1. Introduction
Oxygen plays a vital role in regulating mammalian cells. Oxygen-availability-dependent alterations in cellular metabolism have profound functionality regulation effects in many tissues/organs, such as fetal development, dysfunction of the mucosal surface of the gastrointestinal tract, contractile activity maintenance of skeletal muscle, and blood vessel integrity. The adaptation or dysfunction of metabolic tissues in response to oxygen alteration results in metabolic pattern changes, subcellular structure switch, and cellular differentiation/proliferation [
1]. The control of the cellular response to oxygen alteration involves a large group of specific genes, especially those regulated by
HIF (hypoxia-inducible factor). HIF-1 is a crucial oxygen-sensing transcription factor regulator, consisting of HIF-1α and -1β subunits. In plentiful oxygen, HIF-1α is hydroxylated by prolyl hydroxylase domains (PHDs), and is then recognized and ubiquitinated by a ubiquitin ligase complex (pVHL), leading to its degradation via the proteasome. When the oxygen supply to cells is inadequate, HIF-1α is not hydroxylated due to decreased PHD activity, leading to HIF-1α accumulation and stabilization to form a functional transcription factor with HIF-1β. It then binds to the hypoxia response elements (HREs) in gene promoters, regulating the expression of the downstream genes [
2]. Clarifying how cells respond to oxygen changes in the microenvironment is the premise for understanding the aforementioned biological process.
There is a growing number of studies concerning hypoxia in the mammary glands of mammals. Studies have shown that hypoxia in the mid-pregnant mammary gland can increase the protein expression of HIF-1 and promote GLUT1 expression in mice [
3]. Increased oxygen consumption from fast-proliferating cells leads to hypoxia in breast cancer [
4]. However, these studies were either concerned with pathological breast changes or potential implications for mammary development. Moreover, the milk synthesis and secretion process consume large amounts of oxygen. Some studies have found that hypoxia occurs during the lactation period in the mammary glands. Bovine mammary glands spontaneously develop chronic hypoxia to accommodate lactation and high metabolic load [
5]. Mammary oxygen uptake is significantly higher in early lactation than in late pregnancy, increasing steadily over this period in dairy goats [
6]. In addition, a positive correlation between milk yield and oxygen uptake has been identified in several observations [
7,
8]. A tissue biopsy study showed higher mRNA expression of HIF-1α during early and late lactation than other stages throughout the lactation period [
9], suggesting a potential role of hypoxia in interplaying mammary metabolism. However, the effect of hypoxia on lactation in the mammary gland and its specific mechanisms have not yet been revealed.
The mammary gland is a complex organ composed of several cell types: epithelial cells, adipocytes, perivascular cells, immune cells, and fibroblasts. Mammary epithelial cells (MECs), which proliferate and differentiate to form alveolus, are significant in fulfilling lactation functions [
10]. Studies have demonstrated that milk secretion depends on the amount of MECs in the mammary gland, and that MEC proliferation is an essential determinant of mammalian lactation capacity [
11]. The bovine primary MECs (bMECs) of dairy cows are an ideal cell model for investigating how hypoxia affects proliferation in milk-secreting cells. Moreover, for this study, it was necessary to set up different oxygen concentration gradients to mimic the fluctuating in vivo hypoxic microenvironment. Thus, the study’s objective was to clarify the effect of hypoxia and its underlying mechanisms on mammary cell proliferation under various oxygen concentrations. Outcomes from the current study can be used to enhance and maintain better lactation performance.
2. Materials and Methods
2.1. Isolation of Primary Bovine Mammary Epithelial Cells and Cell Culture
Mammary tissues of Holstein cows were taken from an abattoir (Wuxi, China) which had already obtained permission for sampling. The bMECs were isolated as described below. The fresh tissues were rinsed with 0.3% bromo-geramine and D-Hank’s solution with 100 mg/mL gentamicin and 1000 IU/mL penicillin–streptomycin successively. The tissue was diced into small pieces. The cut tissues were digested with 0.25% trypsin at 37 °C for 30 min, and then the supernatant was removed. Subsequently, 5% collagenase solution, at final concentrations of 130 IU/mL type I and 138.5 IU/mL type II, was added, and digestion continued for 3–5 h at 37 °C. The cell suspension was filtered, and cells were harvested following centrifugation at 1000 rpm for 5 min. Cells were first resuspended in D-Hank’s solution, then centrifuged a second time, then resuspended in medium and cultured for 24 h in the presence of 5% CO2 at 37 °C. Cells were seeded below a density of 0.8 × 104 cells per well in 96-well plates before hypoxic treatment. Finally, cells were cultured under various oxygen concentrations (1, 6, 11, 16, and 21% O2) for 24 h, and each treatment included five replicates.
