumin-Cre-ERT2^tg; Hcfc1^KO/+ heterozygous female and Albumin-Cre-ERT2^tg; Hcfc1^KO/Y knockout male mice to evaluate the effects of both partial and complete HCF-1 loss on the regenerative response in the mouse liver following 2/3rd partial hepatectomy (PH). Overall morphology of the control, Albumin-Cre-ERT2^tg; Hcfc1^KO/+ heterozygous female and Albumin-Cre-ERT2^tg; Hcfc1^KO/Y knockout male mice livers, were examined by performing HE staining at various time points, including 0H, 4H, 12H, 24H, 36H, 48H, 60H, 72H, and 1 week post PH (Additional Fig. 8).

Firstly, we analysed HCF-1 levels with the help of immunoblotting in wild-type mice following partial hepatectomy and observed no clear upregulation (Additional Fig. 9). To further investigate whether the loss of HCF-1 affects liver regeneration at the cellular level, we decided to perform immunostaining for a more detailed assessment. Here, we began by examining the cell proliferation response in both Albumin-Cre-ERT2^tg; Hcfc1^KO/+ heterozygous female and Albumin-Cre-ERT2^tg; Hcfc1^KO/Y knockout male mice before and after tamoxifen-dependent HCF-1 deletion, prior to PH, as shown in Fig. 4A (before tamoxifen) and Fig. 4B and 4 C (after tamoxifen). We utilized Ki67 and histone H3 serine 10 phosphorylation (H3S10P), two mitotic markers, for this analysis. Prior to PH, few, if at all any, hepatocytes were positive for Ki67 or H3S10P in the control (Fig. 4A), Albumin-Cre-ERT2^tg; Hcfc1^KO/+ (Fig. 4B) and Albumin-Cre-ERT2^tg; Hcfc1^KO/Y (Fig. 4C) mice livers (Fig. 4F). We then performed 2/3rd PH to induce a more robust and synchronized regenerative response, ensuring that a large number of hepatocytes re-enter the cell cycle simultaneously, making the analysis more pronounced and easier to observe. Interestingly, within 48 h of 2/3rd PH, we observed that only HCF-1-positive hepatocytes in Hcfc1^KO/+ female mice rapidly entered the cell division cycle, as evidenced by increased Ki67 expression only in patches of HCF-1-positive hepatocytes (red arrows in Fig. 4D). We also observed similar results for two other cell proliferation markers PCNA and H3S10P in Hcfc1^KO/+ female mice (Additional Fig. 10). Conversely, HCF-1-negative hepatocytes in Hcfc1^KO/+ heterozygous female and Hcfc1^KO/Y knockout male mice completely failed to re-enter the cell cycle and remained negative for Ki67 (white arrows in Fig. 4D and E). In fact, in comparison to HCF-1-positive hepatocytes, none of the HCF-1-negative hepatocytes were observed to undergo cell proliferation (Fig. 4G). We observed similar results in Hcfc1^KO/Y knockout male mice at different time points post 2/3rd PH until 6 days, wherein only few HCF-1 positive hepatocytes that either remained as escapers or were a result of transdifferentiation entered cell division (Additional Fig. 11). These results indicate the vital role of HCF-1 in facilitating hepatocyte re-entry into the cell cycle during the regeneration process. Immunostaining for Ki67 in control, however showed rapid proliferation of hepatocytes thus mounting a strong regenerative response post-PH (Additional Fig. 12).

Fig. 4.

HCF-1-depleted hepatocytes fail to proliferate upon partial hepatectomy. Immunofluorescence analysis of cell-cycle progression markers of 10-week old control (0d Ctrl WT; panels A), heterozygous Alb-Cre-ERT2^tg; Hcfc1^hepKO/+ female (7d HET; panels B and D) and knockout Alb-Cre-ERT2^tg; Hcfc1^hepKO/Y male livers (7d KO; panels C and E) 7 days post-tamoxifen treatment before (pre PH) and 48 h after being additionally subjected to 70% PH (48H PH). The paraffin-embedded sections of livers before (panels A, B, C, D, and E) and 48 h after PH (panels G and H) were stained with DAPI (blue), one of two cell-proliferation markers shown in red: H3S10P (red; panels A, B and C), and Ki67 (red; panels D and E), and anti-HCF-1 (green; panels A, B, C, D and E). In panels A, B and C yellow arrows point towards HCF-1-positive non-hepatocytes that are positive for cell proliferation marker H3S10P. The red arrows in panels A and B point towards the HCF-1-positive hepatocytes that are positive for cell proliferation marker H3S10P. In panel D, the HCF-1-positive hepatocytes (red arrows) are positive for cell proliferation marker Ki67. In panels D and E, the HCF-1-negative hepatocytes (white arrows) are negative for the Ki67, whereas the HCF-1-positive non-hepatocytes (yellow arrows; panel E) are positive for Ki67. The indented circles in D reflect some of the visible HCF-1-negative hepatocyte clusters. Scale bar: 50 μm. Percentages of HCF-1 positive hepatocytes also positive for H3S10P were calculated for 0 d Ctrl WT, heterozygous Alb-Cre-ERT2^tg; Hcfc1^hepKO/+ female and knockout Alb-Cre-ERT2^tg; Hcfc1^hepKO/Y male mice livers prior to PH (panel F, n = 4, n.s., p > 0.05). Quantifications for percentages of HCF-1-positive and HCF-1-negative hepatocytes also positive for Ki67 were done 48 h post PH in heterozygous Alb-Cre-ERT2^tg; Hcfc1^hepKO/+ female mice (panel G, n = 4, ****, p < 0.000.1). Students’ T test was used to calculate the significance

The notable disparity between the responses of Hcfc1^hepKO/+ female and Hcfc1^hepKO/Y male mice to the extensive liver injury upon HCF-1 loss, therefore, primarily arises from the fact that HCF-1-deficient hepatocytes are unable to participate in the regenerative response. Hence,Hcfc1^hepKO/Y male mice to succumb to death while the Hcfc1^hepKO/+ female mice recuperate. Consequently, Hcfc1^hepKO/Y male mice not only serve as a model for the spontaneous development of NAFLD but also as a model lacking regenerative capabilities.

