Zhongyan Tang1, Lin Li2, Zhengxiang Xia3. 1. Department of Emergency and Critical Care Medicine, Jin Shan Hospital, Fudan University, Shanghai 201508, China. 2. Department of Operative Dentistry and Endodontics, School and Hosipital of Stomatology, Shanghai Engineering Research Center of Tooth Restoration and Regeneration, Tongji University, 399 Middle Yan Chang Road, Shanghai 200072, China. 3. Department of Pharmacy, School and Hosipital of Stomatology, Shanghai Engineering Research Center of Tooth Restoration and Regeneration, Tongji University, 399 Middle Yan Chang Road, Shanghai 200072, China.
Abstract
Gardeniae fructus (GF), the fruit from Gardenia jasminoides Ellis, is a traditional Chinese medicine used for the treatment of nonalcoholic fatty liver disease (NAFLD) in the clinic. To explore the hepatoprotective mechanism of GF for the treatment of NAFLD, we proposed a novel strategy that integrated in vivo efficacy evaluation, network pharmacology analysis, molecular docking, and experimental validation. A NAFLD animal model induced by high fat diet (HFD) feed was established, then orally administrated with or without GF. The results showed that GF significantly decreased the levels of serum total cholesterol (TC), lipoprotein cholesterol, triglyceride (TG), alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, free fatty acids, glucose, and insulin and the levels of liver TG, TC, and malondialdehyde compared with the nontreated HFD group. Network pharmacology studies showed that quercetin, oleanolic acid, kaempferol, and geniposide were the main biocompounds in GF that targeted the PPARα and PPARγ genes through regulating the PPAR and AMPK signal pathways to protect against NAFLD. The interactions between bioactive compounds and their corresponding target proteins were analyzed by molecular docking and subsequently confirmed using the qRT-PCR assay. Collectively, GF was a therapeutic drug for the treatment of NAFLD.
Gardeniae fructus (GF), the fruit from Gardenia jasminoides Ellis, is a traditional Chinese medicine used for the treatment of nonalcoholic fatty liver disease (NAFLD) in the clinic. To explore the hepatoprotective mechanism of GF for the treatment of NAFLD, we proposed a novel strategy that integrated in vivo efficacy evaluation, network pharmacology analysis, molecular docking, and experimental validation. A NAFLD animal model induced by high fat diet (HFD) feed was established, then orally administrated with or without GF. The results showed that GF significantly decreased the levels of serum total cholesterol (TC), lipoprotein cholesterol, triglyceride (TG), alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, free fatty acids, glucose, and insulin and the levels of liver TG, TC, and malondialdehyde compared with the nontreated HFD group. Network pharmacology studies showed that quercetin, oleanolic acid, kaempferol, and geniposide were the main biocompounds in GF that targeted the PPARα and PPARγ genes through regulating the PPAR and AMPK signal pathways to protect against NAFLD. The interactions between bioactive compounds and their corresponding target proteins were analyzed by molecular docking and subsequently confirmed using the qRT-PCR assay. Collectively, GF was a therapeutic drug for the treatment of NAFLD.
Nonalcoholic fatty liver
disease (NAFLD), a prevalent hepatic manifestation
of metabolic syndrome disorder, is characterized by ectopic accumulations
of triglycerides in the absence of excessive alcohol consumption.[1] NAFLD causes severe and prolonged damage to liver
tissue, which may progress into fibrosis and cirrhosis and eventually
lead to hepatocellular carcinoma. About 30% of adults in the Chinese
population have fatty liver disease, and the incidence of NAFLD increases
in the world every year. However, understand of the precise mechanisms
of NAFLD and an effective treatment strategy continue to lag behind,
and there are no effective drugs approved for the treatment of NAFLD.[2] Thus, the development of novel strategies for
preventing and treating such diseases is urgently needed. Recently,
natural products were found to exert potential efficacy in the prevention
or treatment of NAFLD.[3−5]Gardeniae Fructus (GF), derived from the dried
fruits of Gardenia jasminoides Ellis, is widely used
as a common traditional
Chinese medicine (TCM). GF was recorded in the Chinese Pharmacopoeia
in 2020. It had been also used for the treatment of acute or chronic
hepatic diseases,[6] icteric hepatitis, diabetes,[7] depression, viruses,[8] cancer,[9] and ischemic stroke.[10] A chemical investigation suggested that GF contained
iridoid glycosides, diterpenes, triterpenes, flavonoids, and other
chemical components.[11] Network pharmacology
emerged as a new field that integrated chemistry, pharmacology, bioinformatics,
and genomics to construct a model based on as system-level network
analysis and shed new light on the complicated mechanisms of TCM.[12] Molecular docking, an increasingly important
tool for structural molecular biology, is widely used to identify
the binding modes of mechanisms between small molecules and target
proteins.[13] However, to the best of our
knowledge, no reports had been published on the therapeutic effects
and mechanisms of GF for the treatment of NAFLD up to now. Thus, we
attempted to evaluate the potential efficiency of GF to attenuate
the development of NAFLD induced by the oral administration of a high
fat diet (HFD) in rats as a model animal and explored the mechanism
of action using network pharmacology, molecular docking analysis,
and experiment validation.
