Abstract
The pathogenesis of nonalcoholic steatohepatitis (NASH), a severe stage of nonalcoholic fatty liver disease, is complex and implicates multiple cell interactions. However, therapies for NASH that target multiple cell interactions are still lacking. Melatonin (MEL) alleviates NASH with mechanisms not yet fully understood. Thus, we herein investigate the effects of MEL on key cell types involved in NASH, including hepatocytes, macrophages, and stellate cells. In a mouse NASH model with feeding of a methionine and choline-deficient (MCD) diet, MEL administration suppressed lipid accumulation and peroxidation, improved insulin sensitivity, and attenuated inflammation and fibrogenesis in the liver. Specifically, MEL reduced proinflammatory cytokine expression and inflammatory signal activation and attenuated CD11C+CD206– M1-like macrophage polarization in the liver of NASH mice. The reduction of proinflammatory response by MEL was also observed in the lipopolysaccharide-stimulated Raw264.7 cells. Additionally, MEL increased liver fatty acid β-oxidation, leading to reduced lipid accumulation, and restored the oleate-loaded primary hepatocytes. Finally, MEL attenuated hepatic stellate cell (HSC) activation and fibrogenesis in the liver of MCD-fed mice and in LX-2 human HSCs. In conclusion, MEL acts on multiple cell types in the liver to mitigate NASH-associated phenotypes, supporting MEL or its analog as potential treatment for NASH.
Introduction
Nonalcoholic steatohepatitis (NASH), the invasive form of nonalcoholic fatty liver disease (NAFLD), is emerging as a major cause of liver fibrosis, cirrhosis, and even hepatocellular carcinoma (Cusi 2012). However, the underlying pathogenesis of NASH is not fully understood. The widely accepted ‘multiple-parallel-hit hypothesis’ indicates that NASH development involves multiple cell types within the liver (Buzzetti et al. 2016, Magee et al. 2016). This hypothesis suggests that insulin resistance and fatty acid flux within the liver lead to hepatocyte damage and mitochondrial dysfunction. Hepatocyte-derived reactive oxygen species (ROS) trigger oxidative stress and proinflammatory cytokine excretion, subsequently activating immune cells (macrophages and T lymphocytes) and hepatic stellate cells (HSCs), resulting in a chronic inflammatory response and fibrogenesis in the liver (Mansouri et al. 2018, Cai et al. 2019).
Currently, treatment options for NASH are limited. The involvement of several different cell types in the liver and their interplay suggest that NASH treatment and prevention may require targeting multiple key cell types. A number of pharmacological approaches such as metformin (Nair et al. 2004), vitamin E (Sanyal et al. 2010), ursodeoxycholic acid (Musso et al. 2010), and cenicriviroc (Friedman et al. 2018) are promising therapeutic agents for the treatment of NASH. However, these agents are usually insufficient to limit inflammation and fibrosis in the liver of patients with NASH. Thus, a potential therapy with minimal adverse effects and significant efficacy is urgently needed.
Melatonin (MEL) is a neuron hormone produced in and excreted from the pineal gland at night (Claustrat & Leston 2015). The most well-known function of MEL is to regulate the circadian rhythm (Hardeland 2017). It also exhibits strong antioxidant and anti-inflammatory effects (Cipolla-Neto et al. 2014). MEL is also critically involved in glucose and lipid homeostasis and contributes to suppress the progression of NAFLD (Pakravan et al. 2017, Rong et al. 2019, Stacchiotti et al. 2019). It attenuates body weight gain and hepatic steatosis in patients with NAFLD and alleviates obesity-related liver abnormalities and the proinflammatory response by preventing tumor necrosis factor (TNF) receptor-associated factor-mediated apoptosis signal-regulating kinase 1 deubiquitination in the liver of mice (Li et al. 2019). It improves hepatic steatosis by reducing NLRP3 inflammasome formation in db/db mice (Yu et al. 2021) and alleviates NAFLD by regulating noncoding microRNA (Stacchiotti et al. 2019). However, its effects on NAFLD are targeted at the liver tissue. Thus, whether and how MEL directly regulates multiple key cell types involved in the progression of NASH remain to be further elucidated.
In this study, we used a methionine and choline-deficient (MCD) diet-induced NASH mouse model and three cell lines representing macrophages, hepatocytes, and HSCs to investigate how MEL attenuates NASH-associated phenotypes including lipid accumulation and peroxidation, insulin sensitivity, oxidative stress, inflammation, and fibrogenesis in the liver. Unexpectedly, we found that MEL targets multiple crucial cell types in the liver to prevent NASH.
