Lanlan Wu1,2, Chang Chen1, Yongbiao Li1,2, Cong Guo1, Yuqing Fan1,2, Dingrong Yu1, Tinglan Zhang1,2, Binyu Wen3, Zhiyong Yan2, An Liu1. 1. Key Laboratory of Beijing for Identification and Safety Evaluation of Chinese Medicine, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, No. 16 Nanxiaojie, Dongzhimennei, Beijing 100700, P. R. China. 2. School of Life Science and Engineering, Southwest Jiao Tong University, No. 111, North Section, Second Ring Road, Jinniu District, Chengdu 610031, Sichuan, P. R. China. 3. Dongfang Hospital, Beijing University of Chinese Medicine, No. 6, District 1, Fangxingyuan, Fangzhuang, Fengtai, Beijing 100078, P. R. China.
Abstract
Nuciferine is an aporphine alkaloid monomer that is extracted from the leaves of the lotus species Nymphaea caerulea and Nelumbo nucifera Gaertn. Nuciferine was reported to treat cerebrovascular diseases. However, the potential mechanism of the neuroprotective effects of nuciferine at the metabolomics level is still not unclear. The present research used neurological score, infarct volume, cerebral water content, and ultraperformance liquid chromatography to quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS)-based serum metabolomics to elucidate the anti-ischemic stroke effect and mechanisms of nuciferine. The results showed that nuciferine significantly improved neurological deficit scores and ameliorated cerebral edema and infarction. Multivariate data analysis methods were used to examine the differences in serum endogenous metabolism between groups, and the biomarkers of nuciferine on ischemic stroke were identified. Approximately 19 metabolites and 7 metabolic pathways associated with nuciferine on treatment of stroke were found, which indicated that nuciferine exerted a positive therapeutic action on cerebral ischemic by regulating metabolism. These results provided some data support for the study of anti-stroke effect of nuciferine from the perspective of metabolomics.
Nuciferine is an aporphine alkaloid monomer that is extracted from the leaves of the lotus species Nymphaea caerulea and Nelumbo nucifera Gaertn. Nuciferine was reported to treat cerebrovascular diseases. However, the potential mechanism of the neuroprotective effects of nuciferine at the metabolomics level is still not unclear. The present research used neurological score, infarct volume, cerebral water content, and ultraperformance liquid chromatography to quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS)-based serum metabolomics to elucidate the anti-ischemic stroke effect and mechanisms of nuciferine. The results showed that nuciferine significantly improved neurological deficit scores and ameliorated cerebral edema and infarction. Multivariate data analysis methods were used to examine the differences in serum endogenous metabolism between groups, and the biomarkers of nuciferine on ischemic stroke were identified. Approximately 19 metabolites and 7 metabolic pathways associated with nuciferine on treatment of stroke were found, which indicated that nuciferine exerted a positive therapeutic action on cerebral ischemic by regulating metabolism. These results provided some data support for the study of anti-stroke effect of nuciferine from the perspective of metabolomics.
Globally, stroke is
one of the most serious diseases threatening
human life and health, and approximately 87% of stroke cases belong
to the ischemic category.[1,2] Among different stroke
types, ischemic stroke has the highest rates of morbidity, disability,
and mortality.[3] The etiology of ischemic
disease is associated with internal carotid artery occlusion and stenosis.[4] Increasing evidence shows that excitatory amino
acid toxicity, energy failure, metabolic disorders, and inflammation
are the main causes of stroke.[5] Stroke
treatment options and the therapeutic time window are extremely limited
in clinical practice.[6] Therefore, only
a few patients who are in the right place within the right time frame
can be treated after the onset of symptoms. Moreover, a series of
severe side effects accompany treatment measures, such as postperfusion
lesions and hemorrhage, which hinder the effective treatment of patients
and may aggravate the disease.[7] Therefore,
better treatment and fewer adverse reactions are urgently needed to
overcome the clinical therapeutic limitations. Traditional Chinese
medicine (TCM) has been used to treat ischemic stroke for thousands
of years.[8−10] Some studies confirmed that the safety, effectiveness,
and multitarget characteristics of TCM have significant advantages
in the treatment of ischemic stroke.[11−13]Lotus is a famous
Chinese medicine with high nutritional and medicinal
value, and it was initially recorded in the Chinese Pharmacopoeia.
Previous studies found many bioactive alkaloids in lotus leaf, primarily N-nornuciferine, neferine, and nuciferine. Nuciferine ((R)-1, 2-dimethoxyaporphine; Nuci) is a major natural bioactive
alkaloid containing an aromatic ring and was widely used in ancient
China and India. Nuciferine is used to improve hepatic lipid metabolism,[14] and it exhibits anti-inflammatory,[15] antimicrobial,[16] antioxidant,[17] and antifibrosis[18] activity, as well as other cardiovascular-protective actions.[19] Nuciferine enters the brain through the blood–brain
barrier.[20] However, an overview of the
research both domestically and abroad revealed few studies on the
anti-stroke properties and the mechanism of action of nuciferine,
and our understanding of endogenous substance-related metabolism in
the state of cerebral ischemia is also poor. Therefore, we focused
on the monomer component of effective TCM, nuciferine, to clarify
its anti-ischemic stroke mechanism.Metabolomics is a universally
applicable method for the comprehensive
metabolic profiling of biological samples that reflects the overall
functional state of the body and monitors disease progression according
to dynamic changes in metabolites.[21] Ultraperformance
liquid chromatography to quadrupole time-of-flight mass spectrometry
(UPLC-Q-TOF/MS) is a premier tool for investigating the curative effects
of Chinese medicine, and it is used to measure small molecules in
biological samples, including serum, urine, and feces, and to describe
metabolic abnormalities during pathological processes.[22] Therefore, UPLC-Q-TOF/MS-based metabolomics
was used to screen and identify biomarkers and metabolic pathways
related to ischemic stroke in this study, and the mechanism of the
anti-ischemic action of nuciferine was preliminarily studied at the
level of small molecular metabolites, which provide supporting data
for further study.In the present study, the metabolic profiles
of serum samples from
nuciferine-treated and untreated rats were analyzed to screen potential
biomarkers of brain damage and explore neuroprotective potential of
nuciferine. Then, the metabolic pathways and characteristic metabolites
associated with ischemic stroke were explored by combining the pharmacodynamic
index and metabolic markers to clarify anti-stroke mechanisms of action
of nuciferine.
