Abstract
Application of retinol (Vitamin A, VA) in skincare is limited for
instability, poor water solubility, and skin intolerance that combats
skin aging. We employed computer-aided virtual screening and cell
experiments with transcriptomics, thereby unveiling the comprehensive
gene expression and regulation pathway of photoaging HaCaT cell treated
with ferulic acid (FA) in synergizing with VA. Through network
pharmacology analysis, the combined use of VA and FA exhibited highly
correlated cross-targets with skin aging acting on EGFR, PTPN1, ESR2,
GSK3B, BACE1, PYGL, PTGS2 and APP. The indicators of oxidative stress,
such as SOD, GSH, MDA, CAT and ROS in HaCaT cells after
co-administration, were significantly improved from those in photoaging
group (p<0.0001). 155 differential expressed genes (DEGs) were specific
between groups, while reducing the expression of PTGS2 was identified
as an important regulatory factor in photoaging HaCaT cells by VA and
FA. Those DEGs of co-administration group focused on
oxidative-reduction enzyme activity, skin growth, keratinization, and
steroid biosynthesis. Apparently, the co-administration of VA and FA
effectively mitigated the process of UVB-induced photoaging by reducing
oxidative stress injury, inflammation responses, and regulating cell
growth. This synergistic approach significantly slowed down the
photoaging progression and improved the applied performance of VA in
HaCaT cells.
Keywords: retinol, ferulic acid, cooperative photoprotection, skin
aging, oxidative stress
INTRODUCTION
Aging of the skin is an intricate and unchangeable biological process.
UVR, or ultraviolet light radiation, can cause significant harm to skin
from the sun and artificial sources. This process speeds up skin aging,
called photoaging [[34]1]. Based on wavelength, UVR can be divided into
three groups: UVA (320–400 nm), UVB (280–320 nm), and UVC (100–280 nm).
UVR have detrimental effects that are either short-term or long-term,
including acute erythema, wrinkles, pigmentation, and the breakdown of
collagen and elastin [[35]2]. UVB radiation can penetrate the epidermis
of the skin and cause function damage to cells [[36]3]. Age and
prolonged UVB exposure inevitably cause wrinkles, pigmentation, laxis
of the epidermis, and a decrease in dermal and epidermal thickness. DNA
damage, oxidative stress, cellular inflammatory responses, and
microcirculation alterations all contribute to the development of
photoaging [[37]4]. Reactive oxygen species (ROS) are produced and
accumulate during the photoaging process, mostly for cell peroxidation
and free radicals. Hence, interfere with the body’s dynamic scavenging
of such metabolites, disturbing the skin’s regular processes [[38]5,
[39]6]. ROS production could activate the signaling pathway
phosphatidylinositol 3-kinase (PI3K)/Akt and mitogen-activated protein
kinases (MAPKs), which caused upregulated transcription of inflammatory
mediators [[40]7]. Prostaglandin Endoperoxide Synthase (PTGS2) causes
continuous damage in proliferation and dermoepidermal junction of skin
later. Cyclooxygenase-2 (COX-2) is encoded by the transcription of the
PTGS2 gene, take part in produce of ROS and several inflammatory
cytokines in skin such as IL-1. UVR activates the NFAT, NF-κB pathway
to increase COX-2 transcription by stimulating ROS produced in cells
[[41]8]. The antioxidant defense mechanism of the skin is interfered
with by ROS, which in turn induces inflammation-induced aging due to
overexpression of COX-2 [[42]9]. The best defense against premature
skin aging is to stay out of the UVR, especially as UVB might have an
impact.
Retinol (Vitamin A, VA) has been shown to have both curative and
preventive benefits on the aging process of the skin. VA restored
dermal thickness of skin ex vivo and in vivo by effectively blocking
the reversion of elastic fiber deposition and organization [[43]10].
Through randomized, double-blind clinical trial during 12 weeks, 0.5%
VA cream applied on full face for participants ages 31-56 twice a day,
could reduce the wrinkle surface area and pigmentation significantly
[[44]11]. However, there was restricted application associated with
high doses of VA, including sensitivity, stinging, burning, cutaneous
erythema, peeling, and pruritus [[45]12]. Treatment effect of skin
aging with VA is dose-dependent, and there is often no significant
improvement in photoaging skin at low doses, but high concentrations of
0.5%~1% VA might cause more frequent and intense symptoms such as
dermatitis reaction [[46]13, [47]14]. Efforts have been made to reduce
the irritation of VA while preserving the efficacy. In cosmeceuticals,
combining with different drugs, Chien verified that cosmetic product
with 1% VA, 0.05% retinyl acetate, 0.05% retinol palmitate moderated
facial photodamage persons or the more serious. Patients only treated
with VA experienced tropical skin irritation, which is 6 times more
frequently than those who developed intolerance with combinations
[[48]12]. Therefore, combining other substances may synergistically
take full advantage of VA.
For example, as a commonly used antioxidant in skin care products,
ferulic acid (FA) has a very strong ability in scavenging free
radicals, improving cellular antioxidant defense system and inhibiting
oxidative stress damage to achieve cell protection, which is often used
in combination with other ingredients in skin care products [[49]15].
Relevant literature studies have shown that the different ratios of
antioxidants companied with anti-aging ingredients can reduce the
intolerance to cells. For instance, topical application of combining
vitamin C, vitamin E (VE), and FA for 2 weeks decreased the melanin
index between 26-53 years old men and women [[50]16]. However, the
combination work of VA and FA are unexplored. How to efficiently obtain
the matching ingredients and dosages that reduce the irritation of
retinol is crucial.
Currently, the idea that organs should be the focus of medical
treatment is counterproductive to medication discovery and research.
Preclinical animal models mostly mimic the symptoms of illnesses, with
less understanding of the underlying causes of illness [[51]17]. For
example, ACE inhibitors, such as sacubitril/valsartan, are used for
heart failure [[52]18]. But this treatment is only focus on the
symptoms, rather than the cause of the disease. As consequently, the
technique known as network pharmacology is introduced using virtual
computing, high-throughput data processing, and the creation of
bioinformatics networks [[53]19]. Network pharmacology describes the
occurrence of disease and the possibility of treatment through
endotypes defined by causality [[54]20], which aims at specific
proteins in disease developing pathways directly or indirectly. It
interprets the comorbidities of disease phenotypes through multi-target
signaling pathways, accurately intervenes in each process of disease
occurrence, and accelerates clinical translation [[55]21]. Network
pharmacology maximum save times and pinpoints the effective drugs for
diseases from thousands of compounds. The theories and strategies of
network pharmacology have been successfully applied to the analysis of
single herbs and prescriptions in traditional Chinese medicine. For
example, Moluodan in the treatment of chronic atrophic gastritis which
verified by GSE-1 cells [[56]22]; Based on the metabolic profile of
Alismatis rhizoma in mice, biomarkers against hyperlipidemia were
identified by compound-metabolite network, which verified by qPCR
[[57]23].