Materials and methods
Mice and experimental design
Seven-week-old male C57BL/6 mice were obtained from SLAC Laboratory Animal Co. Ltd. (Shanghai, China). All mice were kept in a specific pathogen-free animal facility with standard conditions (temperature, 23 ± 2°C; humidity, 45 ± 5%) and a 12/12 h light–darkness cycle. Water and food were given ad libitum. After 1 week of adaptation, the mice were randomly divided into the following four feeding groups: normal control diet (NC, n = 6), with 10% of calories from fat; NC with 20 mg/kg MEL (NC + MEL, n = 6); MCD diet (n = 6, A02082002B, Research Diets, New Brunswick, NJ, USA); and MCD with 20 mg/kg MEL (MCD + MEL, n = 6). Before dark, MEL (#M5250, Sigma-Aldrich) was administered by intraperitoneal (i.p.) injection, and the dose was chosen according to previous mouse studies (Zhou et al. 2018a, b , Miguel et al. 2022). In brief, MEL was dissolved in anhydrous alcohol to prepare a stock 0.5% (v/v) MEL solution. Before lights off, mice were intraperitoneally injected daily with 200 μL preparation containing 20 mg/kg MEL in phosphate-buffered saline (PBS) for 4 weeks; animals in control groups were administered a vehicle comprised of 0.5% ethanol in PBS solution.
All animal procedures were approved by the laboratory animal ethical committee of Wenzhou Medical University (wydw2019–0229; Wenzhou, China).
Histological analyses and immunohistochemistry
Liver tissues were fixed in 10% formalin, embedded in paraffin, sectioned, and stained with hematoxylin and eosin (H&E), Azan, and immunostained for extracellular growth factor-like module-containing mucin-like hormone receptor-like 1 (F4/80), α-smooth muscle actin (α-SMA), integrin, alpha X (CD11C), or recombinant cluster of differentiation (CD163) as previously described (Zhuge et al. 2016). The images were captured using a Nikon Eclipse Ci Microscope, and four to five fields of each section were randomly selected to quantify the positive area percentage using the ImageJ software; then the mean analysis was performed.
Fluorescence-activated cell sorting analysis
Fluorescence-activated cell sorting (FACS) was used to assess hepatic macrophage accumulation and polarization. Cells were separated from the left lobe of the liver, as previously described (Ni et al. 2015). After blocking with Fc-Blocker (BD Biosciences, Franklin Lakes, NJ, USA), the cells were incubated with fluorochrome-conjugated antibodies (Supplemental Table 1, see section on supplementary materials given at the end of this article). Flow cytometry and data acquisition were performed using the FACSAria II flow cytometer (BD Biosciences), and data analyses were performed using FlowJo software (Tree Star, Ashland, OR, USA).
Biochemical analyses and glucose tolerance test
Plasma parameters and hepatic lipids were measured as previously described (Ota et al. 2008). A glucose tolerance test was performed as previously described (Xu et al. 2018). For assaying insulin signaling in vivo, four mice were selected from each cohort and intraperitoneally injected with 10 U/kg human insulin.
Detection of gene expression
Total RNA was extracted from the liver tissues and cells using TRIzol reagent (Invitrogen) and reverse transcribed into cDNA by using a SuperScriptTM II Reverse Transcriptase kit (Invitrogen) according to the manufacturer’s instructions. Quantitative real-time PCR was performed using Power SYBR Green PCR master mix (Applied Biosystems) with the CFX96 Touch Real-Time PCR Detection System (Bio-Rad Laboratories, Inc.). mRNA levels were normalized to 18S (in vivo) or β-actin (in vitro) mRNA, and fold change was calculated using ΔΔCt method. The primers employed for qPCR are listed in Supplementary Table 2.
Western blotting analysis
The protein was isolated from the liver tissues with RIPA lysis buffer (Millipore), and the concentration was determined using a BCA Protein Assay Kit (Pierce, Bonn, Germany). The lysates were blotted overnight at 4°C with primary antibodies (Supplementary Table 3) and then incubated with appropriate secondary antibodies (Cell Signalling Technology, Danvers, MA, USA). The proteins were visualized by chemiluminescence (Millipore) and imaged using a gel imaging system (ChemiDoc™ XRS; Bio-Rad). Pixel intensities of the immunoreactive bands were quantified using Quantity One software (ver. 4.5.2; Bio-Rad). β-actin, GAPDH, or α-tubulin were used as loading control. Protein levels were normalized to their total protein or loading control protein.
