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Abstract：
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 compiled based on previous studies, focusing on central metabolism, ion homeostasis, and pathogenicity. Frequency analysis revealed genes with higher occurrence within the identified GO clusters, suggesting their potential as antifungal targets. Notably, the genes TPS2, TPS1, RIM21, PRA1, SAP4, and SAP6 exhibited higher frequencies within the clusters. Through frequency analysis within the GO clusters, several key genes emerged as potential targets for antifungal therapies. These include RSP5, GLC7, SOD2, SOD5, SOD1, SOD6, SOD4, SOD3, and RIM101 which exhibited higher occurrence within the identified clusters.
CONCLUSIONS: This comprehensive study significantly advances our understanding of the dynamic nature of gene expression in C. albicans. The identification of genes with enhanced potential as antifungal drug targets underpins their value for future interventions. The highlighted genes, including TPS2, TPS1, RIM21, PRA1, SAP4, SAP6, RSP5, GLC7, SOD2, SOD5, SOD1, SOD6, SOD4, SOD3, and RIM101, hold promise for the development of targeted antifungal therapies.
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 compiled based on previous studies, focusing on central metabolism, ion homeostasis, and pathogenicity. Frequency analysis revealed genes with higher occurrence within the identified GO clusters, suggesting their potential as antifungal targets. Notably, the genes TPS2, TPS1, RIM21, PRA1, SAP4, and SAP6 exhibited higher frequencies within the clusters. Through frequency analysis within the GO clusters, several key genes emerged as potential targets for antifungal therapies. These include RSP5, GLC7, SOD2, SOD5, SOD1, SOD6, SOD4, SOD3, and RIM101 which exhibited higher occurrence within the identified clusters.
CONCLUSIONS: This comprehensive study significantly advances our understanding of the dynamic nature of gene expression in C. albicans. The identification of genes with enhanced potential as antifungal drug targets underpins their value for future interventions. The highlighted genes, including TPS2, TPS1, RIM21, PRA1, SAP4, SAP6, RSP5, GLC7, SOD2, SOD5, SOD1, SOD6, SOD4, SOD3, and RIM101, hold promise for the development of targeted antifungal therapies.
摘要：
背景：白色念珠菌是一种引起人类感染的真菌病原体。在这里，我们研究了在不同条件下生长的白色念珠菌菌株的差异基因表达模式和功能富集。
方法：系统的GEO数据库搜索确定了239个“白色念珠菌”数据集，其中14个是在严格的标准应用后选出的。从ENA数据库中检索原始测序数据伴随着从数据集描述和原始文章中提取的基本元数据。通过为白色念珠菌量身定制的nf核心管道进行预处理，涉及对齐，基因/转录物定量，和多样化的质量控制措施。通过PCA和DESeq2进行的质量评估确定了重要基因（FDR<=0.05，log2倍变化>=1或<=-1），而topGO进行了GO术语富集分析。根据数据质量和应变相关性进行排除，从而从SC5314菌株背景中选择七个数据集进行深入研究。
结果：对7项选定研究的荟萃分析揭示了大量基因表现出显着的上调（24,689）和下调（18,074）。这些差异表达的基因被进一步分类为2,497个显著上调的和2,573个显著下调的基因本体(GO)ID。GO术语富集分析将这些术语聚集到不同的组中，提供对功能含义的见解。根据以前的研究编制了三个目标基因列表，专注于中枢代谢，离子稳态，和致病性。频率分析显示，在已识别的GO簇内出现的基因较高，表明它们作为抗真菌靶标的潜力。值得注意的是,基因TPS2，TPS1，RIM21，PRA1，SAP4和SAP6在簇内表现出更高的频率。通过GO集群内的频率分析，几个关键基因成为抗真菌治疗的潜在靶点.这些包括RSP5，GLC7，SOD2，SOD5，SOD1，SOD6，SOD4，SOD3和RIM101，它们在鉴定的簇中表现出更高的发生率。
结论：这项全面的研究极大地促进了我们对白色念珠菌基因表达动态性质的理解。具有增强的抗真菌药物靶标潜力的基因的鉴定为其未来干预措施的价值奠定了基础。突出的基因，包括TPS2，TPS1，RIM21，PRA1，SAP4，SAP6，RSP5，GLC7，SOD2，SOD5，SOD1，SOD6，SOD4，SOD3和RIM101，有望开发靶向抗真菌疗法。
方法：系统的GEO数据库搜索确定了239个“白色念珠菌”数据集，其中14个是在严格的标准应用后选出的。从ENA数据库中检索原始测序数据伴随着从数据集描述和原始文章中提取的基本元数据。通过为白色念珠菌量身定制的nf核心管道进行预处理，涉及对齐，基因/转录物定量，和多样化的质量控制措施。通过PCA和DESeq2进行的质量评估确定了重要基因（FDR<=0.05，log2倍变化>=1或<=-1），而topGO进行了GO术语富集分析。根据数据质量和应变相关性进行排除，从而从SC5314菌株背景中选择七个数据集进行深入研究。
结果：对7项选定研究的荟萃分析揭示了大量基因表现出显着的上调（24,689）和下调（18,074）。这些差异表达的基因被进一步分类为2,497个显著上调的和2,573个显著下调的基因本体(GO)ID。GO术语富集分析将这些术语聚集到不同的组中，提供对功能含义的见解。根据以前的研究编制了三个目标基因列表，专注于中枢代谢，离子稳态，和致病性。频率分析显示，在已识别的GO簇内出现的基因较高，表明它们作为抗真菌靶标的潜力。值得注意的是,基因TPS2，TPS1，RIM21，PRA1，SAP4和SAP6在簇内表现出更高的频率。通过GO集群内的频率分析，几个关键基因成为抗真菌治疗的潜在靶点.这些包括RSP5，GLC7，SOD2，SOD5，SOD1，SOD6，SOD4，SOD3和RIM101，它们在鉴定的簇中表现出更高的发生率。
结论：这项全面的研究极大地促进了我们对白色念珠菌基因表达动态性质的理解。具有增强的抗真菌药物靶标潜力的基因的鉴定为其未来干预措施的价值奠定了基础。突出的基因，包括TPS2，TPS1，RIM21，PRA1，SAP4，SAP6，RSP5，GLC7，SOD2，SOD5，SOD1，SOD6，SOD4，SOD3和RIM101，有望开发靶向抗真菌疗法。
