Abstract
Objectives: To evaluate the pharmacodynamical effects and
pharmacological mechanism of Ginsenoside H dripping pills (GH) in
chronic unpredictable mild stress (CUMS) model rats.
Methods: First, the CUMS-induced rat model was established to assess
the anti-depressant effects of GH (28, 56, and 112 mg/kg) by the
changes of the behavioral indexes (sucrose preference, crossing score,
rearing score) and biochemical indexes (serotonin, dopamine,
norepinephrine) in Hippocampus. Then, the components of GH were
identified by ultra-performance liquid chromatography-iron trap-time of
flight-mass spectrometry (UPLC/IT-TOF MS). After network pharmacology
analysis, the active ingredients of GH were further screened out based
on OB and DL, and the PPI network of putative targets of active
ingredients of GH and depression candidate targets was established
based on STRING database. The PPI network was analyzed topologically to
obtain key targets, so as to predict the potential pharmacological
mechanism of GH acting on depression. Finally, some major target
proteins involved in the predictive signaling pathway were validated
experimentally.
Results: The establishment of CUMS depression model was successful and
GH has antidepressant effects, and the middle dose of GH (56 mg/kg)
showed the best inhibitory effects on rats with depressant-like
behavior induced by CUMS. Twenty-eight chemical components of GH were
identified by UPLC/IT-TOF MS. Subsequently, 20(S)-ginsenoside Rh2 was
selected as active ingredient and the PPI network of the 43 putative
targets of 20(S)-ginsenoside Rh2 containing in GH and the 230
depression candidate targets, was established based on STRING database,
and 47 major targets were extracted. Further network pharmacological
analysis indicated that the cAMP signaling pathway may be potential
pharmacological mechanism regulated by GH acting on depression. Among
the cAMP signaling pathway, the major target proteins, namely, cAMP,
PKA, CREB, p-CREB, BDNF, were used to verify in the CUMS model rats.
The results showed that GH could activate the cAMP-PKA-CREB-BDNF
signaling pathway to exert antidepressant effects.
Conclusions: An integrative pharmacology-based pattern was used to
uncover that GH could increase the contents of DA, NE and 5-HT,
activate cAMP-PKA-CREB-BDNF signaling pathway exert antidepressant
effects.
Keywords: ginsenoside H dripping pills, depression, network
pharmacology, chronic unpredictable mild stress, cAMP signaling pathway
Introduction
Depression is a mental disorder illness with a high disability,
morbidity and recurrence rate ([50]Chen et al., 2008). The main
clinical features are decreased food-intake, low mood, anhedonia,
activity decrease, irritability and other symptoms ([51]Yang et al.,
2018). In severe cases, they may have suicidal tendency ([52]Zhu et
al., 2020). An epidemiological multicenter study showed the odds of
being depressed among cancer patients were more than five times higher
than in the general population ([53]Götze et al., 2020). Remarkably,
comorbid depression in patients with cancer was compellingly
established as a risk factor for suicide as well as rapid cancer
progression ([54]Shoval et al., 2019). There is no specific drug for
the treatment of depression in cancer patients, and antidepressants are
generally used. At present, the commonly used chemical antidepressants
are mainly divided into four classes according to the chemical formula
and the mechanism, including selective serotonin-re-uptake inhibitors
(SSRI) such as sertraline and fluoxetine, serotonin and norepinephrine
reuptake inhibitors (SNRI) like duloxetine and milnacipran, tricyclic
anti-depressants (TCA) such as amitriptyline and imipramine, monoamine
oxidase inhibitors (MAOI) like moclobemide and phenelzine ([55]Zhao et
al., 2015; [56]Ostuzzi et al., 2018). There are several Chinese herbal
formulae for the treatment of depression including Chaihu Shugan
powder, Xiaoyao Pill and Shugan Jieyu capsule ([57]Du et al., 2014;
[58]Fu et al., 2014; [59]Wang et al., 2014). Clinically, although
chemical antidepressants are widely used, their side effects are
common, such as hepatotoxicity, drowsiness, sexual dysfunction, nausea,
irritability and psychomotor impairment ([60]Dai et al., 2010;
[61]Gorzalka and Hill, 2011; [62]Zhu et al., 2020). Compared with
chemical drugs, traditional Chinese medicine (TCM) are attracting more
and more attention due to its advantages such as low toxicity and side
effects, high safety, and high efficacy and toxicity reduction ([63]Xie
et al., 2018). Therefore, the research on the treatment of depression
with TCM has certain clinical value.
Ginsenoside H dripping pills (GH), originated from Tasly Group, is the
class 5 new traditional Chinese medicine which obtained from leaves of
Panax Quinquefolium Linn by extracting, chemical degrading and
chromatography separating ([64]Chen et al., 2018). It is designed to be
used for replenishing qi and blood, and is used as an adjuvant drug for
treating cancer. The main ingredient of the drug is ginsenoside Rh2 and
the content of ginsenoside Rh2 is about 30% ([65]Ma et al., 2018).
Early studies have indicated that ginsenoside Rh2 could significantly
inhibit the growth of U14 cervical cancer bearing mouse ([66]Zhang et
al., 2013). Besides, ginsenoside Rh2 can significantly improve the
depressive behavior of depressing mice ([67]Wang et al., 2016). It can
be said that GH not only has significant anti-tumor effects, but also
has antidepressant effects, which provides exclusive drugs for the
treatment of depression in cancer patients and has research value.
However, it is still unclear that antidepressant effects and mechanism
of GH. Therefore, the study adopted the integrated pattern of
“pharmacodynamics - network pharmacological analysis - mechanism
verification” to deeply study the antidepressant effects and potential
mechanism of GH.
Chronic unpredictable mild stress (CUMS) model in rats was the closest
animal model to clinical depression ([68]Su et al., 2017). During the
modeling process, rats which were subjected to different kinds of
chronic unpredictable mild stress, fully simulated the social living
environment of depressive patients and induced rats to produce many
behavioral abnormal symptoms similar to those of depressive patients
([69]Antoniuk et al., 2019; [70]Li et al., 2019). For example, the
reducing the sucrose preference in rats simulated the symptoms of
anhedonia in depressive patients; the reducing the score of Open field
exercise simulated the symptoms of low ability of autonomic movement in
depressive patients ([71]Tan et al., 2015; [72]Liu et al., 2018).
Therefore, the decrease of behavioral indexes (sucrose preference and
open field exercise score) showed that CUMS depression model in rats
were successfully established. In addition, the pathogenesis of
depression is complex. Although several hypotheses about depression
have been proposed, the monoamine hypothesis is still the most common
hypothesis for depression, because most of the current antidepressants
act on monoamine transporters or receptors ([73]Auclair et al., 2013;
[74]Liu et al., 2020). The hypothesis believes that the occurrence of
depression is mainly due to the lack of major monoamine
neurotransmitters such as 5-hydroxytryptamine (5-HT), dopamine (DA) and
norepinephrine (NE) in the central nervous system of the brain
([75]Jesulola et al., 2018). Hence, the contents of 5-HT, DA and NE in
hippocampus were decreased, which indicated that CUMS depression model
in rats was successfully established. In conclusion, the antidepressant
effects of GH were evaluated from the behavioral and biochemical
indexes of depression model rats.
