Transcription factor 19 modulates fatty acid elongation and unfolded protein response to attenuate palmitic acid-induced hepatic dysfunction

Atanu Mondal; Arnab Chakraborty; Sandhik Nandi; Vipin Singh; Siddhesh S Kamat; Chandrima Das

doi:10.1038/s41467-026-72138-9

. 2026 Apr 22;17:5596. doi: 10.1038/s41467-026-72138-9

Transcription factor 19 modulates fatty acid elongation and unfolded protein response to attenuate palmitic acid-induced hepatic dysfunction

Atanu Mondal ^1,², Arnab Chakraborty ³, Sandhik Nandi ^1,², Vipin Singh ^1,², Siddhesh S Kamat ³, Chandrima Das ^1,^2,^✉

PMCID: PMC13315908 PMID: 42020413

Abstract

Saturated fatty acids, which increase during high-fat diets and metabolic disease, disrupt lipid homoeostasis, leading to hepatic dysfunction. Understanding how hepatocytes adapt to this stress is essential for delineating the early events of fatty liver disease and its progression to more severe inflammation and fibrosis. Here, we show that the transcription factor TCF19 acts as a central regulator that helps hepatocytes manage lipid overload and cellular stress in both MAFLD mice model and human clinical samples. Combining lipidomic and transcriptomic analysis, we found that TCF19 controls genes involved in fatty-acid elongation and protein-folding responses, thereby linking lipid metabolism with endoplasmic-reticulum stress-response pathways. Elevated TCF19 levels are associated with lipid accumulation, whereas reducing TCF19 worsens inflammation and fibrotic features of the liver. Together, our findings identify TCF19 as a protective regulator during the transition from early hepatic fat accumulation to inflammatory liver disease, highlighting a potential target for early therapeutic intervention.

Subject terms: Epigenetics, Metabolic disorders

Here the authors report that epigenetic regulation by TCF19 in liver maintain triglyceride pools diminishing free fatty acid-mediated lipotoxicity. Furthermore, it also prevents misfolded protein accumulation, suppressing inflammation and cell death pathways that drive fibrosis.

Introduction

Metabolic dysfunction-associated fatty liver disease (MAFLD) represents a growing global health crisis, affecting ~40% of the world’s population¹. This multifactorial disorder arises from obesity, insulin resistance, type 2 diabetes, dyslipidaemia, and excessive dietary saturated fatty acid intake, which converge to disrupt hepatic lipid homoeostasis. The disease encompasses a progressive spectrum from simple metabolic dysfunction-associated steatosis (MAS) to complex metabolic dysfunction-associated steatohepatitis (MASH) with hepatocellular injury and inflammation, advancing to fibrosis, cirrhosis, and ultimately hepatocellular carcinoma (HCC)². Cellular adaptation to lipotoxic stress involves intricate molecular mechanisms that regulate fatty acid metabolism, lipid storage, and stress response pathways³. Understanding these mechanisms is essential for developing targeted therapeutic strategies to mitigate MAFLD progression. However, the precise transcriptional regulators and molecular networks governing hepatic lipid metabolism during lipotoxic stress remain elusive.

Central to MAFLD is deregulated lipid metabolism manifesting through multiple pathways. The primary driver of hepatic lipid accumulation is an overabundance of dietary free fatty acids (FFA) that exceed the liver’s metabolic capacity². Initially, hepatocytes respond by activating β-oxidation pathways to break down these fatty acids⁴. At the same time, anabolic processes such as de novo lipogenesis (DNL) and fatty acid chain elongation produce short-chain fatty acids and subsequently convert them into longer-chain fatty acids. These fatty acids are stored as triglycerides (TG) within the lipid droplet to reduce the FFA-mediated lipotoxicity^5,6. Disruption of this balance between synthesis, elongation, and β-oxidation underlies MAFLD metabolic dysfunction.

Notably, fatty acids synthesised through DNL get esterified for storage as TG^7,8. The key enzyme in DNL responsible for converting Acetyl-CoASH to Malonyl-CoASH is acetyl-CoA carboxylase (ACC). Subsequently, Malonyl-CoASH gets converted into fatty acid chains, primarily producing Palmitic acid (PA) (16:0), by the enzymatic action of Fatty acid Synthase (FAS/FASN)⁹. Notably, Palmitic acid, the most abundant saturated fatty acid in the Western diet, plays a crucial role in triggering metabolic perturbations that contribute to MAFLD progression^10,11.

Consumption of Palmitate in the diet leads to its conversion to Palmitoyl-CoA in the cytosol, which subsequently enters the ER lumen via Hedgehog acyltransferase (Hhat) transporter¹² for fatty acid unsaturation and chain elongation. The fatty acid chain elongation pathway involves several key enzymes, including acyl-CoA synthetase, 3-keto-acyl-CoA synthase (ELOVLs), 3-hydroxy acyl-CoA dehydratase (HACDs), and 3-keto-acyl-CoA reductase¹³. These enzymes are crucial in mitigating short-chain saturated fatty acid-mediated lipotoxicity. The HACD family, comprising four isoforms (HACD1-4), catalyses the third step of fatty acid chain elongation¹⁴. The ELOVL family, consisting of seven tissue-specific isoforms (ELOVL1-7), controls the rate-limiting condensation process in chain elongation. While ELOVL1, 3, 6, and 7 process saturated and monounsaturated fatty acids, ELOVL2, 4, and 5 handle polyunsaturated fatty acids^15,16. Despite known associations between ELOVL isoforms and metabolic disorders, the specific role of ELOVL1 in MAFLD remains poorly understood^17–19. Similarly, a direct functional role of dehydratase family member HACD3 with MAFLD is yet to be established.

A persistent accumulation of saturated fatty acids disrupts endoplasmic reticulum (ER) calcium homoeostasis, triggering ER stress and activating the unfolded protein response (UPR)²⁰. To curb the situation, protein re-folding machinery plays an active role. In this context, protein disulphide isomerases (PDIAs) play a crucial role in curbing the proteostasis and cell death²¹. In the absence of this re-folding event, acute ER stress sets in, causing an inflammatory response and activation of cell death pathways^22–24. Acute ER stress is instrumental in metabolic dysfunction associated steatosis (MAS) to MASH progression, characterised by hepatic inflammation and cell death stemming from altered lipid metabolism²⁵. Further, persistent inflammation drives hepatic stellate cell activation, resulting in excessive collagen deposition and extracellular matrix (ECM) remodelling^26,27. This ECM stiffening not only impairs hepatic architecture but also creates a mechanically altered microenvironment that perpetuates disease progression and fibrosis.

Epigenetic mechanisms play pivotal roles in regulating lipid metabolism. The chemical modifications on the histone tails govern transcriptional activity at promoters and enhancers of lipogenic and chain elongation enzymes, providing therapeutic avenues for modulating metabolic dysfunction. Transcription factor 19 (TCF19) has emerged as a critical epigenetic factor that can act as a metabolic stress sensor. It functions as a p53-interacting protein regulating mitochondrial energy metabolism during high glucose stress²⁸. Interestingly, the ability of TCF19 to recognise H3K4me3 histone marks²⁹ enables chromatin recruitment of multiple regulatory factors, orchestrating transcription³⁰. One such factor is Transcription Factor 7-like 2 (TCF7l2/TCF4), a type 2 diabetes-associated regulator, which epigenetically controls fatty acid chain elongase genes like PTPLAD1 (HACD3 protein) in concert with TCF19³¹. This positions TCF19 as a master coordinator integrating nutritional signals with epigenetic chromatin states. However, the precise mechanisms by which TCF19 regulates hepatic lipid metabolism during fatty acid overload remain to be elucidated.

The present study comprehensively investigates TCF19 as a master regulator of hepatic lipid metabolism during palmitic acid-induced stress. Using an integrated approach employing hepatic cell lines and primary hepatocytes, and in vivo mouse models, we demonstrate that TCF19 upregulation upon PA treatment promotes fatty acid chain elongation, triglyceride synthesis, and lipid droplet accumulation by transcriptionally activating key elongases ELOVL1 and HACD3, thereby promoting hepatic steatosis. Mechanistically, TCF19 recruits CBP/p300 to enhance H3K27ac enrichment at ELOVL1 and HACD3 promoters, driving their expression. Additionally, TCF19 regulates the ER stress-responsive factor, PDIA4, modulating protein refolding capacity under lipotoxic conditions. Importantly, TCF19 expression is elevated in simple steatosis but reduced during fibrosis in mice and patients. TCF19 depletion exacerbates PA-induced hepatotoxicity by reducing lipid storage capacity, promoting inflammation, apoptosis, PBMC invasion, and fibrotic responses, including enhanced ECM deposition and LOX activity. These findings establish TCF19 as a gatekeeper that promotes adaptive lipid remodelling in early MAFLD while its loss accelerates steatosis-to-steatohepatitis progression. Thus, TCF19-CBP/p300 complex-mediated regulation of ELOVL1 and HACD3 genes could emerge as a potential therapeutic strategy for MAFLD.

Results

TCF19 plays a critical role in fatty acid chain elongation upon free fatty acid-mediated stress induction

To investigate the effects of FFA on lipid metabolism (Supplementary Fig. 1) and the role of TCF19, we treated HepG2 cells (Fig. 1A and Supplementary Fig. 2A) and Balb/c mice (Fig. 1B) with palmitic acid (PA), a 16:0 saturated fatty acid, in conjugation with BSA in the presence or absence of TCF19 and performed comprehensive lipidomics analysis (Fig. 1C). In HepG2 cells, PA-treatment resulted in significant alterations in lipid profiles. We observed a marked increase in very long-chain fatty acids compared to control conditions (Fig. 1C). Lipidomics analysis following TCF19 knockdown revealed significant alterations in fatty acid profiles. Specifically, we observed a significant reduction in monounsaturated very long-chain fatty acid levels in TCF19 knockdown cells compared to control cells, with these effects being further induced by PA treatment (Fig. 1C). Furthermore, knocking down TCF19 upon other FFAs treatment, for example, 18:0 saturated fatty acid, stearic acid (SA) or 18:1 Δ9 monounsaturated fatty acid, oleic acid (OA) treatment also suppressed the production of very long chain monounsaturated fatty acids (Supplementary Fig. 2B–E), suggesting the involvement of TCF19 in the fatty acid chain elongation process (Supplementary Fig. 3).

To validate these findings in vivo, we administered PA to BALB/c mice through tail vein injection (Fig. 1B) and analysed their hepatic lipid content. Consistent with our in vitro observations, PA-treated mice exhibited elevated levels of very long-chain fatty acids (Fig. 1C). Knocking down TCF19 in PA-injected mice by TCF19 anti-sense oligo (ASO) administration significantly altered the pool of very long-chain fatty acids (Fig. 1C), indicating the role of TCF19 in chain elongation of monounsaturated fatty acids.

Given these changes in lipid profiles, we next examined the impact of PA treatment on energy metabolism. A measurement of oxygen consumption rate (OCR) reveals that PA-treatment enhances basal respiration significantly (Supplementary Fig. 4A, B). Strikingly, extracellular acidification rate (ECAR) measurement showed PA treatment has no significant effect on glucose metabolism (Supplementary Fig. 4C, D), indicating that PA-mediated upregulation of cellular respiration could be because of enhanced β-oxidation of FFAs. To investigate whether the fatty acid β-oxidation pathways were modulated in mitochondria or peroxisomes or both upon PA treatment, we performed sub-cellular fractionation to isolate mitochondria and peroxisomes (Supplementary Fig. 5A). The purity of these fractions was confirmed using specific markers: COX-IV for mitochondria, PMP70 for peroxisome and GRP78 for ER (Supplementary Fig. 5B). Analysis of peroxisomal β-oxidation revealed no significant differences between control and PA-treated HepG2 cells (Supplementary Fig. 5C). However, examination of mitochondrial β-oxidation showed a striking induction (Supplementary Fig. 5D–I). Further, to measure the role of TCF19 in the mitochondrial β-oxidation pathway, we measured the OCR upon administration of mitochondrial β-oxidation pathway blocker (etomoxir) and found PA-treatment promotes mitochondrial β-oxidation of FFAs independent of TCF19 (Fig. 2A-B).

Fig. 2 — A, B Measurement and quantification of etomoxir-dependent oxygen consumption rate (OCR) (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. C Measurement of cellular triglyceride in control, PA-treated, TCF19 knockdown and PA-treatment in TCF19 knockdown primary hepatocytes (n = 4). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. D Measurement of serum triglyceride in BSA_Control, PA-injected mice, and PA injection in TCF19 ASO-injected mice (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. Cellular levels of diglycerides (E), triglycerides (G) and phospholipids (I) in control, PA-treated, TCF19 knockdown and PA-treatment in TCF19 knockdown HepG2 cells (n = 3) (A.U., arbitrary units). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. Cellular level of C-13 isotope labelled diglycerides (F), triglycerides (H) and phospholipids (J) in C-13 isotope labelled PA-treated and C-13 isotope labelled PA-treatment in TCF19 knockdown HepG2 cells (n = 3) (A.U., arbitrary units). Unpaired Student's t test (two-tailed) was performed to analyse the p-value significance; the data are presented as mean value ± SEM. K Oil red O staining of lipid droplets in ×20 magnification in Huh7 cells. L, M Quantification of accumulated lipid droplets in control, PA-treated, TCF19 knockdown and PA-treatment in TCF19 knockdown Huh7 (M) and HepG2 (N) cells (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM.