Results
Quility Control of GF
GF was purchased
from Shanghai Kang Qiao Herbal Pieces Co. Ltd. (Shanghai, China).
HPLC was used to identify the active components of GF. Additionally,
the compound was finally confirmed by the comparison with the authentic
compound. The chromatographic separation was carried out on a Diamonsil
C18 column (150 × 4.6 mm i.d., 5 mm) at 25 °C.
The mobile phase consisted of acetonitrile (solvent A) and water with
0.1% formic acid (solvent B). The optimized elution condition was
applied as follows: 0–60 min, 5–95% A. The solvent flow
rate and injection volume were kept as 0.5 mL/min and 5 μL,
respectively. The detection wavelength was 254 nm. As shown by the
results in Figure , compounds 1–5 were identified
as geniposide, genipin 1-gentiobioside, 6α-hydroxygeniposide,
gardenoside, and corcin I through comparing their chromatographic
profiles with standards, and their contents were qualified as 32.32
± 2.13, 1.59 ± 0.12, 0.36 ± 0.09, 0.21 ± 0.05,
and 3.87 ± 0.56 mg/mL, respectively.
Figure 1
(A) HPLC chromatograph
of GF. (B) HPLC chromatograph of compounds 1–5.
(A) HPLC chromatograph
of GF. (B) HPLC chromatograph of compounds 1–5.
GF Reduced the Body Weight, Liver Weight Index,
and Visceral Weight Index in the HFD-Fed Rat
As exhibited
in Figure A, there
were significant differences in body weight between the control group
and the HFD group treated with high fat food for 12 weeks. However,
the GF-treated group exhibited significantly reduced body weight compared
with the HFD group. Additionally, as shown in Figure B and C, the liver and visceral index (g/body
weight) in the HFD group were significantly higher than those in the
control group, suggesting that the hepatic steatosis induced by HFD-modeled
NAFLD was successful. Similarly, the GF treatment reversed these changes.
Moreover, GF administration decreased body weight, liver weight index,
and visceral weight index in a dose-dependent manner.
Figure 2
Effect of the GF treatment
on (A) body weight, (B) liver index/body
weight (%), (C) visceral index/body weight (%), (D) ALT (IU/L), (E)
AST (IU/L), (F) free fatty acid (μmol), (G) TG (mmol/L), (H)
TC (mmol/L), (I) HDL-c (mmol/L), (J) LDL-c (mmol/L), (K) glucose (mmol/L),
and (L) insulin (mU/L) in serum and (M) TC (mg/g) liver, (N) TG (mg/g)
liver, and (O) MDA nmol/mg protein in the liver. Results are expressed
as mean ± SEM (n = 6). #p < 0.05, ##p < 0.01, and ###p < 0.001 vs the
control group and *p < 0.05, **p < 0.01, and ***p < 0.001 vs the HFD group.
Effect of the GF treatment
on (A) body weight, (B) liver index/body
weight (%), (C) visceral index/body weight (%), (D) ALT (IU/L), (E)
AST (IU/L), (F) free fatty acid (μmol), (G) TG (mmol/L), (H)
TC (mmol/L), (I) HDL-c (mmol/L), (J) LDL-c (mmol/L), (K) glucose (mmol/L),
and (L) insulin (mU/L) in serum and (M) TC (mg/g) liver, (N) TG (mg/g)
liver, and (O) MDA nmol/mg protein in the liver. Results are expressed
as mean ± SEM (n = 6). #p < 0.05, ##p < 0.01, and ###p < 0.001 vs the
control group and *p < 0.05, **p < 0.01, and ***p < 0.001 vs the HFD group.