The main objective of this project is to promote the synergistic
protection for photoaging and reduce the irritation of VA by
formulating a mixture with FA. To create a photoaging model that would
show the combined protective influence of VA and FA on UVB-damaged
HaCaT cells. Applied with network pharmacology, excluded the potential
cooperative medication for the VA. The non-linear mixed amount with
zero amount (NLMAZ) was used to modeling synergism patterns
administrated with various of ratios of FA and VA [[58]24]. Then,
observed the morphological changes of HaCaT cells, detected oxidative
stress-related inflammatory factors such as superoxide dismutase (SOD),
malondialdehyde (MDA), reduced glutathione (GSH), catalase (CAT) and
reactive oxygen species (ROS) indicators. Transcriptomics was used to
verify and find the key regulatory targets of VA and FA on UVB-induced
photoaging HaCaT cells. To confirm the profound regulatory connection
that exists between its transcription and the level of keratinocyte
senescence, the vital regulatory protein COX-2 was analyzed.
RESULTS
Collecting targets of retinol, ferulic acid and skin aging
According to the TCMSP, Drugbank and SwissTargetPrediction Database,
134 targets of retinol ([59]Supplementary Table 1) and 107 targets of
ferulic acid ([60]Supplementary Table 2) were collected. A total of 774
skin aging targets were also obtained from GWAS database and GeneCards
database after deduplication ([61]Supplementary Table 3).
Identification synergic biological function of VA and FA
When conducting Venn analysis on synergic targets acting on skin aging
of VA and FA, 82 and 68 genes were intersected by VA and FA at the
target to skin aging ([62]Supplementary Table 4), respectively.
Enrichment analysis showed that 45 and 31 in these targets were
enriched in re-inflammatory processes, antioxidant function and
regulation of immune function. Those genes were considered as the
common targets of VA and FA for skin aging diseases.
The results showed that VA and FA were cooperative in regulating cell
proliferation, oxidation–reduction process and apoptotic process, etc.
([63]Figure 1B). At molecular level, VA and FA mainly acted on enzyme
binding, receptor activator activity, protein kinase binding, ATP
binding ([64]Figure 1A) in the intracellular membrane-bounded
organelle, membrane raft, cell surface, endoplasmic reticulum, plasma
membrane, endoplasmic reticulum membrane and mitochondrion etc.
([65]Figure 1C). In terms of its involved pathways, it showed that
synergic biological function of VA and FA may be effective via
regulating MAPK signaling pathway, calcium signaling pathway, cardiac
muscle contraction, etc. ([66]Figure 1D).
Figure 1.
[67]Figure 1
[68]Open in a new tab
Synergic biological function of VA and FA. (A) Synergic targets of VA
and FA enriched in biological processes (MF); (B) Synergic targets of
VA and FA enriched in cellular component (BP); (C) Synergic targets of
VA and FA enriched in molecular function (CC); (D) Synergic targets of
VA and FA enriched in KEGG enrichment of the intersection targets
between SGR predicted targets and heart failure.
Identification of DEGs in skin aging
We identified 252 DEGs in the [69]GSE155789 dataset using the GEO2R
analysis in GEO database ([70]Supplementary Table 5). Based on the
analysis, 72 genes were up-regulated and 179 genes were down-regulated.
A total of 65 differential genes were screened out by the intersection
analysis of 252 differential genes in 45 and 31 targets, and when these
65 targets were enriched, the results showed that FA and VA both
regulated cell proliferation, redox process and apoptosis process by
binding organelle enzyme binding, receptor activator activity, protein
kinase binding, ATP binding and other synergistic biological functions
by regulating MAPK signaling pathway, calcium signaling pathway,
myocardial contraction, etc. DEGs is illustrated in [71]Figure
2A–[72]2C. The results also indicated that EGFR, PTPN1, ESR2, GSK3B,
BACE1, PYGL, PTGS2 and APP were specifically expressed in skin aging,
which was consistent with the above results of network pharmacology
analysis.
Figure 2.
[73]Figure 2
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Differentially expressed genes of skin aging identification. (A) Heat
map of DEGs in the [75]GSE155789; (B) Cluster of DEGs in the
[76]GSE155789; (C) Volcano plot of differentially DEGs in the
[77]GSE155789. group C: normal HaCaT cells; group VA: 100 nM retinol in
HaCaT cells.
Synergic targets acting on skin aging of VA and FA
[78]Figure 3A showed the distribution characteristic of targets of
retinol, ferulic acid and skin aging. As [79]Figure 3B–[80]3D, after
PPI networks were introduced into Cytoscape software, a total of 25
synergic targets acting on skin aging of VA and FA were selected as key
targets with node degrees were two-fold greater than the average node
degree in the merge network, which consisted of 232 nodes and 680
edges. They mainly exerted photoprotection by targeting EGFR, PTPN1,
ESR2, GSK3B, BACE1, PYGL, PTGS2 and APP ([81]Figure 3E).
Figure 3.
[82]Figure 3
[83]Open in a new tab
Corresponding feature network diagram of targets of retinol, ferulic
acid and skin aging. (A) Distribution characteristic of targets of VA,
FA and skin aging; (pink circle: targets of VA; pink rectangle: targets
of skin aging; green rectangle: targets of FA). (B) PPI network of skin
aging targets; (C) PPI network of VA targets; (D) PPI network of FA
targets; (E) PPI network of Venn analysis of targets between VA, FA and
skin aging.
Both VA and FA had higher docking scores with screened key targets
According to PPI analysis, EGFR, PTPN1, ESR2, GSK3B, BACE1, PYGL, PTGS2
and APP were the synergic key targets of VA and FA, and they were
docked with VA and FA respectively to clarify the interaction
relationships among the key targets. Van der Waals, conventional
hydrogen bonds, carbon hydrogen bonds, pi-sigma, pi-sulfur, amide-pi
stacked, and pi-alkyl were the principal intermolecular forces. As
shown by the docking score, the results showed that VA and FA both had
different degrees of docking with these key targets ([84]Table 1),
indicating VA and FA may have anti-skin aging effect by targeting those
proteins. Result showed the 2D and 3D docking structure of VA and FA
docked with top 5 synergic targets (AK1C3, GSK3B, ESR2, PTGS2, PTPN1).
In current studies, VA exerted pharmacological effects greatly by
Retinoic acid receptor/retinoid X receptor (RAR/RXR) signaling pathway,
while activation of RAR/RXR pathway increased EGFR expression
significantly and reduced transcription of PTGS2 (protein COX-2)
[[85]25, [86]26]. FGFR1 was well known core targets of FA, inhibition
of COX-2 prior to activation of FGFR1 in the transgenic mice also
resulted in decreased of FGFR1 amplified-induced initiation of
hyperplastic lesions [[87]27, [88]28]. Proliferation of FGFR1 and PTGS2
played a role in promoting the course of the disease.