Presence of HCF-1 at transcriptional start sites correlates with transcriptional activity

Having established that the loss of HCF-1 hinders hepatocyte entry into the cell cycle, effectively blocking their regenerative capacity and contributing to the progression of NAFLD, we next sought to investigate the potential mechanisms underlying the effects observed upon loss of HCF-1. HCF-1 regulates gene expression by interacting with various transcription factors, leading to activation or repression of the target genes. In HeLa cells, HCF-1 was found to be bound to CpG-rich promoters of 5400 genes while, in the embryonic stem cells (ESCs), HCF-1 was observed at the transcriptional start sites of 743 promoters [31, 50]. This disparity hints at a context-dependent role for HCF-1 in gene regulation.

Given the association of HCF-1 with several transcription start sites (TSSs) in mouse livers, we wondered whether HCF-1-bound and -unbound TSSs might differ in associated transcriptional activity. To understand how the depletion of HCF-1 affects transcriptional regulation, we first began by performing immunostainings for investigating the presence of H3K4me3 mark, a modification associated with transcriptional activity, on control, Hcfc1^hepKO/Y male and Hcfc1^hepKO/+ female livers. Interestingly, it was observed that upon loss of HCF-1, the H3K4me3 signal appeared to be significantly reduced in HCF-1-depleted Hcfc1^hepKO/Y male livers as compared to the control livers after 7 days of tamoxifen treatment, indicating probable reduction in transcription of genes regulated by HCF-1 (Fig. 5). These results suggest that HCF-1 can have a major impact (direct or indirect) on epigenetic status. Thus, these findings shed new light on the role of HCF-1 in influencing the presence of H3K4me3 mark, highlighting its context-specific interactions, and underscoring its significance in governing gene expression that warrants further investigation.

Fig. 5.

Hepatocytes lacking HCF-1 have significantly lowered H3K4me3 signal. Immunofluorescence analysis of active transcription marker H3K4me3 in (A) control Hcfc1^lox/Y, B heterozygous Alb-Cre-ERT2tg; Hcfc1^hepKO/+ female and (C) Alb-Cre-ERT2^tg; Hcfc1^hepKO/Y male mice, post-tamoxifen treatment. The paraffin-embedded liver sections of control Hcfc1^lox/Y, Hcfc1^hepKO/+, and Hcfc1^hepKO/Y mice were stained with DAPI (blue), anti-H3K4me3(green). The area marked with indented rectangle in panels A3, B3, and C3 is shown at high magnification in A4, B4, and C4, respectively. Scale bar: 50 μm. D Percentage of H3K4me3 positive hepatocytes were calculated in control Hcfc1^lox/Y, heterozygous Alb-Cre-ERT2tg; Hcfc1^hepKO/+ female and Alb-Cre-ERT2^tg; Hcfc1^hepKO/Y male mice (n = 4, **, p ≤ 0.001; ***, p ≤ 0.0001). Students’ T test was used to calculate the significance

The enrichment of H3K4me3 marks and presence of RNA polymerase II near the transcription start sites (TSSs) is indicative of active transcription and robust gene expression [51]. Hence, we performed chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) analyses for trimethylated H3K4 (H3K4Me3) and RNA polymerase II (POL2) in both control (Day 0) and Hcfc1 knockdown livers after 4- and 7-days post induction of hepatocyte-specific Hcfc1 gene disruption. Additionally, HCF-1 genomic localization was also investigated in the murine liver at days 0 (control), 4, and 7 after induction of hepatocyte-specific Hcfc1 gene disruption.

ChIP-Seq peaks signals associated with HCF-1, POL2, and H3K4me3

The distribution of peaks across different chromosomes at day 0, 4 and 7 is visually depicted in circos plot Fig. 6A. Intriguingly, annotation of these peaks revealed a noteworthy pattern. Though HCF-1 is known to bind to TSS, we also observed a notable enrichment of HCF-1 peaks at locations other than TSS. Approximately 28% of HCF-1-associated peaks were found within the promoter-TSS regions, while peaks for H3K4me3 marks enriched around TSS regions were estimated to be 32%. POL2 related signals showed maximum enrichment in TSS regions, about 42%. This insightful delineation of peak distribution is represented in the stacked bar plot presented in Fig. 6B. These findings display the genomic occupancy of HCF-1 and its associated factors, offering an insight into their roles in transcriptional regulation across different genomic contexts.

Fig. 6.

