Abstract
A bioactivity-guided separation strategy was used to identify novel
antistroke compounds from Gymnadenia conopsea (L.) R. Br., a medicinal
plant. As a result, 4 undescribed compounds (1–2, 13, and 17) and 13
known compounds, including 1 new natural product (3), were isolated
from G. conopsea. The structures of these compounds were elucidated
through comprehensive spectroscopic techniques, such as 1D/2D nuclear
magnetic resonance (NMR) spectroscopy, high-resolution electrospray
ionization mass spectrometry (HRESIMS), and quantum chemical
calculations. An oxygen–glucose deprivation/reoxygenation
(OGD/R)-injured rat pheochromocytoma (PC12) cell model was used to
evaluate the antistroke effects of the isolates. Compounds 1–2, 10–11,
13–15, and 17 provided varying degrees of protection against OGD/R
injury in the PC12 cells at concentrations of 12.5, 25, and 50 µM.
Among the tested compounds, compound 17 demonstrated the most potent
neuroprotective effect, which was equivalent to that of the positive
control drug (edaravone). Then, transcriptomic and bioinformatics
analyses were conducted to reveal the regulatory effect of compound 17
on gene expression. In addition, quantitative real-time PCR (qPCR) was
performed to verify the results of the transcriptomic and
bioinformatics analyses. These results suggest that the in vitro
antistroke effect of compound 17 may be associated with the regulation
of the Col27a1 gene. Thus, compound 17 is a promising candidate for the
development of novel antistroke drugs derived from natural products,
and this topic should be further studied.
Keywords: Gymnadenia conopsea, bioactivity-guided separation strategy,
antistroke effect, Col27a1 gene
1. Introduction
Gymnadenia conopsea (L.) R. Br., a member of the family Orchidaceae, is
a perennial herbaceous flowering plant that is distributed at altitudes
from 200 to 4700 m throughout Northern Europe and the temperate and
subtropical zones in Asian countries [[36]1]. This plant has long been
used as a valuable Tibetan medicine in China. The famous Tibetan
Materia Medica book called Jingzhu Bencao describes the use of G.
conopsea to boost vitality and prolong life [[37]2]. The medicinal part
of G. conopsea is the tuber, which is renowned for its palm-like
appearance and characteristic finger-like protrusions [[38]3].
At present, approximately one hundred chemical compounds, including
low-molecular-weight organic acids, benzylester glucosides
[[39]4,[40]5,[41]6,[42]7], dihydrostilbenes [[43]8], phenanthrenes
[[44]8], and alkaloids [[45]9,[46]10], have been reported from G.
conopsea [[47]11]. These various types of secondary metabolites
determine the diverse biological activities of G. conopsea. Extracts of
G. conopsea have been reported to have a remarkable array of
pharmacological effects, including antifatigue, antioxidant, antiviral,
sedative–hypnotic, and immunoregulatory effects [[48]1]. However,
whether G. conopsea has other pharmacological effects remains unknown.
Moreover, although we have a certain understanding of its components,
there is considerable investigation space for the phytochemical aspects
of G. conopsea. In recent years, the use of G. conopsea has
increasingly expanded because of its health care properties [[49]1].
Thus, further investigations on G. conopsea are urgently needed to
determine its multiple pharmacological effects and active compounds and
to improve the application of this valuable plant.
G. conopsea belongs to the subfamily Orchidoideae of the family
Orchidaceae. Gastrodia elata Bl. is also a member of the subfamily
Orchidoideae and the tuber of G. elata, a famous Chinese medicine, has
been reported to exhibit antistroke activity [[50]12]. The principles
of plant chemical taxonomy reveal that closely related species have
similar chemical constituents and bioactivities [[51]13]. Additionally,
the previous phytochemical studies have demonstrated that both G. elata
and G. conopsea contain organic acids, benzylester glucosides,
dihydrostilbenes, phenanthrenes, and alkaloids
[[52]4,[53]5,[54]6,[55]7,[56]8,[57]9,[58]12]. Inspired by the above
principles and related phytochemical findings, we hypothesize that G.
conopsea may also exhibit antistroke activity.
In the present study, a bioactivity-guided separation strategy was used
to isolate the constituents of G. conopsea, and the antistroke effects
of the isolated compounds were evaluated. The novel compound with the
most promising antistroke effect was subsequently examined through
transcriptome analysis to investigate its regulatory effects on gene
expression. Then, quantitative real-time PCR (qPCR) was performed to
verify the results of the transcriptome analysis. Overall, this
comprehensive approach provides insights into the potential antistroke
property of G. conopsea and offers useful data for its further
development and utilization.