Table 1. Docking score of VA and FA with screened key targets.
Target Compound Target Compound
Retinol Ferulic_acid Retinol Ferulic_acid
AK1C3 -9.5 -7.2 PKCE -9 -6.9
BACE1 -7.7 -6.4 PTPN1 -7.2 -7
APP -7 -6.3 PYGL -7.7 -6.6
EGFR 7.7 -6.2 SLC6A3 -6.8 -6
GSK3B -8 -6.8 ESR2 -8.4 -6.5
HSD11B1L -6.4 -5.8 PTGS2 -7.9 -7.4
[89]Open in a new tab
Effects of retinol on HaCaT cell proliferation with ferulic acid
As shown in [90]Figure 4A, the viability of HaCaT cells gradually
decreases as the concentration of VA increases. When the concentration
of retinol reached 1500 μM, HaCaT cell viability drops to a minimum.
According to [91]Figure 4B, the IC[50] concentration of VA is 90nM.
That is, when the concentration of retinol reaches 90nM, it can cause
HaCaT cells in the death of 50%. As shown in [92]Figure 4C, different
concentrations of FA had no effect on the proliferative viability of
HaCaT cells.
Figure 4.
[93]Figure 4
[94]Open in a new tab
The effects of varying doses of VA and FA on the proliferative activity
of HaCaT cells and UVB-induced aging in HaCaT cells. (A) Cellular
viability of VA; (B) Dose-response inhibition of VA; (C) Cellular
viability of FA; (D) Cellular viability of FA and VA in HaCaT cells;
(E) Effects of different ratios of VA and FA on UVB-induced aging cells
proliferation (X-axis presented concentration of VA and FA, Y-axis
presented viability of cells); (F) Isoradiometric analysis of VA and FA
for UVB-induced aging cells proliferation (X-axis presented
concentration of VA, Y-axis presented concentration of FA).
According to the MTT method, administration with mixed VA and FA in the
ratio of 1:0, 1:1, 1:2, 1:4, 1:8, 0:1 showed no significant difference
in survival compared with normal HaCaT cells ([95]Figure 4D). As shown
in [96]Figure 4E, based on the isoradiation principle, mixed VA and FA
in the ratio of 1:0, 8:1, 4:1, 2:1, 1:1, 1:2, 1:4, 1:8, 0:1. Combining
with FA, the anti-aging efficacy of retinol was enhanced while cell
irritant is attenuated at an optimal ratio. The results showed that the
different doses of FA promoted the cytoprotective effect of retinol.
Isoradiometric analysis showed that when FA:VA=1.2:1 (120 nM:100 μM)
([97]Figure 4F), the two drugs had the effect of synergistic protection
on HaCaT cells. Therefore, adopted the ratio of FA:VA=1.2:1 for
subsequently experimental verification. The dose-response curve shows a
combination of VA and FA, the reaction index of which is 0, manifests
itself as a synergistic effect, therefore, ferulic acid and retinol
have a synergistic effect.
Response surface analysis of ferulic acid to retinol verified the optimal
ratio
As shown in [98]Figure 5A–[99]5C, the dose-response curve was described
by quadratic polynomial which showed the combination of VA and FA. The
response index indicated the intensity of their interaction, to
illustrate the degree of interaction among the doses of drug
administration. The result was presented by subtracting the response
index by 1 to 0 as a typical additive. In the 3D response surface model
diagram, the color shade indicated the intensity of the interaction
between the two drugs. When the response index was close to 0, the drug
was shown as an additive effect; when the response index was greater
than 0, it was manifested as antagonism; When less than 0, it
manifested as synergy. The higher the index value, the greater the
intensity of the interaction was, and the response surface plot
appeared to be colored close to either light or dark. The X-axis
represented different doses of VA, the Y axis represented different
doses of ferulic acid, and the Z axis represented a gradient change of
the pairs of drugs in the case of fixed IC[50] of one drug. The
inhibition rate of HaCaT cell activity (IC[50]) was used as the
evaluation index, and the three-dimensional response surface model was
fitted. The synergistic effect was significant when the ratio of
ferulic acid and retinol was between 0.671:1~1.657:1 (nM: μM).
Figure 5.
[100]Figure 5
[101]Open in a new tab
Response surface analysis was used to verify the optimal ratio of FA to
VA. (A) 3D response surface model diagram of administrated groups; (B,
C) Response surface plane projection of VA and FA.
β-galactosidase staining monitored the senescent phenotype on HaCaT cells
with FA and VA
To identify senescent cells, SA-β-gal staining is a commonly used
method [[102]29]. The higher the degree of senescence, the more
blue-colored cells appear in the visual field. As shown in [103]Figure
6, there were significantly more senescent (SA-β-gal positive) HaCaT
cells after UVB irradiation (model group), while cell morphology
contracted and the intercellular gap widened. Following VA-FA and NAC
administration, there were significantly fewer senescent cells in the
visual field, and the intercellular space and cell shape were
comparable to those of the normal group (control group). Only the
administration of VA and FA produced reduced cells and greater
intercellular spaces, but fewer stained cells overall.
Figure 6.
[104]Figure 6
[105]Open in a new tab
Senescence-associated-β-galactosidase (SA-β-gal) staining. Control:
normal group; Model: UVB radiation group; VA-FA: mixture of VA (120 μM)
and FA (100 nM); VA: only retinol (120 μM); FA: only ferulic acid (100
nM).
Effects of retinol and ferulic acid on reactive oxygen species in cells
Photoaging HaCaT cell was induced by UVB, which was loaded with
fluorescent probes of the reactive oxygen species (ROS) detection kit.
The images of each group of cells were observed at FITC mode
([106]Figure 7). Examined under a microscope, the cell morphology of
the UVB irradiation group had obvious changes. The cell boundaries
after irradiation were not clear, the gap increases, shrinks, rounds,
and even cell ruptures. The fluorescence was strong, indicating that
the ROS level was high. Administrated with VA, FA, N-acetylcysteine
(NAC), and vitamin E (VE) separately, the damaged cells recovered and
fluorescence decreased to some extent. The cell contours of the retinol
and ferulic acid groups were clearer than those in the model group, the
number of normal cells was significantly increased, and the
fluorescence was significantly reduced. Numerically, there were
significant differences between the ROS levels of cells in the model
group and the normal group, the co-administration group
(p-value<0.0001), and with the ferulic acid group (p-value<0.01). It
was indicated that the combined administration of retinol and ferulic
acid had a significant inhibitory effect on UVB-induced photoaging of
HaCaT cells. VA and FA slowed down UVB-induced HaCaT cell photoaging by
reducing ROS.
Figure 7.
