Methionine has been identified as one of the most limiting amino acids for milk protein synthesis (Hanigan et al., Reference Hanigan, Crompton, Bequette, Mills and France2002). The addition of methionine to cultured bovine mammary epithelial cells significantly increases β-CASEIN expression (Duan et al., Reference Duan, Lin, Lv, Yang, Jiao and Hou2017). Amino acids not only serve as substrates for milk protein synthesis but also function as signaling molecules that regulate the process. Evidence from work with both bovine mammary epithelial cells and lactating cows demonstrated that amino acid availability may modulate protein translation through the mammalian target of rapamycin (mTOR) signaling pathway (Appuhamy et al., Reference Appuhamy, Bell, Nayananjalie, Escobar and Hanigan2011). Although methionine is a potent stimulator of protein synthesis in the mammary gland, the relationship between methionine supplementation and gene expression related to milk protein synthesis is not well understood.
Gene expression profiles offer new opportunities to elucidate the underlying mechanisms of lactation traits in dairy cows. Several studies of the bovine mammary gland transcriptome by RNA sequencing (RNA-seq) have been reported, and a number of differentially expressed genes (DEGs) and signaling pathways that play regulatory roles during lactation have been identified (Lin et al., Reference Lin, Lv, Jiang, Zhou, Song and Hou2019). However, few studies have been done in a cell model to assess gene expression changes related to milk protein synthesis induced by individual amino acids. It is straightforward to stimulate cells in vitro by the addition of an individual amino acid in the medium. Although a mammary epithelial cell model of milk protein synthesis does not replicate in vivo lactation, its use for gene expression analysis eliminates some of the interference from other cell types. Such a model is thus essential for identifying candidate genes that contribute to milk component synthesis in bovine mammary gland.
Therefore, we established a cell model by stimulating cultured bovine mammary epithelial cells with methionine to produce higher levels of milk protein. RNA sequencing was used to examine the genome-wide gene expression profiles between mammary epithelial cells treated with methionine and untreated cells. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) tools were used to analyze functional enrichment. This study provides valuable insights into the physiological and metabolic adaptations in cells treated with methionine. Understanding the regulation of this transition is essential for effective intervention in lactation process.
Materials and methods
All experimental procedures were approved by the Northeast Agricultural University Animal Care and Use Committee (Harbin, China). Primary mammary epithelial cells were isolated from lactating bovine mammary tissue and cultured in Dulbecco's modified Eagle's medium : Nutrient Mixture F-12 (DMEM/F12, Life Technologies, Carlsbad, CA) containing 10% fetal bovine serum (BI Biological Industries, Kibbutz Beit-Haemek, Israel), 100 U/ml penicillin, 100 μg/ml streptomycin, and lactating hormones (5 μg/ml insulin, 1 μg/ml prolactin, and 1 μg/ml hydrocortisone; Sigma-Aldrich, St Louis, MO) (Duan et al., Reference Duan, Lin, Lv, Yang, Jiao and Hou2017). CYTOKERATIN 18 expression was detected by immunofluorescence (detailed procedures are described in the online Supplementary File). To establish a cell model with a high capacity for milk protein synthesis, mammary epithelial cells were seeded in 6-well plates at a density of 2 × 105 cells/well. When cells grew to ~90% confluence, methionine was added to the medium at a concentration of 0.6 mM (Duan et al., Reference Duan, Lin, Lv, Yang, Jiao and Hou2017). After 24 h of treatment, cells were collected for the detection of β-CASEIN expression by western blot analysis (detailed procedures are described in the online Supplementary File). Cells untreated with methionine were used as the control.
For RNA-seq analysis, total RNA was isolated from three methionine-stimulated samples and three control samples using a Magen HiPure Total RNA Mini kit (Magen, Guangzhou, China). Concentrations and qualities of RNA samples were measured using NanoDrop 2000 (Thermo Scientific, Wilmington, DE) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA). All samples used in this study had an RNA integrity number >8. An RNA-seq transcriptome library was prepared for each sample using 5 μg of total RNA using the TruSeqTM RNA sample preparation kit from Illumina (San Diego, CA). mRNA was isolated by oligo(dT) beads and then fragmented by fragmentation buffer. The SuperScript double-stranded cDNA synthesis kit (Invitrogen, Carlsbad, CA) was used to synthesize cDNA with random hexamer primers (Illumina). The cDNA was subjected to end repair, phosphorylation, and ‘A’ base addition. After 15 cycles of PCR, libraries were size-selected for cDNA target fragments of 200–300 bp on 2% low-range ultra agarose. Then the paired-end RNA-seq libraries were quantified by TBS380 (American Instrument Exchange, Inc., Haverhill, MA) and were sequenced using the Illumina HiSeq 4000 (2 × 150 bp read length).
According to the fragments per kilobase of exon per million mapped reads method, the expression level of each gene was calculated. RNA-seq by Expectation-Maximization was used to quantify gene abundances, and empirical analysis of digital gene expression in R (EdgeR) was used for differential expression analysis. The DEGs between methionine-stimulated and control samples were analyzed by Goatools (https://github.com/tanghaibao/Goatools) and KEGG orthology-based annotation system (KOBAS, http://kobas.cbi.pku.edu.cn/home.do) to identify the GO terms and biological pathways in which DEGs were significantly enriched at Bonferroni-corrected P value ≤0.05 compared with the whole transcriptome background.
Six upregulated DEGs (MCOLN2, JAZF1, TNF24, LIFR, KLHL28, SLC12A5) and six downregulated DEGs (MAP6D1, PPIL6, NOSTRIN, SEC14L5, TMC2, FAM71A) were randomly selected for quantitative reverse transcription-PCR (qRT-PCR) to validate the RNA-seq results. Reverse transcription and real-time PCR were performed with the PrimeScriptRT Reagent kit with gDNA Eraser (Takara Biotechnology Co., Ltd., Dalian, China) and ChamQ Universal SYBR qPCR Master Mix (Vazyme, Nanjing, China). The expression level of each gene was normalized to β–ACTIN. All primer sequences are listed in online Supplementary Table S1.
Results and discussion
We established a cell model that produces a high level of milk protein by stimulating purified bovine mammary epithelial cells with 0.6 mM methionine for 24 h. Immunofluorescence showed that the marker of mammary epithelial cells, CYTOKERATIN 18, was expressed in all cells (online Supplementary Fig. 1A). The expression of β-CASEIN was significantly higher in cells stimulated with methionine than in the control cells (P < 0.01; online Supplementary Fig. 1B, 1C), confirming that methionine stimulation induced mammary epithelial cells to increase production of milk protein.
We identified 458 DEGs (219 upregulated and 239 downregulated) that were significantly differentially expressed between methionine-stimulated cells and control cells based on a |log2 ratio| ≥1 and P value ≤0.05 rule. Details of DEGs are shown in Table 1 and online Supplementary Fig. S2. We randomly selected six upregulated and six downregulated DEGs to validate the RNA-seq results by qRT-PCR. The expression levels calculated via RNA-seq and qRT-PCR were significantly positively correlated (R 2 = 0.9092, P < 0.0001; online Supplementary Fig. S3), confirming that our RNA-seq analysis was successful and accurate.
Top 50 upregulated and downregulated genes between methionine-stimulated cells and control cells
FC, fold change; FDR, false discovery rate.
To investigate the functional associations of all 458 DEGs, the DEGs were analyzed with the GO database. The two highest-ranked GO terms in the ‘molecular function’ category were ‘binding’ and ‘catalytic activity’ (online Supplementary Fig. S4), suggesting that milk protein synthesis in methionine-stimulated cells requires induction of gene expression to increase metabolic activity.
To identify biological pathways that may have been activated in methionine-simulated cells, KEGG analysis was performed with the KOBAS database. Our data showed that DEGs were most common in the ‘translation’ and ‘folding, sorting and degradation’ subcategories of the ‘genetic information processing’ category (online Supplementary Fig. S5), reflecting an increased translational and post-translational modification requirement associated with the synthesis of milk proteins and enzymes in methionine-stimulated cells. KEGG analysis also revealed that DEGs were most enriched in the ‘signal transduction’ subcategory of the ‘environmental information processing’ category (online Supplementary Fig. S5). cGMP-PKG, Rap1, calcium, cAMP, PI3K-AKT, MAPK, and JAK-STAT are the pathways with the highest number of DEGs (Fig. 1).
Summary of KEGG pathways enriched in the signal transduction category. The x axis shows the number of upregulated genes for each term.
It is known that milk protein production is a function of the number and activity of secretory epithelial cells. Activation of the mitogen-activated protein kinase (MAPK) signaling pathway is associated with the increased expression of a wide range of genes that promote cell survival and proliferation (Hicks et al., Reference Hicks, Hu, Macrae and DeWille2015). Our previous study showed that the viability of bovine mammary epithelial cells is significantly increased in cells treated with 0.6 mM methionine (Duan et al., Reference Duan, Lin, Lv, Yang, Jiao and Hou2017). In the current study, we found that four upregulated genes (MAP3K13, AKT3, FGF21, and FGFR4) were enriched in the MAPK signaling pathway, which is consistent with the effect of methionine on mammary epithelial cell survival and proliferation. Additionally, among these gene products, fibroblast growth factor 21 (FGF21) is a metabolic regulator that promotes glucose uptake in mouse 3T3 adipocytes. In dairy cows, plasma FGF21 increases at the onset of lactation (Schoenberg et al., Reference Schoenberg, Giesy, Harvatine, Waldron, Cheng, Kharitonenkov and Boisclair2011). FGF21, betaKlotho, and fibroblast growth factor receptor 4 (FGFR4) form the cognate FGF21 receptor complex, which mediates FGF21 cellular specificity and physiological effects. Milk protein synthesis is an energetically costly process. The higher expression of FGF21 and FGFR4 in methionine-stimulated bovine mammary epithelial cells suggests enhanced glucose uptake and metabolism during methionine-induced milk protein synthesis in mammary glands of dairy cows.
In mice, the response of the mammary gland to prolactin, which leads to milk protein gene expression, is mediated by the JAK-STAT signaling pathway. Our data showed that the JAK-STAT signaling pathway was notably enriched for upregulated DEGs in methionine-stimulated cells. Four members of the JAK-STAT signaling pathway (STAM, AKT3, GHR, and LIFR) were significantly upregulated in methionine-stimulated mammary epithelial cells compared with control cells. Generally, growth hormone receptor (GHR) is expressed in the apical membranes of bovine mammary epithelial cells and mediates the function of growth hormone on milk protein gene expression (Zhou et al., Reference Zhou, Akers and Jiang2008). Our data suggested that the differential expression of these signaling molecules in JAK-STAT signaling was not hormone dependent but was mediated by methionine in bovine mammary epithelial cells.
Protein kinase B (PKB, also known as AKT) is an essential central regulator of mammary epithelial differentiation and lactation. Mice lacking AKT1 exhibit a pronounced metabolic defect during late pregnancy and lactation. Our KEGG analysis revealed four upregulated DEGs in the PI3K-AKT signaling pathway. This is consistent with a recent study in dairy cow mammary gland showing that supplementation with methionine around parturition increases the phosphorylation of AKT, as well as the expression of amino acid transporters (Ma et al., Reference Ma, Batistel, Xu, Han, Bucktrout, Liang, Coleman, Parys and Loor2019). Studies of the roles of AKT in mice showed that loss of AKT1, but not AKT2 or AKT3, inhibits milk production during lactation (Boxer et al., Reference Boxer, Stairs, Dugan, Notarfrancesco, Portocarrero, Keister, Belka, Cho, Rathmell, Thompson, Birnbaum and Chodosh2006). However, our data showed that AKT3 was upregulated by methionine stimulation, suggesting that AKT3 may function in the regulation of milk protein synthesis in mammary glands of dairy cows. Additionally, we found that the PI3K-AKT and JAK-STAT signaling pathways were both significantly enriched for upregulated DEGs by methionine stimulation. This was in agreement with previous studies in mice showing that AKT is necessary for JAK-STAT5 activation and cell proliferation in lactating mammary gland (Chen et al., Reference Chen, Boxer, Stairs, Portocarrero, Horton, Alvarez, Birnbaum and Chodosh2010).
The mammalian target of rapamycin is one of the downstream effectors of PI3K-AKT. Amino acid-induced protein synthesis is at least partially mediated by the mTOR signaling pathway. Several amino acids have been identified as effective activators of mTORC1. In the present study, we found only one upregulated gene related to the mTOR signaling pathway. In bovine mammary epithelial cells, phosphorylation of mTOR is significantly increased in methionine-stimulated cells compared with control cells, but the total level of mTOR does not change (Duan et al., Reference Duan, Lin, Lv, Yang, Jiao and Hou2017). This may indicate that methionine-regulated mTOR signaling is activated via a posttranscriptional mechanism in mammary glands of dairy cows.
In conclusion, we demonstrated that 458 transcripts (219 upregulated and 239 downregulated) were significantly differentially expressed between methionine-stimulated bovine mammary epithelial cells and control cells. Methionine-stimulated milk protein synthesis in bovine mammary epithelial cells is supported by increased gene expression related to the cGMP-PKG, Rap1, calcium, cAMP, PI3K-AKT, MAPK, and JAK-STAT signaling pathways. The identification of enriched DEGs and pathways provides insights into molecular events that occur in methionine-stimulated mammary epithelial cells. Understanding the regulatory effects of methionine on milk protein synthesis is important for improving the model of amino acid requirement for lactation.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0022029920000199.
Acknowledgement
This work was supported by grants from the National Natural Science Foundation of China (31671285 to X. H., 31771453 to Y. L., and 31571338 to F. Z.), and the ‘Academic Backbone’ Project of Northeast Agricultural University (17XG16 to X. H., and 18XG25 to Y. L., China).
