Abstract
Parkinson's disease (PD) is one of the most prevalent neurodegenerative
disorders with no precise etiology. Multiple lines of evidence support
that environmental factors, either neurotoxins or neuroinflammation,
can induce Parkinsonism. In this study, we purified an active compound,
neobaicalein (Skullcapflavone II), from the roots of Scutellaria
pinnatifida (S. pinnatifida). Neobaicalein not only had protective
impacts on rotenone-induced neurotoxicity but in glial cultures, it
dampened the inflammatory response when stimulated with
lipopolysaccharide (LPS). Neobaicalein had high antioxidant activity
without any obvious toxicity. In addition, it could raise the cell
viability, decrease early apoptosis, reduce the generation of reactive
oxygen species (ROS), and keep the neurite's length normal in the
treated SH-SY5Y cells. Pathway enrichment analysis (PEA) and target
prediction provided insights into the PD related genes, protein-protein
interaction (PPI) network, and the key proteins enriched in the
signaling pathways.
Furthermore, docking simulation (DS) on the proteins of the PD-PPI
network revealed that neobaicalein might interact with the key proteins
involved in PD pathology, including MAPK14, MAPK8, and CASP3. It also
blocks the destructive processes, such as cell death, inflammation, and
oxidative stress pathways. Our results demonstrate that neobaicalein
alleviates pathological effects of factors related to PD, and may
provide new insight into PD therapy.
Keywords: Neuroinflammation, Neurotoxins, Neobaicalein, PD's omics
data, Systematic bioinformatics analysis, Cytotoxicity, Biochemistry,
Health sciences, Information science, Network analysis
__________________________________________________________________
Neuroinflammation, Neurotoxins, Neobaicalein, PD's omics data,
Systematic bioinformatics analysis, Cytotoxicity, Biochemistry, Health
sciences, Information science, Network analysis
1. Introduction
Parkinson's disease (PD) is the second-most prevalent neurodegenerative
disorder and the most common form of Parkinsonism with severe chronic
symptoms. The interaction between environmental and genetic factors has
an essential role in the pathogenesis of PD. The exposure to
environmental neurotoxins such as pesticides and excess metals is a
significant contributor to the development of PD and other forms of
Parkinsonism [[33]1, [34]2, [35]3]. One of the most well-known toxins
is rotenone, a natural compound used as a pesticide [[36]4], which can
pass through the blood-brain barrier (BBB) [[37]5]. It causes apoptotic
cell death of tyrosine hydroxylase-positive neurons in substantia nigra
(SN) of rats [[38]6]. It induces aggregation of αSN, Aβ, and Tau in
rotenone-treated mice, inhibits mitochondrial complex I, and eventually
leads to dopaminergic neurodegeneration [[39]7, [40]8, [41]9]. Rotenone
binds to tubulin at the colchicine-site [[42]10], which disturbs its
structure, and depolymerizes microtubules [[43]11]. It also induces
morphological apoptotic features in dopaminergic cells [[44]12,
[45]13]. The use of rotenone in the rat's model of PD has shown the
generation of proteinaceous inclusions in some dopaminergic neurons
that cannot be found in the 6-OHDA and MPTP models [[46]14]. Overall,
it could be an acceptable neurotoxic agent for developing a good model
of PD.
Moreover, internal factors are also known as key participants in the
onset, development, and progression of PD. The main internal factors
are neuroinflammation, oxidative stress, mitochondrial dysfunction,
α-synuclein aggregation, and calcium hemostasis dysregulation [[47]15].
Microglial activation, which usually accompanies the release of
pro-inflammatory cytokines and also ROS production, associates with
dopaminergic neuronal death in PD [[48]16]. Postmortem studies show
elevated pro-inflammatory cytokines such as TNF-α, IL-1β, IL-2, IL-4,
IL-6, IL-10, IFNγ in the striatum, and activated glial cells within the
SN of PD patients [[49]17]. Microglial activation and increased levels
of cytokines have been observed in the mice and adult rats treated with
LPS, and the investigation has shown that direct injection of LPS into
the SN of mice causes TH^+ cell loss [[50]18, [51]19]. Given the
importance of neuroinflammation in PD, developing the compounds with
anti-inflammatory effects can have therapeutic benefits. In this
context, small phytochemical molecules, especially flavonoids, could be
potent modulators [[52]20] as they have antioxidant, anti-inflammatory,
and anti-amyloidogenic properties [[53]21, [54]22, [55]23]. A recent
study showed that small molecules could protect mitochondria in
neurodegenerative diseases [[56]24]. These metabolites seem to have a
multi-target mechanism of action and interact with different signaling
cascades, which can lead to neuronal survival [[57]25, [58]26].
Furthermore, they can cross the BBB [[59]27], induce neurogenesis, and
exert free radical scavenging properties [[60]28]. One source of
flavonoids is the Scutellaria genus, which belongs to the Lamiaceae
family [[61]29]. Extracts and isolated active constituents from
Scutellaria have antioxidant, anti-inflammatory, and neuroprotective
properties [[62]30]. Scutellaria pinnatifida (S. pinnatifida), locally
known as Boshghabi [[63]31], is one of the Iranian species of the
Scutellaria genus. This genus is renowned for its medical benefits for
insomnia, cancer, hepatitis, allergy, and arteriosclerosis [[64]32,
[65]33]. We have previously shown that its flavonoid contents,
particularly those extracted with dichloromethane (DCMex), have the
highest inhibitory activity against the aggregation of α-synuclein, and
show antioxidant properties [[66]34].
Taking all the noteworthy biological features of S. pinnatifida into
account, we investigated the chemical composition of DCMex, isolated
neobaicalein (skullcapflavone II), and for the first time evaluated its
neuroprotective effects on rotenone-induced cell toxicity and LPS
induced inflammation. Due to the multiple biological functions of the
small molecules, the in silico experiments, virtual screening, and
reverse docking methods can simulate their action and shed light on
their interaction with new targets [[67]35, [68]36]. Here, different
methods such as pathway enrichment analysis, reverse docking, and MD
simulation were employed to anticipate the mechanism of multiple
neuroprotective activities of neobaicalein and offer a convenient
perspective towards therapeutic drugs for PD.