2.2. Cell Proliferation Assay
A colony formation assay was used to measure cell proliferation after 24 h of culture under different oxygen concentrations. After 24 h of cell culture, cells were inoculated in a 3.5 cm petri dish with 200 cells per dish. The cells were dispersed uniformly in a petri dish and incubated at 37 °C, 5% CO2, and saturated humidity for about 14 days until visible clones appeared. Then, cells were washed with phosphate buffered solution (PBS) twice and fixed with 4% paraformaldehyde (Shanghai Runjie Chemical Reagent Co., Ltd., Shanghai, China) for 15 min, and the fixing solution was removed. An appropriate amount of crystal violet solution (CAT No. C0003, Shanghai Biyuntian Biotechnology Co., Ltd., Shanghai, China) was added for 10 min, and then slowly washed away with running water. The petri dish was inverted to obtain the image and count the clones.
Cell viability was also assessed at 0, 6, 12, 18, and 24 h of cell culture under different oxygen levels by cell counting kit-8 (CCK8) (C0037, Biyuntian Biotechnology Co., Ltd., Shanghai, China). The cells in 96-well plates were added to the CCK-8 solution (20 mL), then incubated for an additional 3 h under the original culture conditions. The 450 nm optical densities of the plates were detected using a microplate reader.
2.3. The Adenosine Triphosphate (ATP) Level Measurement
The intracellular ATP levels were measured using the ATP Detection Kit (BC0305, Solarbio Science & Technology Co., Ltd, Beijing, China). The specific determination method followed the manufacturer’s instructions.
2.4. The Extracellular Oxygen Consumption Rates (OCR) Measurement
The extracellular OCR was detected using an Extracellular Oxygen Consumption Assay kit (ab197242, Abcam Inc., Cambridge, MA, USA). Cells to be tested were seeded in 96-well plates. The cells were washed with PBS, and then 150 μL of fresh medium was added. The 10 μL extracellular O2 consumption reagent was added and mixed thoroughly. Then, 100 μL of high-sensitivity mineral oil was added to each well to seal it, and the cell plate was used for fluorescence detection to analyze the real-time kinetics of OCR with the ratio EX (excitation wavelength)/EM (emission wavelength) = 380/650 nm. The rate of signal for each sample was calculated to obtain the OCR.
2.5. Electron Microscopy
The original culture solution was discarded after 24 h, and the cells were fixed using paraformaldehyde for 2–4 h at 4 °C. The cells were pelleted by means of low-speed centrifugation, encapsulated with 1% agarose, and then washed thrice for 15 min with phosphate-buffered saline (PBS). Under different concentrations of alcohol and acetone, the cell samples were sequentially dehydrated. After being dehydrated, the cells were soaked in a mixture of Spurr resin and absolute acetone at ratios of 1:1 and 3:1 for 1 h and 3 h, respectively, and subsequently embedded with Spurr resin alone overnight. The embedded sample was heated to 70 °C overnight; then, 70–90 nm sections were obtained using an ultramicrotome (Leica, Wetzlar, Hesse, Germany, EM UC7). Lead citrate and uranyl acetate in 50% ethanol were used to stain the ultrathin sections for examination under a HITACHI H7650 transmissive electron microscope (TEM).
2.6. Mitochondrial Mass Analysis
MitoTracker Green (Biyuntian Biotechnology Co., Ltd., Shanghai, China) was diluted to a final concentration of 20~200 nM (1 mM stock dissolved in DMSO). The pre-warmed solution at 37 °C was added to the bMEC samples. After 15–45 min of co-incubation, the fresh culture solution was replaced at room temperature, and the fluorescence intensity of the cells was observed via fluorescence microscopy (OLYMPUS, Tokyo, Japan). The fluorescence intensity was calculated using ImageJ software version 2.0.0.
