Background The skin is the largest organ of the body and has multiple functions. Wounds remain a significant healthcare problem due to the large number of traumatic and pathophysiological conditions patients suffer. Methods Gene expression profiles of 37 biopsies collected from patients undergoing split-thickness skin grafts at five different time points were downloaded from two datasets (GSE28914 and GSE50425) in the Gene Expression Omnibus (GEO) database. Principal component analysis (PCA) was applied to classify samples into different phases. Subsequently, differentially expressed genes (DEGs) analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway functional enrichment analyses were performed, and protein–protein interaction (PPI) networks created for each phase. Furthermore, based on the results of the PPI, hub genes in each phase were identified by molecular complex detection combined with the ClueGO algorithm. Results Using principal component analysis, the collected samples were divided into four phases, namely intact phase, acute wound phase, inflammatory and proliferation phase, and remodeling phase. Intact samples were used as control group. In the acute wound phase, a total of 1 upregulated and 100 downregulated DEGs were identified. Tyrosinase (TYR), tyrosinase Related Protein 1 (TYRP1) and dopachrome tautomerase (DCT) were considered as hub genes and enriched in tyrosine metabolism which dominate the process of melanogenesis. In the inflammatory and proliferation phase, a total of 85 upregulated and 164 downregulated DEGs were identified. CHEK1, CCNB1 and CDK1 were considered as hub genes and enriched in cell cycle and P53 signaling pathway. In the remodeling phase, a total of 121 upregulated and 49 downregulated DEGs were identified. COL4A1, COL4A2, and COL6A1 were considered as hub genes and enriched in protein digestion and absorption, and ECM-receptor interaction. Conclusion This comprehensive bioinformatic re-analysis of GEO data provides new insights into the molecular pathogenesis of wound healing and the potential identification of therapeutic targets for the treatment of wounds.
Acacia crassicarpa (Fabaceae), a nitrogen-fixing tree species, is critically important for coastal protection in southeast China. In this study, we report the complete chloroplast genome sequence of A. crassicarpa, with a length of 176,493 bp. It contains a pair of inverted repeats (IR 39,851 bp), a large single-copy region (LSC 91,869 bp), and a small single-copy region (SSC 4,922 bp). The complete genome comprises 138 genes, including 93 protein-coding genes, 37 tRNA, and 8 rRNA genes. Our phylogenetic analysis reveals that A. crassicarpa is closely related to A. podalyriifolia and A. dealbata.
The skin is the largest organ of the body and has many functions. Skin wound has become a significant healthcare problem due to the increasing number of trauma and pathophysiological conditions. In an attempt to achieve a more comprehensive understanding of the molecular pathogenesis of wound healing (WH), gene expression profiles of 37 biopsies collected from patients undergoing split-thickness skin graft at five different time points were downloaded from two data sets (GSE28914 and GSE50425) in the Gene Expression Omnibus (GEO) database. According to the principal component analysis, the collected samples were divided into four phases, which are intact phase, acute wound phase, inflammation phase and remodelling phase. Subsequently, different expression genes, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway functional enrichment analyses and protein-protein interaction (PPI) network were performed in each phase. Furthermore, based on the PPI results, hub genes in each phase were identified by Molecular Complex Detection combined with ClueGO algorithm. This comprehensive bioinformatic re-analysis of GEO data provides new insights into the molecular pathogenesis of WH and the potential identification of therapeutic targets for the treatment of WH.
BackgroundsIdentification of hub genes (HGs) using transcriptome data of epithelial membrane protein 2 (EMP2) treated human retinal pigment epithelial cells (hRPECs) samples was helpful to accurately evaluate the functional relevance of genetic alterations in activity proteins (APs) in these cells.ResultsWe performed differential expression genes (DEGs) analyses of public RNA-seq transcriptome data of EMP2 treated hRPECs, victor control (VC) and wild type (WT) hRPECs. VIPER (Virtual Inference of Protein activity by Enriched Regulon analysis) was used to convert DEGs outcomes to APs signatures and ARACNE (Algorithm for the Reconstruction of Accurate Cellular Networks) was used to construct transcription regulatory networks (TRNs) to identify hub genes (HGs). ConclusionsIn addition to identifying a significant fraction of DEGs among EMP2-OE groups and EMP-KD groups when compared to VC or WT groups, respectively, we also accurately inferred aberrant TGNs and found several HGs induced by EMP2-overexpressed hRPECs under hypoxia. Thus, we raise a hypothesis that EMP2 may regulate hRPECs angiogenesis via a PDGFA regulatory network, which would help to understand the complex biology of angiogenesis in EMP2 and hypoxia treated hRPECs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.