UTP11 promotes the growth of hepatocellular carcinoma by enhancing the mRNA stability of Oct4.

BACKGROUND: Several publications suggest that UTP11 may be a promising gene engaged for involvement of hepatocellular carcinoma (HCC) pathology. However, there are extremely limited biological, mechanistic and clinical studies of UTP11 in HCC. METHODS: To anayze the UTP11 mRNA expression in HCC and normal clinical samples and further investigate the correlation between UTP11 expression and pathology and clinical prognosis via the Cancer Tissue Gene Atlas (TCGA) database. The protein levels of UTP11 were checked using the Human Protein Atlas (HPA) database. GO-KEGG enrichment was performed from Cancer Cell Line Encyclopedia (CCLE) database and TCGA dataset. The levels of UTP11 were tested with qRT-PCR and western blotting assays. Cell viability, immunofluorescence and flow cytometry assays and animal models were used to explore the potential involvement of UTP11 in regulating HCC growth in vitro and in vivo. The correlation of UTP11 and tumor stemness scores and stemness-associated proteins from TCGA database. The mRNA stability was treated with Actinomycin D, followed by testing the mRNA expression using qRT-PCR assay. RESULTS: UTP11 was highly expressed in HCC samples compared to normal tissues from TCGA database. Similarly, UTP11 protein expression levels were obviously elevated in HCC tissue samples from HPA database. Furthermore, UTP11 levels were correlated with poor prognosis in HCC patient samples in TCGA dataset. In addition, the UTP11 mRNA levels was notably enhanced in different HCC cell lines than in normal liver cells and knocking down UTP11 was obviously reduced the viability and cell death of HCC cells. UTP11 knockdown suppressed the tumor growth of HCC in vivo experiment and extended the mice survival time. GO-KEEG analysis from CCLE and TCGA database suggested that UTP11 might involve in RNA splicing and the stability of mRNA. Further, UTP11 was positively correlated with tumor stemness scores and stemness-associated proteins from TCGA database. Knockdown of UTP11 was reduced the expression of stem cell-related genes and regulated the mRNA stability of Oct4. CONCLUSIONS: UTP11 is potentially a diagnostic molecule and a therapeutic candidate for treatment of HCC.

MicroRNA-9-5p Is Involved in Lipopolysaccharide-Induced Acute Lung Injury Via the Regulation of Macrophage Polarization.

MicroRNA (miR)-9-5 p has been shown to affect lung cancer progression and lung fibrosis, but the efficacy of miR-9-5 p in acute lung injury (ALI) remained indefinite. The study was performed to probe the modulating mechanism of miR-9-5 p in ALI via regulating macrophage polarization. The ALI mouse model was established and blood samples of ALI patients were obtained. MiR-9-5 p levels in ALI mice and ALI patients were detected. Mouse pulmonary macrophages were extracted from bronchoalveolar lavage fluid and polarized into M1 and M2 macrophages. Intervention of miR-9-5 p expression was performed to observe the effects on M1 polarization and M2 polarization in lung macrophages, inflammatory factors in BALF, wet/dry weight ratio (W/D) in lung tissues, myeloperoxidase (MPO) activity in lung tissues, and lung tissue lesion condition. MiR-9-5 p levels were elevated in the lung tissues of ALI mice and ALI patients. MiR-9-5 p silencing could repress lung macrophages in ALI mice polarized toward the M1 phenotype and promoted the polarization toward the M2 phenotype, reduced the lung lesions, the lung water content, and the secretion levels of the pro-inflammatory factors TNF-α, IL-6, and IL-1ß in BALF, increased the secretion of the anti-inflammatory factor IL-10, as well as impeded the MPO activity in the lung tissues of ALI mice. MiR-9-5 p deletion ameliorates LPS-induced inflammatory infiltration in lung tissues via inhibiting the polarization of mouse lung macrophages to the M1 phenotype and promoting the polarization to the M2 phenotype.

MiR-202-5p Regulates Geese Follicular Selection by Targeting BTBD10 to Regulate Granulosa Cell Proliferation and Apoptosis.

