scholarly journals 3β, 6β-dichloro-5-hydroxy-5α-cholestane facilitates neuronal development through modulating TrkA signaling regulated proteins in primary hippocampal neuron

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Md. Abdul Hannan ◽  
Md. Nazmul Haque ◽  
Raju Dash ◽  
Mahboob Alam ◽  
Il Soo Moon
Keyword(s):  
Neuronal Differentiation ◽  
Neurodegenerative Disorders ◽  
Hippocampal Neurons ◽  
Neuronal Development ◽  
Interaction Network ◽  
Underlying Mechanism ◽  
Bioinformatic Analysis ◽  
Pharmacological Intervention ◽  
Protein Protein Interaction ◽  
Neurotrophic Activity

AbstractPotentiating neuritogenesis through pharmacological intervention might hold therapeutic promise in neurodegenerative disorders and acute brain injury. Here, we investigated the novel neuritogenic potentials of a steroidal chlorohydrin, 3β, 6β-dichloro-5-hydroxy-5α-cholestane (hereafter, SCH) and the change in cellular proteome to gain insight into the underlying mechanism of its neurotrophic activity in hippocampal neurons. Morphometric analysis showed that SCH promoted early neuronal differentiation, dendritic arborization and axonal maturation. Proteomic and bioinformatic analysis revealed that SCH induced upregulation of several proteins, including those associated with neuronal differentiation and development. Immunocytochemical data further indicates that SCH-treated neurons showed upregulation of Hnrnpa2b1 and Map1b, validating their proteomic profiles. In addition, a protein-protein interaction network analysis identified TrkA as a potential target connecting most of the upregulated proteins. The neurite outgrowth effect of SCH was suppressed by TrkA inhibitor, GW441756, verifying TrkA-dependent activity of SCH, which further supports the connection of TrkA with the upregulated proteins. Also, the computational analysis revealed that SCH interacts with the NGF-binding domain of TrkA through Phe327 and Asn355. Collectively, our findings provide evidence that SCH promotes neuronal development via upregulating TrkA-signaling proteins and suggest that SCH could be a promising therapeutic agent in the prevention and treatment of neurodegenerative disorders.

scholarly journals Bioinformatic Analysis of Neuroimmune Mechanism of Neuropathic Pain

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Hao Yu ◽  
Yang Liu ◽  
Chao Li ◽  
Jianhao Wang ◽  
Bo Yu ◽  
...  
Keyword(s):  
Neuropathic Pain ◽  
Inflammatory Responses ◽  
Interaction Network ◽  
Gene Interaction ◽  
Bioinformatic Analysis ◽  
Venn Diagram ◽  
Hub Genes ◽  
Gene Interaction Network ◽  
Pathway Enrichment ◽  
Protein Protein Interaction

Background. Neuropathic pain (NP) is a devastating complication following nerve injury, and it can be alleviated by regulating neuroimmune direction. We aimed to explore the neuroimmune mechanism and identify some new diagnostic or therapeutic targets for NP treatment via bioinformatic analysis. Methods. The microarray GSE18803 was downloaded and analyzed using R. The Venn diagram was drawn to find neuroimmune-related differentially expressed genes (DEGs) in neuropathic pain. Gene Ontology (GO), pathway enrichment, and protein-protein interaction (PPI) network were used to analyze DEGs, respectively. Besides, the identified hub genes were submitted to the DGIdb database to find relevant therapeutic drugs. Results. A total of 91 neuroimmune-related DEGs were identified. The results of GO and pathway enrichment analyses were closely related to immune and inflammatory responses. PPI analysis showed two important modules and 8 hub genes: PTPRC, CD68, CTSS, RAC2, LAPTM5, FCGR3A, CD53, and HCK. The drug-hub gene interaction network was constructed by Cytoscape, and it included 24 candidate drugs and 3 hub genes. Conclusion. The present study helps us better understand the neuroimmune mechanism of neuropathic pain and provides some novel insights on NP treatment, such as modulation of microglia polarization and targeting bone resorption. Besides, CD68, CTSS, LAPTM5, FCGR3A, and CD53 may be used as early diagnostic biomarkers and the gene HCK can be a therapeutic target.

scholarly journals Multiplexed profiling of kinase interactomes quantifies cellular network plasticity