Network pharmacology was first proposed by Hopkins in 2007, which is
based on disease-gene-target-drug interaction network to predict the
material basis and mechanism of drug intervention in diseases ([76]Li
and Zhang, 2013). With the establishment of TCM database systems such
as Encyclopedia of Traditional Chinese Medicine and Traditional Chinese
Medicine Systems Pharmacology Database ([77]Ru et al., 2014; [78]Xu et
al., 2019), network pharmacology has been widely used in TCM ([79]Xu et
al., 2014; [80]Yu et al., 2017; [81]Zhang et al., 2017; [82]Li et al.,
2018). Interestingly, the holistic philosophy of TCM is consistent with
the key idea of emerging network pharmacology ([83]Li et al., 2014).
Our group had previously predicted the underlying pharmacological
mechanism of Xueshuan-Xinmai-Ning (XXNT) acting on coronary heart
disease (CHD) through network pharmacology method, and found that the
XXNT in the treatment of CHD might be involved into the signal
transduction in nervous-endocrine-immune-cardiovascular-metabolic
system, and it is verified by experiments that XXNT plays a role in
treating CHD via VEGF signal pathway ([84]Mao et al., 2019). In
addition, through network pharmacology analysis, it is found that Zhile
alleviated depression-like behaviors by upregulating the cAMP-CREB-BDNF
signaling pathway ([85]Wu et al., 2019). Therefore, the pharmacological
mechanism of the anti-depressant effects of GH could be evaluated by
network pharmacology analysis.
In this study, the integrated pharmacology-based pattern, which adopted
pharmacodynamics-network pharmacology-mechanism verification, was used
to elucidate the pharmacological mechanism of GH in treatment of
depression. The antidepressant effects of GH were first confirmed by
using chronic unpredictable mild stress model rats. The chemical
components containing in GH were then identified by UPLC/IT-TOF MS, and
the active ingredients of GH were further screened out based on OB and
DL. Network pharmacology analysis was conducted to predict the
potential pharmacological mechanism of GH in treatment of depression.
At last, the results predicted by network pharmacology were further
validated by western blotting and enzyme-linked immunosorbent assay. A
flowchart of this study is illustrated in [86]Figure 1.
FIGURE 1.
[87]FIGURE 1
[88]Open in a new tab
Flowchart of the study.
Materials and Methods
Reagents and Materials
Bulk substance of Ginsenoside H dripping pills (GH) and GH
(specification: 30 mg/pill, the total saponin content: 3.12 mg) were
obtained from Tianjin Tasly Pharmaceutical Co., Ltd. (Batch NO.
20120606-16, 20160309, respectively, Tianjin, China). Fluoxetine
hydrochloride (Flu) was provided by Suzhou Eli Lilly and Company
(Suzhou, China). Chromatographic grade methanol and acetonitrile were
obtained from Fisher Scientific Co. (Loughborough, United Kingdom).
Pseudoginsenoside RT5, 20(S)-ginsenoside Rh1, 20(R)-ginsenoside Rh1,
20(S)-ginsenoside F1, ginsenoside Rh4, ginsenoside CK,
20(S)-ginsenoside Rh2, 20(R)-ginsenoside Rh2, isoginsenoside Rh3
standards were obtained from China National Institute for the Control
of Pharmaceutical and Biological Products (Beijing, China).
ginsenosides Rk2 standard was purchased from Chengdu Mansite
Pharmaceutical Co., Ltd. (Chengdu, China). All standards were of at
least 98% purity and were suitable for UPLC/IT-TOF analysis. The
enzyme-linked immunosorbent assay (ELISA) kits, including serotonin
(5-HT), dopamine (DA), norepinephrine (NE) and cyclic Adenosine
monophosphate (cAMP) were supplied by Shanghai Lianshuo Biological
Technology Co., Ltd. (Shanghai, China). The radioactive cyclic-AMP
dependent protein kinase A (PKA) assay kit was purchased from Promega
Corporation (Madison, Wisconsin, United States). The primary antibodies
against brain derived neurotrophic factor (BDNF), cAMP-response element
binding protein (CREB), phosphorylated cAMP-response element binding
protein (p-CREB) and the secondary antibodies goat anti-rabbit IgG-HRP
were purchased from Affinity Biosciences (Cincinnati, OH, United
States). Bicinchoninic acid assay (BCA) kits was produced by Beyotime
Institute of Biotechnology Co., Ltd. (Nanjing, China).
Animals
A total of 80 Specific-pathogen free (SPF) male Sprague Dawley rats
(180–220 g) were obtained from the China National Institutes for Food
and Drug Control (SCXK (jing) 2017-0005). The rats were kept in an
environmentally controlled room (temperature 22 ± 2°C, humidity 50 ±
10%, 12 h/12 h light/dark cycle) and were allowed to eat and drink
freely. The laboratory animals were used according to requirements of
the Ethics Committee of Tianjin University of Traditional Chinese
Medicine (Tianjin, China), and the experimental methods were in line
with the principles for protection of laboratory animals.
Animal Grouping
After 7 days habituation, the rats were randomly divided into six
groups (n = 10) according to the similar sucrose preference, crossing
score and rearing score: the control group, CUMS group, low dose group
of GH (28 mg/kg), middle dose group of GH (56 mg/kg), high dose group
of GH (112 mg/kg), and Flu group (10 mg/kg).
Establishment of Chronic Unpredictable Mild Stress (CUMS) Model and Drug
Treatment
The CUMS procedure was carried out as described in the existing
literatures ([89]Zhong et al., 2018; [90]Lu et al., 2019). The animals,
except the control group, were separately placed and repeatedly exposed
to a set of CUMS as follows: restraint stress (4 h), noise environment
(110 dB, 1 h), electric shock to the foot (3 mA, one shock/5 s), tail
clamp (tail nipped at 1 cm from the tip of the tail for 3 min), damp
bedding (24 h), reversed light/dark cycle (24 h), high temperature
stress (40°C, 20 min), ice-cold swimming (4°C, 5 min), 45° tilted cage
(12 h), cage shaking (15 min), fasting food (24 h), water deprivation
(24 h). Two stressors were applied every day and the whole stress
procedure lasted for 5 weeks in a completely random order. During the
modeling period, rats in the GH group and the Flu group were
administrated with corresponding drugs; rats in the control group and
the CUMS group were administrated with saline. Rats in all group were
injected via gastric gavage at 10 ml/kg once daily.
Behavioral Tests
Sucrose Preference Test
Sucrose preference test (SPT) was conducted at the day 0 and day 35 in
accordance with previously described methods ([91]Zhu et al., 2017).
Briefly, 72 h before the test, the rats were bred individually two
bottles 1% sucrose solution for 24 h, which were aimed to adapt to
sucrose solution. Then, rats were exposed to one bottle of 1% sucrose
solution and one bottle of water for 24 h. Finally, water and food were
deprived for another 24 h. Sucrose preference test was conducted, in
which rats were placed in separate cages and were freely access to two
bottles containing sucrose solution (1%, w/v) and water, respectively.