2.7. ELISA
The superoxide dismutase (SOD; #A001-1-2), glutathione peroxidase (GSH-Px; #A005-1-2), malondialdehyde (MDA; #A003-1-2), total nitric oxide synthase (T-NOS; # A014-2-1), and total antioxidant capacity (T-AOC; #A015-3-1) were detected using enzyme-linked immunosorbent assay (ELISA) kits. The specific determination methods were conducted according to the manufacturer’s instructions (Nanjing Jiancheng Bioengineering Institute, Nanjing, China).
2.8. Flow Cytometric Analysis
The fluorescent probe Dichlorodihydrofluorescein diacetate assay (DCFH-DA) (Solarbio Science & Technology Co., Ltd, Beijing, China) was used to monitor the production of intracellular reactive oxygen species (ROS). ROS in cells oxidized fluorescent DCFH to produce fluorescent DCF, which could be detected. Cells with different oxygen levels were incubated in DCFH-DA (10 μM) (37 °C, 20 min) and washed in PBS. And the intensity of the DCF signal was detected to measure the ROS levels.
2.9. RNA Preparation, Illumina Sequencing, and RNA-Seq Analysis
Total RNA from frozen pbMECs was extracted under different oxygen levels to construct mRNA libraries for five groups, with five replicates per group. A total of 25 samples were sequenced via the Illumina HiSeqTM 2500 sequencing platform at Novogene Biotechnology Company (Tianjin, China). The primary sequencing data were subjected to quality control, and the cutadapt procedure included three steps, as shown below: (1) reads containing adaptors were removed; (2) reads less than 75 bp long after trim removal were removed; and (3) reads at the 5′ or 3′ ends lower than 20 bases, as well as the reads containing more than 5% of nitrogen, were removed. After filtering, clean data were aligned to the cow reference genome. The data were standardized with the fragments per kilobase of transcript per million mapped reads (FPKM) method, and the formula for the FPKM values was as follows: . Furthermore, FPKM values were used in the gene expression analysis. The raw data were uploaded to the NCBI database.
Principal component analysis (PCA) was implemented in R version 4.2.0 using the FactoMineR and factoextra packages. Differentially expressed genes (DEGs) were calculated and analyzed using the R package edgeR. A volcano plot of DEGs was rendered using the ggthemes and ggpubr R packages, with a false discovery rate (FDR) < 0.05 and |log2fold change| > 1 as a filter criterion. A bioinformatics and evolutionary genomics web tool was used to generate a Venn diagram. A soft-clustering analysis was performed with the R package Mfuzz based on the fuzzy c-means algorithm. The converted Entrez Gene IDs were obtained, then assigned to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using the package org.Bt.eg.db. The bubble plots of the top 20 KEGG enrichment pathways were drawn with the ggplot2 package. Heatmaps of DEGs from the key signaling pathways were generated with the R package pheatmap. The protein–protein interaction (PPI) analyses were carried out using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) web (version 11.5;
https://string-db.org/, accessed on 5 February 2023), and the networks were generated using Cytoscape software (version 3.9.1) to screen the key genes.
2.10. Real-Time Quantitative Polymerase Chain Reaction (qPCR)
The mRNA expression levels of five core genes, NGFR, CSF1, KDR, IL1R1, and PPP2R2B, from RNA-seq analysis were detected using the qPCR method. Total RNA was extracted using Trizol lysate, with reference to the TIANGEN Reverse Transcription kit (TIANGEN Biotech Co. Ltd., Beijing, China). The RNA concentration and purity were measured using a NanoDrop2000 spectrophotometer (NanoDrop2000, Thermo Fisher Scientific, Waltham, MA, USA), and the ratios of A260/A280 and A260/A230 were used for evaluation. Subsequently, qPCR was conducted using AceQ qPCR SYBR Green Master Mix (Vayzme, Nanjing, China). The primer sequences are provided in
Table S8. Relative quantification of mRNA levels was based on the reference gene β-actin. Quantitative results of mRNA expression were calculated using the delta-delta Ct method (2
−ΔΔCt) [
12]. Five biological replicates and three technical replicates were detected.
