Abstract
Insufficient milk supply is a widespread issue faced by women globally
and associated with a higher risk of health problems in infants and
mothers. Hemerocallis citrina Baron, commonly known as daylily, is a
perennial edible plant often used in traditional Asian cuisine to
promote lactation. However, the active compound(s) and mechanism of its
lactation-promoting effect remain unclear. This study aimed to confirm
the traditional use of daylily in promoting lactation and investigate
its potential active components and underlying molecular mechanisms.
Our results showed that the aqueous extracts of H. citrina Baroni (HAE)
significantly enhanced milk production, and the serum levels of
lactation-related hormones, and promoted mammary gland development in
lactating rats, as well as increased the levels of milk components in
bovine mammary epithelial cells (BMECs) (p < 0.05). UHPLC-Q-Exactive
Orbitrap-MS analysis revealed that hexamethylquercetin (HQ) is the
representative flavonoid component in HAE, accounting for 42.66% of the
total flavonoids. An integrated network pharmacology and molecular
docking analysis suggested that HQ may be the potential active
flavonoid in HAE that promotes lactation, possibly supporting lactation
by binding to key target proteins such as STAT5A, PIK3CA, IGF1R, TP53,
CCND1, BCL2, INS, AR, and DLD. Cell experiments further demonstrated
that HQ could promote cell proliferation and the synthesis of milk
proteins, lactose, and milk fat in BMECs. Transcriptomic analysis
combined with a quantitative reverse transcription polymerase chain
reaction (RT-qPCR) revealed that both HAE and HQ exert a
lactation-promoting function mainly through regulating the expression
of key genes in the PI3K-Akt signaling pathway.
Keywords: flavonoids, Hemerocallis citrina Baroni,
hexamethylquercetagetin, lactogenic properties
1. Introduction
Insufficient milk supply often leads to an early cessation of exclusive
breastfeeding [[48]1]. This shortage is linked to a greater chance of
various health problems such as diarrhea, leukemia, and respiratory
illnesses in infants and a higher risk of breast and ovarian cancers,
diabetes, and heart attacks in mothers [[49]2]. Successful lactation
involves a multistage process driven by reproductive and metabolic
hormones, including but not limited to estradiol (E[2]), prolactin
(PRL), growth hormone (GH), and thyroid hormone [[50]3]. Medications
like domperidone and metoclopramide are used to raise PRL levels and
potentially increase milk supply [[51]4]. However, given the potential
side effects associated with the long-term use of these medicines,
including tardive dyskinesia, depression, increased risk of ventricular
arrhythmia, and sudden cardiac death [[52]5], finding safe and
effective alternatives is of great importance.
Hemerocallis citrina Baroni, a perennial plant of the Liliales order,
is native to central and northern China, the Korean Peninsula, and
Japan. It has been regarded as a functional vegetable crop in
traditional Asian cuisine due to its rich nutritional value
[[53]6,[54]7]. Recent studies have shown that H. citrina is rich in
flavonoids, alkaloids, carotenoids, amino acid amides, and other
biologically active substances, which are effective in
anti-inflammatory, anxiety-relieving, and sleep-promoting effects
[[55]8,[56]9,[57]10]. Additionally, H. citrina is also known as
“Galactogogue” in many Asian countries and is used as an important
ingredient in soups to enhance milk production in lactating women
[[58]11,[59]12]. Despite its traditional use to promote lactation,
there are currently only a few studies that have reported on its
lactation-promoting properties. For example, Zhong et al. [[60]12]
investigated the effects of H. citrina extract on lactation
insufficiency in chronic unpredictable mild stress (CUMS) dams and
found that the extract could promote weight gain in offspring and
increase the levels of PRL and oxytocin in the serum of the model mice.
Additionally, network pharmacology predicted that the potential key
targets could be MAPK1, STAT3, and TP53. Similarly, Guo et al. [[61]13]
studied the therapeutic effects of H. citrina extract on a rat model of
lactation deficiency induced by bromocriptine. They discovered that the
extract significantly increased milk production, as well as the levels
of PRL, progesterone, and estradiol, and promoted the repair of mammary
gland tissues. Network pharmacology analysis suggested that flavonoid
compounds and phenolic substances might be the active ingredients
enhancing lactation, primarily acting through the JAK2/STAT5 pathway.
However, due to the diversity and complexity of the bioactive
substances, no studies have yet systematically validated the potential
active components of H. citrina for promoting lactation, and its key
targets and mechanisms of action remain unclear.
Flavonoids, a subgroup of polyphenols widely present in plants, exhibit
multiple physiological and pharmacological activities such as
antioxidant, antibacterial, anti-tumor, and anti-cardiovascular disease
properties [[62]14,[63]15]. Numerous studies have demonstrated that
flavonoids improve lactation performance. For instance, Garavaglia et
al. [[64]16] reported an increase in milk production when dairy cows
were fed a diet containing silymarin and lycopene for seven consecutive
days. Cui et al. [[65]17] found that supplementing the basal diet of
dairy cows with 3.0 and 4.5 mg of rutin per kg of diet significantly
increased milk production by 10.06% and 3.37%, respectively. Current
studies suggest that flavonoid compounds can enhance lactation by
binding to the β-estradiol receptor via the α-isoform of
membrane-associated estrogen in lactotrophic cells of the anterior
pituitary gland and antagonizing dopamine receptors [[66]18]. This
leads to up-regulated expressions of PRL receptor (PRLR)-related genes
and stimulates mammary gland development, thereby improving lactation
performance. However, most existing studies have not elucidated the
underlying mechanism of the lactation-promoting effects of H. citrina
and its flavonoids.
Transcriptomics enables a high-throughput detection of changes in gene
expression and provides a comprehensive understanding of the structure
and function of genes on a genome-wide scale, thereby revealing the
potential mechanisms behind biological effects. Network pharmacology
studies functional active substances by constructing a multi-compound,
multi-target, and multi-pathway interaction network through the
comprehensive analysis of biological system networks. Molecular docking
reveals interactions between effective components and potential targets
at the molecular level based on the three-dimensional structure of
receptor macromolecules and the binding of ligand compounds. The
combination of these methods helps to reveal the core targets,
metabolites, and pathways in the lactation regulation network.
In this study, first, the lactation-improvement effect of the aqueous
extracts of H. citrina Baroni (HAE) on lactating rats and bovine
mammary epithelial cells (BMECs) was evaluated. Then, UHPLC-Q-Exactive
Orbitrap-MS was employed to identify and quantify the active components
in HAE responsible for the observed biological effects. Subsequently,
transcriptomic analysis was performed to identify genes that are
differentially expressed after HAE and hexamethylquercetagetin (HQ)
treatment and reveal their corresponding underlying molecular
mechanisms involved in lactation processes. Following this, network
pharmacology and molecular docking were combined to predict the
possible active components in HAE and the core targets related to
lactation and model the interactions between HQ and the core target
proteins. Finally, a quantitative reverse transcription polymerase
chain reaction (RT-qPCR) was employed to clarify the underlying
mechanism related to the lactogenic activity.
2. Materials and Methods
2.1. Chemicals and Reagents
Dried flower buds of H. citrina Baroni (Asphodelaceae) were kindly
provided by Xinfa Food Co. Ltd. (Qidong, Hunan, China) in July 2022.
Methanol and Acetonitrile were LC–MS grade and obtained from CNW
Technologies (CNW Technologies GmbH, Teltow, Germany). Ammonium acetate
was purchased from Sigma-Aldrich Chemical Co. (St. Louis, MO, USA). HQ
was purchased from Yuanye Shengwu Co. Ltd. (Shanghai, China). All other
chemicals and reagents employed in this work were of analytical grade.