Taken together, these results indicate that TCF19 promotes chain elongation of very long chain mono-unsaturated fatty acids but not β-oxidation upon FFA-induced stress conditions.

Free fatty acid treatment induces the formation of diglyceride, triglyceride and phospholipids of very long chain mono-unsaturated fatty acids and promotes lipid droplet formation under the regulation of TCF19

To investigate the effect of TCF19 on the metabolism of very long chain monounsaturated fatty acids upon FFA-treatment, we measured the total triglyceride pool from cells as well as the PA-treated mice serum. We observed that upon knocking down TCF19, there is a significant reduction in the total triglyceride both in the cell (Supplementary Fig. 6A), primary hepatocyte (Fig. 2C) and PA-treated mice serum (Fig. 2D). We further assessed the impact of TCF19 on triglyceride metabolism by lipidomic analysis of diglycerides, triglycerides and phospholipids of very long-chain monounsaturated fatty acids and observed significant reduction upon TCF19 knockdown in the presence or absence of PA (Fig. 2E, G, I and Supplementary Fig. 6B). Furthermore, knocking down TCF19 during SA or OA-treatment also significantly reduces the production of diglycerides, triglycerides and phospholipids of very long-chain monounsaturated fatty acids (Supplementary Fig. 7A, B).

To further validate the incorporation of FFA into the cellular DG, TG and phospholipid pools, we treated the cells with C13 isotope-labelled PA in the presence or absence of TCF19. We found a significant reduction in respective DG, TG, and phospholipid levels upon knocking down TCF19 (Fig. 2F, H, J and Supplementary Fig. 8A). Notably, the unlabelled DG, TG and phosphatidylcholine (PC) pools did not show significant alteration upon TCF19 knockdown, indicating that TCF19 does not have any significant role in DNL (Supplementary Fig. 8B).

To examine the functional consequences of TCF19-mediated regulation on lipid accumulation, we performed Oil Red O staining in both Huh7 (Fig. 2K, L) and HepG2 (Fig. 2M, Supplementary Fig. 8C) cells, which revealed a significant reduction of lipid droplet formation upon TCF19 knockdown in the presence or absence of PA.

Collectively, these results demonstrate that TCF19 is a key regulator of fatty acid metabolism, particularly in the context of chain elongation of monounsaturated fatty acids, and plays a crucial role in triglyceride homoeostasis and lipid droplet accumulation both in vitro and in vivo.

TCF19 functions as a key transcriptional regulator of lipid metabolism in response to palmitic acid

To investigate the molecular mechanisms underlying the role of TCF19 in lipid metabolism, we first examined its expression patterns in 2D and 3D hepatic cell models. At the onset, a concentration range (300–500 μM)^32,33 of BSA-PA conjugates was treated in the hepatic cells, and a gradual induction of TCF19 expression could be observed, with a 500 μM concentration showing a robust induction (Supplementary Fig. 9A). Western blot in hepatic cells (Fig. 3A-B and Supplementary Fig. 9B–D) and immunohistochemistry (IHC) of 3D-spheroid model (Fig. 3C, D) revealed a distinct induction of TCF19 protein upon 500 μM PA treatment. These findings were further validated in vivo through IHC staining and ELISA of hepatic tissue from BSA-control and PA-injected mice, which showed a significant induction in TCF19 level in the latter cohort (Fig. 3E–G).

Fig. 3 — A, B Western blotting of TCF19 and its quantification in control and PA-treated HepG2 cells (n = 3). Unpaired Student's t-test (two-tailed) was performed to analyse the p-value significance; the data are presented as mean value ± SEM. C, D IHC staining and quantification of TCF19 in paraffin-embedded sections of control and PA-treated Huh7 spheroids (n = 3). Unpaired Student’s t-test (two-tailed) was performed to analyse the p-value significance; the data are presented as mean value ± SEM. E, F IHC staining and quantification of TCF19 in hepatic tissue of BSA_Control, PA-injected mice, and PA injection in TCF19 ASO-injected mice (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. G ELISA of TCF19 in hepatic tissue lysate of BSA_Control, PA-injected mice and PA injection in TCF19 ASO-injected mice (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. H Panther pathway analysis of lipid metabolic genes. I KEGG pathway analysis of microarray data of TCF19 knockdown HepG2 cells showing that fatty acid chain elongation is one of the altered pathways. J Common genes of TCF19 knockdown microarray data and PA-treated HepG2 cell RNA seq data. K KEGG pathway analysis of common genes of TCF19 knockdown microarray data and PA-treated HepG2 cell RNA seq data. L qRT-PCR validation of TCF19, ELOVL1, and HACD3 in control, PA-treated, TCF19 knockdown and PA treatment in TCF19 knockdown primary hepatocytes (n = 4). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. M qRT-PCR validation of TCF19, ELOVL1, and HACD3 in hepatic tissue of BSA_Control, PA-injected mice and PA injection in TCF19 ASO-injected mice (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM.

To comprehensively understand the regulatory role of TCF19, we re-analysed the differential gene expression dataset of TCF19 knockdown in HepG2 cells (GEO Accession ID GSE107471). Panther GO pathway analysis of the differentially expressed genes (DEGs) revealed that metabolic genes constituted one of the major altered biological processes (Supplementary Fig. 10A). Among these candidates, the fatty acid metabolic process is one of the major hubs (Fig. 3H). Further, KEGG pathway analysis also revealed that Fatty acid chain elongation was among the top deregulated pathways (Fig. 3I). The KEGG pathway analysis of the common genes of TCF19 DEGs (GEO Accession ID GSE107471) and PA-treated DEGs (GEO Accession ID GSE152091) indicates fatty acid chain elongation is one of the Top 5 altered pathways (Fig. 3J, K).

To validate these findings, we performed qRT-PCR analysis of key metabolic genes in various experimental conditions. We quantified the expression of TCF19 itself (Supplementary Fig. 10B) and several crucial lipid metabolic genes, including, fatty acid chain elongases like ELOVL1, ELOVL2, ELOVL4, PTPLAD1 (HACD3 protein), PTPLB (HACD2 protein), HSD17B12 and genes involved in fatty acid β-oxidation like CPT1A, CPT2, ACOX1, ACOX2, ACOT7 in presence or absence of TCF19 upon PA treatment (Supplementary Fig. 10C–M). We observed that TCF19 crucially regulated the expression of these lipid metabolic genes. To confirm the physiological relevance of these findings, we examined the expression of the same gene set in primary hepatocytes and hepatic tissue upon control and PA treatment in the presence or absence of TCF19. qRT-PCR analysis of TCF19, ELOVL1 and HACD3 (Fig. 3L, M) in these systems showed significant alteration, consistent with our in vitro findings.

Together, these findings establish TCF19 as a critical transcriptional regulator of lipid metabolic genes, particularly in response to palmitic acid treatment, and demonstrate its importance in regulating lipid metabolism in both cellular and physiological contexts.

TCF19 regulates epigenetic interplay between histone H3K4 trimethylation and H3K27 Acetylation for lipid metabolic gene expression

To validate the functional consequences of the transcription regulation, we examined protein expression of two key very long-chain monounsaturated fatty acid chain elongases ELOVL1 and HACD3. Western blot analysis of ELOVL1 and HACD3 in both Huh7 (Fig. 4A and Supplementary Fig. 11A–C) and HepG2 cells (Supplementary Fig. 11D–F) demonstrated significant induction in protein levels upon PA treatment. Further knocking down TCF19 suppresses their expression significantly in control as well as PA-treated conditions (Fig. 4B and Supplementary Fig. 11G–K). To extend these findings to an in vivo context, we performed IHC and ELISA of both ELOVL1 and HACD3 in hepatic tissue from control and PA-treated mice in the presence or absence of TCF19. Our results indicated an induction of ELOVL1 and HACD3 protein upon PA treatment, which was significantly reduced in the TCF19 knockdown condition (Fig. 4C–E).

Fig. 4 — A Western blotting of ELOVL1 and HACD3 in control and PA-treated Huh7 cells (n = 3). B Western blotting of ELOVL1 and HACD3 in control, PA-treated, TCF19 knockdown and PA treatment in TCF19 knockdown HepG2 cells (n = 3). C, D IHC staining of ELOVL1 and HACD3 and its quantification in hepatic tissue of BSA_Control, PA-injected mice and PA injection in TCF19 ASO-injected mice (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. E ELISA of ELOVL1 and HACD3 in hepatic tissue lysate of BSA_Control, PA-injected mice and PA injection in TCF19 ASO-injected mice (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. F Schematic representation of different regions of the ELOVL1 and HACD3 gene promoter. G–J Chromatin Immunoprecipitation (ChIP) assay of TCF19 and H3K4me3 at Region 1 of the ELOVL1 and HACD3 gene promoter in control, PA-treated HepG2 cells (n = 3). Two-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. K–N Chromatin Immunoprecipitation (ChIP) assay of TCF19 and H3K27ac at Region 2 in ELOVL1 and HACD3 gene promoter (n = 3). Two-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM.

To elucidate the molecular mechanism by which TCF19 regulates lipid metabolic gene expression, we performed chromatin immunoprecipitation (ChIP) assays examining two proximal regions (Region 1 and 2) of ELOVL1 and HACD3 (Fig. 4F–N and Supplementary Fig. 12A, B) genes. While PA treatment led to a loss of TCF19 at a particular site (Region 1) on the promoter, its proximal site (Region 2) showed an enriched occupancy (Fig. 4G, H). Remarkably, histone H3K4 trimethylation, previously reported as the binding site of TCF19^29,30, showed a reduced occupancy at the initial site (Region 1) (Fig. 4I, J). In contrast, histone H3K27 acetylation and TCF19 binding were elevated at ELOVL1 and HACD3 gene promoters (Region 2) (Fig. 4K–N). We observed a significant abundance of H3K27ac upon PA treatment in comparison to the control cells in both of these genes, which was substantially diminished upon knocking down TCF19 (Fig. 4M, N and Supplementary Fig. 12C).

These results collectively demonstrate that TCF19 functions as an epigenetic regulator by promoting an interplay between H3K4 trimethylation and H3K27 acetylation at the promoters of fatty acid chain elongases ELOVL1 and HACD3, thereby enhancing their transcription in response to palmitic acid treatment. This epigenetic relay mechanism emphasises the role of epigenetic regulators in fine-tuning transcriptional programmes of the metabolic genes in the context of nutritional stress.

TCF19 recruits CBP/p300 to regulate lipid metabolic gene expression

To identify the molecular partners through which TCF19 mediates its transcriptional regulatory functions, we performed immunoprecipitation of TCF19 followed by mass spectrometry analysis. This approach revealed several TCF19-interacting proteins, including both transcriptional co-activating and co-repressing complexes (Fig. 5A). Histone acetyltransferases CBP and p300 were previously identified as potential mediators engaged in the regulatory function of TCF19²⁸, which is known to acetylate histone H3 at K27 residue³⁴. To validate these interactions, we performed co-immunoprecipitation experiments followed by western blotting for CBP and p300. These experiments confirmed the physical interaction between TCF19 and both CBP and p300 (Fig. 5B), suggesting that TCF19 may recruit these histone acetyltransferases to target gene promoters.

Fig. 5 — A TCF19 immunoprecipitation followed by mass spectrometry (IP-MS) showing different TCF19 interacting transcription co-activating and co-repressing complexes. NG represents normoglycemic media condition (5.5 mM glucose). B Coimmunoprecipitation of TCF19 followed by western blotting to CBP and p300. C, D Chromatin Immunoprecipitation (ChIP) assay of CBP and p300 in the ELOVL1 gene promoter (region 2) in control, TCF19 knockdown, PA-treated and PA treatment upon TCF19 knockdown condition in HepG2 cells (n = 3). Two-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. E Chromatin Immunoprecipitation (ChIP) assay of KDM5C in the ELOVL1 gene promoter (region 1) in control and PA-treated HepG2 cells (n = 3). Two-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. F, G Chromatin Immunoprecipitation (ChIP) assay of H3k4me3 and TCF19 in the ELOVL1 gene promoter (region 1) in PA-treated and PA treatment in KDM5C inhibitor-treated HepG2 cells (n = 3). Two-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. H, I Chromatin Immunoprecipitation (ChIP) assay of H3K27ac and TCF19 in the ELOVL1 gene promoter (region 2) in PA-treated and PA treatment in KDM5C inhibitor-treated HepG2 cells (n = 3). Two-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. J Graphical representation of over all epigenetic regulatory mechanism of the ELOVL1 gene transcription upon PA treatment. Created in BioRender. Das, C. (2026) https://BioRender.com/cclikgu.

To investigate whether TCF19 facilitates the recruitment of CBP and p300 to specific target genes, we performed ChIP assays examining their occupancy at the promoters (Region 2) of ELOVL1 and HACD3. At the ELOVL1 promoter, we observed significant enrichment of both CBP (Fig. 5C) and p300 (Fig. 5D) under PA-treated conditions, which was markedly reduced upon TCF19 knockdown. Similarly, the HACD3 promoter showed PA-dependent recruitment of CBP (Supplementary Fig. 13A) and p300 (Supplementary Fig. 13B), which was also regulated by TCF19.