2. Experimental procedures
2.1. Reagents and chemicals
2′,7′-dichlorodihydrofluorescein diacetate (DCFH-DA),
1,1-diphenyl-2-picrylhydrazyl (DPPH^•),
3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT),
Griess reagent and rotenone were purchased from Sigma-Aldrich. SH-SY5Y
neuroblastoma cell line was acquired from Pasteur Institute (Iran). All
salts and organic solvents were purchased from Merck (Darmstadt,
Germany). The cell culture medium (DMEM-F12, High glucose), fetal
bovine serum (FBS), and antibiotics were from GibcoBRL (Life
Technologies, Paisley, Scotland). Standard blood agar plates were from
Mehrazmalab (Iran), Silica gel (60–100 mesh, pore size 60 Å), and TLC
plates from Sigma-Aldrich (Germany). Neonatal Wistar rats were
purchased from Pasteur Institute, Iran.
2.2. Plant materials
S. pinnatifida was collected in August 2018 from the road of Asalem to
Khalkhal area (Gilan, Iran). The plant has been deposited at the
Herbarium of TARI (Iran) with a voucher specimen (No. 107147). It was
dried at room temperature, and the roots were ground by an electric
blender to increase its surface extent. The air-dried powder roots were
kept in a cold and dry place until they were used for the extraction.
2.3. S. pinnatifida extraction and fractionation procedures
We decided to choose the dichloromethane extract (DCMex) for more
comprehensive analysis as it has the most protective effect on the
α-synuclein fibrillation and neurotoxicity, among other S. pinnatifida
fractions [[69]34]. The air-dried powder roots (170 g) were soaked in 1
L n-hexane solvent at room temperature to eliminate the hydrophobic
compounds. After 48 h, the whole n-hexane extract was removed, and then
the extraction was progressed on the root residues by dichloromethane
(DCM) solvent at room temperature. After 72 h, the whole extract was
filtered, and the solvent was evaporated by a rotary evaporator under
vacuum at 25 °C. The resulted extract (DCMex) was kept at -20 °C for
future studies.
2.3.1. Purification of neobaicalein
2.3.1.1. Evaluation of the extract by thin-layer chromatography (TLC)
The content of the DCMex was analyzed with TLC. Each sample was spotted
on a TLC plate with n-hexane/ethyl acetate (1.5:1) as a mobile phase.
2.3.1.2. Purification of neobaicalein using column chromatography
We used the cylindrical glass column (length = 20 cm, diameter = 1.5
cm) to purify the compounds of DCMex. The concentrated DCMex was run
through a silica gel column chromatography with a gradient of
n-hexane–ethyl acetate as eluent. The column washing initially started
with low polarity solvents (n-hexane: ethyl acetate ratio of 9 to 1) to
a medium polarity and finally ended by adding 100% ethyl acetate.
Twenty fractions were collected, and the purity of the components in
each fraction was evaluated by TLC. Therefore, the same spots on the
TLC plate were mixed and subjected to structure elucidation by ^1H-NMR.
The final compound was dissolved in DMSO and kept at -20 °C.
2.4. Free radical scavenging activity of neobaicalein
100 μL of neobaicalein with different concentrations (0.2, 0.3, 0.5,
and 0.8 mM) was mixed with 200 μL of DPPH^• (final concentration = 100
μM dissolved in methanol), and the mixture was incubated in the dark
for 60 min [[70]37]. The scavenging activity of neobaicalein to reduce
DPPH^• was measured at 517 nm with a plate reader (microplate
spectrophotometer, Epoch 2, BioTek company, Gen5 software, USA). The
experiment was carried out in triplicate, and methanol was used as
blank. The percentage of antioxidant activity was calculated as follow:
[MATH: %ofantioxidantactivity =OD(517nm)ofcontrol−OD(517nm)ofsampleOD(517nm)ofcontrol×100 :MATH]
(1)
where “control” is the untreated DPPH^•, and “sample” is DPPH^• in the
presence of different concentrations of neobaicalein.
2.5. Hemolysis assay
To assess the biocompatibility of neobaicalein, a 100 μL of the
compound)final concentration 0.5 mM( was spread on the surface of a
blood agar plate and incubated for 24 h at 37 °C. As a control, an
equivalent of 0.5 McFarland of Staphylococcus aureus was cultured on
the same culture medium and incubated for 24 h at 37 °C. The lack of
detectable hemolysis was regarded as a mark of biocompatibility
[[71]37, [72]38].
2.6. The effects of rotenone on SH-SY5Y cell line in the presence and absence
of neobaicalein
MTT, ROS, flow cytometry, and the morphology of neurons were
investigated to assess the neurotoxicity effect of rotenone against
dopaminergic SH-SY5Y cells and the neuroprotective effect of
neobaicalein against rotenone. The cells were cultured in DMEM-F12
supplemented with 10% FBS, 100 U/mL penicillin, and 100 μg/mL
streptomycin at 37 °C in a humidified atmosphere with 90% humidity and
5% CO[2]. Rotenone and neobaicalein were dissolved in dimethyl
sulfoxide (DMSO, 100%). Different concentrations of neobaicalein were
added to the cell cultures one hour before adding rotenone (500 nM).
2.6.1. Assessment of the cell metabolic activity
There were four distinct groups: control group (the cells with no
treatment), neobaicalein group (the cells treated with different
concentrations of neobaicalein), rotenone-group (the cells treated with
500 nM of rotenone), and rotenone/neobaicalein group (the cells
pretreated with neobaicalein for one hour followed by exposure to 500
nM rotenone). The MTT colorimetric assay was used to evaluate the
mitochondrial metabolism of viable cells. The oxidoreductase enzymes in
living cells can convert the tetrazolium MTT (yellow dye) to insoluble
purple formazan. SH-SY5Y cells were seeded at a density of 10^4
[cells/well] in 96-well plates (200 μL) incubated for 24 h and treated
with 20, 50, 150, 250 μM of neobaicalein to evaluate the possible
cytotoxic effect. Afterward, the cells were incubated with rotenone
(500 nM) in the presence or absence of neobaicalein for 24 h. The media
were then replaced with fresh pre-warmed media supplemented with 10%
(v/v) MTT stock solution (5 mg/mL in PBS). After 4 h of incubation, 100
μL DMSO was added to dissolve the formazan crystals. To assess the
mitochondrial metabolic activity, the absorbance was read at 570 nm
(microplate spectrophotometer, Epoch 2, BioTek company, Gen5 software,
USA) and the percentage of the viable cells was calculated as follow
[[73]37]:
[MATH: Cellviability(%)=(Absorbance570nm(treatedcells)(Absorbance570nm(untreatedcells)×100 :MATH]
(2)
2.6.2. Flow cytometry to detect early apoptosis and late apoptosis/necrosis
The cells were seeded in 6-well plates at a density of 5×10^5
[cells/well], treated with neobaicalein (150 μM) in the absence or
presence of 500 nM of rotenone and incubated for 24 h. The cells were
then trypsinized (0.25% trypsin, one mM EDTA) and centrifuged for 3 min
at 2000 rpm. The pellets were rinsed with PBS, resuspended in the
binding buffer containing FITC-conjugated Annexin V and PI, incubated
for 5 min in the dark, and then loaded on a Gallios Flow Cytometer
(Beckman Coulter, CA, USA). The percentages of apoptotic or late
apoptotic/necrotic cells were analyzed using Flowing Software v.2.5
[[74]38].
