Pathway Interaction Network Research Articles

Plasma differentially expressed genes and bioinformatics analysis of workers occupationally exposed to mercury

Objective: To screen and identify plasma differentially expressed genes and related signal pathway by human gene expression profile array and fluorescent quantitative PCR. Methods: From September 2018 to October 2019, 291 workers from a Mercury-in-glass thermometer factory in Jiangsu Province were selected for an occupational health examination, a total of 60 persons were divided into two groups: high and low mercury exposure groups (30 persons in each group) . Plasma total RNA samples from the high exposure group and the low exposure group (10 cases each) were detected by gene expression microarray, and differentially expressed genes (DEGs) with fold change >2 were selected. DEGs were submitted to David and Metascape for gene function clustering, pathway and protein interaction network analysis. Finally, fluorescence quantitative PCR was performed to verify the changes in the expression levels of key DEGs in the high exposure group and the low exposure group (another 20 cases in each group) . Results: A total of 269 DEGs, of which 203 up regulated and 66 down regulated were identified in the differential expression analysis of gene expression microarray. Bioinformatics analysis suggested that, DEGs were involved in forebrain development, glial cell fate determinants of GO biological process and PID NF-KB, PTEN signal pathway. NFE2L1, SOX8, SOX6 and RNF2 (P<0.05) were confirmed down regulated in high level group by fluorescent quantitative PCR compared with the low level group (fold changes were 2.10, 11.52, 2.19, and 4.38 respectively) . Conclusion: The plasma NFE2L1, SOX8, SOX6 and RNF2 gene expressions are significantly altered in occupa tional high mercury exposure population. PTEN signaling pathway and fate of glia cells determines the biological process may be closely related to the body injury caused by mercury exposure.

Tumor mutation burden in connection with immune-related survival in uterine corpus endometrial carcinoma

BackgroundUCEC is the most common gynecological malignancy in many countries, and its mechanism of occurrence and development is related to tumor mutation burden (TMB) and immune cell infiltration. Therefore, it is necessary to systematically explore the TMB-related gene profile in immune cells to improve the prognosis of UCEC.MethodsWe integrated TMB-related genes with basic clinical information of UCEC patients based on TCGA dataset. Differentially expressed genes (DEGs) were selected through differential expression screening, PPI, and enrichment analysis. Additionally, we analyzed the components of immune cell infiltration of the DEGs to obtain the differential immunity-related genes. A single factor and multifactor Cox regression analyses were conducted to establish new prognostic indicators of OS and DFS based on TMB-related immune genes. To further study the correlation between survival and immune cell infiltration, a Cox model based on these immune infiltration compositions was built. Using the clinical variables, we established nomograms for OS and DFS.Results393 DEGs were significantly associated with clinical outcomes and the immune component in patients with UCEC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes, Genomes (KEGG) pathway and protein-protein interaction network (PPI) analyses revealed the role of these genes and information on related pathways. Then, two prognostic models were established based on the differential immune genes for OS (GFAP and MX2) and DFS (MX2, GFAP, IGHM, FGF20, and TRAV21). In DFS, the differential immune genes were related to CD4+ T cell, CD8+ T cell, macrophage, and neutrophil (all P < 0.05). B cell and CD8+ T cell were independent prognostic factors from among the immune cell elements in UCEC. Finally, the risk scores of these models were combined with the clinical elements-based nomogram models, and the AUC values were all over 0.7.ConclusionsOur results identified several clinically significant differential immune genes and established relevant prognostic models, providing a basis for the molecular analysis of TMB and immune cells in UCEC, and identified potential prognostic and immune-related genes for UCEC. We added clinical related conditions for further analysis to confirm the identity of the genes and clinical elements-based models.

Short-Term Mild Temperature-Stress-Induced Alterations in the C. elegans Phosphoproteome.