2. Results
2.1. Identification of the Active Fractions
We first evaluated the neuroprotective activities of the fractions to
identify the active fractions. The effects of each fraction on
oxygen–glucose deprivation/reoxygenation (OGD/R)-injured rat
pheochromocytoma (PC12) cells are illustrated in [59]Figure 1. The
neuroprotective effects of the 30% ethanol fraction (D30) and the 50%
ethanol fraction (D50) surpassed that of the 75% ethanol fraction
(D75). Consequently, we systematically separated the compounds within
the D30 and D50 fractions.
Figure 1.
[60]Figure 1
[61]Open in a new tab
Neuroprotective effects of samples prepared from Gymnadenia conopsea on
ODG/R-induced PC12 cells (means ± SDs, n = 3). ^### p < 0.001 versus
the control, * p < 0.05, ** p < 0.01, and *** p < 0.001 versus OGD/R.
2.2. Identification of the Structures
A total of 4 new compounds (1–2, 13, and 17) and 13 known compounds,
including 1 new natural product (3), were isolated from G. conopsea
([62]Figure 2), and their structures were elucidated through
comprehensive spectroscopic techniques, such as 1D/2D nuclear magnetic
resonance (NMR) spectroscopy, high-resolution electrospray ionization
mass spectrometry (HRESIMS), and quantum chemical calculations. The key
heteronuclear multiple bond connectivity (HMBC), correlation
spectroscopy (COSY), and nuclear Overhauser effect spectroscopy (NOESY)
correlations of the four new compounds are shown in [63]Figure 3. The
stereoscopic configuration of compound 17 is shown in [64]Figure 4. The
ultraviolet (UV), infrared (IR), circular dichroism (CD), HRESIMS, 1D
NMR, and 2D NMR spectra of the isolates are shown in [65]Figures
S1–S78.
Figure 2.
[66]Figure 2
[67]Open in a new tab
Structures of compounds 1–17 isolated from G. conopsea.
Figure 3.
[68]Figure 3
[69]Open in a new tab
Key HMBC and ^1H-^1H COSY correlations of compounds 1–2, 13, and 17.
Figure 4.
[70]Figure 4
[71]Open in a new tab
Stereoscopic configuration of compound 17. (A) Correlations between the
calculated and experimental chemical shifts of 2S. (B) Correlations
between the calculated and experimental chemical shifts of 2R. (C) DP4+
probabilities of possible isomers of 17. (D) Experimental ECD spectrum
of 17 (black line) and the calculated spectrum of 17 (red line).
Compound 1 was obtained as a pale yellow powder, and its molecular
formula was determined to be C[20]H[24]O[8] with nine degrees of
unsaturation according to its HRESIMS data ([M + Na]^+ m/z 415.1363,
calcd 415.1363). The ^1H-NMR spectrum of 1 ([72]Figure S5) exhibited
signals for one methyl singlet (δ[H] 2.11), two methylene groups
(including one methylene in glucose), six olefinic protons, and five
glycosyl protons. The ^13C-NMR data ([73]Figure S6) revealed one methyl
group, two methylene groups, eleven methine groups (including six
olefinic carbons), and six quaternary carbons (olefinic carbons). The
^1H-NMR and ^13C-NMR data revealed a pair of overlapping AA′BB′
signals. In the HMBC spectrum, the correlations from H-7′ to C-1′,
C-2′, and C-6′ indicated the presence of a 1′,4′-disubstituted benzyl
moiety. The HMBC correlations from H-7′ to C-5, C-4, and C-6, from H-6
to C-5, C-1, C-2, C-4, and C-7′, from H-3 to C-5, C-1, C-2, and C-4,
and from H-1″ to C-1 indicate the presence of an additional
1,2,4,5-tetrasubstituted phenyl moiety in 1, which was connected to the
1′,4′-disubstituted benzyl moiety. In the ^13C-NMR spectrum, six carbon
signals (δ[C] 104.7, 74.9, 77.7, 71.1, 78.1, and 62.1) assigned to a
glucopyranosyl moiety were observed. Additionally, in the ^1H-NMR
spectrum, terminal protons were observed at δ[H] 4.63 (d, J = 7.2 Hz,
H-1″), and overlapping signals were observed between δ[H] 3.27 and
3.78, indicating the presence of a glucose moiety and suggesting a
β-glycosidic linkage. The D-glucopyranose moieties of 1 were defined by
comparison with those of a standard sample via silica gel thin layer
chromatography (TLC) analysis after acid hydrolysis. The HMBC
correlations from H-1″ to C-1 confirmed that the sugar unit was
connected to the 1,2,4,5-tetrasubstituted phenyl moiety. Thus, the
structure of compound 1 was fully elucidated, and the compound was
named 2-hydroxy-1-[(4-hydroxyphenyl)
methyl]-4-methylphenyl-1-β-D-glucopyranoside.