Cell culture and treatments
The primary hepatocytes were isolated from male C57BL/6J mice (8–12 weeks old) and cultured in Dulbecco’s modified Eagle’s medium (DMEM, Gibco) supplemented with 10% fetal bovine serum (FBS, Gibco). After serum starvation for 6 h, primary hepatocytes were treated with 400 μM oleic acid (OA, Sigma-Aldrich) and MEL (0, 0.1, 1, or 10 μM) for 24 h.
RAW264.7 (TIB-71; ATCC) cells, a murine monocytic cell line, were cultured in DMEM supplemented with 10% FBS in a humidified atmosphere of 5% CO2 at 37°C until the cells reached 90% confluence. RAW264.7 cells were then serum starved for 6 h and incubated with 100 ng/mL lipopolysaccharide (LPS, Sigma-Aldrich) in the presence of 0, 1, 10, or 100 μM MEL for 16 h.
LX-2 human stellate cells (SCC064, Sigma-Aldrich) were maintained in DMEM containing 10% FBS. After 6 h of fasting, the stellate cells were co-cultured with 10 ng/mL transforming growth factor β (TGF-β; R&D Systems) and MEL (0.1, 1, or 10 μM) for 16 h.
Determination of cellular ROS
Intracellular ROS production was determined by flow cytometry as previously described (Salimi et al. 2017). Data were analyzed using FlowJo software (Ashland, OR, USA).
Statistical analyses
Results are expressed as mean ±s.e.of the mean. For experiments with only two groups, the two-tailed Student’s t-test was used for statistical comparisons. Differences between the mean values of in vivo data were determined by two-way ANOVA with a Tukey multiple comparison test. The in vitro data were evaluated using the Shapiro–Wilk test, and the differences between the mean values were examined by one-way ANOVA with a Sidak multiple comparison or Kruskal–Wallis multiple comparison test. P < 0.05 was considered statistically significant. All calculations were performed with GraphPad Prism (ver. 8.0, GraphPad).
Results
MEL suppresses fat accumulation, inflammation, fibrosis, and insulin resistance in MCD-fed mice
The MCD diet is characterized by a lack of methionine and choline, which impairs mitochondrial fatty acid β-oxidation, resulting in hepatic lipid accumulation, oxidative stress, and inflammatory signaling activation, culminating in liver damage (Farrell et al. 2019). After 4 weeks of MCD feeding in the current study, hepatic lipid accumulation, transaminase content, macrophage infiltration, and fibrosis were markedly increased in MCD mice (Fig. 1A-E), suggesting that the NASH model was successfully established. On the other hand, MCD can damage liver parenchymal cells (Machado et al. 2015), resulting in lower plasma triglycerides (TGs) and glucose levels, which were also confirmed in this study (Table 1).
MEL prevents MCD-induced steatohepatitis. (A) Representative oil red O- and H&E-stained liver sections. Scale bars: 100 μm. (B) Levels of hepatic TG, TC, and NEFA. (C) Levels of plasma ALT and AST. (D) Representative F4/80-stained liver sections. Scale bars: 100 μm. (E) Representative Azan-stained liver sections. Scale bars: 100 μm. (F) Hepatic mRNA expression of genes for fatty acid β-oxidation (PPARα and Lcad). (G) Immunoblots and quantification of liver PPARα and nuclear SREBP-1. Data are presented as means ± s.e.m., n = 5–6. Differences were assessed by two-way ANOVA using Tukey multiple comparison test. **P < 0.01 vs NC, #P < 0.05, ##P < 0.01 vs saline. A full color version of this figure is available at https://doi.org/10.1530/JME-22-0075.