Results
Effects of Nuciferine on
Neurological Deficit Scores, Infarct
Volume, and Cerebral Water Content after MCAO in Rats
To
evaluate the protective effect of nuciferine on cerebral ischemia,
the MCAO model was established, and data from behavioral and pharmacodynamics
support its success. The present study statistically analyzed the
neurological function scores of rats (Figure A). After the MCAO surgical intervention,
the scores of the MCAO group significantly increased compared to those
in the sham group (P < 0.001), which verified
the stability of the MCAO model. The scores of rats decreased in all
administration groups, and the scores of the Nuci-H, Nuci-M, and EGb
761 groups significantly decreased (P < 0.01, P < 0.05).
Figure 1
Anti-ischemic cerebral effects of different
doses of nuciferine
in MCAO rats. Results of neurological deficit scores (A), infarct
volume (B, C), and cerebral water content (D) (n =
11 per group). All groups were administered intragastrically 30 min
prior to MCAO. Neurological deficit scores were dramatically higher
than the sham group after MCAO (P < 0.001). However,
pretreatment with EGb 761 and a high dose of nuciferine significantly
reduced the scores (P < 0.01). (B) TTC staining
photograph. Red, healthy tissue; white, infarcted tissue. (C, D) Quantitative
analyses of infarct volume and brain water content, respectively.
After administration of Nuci-H, infarct volume, and cerebral water
content decreased (P < 0.001 or P < 0.05). Data are expressed as mean ± SD. #P < 0.05, ##P < 0.01, ###P < 0.001 vs sham group; *P < 0.05, **P < 0.01, ***P < 0.001 vs MCAO group.
Anti-ischemic cerebral effects of different
doses of nuciferine
in MCAOrats. Results of neurological deficit scores (A), infarct
volume (B, C), and cerebral water content (D) (n =
11 per group). All groups were administered intragastrically 30 min
prior to MCAO. Neurological deficit scores were dramatically higher
than the sham group after MCAO (P < 0.001). However,
pretreatment with EGb 761 and a high dose of nuciferine significantly
reduced the scores (P < 0.01). (B) TTC staining
photograph. Red, healthy tissue; white, infarcted tissue. (C, D) Quantitative
analyses of infarct volume and brain water content, respectively.
After administration of Nuci-H, infarct volume, and cerebral water
content decreased (P < 0.001 or P < 0.05). Data are expressed as mean ± SD. #P < 0.05, ##P < 0.01, ###P < 0.001 vs sham group; *P < 0.05, **P < 0.01, ***P < 0.001 vs MCAO group.MCAO induced brain injury, which primarily manifested
as cerebral
infarct (Figure B,C)
and edema (Figure D). Rats pretreated with Nuci-H showed significantly smaller infarct
volumes than the MCAO group (P < 0.001), as rats
pretreated with Nuci-M (P < 0.05) (Figure B,C). The quantitative statistical
results of cerebral edema in all groups are shown in Figure D, which indicated that MCAO
remarkably increased the cerebral water content (cerebral edema) compared
to that in the sham group (P < 0.001). After treatment
with Nuci-H and EGb 761, the cerebral water content was significantly
reduced (P < 0.05).
UPLC-Q-TOF/MS Analysis
of Serum
According to the neurological
deficit score, infarct volume, and cerebral water content results,
the MCAO group, sham group, and Nuci-H group were selected for serum
metabolomics analysis.After MCAO model preparation and drug
intervention, the levels of metabolites may change. Serum chromatograms
were obtained using the UPLC-Q-TOF/MS system, including positive-
and negative-ion modes. Figure A,B presents the positive- and negative-ion chromatograms,
respectively, for the sham group, MCAO group, and Nuci-H group.
Figure 2
Representative
base peak intensity (BPI) chromatograms of the rat
serum from the treatment groups. The peaks were acquired via analyses
of serum samples of different groups in positive (A) and negative
(B) modes. (A) (ESI+) and (B) (ESI–)
from top to bottom show the sham group, MCAO group, and Nuci-H group.
Representative
base peak intensity (BPI) chromatograms of the rat
serum from the treatment groups. The peaks were acquired via analyses
of serum samples of different groups in positive (A) and negative
(B) modes. (A) (ESI+) and (B) (ESI–)
from top to bottom show the sham group, MCAO group, and Nuci-H group.
Metabolomics Profiling and Multivariate Statistical
Analysis
To reveal the effects of nuciferine on the metabolic
pattern of
MCAOrats, the raw data of the sham group, MCAO group, and Nuci-H
group were analyzed using principal component analysis (PCA) and orthogonal
projections to latent structures discriminant analysis (OPLS-DA).
The PCA mainly presents obvious clustering characteristics from the
complex and multivariate results, which indicate certain differences
in the levels of metabolites. The PCA score plots of the serum samples
of the rats are shown in Figure A,B, and there was good separation among the sham,
MCAO, and Nuci-H groups, which indicated that the MCAO model significantly
disturbed the levels of endogenous metabolites and that nuciferine
administration tended to correct the metabolite levels of MCAOrats.