Exposure to mild early-life stresses can slow down aging, and protein phosphorylation might be an essential regulator in this process. However, the mechanisms of phosphorylation-based signaling networks during mild early-life stress remain elusive. Herein, we systematically analyzed the phosphoproteomes of Caenorhabditis elegans, which were treated with three mild temperatures (15 °C, 20 °C, and 25 °C) in two different short-term groups (10 min and 60 min). By utilizing an iTRAQ-based quantitative phosphoproteomic approach, 18,187 phosphosites from 3330 phosphoproteins were detected in this study. Volcano plots illustrated that the phosphorylation abundance of 374 proteins and 347 proteins, were significantly changed at 15 °C and 25 °C, respectively. Gene ontology, KEGG pathway and protein-protein interaction network analyses revealed that these phosphoproteins were primarily associated with metabolism, translation, development, and lifespan determination. A motif analysis of kinase substrates suggested that MAPK, CK, and CAMK were most likely involved in the adaption processes. Moreover, 16 and 14 aging-regulated proteins were found to undergo phosphorylation modifications under the mild stresses of 15 °C and 25 °C, respectively, indicating that these proteins might be important for maintaining long-term health. Further lifespan experiments confirmed that the candidate phosphoproteins, e.g., EGL-27 and XNP-1 modulated longevity at 15 °C, 20 °C, and 25 °C, and they showed increased tolerance to thermal and oxidative stresses. In conclusion, our findings offered data that supports understanding of the phosphorylation mechanisms involved in mild early-life stresses in C. elegans. Data are available via ProteomeXchange with identifier PXD021081.

Ubiquitome analysis reveals the involvement of lysine ubiquitination in the spermatogenesis process of adult buffalo (Bubalus bubalis) testis.

Protein ubiquitination, a major and conserved post-translational modification, is known to play a critical regulatory role in many biological processes in eukaryotes. Although several ubiquitinated proteins have been found in buffalo (Bubalus bubalis) testis in our previous studies, large-scale profiling of buffalo testis ubiquitome has not been reported to date. In the present study, we first identified a global profiling of lysine ubiquitination of adult buffalo testis using a highly sensitive LC-MS/MS coupled with immune-affinity enrichment of ubiquitinated peptides. In total, 422 lysine ubiquitination sites were identified in 262 proteins in adult buffalo testis tissue. Bioinformatics analysis showed that the ubiquitinated proteins are involved in a variety of biological processes and diverse subcellular localizations. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein interaction network analysis indicated that proteasome, glycolysis/gluconeogenesis and gap junction pathways are modulated by protein ubiquitination in testis. Besides, 44 ubiquitinated proteins may involve in spermatogenesis according to the SpermatogenesisOnline database, of which, the ubiquitination of HSPA2 and UCHL1 were confirmed by Immunoprecipitation (IP)/Western blot analysis. Taken together, these data provide a global view of ubiquitome in buffalo testis for the first time, and serve as an important resource for exploring the physiological role especially spermatogenesis of lysine ubiquitination in testis in mammals.

Elevated TOP2A and UBE2C expressions correlate with poor prognosis in patients with surgically resected lung adenocarcinoma: a study based on immunohistochemical analysis and bioinformatics.

Lung cancer has the highest morbidity and mortality among all cancer types. Reliable prognostic biomarkers are needed to identify high-risk patients apart from TNM system for precision medicine. The present study is designed to identify robust prognostic biomarkers in lung adenocarcinoma (LUAD) based on integration of multiple GEO datasets, The Cancer Genome Atlas (TCGA) database and Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. Four LUAD GEO datasets (GSE10072, GSE2514, GSE43458, and GSE32863) and TCGA database were implemented to analyze the differently expressed genes (DEGs). Gene ontology, KEGG pathway, and protein-protein interaction network (PPI) were conducted based on the above DEGs. Hub genes were selected based on connectivity degree in the PPI network. Expression analysis and Kaplan-Meier survival analysis were conducted in CPTAC lung adenocarcinomas cohort. Kaplan-Meier survival analysis and Cox proportional hazards regression were performed on these hub genes using TCGA and our own cohort. A total of 430 shared genes in all five datasets were identified as DEGs. Based on their PPI network, nine hub genes were selected and all of them were significantly associated with overall survival using GEPIA analysis. Two hub genes, TOP2A and UBE2C, were further combined and showed poorer prognosis in both TCGA dataset and our validated cohort. Analysis in CPTAC revealed that TOP2A and UBE2C were significantly highly expressed in tumor sample. Multivariable analysis suggested TOP2A and UBE2C as independent prognostic factors in LUAD. Using data mining approach, we identified TOP2A and UBE2C as two robust prognostic factors in LUAD. We also demonstrated the TOP2A/UBE2C co-expression status in LUAD, and TOP2A/UBE2C co-expression correlated with poorer prognosis. More in-depth research is needed for transforming this result into clinical setting.