2021 ◽  
Author(s):  
Martin Golkowski ◽  
Andrea Lius ◽  
Tanmay S Sapre ◽  
Ho-Tak Lau ◽  
Taylor Moreno ◽  
...  
Keyword(s):  
Epithelial Mesenchymal Transition ◽  
Interaction Network ◽  
Pharmacological Intervention ◽  
High Plasticity ◽  
Mesenchymal Transition ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Native Cell ◽  
Cancer Types ◽  
Cancer Cell Signaling

Cells utilize protein-protein interaction (PPI) networks to receive, transduce, and respond to stimuli. Interaction network rewiring drives devastating diseases like cancers, making PPIs attractive targets for pharmacological intervention. Kinases are druggable nodes in PPI networks but high-throughput proteomics approaches to quantify disease-associated kinome PPI rewiring are lacking. We introduce kinobead competition and correlation analysis (Ki-CCA), a chemoproteomics approach to simultaneously map hundreds of endogenous kinase PPIs. We identified 2,305 PPIs of 300 kinases across 18 diverse cancer lines, quantifying the high plasticity of interaction networks between cancer types, signaling, and phenotypic states; this database of dynamic kinome PPIs provides deep insights into cancer cell signaling. We discovered an AAK1 complex promoting epithelial-mesenchymal transition and drug resistance, and depleting its components sensitized cells to targeted therapy. Ki-CCA enables rapid and highly multiplexed mapping of kinome PPIs in native cell and tissue lysates, without epitope tagged baits, protein labeling, or antibodies.

scholarly journals Versican V1 Isoform Induces Neuronal Differentiation and Promotes Neurite Outgrowth

2004 ◽  
Vol 15 (5) ◽  
pp. 2093-2104 ◽  
Author(s):  
Yaojiong Wu ◽  
Wang Sheng ◽  
Liwen Chen ◽  
Haiheng Dong ◽  
Vivian Lee ◽  
...  
Keyword(s):  
Epidermal Growth Factor Receptor ◽  
Growth Factor ◽  
Epidermal Growth Factor ◽  
Neurite Outgrowth ◽  
Neuronal Differentiation ◽  
Hippocampal Neurons ◽  
Neuronal Development ◽  
Growth Factor Receptor ◽  
Adult Brain ◽  
Epidermal Growth

The chondroitin sulfate proteoglycan versican is one of the major extracellular components in the developing and adult brain. Here, we show that isoforms of versican play different roles in neuronal differentiation and neurite outgrowth. Expression of versican V1 isoform in PC12 cells induced complete differentiation, whereas expression of V2 induced an aborted differentiation accompanied by apoptosis. V1 promoted neurite outgrowth of hippocampal neurons, but V2 failed to do so. V1 transfection enhanced expression of epidermal growth factor receptor and integrins, and facilitated sustained extracellular signal-regulated kinase/MAPK phosphorylation. Blockade of the epidermal growth factor receptor, β1 integrin, or Src significantly inhibited neuronal differentiation. Finally, we demonstrated that versican V1 isoform also promoted differentiation of neural stem cells into neurons. Our results have implications for understanding how versican regulates neuronal development, function, and repair.

scholarly journals Network Pharmacology-Based Strategy for the Investigation of the Anti-Obesity Effects of an Ethanolic Extract of Zanthoxylum bungeanum Maxim

2020 ◽  
Vol 11 ◽  
Author(s):  
Ying Wang ◽  
Song Hong Yang ◽  
Keying Zhong ◽  
Ting Jiang ◽  
Mi Zhang ◽  
...  
Keyword(s):  
Interaction Network ◽  
Ethanolic Extract ◽  
Underlying Mechanism ◽  
Network Pharmacology ◽  
Global Epidemic ◽  
Protein Protein Interaction ◽  
Target Network ◽  
Drug Ingredient ◽  
Zanthoxylum Bungeanum ◽  
Apoptotic Effects