[107]Figure 7
[108]Open in a new tab
Effect of administration groups on reactive oxygen species. (A)
Representative fluorescence images of HaCaT cells with different
compounds addition; (B) Fluorescence intensity of ROS level among FA
and VA addition groups of HaCaT cell (Control: normal group; Model: UVB
radiation group; VA-FA: mixture of VA (120 μM) and FA (100 nM); VA:
only retionol (120 μM); FA: only ferulic acid (100nM)).
Detection of cellular SOD, MDA, GSH, CAT
The levels of MDA, SOD, GSH, CAT ([109]Table 2) reflected the oxidative
stress response of HaCaT cells after administration. What could be
recognized is that compared with the FA group, normal group and model
group, there were significant differences in all indexes (p<0.0001).
Indicating that after synergistic drug delivery, the level of MDA
caused by oxidative stress was significantly reduced, and the content
of SOD, GSH and CAT was significantly increased. After the
administration of VA and FA, respectively, it also had a certain effect
of increasing the GSH content in photoaging model cells. FA also had
the effect in increasing CAT and reducing MDA levels. It suggested that
FA in synergizing with VA could enhance the protective effect on
photoaging keratinocytes through antioxidant. All experiments followed
the principle of complete randomization. Comparisons between groups
were analyzed using ANOVA, all results were expressed as mean ±
standard deviation, and the above calculations were performed using
GraphPad Prism software.
Table 2. Effects of retinol and ferulic acid on SOD, CAT, GSH, MDA, ROS in
UVB-induced photoaging HaCaT cells
[MATH: (x¯±s, n=3) :MATH]
.
group SOD (U·mgprot^-1) GSH (U·mgprot^-1) MDA (U·mgprot^-1) CAT
(nmol·mgprot^-1)
Control 1.881±0.07079*** 45.52±2.225*** 15.24±2.873*** 289.1±38.49***
Model 0.4823±0.02325 25.16±2.227 40.07±5.796 66.5±8.996
VA-FA 1.473±0.2013*** 39.34±1.245*** 17.95±4.329*** 303.1±19.15***
VA 0.6247±0.1191 29.75±3.268** 31.2±3.916 140±10.92
FA 0.7303±0.1197 30.72±1.168** 28.26±3.496* 186.7±11.82*
[110]Open in a new tab
Note: Compared with the photoaging model group, ***P<0.0001, **p<0.01,
*P<0.05.
A higher correlation between FA and VA groups and normal groups in HaCaT
cells
Through Pearson correlation analysis, [111]Figure 8A, the gene of HaCaT
cells in each of group shows high similarity coefficient, and there
were significant differences between groups. Through principal
component analysis, [112]Figure 8B, [113]8C showed a trend of
aggregation in the normal group, model group, VA and FA administration
group, and the relative dispersion between groups. The relative
position of VA and FA administration group was between the normal group
and the model group, and was closer to the normal group than that of
the drug group alone. It was shown that the abnormal expression of
photoaged HaCaT cells induced by the most UVB induced by VA and FA
administration had a significant callback effect.
Figure 8.
[114]Figure 8
[115]Open in a new tab
Significant intergroup differences among the cells in each group.
(Group 1: control group; group 2: UVB induce aging group; group 3:
VA-FA addition group; group 4: VA addition group; group 5: FA addition
group). (A) Pearson correlation analysis in HaCaT cells; (B)
Two-dimensional principal component analysis in HaCaT cells; (C)
Three-dimensional principal component analysis in HaCaT cells.
Effects of retinol synergistic ferulic acid on gene expression in HaCaT cells
The heat map of each group was visible ([116]Figure 9A–[117]9C and
[118]Supplementary Table 6). Compared with the UVB radiation HaCaT cell
model group, the gene expression difference in the cells of the FA
cooperating with VA administration group was revealed. It was closer to
that of the normal group cells ([119]Figure 9E). Venn plots of the DEGs
([120]Supplementary Table 7) sets obtained by the two groups show the
genes that were common and unique between each gene set ([121]Figure
9D). A total of 332 genes had significant gene expression changes
between the normal group and the model group. 349 genes had significant
gene expression differences between the VA-FA administration group and
the model group. However, 155 genes in the co-administration group,
normal group and model group had distinct differences in gene
expression ([122]Supplementary Table 8). These genes were different
from the effects caused by VA administration and the key genes involved
in the reduction of the keratinocytes photoaging degree by FA in
combination with VA. PTGS2 was identified as core target by
comprehensive analysis of network pharmacology, comparing VA-FA groups
and Model groups, log (FC)=-3.22. At the same time, it was the gene
with significant expression differences in RNA sequencing. The results
showed that the VA-FA group vs model group had more genes in common
with the genome gene set than the normal group VS model group. The
VA-FA group gene set was closer to the normal group.
Figure 9.
[123]Figure 9
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Significant differences in gene expression between the HaCaT cells from
different groups and the model group. (Group 1: control group; group 2:
UVB induce aging group; group 3: VA-FA addition group; group 4: VA
addition group; group 5: FA addition group). (A–C) Heat map of DEGs in
groups of control vs model, VA vs model, VA-FA vs model; (D) Venn plot
of DEGs in HaCaT cell among groups; (E) Heat map of DEGs in HaCaT cell
among groups.
Regulation of COX-2 by ferulic acid in concert with retinol in HaCaT cells
In our present investigation, we explored into how VA and FA affected
COX-2. UVB radiation significantly elevated COX-2 expression in HaCaT
cells, as [125]Table 3 illustrated. Following UVB radiation, the
expression of COX-2 was down-regulated in the group treated with VA and
FA alone, whereas it was down-regulated in the group treated with VA
and FA combined.
Table 3. Effects of retinol and ferulic acid on expression of COX-2 in
UVB-induced photoaging HaCaT cells
[MATH: (x¯±s, n=3) :MATH]
.
group COX-2 concentration (OD) Number of values F P-value
C 0.5928±0.0057*** 3 170.9 <0.0001
M 0.8043±0.0405 3
MIX 0.4101±0.0056*** 3
FA 0.5036±0.0062*** 3
VA 0.6167±0.0024 3
NAC 0.5317±0.0109** 3
[126]Open in a new tab
Note: Compared with the photoaging model group, ***P<0.0001, **p<0.01,
*P<0.05.
Regulatory gene function of VA and FA by enrichment analysis
Enrichment analysis was performed by comparing the genes of each group
with the photoaging HaCaT cell group. As shown in [127]Figure
10A–[128]10H and [129]Supplementary Table 9, the discrepancy between
the normal group and the model group was mainly reflected in oxidative
phosphorylation, oxidoreductase activity, transcription-related
pathways, etc. The synergistic drug delivery group acted on biological
processes such as oxidoreductase activity, skin growth, keratinization,
and steroid biosynthesis. It suggested that the commonality between the
groups was reflected in the regulation of redox reaction, skin growth
and keratinization, thereby producing synergistic protection.