The regulation of granulosa cells (GCs) proliferation and apoptosis is the key step in follicular selection which determines the egg production performance of poultry. miR-202-5p has been reported to be involved in regulating the proliferation and apoptosis of mammalian ovarian GCs. However, its role in regulating the proliferation and apoptosis of goose GCs is still unknown. In the present study, the GCs of pre-hierarchical follicles (phGCs, 8-10 mm) and those of hierarchical follicles (hGCs, F2-F4) were used to investigate the role of miR-202-5p in cell proliferation and apoptosis during follicle selection. In phGCs and hGCs cultured in vitro, miR-202-5p was found to negatively regulate cell proliferation and positively regulate cell apoptosis. The results of RNA-seq showed that BTB Domain Containing 10 (BTBD10) is predicted to be a key target gene for miR-202-5p to regulate the proliferation and apoptosis of GCs. Furthermore, it is confirmed that miR-202-5p can inhibit BTBD10 expression by targeting its 3'UTR region, and BTBD10 was revealed to promote the proliferation and inhibit the apoptosis of phGCs and hGCs. Additionally, co-transfection with BTBD10 effectively prevented miR-202-5p mimic-induced cell apoptosis and the inhibition of cell proliferation. Meanwhile, miR-202-5p also remarkably inhibited the expression of Phosphatidylinositol-4,5-Bisphosphate 3-Kinase Catalytic Subunit Beta (PIK3CB) and AKT Serine/Threonine Kinase 1 (AKT1), while it was significantly restored by BTBD10. Overall, miR-202-5p suppresses the proliferation and promotes the apoptosis of GCs through the downregulation of PIK3CB/AKT1 signaling by targeting BTBD10 during follicular selection. Our study provides a theoretical reference for understanding the molecular mechanism of goose follicular selection, as well as a candidate gene for molecular marker-assisted breeding to improve the geese' egg production performance.

Revealing the potential role of hub metabolism-related genes and their correlation with immune cells in acute ischemic stroke.

OBJECTIVES: Acute ischemic stroke (AIS) is caused by cerebral ischemia due to thrombosis in the blood vessel. The purpose of this study is to identify key genes related to metabolism to aid in the mechanism research and management of AIS. MATERIALS AND METHODS: Gene expression data were downloaded from the Gene Expression Omnibus database. Weighted gene co-expression network analysis, Gene Ontology and kyoto encyclopedia of genes and genomes analysis were used to identify metabolism-related genes that may be involved in the regulation of AIS. A protein protein interaction network was mapped using Cytoscape based on the STRING database. Subsequently, hub metabolism-related genes were identified based on Cytoscape-CytoNCA and Cytoscape-MCODE plug-ins. Least absolute shrinkage and selection operator algorithm and differential expression analysis. In addition, drug prediction, molecular docking, ceRNA network construction, and correlation analysis with immune cell infiltration were performed to explore their potential molecular mechanisms of action in AIS. Finally, the expression of hub gene was verified by real-time PCR. RESULTS: Metabolism-related genes FBL, HEATR1, HSPA8, MTMR4, NDUFC1, NDUFS8 and SNU13 were identified. The AUC values of FBL, HEATR1, HSPA8, MTMR4, NDUFS8 and SNU13 were all greater than 0.8, suggesting that they had good diagnostic accuracy. Correlation analysis found that their expression levels were also related to the infiltration levels of multiple immune cells, such as Activated.CD8.T.cell and Activated.dendritic.cell. It was found that only HSPA8 was successfully matched to drugs with literature support, and these drugs were acetaminophen, bupivacaine, dexamethasone, gentamicin, tretinoin and cisplatin. Moreover, it was also identified that the ENSG000000218510-hsa-miR-330-3p-HEATR1 axis may be involved in regulating AIS. CONCLUSIONS: The identification of FBL, HEATR1, HSPA8, MTMR4, NDUFC1, NDUFS8 and SNU13 provides a new research direction for exploring the molecular mechanisms of AIS, which can help in clinical management and diagnosis.

miR-202-5p Inhibits Lipid Metabolism and Steroidogenesis of Goose Hierarchical Granulosa Cells by Targeting ACSL3.