Cooperative driver pathway discovery via fusion of multi-relational data of genes, miRNAs and pathways.

Discovering driver pathways is an essential step to uncover the molecular mechanism underlying cancer and to explore precise treatments for cancer patients. However, due to the difficulties of mapping genes to pathways and the limited knowledge about pathway interactions, most previous work focus on identifying individual pathways. In practice, two (or even more) pathways interplay and often cooperatively trigger cancer. In this study, we proposed a new approach called CDPathway to discover cooperative driver pathways. First, CDPathway introduces a driver impact quantification function to quantify the driver weight of each gene. CDPathway assumes that genes with larger weights contribute more to the occurrence of the target disease and identifies them as candidate driver genes. Next, it constructs a heterogeneous network composed of genes, miRNAs and pathways nodes based on the known intra(inter)-relations between them and assigns the quantified driver weights to gene-pathway and gene-miRNA relational edges. To transfer driver impacts of genes to pathway interaction pairs, CDPathway collaboratively factorizes the weighted adjacency matrices of the heterogeneous network to explore the latent relations between genes, miRNAs and pathways. After this, it reconstructs the pathway interaction network and identifies the pathway pairs with maximal interactive and driver weights as cooperative driver pathways. Experimental results on the breast, uterine corpus endometrial carcinoma and ovarian cancer data from The Cancer Genome Atlas show that CDPathway can effectively identify candidate driver genes [area under the receiver operating characteristic curve (AUROC) of $\geq $0.9] and reconstruct the pathway interaction network (AUROC of>0.9), and it uncovers much more known (potential) driver genes than other competitive methods. In addition, CDPathway identifies 150% more driver pathways and 60% more potential cooperative driver pathways than the competing methods. The code of CDPathway is available at http://mlda.swu.edu.cn/codes.php?name=CDPathway.

Comparative trachea transcriptome analysis between avian infectious bronchitis virus and avian pathogenic E. coli individual infection and co-infection in SPF chickens.

Avian infectious bronchitis virus (IBV) and avian pathogenic Escherichia coli (APEC) are two important respiratory pathogens in the chicken. The co-infection can lead to chronic complications and considerable economic losses in the poultry industry worldwide. In the present study, we compared differential transcriptional profiles in the trachea tissue of three infected groups (IBV, APEC, and co-infection) with the control group to investigate transcriptome profile changes at the early stage of the infection. After the challenge of SPF chickens with IBV IS-1494 like (GI-23) and APEC, serotype O78: K80, or co-infection, the trachea tissue was used for RNA extraction, and changes in the transcriptome were investigated by Illumina RNA-seq technique. Up-regulated and down-regulated differentially expressed genes (DEGs) in the transcriptome of each group's trachea were identified. Gene ontology category, KEGG pathway, and gene interaction networks (STRING analysis) were analyzed to identify relationships among differentially expressed genes. In general, the numbers of up-regulated genes were higher than of down-regulated genes. In the co-infection group, a more severe immune response and macrophage infiltration occurred; an important cluster of pathway signaling in this group's up-regulated genes was an apoptotic cluster, cytokine-mediated signaling cluster, and the PAMPs recognizing cluster. This is the first study to provide a general overview of transcriptome changes in the trachea at the early stage of infection with these pathogens. Keywords: avian infectious bronchitis virus; avian pathogenic E. coli; transcriptome; RNA-Seq.