2.11. Western Blot Analysis
HIF-1α, dynamin-related protein 1 (DRP1), and optin atrophy protein 1 (OPA1) expression were detected to analyze the hypoxic response and mitochondrial mass. The phosphorylation of ERK and JNK from the MAPK signaling pathway were determined. The bMECs were lysed by radioimmunoprecipitation assay (RIPA) lysates, and then the supernates were harvested by centrifugation at 12,000 rpm for 10 min. According to the instruction, a bicinchoninic acid (BCA) kit (Beyotime Institute of Biotechnology, Shanghai, China) was utilized to access the protein concentration. The supernatant was mixed with the appropriate amount of 5X sodium dodecyl sulfate (SDS) loading buffer, then heated in a boiling water bath for 5 min. After preparing 10% separation adhesive and 5% concentration adhesive, the sample was added to each well in an electrophoresis tank for sample loading and then transferred onto polyvinylidene fluoride (PVDF) membranes. After washing three times (5 min/wash) with Tris-buffered saline and Tween 20 (TBST), incubation of the membranes was performed with the primary antibody overnight at 4 °C. After the incubation, corresponding secondary antibodies were then added and incubated for 1 h, followed by three additional rinses three times at 5 min intervals. Finally, target protein expression was detected using electrochemiluminescence (ECL) luminous fluid, and bands were visualized using Quantity One software (version 4.6.2). Blot bands were analyzed using ImageJ software. The following primary antibodies were used: anti-HIF-1α (#AF1009, Affinity Biosciences, Cincinnati, OH, USA), anti-DRP1 (#HA500487, HUABIO Co., Ltd, Hangzhou, China), anti-OPA1 (#ET1705-9, HUABIO Co., Ltd, Hangzhou, China), anti-ERK1/2 (#4695S, Cell Signaling Technology [CST], Danvers, MA, USA), anti-phospho-ERK1/2 (#9101s, Cell Signaling Technology [CST], Danvers, MA, USA), anti-JNK1/2 (#9252s, Cell Signaling Technology [CST], Danvers, MA, USA), anti-phospho-JNK1/2/3 (#AF3318, Affinity Biosciences, Cincinnati, OH, USA), and anti-GAPDH (#60004-1-Ig, Proteintech, Inc., Wuhan, China). The secondary antibodies (#A0208 and #A0216) were purchased from Shanghai Biyuntian Biotechnology Co., Ltd., Shanghai, China.
2.12. Statistical Analysis
Statistical analyses were performed using GraphPad Prism version 8.4.0. The unpaired t test and one-way analysis of variance (one-way ANOVA) test compared two and multiple groups, respectively. Origin Pro 2017 software (OriginLab, Northampton, MA, USA) was used for the linear regression analyses and curve plotting. p < 0.05 was considered a statistically significant difference, and p < 0.01 indicated an extremely significant difference.
4. Discussion
The proliferation of MECs plays a vital role in maintaining lactation persistency in dairy cows [
13]. Although previous research has suggested that oxygen-responsive genes in the mammary glands of cows at different stages of lactation are altered [
9], the role of oxygen in lactation persistency has not been defined. For the first time, we investigated the proliferation traits of bMECs at various degrees of oxygen availability. By learning about the proliferation traits, oxygen utilization, oxidative stress index, and transcriptomic profiles and validation of relevant key genes, we provided the key proliferative-regulatory molecules responding to oxygen deficiency. The outcomes of the present study may contribute to regulating lactation persistency via mediating mammary proliferation.
A previous study revealed that stability and accumulation of HIF-1α protein increased in an oxygen-concentration-dependent manner in cells [
14]. Some studies have also demonstrated pathologic hypoxia-induced proliferation inhibition of various types of cells, including hematopoietic stem cells, embryonic fibroblasts, and lymphocytes [
15,
16]. In the current study, when the oxygen availability decreased from 21% to 1%, the protein expression of HIF-1α increased gradually, suggesting a vital role of HIF-1α in responding to mammary oxygen deficiency in the mammary gland. Upon the appearance of environmental hypoxia, reduced aerobic respiration and the enhancement of anaerobic respiration can lead to a decrease in cellular ATP generation and oxygen consumption [
2], which is consistent with our study. In addition, HIF-1α can also inhibit the activity of key enzymes in cellular energy metabolism by directly regulating the expression of HIF-dependent genes, which further leads to cell energy deficiency [
17]. Following the gradually altered expression of HIF-1α, we observed a time- and dose-dependent proliferation inhibition due to oxygen deficiency, suggesting the occurrence of proliferation inhibition by hypoxia via different metabolic routes, such as inflammatory cytokine secretion and oxidative damage induction [
18]. This finding indicates that the hypoxic environment was adverse to the periodic renewal of mammary epithelial cells, which can have a potential negative impact on the maintenance of lactation function. Furthermore, we evaluated redox status alteration under different levels of oxygen availability. The gradual increase in ROS and MDA and the reduction in antioxidant enzymes (SOD, GSH-Px, T-AOC, and T-NOS) following gradient hypoxia were associated with cellular proliferation activity. Many studies have stated that HIF-1α and ROS from mitochondrial sources regulate each other positively. The HIF-1α can induce ROS generation, predominantly depending upon several oxygen-dependent enzymes, including nicotinamide adenine dinucleotide phosphate (NADPH) oxidase, cytochrome c oxidase, and uncoupled endothelial nitric oxide synthase (eNOS) [
19,
20], and ROS production inactivates PHD2 and stabilizes HIF-1α [
21]. The oxidative stress was also associated with imbalanced mitochondrial fusion–fission, modulating the gene expression of DRP1 and OPA1 [
22] and causing mitophagy [
23]. This is consistent with our study in that the excessive generation of ROS could result in a decline in cell function and cause progressive cell damage [
24,
25]. Moreover, oxidative stress was connected with inhibiting cell proliferation, and hydrogen peroxide (H
2O
2) treatment was able to suppress cell proliferation [
26,
27]. This evidence suggests the occurrence of hypoxia-induced proliferation inhibition of the mammary gland via impairing its antioxidant system.
The DEGs of the MAPK and Hippo signaling pathways were repressed under 16% oxygen concentrations and lower, compared with 21%, which was the primary cause for the cell proliferation phenotype repression under the four hypoxia group. We found that decreased PPP2R2B of the Hippo signaling pathway was highlighted in the PPI network and associated with the other genes from the p53 signaling pathway under 16% and 11%. A previous study demonstrated that PPP2R2B regulates the nuclear localization and stability of YAP/TAZ [
28], two core components of the kinase cascade, accumulating and entering the nucleus to regulate the gene expressions involved in cell proliferation [
28,
29]. The post-translational modifications of the p53 protein were up-regulated under obvious levels of oxidative stress [
30], and activated p53 signaling further promoted the activity of ROS-generating enzymes, inhibiting the promoter expression of manganese superoxide dismutase (MnSOD) [
31,
32]. Thus, the activated p53 signaling pathway was pivotal in coordinating oxidative stress to suppress cell proliferation through genetic interactions with PPP2R2B from the Hippo signaling pathway at 16% and 11% oxygen. The interaction between the PI3K-Akt and HIF-1 signaling pathways and the MAPK signaling pathway at 6% and 1% concentrations suggested that the altered oxygen availability changed the cellular proliferation through a tertiary kinase cascade-mediated mechanism [
33]. The three-tiered kinase cascade has already been well established; that is, the signaling molecules preferentially activate Ras and then phosphorylate MAP3K (Raf), which subsequently activates MAP2K (MEK) and eventually activates MAPKs (Erk1/2) [
34,
35]. We confirmed the molecular changes in these pathways through RNA-seq and q-PCR approaches, including KDR, CSF1, and NGFR from the MAPK signaling pathway, which is consistent with their previous reported function in cellular proliferation [
33]. The ERK1/2 and JNK1/2/3 subfamilies are crucial components of MAPK cascade, and their decline in phosphorylation further clarified the inhibition of the MAPK pathway under hypoxia. According to the findings of this study, genes from the PI3K-Akt signaling pathway were up-regulated under 6%, and the pathway has been shown to be allied with oxidative stress; that is, ROS can directly activate PI3K in cells [
36,
37]. Moreover, in the gene network generated under a 6% oxygen level, KDR and CSF1 were low-expressed molecules playing a key role in the MAPK signaling pathway, interacting with HIF-1 signaling under 1% and resulting in the oxidative stress of mammary gland and declined mitochondrial function [
21]. Accordingly, the results of the current analysis clarify that cell proliferation was inhibited under four different levels of hypoxia due to the inhibition of the core pathways involved in cell proliferation, i.e., the Hippo and MAPK signaling pathways, which were primarily regulated by activated pathways and genes related to oxidative stress from oxygen concentrations of 16–1%.