RNA-Seq data processing, alignment, and assessment
RNA was isolated from control cells (Non-treated) and 50 nM CCI-779-treated cells for RNA sequencing analysis. By sequencing, 15,138,753 and 18,411,100 raw reads were generated for the control and CCI-779-treated groups, respectively. After the removal of adaptor sequences, ambiguous nucleotides, low-quality sequences, contaminated microbial sequences, and ribosomal RNA sequences, a total of 14,689,607 and 17,861,831 clean reads with lengths of 120–150 bp from 2 sequencing libraries were gathered for further analysis. Clean reads of 2 samples were aligned with TMAP {version 3.4.1} to the goat reference genes and genome, and uniquely aligning reads were summated to generate read count-based gene expression estimates. The mapping ratio to the reference genes ranged from 86.30 to 86.98 %, and above 80 %, whereas the mapping ratio to the reference genome ranged from 98.14 to 98.35 %, exceeding 97 %.
Analysis of differentially expressed genes related to mTOR signaling
To analyze DEGs that were related to mTORC1, all sequenced genes were screened between control cells and treated cells (untreated vs CCI-779). A total of 365 DEGs that were related to mTORC1 were identified in the transcriptomic comparison (Fig. 2a; Additional file 2), comprising 144 upregulated and 221 downregulated DEGs (Fig. 2b, c), suggesting that their expression was associated with mTORC1 in GFb cells.
Functional analysis of differentially expressed genes in untreated vs CCI-779-treated cells
To determine the functions of our DEGs, WEGO was used to attach functional annotations to them. The complete GO enrichment analysis of DEGs is included in Additional file 3. GO functional classification of DEGs was generalized as biological process, cellular process, and molecular function (Fig. 3, Additional file 4), and 300 genes were annotated with 43 GO terms. Overall, “cell (GO: 0005623) (231 genes),” “cell part (GO: 0044464) (231 genes),” and “organelle (GO: 0043226) (177 genes)” were listed as the top Cellular Components; “binding (GO: 0005488) (206 genes)” and “catalytic activity (GO: 0003824) (95 genes)” were the top Molecular Functions; and the most frequent Biological Processes were “cellular process (GO: 0009987) (215 genes),” “signal-organism process (GO: 0044699) (166 genes),” and “metabolic process (GO: 0008152) (173 genes).” Further, DEGs were enriched in KEGG terms, and 293 genes were annotated in 194 pathways, primarily “Metabolic pathways,” “Focal adhesion,” and “Regulation of actin cytoskeleton” (Additional file 5).
CCI-779 induces expression changes in genes encoding proteins involved in mTOR signaling
To examine whether the proteins involved in mTORC1 signaling were differentially expressed in treated cells, the encoding genes were identified by KEGG analysis. Five genes were identified as being significantly altered in untreated versus CCI-779-treated cells—phosphatidylinositol-3-kinase (PI3K) and vascular endothelial growth factor VEGF (LOC102177848) were upregulated, and ribosomal protein S6 kinase (S6K1), regulated in DNA damage and development 1 (REDD1), and mouse protein 25 (MO25) were downregulated (Fig. 4), suggesting that inhibition of mTORC1 changes the expression of molecules that participate in this pathway.
CCI-779 induces expression changes in eukaryotic RNA polymerase subunits and transcription factors in GFb cells
To determine whether the expression of DNA-directed RNA polymerases or transcription factors were affected by mTORC1 inhibition, the expression of several eukaryotic RNA polymerase subunits and transcription factors were analyzed in control and CCI-779-treated GFbs. Eukaryotic RNA polymerase II subunit RPB1 (ODF3L2, B1) and polymerase III subunit POLR3G (C31) were downregulated, whereas CMYA5 (C37) was upregulated in CCI-779-treated GFb cells (Fig. 5). Three transcription factors were differentially expressed—TCF20 was upregulated, and NRL and NFYB were downregulated, indicating that their expression is regulated by mTOR signaling.
Analysis of DEGs in amino acid metabolism related to mTORC1
To determine the function of mTORC1 in amino acid metabolism, a comparative analysis was performed in untreated and CCI-779-treated cells. A total of 6 genes were identified. Compared with control cells, in CCI-779-treated GFbs, 2-oxoglutarate dehydrogenase E1 component (OGDH), short/branched chain acyl-CoA dehydrogenase (ACADSB), and 2,3-bisphosphoglycerate-dependent phosphoglycerate mutase (PGAM2) were upregulated in lysine, valine, leucine, isoleucine, glycine, serine, and threonine metabolism. Glutathione S-transferase GST (LOC102179473, LOC102189581, LOC102188913), 3-hydroxyisobutyrate dehydrogenase mmsB (PSIP1), and histamine N-methyltransferase (HNMT) were downregulated in glutathione, valine, leucine, isoleucine, and histidine metabolism (Fig. 6). These data indicate that mTORC1 has a significant function in amino acid metabolism.