Figure 3
PCA score
based on rat serum samples in the sham, MCAO, and Nuci-H
groups, including ESI+ (A) and ESI– (B)
modes. Every dot represents an animal, and the colors indicate different
treatment groups. S-plot of OPLS-DA for the sham group versus the
MCAO group, the MCAO group vs. the Nuci-H group in ESI+ (C, D) and ESI– (E, F) modes. The black square
represents a different metabolite, and the red square indicates that
this endogenous metabolite with variables with importance parameter
(VIP) > 1 is closely related to stroke. The abbreviations (J, M,
H)
represent the sham group, MCAO group, and Nuci-H group, respectively
(C–F).
PCA score
based on rat serum samples in the sham, MCAO, and Nuci-H
groups, including ESI+ (A) and ESI– (B)
modes. Every dot represents an animal, and the colors indicate different
treatment groups. S-plot of OPLS-DA for the sham group versus the
MCAO group, the MCAO group vs. the Nuci-H group in ESI+ (C, D) and ESI– (E, F) modes. The black square
represents a different metabolite, and the red square indicates that
this endogenous metabolite with variables with importance parameter
(VIP) > 1 is closely related to stroke. The abbreviations (J, M,
H)
represent the sham group, MCAO group, and Nuci-H group, respectively
(C–F).To better elucidate the differences
between groups and identify
the endogenous biomarkers, we used the S-plot of the OPLS-DA model
(Figure C–F).
The relevant parameters of the OPLS-DA model in positive- and negative-ion
modes were identified. Comparison of the sham and MCAO groups showed
an R2Y = 0.9932, Q2 = 0.9020 and R2Y = 0.9682, Q2 = 0.7091,
respectively, whereas the values for the Nuci-H group and MCAO group
comparison were R2Y =
0.9884, Q2 = 0.9695, and R2Y = 0.9933, Q2 = 0.9298, respectively. The results indicated that the OPLS-DA model
showed good stability and predictability. The farther away from the
coordinate origin, the greater the contribution of the metabolites.
Metabolites enclosed in the red quadrilateral indicated VIP > 1.
The
data of the OPLS-DA model derived from the sham group vs. the MCAO
group and the MCAO group vs. the Nuci-H group were shown for ESI+ (Figure C,D)
and ESI– (Figure E,F).
Analysis, Discovery, and Elucidation of Potential
Biomarkers
Briefly, the following steps were used to identify
metabolites
in this investigation. The candidates were preliminarily screened
using Progenesis QI software, and candidates with VIP > 1 from
the
OPLS-DA score plots were selected. The loading plot displayed potential
MCAO-related metabolites according to their variable importance in
projection (VIP) value, which was set to be higher than 1 (VIP >
1)
and significant test, with P < 0.05. Based on
the retention time and mass spectra with the authentic chemicals,
some of the metabolites related to the MCAO-induced stroke injury
were confirmed in rats (Table ).
Table 1
Surgical Procedures and Number of
Rats Used in Various Treatments
sham
MCAO
EGb 761
Nuci-L
Nuci-M
Nuci-H
neurological deficits
n = 11
n = 11
n = 11
n = 11
n = 11
n = 11
infarct volume
brain water content
n = 11
n = 11
n = 11
n = 11
n = 11
n = 11
serum metabolomics
n = 8
n = 8
n = 8
total
n = 30
n = 30
n = 22
n = 22
n = 22
n = 30
Nineteen metabolites were regarded as potential
biomarkers of ischemicstroke in rat serum samples. The candidates were roughly divided into
carboxylic acid compounds, such as L-lactic acid, oxoglutaric acid,
linoleic acid, petroselinic acid, sebacic acid, tauroursodeoxycholic
acid, N-methylnicotinium, vitamin D2 3-glucuronide,
and stearoylcarnitine; amino acid metabolites, such as hydroxyphenylacetylglycine,
glucosylgalactosyl hydroxylysine, isobutyrylglycine, N2-succinyl-L-ornithine,
and glutamylphenylalanine; longer-chain polyunsaturated fatty acids
and olefin compounds, such as neoxanthin, docosahexaenoic acid, and
2-hydroxyestradiol-3-methyl ether; and lipid compounds, such as sphingosine
1-phosphate and sphinganine 1-phosphate. The detailed information
of the 19 differential metabolites (retention time, mass-to-charge
ratio, HMDB, KEGG, trends, etc.) after MCAO preparation and nuciferine
intervention is shown in Table .
Table 2
Information and Changing Trend of
Potential Biomarkers in the Rat Seruma,b
trend
no.
metabolite
tR/min
mass-to-charge
ratio
type
HMDB
KEGG
MCAO/Sham
Nuci-H/MCAO
1
l-lactic acid
0.7254
89.0518
[M – H]−
HMDB0000190
C00256
↑*
↓###
2
hydroxyphenylacetylglycine
1.371
208.0887
[M – H]−
HMDB0000735
C05596
↓*
↓#
3
isobutyrylglycine
1.4258
144.0955
[M – H]−
HMDB0000730
/
↑**
↓##
4
N-methylnicotinium
1.4638
176.067
[M – H]−
HMDB0001009
/
↓*
↓#
5
N2-succinyl-l-ornithine
2.8724
231.1036
[M – H]−
HMDB0001199
C03415
↓*
↓#
6
sebacic acid
3.315
201.0502
[M – H]−
HMDB0000792
C08277
↑**
↓##
7
linoleic acid
4.8949
279.1474
[M – H]−
HMDB0000673
C01595
↑***
↑###
8
tauroursodeoxycholic acid
5.1969
498.2942
[M – H]−
HMDB0000874
/
↓*
↑#
9
sphingosine 1-phosphate
7.9323
378.2575
[M – H]−
HMDB0000277
C06124
↓**
↑###
10
sphinganine 1-phosphate
8.2826
380.2727
[M – H]−
HMDB0001383
C01120
↓***
↑###
11
2-hydroxyestradiol-3-methyl
ether
9.9301
303.2521
[M + H]+
HMDB0000380
/
↓**
↑###
12
glutamylphenylalanine
9.9338
293.2015
[M – H]−
HMDB0029156
/
↓***
↓###
13
vitamin D2 3-glucuronide
10.4886
571.3343
[M – H]−
HMDB0010344
/
↓***
↑###
14
neoxanthin
10.8794
599.3139
[M – H]−
HMDB0003020
C08606
↓***
↑###
15
stearoylcarnitine
11.4485
428.3842
[M + H]+
HMDB0000848
/
↓***
↑#
16
glucosylgalactosyl hydroxylysine
12.3866
485.2889
[M – H]−
HMDB0000585
/
↑**
↑##
17
docosahexaenoic acid
12.5321
327.2532
[M – H]−
HMDB0002183
C06429
↑*
↑##
18
petroselinic acid
12.8482
282.301
[M + H]+
HMDB0002080
C08363
↓***
↑###
19
oxoglutaric acid
13.9886
144.952
[M – H]−
HMDB0000208
C00026
↑***
↓###
Note: *P < 0.05,
**P < 0.01, ***P < 0.001 versus
the sham group; #P < 0.05, ##P < 0.01, ###P < 0.001 versus the MCAO group.