2.6.3. The measurement of intracellular ROS
To assess reactive oxygen species (ROS) activity within the cells, the
cell-permeant fluorogenic reagent DCFH-DA was employed. After diffusion
into cells, DCFH-DA is deacetylated by esterases, which are later
oxidized by ROS into a highly fluorescent compound DCF [[75]39].
SH-SY5Y cells were seeded in 96-well plates with densities of 2 × 10^4
[cells/well] (200 μL) and incubated in the incubator (5% CO[2], 90%
humidity) for 24 h. Subsequently, the cells were treated with 50, 150,
250 μM of neobaicalein in the absence or presence of rotenone (500 nM),
incubated for 6 h in a humidified atmosphere, and DCFH-DA (15 μM) was
added to each well. After 45 min incubation in the dark, the cells were
trypsinized, and their fluorescence emission intensity was measured at
527 nm (excitation: 495 nm).
2.6.4. The differentiated SH-SY5Y cell neurite length analysis
SH-SY5Y cell line is able to undergo neuronal maturation. The cells can
be differentiated into neuron-like cells with neurites outgrowth in
response to all-trans-retinoic acid (RA) [[76]40]. Therefore,
differentiated SH-SY5Y cells have been used as appropriate in vitro
cell model to study the mechanism of rotenone neurotoxicity. SH-SY5Y
cells were grown in 12-well plates to a density of 4×10^4 [cells/well]
and then treated with RA dissolved in DMEM-F12 (2% FBS) to a final
concentration of 10 μM, incubated for eight days (the medium was
replaced every two days) [[77]41]. Subsequently, neobaicalein (150 μM)
in the absence or presence of rotenone (500 nM) was added to each well.
Within 12 h of incubation, the length of the neurites was analyzed
using the Image J software (NIH, USA). The images were taken at 20x
magnification with 4608 × 2592 pixels. By changing the pixels to μM,
the images were calibrated, and then Neuron J [[78]42] plugin Image J
software was used to measure the length of neurites by tracing them
[[79]43].
2.7. NO^• production in the primary mixed glial cells of the rat brain
The rat pups of Wistar strain, less than 72-hour-olds, were used for
the preparation of mixed glial cell cultures. The whole process was
done according to the guidelines of the National Institute of Genetic
Engineering and Biotechnology Ethics Committee (ethics number:
IR.NIGEB.EC.1398.10.18. A). Briefly, the brain was separated from the
cranium, and meninges/vessels were removed carefully using forceps.
Next, the tissue was mechanically triturating by pipetting, and the
cell suspension was placed into a tissue culture flask. The cells were
grown in DMEM high glucose medium supplemented by 20% FBS, 100 U/mL
penicillin, and 100 μg/mL streptomycin at 37 °C and 5% CO[2]. The
medium was changed the next day after the culture establishment and at
five-day intervals. In 5–7 days, the astrocytes form a confluent cell
layer, and microglia and some oligodendrocytes grow on top of the
astrocytic layer. In order to induce inflammation on mixed glial cells,
the cells were trypsinized and seeded at a density of 30×10^4
[cells/well] in a 6-well plate. LPS (10 μg/μL) conducted stimulation of
astrocytes and microglia on mixed glial cells. To evaluate the
protective effect of neobaicalein, one hour prior to LPS exposure, 150
μM of the compound was used for co-treatment with LPS (10 μg/μL). After
48 h of treatment, NO^• production was assessed by indirect measurement
of nitrite concentration using colorimetric Griess assay in a 96-well
plate. This assay relies on a diazotization reaction that was initially
described by Griess in 1879 [[80]44]. Initially, 50 μL of the cell
supernatant was mixed with the 25 μL of 1% sulphanilamide, and
incubated for 5 min. Subsequently, 25 μL of 0.1% N-1-naphthyl
ethylenediamine dihydrochloride (NED) was added, and the samples were
incubated for 5 min in the dark. The absorbance was then measured by a
microplate reader at 540 nm. Standards of sodium nitrite in the range
of 20–200 μM were used to calibrate the assay validation.
2.8. Target prediction and toxicity profile of neobaicalein
2.8.1. Network analysis for PD related genes
To predict the effect of neobaicalein on PD, we first designed a PD
network to identify the key proteins and related molecular pathways. To
this end, the DisGeNET database ([81]http://www.disgenet.org/) was used
to access the genes associated with PD. This platform collects
information from four different sources, including Online Mendelian
Inheritance in Man (OMIM), UniProt/SwissProt (UNIPROT),
Pharmacogenomics Knowledge Base (PharmGKB) and Comparative
Toxicogenomics Database (CTD).
In the next step, the protein-protein interaction (PPI) network of the
related genes was plotted using the Search Tool in the Retrieval of
Interacting Genes database (STRING, [82]http://string.embl.de/). We
used the STRING app in Cytoscape and applied the confidence score ≥0.7
and the maximum number of interactors = 0 as the cut off criterion. We
calculated Radiality, BottleNeck, Betweenness, Stress, and Closeness
parameters by cytohubba plugin to determine the most important proteins
involved in the PD-related PPI network. The top 10% common genes
acquired based on these parameters were considered as hub genes and,
the related sub-network was extracted for these genes.
2.8.2. Functional and pathway enrichment analyses
Gene ontology and pathway enrichment analyses were investigated by
DAVID (Database for Annotation, Visualization, and Integrated
Discovery, [83]https://david.ncifcrf.gov/) based on the key proteins
derived from the PD-related PPI network. Then, the related signaling
pathways were extracted.