A Circos plot depicting the distribution of a) HCF-1 b) POL2 and c) H3K4me3 peaks. Red, blue and green colors represent day 0, day 4 and day 7 respectively. Bioconductor package circlize was used with mm10 as the reference genome. B Stacked bar plot showing the genomic annotation by functional region of HCF-1, POL2 and H3K4me3 peak signals. Annotation was obtained from HOMER. Associated data is available in Additional file 1

As shown in the circos plot (Fig. 6A) there were about 390 HCF-1 associated peaks on day 0, and as anticipated, these numbers decreased over time in day 4 and 7 post-tamoxifen induction in Hcfc1^hepKO/Y male mice. Moreover, there were different trends observed for HCF-1 associated peak signals as shown in the heatmap (Fig. 7A)—(i) a continuous decrease in the signal intensity from day 0 to day 7 [D0 > D4 > D7], (ii) a decrease in the signal intensity from day 0 to day 4, followed by a slight increase on day 7, however, the signal on day 7 was still less compared to that on day 0 [D0 > D4 < D7], (iii) a decrease in signal intensity from day 0 to day 4, which then remained constant from day 4 to day 7 [D0 > D4 = D7], (iv) the peak signal increased from day 0 to day 4, but the signal intensity on day 7 was again less in comparison to day 0 [D0 < D4 > D7] and at last (v) the signal intensity remained same from day 0 to day 4, followed by a decrease on day 7 [D0 = D4 > D7]. Overall, these trends demonstrate a progressive loss of HCF-1 signal over time. Figure 7B shows two genes, Denr and Pura, where the peak signal was found to be decreasing from day 0 to day 7. This loss of HCF-1 signals coincided with alterations in H3K4me3 and POL2 signals, indicating substantial transcriptional changes in genes regulated by HCF-1, leading to subsequent up- or down-regulation of other affected downstream target genes.

Fig. 7.

A Heatmap displaying decreasing trends [D0 > D4 > D7], [D0 > D4 < D7], [D0 > D4 = D7], [D0 < D4 > D7] in HCF-1 peak signals. Here * represent the [D0 = D4 > D7] trend. The color key indicates the associated row z-score. B Visual representation of HCF-1 ChIP-Seq profiles mapped on the genes Denr and Pura for day 0, 4 & 7 showing continuous decrease trends [D0 > D4 > D7] C) Gene ontology (GO) of the genes i.e. Biological process (BP), Molecular Function (MF) and Cellular component (CC) associated with regions where HCF-1 peak signals were decreasing with time. D Pathway analysis of the genes associated with regions where HCF-1 peak signals were decreasing with time. The enrichment in a specific process and pathway was measured by DAVID. The p-value was determined by Fisher's Exact test. E Top ten transcription factor motifs overrepresented in HCF-1 peak regions, found using HOMER. Data associated with each figure is given in Additional file 2

Potential pathways controlled by HCF-1

The dysregulated peak signals (identified from the comparison between day 0, day 4 and day 7) that were directly associated with the genes were then analyzed to get the associated gene ontologies and enriched pathways to infer biological significance (Fig. 7C&D). This analysis revealed multiple pathways and processes in which these genes were enriched. GO Biological processes such as cell cycle, cell proliferation, multicellular organism development and terms related to mitosis and transcription were enriched. Pathways related to MAPK signaling pathway, lipid and atherosclerosis, adaptive immune system, sphingolipid signaling pathway, cellular response to stimulus and stress and transcription were found to be enriched. Dysregulation in signaling pathways can disrupt critical cellular processes closely linked to NAFLD development. The enrichment in developmental processes may impact liver tissue regeneration and maintenance, which could hinder recovery from HCF-1 loss, a contributing factor to NAFLD. Perturbations in cellular and biological processes may influence lipid metabolism, a key element in NAFLD pathogenesis. Genes associated with stimulus response may affect the liver's susceptibility to injury, inflammation, and oxidative stress, all of which are implicated in NAFLD. Dysregulated localization and transportation processes can lead to lipid accumulation, again a hallmark of NAFLD. Aberrations in metabolic pathways are directly linked to lipid build up in the liver, insulin resistance, and hepatic inflammation, all critical factors in NAFLD development. Hence, the combined effect of these dysregulated pathways and processes may disrupt the delicate balance of liver function, ultimately contributing to the development of NAFLD due to Hcfc1 loss. Thus, this categorization presents the overall impact of HCF-1 dysregulation on diverse biological processes and pathways in murine liver, hence, shedding light on the molecular events triggered by HCF-1 modulation.

Binding partners of HCF-1

HCF-1 is a co-transcriptional regulator, and therefore it interacts with the DNA with the help of other transcription factors and DNA modulators. To be confident about the peak signals associated with HCF-1 being analysed, we further searched for recurrent motifs in the DNA regions where peaks were observed. The top ten motifs with p-value ≤ 0.01 found to be enriched in the HCF-1 associated peak regions, along with their matching transcription factors are shown in Fig. 7E. This list contained well known HCF-1 binding partners like THAP, KLF10, E2F and ZNF143 [50, 52]. We also found some other transcription factors that could potentially be interacting with HCF-1 and can be explored further. The complete list of significantly enriched motifs and corresponding transcription factors can be found in the Additional file 2.