After 24 h, the weight of solution in every bottle was measured, and
the rate of sucrose preference was calculated by the following formula:
[MATH:
Sucrose
prefer<
/mi>ence = sucros
e consu<
/mi>mtion <
/mrow>water consump
tion+su<
mi>crose consumtion×100%
:MATH]
Open Field Test
The open field test (OFT) was carried out at day 0 and day 35 according
to previously described methods ([92]Dai et al., 2010). The activity of
rats in each group were measured in a 100 cm × 100 cm × 50 cm box
without ceiling, the inner wall and floor of which were coated with
black paint. A video camera was used to record the rat behavior. The
rats were released from the center of the arena, and were observed for
3 min. The following behavioral parameters were taken into the account:
the crossing score (grid lines it crossed with at least three paws) and
the rearing score (defined as standing upright with hind legs). To
avoid the possible disturbance, the 75% alcohol was used to clean the
floor box before each test.
Hippocampus Sampling
The rats were sacrificed, 24 h after the behavioral tests. The whole
brain was quickly dissected from the rats in ice-cold saline. The
hippocampi were isolated on ice bath and immediately stored in liquid
nitrogen for enzyme-linked immunosorbent assay and western blot
analysis. All samples were stored at −80°C until assays.
Preparation of Samples and Standard Solution
Bulk substance of GH was weighed 100 mg precisely. The powder was
soaked in 20 ml methanol, extracted by ultrasonic at room temperature
for 30 min, and precipitated to 25 ml volume. A stock solution
containing ten standards (pseudoginsenoside RT5, 20(S)-ginsenoside Rh1,
20(R)-ginsenoside Rh1, 20(S)-ginsenoside F1, ginsenoside Rh4,
ginsenoside CK, 20(S)-ginsenoside Rh2, 20(R)-ginsenoside Rh2,
isoginsenoside Rh3 and ginsenoside Rk2) was prepared in methanol. All
samples were filtered through 0.22 µm nylon membrane filters and the
filtrate was analyzed directly by UPLC/IT-TOF.
UPLC/IT-TOF Conditions
The UPLC analysis was performed on a Shimadzu LC-20A (Shimadzu, Kyoto,
Japan) with a Waters Acquity UPLC HSS T3 column (2.1 × 100 mm, 1.8 μm).
The column temperature was set at 35°C. The flow rate was set at
0.44 ml/min. The target sample temperature is set at 10°C and 5 μL of
each sample was injected onto the column. The solvent system composed
of mobile phase A (water) and mobile phase B (acetonitrile) in the
following gradient: 0–9 min, 28–47%B; 9–17 min, 47–55%B; 17–22 min,
55–90%B; 22–24 min, 90–28%B; 24–25 min, 28–28%B. The experiment was
performed on both ESI (+) ionization mode. The desolvation temperature
was set at 200°C with desolvation gas flow set at 1.5 L/min. The
capillary voltage was sat at 4.5 KV for ESI (+). The full scan data
acquisition range was 100–1,300 Da. The LabSolutions-LCMS software
(Shimadzu, Kyoto, Japan) were employed for data analysis and the
chemical components of GH was identified.
Targets Fishing
The chemical components containing in GH identified by UPLC/IT-TOF were
filtered by integrating oral bioavailability (OB), drug similarity (DL)
from Traditional Chinese Medicine Systems Pharmacology Database
(TCMSP).[93] ^1 The chemical components that meet both of the
requirements OB ≥ 30%, DL ≥ 0.18, were retained as candidate active
ingredients ([94]Tao et al., 2013). The targets of candidate active
ingredients were obtained from Swiss Target Prediction[95] ^2
([96]Daina and Zoete, 2019). Species were selected as “Homo sapiens”
and the targets with probability greater than 0 were predicted as the
putative targets.
Known therapeutic targets acting on depression were collected from the
DrugBank[97] ^3 ([98]Knox et al., 2011). Therapeutic Target Database
(TTD)[99] ^4 ([100]Li et al., 2018) and Online Mendelian Inheritance in
Man (OMIM) database[101] ^5 ([102]Hamosh et al., 2005) with the keyword
“depression”. All targets enrolled in this research were human
genes/proteins.
Network Construction and Topological Analysis
Protein-protein interaction (PPI) data were obtained from STRING
database[103] ^6 ([104]Szklarczyk et al., 2017) with setting species as
“Homo sapiens” and the results were imported into the Cytoscape
software (version 3.7.1, Boston, MA, United States) where the
interaction network was constructed and analyzed. The topological
features were calculated using Network Analyzer and the nodes with
degree greater than twice the median degree of all nodes will be
defined as major targets ([105]Guo et al., 2020).
Pathway Enrichment Analysis
To explore potential mechanism of predicted major targets, the Kyoto
Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis
([106]Kanehisa et al., 2017) was performed using the Database
Visualization and Integrated Discovery (DAVID)[107] ^7 ([108]Huang et
al., 2007). KEGG pathways with enrichment p value less than 0.05 were
employed for further study.
Enzyme-Linked Immunoassay
Tissues from the rat hippocampus were homogenized by adding phosphate
buffered saline (PBS) at pH 7.4 (Solarbio Science &Technology Co.,
Ltd., Beijing, China). Homogenate was centrifuged at 4°C for 10 min at
12,000 rpm to obtain the supernatant. The supernatant was separated and
stored at −20°C until analysis. The concentration of 5-HT, DA, NE and
cAMP were measured using commercially available ELISA kits in
accordance with the manufacturer’s instructions. The absorbance at
450 nm was measured with a GloMax microplate reader (Promega, Madison,
WI, United States), and the measured OD values were used to quantify
the expression of the 5-HT, DA, NE and cAMP. All samples were
determined three times repeatedly in the same assay to minimize
inter-assay differences.
Assay of PKA Activity
PKA activity was assayed using a radioactive PKA assay kit in
accordance with the manufacturer’s instructions.
Western Blot
Hippocampus tissue (approximately 50 mg) was solubilized by radio
immunoprecipitation assay lysis buffer (Beijing, China) for 30 min on
ice. The buffer contained 1% phenylmethylsulphonyl fluoride (Beyotime,
China) and/or 1% phosphatase inhibitor. The pyrolysis products were
clarified by centrifuging at 4°C for 15 min at 12,000 rpm. The
supernatant was collected and the protein concentration was measured
with the bicinchoninic acid protein assay kit. Proteins were separated
by 10% sodium dodecyl sulfate polyacrylamide gel electrophoresis
(SDS-PAGE) and then were transferred to polyvinylidene difluoride
(PVDF) membranes, which were blocked in 5% nonfat milk or 5% BSA for
2 h and then washed three times with Tris Buffer Saline supplemented
with 0.1% Tween-20 (TBST) buffer for 10 min each time. The membranes
were incubated overnight at 4°C with primary antibodies BDNF (1:1,000
dilution), CREB (1:1,000 dilution), p-CREB (1:1,000 dilution), and rat
polyclonal antibody GAPDH (1:1,000 dilution). Subsequently, the
membranes were washed three times with TBST and were incubated for 2 h
at room temperature with suitable goat anti-rabbit immunoglobulin
G-horseradish peroxidase (IgG-HRP) secondary antibody (1:5,000
dilution). After rewashing with TBST, the immunoreactivity was observed
using ECL reagent. The membranes were scanned by using an imaging
system (Bio-Rad, Hercules, CA, United States) and the band strength was
analyzed by using ImageJ software (National Institutes of Health,
Bethesda, MD, United States).