GSTZ1-1 downregulates Wnt/β-catenin signalling in hepatocellular carcinoma cells.

Glutathione S‐transferase Zeta 1‐1 (GSTZ1‐1), an enzyme involved in the catabolism of phenylalanine and the detoxification of xenobiotics, plays a tumour suppressor role in hepatocellular carcinoma (HCC), but the underlying mechanism remains largely unknown. Here, we further explored the function of GSTZ1‐1 in HCC through transcriptome analysis by RNA sequencing. The analysis revealed that 223 genes were upregulated and 290 genes were downregulated in GSTZ1‐1‐overexpressing Huh7 cells. Gene Ontology analysis showed that these differentially expressed genes (DEGs) were highly enriched for protein phosphorylation, cell cycle arrest and metabolic processes. Pathway analysis revealed that metabolic pathways were the predominant enriched pathways among the upregulated genes, while the TGF‐β and Wnt/β‐catenin signalling pathways were prominent in the downregulated clusters. Pathway interaction networks also showed that the Wnt/β‐catenin pathway was located in the centre of the cluster. The expression levels of selected DEGs were validated by qRT‐PCR, and Wnt/β‐catenin involvement was validated by luciferase assays, western blotting and immunohistochemical analysis in vitro and in vivo. These results provide a comprehensive overview of the transcriptome in GSTZ1‐1‐overexpressing Huh7 cells and indicate that GSTZ1‐1 may play a tumour suppressor role by inactivating the Wnt/β‐catenin signalling pathway.

Bioinformatics analysis to screen key genes in papillary thyroid carcinoma.

Papillary thyroid carcinoma (PTC) is the most common type of thyroid carcinoma, and its incidence has been on the increase in recent years. However, the molecular mechanism of PTC is unclear and misdiagnosis remains a major issue. Therefore, the present study aimed to investigate this mechanism, and to identify key prognostic biomarkers. Integrated analysis was used to explore differentially expressed genes (DEGs) between PTC and healthy thyroid tissue. To investigate the functions and pathways associated with DEGs, Gene Ontology, pathway and protein-protein interaction (PPI) network analyses were performed. The predictive accuracy of DEGs was evaluated using the receiver operating characteristic (ROC) curve. Based on the four microarray datasets obtained from the Gene Expression Omnibus database, namely GSE33630, GSE27155, GSE3467 and GSE3678, a total of 153 DEGs were identified, including 66 upregulated and 87 downregulated DEGs in PTC compared with controls. These DEGs were significantly enriched in cancer-related pathways and the phosphoinositide 3-kinase-AKT signaling pathway. PPI network analysis screened out key genes, including acetyl-CoA carboxylase beta, cyclin D1, BCL2, and serpin peptidase inhibitor clade A member 1, which may serve important roles in PTC pathogenesis. ROC analysis revealed that these DEGs had excellent predictive performance, thus verifying their potential for clinical diagnosis. Taken together, the findings of the present study suggest that these genes and related pathways are involved in key events of PTC progression and facilitate the identification of prognostic biomarkers.

Analysis of long non-coding RNA and mRNA profiles in epicardial adipose tissue of patients with atrial fibrillation