GF Improved Hepatic Steatosis and Liver Function
in HFD-Fed rats
To further explore the preventive effects
of GF on HFD-induced NAFLD, we measured the serum and liver biochemical
indices in different groups of rats. As exhibited in Figure , the serum levels of alanine
aminotransferase (ALT), aspartate aminotransferase (AST), free fatty
acid, total cholesterol (TC), low density lipoprotein cholesterol
(LDL-C), triglyceride (TG), glucose, and insulin and liver levels
of TC, TG, and malondialdehyde (MDA) were significantly increased
in the HFD group compared with the corresponding indices in the control
group. In contract, when the HFD-fed rats were orally administrated
with GF, the corresponding biochemical features in those rats decreased
significantly in a dose-dependent manner. The serum HDL-C levels exhibited
the opposite trends. On the other hand, the histological changes in
the liver were evaluated by hematoxylin and eosin (H&E) staining.
As shown in Figure , the liver samples obviously increased in terms of hepatocytic lipid
vacuoles and hepatocyte ballooning in the HFD-fed rats compared to
those without any treatment, while these features were reduced significantly
following the administration of the GF supplement to HFD-fed rats.
Moreover, the liver sections were stained with Oil Red O, as shown
in Figure S1. Very strong Oil Red O staining
was observed in the liver issues of the NAFLD model group, which suggested
the hepatocytes were filled with a large amount of lipid. However,
the intensity decreased with the higher dosage of GF. Therefore, the
data suggested that GF treatment on HFD-fed rats exerted protective
effects against NAFLD.
Figure 3
Liver tissue stained with H&E. (A) Control group,
(B) HFD-fed
group, (C) HFD and 25 mg/kg GF, (D) HFD and 50 mg/kg GF, (E) HFD and
100 mg/kg GF, and (F) HFD and metformin.
Liver tissue stained with H&E. (A) Control group,
(B) HFD-fed
group, (C) HFD and 25 mg/kg GF, (D) HFD and 50 mg/kg GF, (E) HFD and
100 mg/kg GF, and (F) HFD and metformin.
In Silico Network Analysis
and Prediction of Target Genes and Pathways Related to NAFLD
Several compounds in GF may act in a synergistic manner to protect
against NAFLD. Network pharmacology analysis was carried out to further
illustrate the mechanism of action of GF-induced hepatoprotective
activity. Seven compounds (Table ) with oral bioavailability (OB) values ≥30%
and drug-like (DL) values ≥0.18 were selected as potential
candidates. On the other hand, 15 overlapping targets (Supporting Information) derived from the target
database of compounds and NAFLD were considered as potential candidates.
Their interactions were constructed using Cytoscape. As showed in Figure A, quercetin,[7] oleanolic acid,[3] kaempferol,[3] and geniposide[3] were
linked to three or more target genes with more degrees. In addition,
the core target genes included peroxisome proliferator-activated receptor-α
(PPARα) regulated by oleanolic acid and quercetin and peroxisome
proliferator-activated receptor-γ (PPARγ) targeted by
quercetin and kaempferol. Overall, the above compounds and their corresponding
target genes might play myriad roles in the development and progression
of NAFLD regulated by GF.
Table 1
A List of the Final Compounds in GF
Selected for Network Analysis
Figure 4
Network pharmacology of GF inhibition against NAFLD. (A) Network
“compound–target–pathway” diagram. (B) The PPI network diagram. (C) KEGG enrichment
analysis map of the potential treatment pathways of GF for NAFLD.
Network pharmacology of GF inhibition against NAFLD. (A) Network
“compound–target–pathway” diagram. (B) The PPI network diagram. (C) KEGG enrichment
analysis map of the potential treatment pathways of GF for NAFLD.
Network Analysis of Protein–Protein
Interactions (PPI)
The interactions among the core 15 target
genes were illustrated in the STRING database, where nodes represent
proteins and edges stand for protein–protein interactions.
The result was downloaded and is shown in Figure B. PPARA possessed four degrees, and PPARG
and ADRB2 possessed five degrees. These proteins featured more degrees
than others, which indicated that they might play important roles
in GF against NAFLD. Interestingly, this was consistent with the conclusion
from the above network analysis.To understand the hepatoprotective
mechanism of action of GF against NFALD, we performed the functional
enrichment analysis (as present in Figure C) of the target genes of bioactive compounds
from GF using DAVID software and the KEGG database. Potential target
genes were functionally associated with various signal transduction
pathways such as PPAR, the glucagon signaling pathway, the AMP-activated
protein kinase (AMPK) signaling pathway, and the cGMP-PKG signaling
pathway (cGMP-PKG) (Table ). Interestingly, the potential target genes appeared to be
connected to the PPAR and AMPK signaling pathways. Subsequently, GF
protected against NAFLD by regulating multiple pathways concentrated
on the PPAR and AMPK signaling pathways.
Table 2
Kyoto Encyclopedia of Genes and Genomes
(KEGG) Pathways and Target Genes of Compounds in the GF Extract (GFE)
Potentially Responsible for the Therapeutic Activities against NAFLD
pathway classification
pathway ID
term
target gene
signal transduction
hsa03320
PPAR
signaling pathway
PPARA, PPARD, PPARG
signal transduction
hsa04970
salivary secretion
ADRB2, ADRA1B, ADRA1A
signal transduction
hsa04080
neuroactive ligand–receptor interaction
ADRB2, ADRA1B, ADRA1A, GLP1R
signal transduction
hsa04922
glucagon signaling pathway
GCG, PPARA, ACACA
signal transduction
hsa04152
AMPK signaling pathway
PPARG, ACACA, ADRA1A
signal transduction
hsa04261
adrenergic
signaling in cardiomyocytes
ADRB2, ADRA1B, ADRA1A
signal transduction
hsa04022
cGMP-PKG
signaling pathway
ADRB2, ADRA1B, ADRA1A
signal transduction
hsa04020
calcium signaling pathway
ADRB2, ADRA1B, ADRA1A
signal transduction
hsa04024
cAMP signaling pathway
PPARA, ADRB2, GLP1R
Docking Exercises of Binding the Main Ingredients
and the Protein
Computational docking exercises were conducted
to explore the characteristics of the ingredient–target binding
mode (Figure ). The
results (Table ) showed
that quercetin and kaempferol formed strong interactions with PPARγ,
geniposide and quercetin formed strong interactions with PPARα,
and quercetin and geniposide formed strong interactions with AMPK,
which featured a hydrogen bond and an other covalent bond with a docking
energy less than −2.53 kcal/moL. The molecular docking results
were consistent with the network analysis, for example, quercetin
and kaempferol wre linked with PPARγ while geniposide and quercetin
were linked with PPARα. Therefore, GF protected against NAFLD via multiple compounds acting on multiple targets. In detail,
quercetin and kaempferol targeted PPARA and quercetin and kaempferol
targeted PPARγ through regulating AMPK signal pathways.
Figure 5
Molecular docking
analyses of the molecular interactions and binding
modes of compounds with the active sites of target genes. (A) PPARγ–quercetin,
(B) PPARγ–kaempferol, (C) PPAR–-geniposide, (D)
PPARα–quercetin, (E) AMPK–quercetin, and (F) AMPK–geniposide.
Table 3
Docking Analysis of Target Genes and
Compounds
target gene
PDB ID
compound
autodock energy (kcal/mol)
PPARγ
3K8S
quercetin
–2.53
kaempferol
–3.83
PPARα
3ET1
geniposide
–3.54
quercetin
–2.78
AMPK
6BX6
quercetin
–2.94
geniposide
–3.25
Molecular docking
analyses of the molecular interactions and binding
modes of compounds with the active sites of target genes. (A) PPARγ–quercetin,
(B) PPARγ–kaempferol, (C) PPAR–-geniposide, (D)
PPARα–quercetin, (E) AMPK–quercetin, and (F) AMPK–geniposide.
Network Pharmacology and Molecular Docking
Analysis Results Confirmed by qRT-PCR
We next searched for
evidence of the mechanism of GF against NAFLD deduced by network pharmacology.
Although molecular docking had clarified the interplay mechanism between
bioactive compounds and targets, the evidence of molecular events
was still deficient, so a qRT-PCR assay was performed using the potential
target genes regulated by GF. The mRNA expression levels of the core
target genes PPARα and PPARγ exhibited by the network
pharmacology network diagram, their related lipogenesis factors (SREBP-1c,
FAS, and CPT-1), and the main signal pathways PPAR and AMPK analyzed
by PPI were measured in the liver. As shown in Figure , the mRNA expression levels of SREBP-1c,
FAS, and PPARγ were remarkably reduced in the HFD-fed rats supplemented
with GF compared with those in the nontreated HFD-fed rats. On the
other hand, the mRNA expression levels of PPARα, CPT-1, and
AMPK were significantly higher in HFD-fed rats supplemented with GF
compared to those in the nontreat HFD-fed rats. The data suggested
that GF protected against NAFLD by regulating the mRNA expression
of lipogenesis (SREBP-1c, FAS, PPARγ, PPARα, CPT-1, and
AMPK) in liver tissue.
Figure 6
Effect of the GF treatment on mRNA expression levels of
(A) SREAP-1,
(B) FAS, (C) PPAR-α, (D) AMPK, (E) CPT-1, and (F) PPAR-γ.
Results are expressed as the mean ± SEM (n = 6). #p < 0.05, ##p < 0.01, and ###p < 0.001 vs the control group and *p < 0.05,
**p < 0.01, and ***p < 0.001
vs the HFD group.
Effect of the GF treatment on mRNA expression levels of
(A) SREAP-1,
(B) FAS, (C) PPAR-α, (D) AMPK, (E) CPT-1, and (F) PPAR-γ.
Results are expressed as the mean ± SEM (n = 6). #p < 0.05, ##p < 0.01, and ###p < 0.001 vs the control group and *p < 0.05,
**p < 0.01, and ***p < 0.001
vs the HFD group.
Discussion
The progression and development
of NAFLD are complicated processes
involving multiple factors that alter the homeostasis of liver tissue.
On the other hand, TCM contains of tens or thousands of compounds
that can act on multiple target proteins by regulating multiple pathways
to exert their synergism or exert compatible pharmacological effects
on complex diseases.[14] Thus, TCM may have
myriad advantages in the treatment of NAFLD.[15] In this paper, we proposed a strategy that integrated pharmaceutical
a efficacy evaluation in an animal model, network pharmacology, molecular
docking, and experimental verification to explore the potential efficacy
and mechanism of action of GF for the treatment of NAFLD.After
the HFD-induced rat model of NAFLD was established and then
treated with GF for 12 weeks, the results of the histopathological
analysis of the liver, the serum and liver biochemical indices, the
body weight and the liver weight index showed that GF exerted potential
protective effects against NAFLD. In detail, we observed significant
changes in serum glucose, insulin, lipid, and liver function enzyme
(ALT and AST) levels in serum and the mRNA expression of lipogenesis
in liver tissue among different groups of rats. ALT, AST, and LDH-c
are the important biochemical indicators of liver function and are
widely used in clinical diagnosis. Moreover, serum glucose, insulin
resistance, dyslipidemia, and metabolic syndromes have played important
roles in NAFLD. For example, insulin resistance inhibited the antilipolytic
activity of insulin in the adipose tissue and increased free fatty
acids (FFAs) in the serum and liver, leading to mitochondrial dysfunction
and cardiac fat accumulation.[16] As expected,
the serum glucose, TC, LDL-c, TG , and insulin levels were lower in
HFD-fed rats supplemented with GF compared to those in untreated rats.
Furthermore, oxidative stress is an essential risk factor for NAFLD,
as it promotes the production of reactive oxygen species (ROS) that
stimulate an inflammatory process in hepatic tissues.[17] Our research showed that the MDA levels in liver were lower
in the HFD-induced rats treated with GF compared to those without
any supplement. Moreover, the higher dosage (100 mg/kg) of GF showed
effects similar to those of the positive control drug metformin in
the treatment of rats with NAFLD. Consequently, GF may play an important
role in preventing or slowing the progression of NAFLD by regulating
multiple factors, such serum glucose and liver enzyme levels, insulin
resistance, oxidative stress, free fatty acids.According to
a network pharmacology analysis, the main bioactive
compounds in GF, including quercetin, oleanolic acid, kaempferol,
and geniposide, played key roles in the treatment of NAFLD by targeting
PPARα and PPARγ. Moreover, these main protein genes exerted
their effects on the PPAR and AMPK signal pathways. Next, we will
discuss their roles in the process of NAFLD from three molecular levels,
namely,compounds, protein genes, and pathways.First, quercetin
and kaempferol are natural flavonoids that are
widely distributed in herbal medicine, vegetables, and edible fruits.