Statistical Analysis
Date were expressed using the mean ± the standard deviation (SD). SPSS
version 21.0 software (IBM, Chicago, IL, United States) was used for
statistical analysis. One-way analysis of variance (ANOVA) was used,
and p value <0.05 was considered to be statistically significant.
Results
Establishment of CUMS Model and Antidepressant Effects of GH
In the study, CUMS rat model was established according to materials and
methods. At the same time, the rats were intragastric administration.
The antidepressant effects of GH were evaluated by the behavioral and
biochemical indexes.
The results of behavioral indexes of rats in each group were shown in
[109]Figures 2A–F, the sucrose preference, the crossing score and the
rearing score of rats in all groups were basically same at day 0 (p >
0.05, p > 0.05, p > 0.05, respectively). However, the sucrose
preference, the crossing score and the rearing score of the CUMS group
had a significant decrease compared with the control group at day 35 (p
< 0.01, p < 0.01, p < 0.01, respectively). The changes of the sucrose
preference, the crossing score and the rearing score of rats are
typical characteristics of depression, which indicated that the
establishment of depression model was successful. The sucrose
preference of rats in low dose group of GH, middle dose group of GH,
high dose group of GH, and Flu group were obviously higher than the
CUMS group (p < 0.05, p < 0.01, p < 0.01, p < 0.01, respectively),
showing the significant remission of depression symptoms. In the open
field test, the crossing score and the rearing score of CUMS rat
treated with middle dose of GH, high dose of GH, and Flu were markedly
increased compared with the CUMS group (p < 0.01, p < 0.05, p < 0.01,
respectively). However, there was no significant difference in crossing
score and rearing score between low dose group of GH and the CUMS group
(p > 0.05). Taken these results together, GH has antidepressant
effects, and the middle dose of GH showed powerfully inhibitory effects
on rats with depressant-like behavior induced by CUMS.
FIGURE 2.
[110]FIGURE 2
[111]Open in a new tab
Effect of GH on CUMS rats in SPT, OET and neurotransmitters levels in
hippocampus. (A) Sucrose preference of rats in each group at day 0. (B)
Crossing score of rats in each group at day 0. (C) Rearing score of
rats in each group at day 0. (D) Sucrose preference of rats in each
group at day 35. (E) Crossing score of rats in each group at day 35.
(F) Rearing score of rats in each group at day 35. (G) The
concentration of 5-HT in each group. (H) The concentration of DA in
each group. (I) The concentration of NE in each group. All data were
expressed as mean ± standard error of mean (n = 10). ##p < 0.01 versus
control group; *p < 0.05, *p < 0.01 versus CUMS group. GH-L (low dose
group of GH), GH-M (middle dose group of GH), GH-H (high dose group of
GH).
The results of biochemical indexes of rats in each group were
demonstrated in [112]Figures 2G–I. CUMS exposure significantly reduced
the concentration of 5-HT, DA and NE (p < 0.01, p < 0.01, p < 0.01,
respectively) compared with the control group, which indicated that the
establishment of depression model was successful. The treatments with
middle dose of GH, high dose of GH, and Flu significantly increased the
concentration of 5-HT (p < 0.01, p < 0.05, p < 0.01, respectively), DA
(p < 0.01, p < 0.05, p < 0.01, respectively) and NE (p < 0.01, p <
0.05, p < 0.01, respectively) compared with the CUMS group. Meanwhile,
the treatments with low dose of GH significantly increased the DA (p <
0.05) and NE (p < 0.05) concentration compared to the CUMS group.
However, low dose of GH had no significant effects on the 5-HT
concentration in the CUMS-exposed rats (p > 0.05). Overall, the results
indicated that middle dose of GH had better antidepressant effects. In
the following mechanism verification experiment, the study mainly
focused on the treatment group of GH at the middle dose (56 mg/kg).
Identification of Chemical Components in GH by UPLC/IT-TOF MS
The UPLC/IT-TOF conditions was systemically optimized to receive good
chromatographic separation and appropriate ionization. The total ion
chromatogram (TIC) of the GH sample and mixed standard sample in the
positive ion modes are, respectively, presented in [113]Figures 3A,B.
The 10 chemical components (component 3, 5, 6, 9, 15, 21, 23, 24, 27,
28) were identified as pseudoginsenoside RT5, 20(S)-ginsenoside Rh1,
20(R)-ginsenoside Rh1, 20(S)-ginsenoside F1, ginsenoside Rh4,
ginsenoside CK, 20(S)-ginsenoside, 20(R)-ginsenoside Rh2, ginsenoside
Rk2, isoginsenoside Rh3 by comparing the retention time, accurate and
high-resolution mass and tandem mass spectra with chemical standards
respectively. For the components without chemical standards, the
molecular formula was established based on high precision quasi
molecular ion such as [M+H]^+, [2M+H]^+or [M+Na]^+ within a mass error
of 5.0 ppm. Moreover, the MS^2 information was used for confirming the
structures of components by comparing the fragmentation regularity with
ten standards or the related literatures ([114]Patel et al., 2012;
[115]Zhu et al., 2018). Overall, a total of 28 chemical components were
identified in GH and the related information of retention times and MS
data was summarized in [116]Table 1. The structures of 16 compounds
related to 28 chemical components are displayed in [117]Figure 4.
FIGURE 3.
[118]FIGURE 3
[119]Open in a new tab
Total ion chromatogram (TIC) of GH sample (A) and mixed standard sample
(B) in positive ion mode using UPLC/IT-TOF MS.
TABLE 1.
Identification of chemical components in GH sample by UPLC/IT-TOF in
positive ion mode.