Analysis of DEGs in lipid metabolism related to mTORC1
To examine the regulatory mechanism of mTORC1 in lipid metabolism and identify important molecules that were related to mTORC1, we compared the expression levels of genes that were associated with lipid metabolism between CCI-779-treated and control cells. A total of 11 genes were differentially expressed in specific metabolic pathways. 3-butanediol dehydrogenase bdh (BDH2), sphingosine kinase SPHK (SPHK1), cytochrome P-450 (CYP) 1B1 (LOC102184252), phosphatidylinositol-4,5-diphosphate-3-kinase PIK3C (PIK3CD), and prostaglandin-endoperoxide synthase1 (PTGS1) were upregulated, while whereas lysosomal acid lipase LIPA (LIPA), microsomal triglyceride transfer protein large subunit (MTTP), triacylglycerol lipase ATGL (LIPG), juvenile hormone acid methyltransferase (JHAMT), protein farnesyltransferase subunit beta FNTB (CHURC1), and decaprenyl-diphosphate synthase subunit1 (PDSS1) were downregulated in treated cells (Fig. 7). BDH2, SPHK1, CYP 1B1, PIK3CD, and PTGS1 mediate butanoate metabolism, sphingolipid metabolism, steroid hormone biosynthesis, inositol phosphate metabolism and arachidonic acid metabolism, respectively. LIPA, MTTP, LIPG, JHAMT, CHURC1, and PDSS1 are involved in steroid biosynthesis, fat digestion and absorption, glycerolipid metabolism, insect hormone biosynthesis, and terpenoid backbone biosynthesis, respectively. These data suggest that mTOR signaling regulates various aspects of lipid metabolism.
Analysis of DEGs in carbohydrate metabolism related to mTORC1
To analyze DEGs in energy homeostasis that were related to mTOR signaling, we focused on DEGs that mediated carbohydrate metabolism in untreated versus CCI-779-treated cells. Six genes were upregulated: chondroitin 6- sulfotransferase3 (CHST3), 2-oxoglutarate dehydrogenase E1 component (OGDH), phosphatidylinositol glycan (PIGK), 2,3-bisphosphoglycerate-dependent phosphoglycerate mutase (PGAM2), ketohexokinase (KHK), and cytochrome-b5 reductase Cyt b5R (LOC102173645). The 5 genes that were downregulated in CCI-779-treated GFbs were N4- (β- N-acetylglucosaminyl)-L-asparaginase (AGA), oligosaccharide translocation protein (RFT1), protein O-GlcNAc transferase OGT (TTC5), acylphosphatase (ACYP1), and acetyl-CoA hydrolase ACH1 (STARD10) (Fig. 8). CHST3, OGDH, PIGK, PGAM2, KHK, and Cyt b5R are involved in glycosaminoglycan biosynthesis, chondroitin sulfate biosynthesis, citrate cycle, glycosylphosphatidylinositol (GPI)-anchor biosynthesis, fructose and mannose metabolism, gluconeogenesis metabolism, and amino sugar and nucleotide sugar metabolism, respectively. AGA, RFT1, TTC5, ACYP1 and STARD10 participate in glycan degradation, N-glycan biosynthesis, other types of O-glycan biosynthesis, and pyruvate metabolism, respectively. These results indicate that carbohydrate metabolism is controlled by mTOR signaling in GFbs.
Analysis of DEGs in single nucleotide metabolism related to mTORC1
To determine the function of mTORC1 in single nucleotide metabolism and identify important molecules that are related to mTORC1, a comparative analysis was performed in untreated versus CCI-779 cells. In CCI-779-treated GFbs, uridine kinase udk (UCK1) and guanylate cyclase 2 F (GUCY2F) were upregulated in uridine/ cytidine and guanosine triphosphate (GTP) metabolism, respectively, whereas, guanylate cyclase soluble subunit beta (GUCY1B3), 3′,5′-cyclic-nucleotide phosphodiesterase PDE8A and nucleoside-diphosphate kinase ndk (LOC102176263) were downregulated in guanylate cyclization, 3′,5′-cyclic guanosine monophosphate (3′,5′-cGMP) and deoxy-ribonucleoside triphosphate (dNTP) metabolism, respectively (Fig. 9). These results indicate that mTOR signaling is associated with single nucleotide metabolism.
Confirmation of gene expression
To analyze the expression patterns of DEGs in the RNA-Seq, 40 DEGs with important functions, including 32 DEGs in amino acid, lipid, carbohydrate, and single nucleotide metabolism, 2 DEGs (VEGF and S6K1/2) involved in mTOR signaling, 3 DEGs (RPB1, POLR3G and CMYA5) related to RNA polymerase and 3 DEGs (TCF20, NRL and NFYB) related to transcription factors, were selected for quantitative real-time PCR analysis, with β-actin as the reference gene. The qPCR results showed high concordance with the RNA-Seq data, suggesting that our RNA-Seq findings are reliable (Fig. 10). The data are listed in Additional file 6. In addition, statistical analysis was performed for 40 DEGs, indicating that all quantitative data we achieved are reliable and the differential expression of each DEG between control and CCI-779-treated groups are all significantly different (p < 0.05) (Fig. 11). Moreover, genes that encoded enzymes in amino acid, lipid, carbohydrate, and single nucleotide metabolism were differentially expressed in mTORC1-inhibited GFbs. The number of DEGs in lipid and carbohydrate metabolism is more than that in amino acid and nucleotide metabolism. In addition, the number of up-regulated DEGs equals to down-regulated genes in amino acids metabolism; the number of down-regulated DEGs are more than up-regulated genes in lipids and single nucleotides metabolism; in contrast, the number of down-regulated DEGs are less than up-regulated DEGs in carbohydrates metabolism (Fig. 12). Thus, mTORC1 signaling might have disparate functions in the metabolism of various macro-molecules.
Emerging evidence indicates that gene transcription and steady-state levels of mRNA expression do not always predict protein levels [43]. To validate the protein expression of certain differentially expressed genes as we found in this study, S6K1 and VEGF were selected for the detection by western blot analysis. These two proteins showed a differential expression between non-treated and treated with CCI-779 groups (p < 0.05). The expression of S6K1 and VEGF were consistent with the results of the transcriptional levels (Fig. 13, Additional file 7: Figure S1). The data showed a preliminary significance of the findings in the protein levels.