They feature a variety of biological functions and are studied primarily
for their potential roles in combating oxidative and inflammatory
processes. They showed potential for the treatment of fatty liver
disease. Previous studies showed that quercetin both alone and in
herbal medicine could ameliorate NAFLD in HFD-induced mice.[18] Moreover, mice treated with up to 3000 mg/kg
quercetin did not show any toxic effects.[19] Kaempferol, which has chemical structure analogous to that of quercetin
with one less hydroxyl, also exhibited a hepatoprotective effect,[20] suppressed hepatic gluconegeonesis, and inhibited
hepatocellular
carcinoma cell. Geniposide, a major characteristic constituent in
GF, exerted protective effects against hepatic steatosis in rats fed
with HFD; the underlying mechanism might be associated with its antioxidant
actions or the regulation of adipocytokine release and the expression
of PPARα.[21] finally, oleanolic acid
attenuated the subsequent development of high fructose diet-induced
NAFLD in rats.[22]Second, we identified
PPARα and PPARγ as potential
target genes using network pharmacology. PPARγ is a regulator
of adipocyte differentiation. Additionally, it has been implicated
in the pathology of numerous diseases including obesity, diabetes,
atherosclerosis, and cancer.[23] Previous
study showed that PPARα could inhibit fatty liver disease by
activating the periostin-dependent JNK signaling pathway and modulating
fatty acid oxidation.[24] PPARs are binder-activated
nuclear receptors that are involved in the transcriptional regulation
of lipid metabolism, energy balance, inflammation, and atherosclerosis.[25]Third, the functions of potential target
genes identified from
the KEGG enrichment analysis were associated with multiple signal
transduction pathways. Among these, the PPAR and AMPK pathways played
the most important roles with highest degrees, which was consistent
with the results from the PPI analysis. Recent research showed that
PPARs were closely related to metabolic syndrome and its relevant
complications. Additionally, PPARs had protective effects on the NAFLD
development because they could regulate the lipid metabolism.[25] Moreover, a large number of studies suggested
that activation of AMPK could ameliorate NAFLD, and AMPK was a potential
therapeutic target for the treatment of NAFLD.[26] On the other hand, previous reports suggested that the
main bioactive compounds from GF regulated these pathways, examples
of which are as follows: Quercetin attenuated NAFLD by improving lipid
metabolism through modulating the AMPK/PPAR pathway and gut microbiome.[27] Kaempferol protected against NAFLD by regulating
hepatic PPARα levels.[28] Geniposide
alleviated NAFLD by blocking Nrf2/AMPK/mTOR signaling pathways.[29] Therefore, our results suggested that these
signal pathways might be coordinated during the NAFLD progression,
and the effects of GF could be mediated through the PPAR and AMPK
signaling pathways.Fourth, computational docking exercises
showed that the main ingredients
from GF formed comparative interactions with their corresponding predicted
proteins. The regulatory mechanisms of the processes are likely valid
targets for modulating lipid metabolism and inflammation in the treatment
of NAFLD. According to the network pharmacology and PPI analysis,
the main bioactive compounds quercetin, kaempferol, and geniposide
interacted with their corresponding targets PPARγ and PPARα
through the AMPK signal pathways.Finally, the mRNA expression
levels of the core target genes and
pathways analyzed by network pharmacology were measured using qRT-PCR.
AMPK is a master energy sensor that monitors metabolic homeostasis,
and the repression of its activity might lead to metabolic disorders,
such as NAFLD and diabetes.[30] In the liver,
AMPK plays an important role in hepatic lipid metabolism through inhibiting
lipogenesis and activating fatty acid oxidation. In detail, PPARα
is mainly restricted to the liver issue,[31] and promotes the uptake and oxidation of hepatic fatty acids; carnitine
palmitoyltransferase-1 (CPT-1) also has a similar function. PPARγ
and PPARα are two PPAR isotypes, but they have different functions.
PPARγ is a master transcription factor in adipogenesis that
participates in the process of lipogenesis, lipid droplet formation,
and TG synthesis.[32] FAS is a transcription
lipogenesis factor that uses acetyl-CoA or malonyl-CoA to synthesize
fatty acids. In this study, GF protected against NAFLD by activating
AMPK signal pathway and then inhibiting AMPK adipogenesis and lipogenesis
by decreasing the mRNA expression levels of PPARγ, FAS, C/EBPα,
and SREBP1; however, it promoted fatty acid oxidation by increasing
mRNA expression levels of PPARα and CPT-1.
Materials and Methods
Chemical Reagents
Gardenoside, geniposide,
genipin 1-gentiobioside, 6α-hydroxygeniposide, and crocetin
I were purchased from EFEBIO (Shanghai, China). Acetonitrile, ethanol,
and formic acid of HPLC grade were purchased from Merck KGaA (Darmstadt,
Germany). Deionized water purified by a Milli-Q water purification
system (Millipore, Billerica, MA) was applied to prepare and extract
plasma samples. Other reagents and chemicals were all of analytical
grade.
Preparation of Gardeniae Fructus Extract (GFE)
GF was purchased from Shanghai Kang Qiao Herbal Pieces Co. Ltd.
(Shanghai, China). Morphological and microscopic authentications,
thin layer chromatography, and HPLC were performed in accordance with
Chinese Pharmacopoeia (2020) by author Dr. Zhengxiang Xia. GFE was
prepared as follows: The herbal materials (200 g) were crushed
into small pieces and mixed/ The mixture was then soaked in 70% ethanol
for 0.5 h before decocted for 1 h. The filtrates were collected, and
the residues were then refluxed in water (1:5, w/v) for 1 h. GFE (equal
to 1.0 g/mL GF) could be obtained by mixing the two-stage filtrates
and concentrating the volume to 200 mL. The chemical profile was characterized
by HPLC (Milford, MA).
Animal Experiment
Five-week-old male
Sprague–Dawley (SD) rats weighing 180–220 g were purchased
from Shanghai SLAC Laboratory Animal Co. Ltd. (Shanghai, China). The
scheme for the animal experimental method is shown in Figure . After a one-week acclimation
period, the rats were divided into six groups (n =
6 each). The control group was fed a normal diet (Con, 10 kcal % fat,
D12450B, Research Diet, Inc., New Brunswick, NJ), and the others were
fed with a HFD (60 kcal % fat, D12492). After six weeks, the NAFLD
model was established, and four groups were supplemented with GFE
(25, 50, and 100 mg/kg, daily oral administration) and metformin (100
mg/kg, daily oral administration), respectively, for six weeks. At
the end of the 13-week treatment period, the rats were sacrificed
with 10% chloral hydrate. Blood was collected from the portal vein
and then centrifuged at 4 °C and 500 × g for 20 min. Plasma was collected and stored at −80 °C
in a centrifuge tube prior to the biochemical analysis. The separated
liver was weighed, and the left lobe fixed in neutral formaldehyde
for histopathological analysis. The rest of liver was snap frozen
in liquid nitrogen and stored at −80 °C for subsequent
analysis. The visceral adipose tissues were collected and weighed,
and body fat rates were calculated. The ethical aspects of animal
experimentation studies were approved by the Ethics Committee on Animal
Research in School and Hosipital of Stomatology, Tongji University.
All surgeries were performed under 10% chloral hydrate, and all efforts
were made to minimize suffering. Body weight and food intake were
surveyed every week.
Figure 7
Schematic overview of the experimental design.
Schematic overview of the experimental design.
Blood and Liver Biochemical Assays
Detection kits for triglycerides (TG), total cholesterol (TC), free
fatty acid, low-density lipoprotein cholesterol (LDL-C), high-density
lipoprotein cholesterol (HDL-C), alanine aminotransferase (ALT), and
aspartate transaminase (AST) in serum and TG, TC, and MDA in the liver
were purchased from Jiangsu Jiancheng Company (Nanjing, China) and
were performed according to the manufacturer’s protocol.
Tests for Glucose and Insulin Metabolic Parameters
When the blood was obtained from each rat, it was quickly measured
using an ACCU-CHEK blood glucose meter (Roche Diagnostics Ltd. Company,
Shanghai, China). Insulin levels were measured using an insulin ELISA
kit (Jiangsu Jiancheng Company, Nanjing, China).
Determination of Lipid Peroxidation and TG
and TC Contents in the Liver
TG, TC, and MDA contents in
the liver were determined using commercial kits (Jiancheng Company,
Nanjing, China) according to the manufacturer’s protocol.
Histopathological Analysis
The liver
tissue specimens were fixed in 10% formalin, embedded in paraffin,
and serially sectioned. H&E staining was used to visualize liver
cells and matrices. Histological changes were observed using light
microscopy (Olympus CX31/BX51, Olympus Optical Co., Tokyo, Japan)
and photographed (Olympus DP70).
Oil Red O Staining
The liver sections
of the rats were stained with Oil Red O (ORO) to assess hepatic steatosis.
The tissues were cut into 5 μm slices, and rinsed with 60% isopropyl
alcohol. To the tissues was then added the Oil Red O staining solution
(Jiangsu Jiancheng, Nanjing, China) according to the manufacturer’s
instructions. The images were observed using light microscopy (Olympus
CX31/BX51, Olympus Optical Co., Tokyo, Japan) and photographed (Olympus
DP70).
Molecular Docking
The crystal structure
of PPARγ was obtained from the Protein Data Bank (PDB ID 3K8S). The crystal structure
of PPARα was also obtained from the Protein Data Bank (PDB ID 3ET1). The crystal structure
of AMPK was also obtained from the Protein Data Bank (PDB ID 6BX6). The docking exercise
was conducted using AutoDock sofware following the procedure from
previous literature.[33,34]
qRT-PCR Analysis
Total RNA liver
tissues were isolated from by TRIzol reagent (Beyotime, Shanghai,
China) according to the manufacturer’s method, and the assay
was subsequently performed as previously report.[35] Primer sequences are shown in Table .
Table 4
Primer Sequences Used in Quantitative
Real-Time PCRa
All results
were shown as the mean ± SEM. Statistical analysis was performed
using one-way analysis of variance with Dunnett’s multiple
comparisons test for multiple comparisons, and p <
0.05 was considered statistically significant. Statistical analysis
was performed using GraphPad Prism Software ver. 8.0 for Windows (GraphPad
Software, La Jolla, CA).
Construction and Screening of the Active
Components in GF
To obtain active components from GF, Gardenia jasminoides was first investigated using the literature
and public databases, such as PubMed, Traditional Chinese Medicine
Systems Pharmacology Database (TCMSP) (available online at http://lsp.nwsusaf.edu.cn/), and TCM Database@Taiwan. Ninety-eight compounds were collected.
Second, the OB and DL values were screened using absorption, distribution,
metabolism, and excretion (ADME) models provided by TCMSP. The threshold
values for these screening models were set to OB ≥ 30% and
DL ≥ 0.18. Finally, seven compounds were selected as candidates
for subsequent analysis.
Target Fishing
To obtain target
information on the active compounds from GF for the treatment of NAFLD,
a comprehensive method was applied using chemoinformatics and a text-mining
database. First, the information obtained from the search tool for
interactions of chemicals and proteins in databases such as STITCH
(http://stitch.embl.de/),
TCMSP (http://lsp.nwu.edu.cn/tcmsp.php), and PharmMapper (http://lilab.ecust.edu.cn/pharmmapper/index.php) were used (Table S2). After the removal
of duplicates, 112 target genes were collected. Second, keywords including
nonalcoholic fatty liver disease, obesity, and lipid metabolism on
NAFLD-associated target genes were searched in the therapeutic targets
database (TTD, http://bidd.nus.edu.sg/BIDD-Databases/TTD/TTD.asp, updated January 11, 2018), Pubmed (https://www.ncbi.nlm.nih.gov/pubmed/), and DRUGBANK (https://www.drugbank.ca/). Third, the overlapping targets that came from the above two methods
were considered to be potential targets in GF for the treatment of
NAFLD and were analyzed using http://jvenn.toulouse.inra.fr/app/example.html. Finally, 15 target genes (Table S1)
were obtained as candidates for subsequent analysis.
Construction of the Target Protein–Protein
Interaction (PPI) Network
To explore the relationships among
these target proteins, the core target proteins of the active compounds
were enriched using STRING (http://string-db.org). The species was limited to Homo sapiens, the
minimum required interaction score was set to 0.400, and the dependent
target protein nodes were shown.
Network Construction and Analysis
To facilitate the visualization of bioactive compounds from GF and
their potential target genes related to NAFLD, networks were constructed
using software Cytoscape ver. 3.2.1. This software was used to visualize
compounds, biological pathways, and molecular interaction networks
to explore the pharmacological mechanism of action. In networks, nodes
represented compounds, target genes, or pathway, and edges indicated
compound–target or compound–pathway interactions. To
illustrate the mechanisms of action of the active compounds from GF
and their roles in signal transduction, the Database for Annotation,
Visualization, and Integrated Discovery (DAVID) was used to analyze
the KEGG pathway enrichment of the target protein genes. The cellular
components involved in the target protein and the pathways were also
described.
Conclusion
In conclusion, our studies
revealed that GF exerted protective
effects against NAFLD in the HFD-induced rats and restored triglycerides
by alleviating histopathological features and suppressing the levels
of ALT, AST, free fatty acid, TC, LDL-C, TG, glucose, and insulin
in serum in addition to TC, TG, and MDA in the liver. GF exhibited
an effect against NAFLD comparable to that of the positive control
metformin. Our subsequent network pharmacology analysis suggested
that quercetin, oleanolic acid, and geniposide from GF treated NAFLD
by targeting PPAR and PPARα through various signaling pathways,
which were concentrated on the AMPK and PPAR signaling pathways. Molecular
docking studies and mRNA expression in the qRT-PCR assay further confirmed
the above results. Therefore, the pharmaceutical mechanism of GF exerting
inhibitory effects on the process of NAFLD was as follows: GF first
activated the AMPK signal. The activated AMPK inhibited adipogenesis
and lipogenesis by decreasing the mRNA expression levels of PPARγ,
FAS, and SREBP1; however, it promoted fatty acid oxidation by increasing
mRNA expression levels of PPAR-α and CPT-1. To our knowledge,
this is first report on the effects and mechanism of GF against NAFLD
that is guided by network pharmacology, molecular docking, and experimental
verification. The results not only provide evidence for the therapeutic
mechanism of action of GF against NAFLD but also shed new light on
the molecular mechanism analysis of other complex drugs.
Authors: I Barroso; M Gurnell; V E Crowley; M Agostini; J W Schwabe; M A Soos; G L Maslen; T D Williams; H Lewis; A J Schafer; V K Chatterjee; S O'Rahilly Journal: Nature Date: 1999 Dec 23-30 Impact factor: 49.962