Compound 2 was obtained as a pale yellow powder, and its molecular
formula was determined to be C[20]H[24]O[7] with nine degrees of
unsaturation on the basis of its HRESIMS data ([M + Na]^+ m/z 399.1409,
calcd 399.1414). The ^1H-NMR spectrum of 2 ([74]Figure S15) exhibited
signals for one methyl singlet (δ[H] 2.16), two methylene groups
(including one methylene in glucose), seven olefinic protons, and five
glycosyl protons. The ^13C-NMR data ([75]Figure S16) revealed one
methyl group, two methylene groups, twelve methine groups (including
seven olefinic carbons), and five quaternary carbons (olefinic
carbons). The ^1H-NMR and ^13C-NMR data revealed a pair of overlapping
AA′BB′ signals. In the HMBC spectrum, the correlations from H-7′ to
C-1′, C-2′, and C-6′ and from H-1″ to C-4′ indicated the presence of a
1′,4′-disubstituted benzyl moiety. In the ^13C-NMR spectrum, six carbon
signals (δ[C] 102.5, 75.0, 78.0, 71.4, 78.1, and 62.5) assigned to a
glucopyranosyl moiety were observed. In the HMBC spectrum, the
correlations from H-1″ to C-4′ indicated that a sugar unit was
connected to the 1′,4′-disubstituted benzyl moiety. In the TLC analysis
after acid hydrolysis, the β-D-glucopyranose part of 2 was confirmed by
comparison with the standard sample. The HMBC correlations from H-7′ to
C-1, C-6, and C-2, from H-4 to C-2 and C-6, from H-3 to C-5, C-1, and
C-2, from H-6 to C-4, C-2, and C-7′, and from CH[3] (δ[H] 2.16, s) to
C-5, C-4, and C-6 indicated the presence of a 1,2,5-trisubstituted
phenyl moiety in 2. The HMBC correlations from H-7′ to C-1, C-6, and
C-2 indicated that the 1,2,5-trisubstituted phenyl moiety was connected
to a 1′,4′-disubstituted benzyl moiety. Thus, the structure of compound
2 was fully elucidated, and the compound was named
2-hydroxy-5-methylphenyl-1-(4-β-D-glucopyranosyloxybenzyl).
Compound 13 was obtained as a white amorphous powder, and its molecular
formula was determined to be C[12]H[11]N[4]O[2] with eight degrees of
unsaturation on the basis of its HRESIMS data ([M + H]^+ m/z 243.0871,
calcd 243.0877). The ^1H and ^13C-NMR data ([76]Figures S24 and S25)
indicate that this compound and 9-benzylhypoxanthine exhibit a high
degree of similarity [[77]14]. Compound 13 has an additional hydroxyl
group at the C-4′ position. This assignment was confirmed by the HMBC
cross peaks from H-7′ to C-1′, C-2′, and C-6′, from 4′-OH to C-4′,
C-3′, and C-5′, from H-2 to C-4 and C-6, and from H-8 to C-4 and C-5.
Consequently, the structure of compound 13 was identified, and it was
named 9-p-hydroxybenzylhypoxanthine.
Compound 17 was obtained as a colorless transparent gum (MeOH). Its
molecular formula was determined to be C[15]H[26]O[10] with three
degrees of unsaturation on the basis of its HRESIMS data ([M + Na]^+
m/z 389.1423, calcd 389.1418). The ^1H and ^13C-NMR data ([78]Figures
S34 and S35) indicate that this compound and
(2R)-2-(β-D-glucopyranosyloxy-2-(2-methylpropyl) butanedioic acid
exhibit a high degree of similarity [[79]15]; however, a
hydroxycarbonyl group (C-4) in
(2R)-2-(β-D-glucopyranosyloxy-2-(2-methylpropyl) butanedioic acid was
replaced by a methoxycarbonyl group in 17. This assignment was
confirmed by the HMBC cross peaks from H-9 to C-4 and from H-3 to C-4,
C-2, C-1, and C-5. A NOESY experiment was performed to determine the
relative configuration of compound 17. Unfortunately, no effective
NOESY cross peak was observed. Next, the configuration of C-2 was
confirmed through NMR calculations. The results showed that S* (R2 =
0.99952) ([80]Figure 4A) is more consistent with the experimental
values than R* (R2 = 0.99872) ([81]Figure 4B), which is further
supported by DP4+ ([82]Figure 4C) and the calculated ECD ([83]Figure
4D). According to the DP4+ analysis, the probability of 2S* is 100%,
and the calculated ECD spectrum of 2S* matches well with the
experimental ECD spectrum, indicating that C-2 has an S configuration.
At this point, the structure of compound 17 was fully elucidated, and
the compound was named
(2S)-2-(β-D-glucopyranosyloxy)-2-(2-methylpropyl) butanedioic acid
4-methyl ester.