Network pharmacology is considered as the next paradigm in drug discovery. In an era when obesity has become global epidemic, network pharmacology becomes an ideal tool to discover novel herbal-based therapeutics with effective anti-obesity effects. Zanthoxylum bungeanum Maxim (ZBM) is a medicinal herb. The mature pericarp of ZBM is used for disease treatments and as spice for cooking. Here, we used the network pharmacology approach to investigate whether ZBM possesses anti-obesity effects and reveal the underlying mechanism of action. We first built up drug–ingredient–gene symbol–disease network and protein–protein interaction network of the ZBM-related obesity targets, followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. The results highlight apoptosis as a promising signaling pathway that mediates the anti-obesity effects of ZBM. Molecular docking also reveals quercetin, a compound in ZBM has the highest degree of connections in the compound-target network and has direct bindings with the apoptotic markers. Furthermore, the apoptotic effects of ZBM are further validated in 3T3-L1 adipocytes and in the high-fat diet–induced obesity mouse model. These findings not only suggest ZBM can be developed as potential anti-obesity therapeutics but also demonstrate the application of network pharmacology for the discovery of herbal-based therapeutics for disease treatments.

Screening of Potential Biomarkers and Therapeutic Targets for T2DM-related Alzheimer's Disease Based on Bioinformatics Analysis

2021 ◽  
Author(s):  
Zhengqiang He
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Actin Filament ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Bioinformatic Analysis ◽  
Gene Expression Omnibus ◽  
Ppi Network ◽  
Protein Protein Interaction

Abstract More and more studies have suggested that type 2 diabetes mellitus (T2DM) was susceptible to trigger Alzheimer’s disease(AD), but the common underlying mechanism were unclear. We want to perform bioinformatic analysis with public databases. The T2DM dataset GSE95849 and AD dataset GSE97760 were selected from Gene Expression Omnibus (GEO) database. Then, we identified differentially expressed genes (DEGs) and the communal DEGs between the two diseases, which perform to the enrichment analysis, protein-protein interaction (PPI) network analysis, correlation analysis.We found 255 communal DEGs between T2DM and AD. They were enriched in negative regulation of actin filament depolymerization and regulation of actin filament depolymerization. Top 5 hub genes which identified from the PPI network were enriched in autophagy. The actin filament and autophagy may be the key association between the two diseases.

scholarly journals NMU Is a Poor Prognostic Biomarker in Patients with Lung Adenocarcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yan Tang ◽  
Chunsheng Hu
Keyword(s):  
Lung Adenocarcinoma ◽  
Gene Mutations ◽  
Interaction Network ◽  
Bioinformatic Analysis ◽  
Specific Gene ◽  
Aberrant Expression ◽  
Protein Protein Interaction ◽  
Web Resource ◽  
Kaplan Meier

Lung adenocarcinoma (LUAD) is the most prevalent histologic type of lung cancer, associated with a high incidence rate and substantial mortality rate worldwide. Accumulating evidence shows that the aberrant expression of neuromedin U (NMU) contributes to the initiation and progression of cancer. Herein, we explored whether NMU could be adopted as a new diagnostic and therapeutic marker in LUAD. The UALCAN and GEPIA web resources were employed to assess data on the NMU expression in LUAD. The STRING web resource was used to develop the PPI (protein-protein interaction) network of NMU, whereas Cytoscape was applied for module analysis. The Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of NMU and the interacting proteins were examined using the WebGestalt tool. Survival analysis was performed with the Kaplan-Meier plotter tool. Results revealed that the NMU expression in LUAD was significantly higher than in the nonmalignant tissues. Moreover, higher NMU levels were dramatically related to shorter overall survival, first progression survival, and postprogression survival. The specific gene mutations G45V, R143T, and F152L of NMU occurred in LUAD samples and were associated with a worse prognosis in patients. KEGG and western blot analyses demonstrated an association of NMU with the cell cycle and the cAMP signaling cascade. Bioinformatic analysis and the in vitro experiments implicated NMU as a promising prognostic signature and treatment target for LUAD.

scholarly journals Research on Potential Pathogenesis of Advanced Diabetic Nephropathy based on Bioinformatic Analysis

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Fang Liu ◽  
Boyi Li ◽  
Xibing Zhang ◽  
Yang Gao
Keyword(s):  
Diabetic Nephropathy ◽  
Kegg Pathway ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Signal Pathways ◽  
Protein Protein Interaction ◽  
Gene Chips ◽  
Protein Protein Interaction Network ◽  
Differential Genes