Interestingly, we observed that proximal to the acetylation site (Region 2), there is an H3K4me3-enriched region (Region 1) in the ELOVL1 and HACD3 gene promoters. Upon PA treatment, we observed a downregulation of the H3K4me3 mark due to the increased recruitment of KDM5C (Fig. 5E and Supplementary Fig. 13C), a well-known demethylase of H3K4me3^35–37. A treatment with KDM5C inhibitor (KDM5Ci) led to stabilisation of H3K4me3 mark (Fig. 5F and Supplementary Fig. 13D) and a consequent reinstatement of TCF19 (Fig. 5G and Supplementary Fig. 13E). In order to validate if the epigenetic relay mechanism was driven by TCF19, treatment with KDM5Ci blocked the H3K27ac at region 2 with a concomitant reduction of TCF19 recruitment at the same region (Fig. 5H, I and Supplementary Fig. 13F, G). Based on these findings, we propose a mechanistic model wherein a reduced occupancy of H3K4me3 as a sequel to the recruitment of KDM5C (Region 1) can be observed in the promoters of ELOVL1 and HACD3 genes upon palmitic acid treatment, leading to basal transcription activation. Concomitantly, TCF19 gets dislodged from the H3K4me3-enriched region (Region 1) and gets recruited to a proximal location (Region 2), assisting in the enhanced occupancy of CBP/p300 complexes to the promoters of ELOVL1 and HACD3 genes. This leads to increased H3K27 acetylation and elevated transcription of these fatty acid chain elongation genes (Fig. 5J). Notably, we observed a significant reduction in the ELOVL1 expression upon inhibiting the activity of CBP/p300 in a PA-treated condition (Supplementary Fig. 13H, I). Thus, by transcriptionally regulating fatty acid chain elongase, TCF19 can modulate the lipid metabolic flux. Remarkably, upon inhibiting ELOVL1, we observed a reduction in the lipid droplet formation in PA-treated conditions (Supplementary Fig. 14A, B), emphasising its role in regulating cellular lipid storage.

These results collectively establish TCF19 as a crucial mediator of the cellular response to palmitic acid treatment, through its ability to modulate the recruitment of histone demethylase and acetyltransferases to specific target genes involved in fatty acid chain elongation, thereby coordinating the transcriptional response to metabolic stress (Supplementary Fig. 14C).

TCF19 regulates ER stress response through transcriptional control of PDIA4 in concert with p300/CBP

FFA treatment induces Endoplasmic Reticulum (ER) stress by disrupting calcium ion transporters. KEGG pathway analysis of DEGs upon TCF19 knockdown shows significant ER stress response pathway alteration (Supplementary Fig. 15A). Further, TCF19 was observed to be upregulated upon induction of ER stress by PA treatment (Fig. 3A) as well as by any conventional ER-stress activators like Thapsigargin (TG) (Supplementary Fig. 15B). To investigate the role of TCF19 in ER stress response under palmitic acid treatment, we first examined the organisation of the endoplasmic reticulum using specific markers for rough and smooth ER. Immunofluorescence imaging of Sec61β, a marker for rough endoplasmic reticulum (RER), revealed significant changes in RER distribution and intensity across control, PA-treated, TCF19 knockdown, and PA-treated in TCF19 knockdown conditions (Fig. 6A, B). This result indicates that the absence of TCF19 upon PA treatment leads to a remarkable reduction in RER amount, indicating the involvement of this epigenetic regulator in curbing the PA-induced ER stress. We also analysed the smooth endoplasmic reticulum (SER) marker, RNT4, and observed a significant reduction by TCF19 knockdown alone, which was partially rescued upon PA treatment (Supplementary Fig. 15C, D). Since SER is the site for fatty acid metabolic processes, these results indicate the significant contribution of TCF19 in mitigating the toxic effect of the FFA pool in the cell. This could result in curbing UPR elicited in the presence of PA. FFA-mediated deregulation of Calcium homoeostasis perturbs the function of ER chaperones, leading to the accumulation of misfolded protein, resulting in the activation of enzymes responsible for protein refolding²⁰. Indeed, we observed an alteration in the ER Calcium Pool when TCF19 was knocked down in a Palmitic acid-treated backdrop (Fig. 6C and Supplementary Fig. 16A, B). Remarkably, TCF19 overexpression could restore cellular Calcium homoeostasis. In the ER, breakdown of the Calcium homoeostasis leads to dysfunction of classical ER chaperones, which function in a Calcium-dependent manner, leading to the accumulation of unfolded proteins. This leads to activation of all three classical ER-stress pathways^38,39. However, in the absence of the ER Calcium pool, GRP78 becomes non-functional, shutting down the protein folding machinery, resulting in heightened accumulation of misfolded protein^40,41.

Fig. 6 — A, B Immunofluorescence imaging and quantification of Sec61β (a marker for RER) in control (n = 37), PA (n = 50), TCF19 knockdown (n = 27) and PA treatment in the TCF19 knockdown condition (n = 50). Each data point represents an individual cell. The box represents the middle 50% of the data, and the central line represents the median. The Whisker ranges from the box to the minimum and maximum value. One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. C Measurement of ER calcium pool in the presence or absence of TCF19 and overexpression of TCF19 in TCF19 knockdown condition, in the presence or absence of PA (n = 8). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. D Measurement of total unfolded protein in HepG2 cells, in the presence or absence of TCF19 and overexpression of TCF19 in TCF19 knockdown condition, in the presence or absence of PA (n = 6). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. E qRT-PCR analysis of PDIA4 in control, PA-treated, TCF19 knockdown and PA treatment in TCF19 knockdown HepG2 cells (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. F, G Western blotting and quantification of ERP72 (PDIA4 gene) in control, PA-treated, TCF19 knock down and PA treatment in TCF19 knockdown HepG2 cells (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. H qRT-PCR validation of PDIA4 in hepatic tissue of BSA_Control mice, PA-injected mice and PA injection in TCF19 ASO-injected mice (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. I ELISA of ERP72 (PDIA4 gene) from the liver lysate of BSA_Control mice, PA-injected mice and PA injection in TCF19 ASO-injected mice (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. Chromatin Immunoprecipitation (ChIP) assay of TCF19 (J) and H3K27ac (K) in PDIA4 gene promoter in control, TCF19 knockdown, PA-treated and PA treatment upon TCF19 knockdown condition in HepG2 cells (n = 3). Two-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. L Schematic representation of TCF19-mediated regulation of misfolded protein load and UPR upon palmitic acid treatment. Created in BioRender. Das, C. (2026) https://BioRender.com/cclikgu.

To score the total amount of misfolded proteins, we set out to perform UPR assays by staining the cells with TPE-MI fluorophore⁴² in a PA-treated background in the presence or absence of TCF19 and also performed rescue experiments with further overexpressing TCF19 (Fig. 6D and Supplementary Fig. 16A–C). Our results indicate that TCF19 could curb the burden of misfolded proteins during PA-treated conditions. In this context, the disulphide isomerase plays a crucial role in refolding these misfolded proteins. From a physiological perspective, there is a crucial contribution of the ER stress pathway in steatohepatitis patients. RNA-Seq data analysis of NAFLD patients shows a significant positive correlation with protein disulphide isomerase 4 (PDIA4) (Supplementary Fig. 17A). Given these changes in ER organisation and Calcium homoeostasis, we examined the expression of PDIA4, a key protein disulphide isomerase involved in protein refolding and ER stress response^43,44. A significant upregulation of PDIA4 at both the RNA and protein (ERP72) levels was observed upon PA treatment and reduction upon TCF19 knockdown in the presence or absence of PA in HepG2 cells (Fig. 6E–G and Supplementary Fig. 17B–G). PDIA4 expression was also found to be elevated in PA-injected mice and was downregulated upon knocking down TCF19 (Fig.6H, I).

To determine whether TCF19 directly regulates PDIA4 transcription, we performed ChIP analysis examining TCF19 binding to the PDIA4 promoter. The results showed significant TCF19 enrichment at the PDIA4 promoter upon PA treatment (Fig. 6J). Additionally, ChIP analysis of H3K27ac at the PDIA4 promoter demonstrated that TCF19 is required for PA-induced increase in H3K27 acetylation at this locus (Fig. 6K and Supplementary Fig. 18A, B). To investigate whether this increased enrichment of H3K27ac was also due to the recruitment of CBP/p300 by TCF19, we performed ChIP assays examining their occupancy at the PDIA4 gene promoter. We observed significant enrichment of both CBP (Supplementary Fig. 18C) and p300 (Supplementary Fig. 18D) upon PA-treatment, which was markedly reduced in TCF19 knockdown cells. Notably, we did not observe any significant alteration in H3K4me3 level upon PA treatment in the PDIA4 gene promoter (Supplementary Fig. 18E). This indicates that the epigenetic cross-talk between H3K4me3 and H3K27ac was a unique signature as observed in the metabolic genes, ELOVL1 and HACD3.

Based on these findings, we propose a model wherein TCF19 acts as a key regulator of the cellular response to PA-induced ER stress by controlling PDIA4 expression and thereby modulating protein refolding capacity and the UPR (Fig. 6L). Thus, the absence of TCF19 upon PA treatment causes acute ER stress, leading to apoptosis and inflammation. This mechanism represents a novel link between lipid-induced stress and protein-refolding homoeostasis in the ER. These results establish TCF19 as a critical regulator of ER stress response through its transcriptional control of PDIA4, suggesting a broader role for TCF19 in maintaining cellular homoeostasis under metabolic stress conditions.

TCF19 expression is altered in MAFLD progression and regulates hepatic inflammation

To validate the role of TCF19 in regulating the fatty acid-mediated stress adaptation, we next moved into a high-fat diet-fed MAFLD mice model experiment in the presence or absence of TCF19 (Supplementary Fig. 19A). We observed that knocking down TCF19 in the MAFL condition can reduce animal body weight (Supplementary Fig. 19B, C), liver weight (Supplementary Fig. 20A), liver fat deposition (Supplementary Fig. 20B), hepatic and serum triglyceride content (Supplementary Fig. 20C) than the MAFL cohort. Interestingly, in the TCF19ASO-injected MAFL mice signature of hepatic lesion could be observed, indicating the absence of TCF19 leads to hepatic injury due to reduced triglyceride accumulation (Fig. 7A and Supplementary Fig. 20B). As a control, MASH mice showed a remarkable tissue injury and aggravated liver fibrosis (Fig. 7A and Supplementary Fig. 20B). We subsequently monitored the expression of TCF19, ELOVL1 and HACD3 both in RNA and protein levels. Our results indicate that TCF19, along with ELOVL1 and HACD3, is induced in MAFL diet-fed mice as compared to chow diet-fed mice, whereas knockdown of TCF19 in MAFL diet-fed mice significantly reduced both the metabolic gene expression, similar to the MASH diet-fed mice (Fig. 7B–I). These results indicate that loss of TCF19 leads to a reduction in fatty acid metabolic gene expression, resulting in reduced triglyceride production, causing hepatic injury.

Fig. 7 — A Representative images of control, MAFL, MAFL with TCF19 ASO and MASH diet-fed mice liver. qRT-PCR analysis of TCF19 (B), ELOVL1 (C) and HACD3 (D) mRNA expression in hepatic tissue of control diet, MAFL diet, MAFL diet with TCF19 ASO and MASH diet-fed mice (n = 5). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. E, F IHC staining and quantification of TCF19 in the hepatic tissue of control diet, MAFL diet, MAFL diet with TCF19 ASO and MASH diet-fed mice (n = 5). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. ELISA of TCF19 (G), ELOVL1 (H) and HACD3 (I) from the hepatic tissue lysate of control diet, MAFL diet, MAFL diet with TCF19 ASO and MASH diet-fed mice (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. mRNA expression of TCF19 (J), ELOVL1 (K) and HACD3 (L) in fibrotic (n = 15) and non-fibrotic patients’ liver samples (n = 17). Data was taken from the R2 genomics database and represented by GraphPad Prism (8.4.2). The box represents the middle 50% of the data, and the central line represents the median. The Whisker ranges from the box to the minimum and maximum value. Unpaired Student t-test (two-tailed) was performed to analyse the p-value significance; the data are presented as mean value ± SEM. M, N IHC staining and quantification of TCF19 in hepatic tissue of healthy control (n = 9), non-alcoholic steatosis (NAS/NAFL) (n = 20) and non-alcoholic steatohepatitis (NASH) (n = 20) patients. The box represents the middle 50% of the data, and the central line represents the median. The Whisker ranges from the box to the minimum and maximum value. One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM.