Accumulating studies have suggested that epicardial adipose tissue (EAT) play an important role in the pathogenesis of atrial fibrillation (AF), but few have characterized the underlying mechanism between their interactions. Recent evidence suggested that bioactive molecules secreted from EAT, including exosomes carrying long non-coding RNAs (lncRNAs), may modulate atrial remodeling. LncRNAs are associated with cardiovascular disorders, including AF, but their roles in EAT remain elusive. The aim of the present study was to investigate the expression profile of lncRNAs in EAT with AF. Differentially expressed lncRNAs and nearby mRNAs interaction networks were constructed.Epicardial adipose samples were collected from patients with persistent non-valvular AF (n = 6) and sinus rhythm (SR) (n = 6), and the expression of lncRNAs and mRNAs were profiled using RNA-sequencing method.A total of 46,577 transcripts, including 35,552 protein-coding pattern, corresponding to 15,404 genes in EAT, among which, 655 mRNAs (265 upregulated and 390 downregulated) and 57 lncRNAs (17 upregulated and 40 downregulated) were differentially expressed between AF and SR (P < 0.05; fold change>1.5). GO enrichment, KEGG pathway analysis and interaction network construction showed that these differentially expressed lncRNAs were enriched in functional categories, including metabolism and stress response, which might contribute to the pathogenesis of AF.Our study demonstrated a differentially expressed lncRNA profile in EAT with AF, and provide a novel insight into the interactions between EAT and AF.

Predicting the Mechanism of the Analgesic Property of Yanhusuo Based on Network Pharmacology

Yanhusuo (Corydalis Rhizoma) extracts are widely used for the treatment of pain and inflammation. The effects of Yanhusuo in pain assays were assessed in a few studies. However, there are few studies on its analgesic mechanism. In this paper, network pharmacology was used to explore the analgesic components of Yanhusuo and its analgesic mechanism. The active components of Yanhusuo were screened by TCMSP database, combined with literature data. PharmMapper and GeneCards databases were used for screening the analgesic targets of the components. The protein interaction network diagram was drawn by String database and Cytoscape software, the gene ontology and KEGG pathway analyses of the target were performed by DAVID database, and the component–target–pathway interaction network diagram was further drawn by Cytoscape3.6.1 software. System Dock Web Site verified the molecular docking among components and targets. Finally, an interaction network of the component–target–pathway of Yanhusuo was constructed, and the functions and pathways were analyzed for preliminarily investigating the mechanism of Yanhusuo in analgesia. The results showed that the active components of analgesic in Yanhusuo were Corynoline, 13-methylpalmatrubine, dehydrocorydaline, saulatine, 2,3,9,10-tetramethoxy-13-methyl-5,6-dihydroisoquinolino[2,1-b]isoquinolin-8-on-e, and Capaurine. The mechanisms were involved in metabolic pathways, PI3k-Akt signaling pathway, pathways in cancer, and so on. The top 3 targets were NOS3, glucose-6-phosphate dehydrogenase, and glucose-6-phosphate isomerase in components-target-pathways network, and they were all enriched in metabolic pathways. Meanwhile the molecular docking showed that there was a high binding activity between the 6 components and the important target proteins, as a further certification for the subsequent network analysis. This study reveals the relationship of the components, targets, and pathways of active components in Yanhusuo, and provides new ideas and methods for further research on the analgesic mechanism of Yanhusuo.

Analysis and significance of circular RNA expression profile in clear cell renal cell carcinoma

Objective To detect the changes of expression of circular RNA (circRNA) in clear cell renal cell carcinoma (ccRCC) and adjacent renal tissue. Methods Four pairs of speicimen of renal clear cell carcinoma and adjacent renal parenchmal tissues diagnosed by pathology were collected and divided in two groups in the Department of Urology, First Affiliated Hospital of Zhengzhou University in December 2018. High-throughput sequencing of circRNA was done. The study analysed and compared expression profiles of circRNA for the two groups, statistically significant difference (P<0.05) were identified. Then we selected four differentially expressed circRNAs randomly for real-time quantitative reverse transcriptase-polymerase chain reaction (RT-qPCR) to verify the sequencing results. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein interaction network analysis were done for differential circRNA in two groups. Results 20668 circRNAs were found, main of them derived from the exon region of the parental gene. 578 circRNAs (|log2FC|≥1, P 0.05). GO and KEGG analysis showed that significantly differentially expressed circRNA involved in various biological processes such as ccRCC components, molecular functions, and signaling pathways. Protein interaction network analysis suggested that protein endcoded by the parental gene of differential circRNAs played important role. Conclusion circRNA, its parental gene and related encoded protein play an important role in the occurrence and development of ccRCC. Key words: Circular RNA; Clear cell renal cell carcinoma; Expression profile; Bioinformatics analysis