miRNAs are critical for steroidogenesis in granulosa cells (GCs) during ovarian follicular development. We have previously shown that miR-202-5p displays a stage-dependent expression pattern in GCs from goose follicles of different sizes, suggesting that this miRNA could be involved in the regulation of the functions of goose GCs; therefore, in this study, the effects of miR-202-5p on lipid metabolism and steroidogenesis in goose hierarchical follicular GCs (hGCs), as well as its mechanisms of action, were evaluated. Oil Red O staining and analyses of intracellular cholesterol and triglyceride contents showed that the overexpression of miR-202-5p significantly inhibited lipid deposition in hGCs; additionally, miR-202-5p significantly inhibited progesterone secretion in hGCs. A bioinformatics analysis and luciferase reporter assay indicated that Acyl-CoA synthetase long-chain family member 3 (ACSL3), which activates long-chain fatty acids for the synthesis of cellular lipids, is a potential target of miR-202-5p. ACSL3 silencing inhibited lipid deposition and estrogen secretion in hGCs. These data suggest that miR-202-5p exerts inhibitory effects on lipid deposition and steroidogenesis in goose hGCs by targeting the ACSL3 gene.

Estrogen Receptor Gene 1 (ESR1) Mediates Lipid Metabolism in Goose Hierarchical Granulosa Cells Rather than in Pre-Hierarchical Granulosa Cells.

(1) Background: The role of estrogen receptor gene 1 (ESR1) in female reproduction and lipid metabolism has been extensively investigated. However, its contribution to lipid metabolism during the development of poultry follicles remains unclear. (2) Methods: This study aimed to explore the function of ESR1 via overexpressing (ESR1ov) and interfering (ESR1si) with its expression in pre-hierarchical granulosa cells (phGCs) and hierarchical granulosa cells (poGCs). (3) Results: We successfully cloned and obtained an 1866 bp segment of the full-length CDS region of the Sichuan white goose ESR1 gene. In phGCs of the ESR1ov and ESR1si groups, there were no significant changes compared to the control group. However, in poGCs, the ESR1ov group exhibited decreased lipid deposition, triglycerides, and cholesterol compared to the control group, while the ESR1si group showed increased lipid deposition, triglycerides, and cholesterol. The expression of APOB and PPARα was significantly reduced in the ESR1ov group compared to the ESR1ov-NC group. Moreover, significant changes in the expression of ACCα, DGAT1, SCD, CPT1, and ATGL were observed between the ESR1si and ESR1si-NC group. (4) Conclusions: These findings shed light on the function and molecular mechanism of ESR1 in lipid metabolism in goose poGCs, providing a better understanding of the physiological process of goose follicular development.

Antibiotic-Induced Dysbiosis of Microbiota Promotes Chicken Lipogenesis by Altering Metabolomics in the Cecum.

Elucidation of the mechanism of lipogenesis and fat deposition is essential for controlling excessive fat deposition in chicken. Studies have shown that gut microbiota plays an important role in regulating host lipogenesis and lipid metabolism. However, the function of gut microbiota in the lipogenesis of chicken and their relevant mechanisms are poorly understood. In the present study, the gut microbiota of chicken was depleted by oral antibiotics. Changes in cecal microbiota and metabolomics were detected by 16S rRNA sequencing and ultra-high performance liquid chromatography coupled with MS/MS (UHPLC-MS/MS) analysis. The correlation between antibiotic-induced dysbiosis of gut microbiota and metabolites and lipogenesis were analysed. We found that oral antibiotics significantly promoted the lipogenesis of chicken. 16S rRNA sequencing indicated that oral antibiotics significantly reduced the diversity and richness and caused dysbiosis of gut microbiota. Specifically, the abundance of Proteobacteria was increased considerably while the abundances of Bacteroidetes and Firmicutes were significantly decreased. At the genus level, the abundances of genera Escherichia-Shigella and Klebsiella were significantly increased while the abundances of 12 genera were significantly decreased, including Bacteroides. UHPLC-MS/MS analysis showed that antibiotic-induced dysbiosis of gut microbiota significantly altered cecal metabolomics and caused declines in abundance of 799 metabolites and increases in abundance of 945 metabolites. Microbiota-metabolite network revealed significant correlations between 4 differential phyla and 244 differential metabolites as well as 15 differential genera and 304 differential metabolites. Three metabolites of l-glutamic acid, pantothenate acid and N-acetyl-l-aspartic acid were identified as potential metabolites that link gut microbiota and lipogenesis in chicken. In conclusion, our results showed that antibiotic-induced dysbiosis of gut microbiota promotes lipogenesis of chicken by altering relevant metabolomics. The efforts in this study laid a basis for further study of the mechanisms that gut microbiota regulates lipogenesis and fat deposition of chicken.

