scholarly journals Insulin-Like Peptide Receptor-Mediated Signaling Pathways Orchestrate Regulation of Growth in the Pacific Oyster (Crassostrea gigas), as Revealed by Gene Expression Profiles

2021 ◽  
Vol 22 (10) ◽  
pp. 5259
Author(s):  
Yongjing Li ◽  
Huiru Fu ◽  
Fuqiang Zhang ◽  
Liting Ren ◽  
Jing Tian ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Signaling Pathway ◽  
Crassostrea Gigas ◽  
Growth Regulation ◽  
Pacific Oyster ◽  
Expression Profiles ◽  
Growth Factor Signaling ◽  
Bioinformatics Analyses ◽  
Peptide Receptor ◽  
Downstream Signaling

The involvement of insulin/insulin-like growth factor signaling (IIS) pathways in the growth regulation of marine invertebrates remains largely unexplored. In this study, we used a fast-growing Pacific oyster (Crassostrea gigas) variety “Haida No.1” as the material with which to unravel the role of IIS systems in growth regulation in oysters. Systematic bioinformatics analyses allowed us to identify major components of the IIS signaling pathway and insulin-like peptide receptor (ILPR)-mediated signaling pathways, including PI3K-AKT, RAS-MAPK, and TOR, in C. gigas. The expression levels of the major genes in IIS and its downstream signaling pathways were significantly higher in “Haida No.1” than in wild oysters, suggesting their involvement in the growth regulation of C. gigas. The expression profiles of IIS and its downstream signaling pathway genes were significantly altered by nutrient abundance and culture temperature. These results suggest that the IIS signaling pathway coupled with the ILPR-mediated signaling pathways orchestrate the regulation of energy metabolism to control growth in Pacific oysters.

scholarly journals Insulin-like peptide receptor mediated signaling pathways orchestrate regulation of energy homeostasis in the Pacific oyster, Crassostrea gigas

2021 ◽  
Author(s):  
Yongjing Li ◽  
Huiru Fu ◽  
Fuqiang Zhang ◽  
Liting Ren ◽  
Jing Tian ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Signaling Pathway ◽  
Crassostrea Gigas ◽  
Energy Homeostasis ◽  
Growth Regulation ◽  
Pacific Oyster ◽  
Peptide Receptor ◽  
Fast Growing ◽  
Downstream Signaling ◽  
The Pacific

AbstractThe involvement of insulin/insulin-like growth factor (IIS) signaling pathway in growth regulation of marine invertebrates remains largely unexplored. In this study, we used a fast-growing Pacific oyster (Crassostrea gigas) variety “Haida No.1” as material to unravel the role of IIS system in growth regulation in oysters. Systematic bioinformatics analyses allowed to identify major components of IIS signaling pathway and insulin-like peptide receptor (ILPR) mediated signaling pathways, including PI3K-AKT, RAS-MAPK, and TOR, in C. gigas. Expression levels of the major genes in IIS and its downstream signaling pathways were significantly higher in “Haida No.1” than wild oysters, suggesting their involvement in growth regulation of C. gigas. Expression profiles of IIS and its downstream signaling pathway genes were significantly altered by nutrient abundance and culture temperature. These results suggested that IIS signaling pathway coupled with the ILPR mediated signaling pathways orchestrated energy homeostasis to regulate growth in the Pacific oyster.Research HighlightsILPR, IRS, IGFBPRP, and IGFALS genes were characterized in the C. gigas.Major genes of IIS signaling pathway were highly expressed in fast-growing C. gigas.IIS and downstream pathways participates in energy homeostasis of oysters.ILPR mediated signaling pathways orchestrate growth regulation in oysters.

scholarly journals Electroacupuncture Alleviates Experimental Chronic Inflammatory Pain by Inhibiting Calcium Voltage-Gated Channel-Mediated Inflammation

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Jie Zhou ◽  
Ying Jin ◽  
Ruijie Ma ◽  
Hongyun Song ◽  
Qin Chen ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Inflammatory Pain ◽  
Expression Profiles ◽  
Arachidonic Acid Metabolism ◽  
Receptor Interaction ◽  
Bioinformatics Analyses ◽  
Protein Coding ◽  
Chronic Inflammatory Pain ◽  
Gated Channel ◽  
Pathway Analyses

Background. Both experimental and clinical studies have shown that electroacupuncture (EA) administration ameliorates chronic inflammatory pain (CIP). However, the multifaceted mechanism underlying the effects of EA on CIP is poorly understood. In this study, the mRNA transcriptome was used to study various therapeutic targets of EA. Methods. Using RNA-sequencing, protein-coding mRNA expression profiles of the L4-L5 dorsal root ganglion (DRG) were examined in the control (CN), complete Freund’s adjuvant- (CFA-) induced CIP, and EA-treated CIP groups. A series of bioinformatics analyses was performed; “EA-reversed upregulated genes with CIP” (up-DEGs) and “EA-reversed downregulated genes with CIP” (down-DEGs) were identified. Thereafter, based on up-DEGs and down-DEGs, biological functions and signaling pathways were enriched using gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses. Results. In total, 189 DEGs were identified, including 134 up- and 55 down-DEGs, which were enriched in arachidonic acid metabolism (rno00590), glutamatergic synapse (rno04724), serotonergic synapse (rno04726), FoxO signaling pathway (rno04068), insulin signaling pathway (rno04910), amyotrophic lateral sclerosis (rno05014), cholinergic synapse (rno04725), ECM-receptor interaction (rno04512), and choline metabolism in cancer (rno05231). Conclusion. We identified a few GOs, pathways, and genes that could play key roles in the amelioration of CIP by EA. Hence, this study may provide a theoretical basis for CIP amelioration by EA.