Citation: Journal of Molecular Endocrinology 70, 1; 10.1530/JME-22-0075
Effects of MEL on metabolic parameters in mice with NASH at 4 weeks of treatment.
| NC | NC + MEL | MCD | MCD+ MEL | |
|---|---|---|---|---|
| Body weight (g) | 23.7 ± 0.54 | 23.6 ± 0.51 | 14.3 ± 0.51b | 13.9 ± 0.55 |
| Liver weight (g) | 0.94 ± 0.04 | 0.84 ± 0.02a | 0.54 ± 0.03a | 0.44 ± 0.01c |
| Food intake (g/day/mouse) | 4.78 ± 0.21 | 5.73 ± 0.23a | 2.40 ± 0.12b | 2.71 ± 0.20c |
| Blood glucose (fasting, mmol/L) | 6.35 ± 0.24 | 5.65 ± 0.11a | 3.92 ± 0.23b | 4.02 ± 0.23 |
| Blood glucose (fed, mmol/L) | 7.48 ± 0.20 | 7.63 ± 0.51 | 5.23 ± 0.23b | 5.02 ± 0.14 |
| Plasma TG (mmol/L) | 0.78 ± 0.09 | 1.05 ± 0.08 | 1.02 ± 0.13 | 0.82 ± 0.15 |
| Plasma TC (mmol/L) | 3.15 ± 0.24 | 2.98 ± 0.50 | 2.06 ± 0.13b | 1.53 ± 0.08c |
| Plasma SOD (U/mL) | 53.5 ± 3.12 | 49.1 ± 2.56 | 35.1 ± 2.21b | 43.4 ± 0.11c |
| Plasma MDA (nmol/mL) | 3.31 ± 0.12 | 2.65 ± 0.56 | 5.31 ± 0.34a | 3.48 ± 0.61c |
| Plasma 8-OHdG (nM) | 17.5 ± 3.0 | 26.6 ± 3.9 | 26.2 ± 3.1a | 20.2 ± 0.43c |
Glucose, TG, and TC levels were measured in the plasma of mice fasting for 16 h. Data are presented as mean ± s.e.m. Differences were assessed by two-way ANOVA using Tukey multiple comparison test. n = 5–6, aP < 0.05, bP < 0.01 vs NC, cP < 0.05.
TG, triglyceride; TC, total cholesterol; SOD, superoxide dismutase; MDA, malondialdehyde; 8-OHdG, 8-hydroxy-2 deoxyguanosine.
To evaluate the impact of MEL on MCD-induced NASH, C57BL/6J mice were fed an MCD with or without 20 mg/kg MEL for 4 weeks. MEL treatment markedly decreased the liver weight in both NC- and MCD-fed conditions, independent of body weight and food intake (Table 1). MEL also attenuated MCD-induced hepatic fat accumulation and steatosis as assessed by oil red O and H&E staining (Fig. 1A). Consistently, MEL significantly attenuated the increase in liver TGs, total cholesterol (TC) and non-esterified fatty acid (NEFA), and plasma TC levels caused by the MCD diet (Fig. 1B and Table 1). Simultaneously, MEL also directly attenuated the lipid storage in the primary hepatocytes (Supplementary Fig. 1A). In addition, MEL significantly decreased the plasma levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), indicating that MEL alleviated MCD-induced liver damage (Fig. 1C). Moreover, administration of MEL attenuated F4/80+ macrophage recruitment and infiltration in the liver of MCD-fed mice (Fig. 1D). Azan staining of liver sections showed that MEL reduced the MCD-induced increase in collagen content (Fig. 1E), suggesting a reduction in fibrosis level. As expected, MEL increased the mRNA expression of fatty acid β-oxidation genes, including peroxisome proliferator-activated receptor α (Pparα) and long-chain acyl-CoA dehydrogenase (Lcad) (Fig. 1F) and the protein level of PPARα (Fig. 1G), but decreased the sterol regulatory element-binding protein (SREBP-1) (Fig. 1G), indicating that MEL modulated lipid metabolism in NASH mice.
NASH is often accompanied with glucose intolerance and insulin resistance (Ota et al. 2007). Here, MEL supplementation attenuated glucose intolerance in MCD-fed mice (Fig. 2A), while plasma levels of glucose were not affected under both fed and fasting conditions (Table 1). Moreover, it reversed hyperinsulinemia in the fed and fasting states of the MCD-fed mice (Fig. 2B). Finally, we found that it increased insulin-stimulated levels of the tyrosine phosphorylated insulin receptor β subunit and serine phosphorylated Akt, suggesting improved insulin signaling sensitivity in MCD-induced NASH mice (Fig. 2C).