AGRP and ESPL1 as Biomarkers of Brain-Metastasis in Lung Adenocarcinoma

In the mortal diseases, lung cancer, approximately one fifth of lung adenocarcinoma(LUAD) patients are associated with brain metastasis(BM). And even some patients die of BM. In the present research, the 22753 genes data of 273 primary LUAD or BM samples were downloaded from gene expression omnibus(GEO) datasets. The 145 common differentially expressed genes(DEGs) both from GPL96 and GPL570 platform profiles were screened out by R package. Gene ontology(GO), pathway and protein protein interaction(PPI) network analysis of the DEGs was enriched by online tools. The 14 up- and 131 down-regulated genes were enriched in 18 GO terms and 147 signal pathway. Protein expression of AGRP and ESPL1 is lower in lung cancer than many other cancers. And the km-plots of lung cancer survival curves are also shown that AGRP and ESPL1 express higher in high risk groups. From the research in this paper, we can believe that AGRP and ESPL1 might be the biomarkers for the diagnostic clue of BM from LUAD.

Proteomic investigations of human HERC2 mutants: Insights into the pathobiology of a neurodevelopmental disorder

HERC2 is a giant protein with E3 ubiquitin ligase activity and other known and suspected functions. Mutations of HERC2 are implicated in the pathogenesis of various cancers and result in severe neurological conditions in Herc2-mutant mice. Recently, a pleotropic autosomal recessive HERC2-associated syndrome of intellectual disability, autism and variable neurological deficits was described; its pathogenetic basis is largely unknown. Using peripheral blood-derived lymphoblasts from 3 persons with homozygous HERC2 variants and 14 age- and gender-matched controls, we performed label-free unbiased HPLC-tandem mass spectrometry-based proteomic analyses to provide insights into HERC2-mediated pathobiology. We found that out of 3427 detected proteins, there were 812 differentially expressed proteins between HERC2-cases vs. controls. 184 canonical pathways were enriched after FDR adjustment, including mitochondrial function, energy metabolism, EIF2 signaling, immune functions, ubiquitination and DNA repair. Ingenuity Pathway Analysis® identified 209 upstream regulators that could drive the differential expression, prominent amongst which were neurodegeneration-associated proteins. Differentially expressed protein interaction networks highlighted themes of immune function/dysfunction, regulation of cell cycle/cell death, and energy metabolism. Overall, the analysis of the HERC2-associated proteome revealed striking differential protein expression between cases and controls. The large number of differentially expressed proteins likely reflects HERC2's multiple domains and numerous interacting proteins. Our canonical pathway and protein interaction network findings suggest derangements of multiple pathways in HERC2-associated disease.

Ki-67/MKI67 as a Predictive Biomarker for Clinical Outcome in Gastric Cancer Patients: an Updated Meta-analysis and Systematic Review involving 53 Studies and 7078 Patients.

