ArticleEuropean journal of medical research2022
Identification of differentially expressed genes and signaling pathways with Candida infection by bioinformatics analysis.
Article in European journal of medical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Transcriptomic meta-analysis to identify potential antifungal targets in Candida albicans.BMC microbiology · 2024Pooled it
- Research progress on BTG2 in non‑tumor diseases (Review).International journal of molecular medicine · 2026Review
- Transdifferentiated BLaER1 cells as a genetically tractable model to study the interaction of pathogenic fungi with macrophages.Disease models & mechanisms · 2026Article
- The Dual Roles of Activating Transcription Factor 3 (ATF3) in Inflammation, Apoptosis, Ferroptosis, and Pathogen Infection Responses.International journal of molecular sciences · 2024Review
- Coexpression network analysis of human candida infection reveals key modules and hub genes responsible for host-pathogen interactions.Frontiers in genetics · 2022Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundOpportunistic Candida species causes severe infections when the human immune system is weakened, leading to high mortality.
methodsIn our study, bioinformatics analysis was used to study the high-throughput sequencing data of samples infected with four kinds of Candida species. And the hub genes were obtained by statistical analysis.
resultsA total of 547, 422, 415 and 405 differentially expressed genes (DEGs) of Candida albicans, Candida glabrata, Candida parapsilosis and Candida tropicalis groups were obtained, respectively. A total of 216 DEGs were obtained after taking intersections of DEGs from the four groups. A protein-protein interaction (PPI) network was established using these 216 genes. The top 10 hub genes (FOSB, EGR1, JUNB, ATF3, EGR2, NR4A1, NR4A2, DUSP1, BTG2, and EGR3) were acquired through calculation by the cytoHubba plug-in in Cytoscape software. Validated by the sequencing data of peripheral blood, JUNB, ATF3 and EGR2 genes were significant statistical significance.
conclusionsIn conclusion, our study demonstrated the potential pathogenic genes in Candida species and their underlying mechanisms by bioinformatic analysis methods. Further, after statistical validation, JUNB, ATF3 and EGR2 genes were attained, which may be used as potential biomarkers with Candida species infection.
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