2.8.3. Druglikeness and toxicity profile
Lipinski et al. formulated specific properties, known as the Rule of
Five (RO5), to determine if the compound could be accepted as a drug
[[84]45]. To this end, MolSoft ([85]https://molsoft.com/mprop/) was
used to evaluate the neobaicalein properties based on Lipinski's rule.
Also, PreADMET ([86]https://preadmet.bmdrc.kr/) and ADVERPred
([87]http://www.way2drug.com/adverpred/) [[88]46] were applied to
assess its toxicity and probable side effects, respectively.
2.8.4. Molecular docking
A docking study was carried out by AutoDock Tools (ADT, 1.5.6) to
investigate and anticipate the interaction of neobaicalein with the key
proteins in the most significant pathways derived from enrichment
analysis. The neobaicalein structure was retrieved from the PubChem
database ([89]https://pubchem.ncbi.nlm.nih.gov/). To acquire the
optimized geometry of the neobaicalein structure, the webserver ATB,
(Automated force field Topology Builder,
[90]http://compbio.biosci.uq.edu.au/atb), was used and 3D structures of
the proteins were obtained from the RCSB PDB database
([91]https://www.rcsb.org/). To apply the PDB data of proteins to ADT,
nonessential chains, water, and ligand molecules, if present, were
removed from the structure of proteins. In addition, Kollman charges
and polar hydrogens were added to the structure files.
Furthermore, rotatable bonds of neobaicalein were indicated, gasteiger
charges were added, and non-polar hydrogens were merged in the ADT
environment. To create the map files for flexible atoms in the active
sites, AutoGrid 4.0 was applied. We used ADT to determine the Docking
Parameter File (DPF). To this end, the proteins were retained rigid
during each docking study, and the docking run was performed by the
Lamarckian Genetic algorithm, with 200 as the total number of runs.
AutoDock 4.0 was used for docking simulation, and the 2D and the 3D
binding interactions were studied with the Discovery Studio
Visualization (DSV).
2.8.5. Molecular dynamics
The Protein-Ligand complex dynamic simulations were carried out for
proteins with the lowest binding energy to check the stability of
docked conformation. All molecular dynamics (MD) simulations were
performed for 50 ns using GROMACS package 5.1 by the GROMOS9643a1 force
field. The topology parameters of the protein and ligands were obtained
from Gromacs and Dundee PRODRG server, respectively. The Simple Point
Charge (SPC) water model was used to develop the solvated systems, and
corresponding ions for each simulation were added to neutralize the
systems. Energy minimization of the docked complexes was achieved using
the steepest descent algorithm at 1000 steps, and the system
equilibration was performed under NVT and NPT ensembles at 300 k for
100 ps. In the end, the MD production run was carried out at 300 K
temperature and 1 bar pressure.
2.9. Data analysis and statistics
The experiments were carried out as triplicates, and the data was
stated as mean ± SD. SPSS software v.25.0 was used to study the
statistically significant differences between the control and
experimental groups. Unpaired Student's t-test and one-way ANOVA were
used to analyze the significant differences between the groups and
within the groups, respectively. P-value < 0.05 was considered as
significant.
3. Results
3.1. Neobaicalein was purified from the roots of Scutellaria pinnatifida
The initial analysis of DCMex through TLC showed four distinct bands
([92]Figure 1a). Among different fractions that were achieved through
purification by column chromatography, those with the same bands on TLC
were mixed and further purified. This purification yielded 12 mg of a
yellow-colored purified metabolite, related to the yellow-colored band
on TLC (RF = 0.5, efficiency: 12%) ([93]Figure 1a). The ^1H-NMR
analysis revealed the chemical structure of this metabolite
([94]Figure 1b). The physical and spectral data of the isolated
compound was identical to neobaicalein [[95]47]. Neobaicalein
(Skullcapflavone II) ([96]Figure 1c) is a flavone with the chemical
name of 5,2′-Dihydroxy-6,7,8,6′-tetramethoxyflavone and molecular
weight of 374.345 g/mol. The detail of ^1H-NMR analysis is mentioned in
the caption of [97]Figure 1.
Figure 1.
[98]Figure 1
[99]Open in a new tab
(a) Isolation pattern of DCMex (left) and neobaicalein (right) on TLC.
(b) ^1H-NMR spectrum of neobaicalein: ^1H-NMR (DMSO, 300 MHz) δ: 12.7
(1H, s, OH-6), 10.4 (1H, s, OH-b), 7.3 (1H, dd, J = 8.4, 8.1 Hz, H-d),
6.6 (2H, m, H-c, H-e), 6.2 (1H, s, H-2), 3.8 (12H, s, O–CH3-7,8,9,f).
(c) The chemical structure of neobaicalein. The full non-adjusted TLC
image is provided in the supplementary material (Figure S1).
3.2. Neobaicalein showed free radical scavenging activity with
biocompatibility character
Treating DPPH^• radicals with different concentrations of purified
neobaicalein, diminished the radicals significantly in a dose-dependent
manner ([100]Figure 2a). However, besides the radical scavenging
properties of herbal compounds, some can be toxic to biological
systems. Therefore, the biocompatibility of neobaicalein was assessed
through the hemolysis assay. The results showed no hemolysis
(γ-hemolysis) upon the spreading of neobaicalein (0.5 mM) on the blood
agar media ([101]Figure 2b).
Figure 2.
[102]Figure 2
[103]Open in a new tab
The antioxidant activity and biocompatibility of neobaicalein. (a) The
scavenging activity was assessed using DPPH^•. Neobaicalein showed
dose-dependent free radical scavenging activity (∗∗ P-value ≤ 0.01
indicates statistically significant differences between the control and
the treated samples). (b) Hemolysis assay was carried out to evaluate
the biocompatibility. Neobaicalein was spread onto the surface of the
blood agar medium. After 24 h of incubation, no hemolysis was detected
in comparison with the β-hemolysis positive control (Staphylococcus
aureus).
3.3. Neobaicalein significantly protected the treated cells against rotenone
neurotoxicity
3.3.1. MTT assay
The effect of neobaicalein on the neuronal cell survival was tested in
the presence and absence of well-known neurotoxic agent rotenone. The
viability of SH-SY5Y cells treated with different concentrations of
neobaicalein (20, 50, 150, 250 μM) did not reduce significantly.
However, rotenone (500 nM) induced significant cell death after 24 h of
treatment (P-value < 0.01). On the other hand, pre-treatment with
neobaicalein before adding rotenone increased cell viability by 34 %
noticeably (P-value < 0.05) ([104]Figure 3a, b).