Figure 10.
[130]Figure 10
[131]Open in a new tab
The combined action of retinol and ferulic acid regulates biological
processes that contribute to the protection of photoaging cells. (A, B)
Bubble diagram and bar chart of DEGs in groups of control vs model; (C,
D) Bubble diagram and bar chart of DEGs in groups of VA-FA vs model;
(E, F) Bubble diagram and bar chart of DEGs in groups of VA vs model;
(G, H) Bubble diagram and bar chart of DEGs in groups of FA vs model.
DISCUSSION
In majority of researches, aging skin exhibits morphological changes,
particularly in the dermis and epidermis. Deterioration of the skin
barrier, wrinkles, pigmentation, chronic inflammation, and infection
risk are all associated with aging skin [[132]30]. Important
contributors to skin aging were endogenous metabolism or UVR that
produced free radicals and reactive oxygen species (ROS) [[133]31]. The
accumulation of ROS induces oxidative stress, mitochondrial DNA damage
[[134]32], guanine oxidizing, protein carbonylation [[135]33],
inflammatory responses and cells damaging [[136]4]. The accumulation of
ROS induces level of proinflammatory cytokines, IL-6, COX-2, TNF-α,
etc. [[137]4, [138]34]. ROS induced by ultraviolet irradiation caused
JNK and p38 to activate transcription of AP-1 in keratinocytes and
fibroblasts. AP-1 binds to the PTGS2 gene promoter, increasing the
transcription of COX-2 [[139]8]. Gene PTGS2 encodes the enzyme
cyclooxygenase-2 (COX-2), which plays a significant role in
orchestrating chronic inflammation, cellular proliferation, apoptosis,
and immunity [[140]35]. These factors make the skin barrier state
unstable and accelerate skin aging. The skin is susceptible to various
redox reactions [[141]36]. Compensatory defensive enzymes and
non-enzymatic antioxidants are brought about by the increase in ROS
concentration of epidermal cells, which can be used as an important
direction for the study of anti-skin aging [[142]37]. Therefore,
oxidative stress plays a pivotal role in cellular senescence,
inflammation, and cell dysfunction.
VA is a powerful free radical scavenger observed in high concentrations
of the epidermis and dermis, protecting skin against ROS-induced
oxidative damage [[143]13]. However, UV-induced damage may reduce the
antioxidant defense system in skin. Some studies have proposed that
topical application of VA to skin may reconstitute a cutaneous
antioxidant system in inhibiting UV-induced oxidative damage [[144]10].
Nevertheless, the antioxidant effect of VA is strictly associated with
the characteristics of the formulation, mainly the concentration.
Accordingly, stable aqueous formulations containing 15%-20% VA, 1%
vitamin E, and 0.5% FA at a pH less than 3.5 have been developed
[[145]38]. These formulations may protect skin against UV-induced
damage because they are more available that promote absorption and
delivery of VA to skin. However, neither study evaluated whether these
formulations induce histological and biochemical alterations in human
skin ex vivo.
In this study, the degree of medication efficacy and interaction
between VA and FA on aging skin was predicted by network pharmacology.
PPI network analysis represented that VA and FA were acted on similar
target proteins of skin aging. GSEA analysis showed synergic biological
function of VA and FA in regulating MAPK signaling pathway, calcium
signaling pathway, cardiac muscle contraction acting on EGFR, PTPN1,
ESR2, GSK3B, BACE1, PYGL, PTGS2 and APP. The heat map and volcano plot
showed significant discrepancy of DEGs in groups of normal and UVB
irradiation groups. The high docking score between VA, FA and 5 top
synergic targets (AK1C3, GSK3B, ESR2, PTGS2, PTPN1) verified the
methodology.
The cell experience was carried out to inquire into the composition and
dose applying VA and FA in skin photoaging. Response surface analysis
and the MTT test showed that while VA did not considerably enhance
photoaging HaCaT cell morphology, it did partially improve it when
given alone. The maximum value of recovery for UVB-induced photoaging
cell viability was attained when the ratio of FA to VA reached
0.671:1~1.657:1 (μM:nM), as indicated by the inhibition rate of HaCaT
cell activity (IC[50]). The synergistic group’s cells showed a dramatic
drop in fluorescence under a microscope in ROS detection, and the cell
morphology recovered significantly. The recovery state of VA-FA group
cells was better than that of the positive drug groups, NAC and VE
groups. The VA group cells exhibited lower fluorescence intensity and
less noticeable cellular morphology recovery. Based on the indicators
of oxidative stress such as MDA, SOD, GSH, and CAT, the levels of VA-FA
group cells in MDA, SOD, CAT were upregulated. The outcome showed the
restoration of antioxidant defense mechanisms in addition to the
scavenging of lipid peroxides and free radicals. The fall in GSH levels
suggested that the structure and function of cell membranes were less
damaged by oxidative interference. Each treatment group’s
pharmacological outcomes matched the medication efficacy routes that
network pharmacology anticipated. Therefore, it appears that the
combination of VA and FA increased the activity of antioxidant enzymes,
which helped to remove the oxidative stress brought on by photoaging.
This achievement of oxidative-reductive balance helped maintain
cellular and organelle homeostasis, thus preventing photoaging of skin
cells.
Principal component analysis (PCA) along with heatmap and volcano plot
visualization in RNA transcriptome was conducted to illustrate the
expression differences of genes among different cell groups. By
comparing the overall gene expression patterns of HaCaT cells in
various groups, it was observed that there was a high similarity within
each group, whereas significant differences exist between the groups. A
total of 155 genes exhibited significant differences in gene expression
among the co-administration group, normal group, and model group cells.
Notably, the gene PTGS2 demonstrated a high binding affinity with VA
and FA in molecular docking analysis. It was believed that PTGS2 played
a crucial role in the collaborative effect of retinol and ferulic acid
regulating the process of UVB-induced photoaging in HaCaT cells. The
expression of PTGS2 associated with skin aging and melanoma, which in
the co-administration group was reduced and overexpressed in
UVB-induced photoaging cells. The inhibition of PTGS2 could suppress
the cell proliferation and migration in malignant melanoma by
overexpression of eukaryotic translation initiation factor 3 subunit B
[[146]39]. The DEGs in each group of cells were enriched in processes
involving the regulation of oxidation-reduction reactions, skin growth,
and keratinization. It is evident that the regulation of oxidative
stress responses constitutes an essential mechanism through which the
combined administration of retinol and ferulic acid effectively
mitigates skin aging.
In summary, for the first time, we have discovered co-administration
with ferulic acid at specific proportions, the utilization efficiency
of retinol can be significantly enhanced, overcoming its limitations.