Integrated Analysis Reveals a lncRNA-miRNA-mRNA Network Associated with Pigeon Skeletal Muscle Development.

Growing evidence has demonstrated the emerging role of long non-coding RNA as competitive endogenous RNA (ceRNA) in regulating skeletal muscle development. However, the mechanism of ceRNA regulated by lncRNA in pigeon skeletal muscle development remains unclear. To reveal the function and regulatory mechanisms of lncRNA, we first analyzed the expression profiles of lncRNA, microRNA (miRNA), and mRNA during the development of pigeon skeletal muscle using high-throughput sequencing. We then constructed a lncRNA-miRNA-mRNA ceRNA network based on differentially expressed (DE) lncRNAs, miRNAs, and mRNAs according to the ceRNA hypothesis. Functional enrichment and short time-series expression miner (STEM) analysis were performed to explore the function of the ceRNA network. Hub lncRNA-miRNA-mRNA interactions were identified by connectivity degree and validated using dual-luciferase activity assay. The results showed that a total of 1625 DE lncRNAs, 11,311 DE mRNAs, and 573 DE miRNAs were identified. A ceRNA network containing 9120 lncRNA-miRNA-mRNA interactions was constructed. STEM analysis indicated that the function of the lncRNA-associated ceRNA network might be developmental specific. Functional enrichment analysis identified potential pathways regulating pigeon skeletal muscle development, such as cell cycle and MAPK signaling. Based on the connectivity degree, lncRNAs TCONS_00066712, TCONS_00026594, TCONS_00001557, TCONS_00001553, and TCONS_00003307 were identified as hub genes in the ceRNA network. lncRNA TCONS_00026594 might regulate the FSHD region gene 1 (FRG1)/ SRC proto-oncogene, non-receptor tyrosine kinase (SRC) by sponge adsorption of cli-miR-1a-3p to affect the development of pigeon skeletal muscle. Our findings provide a data basis for in-depth elucidation of the lncRNA-associated ceRNA mechanism underlying pigeon skeletal muscle development.

Transcriptome Analysis of Differentially Expressed mRNA Related to Pigeon Muscle Development.

The mechanisms behind the gene expression and regulation that modulate the development and growth of pigeon skeletal muscle remain largely unknown. In this study, we performed gene expression analysis on skeletal muscle samples at different developmental and growth stages using RNA sequencing (RNA-Seq). The differentially expressed genes (DEGs) were identified using edgeR software. Weighted gene co-expression network analysis (WGCNA) was used to identify the gene modules related to the growth and development of pigeon skeletal muscle based on DEGs. A total of 11,311 DEGs were identified. WGCNA aggregated 11,311 DEGs into 12 modules. Black and brown modules were significantly correlated with the 1st and 10th day of skeletal muscle growth, while turquoise and cyan modules were significantly correlated with the 8th and 13th days of skeletal muscle embryonic development. Four mRNA-mRNA regulatory networks corresponding to the four significant modules were constructed and visualised using Cytoscape software. Twenty candidate mRNAs were identified based on their connectivity degrees in the networks, including Abca8b, TCONS-00004461, VWF, OGDH, TGIF1, DKK3, Gfpt1 and RFC5, etc. A KEGG pathway enrichment analysis showed that many pathways were related to the growth and development of pigeon skeletal muscle, including PI3K/AKT/mTOR, AMPK, FAK, and thyroid hormone pathways. Five differentially expressed genes (LAST2, MYPN, DKK3, B4GALT6 and OGDH) in the network were selected, and their expression patterns were quantified by qRT-PCR. The results were consistent with our sequencing results. These findings could enhance our understanding of the gene expression and regulation in the development and growth of pigeon muscle.