No tR (min) Formula Ion model Theoretical mass Measured mass Error
(ppm) MS^2 Components
1 3.429 C[30]H[54]O[6] [M+H]^+ [M+Na]^+ 511.3993,533.3813
511.3958,533.3778 −3.5–3.5 493.3876 [M+H-H[2]O]^+ 475.3807
[M+H-2H[2]O]^+ 457.3691 [M+H-3H[2]O]^+ 439.3573 [M+H-4H[2]O]^+ 421.3460
[M+H-5H[2]O]^+ Unknown
2 4.206 C[36]H[62]O[10] [M+H]^+ 655.4416 655.4391 −2.5 637.4292
[M+H-H[2]O]^+ 619.4224 [M+H-2H[2]O]^+ 475.3783 [M+H-H[2]O-glc]^+
457.3664 [M+H-2H[2]O-glc]^+ 439.3567 [M+H-3H[2]O-glc]^+ 421.3459
[M+H-4H[2]O-glc]^+ Pseudoginsenoside RT[4]
3[120] ^a 4.838 C[36]H[62]O[10] [M+H]^+ [M+Na]^+ 655.4416,677.4235
655.4390,677.4200 −2.6–3.5 457.3648 [M+H-2H[2]O-glc]^+ 439.3565
[M+H-3H[2]O-glc]^+ 421.3458 [M+H-4H[2]O-glc]^+ Pseudoginsenoside RT[5]
4 5.402 C[36]H[62]O[9] [M+H]^+ 639.4467 639.4463 −0.4 603.4249
[M+H-2H[2]O]^+ 441.3694 [M+H-2H[2]O-glc]^+ 423.3608 [M+H-3H[2]O-glc]^+
405.3521 [M+H-4H[2]O-glc]^+ Isomer of ginsenoside Rh[1]
5[121] ^a 5.655 C[36]H[62]O[9] [M+Na]^+ 661.4286 661.4274 −1.2 621.4345
[M+H-H[2]O]^+ 603.4256 [M+H-2H[2]O]^+ 477.3926 [M+H-glc]^+ 441.3687
[M+H-2H[2]O-glc]^+ 423.3604 [M+H-3H[2]O-glc]^+ 405.3518
[M+H-4H[2]O-glc]^+ 20(S)-ginsenoside Rh[1]
6[122] ^a 5.799 C[36]H[62]O[9] [M+Na]^+ 661.4286 661.4273 −1.3 621.4348
[M+H-H[2]O]^+ 603.4248 [M+H-2H[2]O]^+ 477.3911 [M+H-glc]^+ 441.3699
[M+H-2H[2]O-glc]^+ 423.3612 [M+H-3H[2]O-glc]^+ 405.3519
[M+H-4H[2]O-glc]^+ 20(R)- ginsenoside Rh[1]
7 6.268 C[36]H[62]O[9] [M+Na]^+ 661.4286 661.4275 −1.1 621.4347
[M+H-H[2]O]^+ 603.4254 [M+H-2H[2]O]^+ 441.3694 [M+H-2H[2]O-glc]^+
423.3606 [M+H-3H[2]O-glc]^+ 405.3512 [M+H-4H[2]O-glc]^+ Isomer of
ginsenoside Rh[1]
8 6.566 C[36]H[60]O[9] [M+H]^+ 637.4310 637.4283 −2.7 619.4206
[M+H-H[2]O]^+ 457.3651 [M+H-H[2]O-glc]^+ 439.3557 [M+H-2H[2]O-glc]^+
421.3463 [M+H-3H[2]O-glc]^+ 403.3338 [M+H-4H[2]O-glc]^+ Ginsenoside
Rh[5]
9[123] ^a 6.875 C[36]H[62]O[9] [M+H]^+ 639.4467 639.4446 −2.1 621.4326
[M+H-H[2]O]^+ 20(S)- ginsenoside F[1]
441.3684 [M+H-2H[2]O-glc]^+
423.3609 [M+H-3H[2]O-glc]^+
10 7.562 C[36]H[60]O[9] [M+H]^+ 637.4310 637.4297 −1.3 619.4240
[M+H-H[2]O]^+ 457.3703 [M+H-H[2]O-glc]^+ 439.3581 [M+H-2H[2]O-glc]^+
421.3461 [M+H-3H[2]O-glc]^+ Ginsenoside Rh[7]/Rh[8]/Rh[9]
11 7.793 C[36]H[60]O[9] [M+H]^+ 637.4310 637.4292 −1.8 619.4221
[M+H-H[2]O]^+ 457.3666 [M+H-H[2]O-glc]^+ 439.3565 [M+H-2H[2]O-glc]^+
421.3457 [M+H-3H[2]O-glc]^+ Ginsenoside Rh[7]/Rh[8]/Rh[9]
12 9.327 C[36]H[60]O[8] [M+H]^+ 621.4361 621.4349 −1.2 603.4246
[M+H-H[2]O]^+ 441.3687 [M+H-H[2]O-glc]^+ 423.3622 [M+H-2H[2]O-glc]^+
405.3535 [M+H-3H[2]O-glc]^+ Ginsenoside Rh[4]/Rk[3] or its isomer
13 9.517 C[36]H[60]O[8] [M+Na]^+ 643.4180 643.4183 0.3 603.4253
[M+H-H[2]O]^+ 441.3695 [M+H-H[2]O-glc]^+ 423.3614 [M+H-2H[2]O-glc]^+
405.3521 [M+H-3H[2]O-glc]^+ Ginsenoside Rh[4]/Rk[3] or its isomer
14 10.321 C[36]H[60]O[8] [M+H]^+ 621.4361 621.4380 1.9 441.3703
[M+H-H[2]O-glc]^+ 423.3613 [M+H-2H[2]O-glc]^+ 405.3521
[M+H-3H[2]O-glc]^+ Ginsenoside Rh[4]/Rk[3] or its isomer
15[124] ^a 10.547 C[36]H[60]O[8] [M+H]^+ 621.4361 621.4326 −3.5
603.4245 [M+H-H[2]O]^+ 441.3698 [M+H-H[2]O-glc]^+ 423.3612
[M+H-2H[2]O-glc]^+ 405.3515 [M+H-3H[2]O-glc]^+ 341.2817
[2glc+H[2]O-H]^+ Ginsenoside Rh[4]
16 10.924 C[36]H[60]O[8] [M+H]^+ 621.4361 621.4342 −1.9 603.4233
[M+H-H[2]O]^+ 441.3699 [M+H-H[2]O-glc]^+ 423.3612 [M+H-2H[2]O-glc]^+
405.3510 [M+H-3H[2]O-glc]^+ 343.2977 [2glc+H[2]O+H]^+ 325.2893
[2glc+H]^+ Ginsenoside Rh[4]/Rk[3] or its isomer
17 11.866 C[36]H[62]O[8] [M+H]^+ 623.4517 623.4485 −3.2 605.4379
[M+H-H[2]O]^+ 587.4325 [M+H-2H[2]O]^+ 443.3880 [M+H-H[2]O-glc]^+
425.3761 [M+H-2H[2]O-glc]^+ 407.3653 [M+H-3H[2]O-glc]^+ Isomer of
ginsenoside Rh[2]
18 14.333 C[36]H[62]O[8] [M+H]^+ 623.4517 623.4484 −3.3 605.4428
[M+H-H[2]O]^+ 587.4309 [M+H-2H[2]O]^+ 425.3758 [M+H-2H[2]O-glc]^+
Isomer of ginsenoside Rh[2]
19 14.912 C[36]H[60]O[8] [M+H]^+ 621.4361 621.4331 −3.0 603.4266
[M+H-H[2]O]^+ 585.4148 [M+H-2H[2]O]^+ 441.3716 [M+H-H[2]O-glc]^+
423.3611 [M+H-2H[2]O-glc]^+ 405.3511 [M+H-3H[2]O-glc]^+ Ginsenoside
Rh[4]/Rk[3] or its isomer
20 16.699 C[36]H[60]O[8] [M+H]^+ 621.4361 621.4345 −1.6 603.4254
[M+H-H[2]O]^+ 585.4178 [M+H-2H[2]O]^+ 441.3703 [M+H-H[2]O-glc]^+
423.3614 [M+H-2H[2]O-glc]^+ 405.3509 [M+H-3H[2]O-glc]^+ Ginsenoside
Rh[4]/Rk[3] or its isomer
21[125] ^a 18.035 C[36]H[62]O[8] [M+H]^+ [M+Na]^+ 623.4517,645.4337
623.4482,645.4407 −3.5 7.0 605.4400 [M+H-H[2]O]^+ 587.4305
[M+H-2H[2]O]^+ 443.3866 [M+H-H[2]O-glc]^+ 425.3755 [M+H-2H[2]O-glc]^+
407.3670 [M+H-3H[2]O-glc]^+ Ginsenoside CK
22 18.809 C[36]H[62]O[8] [2M+H]^+ 1,245.8962 1,245.8940 −2.2 587.4286
[M+H-2H[2]O]^+ 425.3749 [M+H-2H[2]O-glc]^+ 407.3656 [M+H-3H[2]O-glc]^+
Isomer of ginsenoside Rh[2]
23[126] ^a 19.127 C[36]H[62]O[8] [M+Na]^+ [2M+H]^+ 645.4337 1,245.8962