Gastric cancer (GC) threatens human health worldwide and we performed this meta-analysis to evaluate the clinical value of Ki-67/MKI67 in patients with GC. The combined hazard ratio (HR), odds ratio (OR) and 95% confidence interval (95% CI) were calculated to assess the relationships of Ki-67/MKI67 expression with prognoses and clinicopathological characteristics. Genes co-expressed with MKI67 were collected for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) network analyses. In total, 53 studies with 7078 patients were included in this study. The pooled HRs indicated that an elevated expression of Ki-67/MKI67 predicted an unfavorable overall survival (HR: 1.54, 95% CI: 1.33-1.78, P<0.0001) and disease-free survival (HR: 2.28, 95% CI: 1.43-3.64, P<0.0001) in GC patients. Additionally, in patients with advanced GC, a high Ki-67/MKI67 expression was also significantly connected with OS (HR: 1.37, 95% CI: 1.18-1.60, P<0.0001). The combined ORs showed that Ki-67/MKI67 expression was related to TNM stage (stage III/IV versus stage I/II: OR=1.93, 95% CI=1.34-2.78, P<0.0001), tumor differentiation (poor versus well/moderate: OR=1.94, 95% CI=1.32-2.85, P=0.001), lymph node metastasis (yes versus no: OR=1.67, 95% CI=1.23-2.25, P=0.001), distant metastasis (yes versus no: OR=1.67, 95% CI=1.24-2.26, P=0.001) and tumor invasion depth (T3/T4 versus Tis/T1/T2: OR=1.98, 95% CI=1.60-2.44, P<0.0001). The results of GO, KEGG pathway and PPI network analyses indicated that Ki-67/MKI67 may be involved in the development of GC via influencing P53 signaling pathway. Ki-67/MKI67 could be a potential indicator to predict the prognosis of patients with GC and identify high-risk cases. Detecting Ki-67/MKI67 expression in clinic may be helpful in optimizing individual treatment and further improving the survival expectancy of patients with GC.

C1q and TNF related protein 1 regulates expression of inflammatory genes in vascular smooth muscle cells

C1q and TNF related protein 1 (C1QTNF1) is known to be associated with coronary artery diseases. However, the molecular function of C1QTNF1 on the vascular smooth muscles remains to be investigated. This study was therefore undertaken to investigate the effect of C1QTNF1 on gene expression of human smooth muscle cells and to reveal potential molecular mechanisms mediated by C1QTNF1. Vascular smooth muscle cells were incubated with recombinant C1QTNF1 for 16h, followed by determining any change in mRNA expressions by Affymetrix genechip. Gene ontology (GO), KEGG pathway, and protein-protein interaction (PPI) network were analyzed in differentially expressed genes. In addition, validation of microarray data was performed using quantitative real-time PCR. The mRNA expressions of annotated 74 genes were significantly altered after incubation with recombinant C1QTNF1; 41 genes were up-regulated and 33 down-regulated. The differentially expressed genes were enriched in biological processes and KEGG pathways associated with inflammatory responses. In the PPI network analysis, IL-6, CCL2, and ICAM1 were identified as potential key genes with relatively high degree. The cluster analysis in the PPI network identified a significant module composed of upregulated genes, such as IL-6, CCL2, NFKBIA, SOD2, and ICAM1. The quantitative real-time PCR results of potential key genes were consistent with microarray data. The results in the present study provide insights on the effects of C1QTNF1 on gene expression of smooth muscle cells. We believe our findings will help to elucidate the molecular mechanisms regarding the functions of C1QTNF1 on smooth muscle cells in inflammatory diseases.

Reactive Oxygen Species Induces Lipid Droplet Accumulation in HepG2 Cells by Increasing Perilipin 2 Expression.

Non-alcoholic fatty liver disease (NAFLD) has become the world’s most common liver disease. The disease can develop liver fibrosis or even carcinomas from the initial hepatic steatosis, and this process is influenced by many factors. Reactive oxygen species (ROS), as potent oxidants in cells, have been reported previously to play an important role in the development of NAFLD progression via promoting neutral lipid accumulation. Here, we found that ROS can promote lipid droplet formation in hepatocytes by promoting perilipin2 (PLIN2) expression. First, we used different concentrations of hydrogen peroxide to treat HepG2 cells and found that the number of lipid droplets in the cells increased, however also that this effect was dose-independent. Then, the mRNA level of several lipid droplet-associated genes was detected with hydrogen peroxide treatment and the expression of PLIN2, PLIN5, and FSP27 genes was significantly up-regulated (p < 0.05). We overexpressed PLIN2 in HepG2 cells and found that the lipid droplets in the cells were markedly increased. Interference with PLIN2 inhibits ROS-induced lipid droplet formation, revealing that PLIN2 is a critical factor in this process. We subsequently analyzed the regulatory pathway and protein interaction network that is involved in PLIN2 and found that PLIN2 can regulate intracellular lipid metabolism through the PPARα/RXRA and CREB/CREBBP signaling pathways. The majority of the data indicated the correlation between hydrogen peroxide-induced PLIN2 and lipid droplet upregulation. In conclusion, ROS up-regulates the expression of PLIN2 in hepatocytes, whereas PLIN2 promotes the formation of lipid droplets resulting in lipid accumulation in liver tissues.