Figure 3.
[105]Figure 3
[106]Open in a new tab
The effect of neobaicalein (Neo) on the viability of the rotenone
treated SH-SY5Y cells evaluated by MTT and flow cytometry assays. (a)
Different concentrations of neobaicalein (20, 50, 150, and 250 μM) did
not induce cell death after 24 h of incubation. (b) Rotenone induced
cell death and pre-treatment with neobaicalein, increased cell
viability significantly (∗ P-value < 0.05, ∗∗ P-value ≤ 0.01). The
morphology of (c) control cells, (d) rotenone treated cells, and (e)
neobaicalein/rotenone treated cells. Black arrows show the
morphological changes in (d) rotenone-treated cells. Flow cytometry
shows the amount of the early apoptosis, late apoptosis/necrosis of (f)
control cells, (g) rotenone treated cells, and (h)
neobaicalein/rotenone treated cells. In diagrams, the lower left is for
live cells, lower right for early apoptotic cells, upper left for
necrotic cells, and upper right for late apoptotic/necrotic cells. (i)
The table shows the average percentage of the cell count in each
quadrant as mean ± SD.
3.3.2. Flow cytometry assay
The main type of cell death induced by rotenone, as seen in
neurodegeneration phenomena, was apoptosis. Also, in the presence of
neobaicalein (150 μM)/rotenone (500 nM), the rate of early apoptosis,
as well as late apoptosis/necrosis, decreased significantly
([107]Figure 3f–h).
3.3.3. ROS production assay
The result of the DCFH-DA assay demonstrates that ROS increased
significantly in the rotenone-treated SH-SY5Y cells (P-value <0.001)
and different concentrations of neobaicalein moderated its elevation,
significantly (P-value <0.001) ([108]Figure 4a).
Figure 4.
[109]Figure 4
[110]Open in a new tab
(a) The amount of ROS levels in SH-SY5Y cells treated with different
concentrations of neobaicalein alone (50, 150, 250 μM) and in the
presence of 500 nM rotenone detected by DCF fluorescence intensity. The
morphology of differentiated SH-SY5Y cells and their neurites in (b)
the cells with no treatment, (c) the cells treated with rotenone, and
(d) the cells treated with rotenone/neobaicalein (inserts are the whole
lens of the camera, and part of it is magnified). (e) The number of
neurites, (f) the average of neurite length, and (g) the distribution
of various neurite lengths were measured using image J. Scale bar, 100
μm. ∗P-value ≤ 0.05, ∗∗P-value ≤ 0.01, ∗∗∗P-value ≤ 0.001, (N = 3, Mean
± SD).
3.3.4. Neurite length measurement
Outspreading of neurites in neurons is crucial for neuronal activities
such as neurotransmitters recruitment. Inhibition of axonal outgrowth
and neurite elongation is attributed to numerous neurodegenerative
pathologies [[111]48]. In our study, following 8 days of RA usage, the
neurites had an extensive outgrowth, demonstrating the differentiation
property of SH-SY5Ycells ([112]Figure 4b). Nevertheless, treatment with
rotenone significantly influenced the length of neurites
([113]Figure 4c). However, exposing the differentiated SH-SY5Y cells to
neobaicalein before treatment with rotenone sustained the natural
morphology of the neurons with extended neurites ([114]Figure 4d).
Different neurites parameters, including number ([115]Figure 4e), the
average of neurite lengths ([116]Figure 4f), and the distribution of
various neurite lengths ([117]Figure 4g), were evaluated in SH-SY5Y
cells in the presence and absence of rotenone or rotenone/neobaicalein.
Neobaicalein restored the number of neurites, the average of neurite
length, and their prevalence in rotenone treated differentiated SH-SY5Y
cells ([118]Figure 4e–g).
3.4. Neobaicalein alleviated the inflammation response of the primary mixed
glial cells
We also assessed the effect of neobaicalein on the activity of glial
cells, since inflammation plays a crucial role in the progression of
neurodegenerative disorders. Based on the indirect measurement of NO^•
by Griess assay, a significant increase in nitrite level was detected
after 48 h of incubation with 10 μg/μL of LPS compared to the untreated
cells (P-value ≤ 0.001). However, pre-incubation with 150 μM of
neobaicalein, showed significantly less increase in nitrite
concentration (P-value ≤ 0.01) ([119]Figure 5).
Figure 5.
[120]Figure 5
[121]Open in a new tab
NO^• production in LPS-induced glial cells in the presence or absence
of neobaicalein. (a) The morphology of mixed glial cultures (control)
shows the basal layer of astrocytes. The dark-field oligodendrocyte
precursor cells (triangle) adhere to the top of astrocytes, and small
bright-field microglia (arrow) are rounded and floating. (b) The
LPS-stimulated cells show different morphology. Most of them lose their
spindle shapes, become flattened, and are not branched anymore
(circle). (c) The natural morphology of the cells in the presence of
neobaicalein/LPS is better preserved than the LPS-stimulated one
(inserts are the whole lens of the camera, and part of it is
magnified). (d) Nitrite level in the primary mixed glial cells after 48
h of treatment was measured using Griess reagent at 540 nm based on a
standard curve of sodium nitrite. Values indicate the mean ± SD of
three independent experiments. The symbols ∗∗ and ∗∗∗ indicates
significance between the control group and experimental groups at P ≤
0.01 and P ≤ 0.001, respectively.
3.5. Neobaicalein has potential inhibitory activities against death pathways
in PD according to in silico studies
Systematic bioinformatics prediction was employed to gain insight into
the molecular mechanisms involved in the neuroprotective activities of
neobaicalein.
3.5.1. PPI network construction and network analyses
Parkinson's disease-associated PPI (PD-PPI) network was generated using
the STRING plugin of Cytoscape. The final PD-PPI network includes 1000
nodes and 6851 edges ([122]Figure 6). Based on the network analysis
through cytoHubba plugin, among five ranking methods, 44 proteins were
obtained as key proteins ([123]Figure 8a, [124]Table 1).
Figure 6.
[125]Figure 6
[126]Open in a new tab
PD-associated PPI (PD-PPI) network generated with the STRING app of
Cytoscape. The network includes 1000 nodes and 6851 edges.
Figure 8.