Through cellular experiments, it was observed that co-administration
primarily achieves the maintenance of cellular redox homeostasis by
scavenging free radicals and enhancing antioxidant defense
capabilities. The discovery of the PTGS2 gene’s involvement in
oxidative-reduction and inflammatory responses during HaCaT cell
photoaging process suggests that PTGS2 is a key regulatory gene. PTGS2
is the core target for treating oxidative stress in skin photoaging,
holding promise for therapeutic interventions.
CONCLUSIONS
In this study, the regulatory pathway and mechanism of FA in
synergizing with VA were predicted by network pharmacology. Through
cell experiments, the pharmacodynamic effect and optimal ratio of VA
and FA on UVB-induced photoaging of HaCaT cells were explored. FA
blunted to the stratum corneum stimuli from VA, while two drugs
synergistically enhanced photoaging-resistance capacity. At the
concentration of VA:FA of 100 μM:120 nM, the content of MDA and ROS
decreased significantly, and other indicators reflecting the level of
oxidative stress such as SOD, GSH, and CAT also increased to a level
close to normal cells. Moreover, the morphology of photoaged cells
recovered after synergistic administration. RNA sequencing results
exhibited that the transcription level of cells in the
co-administration group was closer to the normal group. A total of 155
the DEGs specifically synergistically acted on photoaged HaCaT cells.
Noteworthy, PTGS2 showed high affinity with VA and FA in molecular
docking, and was verified by transcriptomics as a key expression gene.
The mechanism of VA and FA in alleviating the photoaging process is
mainly involved in restoring anti-oxidative stress system and
anti-inflammatory.
MATERIALS AND METHODS
Collection of known and predicted targets of VA and FA
Known targets of VA and FA were collected from The Traditional Chinese
Medicine Systems Pharmacology Database (TCMSP,
[147]http://lsp.nwu.edu.cn/) and the Drugbank Database
([148]https://go.drugbank.com/). Predicted targets of both components
were collected from SwissTargetPrediction database
([149]http://swisstargetprediction.ch/). In addition, targets
identified in published literature were also collected.
Collection of human skin aging disease targets
The targets of skin aging were obtained from the GWAS database
([150]https://www.ebi.ac.uk/gwas/) and GeneCards Database
([151]https://www.genecards.org/) according to the MESH of diseases
including “Skin Aging”, “Aging, Skin”, “Solar Aging of Skin”,
“Photoaging of Skin”, “Skin Wrinkling”, “Skin Wrinklings”, and
“Wrinkling, Skin”. The disease targets related to human skin aging were
filtered based on a correlation score in databases greater than 0.5 or
80 points.
Venn analysis
Intersection analysis was performed separately on the target proteins
of VA and FA associated with skin aging targets. The intersecting
targets were considered as the common targets for the effects of VA and
FA on skin aging-related diseases. Subsequently, we performed
biological functional analysis on the two intersecting targets
separately using the DAVID database. We screened for targets directly
connected to mechanisms of skin aging diseases, such as regulating
inflammation processes, antioxidant functions, and immune regulation.
These targets were considered as the common targets for both VA and FA
in skin aging. These biological processes and targets form the
foundation for the synergistic action of VA and FA.
Gene set enrichment analysis (GSEA)
Using R 4.2.0 software, Gene Set Enrichment Analysis (GSEA), a
knowledge-based method for analyzing genome-wide expression patterns,
was carried out on hub targets. It included hub target pathway
enrichment from the Kyoto Encyclopedia of Genes, Genomes (KEGG) and
Gene Ontology Annotation (GO). Enrichment bubbles were also constructed
through R software 4.2.0 with top 20 items with significant differences
(adjusted P<0.05).
Identification of differentially expressed genes (DEGs) in skin aging
Expression profiling by high throughput sequencing with series number
[152]GSE182673 based on platform [153]GPL16791 (Illumina HiSeq 2500,
Homo sapiens) was downloaded from the GEO database. This dataset
contained 50 skin aging samples and 25 normal samples, which identified
881 DEGs. DEGs between skin aging groups and normal group were
respectively analyzed using the limma package in R. Fold changes (FCs)
in the expression of individual genes were calculated. DEGs with adj
Pval < 0.05, log FC> 1 for up regulated genes and log FA< − 1 for down
regulated genes were considered as significant. Subsequently, Venn
analysis was performed on the DEGs and selected potential therapeutic
genes. The resulting common genes were considered as the synergistic
targets of VA and FA. The DAVID database was then used to carry out a
second round of biological functional enrichment analysis and KEGG
pathway enrichment analysis, then investigated the pharmacological
effects and molecular mechanisms of the synergistic action of VA and
FA.
Protein–protein interaction analysis and molecular docking
According to the correlation score>0.4, the Protein–Protein Interaction
(PPI) network was built by targets of VA, FA and skin aging, which were
obtained from Search Tool for the Retrieval of Interacting
Genes/Proteins (STRING, a free biological database)
([154]https://cn.string-db.org/cgi/) respectively. PPI network nodes
were introduced into Cytoscape 4.0 software for visualization. The main
targets with top 10 values were screened after network topology
analysis. Then VA and FA were molecularly docked with the top 5 key
targets through Discovery studio software.
Weighted gene co-expression network analysis
Using WGCNAR package, GEO expression file was applied for weighted gene
co-expression network analysis (WGCNA). The association between the
clinical characteristics and expression modules was investigated using
WGCNA. Module eigengenes (MEs) were defined as the first principal
component of each gene module and adopted as the representative of all
genes in each module. Gene significance (GS), as the mediator p-value
(GS=lg P) for each gene, represented the degree of linear correlation
between gene expression of the module and clinical features.
Survival-related modules were defined according to P≤0.01 and the
higher GS value was extracted for further analysis.
Molecular docking on hub targets of VA and FA
The protein structures of hub targets were downloaded from the PDB
Database ([155]https://www.rcsb.org/). The structural files of the key
active compounds of VA and FA were downloaded from the PubChem Database
([156]https://pubchem.ncbi.nlm.nih.gov/) and were saved in *SDF format.
The abovementioned structures were added hydrogens, and the charges
were firstly calculated by Discovery studio software (2.5 version), and
then they were docked through the Discovery studio software, the model
with the highest binding score value was selected, and their binding
structure finally was visualized by Discovery studio software.
Reagents and materials
VA was bought from Shanghai McLean Biochemical Technology Co., Ltd.
(Shanghai, China), and FA was from Shanghai Yuanye Technology Co., Ltd.
(Shanghai, China).
Human immortal keratinocyte cell line (HaCaT) was purchased from
American Type Culture Collection (Rockville, MD, USA). The 10 cm^2 cell
culture dishes, 6-well plates, and 96-well plates were purchased from
Corning Incorporated (Corning, NY, USA). DMEM Medium, fetal bovine
serum, 100 U/ml penicillin, and 100 μg/ml streptomycin were purchased
from Gibco (Thermo Fisher Scientific Co., Ltd, Waltham, MA, USA; Grand
Island, NY, USA). Reactive oxygen species (ROS) assay kit, GSH, SOD,
MDA and assay kit were purchased from Beyotime (Beyotime Biotechnology
Co. Ltd., Shanghai, China). Catalase Activity Assay Kit was purchased
from Abcam (Abcam (Shanghai) Trading Co., Ltd., China; ab83464).
3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) was
purchased from Sigma-Aldrich (MTT, Sigma-Aldrich, St. Louis, MO, USA).
Senescence-associatedβ-galactosidase (SA-β-gal) Stain Kit was produced
from Solarbio Technology Co. Ltd. (Beijing, China). Human
Cyclooxygenase-2 (COX-2) ELISA Kit was produced from Cusabio
Technology, LLC (Wuhan, China). RNA Nano 6000 Assay Kit of the
Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA, USA)
was used.
Cell culture
Human immortalized epidermal cells (HaCaT) were cultured in DMEM (high
glucose) medium with 10% fetal bovine serum and 1%
penicillin-streptomycin double antibody. They were maintained in a cell
incubator with 5% CO[2] at 37° C. Subculture was performed when the
cell confluency reaches 80%.
UVB-irradiation model and validation
HaCaT cells were cultivated to 80%–90% confluence, which were
irradiated at 302 nm and subjected to UVB radiation at varying
intensities (18-54 mJ/cm^2) following a PBS wash. After radiation, the
cells were cultured in full medium supplemented with 10% serum.
Cytotoxicity assay
Cytotoxicity was detected by MTT assay. In brief, HaCaT cells were
seeded into 96-well plates with a density of 1×10^4/well. After
treatment, 10 μL of 5 mg/mL MTT solution was added to each well and
then cells were incubated in the dark for 4 h. After removing the
cultured medium, the crystals were dissolved in 150 μL of DMSO. The
absorbance was measured at 490 nm with a BioTek plate reader (American
Boten Instrument Co., Ltd., Winooski, VT, USA). Using ferulic acid and
retinol cells, respectively, the toxicity of both components to HaCaT
cells and IC[50] values was explored.
Effects of VA and FA on HaCaT cell proliferation
HaCaT cells (1×10^5 cells/well) were seeded in 96-well transparent
plates. After cell adhesion, the original medium was aspirated. 100 μL
complete medium was added to the blank group. The gradient
concentration groups complete medium with 4μM~1.5mM and complete medium
with 1pM~1mM ferulic acid were separately added to cells. After 24 h of
incubation, 5 mg/mL Methyl Thiazolyl Tetrazolium reagent was added to
each well, the supernatant was aspirated after 4 hours, and dimethyl
sulfoxide (DMSO) was added to each well to detect absorbance.
Therefore, the influence of VA and FA on the proliferation of HaCaT
cells was investigated, and calculated the IC[50] dose. The experiment
was repeated 3 times. The experimental data were statistically analyzed
using GraphPad Prism 9, using ordinary one-way ANOVA for multiple
comparisons, and Tukey’s multiple comparisons teat, p<0.05.
Effects of VA and FA on HaCaT cells
HaCaT cells (1×10^5 cells/well) were seeded in 96-well plates, and
after the cells were adhered, discarded the original medium. The blank
group and the model group were added complete medium. In administration
group, VA and FA were set according to the value of IC[50], one of the
drug doses was set to the concentration of IC[50]. Using radiation
design, the two-dimensional coordinates were divided into 8 equal
parts, and 9 different proportions (1:0, 8:1, 4:1, 2:1, 1:1, 1:2, 1:4,
1:8, 0:1) were obtained, carried out ratio test separately. Positive
drug group were treated with N-acetyl cysteine (NAC) and Vitamin E (VE)
in concentration of 2.5 mM and 1.56 μM. Incubated for 24 h, both the
model group and the experimental group were exposed with UVB rays
(54mJ/cm^2). The activity of HaCaT cells in different groups was
measured. Subsequently, the quadratic polynomial was used to describe
the dose-response curve of the combination of FA and VA, and the
response index indicated the interaction strength. Subtract the
response index by 1 and take 0 as a typical addition effect for easy
plotting. In the 3D response surface model diagram, the color shade
indicated the intensity of the interaction between the two drugs. When
the response index was close to 0, the drug was shown as an additive
effect; when greater than 0, it was manifested as antagonism; when less
than 0, it manifested as a synergistic effect. The higher the index
value, the greater the intensity of the interaction, and the response
surface plot appears to be colored close to either light or dark.
Matlab software was used to fit the model and determine the parameters.
Taking the cell viability rate as the evaluation index, the
three-dimensional response surface model was fitted.
Pharmacodynamic response surface analysis of the interaction between VA and
FA
NLMAZ is an extension to the mixed amount with zero amount observation
model that it allows for a different concentration-pharmacodynamic
response in two or more drugs [[157]40]. The absorbance value obtained
from cell experiment were input to describe the dose-response curve by
quadratic polynomial, following each treatment with two drugs in
combination as well as in the case of untreated positive control and
negative control [[158]41]. This stepwise regression method was used to
construct the index and evaluate the model of different proportions of
drugs. Then introduced response index to indicate the interaction
strength. The three-dimensional response surface plots were presented
with Origin9.1 software (OriginLab Corporation, Northampton, MA, USA)
and according to the statistical strategies, calculated the best ratio.
Staining for β-galactosidase activity
HaCaT cells were plated into 6-well plates and cultured for 24 hours.
Blank control, VA-FA, VA, FA, and NAC were introduced to the respective
plates following UVB irradiation, and the plates were then incubated
for 24 hours at 37° C. After 24 h, the cells were fixed and stained
according to the β-galactosidase activity kit instructions, and they
were then left overnight to incubate at 37° C without CO[2]. Under a
microscope, the positive expression of β-galactosidase was observed
under a light microscope to microscope and captured.
Effects of retinol synergistic ferulic acid on HaCaT cell morphology and ROS
HaCaT cells were irradiated with UVB (56 mJ/ cm^2) to induce cell
senescence. The cells were pretreated with mixture of VA and FA (100μM:
80nM), NAC, VE for 24 h before irradiation. Incubated for 24 h,
photograph the cell morphology and fluorescence. HaCaT cells are
stained with 5-(and-6)-carboxy-2’,7’-dichlorodihydrofluorescein
(DCFH-DA), incubated in the dark for 30 min, and washed 3 times with
PBS. Under fluorescence microscopy and excited with blue light, the
emission image of the cell can be observed. Green fluorescence
represented the amount of intracellular ROS that were bound. The
stronger the fluorescence, the higher the ROS content was. The level of
cellular ROS production was determined applying Novo Quanteon flow
cytometer (Agilent ACEA, America) according to the manufacturer’s
protocol. Using the GraphPad Prism 9.0 software, an Ordinary One-Way
ANOVA was performed to compare the differences between the groups. The
post hoc test Dunnett’s t-test was employed to ascertain the
significance of the experimental outcomes.
Collection of test samples
HaCaT cells (50×10^5 cells) were seeded in 6 cm cell culture dishes,
and the model group and the drug administration group were exposed to
UVB rays. After the cells were adhered, pretreated cells with mixture
of VA and FA (100 μM:80 nM), NAC, VE for 24 h before irradiation. Then
incubated for 24h, cells were collected by trypsinization, washed with
ice-cold PBS. Aspirated the cell culture supernatant and added 100 μL
of ripa lysate for each dish. Scraped off the cells in the dishes,
centrifuge at 5000 rpm for 5 mins, removed the pellet, collected the
supernatant, and stored it at -80° C together with the cell culture
supernatant as test sample.
Measurement of MDA, SOD, GSH, CAT
The level of Malondialdehyde (MDA) qualification was measured for the
evaluation of lipid peroxidation rate on HaCaT cells according to the
manufacturer’s protocol. Absorbance was measured at 532 nm to qualify
MDA. Superoxide Dismutase (SOD) activity was measured on HaCaT cells
according to the manufacturer’s protocol. Absorbance was measured at
450 nm, and the values were directly proportional to the SOD inhibition
rate. Content of reduced glutathione (GSH) was measured at 412 nm for
detecting the content of total glutathione. Catalase activity (CAT) was
evaluated in measuring absorbance at OD 570 nm.
The experiment strictly adhered to the principle of complete
randomization. Between-group comparisons were conducted using ANOVA
analysis. All results are presented as mean ± standard deviation. The
calculations were performed using GraphPad Prism software.
RNA extraction
After treatments, HaCaT cells were detached using trypsin digestion.
The supernatant was discarded after centrifugation. Then cells were
washed with RNase-free PBS and centrifuged. For each sample, 1 mL of
Trizol reagent was added, mixed thoroughly. Following the addition of
0.2 mL chloroform and thorough mixing, the mixture was centrifuged at
4° C. The upper aqueous phase was collected. Subsequently, 0.5 mL
isopropanol was added, mixed well, and left to stand for 10 minutes.
The precipitate was obtained after centrifugation, followed by
centrifugation after washing with ice-cold 75% ethanol. Total RNA was
obtained by dissolving the pellet in DEPC-treated (RNase-free) water.
Validation of transcriptome data
According to the kit NEBNext® UltraTM RNA Library Prep Kit, libraries
were established using total RNA greater than 1 μg. RNA purity was
detected by NanoPhotometer spectrophotometer. Precise quantification of
RNA concentration using Qubit2.0 Fluorometer was done. Diluted the
library to 1.5 ng/μL, and detected RNA integrity with Agilent 2100
bioanalyzer.
Sequencing data analysis
The image data obtained from the high-throughput sequencer for
sequenced fragments were converted into sequence data (reads) through
CASAVA base calling. To ensure the quality and reliability of data
analysis, reads containing adapters, reads with N (where N represents
undetermined base information), and low-quality reads (reads with
Qphred ≤ 20, comprising over 50% of the total read length) were
removed. Paired-end clean reads were aligned to the reference genome
using HISAT2 v2.0.5. A spliced alignment database was generated based
on the gene model annotation file. StringTie [[159]42] was employed for
novel gene prediction. The feature Counts tool was utilized to compute
the read counts mapped to each gene. DESeq2 R software (version 1.16.1)
was employed for differential expression analysis between two compared
groups. The Benjamini and Hochberg method was applied to adjust the
P-values. Corrected P-values along with |log2FC| were used as
significance thresholds for differentially expressed genes. The
clusterProfiler R software facilitated Gene Ontology (GO) enrichment
analysis and differential gene analysis in KEGG pathways for the
differentially expressed genes. R Studio software was utilized for
generating heatmaps and volcano plots for analysis. The locally
implemented GSEA analysis tool
([160]http://www.broadinstitute.org/gsea/index.jsp) was used for Gene
Set Enrichment Analysis of GO and KEGG datasets specific to the
species. The RNA-seq data was uploaded to public database, GEO database
([161]https://www.ncbi.nlm.nih.gov/), The BioProject is PRJNA1069325.
Measurement of cyclooxygenase-2 (COX-2)
After 24h of UVB irradiation and sample treatment, cell lysates were
collected from each dish. The concentration of COX-2 was analyzed from
cell lysates using Human Cyclooxygenase-2 (COX-2) ELISA Kit in
accordance with the manufacturer’s instructions.
Data and materials availability
All the data could be obtained from the Supplementary Material and
contacting the corresponding authors.
Supplementary Material
Supplementary Table 1
[162]aging-16-205749-s001.xlsx^ (16.1KB, xlsx)
Supplementary Table 2
[163]aging-16-205749-s002.xlsx^ (14.7KB, xlsx)
Supplementary Table 3
[164]aging-16-205749-s003.xlsx^ (43.2KB, xlsx)
Supplementary Table 4
[165]aging-16-205749-s004.xlsx^ (25KB, xlsx)
Supplementary Table 5
[166]aging-16-205749-s005.xlsx^ (35.1KB, xlsx)
Supplementary Table 6
[167]aging-16-205749-s006.xlsx^ (3MB, xlsx)
Supplementary Table 7
[168]aging-16-205749-s007.xlsx^ (68KB, xlsx)
Supplementary Table 8
[169]aging-16-205749-s008.xlsx^ (271.5KB, xlsx)
Supplementary Table 9
[170]aging-16-205749-s009.xlsx^ (156.6KB, xlsx)
Footnotes
AUTHOR CONTRIBUTIONS: Wei Zhu and Zhiyun Du provided conceptualization
and designed the research process. Peng Shu, Jiaxin Mo and Zunjiang Li
were responsible for the methodology, conducted the final statistical
analysis and graph, wrote the manuscript. Mingjie Li conducted formal
analysis. Peng Shu and Jiaxin Mo reviewed and edited the article. Wei
Zhu and Zhiyun Du were responsible for the decision and final check of
the manuscript. All authors agreed to be accountable for all aspects of
work ensuring integrity and accuracy.
CONFLICTS OF INTEREST: The authors declare that the research was
conducted in the absence of any commercial or financial relationships
that could be construed as a potential conflict of interest.
FUNDING: This work was supported by Guangdong Provincial Hospital of
Traditional Chinese Medicine Science and Technology Research Special
Project (YN2023MS44); Guangdong Province Special Fund for the
Prevention and Control of Novel Coronavirus Science and Technology
(2023A1111020001); Science and Technology Planning Project of Guangdong
Province (2023B1212060063); Guangzhou Fundamental Research Project
(Municipal Institute Joint) (202201020296).
REFERENCES