Objective: Through the bioinformatic analysis of gene chips related to advanced diabetic nephropathy in the GEO database, the key genes of advanced diabetic nephropathy are screened, whose biological functions and signal pathways are predicted as well. Methods: The gene chips related to advanced diabetic nephropathy from the GEO expression profile database was downloaded, and the differentially expressed genes in patients with advanced diabetic nephropathy and normal people were analyzed through R. For the screened differentially expressed genes, the biological function of GO and the enrichment analysis of KEGG signal pathway were used to predict their biological functions and related signal pathways. In addition, a protein-protein interaction network was constructed, so as to screen core pathogenic genes utilizing STRING database and Cytoscape. Results: By analyzing the chip GSE142025, 301 differential genes were obtained, including 197 up-regulated genes and 104 down-regulated genes. Both GO annotation and enrichment analysis suggested that differential genes were mainly involved in immune-inflammatory response and cytokine action. Furthermore, KEGG pathway analysis suggested that the most important pathway related to advanced diabetic nephropathy was MAPK signaling pathway. Through protein-protein interaction network and module analysis, C3, CCR2, CCL19, and SAA1 were selected as the core sites of the interaction. Conclusions: Differential genes participate in the pathogenesis of advanced diabetic nephropathy through the KEGG pathway, the immune inflammatory response and cytokine action, which provides new ways for the diagnosis and treatment of advanced diabetic nephropathy.

scholarly journals Integrate analysis and identification for different expression genes in chondrogenesis

2020 ◽  
Author(s):  
Keda Liu ◽  
Nanjue Cao ◽  
Yuhe Zhu ◽  
Wei Wang
Keyword(s):  
Interaction Network ◽  
Bioinformatic Analysis ◽  
Gene Expression Omnibus ◽  
Data Sets ◽  
Protein Protein Interaction ◽  
Related Data ◽  
Integrate Analysis ◽  
And Function ◽  
Microarray Datasets ◽  
Geo Database

Abstract Background: The intricate mechanisms of articular chondrogenesis are largely unknown. Gradually, with the help of high-throughput platforms, microarrays have become an important and useful method to testify hub genes in desease. Today, advanced bioinformatic analysis of available microarray data can provide more reliable and accurate screening results by duplicating related data sets. Results: Microarray datasets GSE9451 and GSE104113 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were performed, and function enrichment analyses were demonstrated. The protein-protein interaction network (PPI) was constructed and the module analysis was performed by using STRING and Cytoscape. Quantitative PCR was used to confirm the results of bioinformatics analysis. Conclusion: Compared to individual studies, this study can provide extra reliable and accurate screening results by duplicating relevant records. Additional molecular experiments are required to confirm the discovery of candidate genes identified by chondrogenesis. S100A4 is predicted to integrate with miR-325-3p to promote osteogenesis.

scholarly journals Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4674 ◽  
Author(s):  
Jianing Tang ◽  
Deguang Kong ◽  
Qiuxia Cui ◽  
Kun Wang ◽  
Dan Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Thyroid Cancer ◽  
Interaction Network ◽  
Bioinformatic Analysis ◽  
Differentially Expressed ◽  
Rank Test ◽  
Protein Protein Interaction ◽  
Kaplan Meier ◽  
Independent Risk Factors ◽  
Cancer Tissues

Thyroid cancer is one of the most common endocrine malignancies. Multiple evidences revealed that a large number of microRNAs and mRNAs were abnormally expressed in thyroid cancer tissues. These microRNAs and mRNAs play important roles in tumorigenesis. In the present study, we identified 72 microRNAs and 1,766 mRNAs differentially expressed between thyroid cancer tissues and normal thyroid tissues and evaluated their prognostic values using Kaplan-Meier survival curves by log-rank test. Seven microRNAs (miR-146b, miR-184, miR-767, miR-6730, miR-6860, miR-196a-2 and miR-509-3) were associated with the overall survival. Among them, three microRNAs were linked with six differentially expressed mRNAs (miR-767 was predicted to target COL10A1, PLAG1 and PPP1R1C; miR-146b was predicted to target MMP16; miR-196a-2 was predicted to target SYT9). To identify the key genes in the protein-protein interaction network , we screened out the top 10 hub genes (NPY, NMU, KNG1, LPAR5, CCR3, SST, PPY, GABBR2, ADCY8 and SAA1) with higher degrees. Only LPAR5 was associated with the overall survival. Multivariate analysis demonstrated that miR-184, miR-146b, miR-509-3 and LPAR5 were an independent risk factors for prognosis. Our results of the present study identified a series of prognostic microRNAs and mRNAs that have the potential to be the targets for treatment of thyroid cancer.

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