To investigate the clinical relevance of TCF19, we first analysed its expression in human liver samples. Investigation of mRNA expression from the R2 genomics database revealed a significant reduction of TCF19 expression in fibrotic tissue compared to non-fibrotic liver samples (Fig. 7J). Similarly, a reduction of ELOVL1 and HACD3 expression was also observed in the fibrotic tissue (Fig. 7K, L). We subsequently analysed the expression of TCF19 in separate cohorts of MAFLD patients with (AFLD) or without (NAFLD) a history of alcohol consumption. IHC of hepatic tissue from healthy controls, non-alcoholic steatosis (NAS), and non-alcoholic steatohepatitis (NASH) patients revealed an induction of TCF19 expression in NAS and a dramatic reduction in NASH (Fig. 7M, N). Similar observations were also detected in MAFLD patients with a history of alcohol consumption (Supplementary Fig. 21A, B), indicating TCF19 is a crucial transcription factor in metabolism-associated disorders. Further analysis of the R2 genomic database showed strong positive correlations between TCF19 mRNA levels and expression of ELOVL1 and HACD3 (Supplementary Fig. 21C, D) in NAFLD patients. Additionally, hepatic triglyceride levels showed significant positive correlations with the expression of TCF19, ELOVL1, and HACD3 (Supplementary Fig. 21E–G), as determined by Pearson Correlation Coefficient analysis. Further, we also observed that the Triglyceride level was reduced in fibrotic liver patients (Supplementary Fig. 21H), indicating that the FFA available in the hepatocytes is causal for lipotoxicity and fibrosis.

TCF19 is a positive regulator of Triglyceride levels in cells and has a direct correlation with fatty acid chain elongases. Thus, loss of TCF19 in a FFA-mediated stress situation would lead to reduced triglyceride levels, resulting in FFA-mediated lipotoxicity, progressing to hepatic inflammation and cell death.

Analysis of the R2 genomic database demonstrated significant negative correlations between TCF19 mRNA levels and expression of pro-inflammatory genes, including TNF1α, TLR4 and CCL2 (Supplementary Fig. 22A–C) in NAFLD patients. To validate these relationships experimentally, we performed qRT-PCR analysis of these inflammatory markers in hepatic cells, PA-injected mice and high-fat diet-fed mice model in the presence or absence of TCF19. Expression of TLR4 (Fig. 8A–C), TNF1α (Fig. 8D–F), and CCL2 (Fig. 8G–I) showed significant induction upon PA treatment in TCF19 knockdown conditions. To assess the functional consequences of these inflammatory changes⁴⁵, we performed immune cell migration and invasion assays (Supplementary Fig. 22D). The PBMC migration and invasion were significantly enhanced upon PA-treatment in TCF19 knockdown cells compared to controls, which can be suppressed by overexpressing TCF19 (Fig. 8J and Supplementary Fig. 23A–C). We also validated our findings in PA-injected mice and high-fat diet-fed mice models in the presence or absence of TCF19 by quantifying the amounts of invaded macrophages in the hepatic tissue. Remarkably, we observed that knocking down TCF19 expression can significantly upregulate the macrophage invasion in the presence of PA or a high-fat diet (Fig. 8K–M). To understand the role of TCF19 in regulating the PBMC invasion and migration via modulation of the ELOVL1 expression, we inhibited the activity of ELOVL1 or CBP/p300 individually in PA-treated conditions and performed similar assays. We observed that inhibiting either ELOVL1 or CBP/p300 in PA-treated conditions promotes PBMC invasion and migration, whereas overexpression of TCF19 could partially rescue the effect (Fig. 8N andSupplementary Fig. 23D–G).

Fig. 8 — A–C qRT-PCR validation of TLR4 in different condition of HepG2 cell (n = 3), PA injected mice (n = 3) and High-Fat-Diet-Fed mice (n = 5). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. D–F qRT-PCR validation of TNF1α in different conditions of HepG2 cell (n = 3), PA injected mice (n = 3) and High-Fat-Diet-Fed mice (n = 5). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. G–I qRT-PCR validation of CCL2 in different condition of HepG2 cell (n = 3), PA injected mice (n = 3) and high-fat-diet-fed mice (n = 5). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. J Quantification of PBMC invasion and migration assay towards conditional media PA-treated HepG2 cells in the presence and absence of TCF19 (n = 8). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. K IHC staining and quantification of F4/80 in hepatic tissue of BSA_Control mice, PA-injected mice and PA injection in TCF19 ASO-injected mice (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. L, M IHC staining and quantification of F4/80 in the hepatic tissue of control diet, MAFL diet, MAFL diet with TCF19 ASO and MASH diet-fed mice (n = 5). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. N Quantification of PBMC invasion and migration assay towards conditional media PA-treated HepG2 cells in the presence and absence of ELOVL1 inhibitor (n = 8). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM.

These results collectively demonstrate that TCF19 expression is dynamically regulated during MAFLD progression and plays a crucial role in protecting hepatic cells from FFA-induced inflammation. The loss of TCF19 appears to enhance inflammatory responses, suggesting its potential role as a protective factor in early stages of MAFLD that becomes dysregulated during disease progression.

TCF19 promotes cell survival, suppressing extracellular matrix deposition and consequent liver fibrosis

Hepatic cell death and inflammation are critical drivers in the progression from steatosis to steatohepatitis⁴⁶. Given the altered expression of TCF19 in MAFLD, we investigated its role in cell survival. MTT assay (Supplementary Fig. 24A, B) and FACS analysis (Fig. 9A, B) revealed a significant reduction in overall cell viability (Supplementary Fig. 24A, B) and induction in both early (Fig. 9B) and late (Fig. 9B) apoptotic cell death upon PA treatment in a TCF19 knockdown condition.

Fig. 9 — A, B Measurement of apoptotic cell death by FACS and quantification of early apoptotic and late apoptotic cell death (n = 4). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. Cellular (C) and Secretory (D) Lox activity upon PA treatment in the presence or absence of TCF19 or overexpression of the FLAG-TCF19 in HepG2 cells depleted of TCF19 (n = 5). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. E Lox activity in hepatic tissue of BSA_Control mice, PA-injected mice and PA injection in TCF19 ASO-injected mice (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. F Lox activity assay in hepatic tissue of control diet, MAFL diet, MAFL diet with TCF19 ASO and MASH diet-fed mice (n = 5). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. G, H Picrosirius-Red staining and quantification in hepatic tissue of BSA_Control mice, PA-injected mice and PA injection in TCF19 ASO-injected mice (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. I, J Picrosirius-Red staining and quantification in hepatic tissue of control diet, MAFL diet, MAFL diet with TCF19 ASO and MASH diet-fed mice (n = 5). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM. K, L Immunofluorescence image and quantification of collagen I and TCF19 in control, PA-treated, PA-treatment in TCF19 knockdown condition and PA-treatment upon ELOVL1 inhibition in multicellular tumour spheroid (MCTS). Each data point in the quantification graph (L) represents an individual spheroid (n = 3). One-way ANOVA was performed to analyse the p-value significance; the data are presented as mean value ± SEM.

Notably, the progression between MAS and MASH is accompanied by an accumulation of extracellular matrix (ECM) components, making the hepatic tissue fibrotic, which is the hallmark of steatohepatitis^47,48. Since we have observed an important role of TCF19 in preventing lipotoxicity-mediated cell death and hepatic inflammation, we next investigated the role of this dynamic transcription regulator in ECM stiffening leading to fibrosis. During MASH progression, the ECM components get post-translationally modified, contributing towards matrix stiffening⁴⁹. One of the well-known post-translational modifications of the matrix protein collagen is lysyl oxidation mediated by the Lox family enzymes⁵⁰. Analysis of the R2 genomic database demonstrated significant negative correlations between TCF19 mRNA levels and expression of different ECM regulatory genes involved in the maintenance of ECM composition (Lox, LoxL2, FN1), biosynthesis of collagen (COL1A2), Integrin signalling pathway (ITGA2, ITGB8) and TGFβ signalling pathway (TGFβ1, TGFβ2, TGFβ3) (Supplementary Fig. 24C–K) in MAFLD patients.

Next, we focused on understanding the contribution of TCF19 to the maintenance of ECM stiffness in PA-mediated metabolic stress. We measured the cellular and secretory Lox activity in PA-treated conditions, which showed a significant increase in the absence of TCF19 (Fig. 9C, D). Upon over-expressing TCF19, we could observe a reduction in the PA-mediated induction of Lox activity (Fig. 9C, D). The findings could be recapitulated in the primary hepatocytes and the two in vivo mouse models based on PA-injection and high-fat diet. Here, we observed that the lox activity was significantly elevated in the absence of TCF19 in the primary hepatocytes (Supplementary Fig. 25A), as well as both PA-treated and high-fat diet-fed mice models (Fig. 9E, F). To measure the fibrosis progression in mice tissues, we measured the total collagen deposition by Picrosirius red (PSR) staining in both the mice models and found elevated collagen deposition upon knocking down TCF19 under similar conditions (Fig. 9G–J). To understand the role of TCF19 in regulating the ECM deposition via modulation of the ELOVL1 expression, we subsequently knocked down TCF19 or inhibited the activity of ELOVL1 separately in PA-treated conditions and performed immunostaining of collagen and fibronectin in multicellular tumour spheroids (MCTS). Our results indicated that knocking down TCF19 or inhibiting the activity of ELOVL1 in PA-treated conditions significantly enhanced the deposition of both collagen and fibronectin (Fig. 9K, L and Supplementary Fig. 25B, C).

Taken together, we delineate an epigenetic mechanism where TCF19 plays a seminal role in curbing FFA-mediated hepatic stress that leads to a critical transition from steatosis to steatohepatitis as depicted in the model (Fig. 10). The mechanistic insights reveal that TCF19, in conjunction with CBP/p300, plays a crucial role in fatty acid chain elongation during lipotoxic stress. By augmenting fatty acid elongase and dehydratase enzymes, TCF19 facilitates long-chain monounsaturated fatty acid production that subsequently gets converted to di- and tri-glycerides that are stored as lipid droplets, effectively mitigating lipotoxicity-induced cell death and inflammatory responses. In the cells, FFAs also cause protein misfolding and augment ER stress, which could be partially rescued by chaperones responsible for protein refolding. The absence of TCF19 transcriptionally down-regulates the expression of these ‘protein refolding chaperones’, leading to the activation of cell death and inflammation. Thus, TCF19, by regulating ER stress machinery and fatty acid chain elongation process, acts as a gatekeeper preventing steatosis to steatohepatitis transition (Fig. 10). Hence, TCF19 could emerge as a promising transcription factor with therapeutic potential to mitigate the complex metabolic liver disorders by directly intervening in the disease progression mechanisms.

Fig. 10 — Created in BioRender. Das, C. (2026) https://BioRender.com/cclikgu.

Discussion

In this study, we have uncovered a novel regulatory mechanism linking lipid metabolism to transcriptional control through TCF19, providing new insights into the cellular response to lipid stress and its implications for MAFLD progression. A central finding of our study is the identification of a unique epigenetic mechanism by which TCF19 regulates fatty acid chain elongase expression in response to FFA treatment. We observed a reciprocal shift in the histone modification landscape, wherein H3K4 trimethylation occupancy decreases while H3K27 acetylation increases upon FFA treatment, at the gene promoters crucially regulating fatty acid chain elongation programme, driving di and triglyceride formation to be stored in the cells as the lipid droplets. This epigenetic switch steers metabolic genes to cope with the FFA-mediated cytotoxicity. The identification of CBP/p300 as TCF19-interacting partners provides a molecular basis for how TCF19 drives H3K27 acetylation, establishing it as a master regulator that integrates metabolic signals with chromatin transcription.

Through comprehensive lipidomic analysis and functional studies upon PA (16:0) treatment, we demonstrated that TCF19 knockdown significantly impacts long-chain fatty acid levels and cellular triglyceride content. Remarkably, similar treatment with SA (18:0) as well as OA (18:1 ∆9) in the absence of TCF19 led to a reduced production of chain elongated products. Transcriptomic analysis in parallel identified ELOVL1 and HACD3, key enzymes in the fatty acid elongation pathway, that are regulated by TCF19. This upregulation of the expression of the elongase promotes the conversion of palmitic acid into long-chain fatty acids, which are subsequently incorporated into triglycerides. The resulting triglyceride accumulation, observed both in vitro and in vivo, represents a critical adaptive response to waive off the FFA-induced cytotoxicity. By conversion of the excess FFAs into neutral lipid stored within lipid droplets, TCF19 effectively reduces the cellular pool of FFAs that would otherwise exert toxic effects, revealing that fatty acid chain elongation and triglyceride synthesis are tightly coordinated through TCF19-mediated transcriptional control to maintain cellular lipid homoeostasis under conditions of FFA overload.

The protective function of TCF19 extends to endoplasmic reticulum homoeostasis through two complementary mechanisms. First, by promoting triglyceride synthesis and lipid droplet production, TCF19 reduces the burden of FFAs that can disrupt ER function. Second, TCF19 directly regulates the transcription of PDIA4, a protein disulphide isomerase essential for protein refolding during FFA-triggered UPR. The observed changes in the ER organisation following TCF19 knockdown, coupled with alteration in the Calcium pool and increased accumulation of unfolded proteins, demonstrate that TCF19 plays a crucial role in maintaining ER homoeostasis under FFA-mediated stress conditions. This dual mechanism, reducing the lipotoxic insult while simultaneously enhancing the ER’s protein refolding capacity, positions TCF19 as a central coordinator linking lipid metabolism to proteostasis.

Beyond its role in metabolism and ER function, TCF19 plays a previously unrecognised role in modulating inflammatory response, suppressing hepatic immune activation and fibrosis. Notably, in the absence of TCF19, PA injections or MAFL-diet triggers lipotoxic cell death due to the accumulation of FFAs, releasing chemokines that recruit immune cells. Further, the innate immune signalling receptors are also activated, which leads to the release of pro-inflammatory cytokines. Our findings demonstrate that ELOVL1 gene regulation by TCF19 suppresses FFA-triggered PBMC invasion and migration. Remarkably, macrophage invasion in the liver was substantially heightened in the absence of TCF19. The correlations between TCF19 expression and inflammatory markers in MAFLD patients support this protective role. Thus, the TCF19-ELOVL1 axis promotes cell survival and reduces inflammation in the hepatic microenvironment, which has important implications in MAFLD progression.

The anti-inflammatory function of TCF19 has profound consequences for liver fibrosis development. Our study demonstrates that TCF19 suppresses total collagen deposition and Lox activity, thereby negatively regulating fibrosis. Obliterating TCF19 from the primary hepatocytes affects the expression of ELOVL1 and HACD3, translating into alterations in the Triglyceride pools and Lox activity. We further identify that reducing hepatocyte death via apoptosis and dampening inflammation, TCF19 limits the activation of hepatic stellate cells and ECM production. Thus, the epigenetic factor TCF19 emerges as a potential ECM regulator, although the intracellular signalling mechanisms linking TCF19 to fibrogenic pathways remain to be fully established. Through suppressing ECM stiffness, TCF19 prevents fibrosis, thereby blocking the advanced stages of hepatic metabolic dysfunction. Remarkably, shutting down TCF19 or inhibiting ELOVL1 expression in MCTS significantly affects the Collagen I deposition, indicating a convergence between TCF19 and the lipid chain elongase pathway.

The clinical relevance of our findings is supported by the analysis of TCF19 expression in human MAFLD patients, which reveals a dynamic role that evolves with disease stage. The progressive changes in TCF19 expression from healthy liver to steatosis and steatohepatitis, along with its correlations with fat content and inflammatory markers, suggest a potential role in disease progression. TCF19 expression in the early MAFLD stage has a protective role in mitigating lipotoxicity by channelling the excess fatty acids into triglyceride pools. However, as the disease progresses and the lipid burden becomes overwhelming, this protective mechanism becomes dysregulated. Thus, TCF19 promotes triglyceride synthesis as a strategic defence mechanism to reduce FFA toxicity-mediated ER stress, cell death, and immune activation, thereby promoting steatosis to protect the liver from steatohepatitis and fibrosis. This positions TCF19 as a gatekeeper in the steatosis-to-steatohepatitis transition.

Taken together, our results establish a comprehensive regulatory network in which TCF19 serves as a central hub connecting transcriptional regulation, lipid metabolism, ER homoeostasis, inflammation and fibrosis. This study demonstrates how a single transcription factor can orchestrate multiple layers of cellular defence against metabolic stress, connecting the transcriptome to the proteome and the metabolome in a manner that fundamentally determines cellular health and disease outcomes. Further, the study challenges the simplistic view of hepatic steatosis as a pathological condition and instead suggests that transcriptional control by the epigenetic factors can lead to liver triglyceride accumulation that can act as an adaptive and protective response when properly coordinated, suppressing the worst outcome of steatohepatitis.

Several questions remain to be addressed in future research. First, the temporal dynamics of TCF19 regulation during disease progression need better understanding. Second, the potential role of TCF19 in other metabolic tissues and its contribution to systemic metabolism requires investigation. Third, the intracellular signalling mechanisms linking TCF19 to ECM regulation need full elucidation. Finally, the therapeutic potential of targeting the TCF19 and prospectively extending the protective phase of steatosis and delaying the transition to steatohepatitis warrants further exploration.

Methods

Mammalian cell culture

All the experiments were done on HepG2 and Huh7 cells. All the cells were maintained at 37 °C and 5% (v/v) CO₂ incubator in complete Dulbecco’s Modified Eagle Media (DMEM) (Gibco, Invitrogen) supplemented with 5.5 mM glucose (Sigma), 10% foetal bovine serum (FBS) (Gibco, Invitrogen), 1% Antibiotic- Antimycotic (Gibco, Invitrogen), and 1% GlutaMAX (Gibco, Invitrogen).

PA-injected mice experiment

The mice experiment was done in the central animal house facility of IISER, Pune, India, according to the ethical guidelines (IAEC-approved protocol no. IISER_Pune/IAEC/2023_03/02) of IISER Pune. All the experimental mice were housed in an individually ventilated cage (IVC system) from Tecniplast, Italy and maintained under a 12–12 h of photoperiod at 22 °C ± 2 °C temperature with 50–60% relative humidity.

BSA-conjugated palmitic acid (10 mg/Kg body weight, with a concentration of 5 mM) injection through the tail vein was done in 6-week-old BALB/c mice twice a day for 7 days⁵¹. To knock down TCF19, antisense oligo (ASO) (AATTGAGAATCAGTGTGGCC) from AUB Biotech was injected at a 2-day interval at 10 mg per Kg body weight^52–54. An equivalent amount of BSA was injected into control mice. Then, the mice were sacrificed, and the liver tissue and blood serum were collected for further analysis.

High-fat diet-fed mice experiment

Four-week-old BALB/c mice were subdivided into four groups (control, MAFL, MAFL + TCF19ASO, MASH) randomly. The Control, MAFL and MASH mice were fed with chow diet (10% fat) (D12450K), high-fat diet (60% fat as palmitic acid) (D12492) and high-fat, high-fructose, high-cholesterol diet (40% fat as palmitic acid, 20% fructose and 2% cholesterol) (D09100310), respectively, for 3 months⁵⁵. The MAFL + TCF19ASO mice were fed with a high-fat diet (60% fat as palmitic acid) (D12492) for three months, and TCF19ASO (AATTGAGAATCAGTGTGGCC) injection (10 mg per Kg body weight) was given at every 2-day interval for the last month of the experiment tenure through the tail vein^52–54. Then, the mice were sacrificed, and the liver tissue and blood serum were collected for further analysis.

Primary hepatocytes isolation and culture

The primary hepatocyte was extracted from the liver of a 7-week-old BALB/c mouse by the perfusion technique. After collagenase digestion, the hepatic cell was washed with PBS and William’s E media supplemented with 10% FBS and antibiotics, and the viable hepatocyte was isolated from the other type of liver cells by Percoll gradient. The viable hepatocyte was counted and cultured in William’s E media supplemented with BSA, insulin, dexamethasone and antibiotics⁵⁶.

Free fatty acid treatment

At first, the concentration of FFAs, palmitic acid (PA) (Sigma, P9767), SA (Sigma, S475) and oleic acid (OA) (Sigma, O7501), was titrated, and cell viability was estimated by trypan blue staining (Supplementary Fig. 2A–C).

All subsequent experiments were performed with 500 µM of palmitic acid (PA), 500 µM of SA and 500 µM oleic acid (OA) for 16 h in a glucose-free and FBS-free DMEM media⁵⁷. First, FFAs were dissolved in 50% ethanol by heating at 65 °C water bath for 15 min to make a 150 mM stock solution. Then it was mixed with pre-heated (37 °C) fat-free BSA (10% w/v) solution (Sigma) at a final concentration of 20 mM and incubated at 37 °C for 1 h for BSA-fatty acid conjugation. The control cells were kept at equal amounts of 50% ethanol and 10% BSA, containing glucose-free and fat-free DMEM media⁵¹.

Chemical inhibitor treatment

To inhibit the activity of ELOVL1, HepG2 cells were treated with 200 nM of ELOVL1-IN-3 (MedChemExpress, HY-145272) for 24 h⁵⁸. To inhibit the activity of CBP/p300 and KDM5C, cells were treated with 5 µM of SGC-CBP30⁵⁹ (MedChemExpress, HY-15826) for 24 h and 10 µM of KDM5-C70⁶⁰ (MedChemExpress, HY-120400) for 60 h, respectively. To induce ER stress, HepG2 cells were treated with 0.5 µM, 1.0 µM and 1.5 µM of thapsigargin⁶¹ (TG) (MedChemExpress, HY-13433) for 12 h.

Single and multicellular tumour spheroid (MCTS) formation

The Huh7 spheroids were formed in a 6-well ultra-low attachment surface cell culture plate (Corning, 3471). Around 40,000 Huh7 cells were seeded in each well of a 6-well plate in 2 ml of 5.5 mM glucose DMEM media, and let the spheroid grow for 7 days. 1 ml of media was added on each alternative day.

The MCTS were formed using Huh7 and NIH3T3 cells in a 96-well ultra-low attachment plate (Thermo Scientific, 174925). A total of 2000 cells per well at a 3:1 ratio was seeded in 200 µl of DMEM F12 media (supplemented with EGF, FGF, insulin, BSA, B27) and cultured for 5 days for spheroid formation. For the maturation, the media was replaced with complete DMEM (supplemented with 10% FBS, Glutamax, non-essential amino acids and antibiotics) and cultured for 3 days before treating with palmitic acid^62–64.

Immunofluorescence staining of MCTS

The MCTS were fixed with 4% paraformaldehyde and washed with PBS. The permeabilization was done using 1% Triton X-100 and blocked with 5% BSA. The primary antibody binding was done overnight at 4 °C temperature and the fluorophore-conjugated secondary antibody binding was done at room temperature for 1 h. After washing, the MCTS were counterstained with DAPI and mounted on a glass slide. The imaging was done using a Nikon Confocal microscope⁶⁴.

FFPE block preparation and IHC of Spheroid

After palmitic acid treatment spheroid was fixed in a 10% neutral buffer formaldehyde solution for 10 min. Then it was washed with 1X PBS and taken in a Whatman filter paper (Cytiva, 1001-090). The filter paper was cut to contain the spheroid and embedded in parafilm. The paraffin section was cut in 8 µm thickness using a microtome and placed on a poly-L-lysine-coated glass slide. Then the section was deparaffinized at 65 °C temperature for 45 min, followed by two times Xyline wash for 5 min each and one-time absolute ethanol wash for 5 min. The section was hydrated with 90%, 80%, 70%, and 60% ethanol and water respectively. The antigen retrieval was done using Tris-EDTA (pH 9.0) buffer at 95 °C heating conditions for 30 min.

The IHC was done by using an Abcam IHC kit (ab64264) according to the manufacturer’s protocol. In brief, the section was blocked with hydrogen peroxide and 5% fat-free BSA, respectively and incubated with a primary antibody at 4 °C overnight, followed by a specific secondary antibody binding at room temperature for 1 h. The chromogenic colour was developed by using the DAB substrate (3,3′-diaminobenzidine) and mounted by using DPX (Distyrene Plasticizer Xylene). The Image was captured in an EVOS bright-field light microscope at 40× zoom⁶⁴.

FFPE block preparation and IHC of liver tissue

For IHC, the liver tissues were collected in 10% neutral buffer formalin solution. Then it was embedded in parafilm. The paraffin section was cut in 4 µm thickness using a microtome and placed on a poly-L-lysine-coated glass slide. Then the section was deparaffinized at 65 °C temperature for 60 min, followed by two times Xyline wash for 5 min each, followed by two times absolute ethanol wash for 5 min each. The section was hydrated with 90%, 80%, 70%, and 60% ethanol and water, respectively. The antigen retrieval was done by boiling the tissue in Tris-EDTA (pH 9.0) buffer for 15 min.

The IHC was done by using an Abcam IHC kit (ab64264) according to the manufacturer’s protocol. In brief, the section was blocked with hydrogen peroxide and 5% fat-free BAS, respectively and incubated with a primary antibody at room temperature for 1.5 h, followed by a specific secondary antibody at room temperature for 15 min. The chromogenic colour was developed by using the DAB substrate (3,3′-diaminobenzidine) and mounted by using DPX (Distyrene Plasticizer Xylene). The Image was captured in EVOS bright-field light microscope at 20× zoom.

IHC of MAFLD patient’s liver tissue

Tissue microarray (TMA) slides of Healthy control, steatosis, and steatohepatitis patients’ liver tissue were purchased from XenoTech (A BioIVT Company), Cambridge. The product number: TMA.NAS: lot 1810265 (https://www.xenotech.com/in-vitro-test-systems/tissue-samples/microarrays/tma-nas/) and TMA.NASH: lot 2210347 (https://www.xenotech.com/in-vitro-test-systems/tissue-samples/microarrays/tma-nash/). The ethical clearance was conducted by the company as stated ‘All specimens collected under IRB approval’, and the documents can be obtained from the company’s website.

For the IHC, the TMA slides were deparaffinized at 65 °C temperature for 45 min, followed by two times Xyline wash for 5 min each, followed by two times absolute ethanol wash for 5 min each. The section was hydrated with 90%, 80%, 70%, and 60% ethanol and water, respectively. The antigen retrieval was done by boiling the tissue in Tris-EDTA (pH 9.0) buffer for 15 min.

The IHC was done by using an Abcam IHC kit (ab64264) according to the manufacturer’s protocol. In brief, the section was blocked with hydrogen peroxide and 5% fat-free BAS, respectively and incubated with anti-TCF19 primary antibody (at 1:200 dilution in TBST) at 4 °C temperature for 12 h, followed by a specific secondary antibody at room temperature for 15 min. The chromogenic colour was developed by using the DAB substrate (3,3′-diaminobenzidine) and mounted by using DPX (Distyrene Plasticizer Xylene). The Image was captured in EVOS bright-field light microscope at 20× zoom.

Gene knockdown and overexpression

For TCF19 silencing, HepG2 and Huh7 cells were transfected with TCF19 shRNA plasmid construct (GCTGGAAGTTCCCACTATTAC) targeting the 3’ UTR and empty vector (PLKO1) plasmid construct using Lipofectamine 2000 (Invitrogen) in OptiMEM (Invitrogen) media following the manufacturer’s protocol.

For knocking down TCF19 in primary mouse hepatocytes, the cells were transfected with TCF19ASO (AATTGAGAATCAGTGTGGCC) from AUM Bioscience following the manufacturer’s protocol.

The N-terminal FLAG-tagged full-length TCF19 construct³⁰ was transfected to overexpress TCF19 using Lipofectamine 2000.

Microarray and RNA sequencing data reanalysis

The DEGs from the microarray data (GEO Accession ID GSE107471) of control and TCF19 knockdown HepG2 cells and RNA sequencing data of PA-treated HepG2 cells (GEO Accession ID GSE152091) were reanalysed for biological pathways³⁰.

ChIP sequencing data analysis

The ChIP sequencing data of H3K4me3 and H3K27ac from HepG2 cells and human liver samples were downloaded from Common Metabolic Diseases Genome Atlas (CMDGA) and visualised in IGV 2.16.1 using human GRCh38/hg38 as reference sequence.

Reanalysis of RNA-Seq data from NAFLD patient’s sample from R2 Genomics database

RNA sequencing data of NAFLD patients were analysed using the publicly available R2 Genomic database (GEO Accession ID GSE89632) (R2 internal identifier: ps_avgpres_gse89632geo63_ilmnht12v4r2w). The expression and correlation data were plotted using GraphPad Prism (8.4.2).

Biological pathways and gene ontology analysis

KEGG Pathway and Gene Ontology analysis of DEGs from TCF19 knockdown microarray data was done using the DAVID bioinformatic tool & ShinyGO 0.81 and Panther DB, respectively.

Immune migration and invasion assay

Peripheral blood mononuclear cells (PBMC) were isolated from healthy individual blood using HiSep LSM1077 (HiMedia). The collection of blood and isolation of PBMC was approved by the ethics committee of the Institute of Post Graduate Medical Education & Research (IPGME&R), Kolkata, India; approval number: Inst/IEC/2016/502. All participants signed an informed consent form before the collection of blood.

Cell media was collected and spun at 1500 × g for 10 min to remove the cell debris, and was added to the lower chamber of the trans-well plate (ThermoFisher Scientific), and the PBMC was seeded in incomplete DMEM media to the ECM matrix (Geltrex) coated upper chamber and incubated for 24 h at 37 °C and 5% CO₂ incubator. at 37 °C temperature. To measure the amount of invading PBMC, the media from the upper chamber was discarded carefully and fixed with 4% paraformaldehyde, followed by 2% crystal violet staining for 20 min. The image was captured by using a brightfield light microscope (EVOS) at ×20 magnification and was quantified in ImageJ.

The migration assay was done in the same way, except the trans-well plate was coated with diluted Geltrex. The number of migrated cells into the lower chamber was counted by using the automated cell counter (Countess 3, Invitrogen).

Flow cytometry for cell death assay

The apoptotic cell death was measured by Annexin V staining using Annexin V-FITC Apoptosis Staining Kit (ab14085) following the manufacturer’s protocol. The total number of viable cells, apoptotic cells and necrotic cells was quantified by using FACS (BD Biosciences).

Immunofluorescence and RER-SER quantification

For immunofluorescence experiments, cells were seeded on UV-treated coverslips (18 mm). After the treatment, cells were fixed with 4% paraformaldehyde and permeabilised with 0.4% NP-40 for 60 min and blocked with 5% BSA (w/v) dissolved in PBST for 60 min. Primary antibody binding was done at room temperature for 2 h followed by fluorophore-conjugated secondary antibody binding for 45 min. The coverslips were mounted on glass slides by using Glycerol Mounting Medium with DAPI and DABCO (Abcam, ab188804). The immunofluorescence imaging was done at 60× zoom (Nikon Confocal microscope).

Sec61β and RNT4 were stained for RER and SER quantification, respectively. The intensity of Sec61β and RNT4 was quantified by using ImageJ software, and the data were represented by GraphPad Prism software.

Western blotting

Whole-cell lysate and Co-Immunoprecipitated samples were run in 7.5% and 11.5% SDS-PAGE, followed by western blotting. The whole cell was lysed in RIPA buffer (50 mM Tris pH 8.0, 150 mM NaCl, 0.1% SDS, 0.5% sodium deoxycholate, 1% NP-40, 1 mM EDTA pH 8.0) supplemented with protease inhibitor (Roche 04693116001) and phosphatase inhibitor (Roche 4906845001) and sonicated at 50 Hz for 4 min in ice. SDS-PAGE was run at a constant volt (100 V) followed by western blotting using a nitrocellulose membrane at a constant current (300 mM) for 45 min at 4 °C. After blocking the membrane with 5% skimmed milk (w/v) or 5% BSA (w/v) dissolved in 1X TBST and kept at 4 °C overnight for respective primary antibody binding (Supplementary Table 1). Secondary antibody binding was done for 3 h at room temperature in 5% skimmed milk (w/v) dissolved in 1× TBST. The chemiluminescence images were captured using Azure Biosystem ChemiDoc.

Enzyme-linked immunosorbent assay (ELISA)

The liver tissue (100–200 mg) was washed in PBS and homogenised in RIPA buffer, followed by sonication. The insoluble fraction was removed by centrifugation at 7000 × g for 10 min.

The 96-well plate was coated with 7 µg of the respective primary antibody (diluted in 10 mM phosphate buffer, pH 7.4) (Supplementary Table 1) overnight at 4 °C. After washing and blocking, the antigen binding was done at room temperature for 3 h. After washing with PBST, the plate was incubated with 2 µg of primary antibody (diluted in 10 mM phosphate buffer, pH 7.4) for 2 h at room temperature. The fluorescence tag (Alexa Fluor) conjugated secondary antibody was added and incubated at room temperature for 1 h. After washing with PBST and PBS, 100 µl of PBS was added to each well and fluorescence was measured at the appropriate Ex/Em. The fluorescence intensity was normalised with GAPDH and plotted using GraphPad Prism.

Co-immunoprecipitation

The cell was lysed in RIPA buffer (50 mM Tris pH 8.0, 150 mM NaCl, 0.1% SDS, 0.5% Sodium Deoxycholate, 1% NP-40, 1 mM EDTA pH 8.0) supplemented with protease inhibitor and phosphatase inhibitor and sonicated at 50 Hz for 4 min in ice. Normal sheep serum was used for pre-clearing the lysate and the IP was set overnight using 500 µg pre-cleared protein (for both IP and IgG) at 4 °C. 5% BSA (w/v) (dissolved in RIPA) blocked Dynabead was used for bead binding (2 h at 4 °C). The protein was eluted from the bead by heating at 95 °C temperature for 6-8 min in 30 µl RIPA buffer.

Chromatin immunoprecipitation

ChIP assay was performed using our previously published standard protocol^28,65. In brief, cells were harvested after cross-linking with 1% formaldehyde treatment for 10 min and neutralising with 125 mM Glycine for 10 min. The nuclear pellet was isolated after lysing with Farhan’s Lysis Buffer (5 mM PIPES pH 8.0, 85 mM KCl, 0.5% NP-40) supplemented with 1 mM DTT and protease inhibitors. The nuclear pellet was lysed with Lysis Buffer (1% SDS, 10 mM EDTA pH 8.0, 50 mM Tris pH 8.0) supplemented with 1 mM DTT and protease inhibitors. Sonication at 50 Hz was done several times to get 300–500 bp of DNA fragments, and the lysate was precleared with normal sheep serum and Dynabeads. The desired amount of lysate was taken to set the immunoprecipitation for overnight at 4 °C. After bead binding the bead was washed with low salt buffer (20 mM Tris pH 8.0, 2 mM EDTA pH 8.0, 125 mM NaCl, 0.05% SDS, 1% Triton X-100), High Salt Buffer (20 mM Tris pH 8.0, 2 mM EDTA pH 8.0, 500 mM NaCl, 0.05% SDS, 1% Triton X-100), Lithium Chloride Buffer (10 mM Tris pH 8.0, 1 mM EDTA pH 8.0, 250 mM LiCl, 1% NP-40, 1% Sodium Deoxycholate) and TE Buffer (10 mM Tris pH 8.0, 1 mM EDTA pH 8.0). After washing the bead was dissolved in TE buffer and 1 h RNAse treatment and Proteinase K treatment were done at 37 °C and 55 °C, respectively, followed by overnight decrosslinking at 65 °C. The DNA was isolated by the phenol-chloroform precipitation method and qRT-PCR was done with respective ChIP primer (Supplementary Table 3) to quantify the enrichment. The ELOVL1 ChIP primer sites are ELOVL1-H3k4me3 (Region 1): chr1: 43,368,551-43,368,570; ELOVL1-H3K27ac (Region 2): chr1: 43,368,611-43,368,630. The HACD3 ChIP primer sites are HACD3-H3k4me3 (Region 1): chr15: 65,530,215-65,530,234; HACD3-H3K27ac (Region 2): chr15:65,530,093-65,530,114. All the experiments were repeated three times.

RNA isolation and qRT-PCR

After all the treatments, HepG2 cells and liver tissues were harvested in 1 ml TriZol (Ambion). The total mRNA was isolated and precipitated by using chloroform and isopropanol, respectively. The quality and concentration were measured by NanoDrop (Thermo Fisher Scientific) and Qubit 4 Fluorometer (Invitrogen). Two micrograms mRNA was used for preparing cDNA using RevertAid First Strand cDNA synthesis kit (Thermo Fisher Scientific) in a 96-well Thermal Cycler (Applied Biosystem).

BioRad SYBR-Green mix was used for quantitative real-time PCR (qRT-PCR) with respective primers (Supplementary Tables 2 and 4) in 96-well plates using Applied Biosystem Step-One Plus Real-Time PCR System in triplicate. All the experiments were repeated three times.

Triglyceride production assay

The total amount of Triglyceride was measured by using a Triglyceride production assay kit (Abcam, 65336). After all the treatment, 2 × 10⁶ viable HepG2 cells were harvested by trypsinisation and lysed in 5% NP-40 (v/v). Then the solution was heated at 95 °C for 5 min and cooled down. The cycle was repeated several times until the solution became transparent at room temperature. The total amount of triglyceride was measured according to the manufacturer’s protocol.

Lipid droplet staining and quantification

Oil Red O (Sigma) stock solution was prepared in 99% isopropanol at a 3:1 ratio. Then the stock solution was mixed with 60% isopropanol at a 3:2 ratio to make the Oil red O working solution. Cells were seeded in a 6-well plate (for imaging) and a 24-well plate (for quantification). After discarding the media cells were washed with 1× PBS, fixed with 10% formalin (Sigma) for 30 min and washed with 60% isopropanol for 5 min. Then cells were stained with 60% Oil red O working solution for 30 min and washed with 1x PBS and imaged. For quantification, after staining, the Oil red O stain was dissolved in 100% isopropanol and absorbance was measured at 510 nm in a 96-well plate reader.

Extracellular flux (ECAR & OCR) analysis

Extracellular Flux was measured using an XFp Extracellular Flux Analyser (Agelant, Seahorse Bioscience)²⁸. Cells were seeded in 8-well Extracellular Flux Analysis plates and grown in complete DMEM cell culture media overnight at 37 °C in 5% CO₂ incubator. The Extracellular Flux Analysis cartridge was kept in water at a 37 °C incubator without CO₂ overnight for hydration. On the day of the experiment, the cells were washed thrice with Extracellular Flux Analysis media and 180 µl of Extracellular Flux Analysis media was added (for ECAR XF Base Medium Minimal DMEM, 102353-100, supplemented with 1 mM Sodium pyruvate, 2 mM Glutamax, adjusted pH 7.4 and for OCR XF Base Medium Minimal DMEM, 102353-100, supplemented with 1 mM Sodium pyruvate, 2 mM Glutamax, 10 mM glucose, adjusted pH 7.4) and incubated at 37 °C incubator without CO₂ for 1.5 h. The water in the cartridge was replaced with an extracellular flux analysis calibrant and incubated at 37 °C in a CO₂-free incubator for 30 min. The cartridge was loaded with respective inhibitors for ECAR and OCR, and a run was done. For OCR 1 µM oligomycin, 1.5 µM FCCP and 1 µM rotenone were loaded in ports A, B and C, respectively. For ECAR 2 mM glucose, 1 µM oligomycin and 1 mM 2-DG were loaded in ports A, B and C, respectively. The data were analysed by Wave Desktop 2.6.3 software (powered by Agilent technology) and GraphPad Prism 8.4.2.

Peroxisome, mitochondria and endoplasmic reticulum purification

HepG2 cells were harvested by trypsinisation and were washed with cold 1× PBS and taken in equal numbers (around 2 × 10⁷). Then the cells were dissolved in three times cell volume of 1× peroxisomal extraction buffer (PEB) (5 mM MOPS pH 7.65, 250 mM sucrose, 1 mM EDTA and 0.1% ethanol) and homogenised. Then the intact cells and nucleus were separated by centrifugation at 1000 g and 2000 g, respectively for 10 min. Then crude peroxisomal fraction (CPF) was precipitated by centrifugation at 25,000 × g for 20 min at 4 °C.

Then the CPF was dissolved in 1.2 ml of 1× PEB, 1.69 ml of 60% (w/v) iodixanol and 1.61 ml of 1× dilution buffer (5 mM MOPS, pH 8.0, 0.1% ethanol and 1 mM EDTA) to get 22.5% iodixanol-containing CPF. 27.5% and 20% iodixanol solution was also prepared by diluting the 60% iodixanol solution in 1× dilution buffer. An 8 ml density gradient column was prepared in an 8 ml ultracentrifuge tube by placing 4 ml of 22.5% CPE between 27.5% and 20% iodixanol solution. The column was centrifuged at 100,000 × g for 2 h, and 300 µl of each fraction was collected in a 1.5 ml Eppendorf tube. A western blot was run with 15 µl of each fraction to check the purity of the peroxisomal, mitochondrial and ER fractions.

Peroxisomal β-oxidation measurement

Peroxisomal β-oxidation was measured by following a previously published protocol⁶⁶. The fraction containing the pure peroxisome was used for peroxisomal β-oxidation measurement. A reaction mix was prepared with 20 mM β-NAD + , 0.33 M DTT, 1.5% (w/v) BSA, 2% (v/v) triton-X 100, 10 mM Coenzyme A, 1 mM FAD, 100 mM KCN, 5 mM C12-CoA. The reaction was set in a 96-well plate with 10 µl of fractions and a final volume of 200 µl was achieved with 50 mM tris-HCl (pH 8.0). The absorbance was measured at 340 nm in a 96-well plate reader after 5 min of incubation at 37 °C. A blank set of reactions, containing no peroxisomal fraction, was also set to subtract the background absorbance.

Mitochondrial β-oxidation measurement

Mitochondrial beta-oxidation was measured with little modification of the previously published protocol⁶⁷ and a schematic representation shows the workflow of the overall experimental procedure (Supplementary Fig. 4D, E). An equal number of control and PA-treated HepG2 cells were used to purify mitochondria. Twenty microliters of three different mitochondrial fractions were used for the measurement. 20 µl of control and PA-treated mitochondrial fraction, 167.7 µl of reaction buffer (130 mM KCl, 10 mM HEPES pH 7.9, 0.1 mM EGTA pH 8.0; pH was adjusted to 7.2) and 12.3 µl of master mix (0.5 mM K3Fe(CN)6, 1 mM ADP, 1 mM K2HPO4, 1 mM KCN, 0.1 mg/ml Cytochrome C, 1.5 mg/ml BSA) was taken in a 96well plate for the reaction wells and 187.7 µl of reaction buffer and 12.3 µl of master mix for blank well and absorbance was measured in a 96well plate reader at 420 nm. To block the electron transfer through the electron transport chain of mitochondria 30 µg/ml of Rotenone (dissolved in DMSO) was added in each well and absorbance was measured at 420 nm three times at 4-min intervals to measure the conversion of ferricyanide to ferrocyanide that is not because of beta-oxidation. To initiate the beta-oxidation, palmitoyl-L-carnitine (20 µM) was added in each well and absorbance was measured at 420 nm three times at 4-min intervals to measure the conversion of ferricyanide to ferrocyanide mediated by beta-oxidation. Lower absorbance indicates higher production of ferrocyanide from ferricyanide (high absorbance at 420 nm), thus a higher rate of beta-oxidation. To induce the rate of beta-oxidation further 10 mM oxaloacetate was added in each well and absorbance was measured at 420 nm three times at 4-min intervals. The absorbance of the blank wells was subtracted from the reaction well to measure the conversion of ferricyanide to ferrocyanide.

β-oxidation measurement by the extracellular flux analyser

β-oxidation from HepG2 cells was measured using an XFp Extracellular Flux Analyser (Agelant, Seahorse Bioscience)²⁸. HepG2 cells were seeded in 8-well Extracellular Flux Analysis plates and grown in complete DMEM cell culture media overnight at 37 °C in 5% CO₂ incubator. The Extracellular Flux Analysis cartridge was kept in water at a 37 °C incubator without CO₂ overnight for hydration. On the day of the experiment, the cells were washed thrice with extracellular flux analysis media and 180 µl of Extracellular Flux Analysis media was added (XF Base Medium Minimal DMEM, 102353-100, supplemented with 1 mM Sodium pyruvate, 2 mM Glutamax, 10 mM glucose, adjusted pH 7.4) and incubated at 37 °C incubator without CO₂ for 1 h. The water in the cartridge was replaced with an Extracellular Flux Analysis calibrant and incubated at 37 °C in a CO₂-free incubator for 30 min. The cartridge was loaded with inhibitors 2 µM Etomoxir (Port A), 1 µM oligomycin (Port B), 1.5 µM FCCP (Port C) and 1 µM rotenone (Port D). Then the OCR measurement was done, and the etomoxir-responsive OCR was calculated by Wave Desktop 2.6.3 software (powered by Agilent technology) and plotted using GraphPad Prism 8.4.2.

Lox activity assay

Lox activity assay from hepatic tissue, cell lysate and cell media (secretory lox) were measured by using the Lysyl Oxidase Activity Assay Kit (Abcam, ab112139) following the manufacturer’s protocol. The hepatic tissue was homogenised in detergent-free buffer and the reading was normalised with initial tissue weight. The cells were lysed in PBS by sonication and normalised with protein concentration. The media was concentrated before performing the assay and was normalised with concentrating factor and cellular protein concentration. The fluorescence was measured at Ex 540 nm and Em 590 nm wavelength.

Picrosirius red staining

For collagen staining the tissue sections were stained with PSR stain (Polyscience, 24901B-250) following the manufacturer’s protocol. Briefly, 4 µm FFPE tissue section was deparaffinised at 65 °C for 30 min followed by xylene, 100%, 90%, 80%, 70% alcohol and water wash for 5 min each. Then the tissue sections were incubated in Solution A for 2 min and washed in deionized water. After that, it was stained with Solution B for 60 min and Solution C for 2 min and washed in 70% ethanol and 100% ethanol for 45 s each. The images were captured in EVOS bright-field light microscope at 20× zoom and were quantified by using ImageJ.

IP/MS

HepG2 cells were harvested by trypsinisation and washed with PBS, and the nucleus was collected by centrifugation at 13,000 × g at 4 °C for 10 min after lysing the cytosol in buffer containing 10 mM Tris-HCl, pH 7.5, 2 mM MgCl₂, 3 mM CaCl₂, and 0.3 M Sucrose. The nucleus was lysed in 0.65% NP-40. After pre-clearing the nuclear lysate with IgG antibody, the IP was set with anti-TCF19 antibody (Santa Cruz, sc390923), followed by dynabead-mediated pull-down. The bead-bound protein complex was washed with buffer containing 20 mM HEPES, pH 7.9, 200 mM NaCl, 1.5 mM MgCl₂, 0.2 mM EDTA, 1% NP-40, 1 mM DTT, and 1x PIC and eluted with 28% Glycerol, 10% SDS, 120 mM Tris, pH 6.8, and 50 mM DTT containing buffer. The protein complex was detected by LC-MS/MS at UT Southwestern Medical Centre’s Proteomics Core following the standard protocol⁶⁸. The abundance of the complex components represents the ratio of abundance in IP and abundance in the negative control (IgG).

UPR measurement by TPE-MI staining

The total amount of unfolded protein was measured by using Tetraphenylethene maleimide (TPE-MI dye) (MedChemExpress, HY-143218)⁴². After the treatment, the cell media was discarded and kept in 50 µm TPE-MI in PBS for 45 min at 37 °C CO₂ incubator. Then the cells were washed with PBS and lysed in RIPA buffer and the fluorescence was measured at Ex/Em 350/470 and normalised with total protein concentration.

Measurement of the store-operated calcium entry

HepG2 cells were cultured and treated in a 96-well plate. After treatment, cells were washed with calcium-free PBS and incubated with Fluo-8 AM (0.1 mg/ml) for 45 min at 37 °C. After washing with calcium-free PBS, the cells were treated with 4 µM thapsigargin for 20 min, followed by 3 mM EGTA treatment. To measure the calcium intake, 2 mM Ca²⁺ was added, and fluorescence was measured at Ex/Em 340/380 nm⁶⁹.

Lipid extraction profiling and C13 isotope labelled experiment

An equal number (4 × 10⁶) of viable Control, PA, TCF19 knockdown, PA-treated TCF19 knockdown cells, SA-treated, OA-treated, SA-treated TCF19 knockdown and OA-treated TCF19 knockdown cells and homogenised hepatic tissue of control, PA-injected and TCF19-ASO plus PA-injected mice were resuspended in 0.5 mL DPBS and made up to a 2 mL mixture of 2:1:1 chloroform (CHCl3): methanol (MeOH): PBS. For semi-quantitative analysis of lipids, 1 nmol of C15:0 MAG (Synthesised by us as per previously described schemes)⁷⁰ and 1 nmol of pentadecanoic acid (C15:0 FFA) (Sigma Aldrich, #P6125) were added as internal standards for positive and negative mode analytes, respectively. The mixture was vortexed vigorously and centrifuged at 2800 × g for 10 min at room temperature. The bottom organic phase was collected carefully in a separate glass vial. To enhance the extraction of phospholipids from the aqueous layer, 50 μL of formic acid (MS grade, Honeywell, #94318) was added, and this mixture was vigorously mixed. One milliliter (1 mL) of chloroform was added, and this mixture was vortexed and centrifuged at the conditions described previously. The organic phases were pooled and dried in a nitrogen evaporator.

The dried lipid extracts were resuspended in 200 μL of 2:1 CHCl3: MeOH, and 10 μL was injected into an Agilent 6545 LC-QTOF (quadrupole-time-of-flight) LC-MS/MS for semi-quantitative analysis using high-resolution auto MS-MS methods and chromatography techniques. A Gemini 5U C-18 column (Phenomenex) coupled with a Gemini guard column (Phenomenex, 4 × 3 mm, Phenomenex security cartridge) was used for LC separation. The solvents used for negative ion mode were: buffer A: 95:5 H2O: MeOH + 0.1% ammonium hydroxide and buffer B: 60:35:5 Isopropanol (iPrOH): MeOH: H2O + 0.1% ammonium hydroxide. The 0.1% ammonium hydroxide in each buffer was replaced by 0.1% Formic acid + 10 mM ammonium formate for positive ion mode runs. All LC-MS runs were 60 min, starting with 0.3 mL/min 100% buffer A for 5 min, 0.5 mL/min linear gradient to 100% buffer B over 40 min, 0.5 mL/min 100% buffer B for 10 min, and equilibration with 0.5 mL/min 100% buffer A for 5 min.

The following settings were used for the ESI-MS analysis: drying gas and sheath gas temperature: 320 °C, drying gas and sheath gas flow rate: 10 L/min, fragmentor voltage: 150 V, capillary voltage: 4000 V, nebuliser (ion source gas) pressure: 45 psi and nozzle voltage: 1000 V. The top 4 precursor masses in each cycle were subjected to further fragmentation to generate characteristic MS2 masses.

For analysis, an in-house lipid library was employed in the form of a Personal Compound Database Library (PCDL) comprising lipid classes such as fatty acyls, glycerolipids, and glycerophospholipids. Peaks were first validated by comparing their MS1 masses to the database (<10 ppm error) and then by comparing their MS2 masses (wherever applicable) to characteristic masses for each species manually⁷¹. For the C-13 isotope labelling experiment, we made a list comprising masses corresponding to different potential labelled lipids, and all such peaks detected (<10 ppm error) were manually integrated and quantified. Relative retention times were compared (across chain lengths, based on hydrophobicity) to further validate the accuracy of these annotations.

Quantification of all lipid species involved the normalisation of areas under the curve to the corresponding internal standard area and further normalisation to the total cell count, protein concentration or tissue weight.

MTT assay

After the treatment cells were washed with 1× PBS and 50 µg/ml MTT (from a 10 mg/ml stock solution) was added in a phenol red-free DMEM media and incubated for 4 h in a 37 °C 5% CO₂ incubator. The media was discarded and the formazan was dissolved in DMSO. The absorbance was measured in a 96-well plate reader at 570 nm and 650 nm wavelength.

Statistical analysis

All the statistical analyses were done by GraphPad Prism software.

Ordinary One-way ANOVA (Gaussian distribution, Dunnett Test and 95% confidence interval), was performed to calculate the statistical p-value significance (*p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001 ns non-significant where p > 0.05) of data sets having more than two variables. ‘n’ represents the number of biological replicates.

Two-way ANOVA (Tukey Test and 95% confidence interval) was performed to calculate the statistical p-value significance (*p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001 ns non-significant where p > 0.05) of data sets having more than one distinct independent variable. ‘n’ represents the number of biological replicates.

An unpaired Student’s t-test was performed (two-tailed, 95% confidence interval), was performed to calculate the statistical p-value significance (*p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001 ns non-significant where p > 0.05) of data sets having two variables. ‘n’ represents the number of biological replicates.