By comparing the spectroscopic data from the isolated compounds with
the data reported in the literature, the other 13 known compounds were
identified as
4-[[[(2E)-3-(4-hydroxy-3-methoxyphenyl)-1-oxo-2-propen-1-yl]oxy]methyl]
phenyl β-D-glucopyranoside (3) [[84]16], 4-hydroxy-trans-cinnamomic
acid 4-β-D-glucopyranosyloxybenzyl ester (4) [[85]17],
4-O-(6′-O-glucosyl-p-coumaroyl)-4-hydroxybenzy alcohol (5) [[86]18],
amburoside B (6) [[87]19], 4-β-D-glucopyranosyloxybenzyl ester (7)
[[88]17], vanillic acid (8) [[89]20], 4-hydroxybenzaldehyde (9)
[[90]21], 4-methylphenyl β-D-glucopyranoside (10) [[91]22],
4-(methoxymethyl) phenyl-1-O-β-D-glucopyranoside (11) [[92]23],
4-(β-D-glucopyranosyloxy) benzyl ethyl ether (12) [[93]24],
6-(ethoxymethyl) pyridin-3-ol (14) [[94]25],
1-(2,3-dihydroxyphenyl)pyrrolidin-2-one (15) [[95]26], and
N^6-(4-hydroxybenzyl)-adenosine (16) [[96]24].
2.3. Neuroprotective Activity Results
After systematic separation, the antistroke activity of the 17 isolated
compounds was evaluated. The PC12 cell line possesses typical neuron
features and has been extensively used in related neurological studies
[[97]27,[98]28]. Therefore, we used PC12 cells to establish
OGD/R-induced PC12 cell damage model to mimic the ischemia and
reperfusion process of stroke and to investigate their in vitro
neuroprotective activities [[99]28]. The results revealed that
compounds 1–2, 10–11, 13–15, and 17 had varying degrees of protective
effects on the OGD/R-injured PC12 cells at concentrations of 12.5, 25,
and 50 µM ([100]Figure 5). Notably, compound 17 demonstrated a potent
neuroprotective effect. The positive control, edaravone, exhibited
protective effect on the OGD/R-injured PC12 cells, with cell survival
rates of 65.47%, 66.71%, and 74.31% at concentrations of 12.5 μM, 25
μM, and 50 μM, respectively, and those of compound 17 were 68.39%,
69.62%, and 74.16%, respectively, indicating that compound 17 exhibited
neuroprotective effect comparable to that of edaravone. The above
results indicate that compound 17 is a promising antistroke drug
candidate.
Figure 5.
[101]Figure 5
[102]Open in a new tab
Neuroprotective effects of the isolated compounds on ODG/R-induced PC12
cells (means ± SDs, n = 3). ^### p < 0.001 versus the control, * p <
0.05, ** p < 0.01, and *** p < 0.001 versus OGD/R. Positive control:
edaravone (Eda).
2.4. Transcriptomic and Bioinformatic Analyses and qPCR Experiments Results
Transcriptome sequencing analysis was performed to further elucidate
the protective effect of compound 17 on the OGD/R-injured PC12 cells
and to determine the variations in transcriptome levels among the
normal group, model group, and treatment group. Box plot distributions
of transcripts per million (TPM) depict the median and quartile values
of mRNA expression across different groups ([103]Figure 6A). Principal
component analysis revealed that the distinct groups could be readily
distinguished, suggesting that the transcriptional profile of PC12
cells was altered by OGD/R and drugs ([104]Figure 6B). Additionally,
differential gene expression analysis was conducted. The results
revealed that compared with the normal group, the model group contained
99 downregulated genes and 112 upregulated genes. Furthermore, compared
with the normal group, the treatment group contained 323 downregulated
genes and 232 upregulated genes, and when the treatment group was
compared with the model group, 14 downregulated genes and 8 upregulated
genes were observed ([105]Figure 6C).
Figure 6.
[106]Figure 6
[107]Open in a new tab
Differentially expressed gene (DEG) analysis. (3 = compound 17) (A) Box
plot of log[2] (TPM) values for mRNA under different conditions. (B)
PCA diagram of normalized mRNA expression values illuminating the
general relationship between datasets. (C) Upregulated and
downregulated genes in the mRNA database among the three groups. The
green dots indicate downregulated genes, and the red dots indicate
upregulated genes.