Annotation of HCF-1 peak signals localized in intergenic regions

As shown in Fig. 6B, a lot of the HCF-1 signals were found in the intergenic regions (regions located between two different genes) and hence could not be directly associated with a functional annotation. Therefore, these regions were explored for their potential using HOMER, which presents chromatin state annotations derived from ChIP-seq of histone modifications [53]. Many of these intergenic regions with HCF-1 peak signals were found to be in one of the following categories- (i) Simple repeat (ii) Short Interspersed Nuclear Element (SINE) (iii) Long Interspersed Nuclear Element (LINE) (iv) Low complexity (v) Cytosine-phosphate-Guanine (CpG) (vi) signal recognition particle RNA (srpRNA) (vii) Satellite (viii) Young repetitive elements (YREP_Mm) (ix) tRNA and (x) intergenic regions as shown in Fig. 8A. These annotated intergenic sites were analyzed for their sequence features and matched with transcription factors using ORegAnno [54] (Fig. 8B). The significantly enriched transcriptional factors were studied for their functional roles in the cells to infer their biological significance (Table 3). As previously noted, these transcription factors were involved in transcriptional regulation, methylation activity, chromatin remodelling and many more.

Fig. 8.

A Donut chart representing the percentage of functional annotation of intergenic regions with HCF-1 peak signals. Epigenomic resource of HOMER was utilized for the annotation. B Sunburst chart displaying the transcription factors mapped for the annotated intergenic sites with HCF-1 peak signals. Associated data is available in Additional file 3

Table 3.

Functional role of significantly enriched transcription factors mapped to regulatory sites present in the intergenic region interacting with HCF-1

Transcription Factor	Function
Stat1	Signal transducer and transcription activator that mediates cellular responses to interferons (IFNs), cytokine KITLG/SCF and others, and growth factors. Also leads to activation of the JAK-STAT signaling pathway
Foxa2	Involved in longevity regulating pathway. Involved in the development of multiple endoderm-derived organ systems such as the liver, pancreas, and lungs. Essential for hepatic specification and bile duct formation, IL-6 induced fibrinogen beta transcriptional activation. Transcription activator for number of liver genes such as AFP, albumin, tyrosine aminotransferase, PEPCK etc. Onset of diabetes- Involved in glucose homeostasis, regulates fat metabolism, activates transcriptional programs of lipid metabolism and ketogenesis at low insulin state
Klf1/Elkf	Transcription regulator of erythrocyte development. Binds to the CACCC box in the beta-globin gene promoter and activates transcription. When SUMOylated, acts as a transcriptional repressor by promoting interaction with CDH2/MI2beta and also represses megakaryocytic differentiation
Tbx3	Involved in signaling pathways regulating pluripotency of stem cells
Cdx1	Plays a role in transcriptional regulation. Involved in activated KRAS-mediated transcriptional activation of PRKD1 in colorectal cancer (CRC) cells
Mtf2	Regulates the transcriptional networks during embryonic stem cell self-renewal and differentiation. Enhances PRC2 H3K27me3 methylation activity
Spi1	Controls hematopoietic cell fate by decompacting stem cell heterochromatin and allowing other transcription factors to enter otherwise inaccessible genomic sites
Jarid2	Regulator of histone methyltransferase complexes that plays an essential role in embryonic development, including heart and liver development. Binds DNA and mediates the recruitment of the PRC2 (Polycomb Repressive Complex 2 Subunit) complex to target genes in embryonic stem cells, thereby playing a key role in stem cell differentiation and normal embryonic development
Ezh2	This gene encodes a member of the Polycomb-group (PcG) family. PcG family members form multimeric protein complexes, which are involved in maintaining the transcriptional repressive state of genes over successive cell generations
Suz12	Polycomb group (PcG) protein. Component of the PRC2 complex, which methylates'Lys-9'(H3K9me) and'Lys-27'(H3K27me) of histone H3, leading to transcriptional repression of the affected target gene.The PRC2 complex may also serve as a recruiting platform for DNA methyltransferases, thereby linking two epigenetic repression systems
Erg	This gene encodes a member of the erythroblast transformation-specific (ETS) family of transcriptions factors. All members of this family are key regulators of embryonic development, cell proliferation, differentiation, angiogenesis, inflammation, and apoptosis
Ebf1	Enable DNA-binding transcription activator activity, RNA polymerase II-specific and RNA polymerase II cis-regulatory region sequence-specific DNA binding activity
Atoh1	Enables sequence-specific double-stranded DNA binding activity. Predicted to be involved in neuron differentiation; positive regulation of neuron differentiation; and regulation of transcription by RNA polymerase II

Changes in gene expression profiles and its regulation by methylation upon loss of HCF-1

In line with the experimental results, many genes involved in the process of cell cycle were found to be dysregulated (as inferred from ChIP-seq analysis of Hcfc1 KO group, HCF-1 peak signals decreasing over time). Some of the major players included Brd7 (bromodomain containing 7), Ppp2r5b (protein phosphatase 2 regulatory subunit B), Cdk6 (cyclin dependent kinase 6), Cdk12 (cyclin dependent kinase 12) and Cdc27 (cell division cycle 27). These genes are known to play vital roles in the control of cell cycle progression, DNA repair, and genomic stability, respectively. Their proper functioning is crucial for normal cellular development, tissue homeostasis, and efficient regeneration processes. Additionally, many genes associated with liver regeneration process were also found enriched in regions where the POL2 and H3K4me3 peak signals decreased from day 0 to day 7. Some selected genes and their functions have been listed in Table 4).

Table 4.