645.4323 1,245.8922 −1.4–4.0 605.4396 [M+H-H[2]O]^+ 587.4279
[M+H-2H[2]O]^+ 425.3741 [M+H-2H[2]O-glc]^+ 407.3661 [M+H-3H[2]O-glc]^+
20(S)-ginsenoside Rh[2]
24[127] ^a 19.367 C[36]H[62]O[8] [M+Na]^+ [2M+H]^+ 645.4337 1,245.8962
645.4333 1,245.8895 −0.4–6.7 605.4403 [M+H-H[2]O]^+ 587.4296
[M+H-2H[2]O]^+ 425.3751 [M+H-2H[2]O-glc]^+ 407.3652 [M+H-3H[2]O-glc]^+
20(R)-ginsenoside Rh[2]
25 20.349 C[36]H[62]O[8] [M+Na]^+ 645.4337 645.4316 −2.1 605.4405
[M+H-H[2]O]^+ 587.4301 [M+H-2H[2]O]^+ 443.3876 [M+H-H[2]O-glc]^+
425.3750 [M+H-2H[2]O-glc]^+ 407.3667 [M+H-3H[2]O-glc]^+ Isomer of
ginsenoside Rh[2]
26 20.659 C[36]H[62]O[8] [2M+H]^+ 1,245.8962 1,245.8914 −4.8 587.4309
[M+H-2H[2]O]^+ 443.3858 [M+H-H[2]O-glc]^+ 425.3751 [M+H-2H[2]O-glc]^+
407.3648 [M+H-3H[2]O-glc]^+ Isomer of ginsenoside Rh[2]
27[128] ^a 21.328 C[36]H[60]O[7] [M+H]^+ 605.4412 605.4398 −1.4
587.4308 [M+H-H[2]O]^+ 543.4216 [M+H-H[2]O-CO[2]]^+ 443.3841
[M+H-glc]^+ 425.3750 [M+H-H[2]O-glc]^+ 407.3655 [M+H-2H[2]O-glc]^+
Ginsenoside Rk[2]
28[129] ^a 21.547 C[36]H[60]O[7] [M+Na]^+ 605.4412 605.4426 1.4
587.4328 [M+H-H[2]O]^+ 425.3748 [M+H-H[2]O-glc]^+ 407.3657
[M+H-2H[2]O-glc]^+ Isoginsenoside Rh[3]
[130]Open in a new tab
^a
Accurately identified with reference standards.
FIGURE 4.
[131]FIGURE 4
[132]Open in a new tab
Structures of compounds in GH.
PPI Network Construction
Among the 16 compounds, only 20(S)-ginsenoside Rh2 satisfied the
screening rules, OB ≥ 30% and DL ≥ 0.18. So, 20(S)-ginsenoside Rh2 was
selected as active ingredient. Detailed information about OB and DL of
16 compounds was shown in [133]Supplementary Table S1. The structure of
20(S)-ginsenoside Rh2 was used for predicting the putative targets in
Swiss Target Prediction database. Totally, 43 putative targets of
20(S)-ginsenoside Rh2 containing in GH were predicted. Detailed target
information about putative targets was shown in [134]Supplementary
Table S2. A total of 5 and 43 known therapeutic targets for depression
were collected from DrugBank and Therapeutic Target Database (TTD)
database, respectively, and 184 known targets of depression were
obtained from OMIM database. In total, 230 depression candidate targets
were enrolled after removing redundant entries. The detailed
information is supplemented in [135]Supplementary Table S3. The PPI
network of the 43 putative targets of 20(S)-ginsenoside Rh2 containing
in GH and the 230 depression candidate targets, was established based
on STRING database, consisting of 184 nodes and 1,392 edges. Detailed
information about this network was reflected in [136]Supplementary
Table S4.
Network and Pathway Analysis
Network analyzer was employed to calculate the topological feature
degree of the nodes in the PPI network. Nodes with degrees higher than
two-fold median value of all nodes in the network (degree >23) were
identified as the major targets. Consequently, 47 major targets were
extracted. Among them, 29 targets were putative targets of
20(S)-ginsenoside Rh2 containing in GH, 32 targets were depression
candidate targets, 15 targets were common targets, which were between
putative targets of GH and depression candidate targets. The details
were shown in [137]Supplementary Table S5.
In order to analyze the representative pathways related to the major
targets, KEGG pathway analysis was performed to explore the potential
pathways effected by GH and totally 45 significant pathways (p value
<0.05) were obtained. The top 10 signal pathways were selected by p
value for further study and were as shown in [138]Figure 5A. The top 10
significant pathways could be divided into three functional modules,
which were related to dopamine, hypothalamic-pituitary-adrenal (HPA)
axis and neural plasticity respectively. Detailed information about
results of pathways analysis was provided in [139]Supplementary Table
S6. Afterward a network consisted of the interactions between the
active ingredient of GH, major targets, and top 10 significant pathways
was constructed to illustrate the potential mechanism ([140]Figure 5B).
This network illustrated that GH may indirectly influence or directly
interact with major targets which are involved in pathways related to
HPA axis (such as pathways in cancer, proteoglycans in cancer),
dopamine (such as neuroactive ligand-receptor interaction, cocaine
addiction, dopaminergic synapse) and neural plasticity (such as cAMP
signaling pathway, glutamatergic synapse, gap junction, PI3K-Akt
signaling pathway and estrogen signaling pathway) to achieve the
antidepressant effects.
FIGURE 5.
[141]FIGURE 5
[142]Open in a new tab
The network pharmacological results associating with GH in the
treatment of depression. (A) KEGG pathway analysis of major targets.