Next, clustering analysis was performed to describe the widespread
patterns and trends of transcriptional changes. Based on the scaled and
centralized mean expression values obtained, we applied the fuzzy
c-means clustering algorithm to the protein-coding genes and determined
the optimal number of clusters (k = 6) through gap statistics
([108]Figure 7A). Heatmaps and line plots depict the dynamic
transcriptional features of the normal group, model group, and
treatment group ([109]Figure 7B). Among the six clusters, significant
differences were observed in the increase in genes in cluster 2 after
modeling and the decrease in genes in cluster 2 after treatment
([110]Figure 7C,D). Based on the GO enrichment analysis and KEGG
pathway enrichment analysis of the gene cluster, GO enrichment analysis
of cluster 2 focused primarily on processes such as proteasome-mediated
ubiquitin-dependent protein catabolic processes, protein acylation, the
endoplasmic reticulum membrane, histone modification, and DNA
replication. KEGG enrichment analysis revealed that the enriched genes
were related mainly to the cell cycle, endoplasmic reticulum protein
processing, and nuclear transport. Next, by taking the intersection of
cluster 2 genes and DEGs, we identified the key gene Col27a1
([111]Figure 8A). To verify the reliability of the RNA sequencing
(RNA-Seq) results, qPCR was used to validate the differentially
expressed genes (Col27a1, Banp, Hmgcs1, Insig1, Sytl3, Gsta5, Egr1, and
Armcx5). The qPCR results were similar to the RNA-Seq results,
indicating the reliability of the RNA-Seq results ([112]Figure 9). A
literature review revealed that Col27a1 is regulated by SOX9
[[113]29,[114]30], but its role in OGD/R must be further investigated.
According to the GO and KEGG enrichment analyses of the Col27a1 gene,
we may focus on pathways related to developmental growth and protein
digestion and absorption in the subsequent studies ([115]Figure 8B,C).
Figure 7.
[116]Figure 7
[117]Open in a new tab
Global changes in gene expression for multiple time points. (3 =
compound 17) (A) Optimal number of clusters. (B) Line plot displaying
the expression patterns of mRNAs and cluster centroids identified by
the fuzzy c-means algorithm at different developmental time points. (C)
Heatmap displaying six obtained clusters with dynamic gene expression
patterns. (D) The clusters’ overall gene expression dynamics are
displayed as area plots (visualized in relation to cluster centroids).
Figure 8.
[118]Figure 8
[119]Open in a new tab
Identification of key genes. (3 = compound 17) (A) Key genes identified
via a Venn diagram. (B,C) GSEA enrichment analysis showing that DEGs
are significantly enriched in the developmental growth pathway (B) and
protein digestion and absorption (C).
Figure 9.
[120]Figure 9
[121]Open in a new tab
Comparisons of the expression patterns of Sytl3, Gsta5, Hmgcs1, Insig1,
Egr1, Armcx5, Col27a1, and Banp obtained via qPCR and those obtained
via RNA-seq.
Overall, the present study has enriched the pharmacological and
phytochemical studies of G. conopsea. For the first time, G. conopsea
was found to have an in vitro antistroke effect, which offers a new
perspective to better understand the pharmacological actions of this
medicinal plant and reveals more possibilities for its further
applications. A total of 4 undescribed compounds, along with 13 known
compounds, were isolated and identified. These compounds are phenolic
glycosides, alkaloids, and organic acid glycosides, and this finding
supports the previous phytochemical results of G. conopsea [[122]11].
Eight compounds exhibited protective effects on the OGD/R-injured PC12
cells at the tested concentrations. More importantly, the activity of
compound 17 was comparable to that of edaravone. Transcriptomic and
bioinformatic analyses, along with qPCR experiments, indicate that the
in vitro antistroke effect of compound 17 may be associated with the
regulation of the Col27a1 gene. However, the related mechanisms need
further investigation. Structural modification and target confirmation
studies are needed to identify the lead compounds based on compound 17
for novel drug development. Overall, our studies highlight the
medicinal value of G. conopsea and provide a theoretical basis for its
further development and utilization.
3. Materials and Methods
3.1. General Experimental Procedures
The 1D and 2D NMR data were measured on a Bruker AVANCE 600 (Bruker,
Billerica, MA, USA) spectrometer using TMS as an internal standard.
HRESIMS analyses were performed on a MaXis quadrupole time-of-flight
mass spectrometer (Bruker, Billerica, MA, USA). UV spectra, IR spectra,
CD spectra, and optical rotations were recorded on a Shimadzu U-3900
spectrometer (Shimadzu, Kyoto, Japan), Varian Cary 610/670 IR
spectrometer (Varian, Palo Alto, CA, USA), J-810 Circular Dichroism
spectrapolarimeter (JASCO, Tokyo, Janpan), and WZZ-2B automatic
polarimeter (Shanghai Sincere Dedication of Science and Technology
Innovation, Shanghai, China), respectively. Column chromatography
(CC)-based separations were performed using a Sephadex LH-20 column
(Cytiva, Uppsala, Sweden), silica gel (Qingdao Marine Chemistry Ltd.,
Qingdao, China), and an ODS C18 column (Merck, Darmstadt, Germany).
Semipreparative high-performance liquid chromatography (HPLC)
separations were performed via an Agilent 1260 Infinity II (Agilent
Technologies, Palo Alto, CA, USA) instrument equipped with a Cosmosil
ODS column and a DAD detector. All the solvents used were of analytical
grade (Sinopharm Chemical Reagent Co., Ltd., Shanghai, China).