Identification of intracellular peptides associated with thermogenesis in human brown adipocytes.

Currently, brown adipose tissue (BAT) is a therapeutic target in obesity and diabetes, but the mechanism of BAT activation remains unclear. Because increasing emphasis has been placed on the role of intracellular peptides in biological processes, we conducted a study to gain insight into the mechanism of BAT activation by using a peptidomic approach and then attempted to identify peptides that are capable of activating BAT. In the presentstudy, we generated the peptidomic profile of the intracellular peptides in brown adipocytes treated with forskolin (FSK) using a peptidomic approach. Then, the differentially expressed peptides were evaluated via Gene Ontology (GO) enrichment, KEGG pathway, and protein-protein interaction (PPI) network analysis. Finally, we selected candidate peptides for further validation via assessing the expression levels of UCP-1 and PGC-1α in brown adipocytes exposed to the peptides. A total of 4,370 peptides were identified, of which 951 were upregulated and 379 were downregulated after FSK treatment. Bioinformatic analysis demonstrated that the ECM-receptor interaction GO term was the most enriched and that collagen alpha-related proteins exhibited the highest degree of PPI. Four peptides separately derived from TSC22 domain family protein 1 (T22D1), bromodomain and WD repeat-containing protein 1 (BRWD1), protein piccolo (PCLO), and collagen alpha-1 (III) chain (CO3A1) increased the expression levels of UCP-1 and PGC-1α. ECM-receptor interaction may play an important role in the process of FSK-stimulated BAT activation, and the pT22D1tide, pBRWD1tide, pPCLOtide, and pCO3A1tide peptides potentially promote BAT thermogenesis.

Integrated analysis of hepatic mRNA and miRNA profiles identified molecular networks and potential biomarkers of NAFLD

To enhance our understanding of molecular mechanisms and mine novel biomarkers of non-alcoholic fatty liver disease (NAFLD), RNA sequencing was performed to gain hepatic expression profiles of mRNAs and miRNAs in NAFLD and normal rats. Using DESeq with thresholds of a two-fold change and a false discovery rate (FDR) less than 0.05, 336 mRNAs and 21 miRNAs were identified as differentially expressed. Among those, 17 miRNAs (e.g., miR-144-3p, miR-99a-3p, miR-200b-3p, miR-200b-5p, miR-200c-3p, etc.) might serve as novel biomarkers of NAFLD. MiRNA target genes (13565) were predicted by the miRWalk database. Using DAVID 6.8, the intersection (195 genes) of differentially expressed mRNAs and miRNA-predicted target genes were enriched in 47 gene ontology (GO) terms and 28 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Using Cytoscape, pathway interaction and protein-protein interaction (PPI) networks were constructed, and hub genes (e.g., Abcg8, Cyp1a1, Cyp51, Hmgcr, etc.) associated with NAFLD were obtained. Moreover, 673 miRNA-mRNA negative regulatory pairs were obtained, and networks were constructed. Finally, several representative miRNAs and mRNAs were validated by real-time qPCR. In conclusion, potential molecular mechanisms of NAFLD could be inferred from integrated analysis of mRNA and miRNA profiles, which may indicate novel biomarkers of NAFLD.

Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata.

The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C) in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata, identifying the existence of a turning point (on day 3) at which P. radiata plants changed from an initial stress response program (shorter-term response) to an acclimation one (longer-term response). Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs), fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata, with zeatin riboside (ZR) and isopentenyl adenosine (iPA) as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata, as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin), crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature.