The Identification of Key Genes and Biological Pathways in Cardiac Arrest by Integrated Bioinformatics and Next Generation Sequencing Data Analysis

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 19, 2024

Abstract Cardiac arrest (CA) is a common cause of death world wide. The disease has lacks effective treatment. Efforts have been made to elucidate the molecular pathogenesis CA, but mechanisms remain elusive. To identify key genes and pathways in next generation sequencing (NGS) GSE200117 dataset was downloaded from Gene Expression Omnibus (GEO) database. DESeq2 tool used recognize differentially expressed (DEGs). ontology (GO) REACTOME pathway enrichment analyses were performed analyze DEGs associated signal g:Profiler IID database construct protein-protein interaction (PPI) network, modules analysis using Cytoscape. A miRNA-hub gene regulatory network TF-hub then constructed screen miRNAs, TFs hub by miRNet NetworkAnalyst Cityscape software. Receiver operating characteristic curve (ROC) verified genes. In total, 844 identified, comprising 414 up regulated 430 down GO indicated that for CA mainly enriched organonitrogen compound metabolic process, response stimulus, translation immune system. Ten (up-regulated: HSPA8, HOXA1, INCA1 TP53; down-regulated: HSPB1, LMNA, SNCA, ADAMTSL4 PDLIM7) screened. We also predicted miRNAs (hsa-mir-1914-5p hsa-mir-598-3p) (JUN PRRX2) targeting This study uses series bioinformatics technologies obtain hug genes, TFs, related CA. These results provide us with new ideas finding biomarkers treatment methods

Language: Английский

---

Identification of virus-rich intermediate cells as crucial players in SARS-CoV-2 infection and differentiation dynamics of human airway epithelium

Frontiers in Microbiology, Journal Year: 2024, Volume and Issue: 15

Published: Dec. 13, 2024

Understanding the early interactions between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and human airway epithelial cells is essential for unraveling viral replication spread mechanisms. In this study, we investigated dynamics of during SARS-CoV-2 infection using well-differentiated nasal tracheal cell cultures by incorporating three publicly available single-cell RNA sequencing datasets. We identified a previously uncharacterized population, termed virus-rich intermediate (VRI) cells, representing an differentiation stage basal ciliated cells. These VRI exhibited high loads at all time points, strong interferon inflammatory responses, increased mRNA expression microvilli-related genes (PAK1, PAK4, VIL1), suppression apoptosis markers (BAX, CASP3) alongside anti-apoptotic gene (BCL2). Cell-cell interaction analysis revealed that send signals to via receptor-ligand pathways such as EPHA VEGF, likely promoting proliferation through MAPK signaling. findings suggest utilizes primary site spread, leveraging these cells’ unique state evade host death facilitate propagation. This study provides insights into cellular responses highlights potential therapeutic targets limit spread.

Language: Английский

---

Identification of novel key genes and signaling pathways in hypertrophic cardiomyopathy: evidence from bioinformatics and next generation sequencing data analysis

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 15, 2024

Abstract Hypertrophic cardiomyopathy (HCM) is a global health problem characterized by left ventricle become thick and stiff with effect of indication including chest pain, fluttering, fainting shortness breath. In this investigation, we aimed to identify diagnostic markers analyzed the therapeutic potential essential genes. Next generation sequencing (NGS) dataset GSE180313 was obtained from Gene Expression Omnibus (GEO) database used differentially expressed genes (DEGs) in HCM. DEGs were screened using DESeq2 Rbioconductor tool. Then, Ontology (GO) REACTOME pathway enrichment analyses performed. Moreover, protein-protein interaction (PPI) network constructed, module analysis Next, miRNA-hub gene regulatory TF-hub constructed analyzed. Finally, values hub assessed receiver operating characteristic (ROC) curve analysis. By performing analysis, total 958 (479 up regulated 479 down genes) successfully identified GSE180313, respectively. GO revealed that functions signaling pathways significantly enriched response stimulus, multicellular organismal process, metabolism extracellular matrix organization. The FN1, SOX2, TUBA4A, RPS2, TUBA1C, ESR1, SNCA, LCK, PAK1 APLNR might be associated gens FN1 TPM3, together corresponding predicted miRNAs (e.g., hsa-mir-374a-5p hsa-miR-8052), SH3KBP1 ESR1 TFs (e.g PRRX2 STAT3) found correlated This investigation could serve as basis for further understanding molecular pathogenesis targets

Language: Английский

---