3.2. Plant Material
Tubers of G. conopsea were collected from Tibet, China, in March 2020
and identified by Prof. Liang Liu, one of the authors. A voucher
specimen (SZS20200328) was deposited at the Medical College of Yangzhou
University.
3.3. Extraction and Isolation
The dried tubers of G. conopsea (20.0 kg) were ground into a powder and
extracted three times with aqueous ethanol (EtOH) (95%, v/v). The
combined extract was filtered and concentrated under reduced pressure
to generate a residue (1.0 kg), which was separated via a D101
macroporous resin (20 kg/30 BV) CC, with a flow rate of approximately
2–3 BV/h. Gradient elution was carried out using 30% ethanol, 50%
ethanol, and 75% ethanol, yielding the following fractions: D30 (Fr. 1,
231.4 g), D50 (Fr. 2, 78.8 g), and D75 (Fr. 3, 78.3 g). Fr. 1 was
subjected to silica gel (200–300 mesh) CC using a
dichloromethane–methanol gradient (50:1 to 0:1) to yield 9 fractions
(Fr. 1.1 to Fr. 1.9). After Fr. 1.3 was recrystallized, compound 8
(10.5 mg) was obtained. Fr. 1.4 was subjected to several purification
processes, including Sephadex LH-20 CC and ODS CC, purified by
semipreparative HPLC, and eluted with ACN/H[2]O (3:17) to obtain
compounds 14 (4.7 mg) and 15 (3.1 mg). Then, several purification
processes were performed on Fr. 1.7, including silica gel CC (200–300
mesh, silica gel H), ODS CC, and Sephadex LH-20 CC, resulting in the
isolation of compounds 10 (5.7 mg), 11 (9.5 mg), 12 (30.6 mg), 13 (1.0
mg), and 16 (2.0 mg). Subsequently, semipreparative HPLC purification
was performed using ACN/H[2]O (1:4) as the elution solvent, yielding
compound 17 (21.3 mg). Fr. 2 was subjected to silica gel (200–300 mesh)
CC with a dichloromethane–methanol gradient (50:1 to 0:1), generating
nine fractions (Fr. 2.1 to Fr. 2.9). Fr. 2.1 was subjected to ODS CC
with a methanol–water gradient (1:9 to 1:0), resulting in the isolation
of four subfractions (Fr. 2.1.1 to Fr. 2.1.4). Fr. 2.1.2 was further
purified through semipreparative HPLC with ACN/H[2]O (1:4) as the
elution solvent, yielding compound 9 (7.5 mg). Fr. 2.5 was subjected to
silica gel H CC with a dichloromethane–methanol gradient (50:1 to 0:1),
resulting in eight subfractions (Fr. 2.5.1 to Fr. 2.5.8). Fr. 2.5.5 was
purified by semipreparative HPLC using ACN/H[2]O (1:3) as the elution
solvent to generate compounds 1 (3.1 mg), 2 (2.7 mg), 3 (2.1 mg), 4
(1.7 mg), 5 (1.7 mg), 6 (4.4 mg), and 7 (2.8 mg).
Compound 1. Pale yellow powder; [α
[MATH: ]D25 :MATH]
−1.13 (c 0.04, MeOH); UV (MeOH) λ[max] (logє) 209.5 nm (3.72), 223.5 nm
(3.59), and 280.5 nm (3.17); IR (KBr) v[max] 3376, 3070, 2919, 1610,
1511, 1220, 1074, and 1022 cm^−1; CD (MeOH) 204.1 nm (−1.43), 210.3 nm
(−7.11), 215.7 nm (−3.17), 220.5 nm (−4.00), 227.3 nm (−1.90), 247.4 nm
(+0.26), and 278.8 nm (−1.45); ^1H-NMR (CD[3]OD, 600 MHz) and ^13C-NMR
(CD[3]OD, 150 MHz) data in [123]Table S1; HRESIMS (m/z): 415.1363 [M +
Na]^+ (calcd. for C[20]H[24]O[8]Na, 415.1363).
Compound 2. Pale yellow powder; [α
[MATH: ]D25 :MATH]
+2.59 (c 0.04, MeOH); UV (MeOH) λ[max] (logє) 218.5 nm (3.61) and 279.5
nm (2.97); IR (KBr) v[max] 3384, 2925, 1612, 1509, 1226, 1076, and 819
cm^−1; CD (MeOH) 210.0 nm (+9.08), 223.0 nm (−6.75), and 271.2 nm
(−2.33); ^1H-NMR (CD[3]OD, 600 MHz) and ^13C-NMR (CD[3]OD, 150 MHz)
data in [124]Table S1; HRESIMS (m/z): 399.1409 [M + Na]^+ (calcd. for
C[20]H[24]O[7]Na, 399.1414).