scholarly journals Identifying hub genes and immune infiltration of osteoarthritis using comprehensive bioinformatics analysis

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Zheng-yuan Wu ◽  
Gang Du ◽  
Yi-cai Lin
Keyword(s):  
Gene Expression ◽  
Signaling Pathway ◽  
Cell Activation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Joint Space ◽  
Mast Cell Activation ◽  
Healthy Controls ◽  
Bioinformatics Analyses ◽  
Immune Infiltration

Abstract Background Osteoarthritis (OA) is the most common chronic degenerative joint disorder globally that is characterized by synovitis, cartilage degeneration, joint space stenosis, and sub-cartilage bone hyperplasia. However, the pathophysiologic mechanisms of OA have not been thoroughly investigated. Methods In this study, we conducted various bioinformatics analyses to identify hub biomarkers and immune infiltration in OA. The gene expression profiles of synovial tissues from 29 healthy controls and 36 OA samples were obtained from the gene expression omnibus database to identify differentially expressed genes (DEGs). The CIBERSORT algorithm was used to explore the association between immune infiltration and arthritis. Results Eighteen hub DEGs were identified as critical biomarkers for OA. Through gene ontology and pathway enrichment analyses, it was found that these DEGs were primarily involved in PI3K-Akt signaling pathway and Rap1 signaling pathway. Furthermore, immune infiltration analysis revealed differences in immune infiltration between patients with OA and healthy controls. The hub gene ZNF160 was closely related to immune cells, especially mast cell activation in OA. Conclusion Overall, this study presented a novel method to identify hub DEGs and their correlation with immune infiltration, which may provide novel insights into the diagnosis and treatment of patients with OA.

scholarly journals Comprehensive Analysis of Differentially Expressed mRNA, Non-coding RNA, and Their Competitive Endogenous RNA Network of Pacific Oyster Crassostrea gigas With Different Glycogen Content Between Different Environments

2021 ◽  
Vol 8 ◽  
Author(s):  
Xue Wang ◽  
Weijun Wang ◽  
Zan Li ◽  
Guohua Sun ◽  
Tao Xu ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Signaling Pathway ◽  
Crassostrea Gigas ◽  
Glycogen Content ◽  
Pacific Oyster ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Non Coding Rna ◽  
Huanghai Sea

Glycogen content is a quantitative trait, its phenotype differences are found between individual oysters due to genetic effects and environmental factors which were including food, water temperature, salinity, and so on. In this study, a full sibling family of Pacific oyster Crassostrea gigas showed different phenotypes with high and low glycogen content between South Huanghai Sea (Rizhao offshore area, RZ) and North Huanghai Sea (Kongtong Dao area, KTD), respectively. At the same time, the content of 11 glucogenic amino acids and 13 fatty acids were also significant differences between RZ and KTD. RNA-seq and small RNA-seq technologies were used for transcriptome sequencing and functional enrichment analysis of differentially expressed RNA were used by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. A total of 2,084 mRNAs, 1,080 long non-coding RNAs (lncRNAs), 34 circular RNAs (circRNAs), and 7 microRNAs (miRNAs) were differentially expressed. Based on these differentially expressed genes (DEGs), miRNA target interactions (lncRNA/circRNA–miRNA pairs and miRNA–mRNA pairs) were predicted using the miRanda software. The differentially expressed mRNAs in this network were mainly shown to be involved in calcium signaling pathway and insulin signaling pathway. These findings could help to speculate that environmental factors may be epigenetically regulated by non-coding RNA in C. gigas, thereby further affecting glycogen content.

scholarly journals Classification of ovarian cancer associated with BRCA1 mutations, immune checkpoints, and tumor microenvironment based on immunogenomic profiling

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10414
Author(s):  
Yousheng Wei ◽  
Tingyu Ou ◽  
Yan Lu ◽  
Guangteng Wu ◽  
Ying Long ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Interleukin 17 ◽  
Brca1 Mutations ◽  
Gene Sets ◽  
Subtype 3

Background Ovarian cancer is a highly fatal gynecological malignancy and new, more effective treatments are needed. Immunotherapy is gaining attention from researchers worldwide, although it has not proven to be consistently effective in the treatment of ovarian cancer. We studied the immune landscape of ovarian cancer patients to improve the efficacy of immunotherapy as a treatment option. Methods We obtained expression profiles, somatic mutation data, and clinical information from The Cancer Genome Atlas. Ovarian cancer was classified based on 29 immune-associated gene sets, which represented different immune cell types, functions, and pathways. Single-sample gene set enrichment (ssGSEA) was used to quantify the activity or enrichment levels of the gene sets in ovarian cancer, and the unsupervised machine learning method was used sort the classifications. Our classifications were validated using Gene Expression Omnibus datasets. Results We divided ovarian cancer into three subtypes according to the ssGSEA score: subtype 1 (low immunity), subtype 2 (median immunity), and subtype 3 (high immunity). Most tumor-infiltrating immune cells and immune checkpoint molecules were upgraded in subtype 3 compared with those in the other subtypes. The tumor mutation burden (TMB) was not significantly different among the three subtypes. However, patients with BRCA1 mutations were consistently detected in subtype 3. Furthermore, most immune signature pathways were hyperactivated in subtype 3, including T and B cell receptor signaling pathways, PD-L1 expression and PD-1 checkpoint pathway the NF-κB signaling pathway, Th17 cell differentiation and interleukin-17 signaling pathways, and the TNF signaling pathway. Conclusion Ovarian cancer subtypes that are based on immune biosignatures may contribute to the development of novel therapeutic treatment strategies for ovarian cancer.

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