All the experiments were repeated at least three times (Biological Replicates), and the data were represented as the arithmetic mean (Central Tendency) with an error bar representing the standard error of the mean (SEM) for scattered plots (for sample size less than 10) and for the Box-whisker plot (for sample size more than 10), the box represents the middle 50% of the data, and the central line represents the median (central tendency). The Whisker ranges from the box to the minimum and maximum value.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Supplementary information

Supplementary Information^{(4.5MB, pdf)}

Reporting Summary^{(78.9KB, pdf)}

Transparent Peer Review file^{(14.3MB, pdf)}

Source data

Source Data^{(9MB, zip)}

Acknowledgements

We acknowledge Dr. Siddhartha Roy, IICB, Kolkata, India, for his critical inputs on the manuscript. We also acknowledge Dr. Payel Mondal, Mr. Antariksh Venkataramanan and Ms. Indrakshi Banerjee for their assistance during this study. We acknowledge the staff of the animal house at IISER, Pune, India, for their technical support with the animal experiments. C.D. acknowledges ‘S. Ramachandran National Bioscience Award for Career Development 2019’ (BT/HRD-NBA-NWB/38/2019-20), BT/PR52628/MED/30/2553/2024 by the Department of Biotechnology, ‘SwarnaJayanti Fellowship’ (DST/SJF/LSA-02/2017-18), ‘Core Research Grant’ (CRG/2022/005052) by the Department of Science and Technology and ‘Basic and Applied Research in Biophysics and Material Science’ (RSI 4002) and ‘Basic and Applied Research in Biophysical Sciences’ (RSI 4008) by the Department of Atomic Energy Govt. of India for funding this study. S.S.K. acknowledges ‘SwarnaJayanti Fellowship’ (SB/SJF/2021-22/01), Department of Science and Technology, Government of India, for funding this study.

Author contributions

C.D. conceived the study and designed experiments. A.M., A.C. and S.S.K. designed and performed the experiments and analysed the data. S.N. and V.S. were also engaged in performing the experiments. CD and AM were involved in manuscript writing. All the authors approved the final version of the manuscript.

Peer review

Peer review information

Nature Communications thanks Dawn Davis, who co-reviewed with Joseph Blumer, and the other anonymous reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

Data availability

The TCF19 Knockdown microarray data in HepG2 cells are available in GSE107471 [10.1074/jbc.M117.786863], and the analysed data can be found in the Source Data File. RNA-Seq data for Palmitic acid treatment are available in GSE152091 [10.1038/s42003-023-04710-8], and the analysed data can be found in the Source Data File. The RNA-Seq data of NAFLD patient samples are available in GSE89632 [10.1002/hep.27695], and the analysed data can be found in the Source Data File. The ChIP-Seq data are available in TSTFF590972, TSTFF056736, DFF27OUVM, and DFF952ODU. The raw proteomic data (IP/MS) to identify the TCF19 interacting partners are not available due to data privacy, and can be obtained on reasonable request to the corresponding author and the processed data are available in the Source Data File. The raw Lipidomic data generated in this study have been deposited in the MetaboLights database under accession code REQ20260213217069. The raw lipidomic data are available under restricted access for data protection, and access can be obtained on reasonable request to the corresponding author, and the processed data are available in the Source Data File. Source data are provided with this paper.

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.

Supplementary information

The online version contains supplementary material available at 10.1038/s41467-026-72138-9.

References

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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 Information^{(4.5MB, pdf)}

Reporting Summary^{(78.9KB, pdf)}

Transparent Peer Review file^{(14.3MB, pdf)}

Source Data^{(9MB, zip)}

Data Availability Statement

[CR1] 1.Wong, V. W. S., Ekstedt, M., Wong, G. L. H. & Hagström, H. Changing epidemiology, global trends and implications for outcomes of NAFLD. J. Hepatol.79, 842–852 (2023). [DOI] [PubMed] [Google Scholar]

[CR2] 2.Girish, V. & John, S. Metabolic dysfunction-associated steatotic liver disease (MΑSLD). StatPearlshttps://www.ncbi.nlm.nih.gov/books/NBK541033/ (2025). [PubMed]

[CR3] 3.Farrell, G. C., Haczeyni, F. & Chitturi, S. Pathogenesis of NASH: how metabolic complications of overnutrition favour lipotoxicity and pro-inflammatory fatty liver disease. Adv. Exp. Med. Biol.1061, 19–44 (2018). [DOI] [PubMed] [Google Scholar]

[CR4] 4.Molecular mechanisms of metabolic associated fatty liver disease (MAFLD): functional analysis of lipid metabolism pathways | Clinical Science | Portland Press. https://portlandpress.com/clinsci/article/136/18/1347/231842/Molecular-mechanisms-of-metabolic-associated-fatty. [DOI] [PMC free article] [PubMed]

[CR5] 5.Listenberger, L. L. et al. Triglyceride accumulation protects against fatty acid-induced lipotoxicity. Proc. Natl. Acad. Sci. USA100, 3077–3082 (2003). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR6] 6.Yamaguchi, K. et al. Inhibiting triglyceride synthesis improves hepatic steatosis but exacerbates liver damage and fibrosis in obese mice with nonalcoholic steatohepatitis. Hepatology45, 1366–1374 (2007). [DOI] [PubMed] [Google Scholar]

[CR7] 7.Rowland, L. A. et al. De novo lipogenesis fuels adipocyte autophagosome and lysosome membrane dynamics. Nat. Commun.14, 1–14 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR8] 8.Worthmann, A. et al. Fatty acid synthesis suppresses dietary polyunsaturated fatty acid use. Nat. Commun.15, 1–13 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR9] 9.Sanders, F. W. B. & Griffin, J. L. De novo lipogenesis in the liver in health and disease: more than just a shunting yard for glucose. Biol. Rev.91, 452–468 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR10] 10.Murru, E., Manca, C., Carta, G. & Banni, S. Impact of dietary palmitic acid on lipid metabolism. Front. Nutr.9, 861664 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR11] 11.Carta, G., Murru, E., Banni, S. & Manca, C. Palmitic acid: physiological role, metabolism and nutritional implications. Front. Physiol.8, 306122 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR12] 12.Asciolla, J. J. & Resh, M. D. Hedgehog acyltransferase promotes uptake of palmitoyl-CoA across the endoplasmic reticulum membrane. Cell Rep.29, 4608–4619.e4 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR13] 13.Cook, H. W. & McMaster, C. R. Chapter 7 fatty acid desaturation and chain elongation in eukaryotes. New Compr. Biochem.36, 181–204 (2002). [Google Scholar]

[CR14] 14.Sawai, M. et al. The 3-hydroxyacyl-CoA dehydratases HACD1 and HACD2 exhibit functional redundancy and are active in a wide range of fatty acid elongation pathways. J. Biol. Chem.292, 15538–15551 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR15] 15.Wang, X., Yu, H., Gao, R., Liu, M. & Xie, W. A comprehensive review of the family of very-long-chain fatty acid elongases: structure, function, and implications in physiology and pathology. Eur. J. Med. Res.28, 1–12 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR16] 16.Nie, L. et al. The structural basis of fatty acid elongation by the ELOVL elongases. Nat. Struct. Mol. Biol.28, 512–520 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR17] 17.Ferrero, E., Vaz, F. M., Cheillan, D., Brusco, A. & Marelli, C. The ELOVL proteins: very and ultra long-chain fatty acids at the crossroads between metabolic and neurodegenerative disorders. Mol. Genet. Metab.144, 109050 (2025). [DOI] [PubMed] [Google Scholar]

[CR18] 18.Ofman, R. et al. The role of ELOVL1 in very long-chain fatty acid homeostasis and X-linked adrenoleukodystrophy. EMBO Mol. Med.2, 90–97 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR19] 19.Siddiqui, A. J. et al. Therapeutic role of ELOVL in neurological diseases. ACS Omega8, 9764–9774 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR20] 20.Bosma, M. et al. Sequestration of fatty acids in triglycerides prevents endoplasmic reticulum stress in an in vitro model of cardiomyocyte lipotoxicity. Biochim. Biophys. Acta1841, 1648–1655 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR21] 21.Yu, J. et al. Phosphorylation switches protein disulfide isomerase activity to maintain proteostasis and attenuate ER stress. EMBO J.39, EMBJ2019103841 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR22] 22.Hasnain, S. Z., Lourie, R., Das, I., Chen, A. C. H. & McGuckin, M. A. The interplay between endoplasmic reticulum stress and inflammation. Immunol. Cell Biol.90, 260–270 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR23] 23.Zhang, K. & Kaufman, R. J. From endoplasmic-reticulum stress to the inflammatory response. Nature454, 455–462 (2008). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR24] 24.Di Conza, G., Ho, P. C., Cubillos-Ruiz, J. R. & Huang, S. C. C. Control of immune cell function by the unfolded protein response. Nat. Rev. Immunol.23, 546–562 (2023). [DOI] [PubMed] [Google Scholar]

[CR25] 25.Obaseki, E., Adebayo, D., Bandyopadhyay, S. & Hariri, H. Lipid droplets and fatty acid-induced lipotoxicity: in a nutshell. FEBS Lett.598, 1207–1214 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR26] 26.Dong, Z. et al. Palmitic acid stimulates NLRP3 inflammasome activation through TLR4-NF-κB signal pathway in hepatic stellate cells. Ann. Transl. Med.8, 168–168 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

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PERMALINK

Transcription factor 19 modulates fatty acid elongation and unfolded protein response to attenuate palmitic acid-induced hepatic dysfunction

Atanu Mondal

Arnab Chakraborty

Sandhik Nandi

Vipin Singh

Siddhesh S Kamat

Chandrima Das

Abstract

Introduction

Results

TCF19 plays a critical role in fatty acid chain elongation upon free fatty acid-mediated stress induction

Fig. 1. TCF19 promotes fatty acid chain elongation upon palmitic acid treatment in cells and mice hepatic tissue.

Fig. 2. TCF19 promotes triglyceride production and lipid droplet accumulation.

Free fatty acid treatment induces the formation of diglyceride, triglyceride and phospholipids of very long chain mono-unsaturated fatty acids and promotes lipid droplet formation under the regulation of TCF19

TCF19 functions as a key transcriptional regulator of lipid metabolism in response to palmitic acid

Fig. 3. TCF19 regulates the transcription of different lipid metabolic genes upon palmitic acid treatment.

TCF19 regulates epigenetic interplay between histone H3K4 trimethylation and H3K27 Acetylation for lipid metabolic gene expression

Fig. 4. TCF19 promotes the histone H3K27ac to the promoter of fatty acid chain elongase ELOVL1 and HACD3, enhancing its transcription upon palmitic acid treatment.

TCF19 recruits CBP/p300 to regulate lipid metabolic gene expression

Fig. 5. TCF19 interacts with CBP/p300 and promotes its recruitment to the promoter of ELOVL1 and HACD3 gene.

TCF19 regulates ER stress response through transcriptional control of PDIA4 in concert with p300/CBP

Fig. 6. TCF19 regulates the transcription of ER stress-responsive gene PDIA4, regulating misfolded protein load upon PA-mediated ER stress condition.

TCF19 expression is altered in MAFLD progression and regulates hepatic inflammation

Fig. 7. TCF19 gets upregulated in simple steatosis conditions and down-regulated upon fibrosis in mice model and human patients.

Fig. 8. Knocking down TCF19 promotes hepatic inflammation in the PA-treated condition.

TCF19 promotes cell survival, suppressing extracellular matrix deposition and consequent liver fibrosis

Fig. 9. Knocking down TCF19 promotes apoptotic cell death and hepatic fibrosis in PA-treated conditions.

Fig. 10. Graphical representation of the TCF19-mediated overall regulatory mechanism of steatosis and steatohepatitis.

Discussion

Methods

Mammalian cell culture

PA-injected mice experiment

High-fat diet-fed mice experiment

Primary hepatocytes isolation and culture

Free fatty acid treatment

Chemical inhibitor treatment

Single and multicellular tumour spheroid (MCTS) formation

Immunofluorescence staining of MCTS

FFPE block preparation and IHC of Spheroid

FFPE block preparation and IHC of liver tissue

IHC of MAFLD patient’s liver tissue

Gene knockdown and overexpression

Microarray and RNA sequencing data reanalysis

ChIP sequencing data analysis

Reanalysis of RNA-Seq data from NAFLD patient’s sample from R2 Genomics database

Biological pathways and gene ontology analysis

Immune migration and invasion assay

Flow cytometry for cell death assay

Immunofluorescence and RER-SER quantification

Western blotting

Enzyme-linked immunosorbent assay (ELISA)

Co-immunoprecipitation

Chromatin immunoprecipitation

RNA isolation and qRT-PCR

Triglyceride production assay

Lipid droplet staining and quantification

Extracellular flux (ECAR & OCR) analysis

Peroxisome, mitochondria and endoplasmic reticulum purification

Peroxisomal β-oxidation measurement

Mitochondrial β-oxidation measurement

β-oxidation measurement by the extracellular flux analyser

Lox activity assay

Picrosirius red staining

IP/MS

UPR measurement by TPE-MI staining

Measurement of the store-operated calcium entry

Lipid extraction profiling and C13 isotope labelled experiment

MTT assay

Statistical analysis

Reporting summary

Supplementary information

Source data

Acknowledgements

Author contributions

Peer review

Peer review information

Data availability

Competing interests

Footnotes