Transcriptomic meta-analysis to identify potential antifungal targets in Candida albicans

作者：Zeinab Abdelmoghis Hefny, Boyang Ji, Ibrahim E. Elsemman, Jens Nielsen, Patrick Van Dijck · 发表于：BMC Microbiology · 年份：2024 · DOI：10.1186/s12866-024-03213-8 · 被引用次数：14 · 研究领域：Antifungal resistance and susceptibility、Fungal Infections and Studies、Microbial Natural Products and Biosynthesis

BACKGROUND: Candida albicans is a fungal pathogen causing human infections. Here we investigated differential gene expression patterns and functional enrichment in C. albicans strains grown under different conditions. METHODS: A systematic GEO database search identified 239 "Candida albicans" datasets, of which 14 were selected after rigorous criteria application. Retrieval of raw sequencing data from the ENA database was accompanied by essential metadata extraction from dataset descriptions and original articles. Pre-processing via the tailored nf-core pipeline for C. albicans involved alignment, gene/transcript quantification, and diverse quality control measures. Quality assessment via PCA and DESeq2 identified significant genes (FDR < = 0.05, log2-fold change > = 1 or <= -1), while topGO conducted GO term enrichment analysis. Exclusions were made based on data quality and strain relevance, resulting in the selection of seven datasets from the SC5314 strain background for in-depth investigation. RESULTS: The meta-analysis of seven selected studies unveiled a substantial number of genes exhibiting significant up-regulation (24,689) and down-regulation (18,074). These differentially expressed genes were further categorized into 2,497 significantly up-regulated and 2,573 significantly down-regulated Gene Ontology (GO) IDs. GO term enrichment analysis clustered these terms into distinct groups, providing insights into the functional implications. Three target gene lists were c...