Gene Ontology and Pathway Enrichment Analysis

Microorganism is an important part of ecosystems; it is very sensitive to environmental change. In order to study the effects of sound on organisms, it’s meaningful to study mechanism of microbial exposure to sound. In our previous experiments, the effects of different sound intensity and frequency on the growth of E. coli K12 were studied. It was found that in stationary phase the bacteria concentration of sound expose group was higher than control. In this study, we aimed to understand the mechanisms of E. coli underlying sound expose by using Gene Ontology and KEGG Pathway Enrichment Analysis, and established a systematic pathway for the E. coli response to sound expose. At 6 hour, the chemotaxis pathway was significantly up-regulated which responses to the changes of the external environment and leads bacteria to favorable environment. At 12 hour, the glycerophospholipid pathway was significant up-regulated, it is related to the energy metabolism and cell division. At 24 hours, the energy metabolism, nucleotide synthesis and transcriptional translation pathways were significant differences. When bacteria entered the stationary phase (36 hour), in sound exposure group the pathways related to reduce the harmful substances were down-regulated and the pathways about degrade aromatic compounds provides energy were up-regulated, so that the E. coli K12 in sound exposure have a better ability to adapt poor living environment. Comparative transcriptome analysis of sound exposed E. coli K12 can not only reveal the behavior of E. coli K12 response to sound expose, but also lay a foundation for further study the mechanism of prokaryotes response to physical stimulus.

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The influence of metabolic network structures and energy metabolic pattern on E. coli K12 exposed to acoustic field: based on Gene Ontology and KEGG pathway enrichment analysis

10.7287/peerj.preprints.2821v1 ◽

2017 ◽

Cited By ~ 1

Author(s):

Shaobin Gu ◽

Suyu Qiao ◽

Ying Wu

Keyword(s):

Gene Ontology ◽

Energy Metabolism ◽

Stationary Phase ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Living Environment ◽

Pathway Enrichment Analysis ◽

E Coli ◽

Pathway Enrichment ◽

Sound Exposure

Microorganism is an important part of ecosystems; it is very sensitive to environmental change. In order to study the effects of sound on organisms, it’s meaningful to study mechanism of microbial exposure to sound. In our previous experiments, the effects of different sound intensity and frequency on the growth of E. coli K12 were studied. It was found that in stationary phase the bacteria concentration of sound expose group was higher than control. In this study, we aimed to understand the mechanisms of E. coli underlying sound expose by using Gene Ontology and KEGG Pathway Enrichment Analysis, and established a systematic pathway for the E. coli response to sound expose. At 6 hour, the chemotaxis pathway was significantly up-regulated which responses to the changes of the external environment and leads bacteria to favorable environment. At 12 hour, the glycerophospholipid pathway was significant up-regulated, it is related to the energy metabolism and cell division. At 24 hours, the energy metabolism, nucleotide synthesis and transcriptional translation pathways were significant differences. When bacteria entered the stationary phase (36 hour), in sound exposure group the pathways related to reduce the harmful substances were down-regulated and the pathways about degrade aromatic compounds provides energy were up-regulated, so that the E. coli K12 in sound exposure have a better ability to adapt poor living environment. Comparative transcriptome analysis of sound exposed E. coli K12 can not only reveal the behavior of E. coli K12 response to sound expose, but also lay a foundation for further study the mechanism of prokaryotes response to physical stimulus.

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An Integrated Analysis of Prognostic and Immune Infiltrates for Hub Genes as Potential Survival Indicators in Patients with Lung Adenocarcinoma

10.21203/rs.3.rs-900442/v1 ◽

2021 ◽

Author(s):

Zhiyun Xu ◽

Shi Wang ◽

Zhijian Ren ◽

Xiang Gao ◽

Lin Xu ◽

...

Keyword(s):

Cell Cycle ◽

Gene Ontology ◽

Lung Adenocarcinoma ◽

Immune Cells ◽

Enrichment Analysis ◽

Integrated Analysis ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Expression Levels ◽

Pathway Enrichment

Abstract Objective: Lung adenocarcinoma is one of the major subtypes of lung cancer. However, the prognosis of individuals with LUAD is still not promising. Therefore, this research aims to discover useful biomarkers to enhance the treatment and diagnosis of LUAD.Methods: GEO2R was used to identify common up-regulated DEGs in the GSE32863, GSE40791 and GSE75037. The DEGs were submitted to Metascape for gene ontology and pathway enrichment analysis. Metascape was also utilized to construct the PPI network, and the MCODE plug-in was employed to filter important subnetworks. The prognosis and expression levels of the hub genes were evaluated using the UALCAN, GEPIA2, and Kaplan-Meier plotter databases. The Timer database was utilized to confirm the correlation between immune cells infiltration and the expression levels of hub genes in LUAD tissues.Results: This research discovered 307 common up-regulated DEGs, and gene ontology and pathway enrichment analysis indicated that they were mostly enriched in mitotic cell cycle process and cell cycle pathway. DEGs in the subnetwork with the largest number of genes were AURKB, CCNB2, CDC20, CDCA5, CDCA8, CENPF and KNTC1. The seven hub genes were highly expressed in LUAD tissues and had a poor prognosis. AURKB, CCNB2, and CDC20 were inversely associated with B and CD4+ T cells. CDCA5, CDCA8, and CENPF have a substantially negative correlation with B Cell, but positive correlation with Neutrophil. Conclusions: This research demonstrates that increased expression of seven hub genes is associated with worse prognosis for LUAD patients. Additionally, immune cells infiltrating LUAD tissues may serve as a regulating mechanism.

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Faculty Opinions recommendation of Impact of outdated gene annotations on pathway enrichment analysis.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.726696046.793531028 ◽

2017 ◽

Author(s):

Peter Robinson

Keyword(s):

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Pathway Enrichment ◽

Gene Annotations

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A Method of Pathway Enrichment Analysis Based Gene Expression Variability

ACTA AGRONOMICA SINICA ◽

10.3724/sp.j.1206.2012.00410 ◽

2013 ◽

Vol 40 (12) ◽

pp. 1256

Author(s):

XiaoDong JIA ◽

XiuJie CHEN ◽

Xin WU ◽

JianKai XU ◽

FuJian TAN ◽

...

Keyword(s):

Gene Expression ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Expression Variability ◽

Pathway Enrichment

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Systematic Investigation of Quercetin for Treating Cardiovascular Disease Based on Network Pharmacology

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207322666190717124507 ◽

2019 ◽

Vol 22 (6) ◽

pp. 411-420 ◽

Cited By ~ 5

Author(s):

Xian-Jun Wu ◽

Xin-Bin Zhou ◽

Chen Chen ◽

Wei Mao

Keyword(s):

Cardiovascular Disease ◽

Cardiovascular Diseases ◽

Signaling Pathway ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Therapeutic Effects ◽

Pathway Enrichment ◽

Compound Target

Aim and Objective: Cardiovascular disease is a serious threat to human health because of its high mortality and morbidity rates. At present, there is no effective treatment. In Southeast Asia, traditional Chinese medicine is widely used in the treatment of cardiovascular diseases. Quercetin is a flavonoid extract of Ginkgo biloba leaves. Basic experiments and clinical studies have shown that quercetin has a significant effect on the treatment of cardiovascular diseases. However, its precise mechanism is still unclear. Therefore, it is necessary to exploit the network pharmacological potential effects of quercetin on cardiovascular disease. Materials and Methods: In the present study, a novel network pharmacology strategy based on pharmacokinetic filtering, target fishing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, compound-target-pathway network structured was performed to explore the anti- cardiovascular disease mechanism of quercetin. Results:: The outcomes showed that quercetin possesses favorable pharmacokinetic profiles, which have interactions with 47 cardiovascular disease-related targets and 12 KEGG signaling pathways to provide potential synergistic therapeutic effects. Following the construction of Compound-Target-Pathway (C-T-P) network, and the network topological feature calculation, we obtained top 10 core genes in this network which were AKT1, IL1B, TNF, IL6, JUN, CCL2, FOS, VEGFA, CXCL8, and ICAM1. KEGG pathway enrichment analysis. These indicated that quercetin produced the therapeutic effects against cardiovascular disease by systemically and holistically regulating many signaling pathways, including Fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, MAPK signaling pathway, IL-17 signaling pathway and PI3K-Akt signaling pathway.