MEL alleviates glucose intolerance and insulin sensitivity in MCD diet-fed mice. (A) Glucose tolerance test (GTT). **P < 0.01 vs NC, #P < 0.05 vs MCD. (B) Levels of plasma insulin. (C) Immunoblots of proteins involved in insulin signaling. Data are presented as means ± s.e.m., n = 5–6. Differences were assessed by two-way ANOVA using Tukey multiple comparison test. *P < 0.05, **P < 0.01 vs NC, #P < 0.05, ##P < 0.01 vs saline.
Citation: Journal of Molecular Endocrinology 70, 1; 10.1530/JME-22-0075
MEL attenuates inflammation by suppressing the activation of macrophages
The progression of NASH is accompanied by the chronic inflammation and activation of macrophages/Kupffer cells in the liver (Cai et al. 2019). In this study, the induction of proinflammatory cytokines (Tnfα) and C-C motif chemokines (Ccl5 and Ccr2) in the liver of MCD-fed mice was significantly decreased in MEL-treated mice (Fig. 3A). Consistently, MEL markedly reduced the plasma levels of TNFα and LPS in mice with NASH (Fig. 3B). These changes were accompanied by the attenuation of levels of inducible nitric oxide synthase protein and a decrease in the protein levels of phosphorylated nuclear factor kappa B (p-NF-κB) p65, p38 mitogen-activated protein kinase (MAPK), c-Jun N-terminal kinase (JNK), and extracellular signal-related kinase (ERK) in the liver of NASH mice (Fig. 3C and Supplementary Fig. 2A). In addition, MEL also decreased the protein levels of p-eIF2α and C/EBP homologous protein, which contribute to endoplasmic reticulum stress (Fig. 3C and Supplementary Fig. 2A). In accordance with attenuated hepatic inflammation, 8-OHdG, a marker of oxidized DNA damage, was significantly reduced by MEL in both the circulation and liver (Table 1 and Supplementary Fig. 2B). In addition, increased lipid peroxidation, assessed by malondialdehyde in the liver and plasma of MCD mice, was suppressed by MEL (Table 1 and Supplementary Fig. 2B), whereas superoxide dismutase (SOD), an important antioxidant enzyme, was increased in MCD + MEL mice (Table 1). These findings occurred in association with the decreased mRNA expression of NADPH oxidase subunits (NAPDH oxidase 2 and p22phox) and increased the mRNA levels of antioxidant stress genes (catalase and Sod) in the liver of MCD + MEL mice (Supplementary Fig. 2C and D). Taken together, these data indicate that MEL supplementation suppresses the NASH-related inflammation, oxidative stress, and plasma endotoxin.
MEL attenuates inflammation and M1-like macrophages polarization in liver. (A) mRNA expression of genes for cytokine (Tnfα) and chemokines (Ccl5 and Ccr2). (B) Levels of plasma TNFα and LPS. (C) Immunoblots of protein involved in proinflammatory signaling and ER-stress. (D) Immunostaining of liver sections for CD11C and CD163, Scale bar: 100 μm. (E) Representative plot of total macrophages (F4/80+CD11b+) in the liver. (F) Representative plot of M1-type (CD11c+CD206-) and M2-type (CD11c-CD206+) macrophages in the liver. (G) Percentages of total macrophages, M1- and M2-type macrophages, and the M1/M2 macrophage ratios in the liver. Data are presented as means ± s.e.m., n = 5–6. Differences of mean values of A–D were assessed by two-way ANOVA using Tukey multiple comparison test. Differences of mean values of E and F were assessed by two-tailed Student’s t-test. *P < 0.05 vs NC, #P < 0.05 vs saline. A full color version of this figure is available at https://doi.org/10.1530/JME-22-0075.
Citation: Journal of Molecular Endocrinology 70, 1; 10.1530/JME-22-0075
The striking mitigation in hepatic inflammation in MCD + MEL mice prompted us to further determine the liver macrophages homeostasis. The immunostaining revealed that the M1/M2 macrophage status of NC and NC + MEL mice was comparable (Fig. 3D). However, MEL administration decreased the M1 macrophage marker CD11c+ cells and increased the M2 marker CD163+ cells in the MCD-fed mice (Fig. 3D). Concurrently, the data of FACS showed that MEL supplementation markedly decreased the percentage of total liver macrophages (CD11b+F4/80+) and proinflammatory M1-like macrophages (CD11c+CD206–), while the anti-inflammatory M2-like (CD11c−CD206+) macrophages remained unchanged in the livers of MCD and MCD + MEL mice, resulting in a decrease in M1/M2 ratio (i.e. the number of M1-like macrophages divided by the number of M2-like macrophages) (Fig. 3E, F and G). Consistently, the cluster of differentiation 11c (Cd11c), a marker of M1-like macrophages, was downregulated by MEL supplementation, whereas the expression levels of M2 macrophage markers (Cd206, mannose receptor C type 2, and Cd163) were increased (Supplementary Fig. 2E and F).
To test whether MEL directly affects macrophages to suppress inflammation, we used LPS (100 ng/mL) to induce macrophage activation and inflammatory situation in Raw264.7 cells, a mouse macrophage cell line, and co-treated the cells with MEL (0–10 μM). The results showed that MEL dose dependently decreased the expression of inflammatory cytokines (Tnfα and Il-1β) and chemokines (Mcp1 and Ccl5) in LPS-stimulated cells (Fig. 4A). Excessive ROS production leads to M1 polarization and attenuates M2 polarization in LPS-treated macrophages by activating the MAPK and NF-κB pathways (Furukawa et al. 2004, Dey et al. 2014). We found that the increase in ROS production in macrophages by LPS stimulation was decreased by MEL treatment (Fig. 4B) with an increase in SOD activity (Fig. 4C). These results were concurrent with the decreased mRNA level of NADPH oxidase subunits and increased mRNA level of antioxidant stress genes in LPS-induced macrophages (Fig. 4D and E). Consistently, MEL significantly prevented the LPS-stimulated activation of NF-κB and MAPK pathways, with decreased phosphorylation of NF-κB, p38 MAPK, JNK, and ERK (Fig. 4F). These findings in Raw264.7 macrophages indicate that MEL may suppress inflammatory signaling via a direct cell-autonomous mechanism. Similar to macrophages, MEL also attenuated the oleate-induced ROS generation in hepatic parenchymal cells (Supplementary Fig. 3A).
MEL directly inhibits oxidative stress and inflammation in vitro. (A) mRNA expression of LPS-stimulated proinflammatory genes in Raw264.7 cells. (B) Detection of ROS by flow cytometry in Raw264.7 cells. (C) SOD activity in Raw264.7 cells. (D) mRNA expression of NADPH oxidase subunit in RAW264.7 cells. (E) mRNA expression of anti-oxidative stress-related genes in RAW264.7 cells. (F) Immunoblots of proinflammatory proteins in Raw264.7 cells. n = 5–6. Differences were assessed by one-way ANOVA using Sidak multiple comparison test. *P < 0.05, **P < 0.01, vs mock, #P < 0.05, ##P < 0.01, vs LPS-induced cells. A full color version of this figure is available at https://doi.org/10.1530/JME-22-0075.
Citation: Journal of Molecular Endocrinology 70, 1; 10.1530/JME-22-0075
MEL reduces liver fibrosis by attenuating HSC activation in NASH mice
Activation of HSCs is a key process in liver fibrogenesis (Friedman 2008). Thus, the impact of MEL on HSC activation in MCD-fed mice was evaluated in this study. Consistent with the attenuation of liver fibrosis, MEL markedly attenuated hepatic levels of hydroxyproline, a marker of collagen fiber content (Fig. 5A). Furthermore, the numbers of α-SMA+ HSCs increased in MCD mice and decreased in MCD + MEL mice (Fig. 5B). These results were further verified by immunoblotting, namely the protein levels of α-SMA were also decreased in MCD + MEL mice (Fig. 5C). In addition, MEL administration also decreased the mRNA expression of the involved fibrogenesis genes, including Tgf-β1, α-Sma, collagen type I, alpha 1 (Col1α1), and plasminogen activator inhibitor-1 (Pai-1) (Fig. 5D). Finally, MEL decreased mRNA levels of TGF-β-stimulated fibrogenesis genes (α-SMA and COL1α1), in dose- and time-dependent manners, in the LX-2 HSC line (Fig. 5E and F).
MEL attenuates hepatic fibrosis in NASH mice. (A) Hydroxyproline contents in the liver. (B) Representative α-SMA-stained liver sections. Scale bars: 100 μm. (C) Immunoblot of α-SMA in the liver. (D) mRNA expression of fibrogenesis-related genes in the liver. Data are presented as means ± s.e.m., n = 5–6. Differences were assessed by two-way ANOVA using Tukey multiple comparison test. *P < 0.05, **P < 0.01 vs NC, #P < 0.05, ##P < 0.01, vs MCD. (E) mRNA expression of fibrogenesis-related genes in LX-2 cells. n = 5–6, Data are expressed as means ± s.e.m. Differences were assessed by one-way ANOVA using Sidak multiple comparison test. **P < 0.01 vs mock, #P < 0.05, ##P < 0.01 vs TGF-β1-treated condition. (F) Time course of mRNA expression of fibrogenesis-related genes in LX-2 cells. n = 5–6, Data are expressed as means ± s.e.m. Differences of mean values of F were assessed by two-tailed Student’s t-test. *P < 0.01 vs TGF-β1-treated condition. A full color version of this figure is available at https://doi.org/10.1530/JME-22-0075.
Citation: Journal of Molecular Endocrinology 70, 1; 10.1530/JME-22-0075
Discussion
We demonstrated that supplementation with MEL suppressed the progression of NASH by regulating multiple key cell types in the liver. In particular, MEL prevented macrophage infiltration and M1-type activation, improved hepatocyte lipid metabolism, and reduced HSC activation, thereby mitigating hepatic steatosis, inflammation, and fibrosis, and ultimately preventing progression of MCD diet-induced NASH (Fig. 6). In addition, our in vitro cell line studies further suggested that MEL may mitigate NASH by acting on multiple cells, including parenchymal cells and nonparenchymal cells.
Schematic representation of the beneficial effects of MEL on the progression of NASH. MCD diet leads to hepatocyte damage and mitochondrial dysfunction involving excessive ROS production driven by lipotoxic metabolites, which trigger oxidative stress and inflammatory signaling response, leading to macrophages and other innate immune cells direct recruitment and activation. Activated macrophages (e.g. M1 macrophages) and damaged hepatocytes deliver a large number of proinflammatory cytokines, such as TNFα, which cause liver inflammation. HSCs are subsequently activated by oxidative stress and inflammatory cytokines and produce excessive extracellular matrix, leading to progressive fibrosis. MEL prevents ROS production by regulating hepatocyte mitochondrial dysfunction and subsequently prevents activation of macrophages and stellate cells, resulting in attenuation of hepatic inflammation and fibrosis. Overall, MEL prevents the progression of NASH by targeting hepatocyte, liver macrophage, and stellate cells. A full color version of this figure is available at https://doi.org/10.1530/JME-22-0075.
Citation: Journal of Molecular Endocrinology 70, 1; 10.1530/JME-22-0075
Chronic inflammation caused by hepatic M1-like macrophage-derived ROS, cytokines, and chemokines in NASH aggravates lipogenesis by suppressing insulin signaling and activation of SREBP-1 (Zhao & Saltiel 2020). Absence of M1 liver macrophages improves insulin sensitivity and attenuates hepatic lipid deposition in obese mice (Patsouris et al. 2008), whereas the reduction of M2 macrophages predisposes normal mice to insulin resistance (Odegaard et al. 2007, Odegaard et al. 2008). Hepatic M2 macrophage polarization protects against NAFLD by increasing M1 macrophage apoptosis (Wan et al. 2014). Thus, the reprogramming of liver macrophage polarization, particularly promoting the M2-dominant shift, is crucial in the targeted therapy of macrophages and has the prospect of being applied to clinical studies. Indeed, we previously reported that antioxidants, including astaxanthin and lycopene, attenuate diet-induced NASH by regulating hepatic macrophage/Kupffer cell polarization (Ni et al. 2015, 2020). Unsurprisingly, MEL as a well-known antioxidant causes a reciprocal decrease in the proportion of M1-type macrophages, leading to improved insulin sensitivity and inflammation in mice with NASH. To the best of our knowledge, this is the first study on the effects of MEL on macrophage homeostasis in a dietary model of NASH.
Fatty acid peroxidation in the fatty liver causes cellular oxidative stresses, which induce an innate immune response and fibrogenesis by activating Kupffer cells and HSCs in the liver (Buzzetti et al. 2016). β-oxidation with fatty acid as the substrate in mitochondria is the most effective manner of energy generation in metabolic tissues such as the liver, heart, and muscle (Houten et al. 2016), which can resist lipid peroxidation (Van Wyngene et al. 2020). PPARα is an essential enzyme for glucagon-mediated fatty acid oxidation (Francque et al. 2015). PPARα regulates the transcription of genes related to peroxisomal and mitochondrial oxidation, fatty acid transport, and hepatic glucose production. Importantly, MEL increased the expression of PPARα and other genes involved in fatty acid oxidation-related in metabolic tissues of obese mice, resulting in increased fatty acid oxidation and lipolysis, and attenuated the development of obesity (Xu et al. 2022). Thus, the elevation of PPARα in MCD + MEL mice may contribute to exhaustion of TGs and attenuation of NASH.
In addition, PPARα negatively regulates chronic inflammation through NF-κB and activator protein 1 (AP-1) inflammatory signaling and attenuates insulin resistance and NASH (Pawlak et al. 2015). PPARα expression is already detectable in monocytes, and it increases as monocytes differentiate into macrophages (Chinetti et al. 1998). Indeed, macrophage itself also expressed PPARα and regulates fatty acid metabolism and inflammation in mouse model (Chinetti et al. 2000, Babaev et al. 2007). Enhancing PPARα drives macrophages toward an M2 profile, markedly inhibiting the M1 phenotype (Penas et al. 2015). Therefore, MEL suppressed the activation of macrophages and M1 polarization and attenuated hepatic inflammation in NASH mice, at least in part, via an increase in PPARα.
Transdifferentiation of resting HSCs into hyperproliferative myofibroblast-like activated HSCs is the critical trigger of liver fibrogenesis. With NASH, the oxidative stress derived from hepatocytes, Kupffer cells/macrophages, and HSC itself promotes the proliferation and differentiation of HSCs and ultimately induces the occurrence of liver fibrosis (Kisseleva & Brenner 2007). In particular, TGF-β, mainly derived from M1-type macrophages, is an important fibrogenic cytokine that can impair NADPH oxidase and leads to the production of ROS required for HSC activation (Liang et al. 2016). In this study, MEL administration suppressed the activation of HSCs and reduced the mRNA levels of TGF-β1 in the liver of mice with NASH. Strikingly, MEL directly attenuated intracellular TGF-β signaling and reduced excessive ROS production in LX-2 human HSCs. These findings suggest that apart from attenuation of inflammation, MEL may also alleviate TGF-β-mediated HSC activation to reduce liver fibrogenesis in NASH progression.
Our results indicate that the beneficial effects of MEL on the phenotypes of steatohepatitis were not secondary to the reduction in body mass and food intake. Intriguingly, the protein expression levels of the two known MEL receptors (MTNR1A and MTNR1B) were not detectable in primary hepatocytes, Kupffer cells, or HSCs (data not shown), although the mRNA level of melatonin receptor type 1a (Mtnr1a) (Mtnr1b mRNA was not detectable) was upregulated in the liver of MCD-fed mice (data not shown). Thus, MEL may act on various cell types through an unknown pathway to regulate the activation of parenchymal and nonparenchymal cells in the development of NASH. This point warrants further investigation.
Collectively, our findings show the potent therapeutic and hepatoprotective effects of MEL in preventing a succession of NASH-related hepatic abnormalities, through inhibiting excessive lipid deposition and inflammation. Moreover, the beneficial effects of MEL are, at least in part, due to the reduction of the M1-like polarization in liver macrophages and inhibition of HSC activation. Although we were aware that i.p. injection of MEL is weaker than oral administration in clinical relevance (Bahrami et al. 2020) and regulation of intestinal microecology, our data suggest that MEL is a promising candidate for the treatment of NASH by acting on multiple key cell types in the liver.
Supplementary materials
This is linked to the online version of the paper at https://doi.org/10.1530/JME-22-0075.
Declaration of interest
The authors have no conflicts of interest to declare.
Funding
This work was supported by National Natural Science Foundation of China to L.X. (no. 81900778), Natural Science Foundation of Zhejiang Province to L.X. (no. LY21H070004) and High-Level Innovation Team of Universities in Zhejiang Province to CD (no. 604090352/610).
Author contribution statement
LX contributed to the study conception and design. LX, WH, and CD contributed to data analysis and manuscript writing. HL, OZ, RD, CH, FZ, MS, MM, YZ, and DL performed the animal and cell experiments and harvested and analyzed data. ZD, SJ, and WH contributed to discussions. LX and CD obtained the financial support and supervised the study. WH and CD approved the final manuscript.
Acknowledgements
The authors thank Textcheck for help in the preparation of the manuscript. Please see the certificate: http://www.textcheck.com/certificate/index/PQ0HOZ
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