[127]Figure 8
[128]Open in a new tab
(a) The key proteins related to the PPI-PD network obtained as common
proteins with the highest score through five ranking methods. (b)
PANTHER pathway of the key proteins represents the signaling pathways
associated with these proteins. The circle and the rhombus indicate the
proteins and the signaling pathways, respectively. The color spectrum
of signaling pathways varies from red (>0.05) to green (≤0.05) based on
P-value.
Table 1.
The top 10% genes according to 5 cytoHubba ranking methods.
The ranking methods in cytoHubba Top 10% genes
Betweenness FGF2, ADRB2, UBB, ADAM10, UBC, VCP, HSPA9, HSPA8, HSPA4,
HSPA5, EIF2S2, ESR1, RAP1B, FOXO3, DLG4, CYC1, MBP, BDNF, DRD2, CXCL8,
TAC1, NFKB1, MGEA5, CXCL12, CASP3, IL4, PTEN, IL6, ITGAM, LRRK2, GNAL,
GFAP, MT-CYB, CDK5, GSK3B, ALB, LAMC2, EIF4G1, PIK3CA, YWHAZ, GAPDH,
MMP9, NGF, CAT, MAPK1, MAPK8, APOA1, SNCA, MAPK3, DCTN1, CDC42, INS,
RAB1A, PLG, FYN, EIF4E, RAB29, MTOR, PINK1, EGF, SOD2, SYT11, SOD1,
MAPK14, APP, ACTB, TFRC, AKT1, CSNK1D, VDAC1, TP53, AR, TXN, EGR1,
APOE, DECR1, HMOX1, IGF1, TH, MT-CO2, ATM, PPARGC1A, RAC1, IL10, PARP1,
EDN1, MAPT, SHH, TLR4, AVP, GAK, CXCR4, PARK2, SIRT1, F2, ADCY5, PPARA,
VEGFA, RPS27A, TNF
Closeness FGF2, SH3GL2, ADRB2, UBB, ADAM10, UBC, VCP, TGFB1, HSPA8,
SQSTM1, HSPA4, HSPA5, ESR1, FOXO3, FOXO1, BDNF, CXCL8, NFKB1, HSPB1,
CASP8, IGF2R, CXCL12, IL4, CASP3, PTEN, IL6, PICALM, CDK5, GSK3B, ALB,
BCL2L1, PIK3CA, GAPDH, YWHAZ, MMP9, NGF, CAT, MAPK1, MAPK8, TRAF6,
SNCA, LRP2, MAPK3, DNAJC6, CDC42, NOS3, INS, CCL2, FYN, MTOR, PINK1,
EGF, SOD2, LEP, STUB1, SOD1, MAPK14, APP, ACTB, ICAM1, TFRC, AKT1,
BIN1, TP53, AR, HIF1A, EGR1, APOE, HMOX1, DECR1, IGF1, TF, TH, RAC1,
IL10, EDN1, MAPT, SHH, TLR4, TLR2, AVP, GAK, CXCR4, PARK2, SIRT1, IL1B,
F2, PPARG, HTT, PTGS2, GCG, CDKN2A, VEGFA, SPP1, HSPA1A, RPS27A, IGF1R,
TNF, HGF, WNT5A
BottleNeck FGF2, ADRB2, CPLX1, UBB, ADAM10, NTS, UBC, RPSA, HSPA9,
HSPA8, HSPA4, FKBP4, HSPA5, EIF2S2, ESR1, DLG4, FGFR4, BDNF, DRD2,
SLC40A1, CXCL8, NFKB1, DRD4, HSPB1, CASP8, ALDH2, CASP3, PTEN, IL6,
ITGAM, SYNJ1, GFAP, AXIN1, MT-CYB, ALB, LAMC2, PIK3CA, YWHAZ, GAPDH,
HSPD1, MMP9, THBS1, CAT, MAPK1, MAPK8, APOA1, TRAF6, SNCA, MAPK3,
NCAM1, CDC42, NOS3, INS, HDAC1, RAB1A, POMC, BAX, PLG, RAB1B, EIF4E,
RAB29, SOD2, SYT11, SOD1, MAPK14, APP, CCDC62, ACTB, AGFG1, TFAM, AKT1,
TP53, HIF1A, TXN, OPTN, HMOX1, CYP2E1, ACE, BST1, TH, ATM, PPARGC1A,
GRIN2B, RAC1, IL10, PARP1, MAPT, TLR4, TLR2, AVP, GAK, TOMM40, PARK2,
ADCY5, VEGFA, NSF, RPS27A, TSC2, HGF, PARK7
Stress FGF2, ADRB2, UBB, ADAM10, UBC, VCP, HSPA9, HSPA8, HSPA4, HSPA5,
ESR1, RAP1B, FOXO3, FOXO1, DNMT1, DLG4, CYC1, MBP, BDNF, DRD2, CXCL8,
NFKB1, CXCL12, CASP3, IL4, PTEN, IL6, ITGAM, LRRK2, GFAP, MT-CYB,
GSK3B, ALB, EIF4G1, PIK3CA, GAPDH, HSPD1, MMP9, NGF, CAT, MAPK1, MAPK8,
TRAF6, SNCA, MAPK3, DCTN1, CDC42, INS, RAB1A, POMC, PLG, FYN, RAB29,
MTOR, PINK1, EGF, SOD2, SYT11, SOD1, MAPK14, APP, ACTB, AKT1, VDAC1,
TP53, AR, TXN, CRHR1, EGR1, APOE, DECR1, HMOX1, IGF1, TH, MT-CO2, ATM,
PPARGC1A, RAC1, IL10, PARP1, EDN1, MAPT, SHH, TLR4, AVP, SLC18A3, GAK,
TOMM40, CXCR4, PARK2, SIRT1, F2, ADCY5, PPARA, GCG, VEGFA, HSPA1A,
RPS27A, TNF, HGF
Radiality FGF2, SH3GL2, ADRB2, UBB, ADAM10, UBC, VCP, TGFB1, HSPA8,
SQSTM1, HSPA4, HSPA5, ESR1, FOXO3, FOXO1, BDNF, CXCL8, NFKB1, HSPB1,
CASP8, IGF2R, CXCL12, IL4, CASP3, PTEN, IL6, PICALM, CDK5, GSK3B, ALB,
BCL2L1, PIK3CA, GAPDH, YWHAZ, MMP9, NGF, CAT, MAPK1, MAPK8, TRAF6,
SNCA, LRP2, MAPK3, DNAJC6, CDC42, NOS3, INS, CCL2, FYN, MTOR, PINK1,
EGF, SOD2, LEP, STUB1, SOD1, MAPK14, APP, ACTB, ICAM1, AKT1, BIN1,
TP53, AR, HIF1A, EGR1, APOE, HMOX1, DECR1, IGF2, IGF1, TF, TH, IDE,
RAC1, IL10, EDN1, MAPT, SHH, TLR4, TLR2, AVP, GAK, CXCR4, PARK2, SIRT1,
IL1B, PPARG, HTT, PTGS2, GCG, CDKN2A, VEGFA, SPP1, HSPA1A, RPS27A,
IGF1R, TNF, HGF, WNT5A
[129]Open in a new tab
3.5.2. The key proteins extracted from the network were enriched in the
programmed cell death, regulation of cell death and apoptosis
Pathway and GO enrichment analyses of key proteins were obtained with
DAVID. The top 10 results obtained from the GO enrichment analysis
(according to P-value) are shown in [130]Figure 7. The results include
three parts: biological process (BP), molecular function (MF), and cell
component (CC). Based on the data obtained from BP, the key proteins
were significantly enriched in the regulation of programmed cell death
(GO: 0043067), regulation of cell death (GO: 0010941) and regulation of
apoptosis (GO: 0042981), which are all related to neuronal cell death
as the major event in PD. In addition, these proteins were mainly
enriched in the cytosol as CC-ontology and enzyme binding for
MF-ontology. PANTHER pathways of the key proteins are shown in
[131]Figure 8b. The apoptosis signaling pathway, Parkinson's disease
pathway, and Ras pathway are the most significant pathways related to
these proteins. As a result, by using the network and pathway analyses,
we identified key proteins in the PD-PPI network, which participate in
the signaling pathways associated with PD. In the next step, to
determine the neobaicalein inhibitory effect on these pathways, CASP3,
TP53, MAPK14, and MAPK8 proteins were selected since the inhibition of
these proteins leads to the inhibition of specified downstream
signaling pathways.
Figure 7.
[132]Figure 7
[133]Open in a new tab
Top 10 results obtained from the GO enrichment analysis.
3.5.3. Neobaicalein could be a suitable candidate for pharmaceutical purposes
According to the data obtained from PreADME and ADVERPred, neobaicalein
is a non-mutagen compound without hepatotoxicity ([134]Figure 9a),
which also obeys Lipinski's RO5 ([135]Figure 9b).
Figure 9.
[136]Figure 9
[137]Open in a new tab
The results of (a) neobaicalein toxicity prediction and its adverse
side effects using PreADMET and ADVERPred Web Services and (b) the
Lipinski's RO5 of neobaicalein.
3.5.4. Docking prediction studies revealed the potential interaction of
neobaicalein with MAPK14, MAPK8, and CASP3
Docking simulation was performed to study the interaction of
neobaicalein with the key proteins, including MAPK14 (PDB ID:
[138]5XYY), MAPK8 (PDB ID: [139]2H96), CASP3 (PDB ID: [140]3GJQ), and
TP53 (PDB ID: [141]1TSR) ([142]Figure 10). Results show that
neobaicalein significantly inhibits MAPK14 (lowest binding energy:
-7.17 kcal/mol), CASP3 (lowest binding energy: -6.65 kcal/mol), and
MAPK8 (lowest binding energy: -6.63 kcal/mol). However, neobaicalein
showed less inhibitory effect against P53 (lowest binding energy: -4.51
kcal/mol). Since CASP3 and P53 are pro-apoptotic proteins [[143]49],
and the activation of MAPKs contributes to elevated oxidative stress
[[144]50], neobaicalein has the potential to inhibit the principal
contributors of PD pathogenesis.
Figure 10.
[145]Figure 10
[146]Open in a new tab
A visual illustration of the 2D (right) and 3D (left) interaction of
neobaicalein with (a) MAPK14, (b) CASP3, (c) MAPK8 and (d) TP53. Amino
acids involved in hydrogen bonds are shown in sharp green.
3.5.5. Molecular dynamics of neobaicalein with MAPK14 and CASP3
MD simulation was performed for 50 ns to assess neobaicalein dynamics
behavior. To this end, the lowest binding energy conformation of
MAPK14-neobaicalein and CASP3-neobaicalein complexes were derived, as
incipient conformation for MD simulation. After the MD run, the Root
Means Square Deviation (RMSD), and Root Mean Square Fluctuation (RMSF)
were calculated using the GROMACS 5.0 'rmsdist' algorithm and 'rmsf'
algorithm, respectively. The RMSD of MAPK14 and CASP3 with neobaicalein
reached the stable configuration after 40 and 45 ns, respectively
([147]Figure 11a, c). Moreover, RMSF of all residues, which shows the
time average of RMSD for each residue, was evaluated for MAPK14 and
CASP3. RMSF plot of MAPK14 in its binding form showed fluctuations of
0.15, indicating the stability of the complex ([148]Figure 11b). The
PDB structure of CASP3 has two chains, and the pick shown in the CASP3
RMSF plot is related to the region between these two chains
([149]Figure 11d).
Figure 11.
[150]Figure 11
[151]Open in a new tab
(a) RMSD and (b) RMSF plot of MAPK14-neobaicalein. (c) RMSD and (d)
RMSF plot of CASP3-neobaicalein.
4. Discussion
Different species of Scutellaria are commonly used in traditional
medicine due to the enrichment of high valuable secondary metabolites,
especially flavonoids [[152]30]. Since the DCMex of S. pinnatifida
contains a considerable amount of flavonoids [[153]34], we further
analyzed this extract and purified a compound, neobaicalein, to
evaluate its function. After obtaining highly purified neobaicalein,
which established by TLC and NMR, its radical scavenging activity as a
flavonoid compound was analyzed. There are three phenolic rings in the
neobaicalein structure, which can trap free radicals as scavengers.
Small molecules should be biocompatible to be used as a drug.
Neobaicalein did not lyse red blood cells even at high concentrations
(0.5mM), demonstrating its biocompatibility. In addition, neobaicalein
is a non-mutagen compound without hepatotoxicity and obeys the RO5 (log
P < 5, H-bonds donors <5, H-bonds acceptors <10, and molecular weight
<500). Neobaicalein has a great opportunity to enter the market as a
drug since it conforms to the RO5, and could pass clinical trials more
efficiently [[154]51]. We also explored the neuroprotective effect of
neobaicalein on rotenone's toxicity, and the inflammation response in
induced glial cells. Although previous studies have reported the
presence of neobaicalein in S. pinnatifida [[155]52, [156]53], no
studies have yet been done on its neuroprotective effects, and
according to our knowledge, this is the first report. However, there
are few studies on neobaicalein remediation activity in other
disorders. For instance, neobaicalein inhibits the degradation of type
I collagen in human skin fibroblasts, which preserves the integrity of
the extracellular matrix [[157]54] and also prevents airway
inflammation in a mouse model of asthma [[158]55]. Additionally,
neobaicalein precludes the expression of pro-protein convertase
subtilisin/Kexin type 9, which avoids the recycling of
low-density-lipoprotein receptors (LDLRs), and leads to the control of
plasma cholesterol levels [[159]56].
In this study, rotenone, which can cross the BBB [[160]5] and induce
neurodegeneration [[161]57], was used to simulate an in vitro model of
PD. In this regard, rotenone's toxicity effects on SH-SY5Y cells were
analyzed in the absence and presence of different concentrations of
neobaicalein. The results showed that neobaicalein considerably
neutralized rotenone's neurotoxicity in 150 μM. One of the main reasons
for rotenone's toxicity is its direct inhibitory effect on the
mitochondrial complex I activity, which leads to dopaminergic
neurodegeneration in PD [[162]7]. Mitochondria provide ATP for the
neurons and adjust the cytosolic calcium, the two necessary functions
for recycling the synaptic vesicles, and the preservation of
electrochemical gradients [[163]58]. Complex I deficiency is detected
in the neurons of those affected by PD, which disturbs ATP production,
calcium homeostasis, and intensifies oxidative stress [[164]8,
[165]59]. Usually, these events lead to apoptotic neuronal death, as we
also observed in the SH-SY5Y cells were treated with rotenone. However,
neobaicalein pre-treatment survived the rotenone treated cells
significantly and decreased the rate of early apoptosis, as well as
late apoptosis/necrosis. Other flavonoids with a similar structure as
neobaicalein have also been shown the potential against rotenone
toxicity, suggesting the neuroprotective effects of flavonoids [[166]9,
[167]60, [168]61]. In addition to cell death, another reason, which can
explain the symptoms of PD, is the disability of neurons in recruiting
transmitters, synaptic communication with neighbor neurons, and glial
cells. Different harmful environmental factors that disturb neuronal
neurites' structure and polarization contribute to the
neurodegenerative processes [[169]62]. Experimental analysis on the
hippocampal neurons revealed that rotenone administration led to
inhibition of axon formation, and also reduced the length of the
neurites in dopaminergic neurons [[170]63]. Multiple lines of studies
provide evidence that the inhibition of neuritogenesis by rotenone
could be based on its effect on microtubule dynamics, the actin
cytoskeleton, and different regulatory pathways, especially through
modifying the small Rho GTPase RhoA [[171]63]. In our experiment,
rotenone diminished the number of neurites, neurite lengths, and their
prevalence in differentiated SH-SY5Y cells remarkably. In the presence
of neobaicalein, however, the neurites of differentiated SH-SY5Y cells
remained normal remarkably.
Additionally, inflammatory events can contribute to the development of
neurodegeneration by inducing the apoptotic pathways in neuronal cells
[[172]16]. Sometimes activation of glial cells leads to the initiation
of the inflammatory events through the release of pro-inflammatory
molecules such as NO^•, TNF-α, IL-6, and IL-1β. In this regard,
flavonoids show neuroprotective properties by inhibiting the release of
pro-inflammatory cytokines through the MAPK signaling cascade
[[173]64]. The results of our study also confirmed the
anti-inflammation effects of neobaicalein through the modulation of
NO^• production induced by LPS in mixed glial cells.
Since neobaicalein neutralizes the effects of multiple factors related
to PD, we decided to employ bioinformatics tools to gain knowledge on
the mechanisms of its neuroprotective activities. A protein network
associated with PD was identified, and its key proteins were selected.
Pathway and GO enrichment analyses of the chosen proteins showed that
those proteins were significantly enriched in the regulation of the
programmed cell death and apoptosis-related to neuronal degeneration.
In addition, based on PANTHER pathways, these proteins were associated
with three pathways, including apoptosis signaling pathway, PD, and Ras
pathway. Among the key proteins related to these pathways, MAPK14,
CASP3, MAPK8, and TP53 were selected, as their inhibition can block
downstream signaling cascades with the aim of neuroprotectivity. MAPK8
(JNK1), MAPK14 (p38α), and CASP3 have important roles in the death
pathways [[174]65, [175]66]. Different investigations have demonstrated
that oxidative stress in dopaminergic neurons initiates the JNK and p38
pathways, which, consequently, induces apoptosis [[176]50, [177]67].
Studies on the postmortem human brain have shown a correlation between
the loss of dopaminergic neurons in the mesencephalon of PD patients
and increased expression of CASP3 [[178]68]. Neurotoxins, including
rotenone, can activate microglial cells through the p38/MAPK pathway
and induce apoptosis via JNK and CASP3 activity [[179]69, [180]70,
[181]71]. Taken together, targeting these signaling pathways may be
effective in the control of PD. According to the docking analysis of
this study, neobaicalein showed interactions against MAPK14, CASP3, and
MAPK8. Consequently, restraining these proteins by neobaicalein gives
insight into PD molecular targets for the development of therapeutic
drugs. In future studies, methods such as Next Generation Sequencing
can be used to assess the molecular mechanisms involved in neobaicalein
protecting activity on the dopaminergic neurons.
5. Conclusion
We conclude that neobaicalein, a flavonoid derived from S. pinnatifida,
could be a potential compound against the mechanisms leading to PD,
such as oxidative stress, inflammation, and neurotoxins.
Declarations
Author contribution statement
Soha Parsafar: Performed the experiments; Analyzed and interpreted the
data; Contributed reagents, materials, analysis tools or data; Wrote
the paper.
Zahra Nayeri, Farhang Aliakbari, Farshad Shahi: Performed the
experiments.
Mehdi Mohammadi, Dina Morshedi: Conceived and designed the experiments;
Analyzed and interpreted the data.
Funding statement
This work was supported by the National Institute of Genetic
Engineering and Biotechnology (NIGEB, Tehran, Iran) and Iran National
Science Foundation (INSF) (Grant 98003955).
Competing interest statement
The authors declare no conflict of interest.
Additional information
No additional information is available for this paper.
Acknowledgements