Compound 13. White amorphous powder; UV (MeOH) λ[max] (logє) 209.5 nm
(4.21), 229.5 nm (4.14), and 251.5 nm (4.05); IR (KBr) v[max] 3455,
3268, 2784, 1691, 1590, 1511, 1228, and 767 cm^−1; ^1H-NMR (CD[3]OD,
600 MHz) and ^13C-NMR (CD[3]OD, 150 MHz) data in [125]Table S2; HRESIMS
(m/z): 243.0871 [M + H]^+ (calcd. for C[12]H[11]N[4]O[2], 243.0877).
Compound 17. Colorless transparent gum (MeOH); [α
[MATH: ]D25 :MATH]
−0.26 (c 0.31, MeOH); UV (MeOH) λ[max] (logє) 203.5 nm (3.18), 209.1 nm
(3.16), and 261.2 nm (2.68); IR (KBr) v[max] 3380, 2954, 2871, 1733,
1438, 1394, 1236, 1074, 1031, and 644 cm^−1; CD (MeOH) 211.0 nm
(+72.57); ^1H-NMR (CD[3]OD, 600 MHz) and ^13C-NMR (CD[3]OD, 150 MHz)
data are shown in [126]Table S3; HRESIMS (m/z): 389.1423 [M+Na]^+
(calcd. for C[15]H[26]O[10]Na, 389.1418).
3.4. Acid Hydrolysis
Compound 1 (1.5 mg) was heated at 80 °C for 4 h in 3 mL of 10%
HCl–dioxane (1:1). After dioxane was removed, the solution was
extracted with ethyl acetate (3 mL × 3) to obtain aglycones and sugars.
The aqueous layer was neutralized with NaHCO[3] and concentrated
[[127]31]. The residual sugar components in the water layer after acid
hydrolysis were analyzed by TLC and compared with those of standard
sugars. The solvent system was CHCl[3]–MeOH–H[2]O (8:5:1), and 95%
EtOH–H[2]SO[4]–anisaldehyde (9:0.5:0.5, v/v) was sprayed to yield spots
by heating at 120 °C for 10 min. The same analysis was carried out on
compounds 2 and 17.
3.5. Computer Simulations
The computational chemistry workflow involved the use of Gaussian 09
for both density functional theory (DFT) and time-dependent density
functional theory (TD-DFT) calculations. GaussView was used for
structure generation and analysis, and theoretical calculations were
conducted on the ECD or NMR data of the compounds. Fitting was
performed via Origin 2021 and SpecDis 1.71 (σ = 0.30 eV). With the help
of the SPARTAN 16 program package, the initial conformation of compound
17 was analyzed via the Monte Carlo search algorithm through the MMFF94
molecular mechanics force field, and the low-energy conformation
accounting for more than 2% of the equilibrium population was applied
to the next calculation. The minimum energy conformation of the force
field obtained was subsequently optimized by performing DFT
calculations at the B3LYP/6-31G (d) energy level in the Gaussian 09
software package. The NMR computations were performed with DFT
calculations at the mPW1PW91/6-311G (2d, p) level in MeOH via the
polarizable continuum model (PCM) solvent model. Additionally,
structural confirmation was enhanced via methods such as DP4+. For the
ECD calculations, by using PCM solvent model, time-dependent density
functional theory (TDDFT) calculations were carried out at the
B3LYP/6-311G (d, p) level in MeOH to perform theoretical ECD
calculations on these main conformations. The energy, oscillator
strength, and rotational strength of each conformation were calculated
via the Gaussian 09 software package. According to the Boltzmann
weighted overall contribution of SpecDisv1.71, the final ECD spectra of
the individual conformers were summed.
3.6. Neuroprotective Effect Evaluation
The PC12 cells were cultured in complete RPMI 1640 medium supplemented
with 10% fetal bovine serum and 1% penicillin-streptomycin. The cells
were inoculated at a density of 5 × 10^4 cells/mL into a 96-well plate
in the following groups: control group, OGD/R group, and treatment
group (OGD/R + tested fractions or compounds). After the cells had
adhered to the well, the original culture medium was removed, and the
wells were washed twice with PBS. The control group was replenished
with the original culture medium and maintained under the original
conditions. Moreover, the OGD/R and treatment groups were supplied
glucose-free DMEM and subjected to low-oxygen treatment for 6 h in a
three-gas incubator containing 1% O[2], 94% N[2], and 5% CO[2].
Following the deprivation period, the DMEM glucose-free culture medium
was replaced with complete 1640 medium (OGD/R group) or medium
containing various concentrations of fractions or compounds, and the
cells were maintained under the original conditions to stop glucose and
oxygen deprivation. After 24 h, the intervention was terminated, and 10
μL of CCK-8 working solution was added to each well. The plate was then
incubated for 90 min. Finally, the absorbance value (OD value) was
measured via an enzyme-linked immunosorbent assay (ELISA) at a
wavelength of 450 nm. Edaravone was used as the positive control.
3.7. RNA Extraction, Library Preparation and Sequencing
Total RNA was extracted via a TRIzol reagent kit (Invitrogen, Carlsbad,
CA, USA) according to the manufacturer’s protocol. RNA quality was
assessed on an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo
Alto, CA, USA) and checked via RNase-free agarose gel electrophoresis.
RNA purification, reverse transcription, library construction, and
sequencing were performed at Shanghai Majorbio Biopharm Biotechnology
Co., Ltd. (Shanghai, China) according to the manufacturer’s
instructions (Illumina, San Diego, CA, USA). The raw paired-end reads
resulting from sequencing were aligned to a reference rat genome
(mRatBN7.2) via the rnaseq pipeline from nf-core.
3.8. Differential Expression Analysis
Differential gene expression analysis across various groups was
performed via the R package DESeq2 (version: 1.34.0) [[128]32], and
genes with p-adj < 0.05 and |log[2]FC| ≥ 0.26 were identified as
differentially expressed genes. Gene functional enrichment analysis was
conducted via hypergeometric distribution tests using enrichGO and
enrichKEGG in the R package clusterProfiler (version: 4.2.2) [[129]33].
Enriched pathways with a significance threshold of p < 0.05 were
retained.
3.9. Soft Clustering Analysis
The fuzzy c-means (FCM) clustering algorithm in the R package Mfuzz
(version: 2.54.0) was used to perform soft-clustering analysis to
identify various expression patterns of genes in time series
experimental designs [[130]34]. In this analysis, parameters c (number
of clusters) and m (fuzzification parameter) were employed. The value
of parameter c was determined by assessing the sum of the squared
errors generated as the number of clusters increases. Additionally, the
mestimate function within the Mfuzz software (version: 2.62.0) package
was utilized to obtain a value for parameter m.
3.10. qPCR Assay
The qPCR primers were designed via Primer Premier 5.0 software on the
basis of the gene sequence published in the GenBank database. The GAPDH
gene was used as an internal control. All primers were synthesized by
Sangon Biotechnology (Shanghai, China), and the corresponding sequences
are shown in [131]Table S4. qPCR analysis was performed via a real-time
fluorescence quantification kit (Vazyme Biotech Co., Ltd. Nanjing,
China). All qPCR assays were conducted in a 20 µL mixture composed of 2
µL of cDNA, 0.4 µL of each primer (10 µmol/L), 10 µL of 2×AceQ
Universal SYBR qPCR Master Mix, and 7.2 µL of ddH[2]O. The thermocycler
settings were as follows: 95 °C for 5 min; 40 cycles at 95 °C for 5 s
and 60 °C for 30 s. Melting curves were then used to confirm the
specificity of the amplified products. Three independent experimental
replicates were conducted for all analyses. The results of relative
quantification were analyzed and processed via the 2^−ΔΔCt method.
3.11. Statistical Analysis
All the data are presented as the means ± SDs for each group and were
evaluated via one-way analysis of variance (ANOVA). All the results of
the cell experiments were statistically analyzed via SPSS Version 25.0
for Windows (IBM SPSS Inc., Chicago, IL, USA). p < 0.05 was considered
statistically significant. All the results of the RNA-Seq experiments
were statistically analyzed in the R environment (version: 4.1.3), and
the data were visualized via the R package ggplot2 (version: 3.3.5).
4. Conclusions
In the present study, we revealed the in vitro antistroke effect of G.
conopsea for the first time, which offers a new angle of view for its
pharmacological action study. Then, a bioactivity-guided separation
strategy was performed to identify the antistroke constituents of G.
conopsea. This process led to the isolation of 4 undescribed compounds,
along with 13 known compounds, among which 8 compounds exhibited
protective effects on OGD/R-injured PC12 cells at the tested
concentrations. More importantly, compound 17 is a promising candidate
for the development of novel antistroke drugs and deserves further
study.
Supplementary Materials
The supporting information can be downloaded at
[132]https://www.mdpi.com/article/10.3390/molecules29184389/s1.
[133]molecules-29-04389-s001.zip^ (2.5MB, zip)
Author Contributions
Conceptualization, formal analysis, investigation, and writing—original
draft, J.Q.; formal analysis and investigation, S.X., C.X. and J.J.;
supervision, J.W. and H.Y.; and funding acquisition, resources,
supervision, and writing—review and editing, L.L. All authors have read
and agreed to the published version of the manuscript.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
The original contributions presented in the study are included in the
article/[134]Supplemental Materials. Further inquiries can be directed
to the corresponding author.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
Funding Statement
This research was supported by the High-end Talents Supporting Project
of Yangzhou University (No. 20190223) and the Postgraduate Scientific
Research Innovation Project of Jiangsu Province (No. KYCX22_3573).
Footnotes
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References