X-axis shows ratio and Y-axis shows involved pathways. Count and p
value are shown on right. (B) Network of active ingredient in GH, major
targets, the corresponding pathways and pharmagological effects. Orange
oval nodes represent active ingredient in GH, yellow rectangle nodes
represent related major targets of active ingredient in GH, pink
rectangle nodes represent related major targets of depression, green
rectangle nodes represent common major targets for both GH and
depression, grey rectangle node represents other target, red rectangle
nodes represent involved pathways from enrichment analysis of major
targets, edges represent interactions among them.
Experimental Validation of Major Targets and Pathway
To explore the effects of GH on the cAMP pathway, we examined the
concentration of cAMP via ELISA, PKA activity using a radioactive PKA
assay kit, and protein expression levels of BDNF, CREB, p-CREB in the
hippocampus of each group rats by Western blot ([143]Figure 6).
Compared with the control group, a significant decrease in cAMP
concentration and PKA activity was observed in the hippocampus of the
CUMS group (p < 0.01, p < 0.01, respectively), but daily administration
of GH (56 mg/kg) or fluoxetine (10 mg/kg) obviously increased cAMP
concentration and PKA activity in the hippocampus (p < 0.01, p < 0.01,
respectively) compared with the CUMS rats. Meanwhile, BDNF expression
levels and the p-CREB/CREB ratio in the hippocampus of the CUMS group
were decreased (p < 0.01, p < 0.01, respectively). Following treatment
with GH (56 mg/kg) or fluoxetine (10 mg/kg), BDNF expression levels and
the p-CREB/CREB ratio in the GH and Flu groups were significantly
higher than the CUMS group (p < 0.01, p < 0.01, respectively),
suggesting that GH may regulate the cAMP-PKA-CREB-BDNF signal pathway
to play an antidepressant role.
FIGURE 6.
[144]FIGURE 6
[145]Open in a new tab
Experimental validation of target proteins involed in cAMP signaling
pathway in the hippocampus of CUMS-induced rats. (A) Effect of GH
treatment on cAMP concentrations (n = 10). (B) Effect of GH treatment
on PKA activity (n = 10). (C) Effect of GH treatment on BDNF
expression. (D) Effect of GH treatment on p-CREB/CREB ratio. All data
were expressed as mean ± standard error of mean. ##p < 0.01 versus
control group; *p < 0.05, **p < 0.01 versus CUMS group.
Discussion
Depression is a mental disease characterized by constant low mood, loss
of interest, anhedonia, unresponsiveness and sleeplessness ([146]Wang
et al., 2017). The causes of depression are complex, among which the
increasing competitive pressure, unreasonable living habits and weak
adaptability to the social environment are more crucial inducing
factors ([147]Wang et al., 2020). The CUMS is a mature animal model of
depression that can simulate the chronic stress encountered by
depressed patients in clinical observation ([148]Yang et al., 2018).
Currently, the widely used assays for depressive-like behaviors include
the Sucrose preference test (SPT) and the Open field test (OFT). The
SPT could mimic anhedonia-like behavior, a core symptom of depression
in human ([149]Sideromenos et al., 2020), and the OFT was used to
determine general activity and exploratory behavior, signs of
depression ([150]Adelöf et al., 2018). Thus, the study established CUMS
rat model and conducted a series of behavioral tests, including SPT and
OFT, to study the effects of GH on antidepressant-like behaviors. The
results of behavioral indexes of rats in each group indicated that GH
has antidepressant effects, and the middle dose of GH showed powerfully
inhibitory effects on rats with depressant-like behavior induced by
CUMS.
Based on the characteristics of multi-channel and multi-target effects
of Chinese herbal compound, the monoamine neurotransmitters such as DA,
NE and 5-HT were regarded as the biochemical indexes to further study
the antidepressant effects of GH ([151]Gu et al., 2018). The monoamine
hypothesis believes that the deficiency of major monoamine
neurotransmitters (5-HT, DA, and NE) will lead to decrease of
neurotransmission in the brain and the impairment of cognitive
performance which may lead to depression ([152]Kofler et al., 2019).
Therefore, this study established a CUMS rat model for five weeks to
observe the effects of GH intervention on the depressive-like behaviors
and the changes of the monoamine neurotransmitters levels in the
hypothalamus. The results of biochemical indexes of rats in each group
indicated that GH has antidepressant effects, and middle dose of GH had
stronger antidepressant effect. In the following mechanism verification
experiment, the study mainly focused on the treatment group of GH at
the middle dose (56 mg/kg).
Chromatographic techniques coupled with mass spectrometry has been an
available method for rapid identification of components in Chinese
medicine ([153]Guo et al., 2018). UPLC/IT-TOF MS analysis was performed
to identify the chemical components in GH. In this study, the 28
chemical components of GH were identified. Among the chemical
components, only 20(S)-ginsenoside Rh2 was selected as active
ingredient which satisfied the screening rules, OB ≥ 30% and DL ≥ 0.18.
It is consistent with previous studies that ginsenoside Rh2, a main
component in GH ([154]Zhou et al., 2014), was a detectable compound in
human plasma ([155]Yue et al., 2019), and it can be filtered out by
cell membrane chromatography ([156]Ma et al., 2018).
To investigate the pharmacological mechanism of antidepressant effects
of GH, 20(S)- ginsenoside Rh2, the active ingredient of GH, was used
for network pharmacological analysis, and the top 10 significant
signaling pathways were enriched by KEGG according to the p value.
Based on literature search, the top 10 significant signaling pathways
could involve in the occurrence of depression in varying degrees. For
example, pathways in cancer and proteoglycans in cancer indirectly
change the probability of depression by influencing HPA axis function
([157]Young and Singh, 2018); Neuroactive ligand-receptor interaction,
cocaine addiction and dopaminergic synapse could affect the occurrence
of depression through regulating dopamine levels, emotion, learning and
memory functions ([158]Haile et al., 2007; [159]Yang et al., 2017;
[160]Sun et al., 2018); cAMP signaling pathway, PI3K-Akt signaling
pathway, estrogen signaling pathway, glutamatergic synapse and gap
junction could intervene the occurrence of depression by mediating
neural plasticity ([161]Hennebelle et al., 2014; [162]Crider and
Pillai, 2017; [163]Peng et al., 2018; [164]Ren et al., 2018; [165]Wu et
al., 2018).
At present, the antidepressant mechanism of GH is unknown. Among the
top 10 signaling pathways predicted by network pharmacological, the
signaling pathway ranking at the top had strong correlation with the
antidepressant effects of GH, which is the main signaling pathway of
the antidepressant mechanism of GH. Therefore, the signaling pathway
ranking at the top has more research value ([166]Xiong et al., 2020).
The first signaling pathway is neuroactive ligand-receptor interaction,
which was related to all receptors and ligands associated with
intracellular and extracellular signaling pathways in the plasma
membrane ([167]Pan et al., 2011). However, the neuroactive
ligand-receptor interaction signaling pathway was related to the
occurrence of various diseases, the mechanism of action on depression
is not specific, and there are only two targets of receptor and ligand.