The treads of biomarkers were expressed with (↓) downregulated
and (↑) upregulated.
FC > 1 showed that the content of
metabolites in the MCAO group was higher than that in the sham group,
and vice versa. Compared with the MCAO group, the situation of Nuci-H
group was the same as above.
Note: *P < 0.05,
**P < 0.01, ***P < 0.001 versus
the sham group; #P < 0.05, ##P < 0.01, ###P < 0.001 versus the MCAO group.
The treads of biomarkers were expressed with (↓) downregulated
and (↑) upregulated.FC > 1 showed that the content of
metabolites in the MCAO group was higher than that in the sham group,
and vice versa. Compared with the MCAO group, the situation of Nuci-H
group was the same as above.
Metabolic Pathway Analysis
Based on the results of
pharmacodynamics and multidata analyses, biomarkers reflecting the
treatment of nuciferine on stroke were determined. According to the
identified metabolites, the metabolic networks were constructed using
Cytoscape 3.7.2 software, which was conducive to better understand
the internal correlation of the biomarkers in terms of the enzyme
or gene levels and clearly demonstrate the relationship between the
occurrence of stroke and the efficacy of nuciferine. The metabolic
networks that were established based on the markedly different metabolites
are shown in Figure . A total of seven stroke-related pathways were found in this study,
which was labeled in the following figure and mainly involved: di-unsaturated
fatty acid β-oxidation; glycine, serine, alanine, and threonine
metabolism; glycolysis and gluconeogenesis; glycosphingolipid metabolism;
linoleate metabolism; TCA cycle; urea cycle and metabolism of arginine,
proline, glutamate, aspartate, and asparagine. Based on the discovery
of the relevant biomarkers and determined metabolic pathways in the
metabolic networks, we have elaborated the anti-stroke molecular mechanisms
of nuciferine in our research (Figure ). The identified metabolites contributed to the information
of the metabolic pathways (Table S1).
Figure 4
Metabolic
correlation network analysis. Metabolomics pathways were
discovered and determined using Cytoscape 3.7.2. Hexagon, metabolites;
round rectangle, enzyme; ellipse, gene; and diamond, reaction. Di-unsaturated
fatty acid β-oxidation metabolism; glycine, serine, alanine,
and threonine metabolism; and glycolysis and gluconeogenesis metabolism
are shown in (A, B), and C, respectively. Sphingosine kinases (SphK1
and SphK2) and sphingosine 1-phosphate (S1P) are involved in glycosphingolipid
metabolism (D). (E) represents the linoleate metabolism. F shows that
certain enzymes and metabolites participated in the TCA cycle, such
as isocitrate dehydrogenase enzymes (IDH) and oxoglutaric acid. Glutamate
oxaloacetate transaminase (GOT) and glutamate-pyruvate transaminase
(GPT) were also involved in the urea cycle and metabolism of arginine,
proline, glutamate, aspartate, and asparagine metabolism (G). The
original unprocessed and high-resolution (this figure) data are shown
in Figure S1.
Figure 5
Schematic
diagram of the perturbed metabolic pathways that were
detected by the UPLC/MS/MS, showing the network links between the
identified biomarker pathways and MCAO-induced ischemic stroke. The
red metabolites were upregulated, while the green metabolites were
downregulated in the Nuci-H group compared to the MCAO group.
Metabolic
correlation network analysis. Metabolomics pathways were
discovered and determined using Cytoscape 3.7.2. Hexagon, metabolites;
round rectangle, enzyme; ellipse, gene; and diamond, reaction. Di-unsaturated
fatty acid β-oxidation metabolism; glycine, serine, alanine,
and threonine metabolism; and glycolysis and gluconeogenesis metabolism
are shown in (A, B), and C, respectively. Sphingosine kinases (SphK1
and SphK2) and sphingosine 1-phosphate (S1P) are involved in glycosphingolipid
metabolism (D). (E) represents the linoleate metabolism. F shows that
certain enzymes and metabolites participated in the TCA cycle, such
as isocitrate dehydrogenase enzymes (IDH) and oxoglutaric acid. Glutamateoxaloacetate transaminase (GOT) and glutamate-pyruvate transaminase
(GPT) were also involved in the urea cycle and metabolism of arginine,
proline, glutamate, aspartate, and asparagine metabolism (G). The
original unprocessed and high-resolution (this figure) data are shown
in Figure S1.Schematic
diagram of the perturbed metabolic pathways that were
detected by the UPLC/MS/MS, showing the network links between the
identified biomarker pathways and MCAO-induced ischemic stroke. The
red metabolites were upregulated, while the green metabolites were
downregulated in the Nuci-H group compared to the MCAO group.