Genes associated with liver regeneration were found to be downregulated upon loss of Hcfc1

Genes	Function	References
Genes enriched in regions where POL2 peak signals decreased over time
A1CF	APOBEC1 complementation factor, involved in RNA editing and alternative splicing regulation. Plays a role in post-transcriptional modification and mRNA processing	[55]
ADAM10	A Disintegrin and Metalloprotease 10, involved in cell adhesion, migration, plays a role in Notch signaling.	[56]
E2F3	Transcription factor that regulates the cell cycle, involved in promoting cell proliferation and DNA synthesis.	[57]
EGFR	Epidermal Growth Factor Receptor, receptor tyrosine kinase, involved in cell growth, proliferation, and survival.	[58]
FOXO3	Forkhead Box O3, transcription factor, plays a role in regulating cell cycle arrest, apoptosis, DNA repair, and oxidative stress response.	[59]
GAB1	Grb2-associated binder 1, adaptor protein involved in signaling cascades, interacts with various receptor tyrosine kinases and acts as a scaffold to transmit signals for cell growth, differentiation, and survival.	[60]
GHR	Growth Hormone Receptor, involved in growth promotion, metabolism regulation, and cell proliferation.	[61]
JUN	Component of the transcription factor complex AP-1 (Activator Protein 1), involved in processes like cell proliferation, differentiation, apoptosis, and response to stress signals.	[62]
MCL1	Myeloid Cell Leukemia-1, anti-apoptotic protein, inhibits caspase activation and promotes cell survival.	[63]
NFATC3	Nuclear Factor of Activated T Cells, Cytoplasmic 3, transcription factor, plays a role in immune response, cell differentiation, and development.	[64]
NFE2L2	Nuclear factor erythroid 2-related factor 2, transcription factor, plays a central role in cellular defense against oxidative stress.	[65]
NR0B2	Nuclear Receptor Subfamily 0 Group B Member 2, nuclear receptor that functions as a transcriptional corepressor, plays a role in liver development, metabolism, and bile acid homeostasis.	[66]
ONECUT1	One Cut Homeobox 1, transcription factor involved in the development and differentiation of various tissues, including the liver, pancreas, and neural tissues.	[67]
PDPK1	3-Phosphoinositide Dependent Protein Kinase-1, serine/threonine protein kinase, involved in the activation of various kinases, including protein kinase B (AKT), and regulates processes like cell proliferation, survival, and metabolism.	[68]
PLG	Plasminogen, synthesized and secreted by the liver and is involved in the fibrinolytic system, which is responsible for the breakdown of blood clots.	[69]
PPARA	Peroxisome Proliferator-Activated Receptor Alpha,nuclear receptor, regulates the expression of genes involved in fatty acid metabolism, lipid transport, and inflammation.	[70]
RXRA	Retinoid X Receptor Alpha, nuclear receptor, involved in gene regulation, particularly in developmental processes, cellular differentiation, and metabolism.	[71]
SOCS3	Suppressor of Cytokine Signaling 3, negative feedback inhibitor of cytokine signaling, involved in development and maintaining tissue homeostasis.	[72]
TGFB1	Transforming Growth Factor Beta 1, cytokine, regulates cell growth, differentiation, apoptosis, and immune responses.	[73]
TXNIP	Thioredoxin Interacting Protein, inhibits the activity of thioredoxin, a key regulator of redox signaling, involved in cellular responses to oxidative stress, glucose metabolism, and apoptosis.	[74]
Genes enriched in regions where H3K4me peak signals decreased with time
E2F1	Transcription factor, regulates cell cycle progression and cell proliferation, involved in apoptosis, DNA repair, and differentiation processes.	[57]
FABP1	Liver fatty acid-binding protein (L-FABP), involved in the uptake, transport, and metabolism of fatty acids in hepatocytes.	[75]
FADD	Fas-associated death domain protein, adaptor protein involved in mediating apoptosis, or programmed cell death.	[76]
NR1I2	Nuclear receptor protein that acts as a transcription factor, primarily expressed in the liver and intestine and is involved in the regulation of drug metabolism and detoxification.	[77]
PDPK1	3-phosphoinositide-dependent protein kinase-1, key regulator of the phosphoinositide 3-kinase (PI3K) signaling pathway and is involved in the activation of various downstream kinases, including Akt (protein kinase B), S6K (p70 ribosomal protein S6 kinase), and PKC (protein kinase C). These kinases regulate multiple cellular processes, such as cell survival, growth, proliferation, and metabolism.	[68]

As mentioned before, HCF-1 is known to interact with the genes as both a repressor and an activator to regulate their transcriptional activity. A similar trend was found for H3K4me3 epigenetic modifications as well. We found a significant number of genes (heatmap shown in Fig. 9A&B) with alterations in the methylation pattern. The functional role of these genes has also been summarized in Fig. 9C&D. These genes are majorly involved in lipid metabolic process, liver regeneration, cholesterol metabolism, chromatin remodelling, insulin resistance, fatty acid metabolism and many more. Functional dysregulation inferred from the changing POL2 peak signals also reflected the same processes, which re-emphasised on the importance of these major biological processes being regulated by HCF-1 (Fig. 10). Clearly, the ChIP-seq analysis was conforming to the experimental observations discussed above.

Fig. 9.

A Heatmap displaying increasing trends [D0 > D4 < D7], [D0 < D4 > D7] in H3K4me3 peak signals. Here * represent the [D0 < D4 < D7], [D0 = D4 < D7], [D0 < D4 = D7] trends. The color key indicates the associated row z-score. B Heatmap displaying decreasing trends [D0 > D4 > D7], [D0 > D4 < D7], [D0 < D4 > D7] in H3K4me3 peak signals. Here * represent the [D0 > D4 = D7], [D0 = D4 > D7] trends. The color key indicates the associated row z-score. C KEGG pathway analysis of the genes associated with regions where H3K4me3 peak signals increased and decreased over time. D Biological Process analysis of the genes associated with regions where H3K4me3 peak signals increased and decreased over time. The enrichment of genes for different GO terms and pathways was found using DAVID. All the data associated with these figures is included in Additional file 4

Fig. 10.

A Heatmap displaying increasing trends [D0 > D4 < D7], [D0 < D4 > D7] in POL2 peak signals. Here * represent the [D0 < D4 < D7], [D0 = D4 < D7], [D0 < D4 = D7] trends. The color key indicates the associated row z-score. B Heatmap displaying decreasing trends [D0 > D4 > D7], [D0 > D4 < D7], [D0 < D4 > D7] in POL2 peak signals. Here * represent the [D0 > D4 = D7], [D0 = D4 > D7] trends. The color key indicates the associated row z-score. C KEGG pathway analysis of the genes associated with regions where POL2 peak signals increased and decreased over time. D Biological Process analysis of the genes associated with regions where POL2 peak signals increased and decreased over time. The enrichment of genes for different GO terms and pathways was found using DAVID. Additional file 5 contains data associated with these figures

Functional inactivation of HCF-1 leads to a disturbed metabolic and signaling networks in Hcfc1 knockout mice

We found many genes which had changes in both H3K4me3 and POL2 peak signals from day 0 to day 4 and day 7. We next elucidated the biological role of the complete gene set with the help of pathway enrichment analysis using g:Profiler and EnrichmentMap. The most significant KEGG pathways reflecting the involvement of dysregulated genes were metabolic pathways and cell proliferation related processes as shown in Fig. 11A &B. These enriched pathways are also listed in additional file 6. To further add to this analysis and examine the effects of HCF-1 loss on gene expression, we compared the RNA-Seq results of Hcfc1^hepKO/Y male livers to those for control Hcfc1^lox/Y male and Hcfc1^hepKO/+ heterozygous female livers from a previously reported study [5]. This comparison identified 654 downregulated and 521 upregulated transcripts (Additional file 7). To explore the biological significance of these dysregulated genes, we performed gene ontology enrichment analysis using the DAVID. Upregulated genes in Hcfc1^hepKO/Y livers were associated with processes such as innate immune response, autophagy, cholesterol metabolism, mitochondrial translation, and oxidoreductase activity (Fig. 12A). In contrast, downregulated genes were enriched in ontologies related to apoptotic processes, chromatin remodeling, DNA repair, lipid metabolism, protein ubiquitination, and mitochondrial organization (Fig. 12C). Pathway analysis revealed that upregulated genes were linked to processes such as fatty acid degradation, alcoholic liver disease, beta-alanine metabolism, lysine degradation, aminoacyl-tRNA biosynthesis, and other metabolic pathways (Fig. 12B). Meanwhile, downregulated genes were associated with pathways related to fatty acid metabolism, peroxisome function, PPAR signaling, and linoleic acid metabolism (Fig. 12D). Further cellular component analysis highlighted a profound impact on mitochondrial structure and function, indicating mitochondrial dysfunction. The affected transcripts were involved in mitochondrial translation, electron transport chain, mitochondrial RNA metabolism, fatty acid beta-oxidation, positive regulation of mitochondrial fission, and mitochondrial DNA repair (Fig. 12E). These findings were consistent with insights drawn from the ChIP-seq analysis. Notably, Fig. 12F illustrates the key genes involved in mitochondrial structure and function, aligning with significant changes observed in mitochondrial morphology and metabolic activities following HCF-1 loss. The strong concordance between RNA-seq and ChIP-seq data further reinforces the robustness of our findings.

Fig. 11.

Pathway enrichment analysis of the dysregulated genes A) D0 > > D7 and B) D7 > > D0 found to be common in POL2 and H3K4me3 peak signals. g:Profiler and Cytoscape plugin EnrichmentMap were used for the analysis. Additional file 6 contains data associated with these figures

Fig. 12.

GO enrichment analysis shows biological process (BP), cellular component (CC) and molecular functions (MF) linked with A) upregulated genes and C) downregulated genes. The larger the bar chart is, the higher the enrichment degree of each process, and the color of the bar plot map represents the significance (p-value). The dot plot represents the KEGG pathways on the y-axis and gene count on the x-axis for B) upregulated genes D) downregulated genes. Greater the gene count corresponds to a greater dot. The colour of the dot varies based on the p-value. The enrichment of genes for different GO terms and pathways was found using DAVID. E The treemap illustrates mitochondrial processes linked to dysregulated genes. F A schematic representation of a mitochondrion shows functionally annotated genes, indicating upregulation (green) or downregulation (red) resulting from the loss of HCF-1. Additional file 7 contains data associated with these figures

Electron microscopic images of liver tissue sections from Hcfc1^hepKO/Y male mice clearly showed mitochondria with altered structure. We also observed lipid deposition as early as 4 days post tamoxifen administration (Additional Fig. 13). To assess the impact of HCF-1 loss on oxidative phosphorylation, we examined mitochondrial electron transport chain complexes using anti-OXPHOS, which detects a key subunit from ETC complexes. Immunoblot analysis showed a marked reduction in the expression of NDUFB8 (complex I), SDHB (complex II), and ATP5α (complex V), while UQCRC2 (complex III) remained largely unchanged (Additional Fig. 14). These findings were corroborated by immunofluorescence staining, where MTCO1, ATP5α, and overall OXPHOS staining signals were significantly diminished in Hcfc1^hepKO/Y male liver sections compared to controls (Fig. 13, Additional Fig. 15). The disruption of oxidative phosphorylation suggests compromised mitochondrial function, which may contribute to impaired β-oxidation of fatty acids, increased lipid accumulation, and the rapid progression from NAFLD to NASH.

Fig. 13.

Depletion of Hcfc1 expression adversely impacts mitochondrial function in Hcfc1^hepKO/Y male livers. Immunofluorescence analysis of paraffin-embedded sections of 0 d control and 7 d Hcfc1^hepKO/Y knockout male livers stained with (A) ATP5α (red), (B) MTCO1 (red) and DAPI (blue). Scale bar: 50 μm

In conclusion, our results here display the interplay between POL2, H3K4me3, and HCF-1 that plays an important role in maintaining liver homeostasis. These findings underscore the critical role of HCF-1 in governing fundamental biological processes, with a particular emphasis on hepatic metabolic pathways and cell cycle control. This in-depth analysis not only deepens our understanding of the impact of HCF-1 on transcriptional regulation but also paves the way for further investigations into the molecular events underlying the development of metabolic disorders, such as NAFLD.

Discussion

Non-alcoholic fatty liver disease (NAFLD) is a prevalent and complex liver disorder characterized by a disease spectrum ranging from simple hepatic steatosis to non-alcoholic steatohepatitis (NASH), often progressing to fibrosis, cirrhosis, and even hepatocellular carcinoma [78–81]. Despite its clinical significance, however, the molecular mechanisms underlying NAFLD pathogenesis are still not fully understood. Our study explores the role of a conserved metazoan transcriptional co-regulator HCF-1 in mouse hepatocytes, shedding light on its contribution to hepatic epigenetic regulation and, when disrupted, its profound implications for NAFLD progression and recovery.

The liver’s remarkable regenerative capacity has long been a subject of study, particularly through models like partial hepatectomy (PH) [82]. These studies have shown that this response to hepatic insufficiency is precisely regulated, and results in restoration of the original liver-to-body mass ratio [1, 2]. Experimental analyses in pharmacologically- and genetically-manipulated mice using PH and other models have identified many signals essential for normal liver regeneration [83, 84]. These include cytokines, growth factors, intracellular signaling events, and transcription factors, which direct the induction of specific gene expression programs that induce hepatocellular proliferation and the eventual recovery of liver mass [85, 86]. However, despite significant progress, the precise signals governing the initiation and termination of hepatic regeneration remain elusive. Also, the extent and efficiency of regeneration can be affected if the liver is damaged and scarred, for example, during the course of NAFLD [81, 87–90].

Building upon this existing knowledge, our study investigates the role of the transcriptional co-regulator HCF-1 in hepatocytes. HCF-1 has been shown to various roles in cell cycle progression [18, 27, 30, 91]. Remarkably, the loss of HCF-1 in mouse hepatocytes has been found to trigger a rapid recapitulation of NAFLD in mice, a phenomenon previously documented [5]. The induction of NAFLD in mice lacking hepatocyte-specific HCF-1 expression is attributed to significant alterations in expression of genes associated with mitochondrial structure and function, including oxidative phosphorylation. Loss of HCF-1 also leads to associated metabolic dysfunction, impaired gluconeogenesis and faulty β-oxidation, possibly through destabilization of PGC1α which is known to be involved in hepatic metabolism and mitochondrial functioning [5, 24, 92]. Hepatocyte-specific loss of HCF-1 leads to rapid steatosis within the first week, indicating its critical role in maintaining normal mitochondrial function and lipid metabolism. Additionally, HCF-1-negative hepatocytes cannot contribute to the regenerative response even if the mouse liver is subjected to resection in 2/3rd partial hepatectomy [4]. Thus, it is evident that HCF-1 regulates genes involved in hepatocyte proliferation, mitochondrial structure–function and hepatic metabolism, but the mechanism behind this regulation remains unclear. Here, with the help of RNA-seq and ChIP-seq analyses, we have revealed that the absence of HCF-1 exerts a marked influence on H3K4me3 modifications that is complemented by changes in POL2 signals as well, indicative of significant perturbations in the transcriptional activity.This raises the question of whether HCF-1 influences mitochondrial-, proliferation-, and metabolism- related genes by modulating the H3K4me3 mark. The link between HCF-1 depletion and altered transcriptional regulation at these gene promoters suggests that changes in H3K4me3 could underlie the mitochondrial dysfunction, reduction in proliferation and metabolic errors leading to accelerated steatosis and cell death and lack of recovery seen in the absence of HCF-1.This observation underscores the global impact of HCF-1 on gene expression and emphasizes its role as a central hub in orchestrating transcriptional programs critical for liver homeostasis. While this study focuses on promoter-associated H3K4me3 modifications, future analyses of H3K27ac levels could provide a broader view of HCF-1’s role in chromatin regulation. Additionally, co-immunoprecipitation assays would help establish direct interactions between HCF-1 and histone-modifying enzymes, further clarifying its role in chromatin remodeling and transcriptional activation.

Our findings show the following: Firstly, they underscore the complexity of NAFLD, which involves not only metabolic factors but also intricate epigenetic and transcriptional mechanisms. Secondly, the role of HCF-1 as a critical mediator in liver homeostasis demands further investigation. These mice offer a unique and rapid model for studying NAFLD. It is evident that HCF-1 loss disrupts the finely tuned balance of epigenetic marks and transcriptional machinery in hepatocytes, leading to the rapid onset of NAFLD. Such associations of HCF-1 effecting epigenetic modifiers have already been reported in the past [16–18, 28, 93–96]. Furthermore, HCF-1, has also been shown to be important for liver regeneration in mouse hepatocytes. Thus, the livers with hepatocyte-specific loss of HCF-1 fail to regenerate despite severe liver damage. Hence, understanding the specific genes and pathways affected by these alterations could unveil potential therapeutic targets for NAFLD and related metabolic disorders.

Also, our study has uncovered several genes that are affected by HCF-1 loss. These genes encompass a diverse array of functions, including cell proliferation, apoptosis regulation, growth factor signaling, and metabolic control. The dysregulated genes identified through our analysis are found to be enriched in various pathways and processes, providing additional insights into the impact of HCF-1 dysregulation. Specifically, we have categorized these enrichments into distinct groups, ranging from signaling pathways, developmental processes, and cellular and biological processes to responses to stimuli, localization and transportation, and metabolic processes. Each of these categories offers potential connections to NAFLD pathogenesis.

Importantly, our results show that the absence of HCF-1 leads to increased cell death in Hcfc1^hepKO/Y male mice and is manifested as a severe liver insult. The Hcfc1^hepKO/+ heterozygous female mice are capable of building up a robust regenerative response whereas Hcfc1^hepKO/Y male mice succumb to Hcfc1 loss. This notable contrast in the outcomes between these two groups primarily stems from a fundamental limitation imposed by HCF-1 deficiency. In Hcfc1^hepKO/Y male mice, HCF-1-deficient hepatocytes are rendered incapable of actively participating in the regenerative response that is typically initiated in response to liver damage. As a result, Hcfc1^hepKO/Y male mice emerge not only as a model for the spontaneous development of NAFLD, elucidating the role of HCF-1 in its pathogenesis, but also serve as a unique model characterized by an absence of regenerative capabilities. This dual role of the Hcfc1^hepKO/Y male mice provides a comprehensive platform for investigating both the molecular underpinnings of NAFLD and the mechanisms governing hepatic regeneration.

Conclusion

In summary, our findings suggest that HCF-1 loss represents itself as a severe insult to the liver, recapitulating the biochemical, metabolomic and morphological features of NAFLD that progresses to NASH. Moreover, HCF-1 deletion also debilitates the liver’s regenerative ability upon partial hepatectomy. Depletion of HCF-1, affects a defined set of genes with a distinct focus on metabolic processes, signalling pathways, methylation activity, chromatin remodelling, cell proliferation and many more by significantly perturbing their expression patterns. Therefore, in addition to adversely impacting the mitochondrial structure and function, known to be one of primary factors in NAFLD pathogenesis and its transition to NASH, loss of HCF-1 also alters the transcriptional status of genes involved in diverse biological processes by perturbing the presence of H3K4me3 epigenetic marks. These insights shed new light on the intricate molecular mechanisms governing liver health and disease, adding another layer to our understanding of hepatic regeneration and metabolic regulation. Our study underscores the role of HCF-1 in hepatocyte function and its impact on the epigenetic and transcriptional activity of the liver.

Abbreviations

ChIP-Seq

Chromatin Immunoprecipitation sequencing

CpG

Cytosine-phosphate-Guanine

DAVID

The Database for Annotation, Visualization and Integrated Discovery

H3K4me3

Histone H3 Lysine 4 trimethylation

HET

Heterozygous

HCF-1

Host Cell Factor 1

KO

Knockout

LINE

Long Interspersed Nuclear Element

NASH

Non-alcoholic steatohepatitis

NAFLD

Non-alcoholic fatty liver disease

OGT

O-linked β-N-acetylglucosamine transferase

POL2

RNA polymerase II

PH

Partial hepatectomy

SrpRNA

Signal recognition particle RNA

SMA

Smooth muscle α-actin

TSS

Transcriptional start sites

Authors’ contributions

The experiments were conceived and designed by S.M., J.K.D., and W.H. The experiments were performed by S.M., Sh.K., and D.B.. S.M., Sa.K., and W.H. analyzed the wet lab data. Sh.K., Sa.K., and J.K.D. analyzed the bioinformatics data. S.M. and J.K.D. wrote the paper. All authors participated in the discussion of the data and the production of the final version of the manuscript.

Funding

S.M. was supported by a Start-Up Research Grant from the Science and Engineering Board (SRG/2021/000341), a Ramalingaswami re-entry fellowship from the Department of Biotechnology (BT/RLF/Re-entry/70/217), and IFCPAR/CEFIPRA (Indo-French Centre for Promotion of Advanced Research/Centre Franco-Indien pour la Promotion de la Recherche Avancée) grant no. 6503-J. J.K.D. was supported by Har Govind Khorana-Innovative Young Biotechnologist Award from the Department of Biotechnology (BT/13/IYBA/2020/07). This research was supported in part by Swiss National Science Foundation grant CRSII3_160798 to W.H. and the University of Lausanne.

Data availability

Sequence data that support the findings of this study have been deposited in the INSDC with the primary accession code PRJEB82566 provided by EMBL-EBI European Nucleotide Archive (ENA).

Declarations

Ethics approval and consent to participate

All animal experiments were approved by the Cantonal Veterinary Authority of Vaud, Switzerland (Permit No. 2691.0) and conducted in compliance with Swiss federal regulations, including the Animal Welfare Act and Animal Protection Ordinance. Experiments were performed at the University of Lausanne in collaboration with the RESAL– Lemanic Animal Facility Network.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.