Consequently, the first signaling pathway was not selected to further
research. The second signaling pathway is cAMP signaling pathway, which
was the most widely studied signaling pathway in the mechanism of
antidepressant effects. In the cAMP signaling pathway, BDNF, the
terminal downstream protein neurotrophic factor, could resist the
damage of neurons, promote the repair and regeneration of neurons, and
increased the secretion of monoamine neurotransmitters. Hence, Stress
events compromise neuroplasticity via reduction of BDNF and lead to the
occurrence of depression ([168]Schmitt et al., 2016). According to the
literature, neuroimaging and post-mortem studies have revealed impaired
cAMP signaling in depressive patients, indicating cAMP signaling
pathway was significantly associated with depression ([169]Plattner et
al., 2015). Thus, cAMP signaling pathway is selected to study the
antidepressant mechanism of GH.
It is extremely clear that the mechanism of the cAMP signal pathway on
depression. Under normal physiological conditions, monoamine
neurotransmitters (such as 5-HT, DA, NE) interacts with specific G
protein-coupled receptors (including 5-HT receptors, DA receptors, NE
receptors) on the cell membrane to activate G protein
([170]Cabrera-Vera et al., 2003; [171]Fredriksson et al., 2003). The
G-protein binds to Guanosine triphosphate (GTP) and subsequently GTP-G
protein binds to the C2 domain and activates the adenylate cyclase (AC)
enzyme. Activated AC catalyzes the biosynthesis of cAMP from adenosine
triphosphate (ATP) ([172]Frezza et al., 2018). The cAMP binds to the
regulatory subunits of PKA (a tetramer consists of two regulatory
subunits and two catalytic subunits), which resulted in the
dissociation of catalytic subunit of PKA and enter to the cell nucleus
([173]Wang et al., 2018). In the nucleus, the catalytic subunit of PKA
binds to the Ser-133 site of CREB and phosphorylates CREB ([174]Tu et
al., 2019). Phosphorylated CREB (p-CREB) combines with the cAMP
responsive elements (CRE) in the promoter region of BDNF, which can
regulate BDNF transcription ([175]Björkholm and Monteggia, 2016). Under
the pathological conditions, continuous mental stress and stimulation
would lead to the decrease in the content of monoamine
neurotransmitters in the patient’s body and weaken the transduction of
cAMP signaling pathway, which cause the decrease of BDNF expression
([176]Zhang et al., 2012). Lower expression of BDNF is difficult to
resist the injury of neurons under stress, which could lead to
depression ([177]van den Buuse et al., 2020).
In cAMP signaling pathway, 11 target proteins, such as BDNF, GRIA1,
CREB1, ADORA1 and so on, were enriched. The high-degree target proteins
in the network may account for the essential therapeutic effects of GH
on depression ([178]Guo et al., 2019). The degree value of BDNF is the
largest, indicating that BDNF is the most important in cAMP signaling
pathway. BDNF is related to the survival, growth, and differentiation
of neurons, and plays an important role in the signal transduction of
depression ([179]Wang et al., 2017). As the upstream protein of BDNF,
p-CREB could regulate the expression of BDNF. At the same time, CREB
has been confirmed to be related to the pathogenesis of depression and
is one of the transcription factors with the most research on
antidepressant effects ([180]Wang et al., 2018). Therefore, Western
blot was used to determine the expression level of BDNF and the ratio
of p-CREB/CREB to study the antidepressant mechanism of GH. The results
showed that GH significantly increased the expression level of BDNF and
the ratio of p-CREB/CREB in the hippocampus of CUMS model rats. In
order to further study the antidepressant mechanism of GH, the
radioactive PKA assay kit was used to assay the activity of PKA which
is the upstream protein of CREB. ELISA was used to detect the contents
of cAMP which is the activator of PKA. As shown in our results, GH
significantly upregulated the activity of PKA and the content of cAMP
in hippocampus of CUMS model rats. Therefore, GH may play an
antidepressant effects by regulating cAMP-PKA-CREB-BDNF signaling
transduction. The cAMP-PKA-CREB-BDNF signaling pathway was presented in
[181]Figure 7.
FIGURE 7.
[182]FIGURE 7
[183]Open in a new tab
The cAMP-PKA-CREB-BDNF signaling pathway.
Fluoxetine, a serotonin reuptake inhibitor (SSRI), is mainly used in
the treatment of depression in clinic, which can improve the content of
5-HT. The 5-HT combined with its receptors, which resulted in that the
cAMP signal pathway is activated and the levels of cAMP, PKA and the
ratio of p-CREB/CREB were increased ([184]Mato et al., 2010; [185]Zhang
et al., 2018). Then the expression level of BDNF is increased, which
resisted the injury of neurons under stress, and exert antidepressant
effects ([186]Xie et al., 2019). During this process, BDNF increased
the content of monoamine neurotransmitters by improving the activity of
dopaminergic neurons and noradrenergic neurons, which is more conducive
to play an antidepressant effects ([187]Siuciak et al., 1996;
[188]Zhang et al., 2007), Therefore, fluoxetine was selected as a
positive drug to explore whether GH exerts antidepressant effects by
activating the cAMP signal pathway. The results indicated that GH could
activate cAMP signaling pathway to play an antidepressant role, but
whether it has the same antidepressant mechanism as fluoxetine through
increasing 5-HT content and activating cAMP signaling pathway remains
to be further studied.
Conclusion
In the present study, an integrative pharmacology-based pattern, which
adopted pharmacodynamics-network pharmacology-mechanism verification,
was used to uncover the pharmacological mechanism of GH against
depression. Firstly, it was found that GH at the middle dose (56 mg/kg)
obviously alleviated depression-like behaviors induced by CUMS and
showed powerful antidepressant effects. Then, we identified 28 main
chemical components of GH by UPLC/IT-TOF MS. Furthermore, network
pharmacology analysis predicted that cAMP signaling pathway may be the
potential pharmacological mechanism regulated by GH acting on
depression. Finally, the cAMP signaling pathway was verified as the
mechanism of GH against depression through experimental validation of
the target proteins (cAMP, PKA, p-CREB, and BDNF). Taken together, the
current study suggested that GH could exert antidepressant effects by
activating the cAMP-PKA-CREB-BDNF signaling pathway in hippocampus,
which provided an effective method to uncover the pharmacological
mechanism of traditional Chinese medicine.
Data Availability Statement
The raw data supporting the conclusions of this article will be made
available by the authors, without undue reservation, to any qualified
researcher.
Ethics Statement
The animal study was reviewed and approved by Tianjin University of
Traditional Chinese Medicine Animal Care Committee.
Author Contributions
LZ performed the experiments, drafted and modified the manuscript. RG,
NC, YL, and XM analyzed the data and modified the manuscript. SP and WY
prepared the materials of the paper. YZ, YL, and ZS conceived or
designed the studies. WD, XX, and CL contributed to research design,
experimental setup, results monitoring, and manuscript correction. All
the authors read and approved the final manuscript.
Funding
The research was supported by the National Natural Science Foundation
of China (81973557), Natural Science Fund of Tianjin City
(20JCZDJC00010), and the National Major Scientific and Technological
Special Project of China (2018ZX09303-024, 2018ZX09737-019).
Conflict of Interest
The authors declare that the research was conducted in the absence of
any commercial or financial relationships that could be construed as a
potential conflict of interest.
Acknowledgments