Cytoscape to Explore the Metabolite–Protein
Network
Subsequently, to further explore the intrinsic relationship
between
the potential biomarkers and potential proteins, the networks involved
in some categories (genes, enzymes, etc.) were also discovered using
Cytoscape 3.7.2.[31] Approximately 93 genes
were found. These genes were imported into an online database for
analysis (http://ci.smu.edu.cn/GenCLiP2/analysis.php#). A total of 11
proteins were confirmed as follows: PLA2, 12/15-LOX, SPHK1, SPHK2,
IDH, GOT1, AGXT2, CYP2B, FADS, DLDH, and GPT. The details with abbreviations
and full names of proteins considered as potential markers for MCAO-induced
stroke and the role of nuciferine are shown in Table .
Table 3
Full Names of the
Potential Protein
Targetsa
name abbreviation
full name
PLA2
phospholipase A2
12/15-LOX
12/15-lipoxygenase
SPHK1
sphingosine kinase 1
SPHK2
sphingosine kinase 2
IDH
isocitrate dehydrogenase
enzymes
GOT1
glutamate
oxaloacetate transaminase
1
AGXT2
alanine-glyoxylate aminotransferase
2
CYP2B
cytochrome P450 2B
FADS
fatty acid desaturase
DLDH
dihydrolipoamide dehydrogenase
GPT
glutamate-pyruvate transaminase
These targets in serum are the targets
after administration and related to MCAO.
These targets in serum are the targets
after administration and related to MCAO.
Discussion
Ischemic cerebral stroke
is the second leading cause of death and
carries a tremendous public health burden, especially in developing
countries. It results in a mortality rate of approximately 30%,[32,33] and its costs account for approximately 3–7% of total national
health care expenditures.[34,35] Stroke is a multifactorial
and complex pathophysiological process. The specific pathogenesis
is not clear, and the available drugs are not ideal. The present study
confirmed that nuciferine, a bioactive monomer extract from Nymphaea caerulea and Nelumbo nucifera Gaertn, could significantly improve the ethological aspect of rats
with cerebral ischemia. However, the molecular mechanism has not been
elucidated, which hindered the progress of anti-stroke research. Metabolomics
is a systematic method that contributes to the study of the possible
therapeutic mechanisms of drugs. These facts encouraged us to use
the UPLC-Q-TOF/MS-based serum metabolomics method to study the metabolic
responses and the metabolic pathways of rats after intervention with
nuciferine. After that, the relevant biomarkers and pathways in the
metabolic networks were discovered (Figure ). This provides a new idea for us to explore
the anti-stroke molecular mechanisms of nuciferine.In this
study, a metabolomics method was used to analyze the serum
samples of MCAO model rats, a total of 12 endogenous metabolites were
identified in the serum of MCAO-induced rats. The increase or decrease
of the metabolites content in the serum of rats caused the disorder
of the corresponding biological metabolic pathways, indicating that
MCAO caused the metabolic disorder of the body and induced the occurrence
of cerebral ischemic diseases. After nuciferine administration, the
contents of l-lactic acid, tauroursodeoxycholic acid, docosahexaenoic
acid, oxoglutaric acid, sphinganine 1-phosphate, and sphingosine 1-phosphate
could be recalled, mainly involved in energy metabolism, sphingolipid
metabolism, and anti-inflammatory and antiapoptotic processes. Eventually,
nuciferine can regulate the normal physiological metabolism level
of rats, thereby exerting anti-cerebral ischemic effects.
Macroscopic
Analysis and Other Metabolites and Enzymes
At this stage
of research, the MCAO model was established, and the
protective effects of nuciferine against cerebral ischemia were evaluated.
Numerous studies have shown that the MCAO model is consistent with
the pathogenesis of humanstroke, and it possesses the advantages
of good repeatability and high stability, which provides a powerful
tool for the study of ischemic encephalopathy mechanism and drug screening.[36] Weakness of the contralateral limbs is the most
important symptom of stroke.[37] We performed
the initial evaluation of the nuciferine treatment using neurological
scores. Compared to the MCAO group, the neurological function scores
of the rats in the EGb 761 group and the Nuci-H group were significantly
reversed, and the rats could almost crawl normally, which indicated
that a sufficient concentration of nuciferine repaired the embolism-induced
movement disorders.The MCAO thread ligation model causes behavioral
and physiological abnormalities in rats, which may be related to the
decrease in cerebral blood flow (CBF), which disrupts the balance
in the brain. Huang et al.[38] found that
an inflammatory response or cytokines (TNF-α and IL-1α/β)
were initiated when cerebral stroke occurred, and vice versa. Edema
and infarct volume, which are consistent with the above factors, are
the most obvious pathological manifestations of stroke. Our current
data demonstrated that nuciferine attenuated the increase in infarct
volume and brain edema (Figure B–D). Dispersants and protections are produced by 12/15-LOX
from the longer-chain polyunsaturated fatty aciddocosahexaenoic acid,[39] which are effective anti-inflammatory compounds
that may limit inflammation-induced brain damage.[40] The expression of some proteins (PLA2, 12/15-LOX) alters
metabolites and the di-unsaturated fatty acid β-oxidation metabolism
that contributes to the alleviation of the characteristics of stroke
injury. The above results showed that nuciferine regulated the levels
of endogenous metabolites associated with the release of inflammatory
cytokines and achieved the anti-stroke effects via inhibition of the
occurrence of inflammation, which provided some ideas to support our
examination of nuciferine treatment of cerebral ischemic stroke in
the future.
Biomarkers Obtained and Discussion of Sphingolipid
Metabolism
Sphingolipids (including sphingosine and sphinganine)
are critical
mediators of neuronal cell death, proliferation, and migration, which
are related to ischemic stroke.[41,42] Sphinganine may be
converted to ceramides, sphingosine, and sphingosine 1-phosphate (S1P).
Several studies have provided evidence that S1P is an immunomodulatory
factor.[43] Sphingosine plays a neuroprotective
role only when it is phosphorylated and transformed into endogenous
S1P. Sphingosine kinases (SphK1 and SphK2) are the rate-limiting enzymes
that convert sphingosine into S1P.[44] Blondeau
et al.[45] and Wacker et al.[46] found that the level of Sphk2, but not Sphk1, is increased
by stroke. Pfeilschifter et al.[47] identified
larger infarcts in Sphk2-deficient mice compared to those with normal
levels. Increasing evidence suggests that the Sphk2/S1P axis acts
as an indispensable mediator of stroke. The content of S1P was significantly
reduced in the MCAO group in our study, which may be related to the
inhibition of SphK2 activity. Notably, S1P was reversed after the
administration of nuciferine. MCAO may restrain SphK activity and
reduce the concentrations of synthetic S1P to cause an imbalance of
material metabolism (glycosphingolipid metabolism), which results
in stroke symptoms.
Energy Metabolism
The brain has
the most vigorous energy
metabolism of any organ, but it does not store energy. When blood
vessels are blocked, cerebral blood flow decreases and oxygen delivery
is restricted, which initiate anaerobic glycolysis to produce a small
amount of ATP to provide energy to the brain, and it results in an
accumulation of hydrogen ions.[48] Compensatory
mechanisms are initiated, glycogen is quickly depleted, and a large
amount of lactic acid is produced.[49] Lactic
acid is a marker product of anaerobic glucose fermentation. Lactic
acid and its synergistic acid effect (hydrogen ion enrichment) are
important factors in neuronal damage in brain injury. In this experiment,
after MCAO intervention, the content of L-lactic acid was increased,
and the level of l-lactate in the Nuci-H group was extremely
significantly decreased (P < 0.001). l-lactic acid reflects the degree of the ischemic core area, which
is consistent with the cerebral infarction volume with the trend of l-lactate. These data demonstrated that the neuroprotective
function of nuciferine on stroke occurred via the correcting of the
abnormal energy metabolism pattern, which was related to the tricarboxylic
acid (TCA) cycle and resulted in the reduced rate of infarct and the
death of neurons.The conversion of glucose to pyruvate is a
common process. Oxoglutaric acid is produced under the action of pyruvate
dehydrogenase and isocitrate dehydrogenase enzymes (IDH), and it is
the precursor of glutamate synthesis. Therefore, the trend of oxoglutaric
acid can indirectly indicate the content of excitatory amino acids.
Our data revealed that the levels of oxoglutaric acid, a TCA cycle
intermediate, were obviously increased in the MCAO group (P < 0.001), which may indicate that energy production
was disordered in MCAOrats. Surprisingly, oxoglutaric acid showed
a downward trend in the Nuci-H group. These results indicated that
brain protection against stroke in MCAOrats occurred via improved
energy metabolism and anti-glutamate excitotoxicity.[50]Further, we conclude that anaerobic glycolysis (lactic
acid) and
TCA cycle (oxoglutaric acid) indicators were affected, which are directly
related to energy metabolism. These results indicate that the therapeutic
effects of nuciferine on cerebral ischemia are partially due to its
ability to repair energy metabolism.
Other Metabolisms
Tauroursodeoxycholic acid (TUDCA),
an endogenous hydrophilic bile acid, which is formed by the conjugation
of ursodeoxycholic acid (UDCA) with taurine.[51] TUDCA exhibits anti-inflammatory effects and attenuates neuronal
loss (apoptosis) in neurodegenerative diseases.[52] The possible neuroprotective mechanisms of TUDCA is inhibiting
apoptosis by modulating Bcl-2, BAX, and caspase activation.[53] Apoptosis plays a vital role in maintaining
homeostasis, physiological processes, and many diseases.[54] Rodrigues et al.[55] investigated that TUDCA could alleviate brain injury by inhibiting
the expression of Caspase-3 in MCAOrats. In our study, the concentrations
of TUDCA were obviously decreased in the MCAO group. This result may
indicate that apoptotic destroys the neural cell structure, resulting
in the symptoms of stroke. After nuciferine treatment, the level of
TUDCA could significantly increase.Nuciferine downregulated
L-lactic acid, isobutyrylglycine, sebacic acid, hydroxyphenylacetylglycine,
N-methylnicotinium, N2-succinyl-L-ornithine, glutamylphenylalanine,
and oxoglutaric acid, and it upregulated tauroursodeoxycholic acid,
sphingosine 1-phosphate, sphinganine 1-phosphate, 2-hydroxyestradiol-3-methyl
ether, vitamin D2 3-glucuronide, neoxanthin, stearoylcarnitine, petroselinic
acid, linoleic acid, glucosylgalactosyl hydroxylysine, and docosahexaenoic
acid in rat serum. It is worth exploring the activity of certain genes
and enzymes related to stroke occurrence and metabolites, such as
PLA2, 12/15-LOX, SPHK, IDH, GOT1, CYP2B, FADS, and GPT, which are
highly relevant to nuciferine, in further investigations.
Conclusions
The complex and incompletely clear pathogenesis of stroke, accompanied
by serious and irreversible sequelae such as deformity, language dysfunction,
and dementia, hinder the progress in global medical treatment of this
disease. Although several therapeutic methods have been developed
for key pathophysiological targets, these treatments are not ideal.
The present study examined the protective effects of nuciferine on
ischemic stroke using a metabolomics approach based on UPLC-Q-TOF/MS
for the first time. Twelve metabolites closely associated with MCAO-induced
strokerats were identified. Moreover, we focused on the effects of
nuciferine in MCAOrats. The neurological function scores evaluated
the anti-ischemic effect of nuciferine using behavioral testing, and
infarct volume and cerebral water content were investigated to evaluate
the pharmacodynamic effects. After oral administration of nuciferine,
the behavioral and pharmacodynamic indicators tended toward or returned
to normal levels and restored the metabolic disturbances.Overall,
our results demonstrated that sphingolipid metabolism,
metabolic stress, energy metabolism (glycolysis and gluconeogenesis
and TCA cycle), and other metabolisms were the notable involved pathways
whose modulation may prevent suffering from the occurrence of stroke.
After drug intervention, it was shown that nuciferine can regulate
the body’s metabolic balance by exerting neuroprotective, antiapoptotic,
and anti-inflammatory effects, thereby playing an anti-stroke effect.
These findings provide a basis for the study of nuciferine for the
treatment of stroke.
Materials and Methods
Chemicals and Reagents
Nuciferine (Nuci) was purchased
from Sigma-Aldrich (Burlington, MA) (purity ≥ 98%; Shanghai,
China). The positive control was EGb 761 (Chinese National Medicine
permission number: H2O140768), which was researched and manufactured
by Dr. Willmar Schwabe Pharmaceuticals Co., Ltd. (Germany). Chloral
hydrate and carboxymethylcellulose sodium (CMC-Na) were purchased
from Beijing BioDee Biotechnology Co., Ltd. (Beijing, China). Formic
acid and acetonitrile were acquired from Fisher Co. Ltd. (Pittsburgh,
PA). Double-distilled water was provided by a Milli-Q system (Millipore,
MA).
Experimental Animals
Adult male Sprague-Dawley (SD)
rats weighing 240–270 g were purchased from Beijing Vital River
Laboratory Animal Technology Co., Ltd. (Beijing, China) and kept in
propylene cages for adaptation periods of 3 days at a temperature
of 25 ± 2 °C, a relative humidity of 45 ± 15%, and
a 12 h light–dark cycle and fed freely. The China Academy of
Chinese Medical Science’s Administrative Panel on Laboratory
Animal Care approved all of the experimental procedures, which followed
the guidelines on experimental design and analysis in pharmacology.
Every effort was made to minimize the suffering of animals.
Animal
Groups and Model Establishment
After adaptive
feeding, all male rats were randomly divided into six groups (n = 11): the sham group, the MCAO group, the positive control
group (EGb 761), and the low-, middle- and high-dose nuciferine treatment
groups (Nuci-L, Nuci-M, and Nuci-H, respectively). The number of rats
used in various treatments are shown in Table . The nuciferine doses given were 10, 20,
and 40 mg/kg, respectively.The rats were anesthetized with
10% chloral hydrate (350 mg/kg), and the MCAO model was established
as previously indicated.[23−25] The surgeries were performed
after the response to the noxious stimulus disappeared and breathing,
body temperature, and other normal physiological conditions stabilized.[26] Briefly, the animals were attached to the operating
board with the abdomen upward, and the origin of the MCA was occluded
via the insertion of a 4–0 single nylon suture with a round
head into the internal carotid artery from the left external carotid
artery.[27] The surgical site was closed
with a degradable surgical suture after disinfection. The sham group
underwent the same surgical experimental procedure without filament
insertion.The entire modeling process ensured that the experimenters
and
the environment were consistent. All treatment groups were assigned
in a randomized manner.
Dosing Regimens
Considering the
low solubility of nuciferine,
an equal amount of carboxymethylcellulose (CMC-Na) was added, and
ultrasound-assisted dissolution was used. The sham and MCAO groups
were fed an equivalent volume of 5% CMC-Nawater solution. The three
nuciferine treatment groups were 10, 20, and 40 mg/kg. The EGb 761
group was treated with 100 mg/kg. All treatments were given intragastrically
within 30 min before surgery.
Evaluation of Neurological
Deficits
After surgery,
the rats were carefully placed in cages. The experimenters observed
that all animals woke normally, and rats that died after surgery were
recorded and excluded. Behavioral scoring was performed 24 h after
MCAO, and a single researcher who was not aware of the experimental
group assignments performed the entire process. The behaviors were
scored on a five-point scale (0–4 points) as described previously.[28]
Evaluation of Cerebral Infarct Volume
After the neurological
function scoring was completed, the rats were anesthetized via intraperitoneal
injection and brain tissues were collected and washed with a physiological
saline solution. The intact brain tissues were stored in a flat dish
at −20 °C and removed after completely hardening. Then,
the tissues were carefully cut into six 2 mm thick coronal sections
and stained with 2% TTC at room temperature until a red/white color
boundary appeared. A digital camera was used to record the stained
brain slices. Brain slice data were quantitatively analyzed using
ImagePro Plus 6.0 to measure the infarct volume.
Quantification
of Brain Water Content
The effects of
nuciferine on the rate of postoperative brain edema was evaluated
via measurement of the cerebral water content. Two fresh hemispheres
were separately weighed and recorded. The water content was calculated
as follows: cerebral water content = (left brain – right brain)/(left
brain + right brain) × 100%. The infarction cerebral hemisphere
was the left brain.
Serum Sample Collection and Handling for
Metabolomics Analysis
After successfully establishing the
MCAO model, whole blood of
all rats (3–5 mL) was collected from the abdominal aorta and
placed in a centrifuge tube. The blood samples were numbered and left
to stand on ice for 30 min. Then, they were centrifuged at 3500 g
for 15 min at 4 °C. The supernatant serum was carefully removed
using a pipette, placed in a new EP tube, and then stored at −20
°C for approximately 20 min. The serum samples were stored at
−80 °C for further metabolic analysis.Prior to
UPLC-Q-TOF/MS detection, the serum sample was removed from the refrigerator
and thawed at room temperature. A volume of 150 μL of serum
was transferred to a new tube, and 450 μL of acetonitrile was
added to precipitate the protein. The above mixture (600 μL)
was vortexed and centrifuged sequentially at 2000 rpm for 10 min and
then 13 000 rpm for 10 min at 4 °C. The supernatant (400
μL) was transferred to a new EP tube and evaporated to dryness
under a steady nitrogen flow in the fume hood. Residues were redissolved
in 100 μL of 10% acetonitrile, followed by vortexing and centrifugation.
The supernatant was collected again. The supernatant (80 μL)
was injected into a sampling bottle for metabolomics analysis. Due
to the characteristics of the sample, the entire process was carried
out on ice.
Quality Control Sample
To evaluate
the stability and
repeatability of the UPLC-Q-TOF/MS analysis system, 10 μL of
the supernatants of every serum samples from each group were selected
and mixed as a pooled quality control (QC) sample. QC samples were
handled as same as serum samples. One QC sample was analyzed after
every 10 test samples to check the stability and performance of the
instrument.
UPLC-Q-TOF/MS Analysis
During the
course of this experimental
study, metabolomics analysis was performed using a Synapt G2 UPLC-Q-TOF/MS
(Waters Corporation, Milford, MA) system. The chromatographic separation
(UPLC) conditions are shown below. An Acquity UPLC HSS C18 column (1.7 μm, 2.1 × 100 mm2) was used with
an injection volume of 4 μL. The column temperature and flow
rate were maintained at 40 °C and 0.4 mL/min, respectively. The
mobile phases of serum samples consisted of 0.1% formic acid–water
(solvent A) and 0.1% formic acid–acetonitrile (solvent B).
Notably, the standard elution program conditions were as follows:
0–1.5 min with 10–20% B; 1.5–4 min with 20–40%
B; 4–13 min with 40–90% B; 13.1–14 min with 90%
B; and 14.1–17 min with 10% B.The UPLC-Q-TOF/MS acquisition
was used in the MSe mode. This mode can scan the primary and secondary
mass spectra simultaneously. Mass spectrometry (MS) analysis was performed
in positive- and negative-ion modes equipped with an electrospray
ionization (ESI) source. Leucine–enkephalin (ESI+, m/z 556.2771; ESI–, m/z 554.2615) was used as
a standard for quality determination and lock mass solution. The following
final MS conditions were used in the positive-ion detection mode:
capillary voltage, 2.7 kV; source temperature, 120 °C; desolvation
temperature, 500 °C; cone gas flow, 50 L/h; desolvation gas flow,
800 L/h; low collision energy for precursors, 25 V; high energy for
fragment ions, 50 V. The same detection method was used for both the
negative ion and positive ion, except that the negative ion was under
2.1 kV capillary voltage. The mass spectrum collected and analyzed
ranged from 50 to 1000 m/z.
Multivariate
Data Analysis
According to the above methodology,
the raw data were obtained from the UPLC-Q-TOF/MS system, which were
processed and analyzed in Progenesis QI (Waters Corporation, Milford,
MA), including nonlinear retention time alignment, peak discrimination,
filtering, alignment, matching, and identification. The parameters
for each ion primarily included the retention time and mass-to-ratio
data pairs. Unit variance scaling and the mean-centered method were
used to handle data, followed by multivariate analysis including principal
component analysis (PCA), which revealed the aggregation and dispersion
of samples. An orthogonal partial least-squares discriminate analysis
(OPLS-DA) algorithm was further constructed using the permutation
test to prevent overfitting. OPLS-DA showed differences between two
groups. The OPLS-DA score plots were described using the cross-validation
parameters R2Y and Q2, where R2Y
indicates the goodness of fit of the model, and Q2 estimates
its prediction ability.[29] The variable
importance in the projection (VIP) values, which expresses the significance
in discriminating between groups, were used to select the biomarkers.
The present study selected VIP > 1 in the OPLS-DA model, which
were
identified as potential variables. The average peak area of metabolites
between the two groups (FC) was used to judge the change in the metabolite
content between different groups. FC > 1 indicated that the content
of the metabolite increases, whereas FC < 1 indicated that the
content decreases. After that, P values were obtained and the metabolites
were determined in the next step. Finally, when P < 0.05 and VIP > 1, the metabolites were considered statistically
significant.[30]The other statistical
(pharmacodynamic statistical) analyses performed were processed using
SPSS 17.0 (SPSS Inc., USA). The values are presented as mean ±
standard deviation (SD). The difference among the groups was compared
primarily using one-way analysis of variance (ANOVA) followed by Fisher’s
post hoc test. Neurological deficit data were collected using the
Kruskal–Wallis test. P < 0.05 was considered
statistically significant, and differences were considered extremely
significant when P < 0.01 or 0.001.
Biomarker
Identification, Metabolic Pathway, and Protein Correlation
Analysis
The possible metabolites were screened and identified
using certain online databases, such as the Human Metabolome Database
(http://www.hmdb.ca/), METLIN
(http://metlin.scripps.edu), and SMPD (http://www.smpdb.ca/). The spectra were compared with the MS/MS information from the
above databases to verify the structure of the putative metabolites.
The metabolites were identified via comparison of the retention times
and fragments of metabolites with the reference samples. The identified
potential biomarkers were transferred to Cytoscape 3.7.2. The pathways
and metabolite-correlation protein network were constructed using
Cytoscape 3.7.2 and GeneCards (https://www.genecards.org/), which were also used to acquire
potential protein targets of nuciferine. Protein targets related to
biomarkers were identified using Cytoscape, and the potential protein
targets were predicted using GeneCards.
Authors: Alberto Ouro; Clara Correa-Paz; Elena Maqueda; Antía Custodia; Marta Aramburu-Núñez; Daniel Romaus-Sanjurjo; Adrián Posado-Fernández; María Candamo-Lourido; Maria Luz Alonso-Alonso; Pablo Hervella; Ramón Iglesias-Rey; José Castillo; Francisco Campos; Tomás Sobrino Journal: Front Mol Biosci Date: 2022-04-20
Authors: Bin Yu; Yao Yao; Xiaofeng Zhang; Ming Ruan; Zhennian Zhang; Li Xu; Tao Liang; Jinfu Lu Journal: Front Pharmacol Date: 2021-06-16 Impact factor: 5.810