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Signature RNAS and related regulatory roles in type 1 diabetes mellitus based on competing endogenous RNA regulatory network analysis

BMC Medical Genomics ◽

10.1186/s12920-021-00931-0 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Qinghong Shi ◽

Hanxin Yao

Keyword(s):

Diabetes Mellitus ◽

Type 1 Diabetes ◽

Network Analysis ◽

Type 1 Diabetes Mellitus ◽

Regulatory Network ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Competing Endogenous Rna ◽

Pathway Enrichment

Abstract Background Our study aimed to investigate signature RNAs and their potential roles in type 1 diabetes mellitus (T1DM) using a competing endogenous RNA regulatory network analysis. Methods Expression profiles of GSE55100, deposited from peripheral blood mononuclear cells of 12 T1DM patients and 10 normal controls, were downloaded from the Gene Expression Omnibus to uncover differentially expressed long non-coding RNAs (lncRNAs), mRNAs, and microRNAs (miRNAs). The ceRNA regulatory network was constructed, then functional and pathway enrichment analysis was conducted. AT1DM-related ceRNA regulatory network was established based on the Human microRNA Disease Database to carry out pathway enrichment analysis. Meanwhile, the T1DM-related pathways were retrieved from the Comparative Toxicogenomics Database (CTD). Results In total, 847 mRNAs, 41 lncRNAs, and 38 miRNAs were significantly differentially expressed. The ceRNA regulatory network consisted of 12 lncRNAs, 10 miRNAs, and 24 mRNAs. Two miRNAs (hsa-miR-181a and hsa-miR-1275) were screened as T1DM-related miRNAs to build the T1DM-related ceRNA regulatory network, in which genes were considerably enriched in seven pathways. Moreover, three overlapping pathways, including the phosphatidylinositol signaling system (involving PIP4K2A, INPP4A, PIP4K2C, and CALM1); dopaminergic synapse (involving CALM1 and PPP2R5C); and the insulin signaling pathway (involving CBLB and CALM1) were revealed by comparing with T1DM-related pathways in the CTD, which involved four lncRNAs (LINC01278, TRG-AS1, MIAT, and GAS5-AS1). Conclusion The identified signature RNAs may serve as important regulators in the pathogenesis of T1DM.

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Identification of novel cardiovascular disease associated metabolites using untargeted metabolomics

Biological Chemistry ◽

10.1515/hsz-2020-0331 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Shams Tabrez ◽

Mohammed Razeeth Shait Mohammed ◽

Nasimudeen R. Jabir ◽

Mohammad Imran Khan

Keyword(s):

Cardiovascular Disease ◽

Metabolic Pathways ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Healthy Individuals ◽

Great Opportunity ◽

Pathway Enrichment ◽

Pathophysiological Role ◽

The World ◽

Metabolomic Approach

Abstract Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality around the world. Early diagnosis of CVD could provide the opportunity for sensible management and better clinical outcome along with the prevention of further progression of the disease. In the current study, we used an untargeted metabolomic approach to identify possible metabolite(s) that associate well with the CVD and could serve either as therapeutic target or disease-associated metabolite. We identified 26 rationally adjusted unique metabolites that were differentially present in the serum of CVD patients compared with healthy individuals, among them 15 were found to be statistically significant. Out of these metabolites, we identified some novel metabolites like UDP-l-rhamnose and N1-acetylspermidine that have not been reported to be linked with CVD directly. Further, we also found that some metabolites like ethanolamide, solanidine, dimethylarginine, N-acetyl-l-tyrosine, can act as a discriminator of CVD. Metabolites integrating pathway enrichment analysis showed enrichment of various important metabolic pathways like histidine metabolism, methyl histidine metabolism, carnitine synthesis, along with arginine and proline metabolism in CVD patients. Our study provides a great opportunity to understand the pathophysiological role and impact of the identified unique metabolites and can be extrapolated as specific CVD specific metabolites.

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