2.2. Preparation of HAE
In total, 100 g H. citrina Baroni was ground to powder, extracted twice
with 3500 mL of water, and maintained for 20 min in an ultrasonic bath
(40 KHz) at 50 °C. The mixture was centrifuged at 10,000 rpm for 15 min
at 4 °C and then concentrated by a rotary evaporator (SENCQ R-501,
Shenshun Biotechnology Co., Shanghai, China). Finally, the concentrate
was lyophilized for 72 h to obtain HAE powder and stored in the
refrigerator at −20 °C. LC–MS analysis confirmed that colchicine is not
present in the HAE lyophilized powder.
2.3. Components in HAE by UHPLC-Q-Exactive Orbitrap-MS Analysis
The separation was performed employing a Vanquish UHPLC system (Thermo
Fisher Scientific, Bremen, Germany) in conjunction with an UPLC HSS T3
column (2.1 mm × 100 mm, 1.8 μm). The separated analytes were then
detected by an Orbitrap Exploris 120 mass spectrometer (Thermo Fisher
Scientific, Bremen, Germany). The mobile phase consists of eluent A (5
mmol/L ammonium acetate and 5 mmol/L acetic acid in water) and eluent B
(methanol). The solvent gradient was set as follows: 1% B, 0.7 min;
1–99% B, 9.5 min; 99% B, 11.8 min; 99–1% B, 12 min; 1% B, 15 min. The
mass spectrometer was operated in positive/negative polarity mode with
a capillary temperature of 320 °C, sheath gas flow rate of 50 arb,
auxiliary gas flow rate of 15 arb, and a spray voltage of 3.8 kV
(positive) or −3.4 kV (negative).
2.4. Experiments Performed with Animals
2.4.1. Experimental Design and Treatments
A total of 12 SD rats (8 ± 2 weeks old) at the beginning of lactation
and 120 suckling pups were purchased from Hunan SJA Laboratory Animal
Co. Ltd. (license no. SCXK 2023-0004, Changsha, Hunan, China). The
animals were placed in standard cages with wood chips and given free
access to food and water. The system was set to maintain conditions
with a 12 h light and 12 h dark cycle between 22 and 24 °C. Then, 12
lactating rats, each of which had 10 pups, were randomly divided into
three groups: the control group (CK), the low-dose aqueous extracts of
H. citrina Baroni group (HAE-L, 100 mg/kg/day), and the high-dose
aqueous extracts of H. citrina Baroni group (HAE-H, 300 mg/kg/day). The
CK of rats were treated with orally administered distilled water. The
experimental protocols were conducted based on the standards of the
ARRIVE guidelines, and all animal-care procedures were approved by the
Ethical Committee of Hunan Academy of Agricultural Sciences (no.
2023012).
2.4.2. The Weight Gain per Litter and the Organ/Tissue Index of Lactating
Rats
Using each litter as the fundamental unit of observation, the pups in
each litter were weighed every three days from the 1st day to the 18th
day, according to a previous report with some modifications [[67]19].
The weight increase for each litter was determined using the formula:
[MATH: WG=W(W)−W(I) :MATH]
.
2.4.3. Detection of Serum Hormone Levels
After isoflurane anesthesia, the blood sample was collected with vacuum
tubes containing heparin sodium anticoagulant following a cardiac
puncture. The blood samples were then centrifuged at 1000 rpm for 15
min at 4 °C, and the serum was stored at −80 °C for subsequent assays.
The assays for serum hormones were carried out using the rat PRL, PRLR,
and E[2] enzyme-linked immunosorbent assay (ELISA) kits, respectively
(Huangshi Inselisa Biotechnology Co., Ltd., Huangshi, China).
2.4.4. Histopathological Analysis
Histopathological analysis of mammary glands was conducted using an
optical microscopy on paraffin material [[68]20]. Briefly, the
formalin-treated mammary gland tissues were gradually dehydrated by
being immersed in 10% graded ethanol solutions and then embedded in
pre-melted paraffin. Sections of 5 µm thickness were produced using a
paraffin microtome. The prepared sections were then stained with
hematoxylin and eosin (H&E). Finally, mammary tissue morphology of each
group was observed and photographed under a microscope Leica digital
camera (Leica DFC420C, Leica Mikrosysteme Vertrieb GmbH, Wetzlar,
Germany).
2.5. Cell Experimentation
2.5.1. Cell Cultures
The immortalized BMECs from the mammary tissues of Bos taurus were
purchased from WHELAB (Shanghai, China). The cells were subcultured in
90% Dulbecco’s Modified Eagle’s Medium/F12 (DMEM/F12; Gibco, Carlsbad,
CA, USA) supplemented with 10% fetal bovine serum (VivaCell, Shanghai,
China) and 1% penicillin-streptomycin (VivaCell) in a humidified
incubator at 37 °C under an atmosphere with 5% CO[2]. The passage was
performed when the cell density reached 90%, and the passage ratio was
1:3.
2.5.2. Cell Proliferation Assay
Cell Counting Kit-8 assay was utilized to assess the effect of HAE and
HQ on the viability of BMECs [[69]21]. Briefly, cells were seeded into
96-well microplates (1 × 10^4 cells/well) to attach at 37 °C and 5%
CO[2] for 24 h. In the CK group, cells were treated with DMEM/F12
medium without HQ. In the treated group, cells were exposed to a medium
containing different concentration gradients of HAE (20, 40, 80, and
160 μg/mL) and HQ (100, 200, 400, and 800 μM). After the 48 h
incubation times indicated, 10 μL of cell counting kit-8 (CCK-8)
reagent (Biosharp, Shanghai, China) was added to the corresponding well
and incubated at 37 °C for 2 h. Finally, the absorbance at 450 nm was
recorded. The proliferation rate was calculated using the following
equation:
[MATH: Proliferation rate100%=ODtreate
d−ODblankODco<
/mi>ntrol−ODblank×100 :MATH]
2.5.3. Determination of Milk Protein, Lactose, and Milk Fat Content by ELISA
A total of 5 × 10^6 cells were inoculated into each well of 6-well
plates, grown overnight, and treated with different concentrations of
HAE (20, 40, 80, and 160 μM) and HQ (100, 200, and 400 μg/mL) for 48 h.
Cell debris was eliminated from the culture supernatants by
centrifuging them at 3000× g for 10 min at 4 °C to remove cell debris,
after which they were collected for ELISA to determine the milk protein
(α-casein, β-casein, and whey protein), lactose, and milk fat levels
according to the manufacturer’s instructions (Fujian Quanzhou Ruixin
Biotechnology Co., Ltd., Quanzhou, China). The absorbance values of
samples were measured at 450 nm and used to calculate the
concentrations with standard curves.
2.6. Network Pharmacology Analysis
2.6.1. Screening of HAE Flavonoid Targets and Lactation-Related Targets
The SwissADME platform ([70]http://www.swissadme.ch/, accessed on 28
March 2023) was utilized to screen the HAE flavonoid components
detected using UHPLC-Q-Exactive Orbitrap-MS analysis. The screening
criteria were as follows: High Gl absorption and positive results in at
least 2 of 5 drug property predictions (Lipinski, Ghose, Veber, Egan,
Muegge). The targets for potential flavonoid components were screened
using the PharmMapper database
([71]http://lilab-ecust.cn/pharmmapper/index.html, accessed on 28 March
2023). Lactation-related targets were obtained through GeneCards and
OMIM ([72]http://www.omim.org/, accessed on 28 March 2023), using
“Lactation” as the keyword. All targets were standardized as Gene
Symbols using the UniProt protein database
([73]https://www.uniprot.org, accessed on 29 March 2023). The
intersection of potential targets for HAE flavonoids and
lactation-related targets was obtained through Venny 2.1.0
([74]https://bioinfogp.cnb.csic.es/tools/venny/, accessed on 29 March
2023).
2.6.2. Protein–Protein Interaction (PPI) Network Construction
The PPI network was constructed by submitting the target proteins to
the STRING12.0 database ([75]https://string-db.org, accessed on 1 April
2022), with the biological species set to “Homo sapiens”, and the
minimal connection score threshold set to 0.700. The network
relationship file was imported into Cytoscape 3.7.1 to visualize the
PPI network. Potential functional protein modules were then identified
using the MCODE plugin for further PPI network analysis.
2.6.3. Core Target Functional Enrichment Analysis
The intersection of potential targets for HAE flavonoids and
lactation-related targets, as well as the potential core targets, was
uploaded to the Metascape platform
([76]http://metascape.org/gp/index.html, accessed on 1 April 2022) for
Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes
(KEGG) pathway enrichment analysis. The results were visualized using
an online bioinformatics tool ([77]http://www.bioinformatics.com.cn,
accessed on 1 April 2022).
2.7. Molecular Docking
The key flavonoid components and potential core targets of HAE were
obtained through ITP network analysis. The 3D protein structures of
these targets were obtained from the PDB database
([78]https://www.rcsb.org) (accessed on 5 April 2022). Then, these
protein structures were imported into PyMOL 3.0.2 software, the targets
were dehydrated and hydrogenated, and the irrelevant ligands were
removed. The key flavonoid components and receptor proteins were docked
using the AutoDockTools program, and the docking results were then
imported into PyMOL 3.0.2 software for visualization analysis.
2.8. Transcriptomic Analysis
After the BEMCs were treated with a medium containing 400 μg/mL HAE and
80 μM HQ for 48 h, the cells were washed twice with PBS. Then, total
RNA was extracted using Trizol reagent (YEASEN Biotechnology Co., Ltd.,
Shanghai, China) based on the manufacturer’s instructions. The RNA
amount and purity were quantified utilizing a NanoDrop ND-1000
spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA), and the
RNA integrity was assessed by 1% agarose gel electrophoresis and a
universal hood II transilluminator gel documentation system (BIO-RAD,
Hercules, CA, USA). Library preparation and sequencing were performed
at Gene Denovo Biotechnology Co. (Guangzhou, China). GO function and
KEGG pathway enrichment analysis were performed to analyze the main
functions and identify significantly enriched pathways of
differentially expressed genes (DEGs), respectively.
2.9. DEG Validation by RT-qPCR
The total RNA concentration of 400 μg/mL HAE and 80 μM of HQ-treated
cells and CK cells were extracted. The Hifair^® III 1st Strand cDNA
Synthesis Kit (YEASEN, Shanghai, China) was utilized to synthesize cDNA
according to the manufacturer’s instructions. RT-qPCR was performed
using a CFX96 Touch real-time PCR detection system (Bio-Rad
Laboratories, Hercules, CA, USA) with 10 μL of PCR reaction mixture,
including 1 μL of cDNA, 5 μL of Hieff^® qPCR SYBR Green Master Mix with
Low Rox Plus (Yeasan, Shanghai, China), 0.2 μL of forward primer, 0.2
μL of reverse primer, and 3.6 μL of double-distilled water. The GAPDH
gene was selected as the reference gene, and the primer sequences are
presented in [79]Table S1. The reactions were incubated at 95 °C for 5
min, followed by 40 cycles of 95 °C for 10 s and 60 °C for 30 s. The
RT-qPCR data were calculated using the 2^−△△Ct method.
2.10. Statistical Analysis
Data are expressed as mean ± standard deviation. Statistical analysis
and plotting were conducted utilizing GraphPad Prism 8.0 (GraphPad
Software, La Jolla, CA, USA). The treatment groups were analyzed using
one-way ANOVA followed by Tukey’s post hoc test, and p < 0.05 was
considered statistically significant.
3. Results
3.1. HAE Up-Regulated Lactation Performance in Lactating Rats
To explore the lactation-promoting activity of HAE in lactating rats,
the litter weight of the pups was measured, and the weight gain was
calculated as a response variable that indirectly reflects the amount
of lactation. As shown in [80]Figure 1A, there was no significant
difference in the average litter weight gain of the pups in comparison
to the CK group on days 3–12 of the lactation period. However, pups in
the two groups receiving HAE supplementation experienced a higher
average weight gain per litter compared to the CK group on days 15–18
(p < 0.05), among which the HAE-L group presented a better effect. The
litter weight of the pups in the HAE-L group was enhanced by 15.8% in
comparison to the CK on the last day of lactation. The results for the
organ/tissue index of the lactating rats are shown in [81]Figure 1B.
The mammary gland tissue index of the lactating rats in the HAE-L group
was significantly increased compared to the CK group (p < 0.05), which
was enhanced by 1.2 times. The uterus index increased significantly in
both the HAE-L and HAE-H groups (p < 0.05), while the enhancement was
more obvious in the HAE-L group. There was no significant difference in
the ovarian index between groups. These results suggest that HAE,
especially at low doses, can promote weight gain in pups and contribute
to lactation. ELISA was used to assess the effects of HAE on
lactation-related hormone levels in the serum of lactating rats. As
shown in [82]Figure 1C–E, HAE increased the serum hormone levels of
PRL, PRLR, and E[2] in comparison to the CK group. Specifically, the
HAE-L group showed significantly higher levels of PRL and PRLR compared
to the CK group (p < 0.05), with increases of 15.15% and 11.95%,
respectively. In the HAE-H group, the levels of PRLR and E[2] were
significantly higher than the CK group (p < 0.05), increasing by 8.65%
and 9.27%, respectively. Histopathological analysis was utilized to
investigate the impact of HAE on the mammary gland structure of
lactating rats. As shown in [83]Figure 1F, mammary gland sections from
the various treatment groups displayed a typical lactation-stage
appearance. Specifically, in the CK group, the acinar and ductal lumens
were significantly expanded, and most of the acinar lumens contained
pink secretions. Additionally, fibrous connective tissue and adipose
tissue were interspersed throughout the lobules. In contrast, the HAE-L
group showed well-developed mammary tissue characterized by enlarged
and densely distributed acinar cavities and clearly defined lobules.
Many acini were filled with secretions, and the amount of fibrous
connective tissue and fatty tissue was significantly reduced,
suggesting active milk secretion within the mammary tissue. Meanwhile,
in the HAE-H group, the mammary gland tissue showed extended ducts and
irregular-shaped acini. The lobular structure was less distinct, with
fibrous connective and fatty tissue spread within the stroma of the
mammary gland.
Figure 1.
[84]Figure 1
[85]Figure 1
[86]Open in a new tab
Effect of HAE on lactation function. (A) The weight gain per litter of
pups during the lactation. (B) The ovaries, mammary glands, and uterus
index of lactating rats. (C) The serum prolactin (PRL) level of
lactating rats. (D) The serum prolactin receptor (PRLR) level of
lactating rats. (E) The serum estradiol (E[2]) level of lactating rats.
(F) Mammary gland structure (40 magnification, H&E stained section) of
lactating rats from the CK group (a1,a2), the HAE-L group (b1,b2), and
the HAE-H group (c1,c2). The green arrows indicate pink secretions; the
black arrows indicate fibrous connective and adipose tissues. (G) The
effect of various concentrations of HAE on the cell viability of BMECs.
The contents of α-casein (H), β-casein (I), whey protein (J), lactose
(K), and milk fat (L) of samples from the HAE group and the CK group.
ns represents not significant. * p < 0.05, ** p < 0.01, *** p < 0.001.
3.2. HAE Increased Milk Protein, Lactose, and Milk Fat Contents in BMECs
The effects of HAE on lactation were investigated using a BMEC model to
determine its capability to stimulate milk production. Initially, the
CCK-8 assay was used to detect the effect of different concentrations
of HAE (100–800 μg/mL) on the cell viability. As shown in [87]Figure
1G, all concentrations of HAE promoted the proliferation of BMECs in
comparison to the CK group. However, at a concentration of 800 μg/mL,
cell viability was reduced to a certain extent compared to 400 μg/mL.
Therefore, the selected range for HAE was determined to be 0–400 μg/mL.
The effects of varying concentrations of HAE (0–400 μg/mL) on milk
protein (α-casein, β-casein, and whey protein), lactose, and milk fat
content in BMECs was assessed by ELISA. As shown in [88]Figure 1H,I,
the casein content was significantly increased after 400 μg/mL HAE
treatment (p < 0.05). The contents of α-casein and β-casein were 122.29
and 79.56 μg/mL, respectively, which were 1.17 and 1.20 times that of
the CK group. [89]Figure 1J showed that all of the concentrations of
HAE enhanced whey protein content in a dose-dependent manner, with
significant (p < 0.05) and highly significant (p < 0.01) enhancements
at 200 and 400 μg/mL, respectively. [90]Figure 1K,L revealed that
treatment with different HAE concentrations significantly increased
lactose and milk fat content (p < 0.05), with the highest values of
297.05 μg/mL and 1282.19 pg/mL, respectively, observed at 100 μg/mL.
3.3. RNA-seq Revealed the Regulatory Mechanism of HAE on the
Lactation-Promoting Effect of BMECs
The effect of HAE (400 μg/mL) on the transcript profile in BMECs was
conducted to investigate the potential mechanisms behind the lactogenic
performance. Following the filtration of raw data, examination of
sequencing error rates, and analysis of guanine–cytosine content, a
total of 43.63 Gb of clean data were generated, averaging 7.27 Gb for
each sample. The Q30 base percentage ranged from 90.86 to 93.00%, and
the GC content varied from 51.56 to 52.26%, indicating an evenly
distributed base and high sequencing accuracy ([91]Table S2). The
alignment efficiency is the most direct reflection of transcriptome
data utilization. The rate of the successful alignment of sequenced
reads to the genome exceeded 96.14%, with a matching efficiency
exceeding 93.68%, showing the high accuracy of the sequencing
([92]Table S3). The FPKM distribution violin diagram of the samples
showed a low variability in gene expression levels within each sample
and high overall expression levels ([93]Figure 2A). The PCA results
showed that the samples between the HAE group and the CK group were
well separated, representing significant differences between samples
from different treatments ([94]Figure 2B). The combined contribution
rate of PC1 and PC2 was 95.1%, reflecting strong parallelism within the
groups. Based on the differential analysis criteria of FoldChange > 1.2
and FDR < 0.05, a total of 2489 genes were identified as DEGs, with
1520 significantly up-regulated and 969 significantly down-regulated.
In the volcano plot, different expressions of genes were represented
using different colors ([95]Figure 2C). The clustering heat map of each
group differentiated is shown in [96]Figure 2D. Combined with the PCA,
significant differences in the expression patterns of genes were
observed in the BMECs between the HAE group and the CK group. The
enrichment analysis of all DEGs was conducted through GO and KEGG
enrichment analyses; the results are shown in [97]Figure S1.
Figure 2.
[98]Figure 2
[99]Open in a new tab
Transcriptome analysis of BMECs from the HAE group and the CK group.
(A) Violin plot for gene expression. The x-axis of the plot represents
different samples; the y-axis represents the logarithmic scale of FPKM
expression levels for the samples. (B) Principal component analysis
(PCA) diagram. The percentages indicate the contribution of each
principal component to the variance in the dataset. (C) Volcano plot of
DEGs. Genes expressed at higher levels are shown in red; genes
expressed at lower levels are shown in blue. (D) Clustering heat map of
DEGs. Hierarchical clustering is based on log[10] (FPKM + 1). (E) GO
enrichment analysis of DEGs. (F) KEGG enrichment analysis of DEGs.
The lactation process involves complex molecular systems and pathways,
including the secretion of lactation-related hormones and the
proliferation and specialization of acinar epithelial cells, along with
the synthesis and secretion of milk constituents. To understand how HAE
influences the molecular pathways related to lactation, a total of 125
DEGs associated with the lactation process in the CK group vs. the HAE
group is presented in [100]Table S4, and the GO and KEGG enrichment
analyses of these DEGs were conducted. The GO enrichment analysis of
DEGs related to lactation process is shown in [101]Figure 2E. These
DEGs were mainly enriched in the phosphate-containing compound
metabolic process (GO:0006796), phosphorus metabolic process
(GO:0006793), cellular lipid metabolic process (GO:0044255),
phosphotransferase activity, alcohol group as acceptors (GO:0016773),
and lipid metabolic process (GO:0006629). These pathways are crucial
for the metabolic activities and cellular processes necessary for
lactation, emphasizing the role of phosphorus and lipid metabolism in
milk production and secretion. The KEGG enrichment analysis of DEGs
related to lactation process is shown in [102]Figure 2F. These DEGs
were mainly enriched in the PI3K-Akt signaling pathway (ko04151),
growth hormone synthesis, secretion and action (ko04935), estrogen
signaling pathway (ko04915), EGFR tyrosine kinase inhibitor resistance
(ko01521), and ErbB signaling pathway (ko04012). Among the top 30
enriched pathways, the PI3K-Akt signaling pathway was found to be the
most significant pathway with the highest number of genes and is known
for its role in cell growth and survival, indicating its potential role
in the lactogenic effects of HAE.
3.4. Identification of the Compounds in HAE Based on UHPLC-Q-Exactive
Orbitrap-MS
UHPLC-Q-Exactive Orbitrap-MS was employed for a comprehensive
characterization of the compounds in HAE. The total ion current (TIC)
diagrams of the compounds analyzed using both ESI+ and ESI- modes are
shown in [103]Figure S2. As a result, 499 compounds were identified,
including mainly alkaloids (22), amino acids and derivatives (58),
esters and derivatives (21), fatty acids (43), flavonoids (75), lipids
(22), organic acids and derivatives (50), phenolics (78), pyridines and
derivatives (8), saccharides and alcohols (43), terpenes and steroids
(21), and others (58). The donut chart illustrated the proportional
representation of various compound categories within the total
composition ([104]Figure 3A). The results showed that flavonoids had
the highest relative content and occupied the largest proportion of the
analyzed compounds at 21.1%. The peak areas of all flavonoids were
further compared, and the top 20 flavonoids are shown in [105]Table 1.
Among them, HQ was identified as the flavonoid with the highest
relative content, significantly exceeding other flavonoids and
accounting for 42.66% of the total flavonoid content. HQ is a
polyethoxylated flavonoid, with its structure shown in [106]Figure 3B.
It has six methoxy groups (-OCH3) at positions 5, 6, 7, and 8 on the
benzopyran ring and positions 2′ and 4′ on the phenyl ring, which may
help define the chemical properties and biological activities of HAE.
Figure 3.
[107]Figure 3
[108]Open in a new tab
Results of UHPLC-Q-Exactive Orbitrap-MS analysis and network
pharmacology analysis of HAE. (A) The proportional representation of
various compound categories in HAE. (B) The structure of HQ. (C) The
Venn diagram of the intersection between HAE flavonoids and lactation.
(D) Target classification. (E) PPI network. Targets with larger nodes
in the network have higher degree values; the thickness of edges
represents interactions between targets. (F) PPI network clusters. GO
(G) and KRGG (H) enrichment analysis of the potential functional
protein modules after cluster analysis using the MCODE plugin. (I) ITP
network. The blue–green nodes are potential flavonoid components; the
yellow nodes are the potential functional protein modules; and the red
dots are the KEGG signaling pathway. Larger node sizes indicate higher
degree values. (J) The main targets of HQ. The thickness of edges
represents interactions between targets. (K) The Venn diagram of the
intersection between 125 lactation-related DEGs based on RNA-Seq and 30
potential core targets.
Table 1.
Composition and identification of top 20 flavonoids in HAE.
Compound Name Formula Molecular Weight CAS m/z Ionization Model Peak
Area
Hexamethylquercetagetin C[21]H[22]O[8] 402.4 1251-84-9 401.13 [M − H]−
421,194,790.80
4′,5,6,7,8-Pentahydroxy-3’-methoxyflavone C[16]H[12]O[8] 332.26
181020-34-8 333.07 [M + H]+ 64,114,119.42
Rutin C[27]H[30]O[16] 610.5 153-18-4 611.16 [M + H]+ 60,833,174.93
Myricetin 3-robinobioside C[27]H[30]O[17] 626.5 145544-43-0 627.15 [M +
H]+ 59,991,262.61
Licoisoflavone A C[20]H[18]O[6] 354.4 66056-19-7 353.11 [M − H]−
59,916,514.78
Myricetin 3-galactoside C[21]H[20]O[13] 480.4 15648-86-9 481.10 [M +
H]+ 35,915,744.05
Naringenin C[15]H[12]O[5] 272.25 480-41-1 271.06 [M − H]− 18,411,397.14
Quercetin C[15]H[10]O[7] 302.23 117-39-5 301.03 [M − H]− 15,911,669.73
Kaempferol C[15]H[10]O[6] 286.24 520-18-3 287.05 [M + H]+ 14,296,488.93
7-Hydroxy-2-methylisoflavone C[16]H[12]O[3] 252.26 2859-88-3 253.08 [M
+ H]+ 14,280,814.31
Petunidin 3-galactoside C[22]H[23]O[12+] 479.4 28500-02-9 479.12 [M +
H]+ 14,378,042.42
Daidzin C[21]H[20]O[9] 416.4 552-66-9 415.11 [M − H]− 7,576,634.70
Lutein C[40]H[56]O[2] 568.9 127-40-2 568.43 [M + H]+ 10,175,254.17
Malvidin 3-(6-acetylglucoside) C[25]H[27]O[13+] 535.5 101072-66-6
536.16 [M + H]+ 10,822,103.81
Orientin C[21]H[20]O[11] 448.4 28608-75-5 449.11 [M + H]+ 5,787,667.10
Multinoside A C[27]H[30]O[16] 610.5 59262-54-3 645.12 [M − H]−
6,037,243.24
Isorhamnetin C[16]H[12]O[7] 316.26 480-19-3 317.06 [M + H]+
4,581,085.32
Myricetin 3-arabinoside C[20]H[18]O[12] 450.3 132679-85-7 451.09 [M +
H]+ 4,635,990.00
Citroside A C[19]H[30]O[8] 386.4 120330-44-1 387.20 [M + H]+
3,243,535.37
4′,8-Dimethylgossypetin 3-glucoside C[23]H[24]O[13] 508.4 90456-57-8
509.13 [M + H]+ 3,126,823.92
[109]Open in a new tab
3.5. Network Pharmacology Combined with RNA-seq Revealed HAE
Flavonoid-Promoting Effects through Potential Core Targets
The SwissADME platform was used to screen the HAE flavonoid components
detected in the above section, resulting in a total of 23 potentially
active flavonoids. The targets for potential flavonoid components are
screened using the PharmMapper platform, yielding 737 targets.
Lactation-related targets were obtained through GeneCards and OMIM, and
996 lactation targets were generated after removing duplicates. The 737
targets of HAE flavonoids intersected with the 996 lactation targets,
resulting in 65 potential therapeutic targets ([110]Figure 3C). The
details of the 65 targets are listed in [111]Table S5. These targets
were further classified, with the highest proportion being metabolic
enzymes (18.64%) ([112]Figure 3D). These results indicate that the
metabolic enzymes play crucial roles in various biochemical pathways
involved in lactation, and the potential modulation of these enzymes by
HAE flavonoids may contribute to their therapeutic effects.
Furthermore, these 65 intersection targets were uploaded to the
STRING12.0 database to obtain the PPI network information. After hiding
the targets without relevant connection, a network containing 61 nodes
and 362 edges was constructed ([113]Figure S3), which was subsequently
reconstructed using the Cytoscape 3.7 software ([114]Figure 3E). Using
the MCODE plugin to further analyze the PPI network, a potential
functional protein module consisting of 30 notes and 206 edges was
obtained ([115]Figure 3F). Targets with larger nodes in the network
have higher degree values.
The GO and KEGG enrichment analyses of the intersection targets
([116]Figure S4A,B) and core targets ([117]Figure 3G,H) were conducted
using the Metascape platform. Detailed information on the top 30 KEGG
signaling pathways of the intersection of potential targets for HAE
flavonoids and lactation-related targets, as well as the potential core
targets, is in [118]Tables S6 and S7, respectively. The GO enrichment
analysis of the potential core targets is shown in [119]Figure 3G.
These targets were mainly enriched in response to hormone (GO:0009725),
carbohydrate metabolic process (GO:0005975), and glucose metabolic
process (GO:0006006). The results suggested that the potential core
targets identified in this study may play critical roles in
coordinating hormonal signaling and metabolic processes for successful
lactation. The KEGG enrichment analysis of the potential core targets
is shown in [120]Figure 3H. The results showed that, among the top ten
KEGG pathways, pathways closely related to the lactation process
include amino acid biosynthesis (hsa04510), the prolactin signaling
pathway (hsa00630), and the PI3K-Akt signaling pathway (hsa01210). The
enrichment of the amino acid biosynthesis pathway revealed the
importance of these core targets in regulating the synthesis of amino
acids, which are the building blocks of milk proteins. The enrichment
of the prolactin signaling pathway showed that these core targets could
have direct implications for the initiation and sustenance of
lactation. Additionally, the PI3K-Akt signaling pathway is a well-known
regulator of cell growth, proliferation, and survival, all of which are
important for mammary gland development and lactation. This pathway was
also identified as the top enriched pathway in the previous
transcriptome KEGG enrichment analysis. This consistent finding further
highlights the central importance of the PI3K-Akt pathway in modulating
the effects of HAE flavonoids on lactation-related processes.
Based on the KEGG analysis results of potential core targets, an
ingredient-target-pathway network (ITP) consisting of 30 core targets,
23 flavonoid components, and 20 pathways was constructed ([121]Figure
3I). Built-in tools in Cytoscape 3.7 software were employed to analyze
the topological parameters of the network, revealing the core
ingredients and core targets. The results showed that HQ, cichoriin,
paeonoside, jaceidin, catechin, kaempferol, and tangeritin were
predicted as the potential core flavonoids ([122]Table S8). Among them,
HQ had the highest degree value and closeness centrality, indicating
that HQ may be the core flavonoid component of HAE in promoting
lactation. The network of HQ is displayed in [123]Figure 3J. In
addition, STAT5A, PIK3CA, IGF1R, TP53, CCND1, BCL2, INS, AR, and DLD
were predicted as the potential core targets ([124]Table S9). The 30
potential core targets were further intersected with the 125
lactation-related DEGs previously obtained through RNA-seq. Five gene
symbols including BCL2, ESR1, FN1, PIK3CA, and PYGL were obtained
([125]Figure 3K), and their FoldChange is shown in [126]Figure S5.
Among them, BCL2, ESR1, FN1, and PYGL5 were significantly up-regulated,
indicating that their regulatory roles in diverse biological processes,
such as cell survival, hormone signaling, extracellular matrix
remodeling, and glucose metabolism, are crucial for the successful
establishment and maintenance of lactation.
3.6. Molecular Docking of HQ and Nine Core Targets
After the ITP network analysis, the key flavonoid component HQ and nine
potential core targets (STAT5A, PIK3CA, IGF1R, TP53, CCND1, BCL2, INS,
AR, and DLD) were obtained. A molecular docking study was performed on
them using AutoDockTools 1.5.6 software, and docking patterns were
visualized using PyMOL 2.6.0 software ([127]Figure 4). The results
showed that the binding energies of these nine groups of docking
complexes were −4.35, −6.43, −4.99, −3.95, −3.92, −3.72, −3.97, −6.23,
and −5.93 kcal/mol, respectively. Generally, binding energy with less
than −4.25, −5.0, or −7.0 kcal/mol is considered as a certain good or
strong binding activity between the ligand and the receptor,
respectively. The docking complex formed by PIK3CA and HQ had the
lowest binding energy, indicating the strongest affinity between them.
The results showed that the ligand HQ can interact with PIK3CA by
forming hydrogen bonds with residues Arg818A. The distance between the
hydrogen atom and the acceptor atom is 3.45 Å, and the distance between
the donor atom and the acceptor atom is 3.99 Å. The above results
indicated that residue Arg818A plays an important role in the binding
process of HQ and PIK3CA, and they also showed that the hydrogen
bonding network is the primary factor contributing to the stability of
this complex.
Figure 4.
[128]Figure 4
[129]Open in a new tab
3D schematic diagram of the molecular docking complex between HQ and 9
potential core targets. The sky-blue structures represent the targets.
Gray structures represent the target’s amino acid residues that bind to
HQ. Blue dashed lines show the hydrogen bonds formed between HQ and the
amino acid residues. Orange dashed lines show hydrophobic interactions.
Yellow dashed lines show π-cation interactions. The numbers next to the
interactions indicate their lengths in Å.
3.7. HQ Up-Regulated Lactation-Promoting Function in BMECs
The effects of the different concentrations of HQ (0–160 μM) on the
cell viability of the BMECs were assessed using the CCK-8 assay
([130]Figure 5A). The results indicated that all of the concentrations
of HQ were non-toxic to BMEC. The effects of the different
concentrations of HQ (0–80 μM) on the contents of milk proteins
(α-casein, β-casein, and whey protein), lactose, and milk fat were
investigated using the ELISA method. As shown in [131]Figure 5B–D, HQ
greatly increased the casein content in BMECs in a dose-dependent
manner. In detail, the contents of α-casein, β-casein, and whey protein
in the group treated with 80 μM HQ were 136.22, 82.33, and 4.56 μg/mL,
respectively, which were 1.42, 1.14, and 1.29 times that of the CK
group. In addition, the effects of HQ on the lactose and milk fat
levels in BMECs are shown in [132]Figure 5E,F. Our results indicate
that, contrary to the results for milk proteins, low concentrations of
HQ are more effective in stimulating the secretion of lactose and milk
fat in BMECs. In detail, after treatment with 20 μM HQ, both the
lactose and milk fat contents reached peak values of 306.85 μg/mL and
1443.85 pg/mL, respectively. The above results are consistent with the
results of the HAE treatment of BMECs.
Figure 5.
[133]Figure 5
[134]Open in a new tab
Effects of HQ treatment on lactation performance and transcriptional
profile of BMECs. (A) The effect of various concentrations of HQ on the
cell viability of BMECs. Data are mean ± SEM (n = 6). The contents of
α-casein (B), β-casein (C), whey protein (D), lactose (E), and milk fat
(F) of samples from the HQ group and the CK group. Data are mean ± SEM
(n = 3); * p < 0.05, ** p < 0.01. (G) PCA diagram. The percentages
indicate the contribution of each principal component to the variance
in the dataset. (H) Volcano plot of DEGs. Genes expressed at higher
levels are shown in red; genes expressed at lower levels are shown in
blue. (I) Clustering heat map of DEGs. Hierarchical clustering is based
on log[10] (FPKM + 1). (J) GO enrichment analysis of DEGs. (K) KEGG
enrichment analysis of DEGs.
3.8. Effect of HQ on the Lactation-Related Pathways via DEG Enrichment
Analysis
The transcriptome profiling was further used to investigate the
potential mechanisms of the lactation-promoting effect of HQ (80 μM) in
BMECs. The quality control and comparison results are shown in
[135]Tables S10 and S11, indicating high sequencing accuracy and
reliable results. The effect of HQ on the transcript profile is shown
in [136]Figure 5G–I and [137]Figure S6. Based on the differential
analysis criteria of FoldChange > 1.2 and FDR < 0.05, a total of 1707
genes were differentially expressed, including 1172 up-regulated and
535 down-regulated genes. To narrow down the scope of the study, a
total of 131 DEGs associated with the lactation process in the CK group
vs. the HQ group were screened out ([138]Table S12), and the GO and
KEGG enrichment analyses of these DEGs were conducted. The GO
enrichment analysis of DEGs related to the lactation process is shown
in [139]Figure 5J. These DEGs were mainly enriched in
phosphate-containing compound metabolic process (GO:0006796), response
to organic substance (GO:0010033), phosphorus metabolic process
(GO:0006793), cellular response to organic substance (GO:0071310), and
cellular lipid metabolic process (GO:0044255). It is shown that,
similar to HAE, HQ also mainly acted on the phosphorus metabolism and
lipid metabolism processes to promote the lactation performance of
cells. The up-regulation of the genes involved in phosphorus metabolism
and lipid metabolism may enhance energy production for milk synthesis
and alter milk fat synthesis and composition. The KEGG enrichment
analysis of the DEGs related to lactation process is shown in
[140]Figure 5K. These DEGs were mainly enriched in the PI3K-Akt
signaling pathway (ko04151), growth hormone synthesis, secretion and
action (ko04935), estrogen signaling pathway (ko04915), ErbB signaling
pathway (ko04012), and insulin signaling pathway (ko04910). Among these
metabolic pathways, the PI3K-Akt signaling pathway is still the
metabolic pathway with the largest number of enriched DEGs and the
highest significance, indicating that HQ may also exert
lactation-promoting activity through the PI3K-Akt signaling pathway.
The GO and KEGG enrichment results from the HQ-treated cells showed
significant overlap with those observed in the HAE-treated cells,
particularly in the metabolic and hormone-related signaling pathways.
This similarity suggested that HQ may replicate the signaling pathways
modulated by HAE in BMECs, thereby exerting a similar promotive effect
on lactation function.
3.9. Analysis of Common DEGs of HAE and HQ
In order to investigate the lactation-promoting mechanism of HQ and its
relationship with HAE, the expression changes of common DEGs in CK vs.
HAE and CK vs. HQ were investigated. As shown in [141]Figure 6A, the
Venn diagram revealed 1460 common DEGs between CK vs. HAE and CK vs.
HQ. From them, 125 DEGs were selectively screened based on
lactation-related information, and the expression levels of these
common DEGs were further analyzed using a correlation heat map
([142]Figure 6B). The results showed that the genes involved in milk
protein synthesis, including mTOR (ncbi_100139219), EIF4B
(ncbi_505850), INSR (ncbi_408017), PRKACA (ncbi_282322), PRKAR1B
(ncbi_505370), and PRKAR2A (ncbi_100139910), were up-regulated.
Additionally, the genes involved in lactose synthesis, involving GYS1
(ncbi_786335), PGM1 (ncbi_534402), PRKACA (ncbi_282322), and B4GALT1
(ncbi_281781), were up-regulated. Furthermore, an increase in the
expression of the genes related to milk fat synthesis was observed,
including GK (ncbi_505987) and PPARGC1B (ncbi_514750). The KEGG
enrichment analysis of these common DEGs in CK vs. HAE and CK vs. HQ
related to the lactation process was performed ([143]Figure 6C). The
results showed that 45 of these DEGs were enriched in the PI3K-Akt
signaling pathway (ko04151), 23 DEGs were enriched in the insulin
signaling pathway (ko04910), and 26 DEGs were enriched in focal
adhesion (ko04510). This finding further confirmed that the PI3K-Akt
signaling pathway is the most critical metabolic pathway for HAE and HQ
to exert their lactation-promoting effects, and the effects of HAE and
HQ on the PI3K-Akt signaling pathway are shown in [144]Figure 6D. The
results showed that 38 lactation-related DEGs were up-regulated and 7
lactation-related DEGs were down-regulated in the PI3K-Akt signaling
pathway.
Figure 6.
[145]Figure 6
[146]Figure 6
[147]Open in a new tab
Analysis and RT-qPCR validation of common DEGs in CK vs. HAE and CK vs.
HQ. (A) Venn diagram of common and unique DEGs among different
comparison groups. (B) Correlation heat map of common DEGs in CK vs.
HAE and CK vs. HQ related to lactation process. Redder squares indicate
higher expression and bluer squares indicate lower expression. (C) KEGG
enrichment of common DEGs in CK vs. HAE and CK vs. HQ related to
lactation process. The abscissa indicates the percentage of
lactation-related genes in the pathway to the total lactation-related
genes. The color of the bars represents the −log[10](Q value) of
enrichment. (D) Effect of HAE and HQ on PI3K-Akt signaling pathway. Red
means the DEGs are up-regulated, and green means down-regulated. Effect
of 400 μg/mL HAE (E) and 80 μM HQ (F) on PI3K-Akt pathway via RT-qPCR
assays. Data are mean ± SEM (n = 3); * p < 0.05, ** p < 0.01.
3.10. Effect of HAE and HQ on PI3K-Akt Pathway via RT-qPCR Assays
To confirm the gene expression patterns identified at the transcriptome
level, six key genes associated with the PI3K-Akt signaling pathway
were analyzed for RT-qPCR validation ([148]Figure 6E,F). RT-qPCR is a
highly sensitive technique that quantifies mRNA levels, providing a
reliable measure of gene expression, and the 2^−△△Ct method was used to
calculate the relative changes in gene expression. The results showed
that the mRNA expression levels of PI3K, Akt2, mTOR, JAK2, and eIF4B
were significantly up-regulated, while AMPK was down-regulated after
the HAE or HQ treatment (p < 0.05). The up-regulation of PI3K, Akt2,
mTOR, JAK2, and eIF4B suggested an enhanced activation of the PI3K-Akt
signaling pathway, which is known to play an important role in cell
growth, proliferation, and lactation. Conversely, the down-regulation
of AMPK, a gene associated with the energy regulation and inhibition of
anabolic processes, supported the shift towards promoting lactation.
The results confirmed that qPCR analysis was consistent with the
RNA-seq data, further validating the accuracy of the transcriptomic.
Additionally, these results revealed that both HAQ and HQ exhibited
similar trends in the modulation of key genes in the PI3K-Akt pathway.
4. Discussion
Recognized in the ancient traditional Chinese medicine books, H.
citrina has been historically employed to promote milk secretion in
lactating women [[149]22]. However, modern research has not provided
clear evidence to clarify this historical claim. In this study, the
lactation-promoting effects of H. citrina on BMECs and lactating rats
are verified. The results showed that HAE significantly (p < 0.05)
increased the synthesis of milk proteins, lactose, and fat in BMECs and
enhanced the weight gain of pups, as well as the mammary gland tissue
indices, uterine indices, and serum hormone levels (PRL, PRLR, and
E[2]) of lactating rats. Additionally, HAE was observed to stimulate
mammary gland development, accelerate the transformation of the lobular
acinar system, enhance acinar density and secretion, and reduce fibrous
connective and fatty tissues. It was revealed that PRL, PRLR, and E[2]
are essential in the development of the mammary gland, the initiation
of milk production, and the maintenance of milk secretion [[150]23].
During pregnancy, PRL directly or indirectly promotes the development
of milk-secreting lobuloalveolar by binding to PRLR or regulating the
systemic hormonal environment through the pituitary–ovarian axis
[[151]24]. Oakes et al. [[152]24] noted that PRL can induce ductal side
branching by regulating the production of ovarian progesterone. During
lactation, PRL modulates mammary gland development and milk production
by activating the JAK2-STAT5 signaling pathway [[153]25]. Upon binding
to PRLR on the cell membrane, PRL stimulates JAK2, which phosphorylates
the intracellular tyrosines of receptor complex after receptor
oligomerization [[154]26]. This progress creates docking sites for
STAT5. The phosphorylated STAT5A and STAT5B form homodimers, and
heterodimers then migrate to the cell nucleus in mammary epithelial
cells to initiate the transcription of casein genes, thus promoting
lactation. Zhou et al. [[155]27] demonstrated that PRL is capable of
regulating the expression and activity of the L-type amino acid
transporter 1 (LAT1) in mammary epithelial cells through the STAT5
pathway. This regulation enhanced the availability of amino acids and
the synthesis of milk protein in the mammary glands of dairy cows.
Estrogen, specifically E[2], the most potent form of mammalian
estrogen, is crucial for ductal development and mammary epithelial cell
proliferation. Arendt and Kuperwasser [[156]28] reported that E[2] can
drive the rapid growth of ducts into the mammary fat pad through its
receptor α (ERα). Furthermore, Błasiak and Molik [[157]29] found that
E[2] can indirectly prompt the pituitary gland to release PRL and to
increase the presence of PRLR in the mammary gland.
To systematically reveal the key components of the lactation-promoting
effect in H. citrina, water (the safest and most frequently used
food-grade solvent) was utilized to extract the functional components
in HAE. In this study, a total of 499 components were identified
through UHPLC-OE-MS analysis. The predominant constituents included
flavonoids, saccharides and alcohols, lipids, amino acids and
derivatives, and phenolics. Consistent with our findings, recent
research utilizing UPLC-MS/MS identified a total of 728 metabolites
within H. citrina, and flavonoids, lipids, phenolic acids, and amino
acids, and their derivatives, were found to be the main components
[[158]10]. Ma et al. [[159]9] determined the components of H. citrina
using UHPLC-Q-TOF-MS/MS and UHPLC-QQQ-MS/MS analysis and identified 132
components, encompassing flavonoids, phenylpropanoids, lipids,
alkaloids, and other types of compounds. In these compounds, flavonoids
represent a class of secondary metabolites widely present in nature.
Numerous studies have demonstrated that plant flavonoids contribute to
improving lactation performance [[160]30,[161]31]. In our analysis of
the flavonoid composition in H. citrina, HQ,
4′,5,6,7,8-pentahydroxy-3’-methoxyflavone, rutin, myricetin
3-robinobioside, licoisoflavone A, myricetin 3-galactoside, naringenin,
quercetin, and kaempferol were identified as the primary flavonoid
compounds. Among them, rutin, kaempferol, quercetin, and naringenin
have been well documented for their beneficial impacts on mammary
health and milk production enhancement [[162]17,[163]19,[164]32].
However, the lactogenic potential of HQ, the most abundant flavonoid
component in our study, has not been previously reported.
The data from the current study indicate that the cell proliferation
and synthesis of milk proteins, lactose, and fat in BMECs were
positively regulated with the treatment of HQ, indicating that HQ has a
good lactation-promoting effect and may be the potential material basis
for the lactation-promoting activity of HAE. Transcriptomic coupled
with RT-qPCR further revealed that DEGs in both the HAE and HQ groups
were mainly enriched in the PI3K-Akt signaling pathway, indicating that
HAE and HQ primarily exert their lactogenic effects through the
PI3K-Akt signaling pathway. It is noteworthy that, although we have
demonstrated that HQ can promote lactation by regulating the same
metabolic pathways as HAE, the synergistic effects between different
compounds should not be ignored. For instance, Shalev et al. [[165]33]
found that extracts of Pistacia lentiscus (lentisk) were more effective
in enhancing mitochondrial productivity and activity and regulating the
secretion of milk components compared to isolated active components
like myricetin or gallic acid, indicating that different active
components have additive or synergistic effects on the lactation
performance of mammary epithelial cells.
To clarify the underlying mechanisms of the lactation-promoting effect,
common DEGs related to lactation between CK and HAE and CK and HQ were
screened, and the functional enrichment analysis of these DEGs was
performed. The results showed that these DEGs were indeed mainly
enriched in the PI3K-Akt signaling pathway, and the mRNA expression of
genes in the PI3K-Akt signaling pathway, including EGFR, FGFR3, INSR,
IRS1, PI3K, GNB1, GNG4, Akt2, mTOR, eIF4B, MYC, PRKCA, and PRKAR1B,
were significantly up-regulated in comparison to the CK group in both
the HAE and HQ-treated groups (p < 0.05).
The proteins in milk mainly include casein, whey protein, various
enzymes and endogenous peptides, etc., which provide basic nutritional
support for the growth and development of infants [[166]34]. In the
PI3K-Akt signaling pathway, signaling molecules bind to corresponding
receptors such as the epidermal growth factor receptor (EGFR),
fibroblast growth factor receptor 3 (FGFR3), and insulin receptor
(INSR) to activate genes encoding downstream factors, namely, insulin
receptor substrate-1 (IRS1), G protein subunit beta 1 (GNB1), and G
protein subunit gamma 4 (GNG4) [[167]35]. Then, activated
phosphoinositide 3-kinase (PI3K) induces the conversion of
phosphatidylinositol (4,5)-bisphosphate (PIP2) into
phosphatidylinositol (3,4,5)-trisphosphate (PIP3) through a cascade
reaction, further activating protein kinase B (Akt) [[168]36]. This
resulted in the up-regulation of mTOR and the subsequent induction of
eukaryotic initiation factor 4B (eIF4B) expression, thereby enhancing
translation initiation and promoting protein synthesis. Previous
research has reported that mTOR contributed to regulating the mRNA
levels for CSN1S1, CSN2 and CSN3, encoding αs1-casein, β-casein, and
κ-casein, respectively, in BMECs via 4E binding protein (4EBP1) and
ribosomal protein S6 kinase 1 (S6K1) [[169]37,[170]38].
Additionally, research indicated that 55–70% of glucose in the mammary
gland is utilized for lactose synthesis, and a portion of glucose
serves as a substrate to power the synthesis of lactose [[171]39]. In
this study, HAE and HQ treatment significantly increased the expression
of PRKCA, GYS, PGM1, and B4GALT1. In the PI3K-Akt signaling pathway,
up-regulated PI3K activates downstream effectors such as
phosphoinositide-dependent kinase-1 (PDPK1) and Akt through a cascade
reaction. Activated PDK1 further phosphorylates protein kinase C α
(PRKCA), enhances glucose uptake and intracellular vesicle transport,
and provides raw materials and energy for lactose synthesis [[172]40].
At the same time, the activation of Akt increases the activity of
glycogen synthase (GYS) and promotes glycogen synthesis. The
synthesized glycogen then participates in galactose metabolism and
lactose synthesis processes, respectively, under the action of
up-regulated genes PGM1 and B4GALT1 in other pathways. Similarly,
Sevrin et al. [[173]41] found that dietary fenugreek supplementation
can promote the synthesis of milk components by up-regulating the
expression of genes related to the uptake of glucose (GLUT1),
metabolism of galactose (PGM1), and synthesis of lactose (B4GALT1).
Milk fat synthesis includes fatty acid de novo synthesis, uptake,
activation, intracellular trafficking, elongation, desaturation,
triacylglycerol assembly, and lipid droplet formation within the
mammary gland epithelial cells [[174]37]. This study revealed that the
mRNA expression of PI3K, mTOR in the PI3K-Akt signaling pathway, and GK
in the insulin signaling pathway were significantly up-regulated. The
enhanced expression of PI3K and mTOR plays a key role in promoting
fatty acid synthesis and subsequent lipid droplet formation in mammary
gland epithelial cells. This up-regulation facilitates anabolic
processes, including the synthesis of triacylglycerols, the primary
constituents of milk fat. Wang et al. [[175]42] also found that
acylated ghrelin promotes milk fat synthesis in BMECs through the
PI3K-mTOR signaling pathway. Additionally, the up-regulation of GK
within the insulin signaling pathway further promotes its conversion to
glycerol-3-phosphate, a backbone for triacylglycerol formation
[[176]43]. Taken together, we speculate that HAE and HQ could improve
lactogenic activity by enhancing milk protein synthesis, regulating
glucose uptake and galactose metabolism, and promoting fatty acid
synthesis ([177]Figure 7).
Figure 7.
[178]Figure 7
[179]Open in a new tab
Proposed mechanism by which HAE improves lactation. The arrows indicate
the direction of signal transduction or molecular interactions. Solid
arrows represent activation or stimulation of downstream molecules or
pathways. Dashed lines with a bar at the end indicate inhibition or
suppression of downstream targets.
5. Conclusions
In conclusion, our study provides systematic evidence supporting the
lactation-promoting effect of the flavonoid compounds in HAE in
lactating rats and BMECs. Network pharmacology predicted that HQ,
cichoriin, paeonoside, jaceidin, and catechin were possible lactogenic
active components, and STAT5A, PIK3CA, IGF1R, TP53, and CCND1 were
potential core targets. HQ was identified for the first time as the
flavonoid with the highest concentration in HAE. RNA-seq studies
further revealed the importance of the PI3K-Akt signaling pathway.
Cell-based experiments combined with qRT-PCR verified the potential
pathways and its molecular targets. The analysis of common DEGs in CK
vs. HAE and CK vs. HQ indicated that both HAE and HQ enhanced
lactogenic activity mainly through the PI3K-Akt signaling pathway by
improving milk protein synthesis, regulating glucose uptake and
galactose metabolism, and promoting fatty acid synthesis. However, the
lactation-promoting potential of HQ was only evaluated at the cellular
level in this study. Further validation in animal models is necessary
to confirm its efficacy and safety in a more complex biological system.
Additionally, more comprehensive and systematic studies such as
multi-omics analysis, deep machine learning, and single-cell sequencing
to verify its biological effects and underlying mechanisms should be
needed in the future. These results provide scientific evidence for HQ
as a functional food factor in H. citrina that promotes lactation.
Acknowledgments