Transcriptomic meta-analysis to identify potential antifungal targets in Candida albicans
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”...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2024-02-01
|
| Series: | BMC Microbiology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12866-024-03213-8 |
| _version_ | 1797275590346145792 |
|---|---|
| author | Zeinab Abdelmoghis Hefny Boyang Ji Ibrahim E. Elsemman Jens Nielsen Patrick Van Dijck |
| author_facet | Zeinab Abdelmoghis Hefny Boyang Ji Ibrahim E. Elsemman Jens Nielsen Patrick Van Dijck |
| author_sort | Zeinab Abdelmoghis Hefny |
| collection | DOAJ |
| description | 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. Conclusion 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. |
| first_indexed | 2024-03-07T15:16:39Z |
| format | Article |
| id | doaj.art-002bfa64d52043538e51836a4af544a6 |
| institution | Directory Open Access Journal |
| issn | 1471-2180 |
| language | English |
| last_indexed | 2024-03-07T15:16:39Z |
| publishDate | 2024-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Microbiology |
| spelling | doaj.art-002bfa64d52043538e51836a4af544a62024-03-05T17:51:42ZengBMCBMC Microbiology1471-21802024-02-0124111910.1186/s12866-024-03213-8Transcriptomic meta-analysis to identify potential antifungal targets in Candida albicansZeinab Abdelmoghis Hefny0Boyang Ji1Ibrahim E. Elsemman2Jens Nielsen3Patrick Van Dijck4Laboratory of Molecular Cell Biology, Department of Biology, Katholieke Universiteit LeuvenBioInnovation InstituteDepartment of Information Systems, Faculty of Computers and Information, Assiut UniversityBioInnovation InstituteLaboratory of Molecular Cell Biology, Department of Biology, Katholieke Universiteit LeuvenAbstract 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. Conclusion 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.https://doi.org/10.1186/s12866-024-03213-8Candida albicansHigh-throughput sequencingDifferentially expressed genesGO enrichmentAntifungal targets |
| spellingShingle | Zeinab Abdelmoghis Hefny Boyang Ji Ibrahim E. Elsemman Jens Nielsen Patrick Van Dijck Transcriptomic meta-analysis to identify potential antifungal targets in Candida albicans BMC Microbiology Candida albicans High-throughput sequencing Differentially expressed genes GO enrichment Antifungal targets |
| title | Transcriptomic meta-analysis to identify potential antifungal targets in Candida albicans |
| title_full | Transcriptomic meta-analysis to identify potential antifungal targets in Candida albicans |
| title_fullStr | Transcriptomic meta-analysis to identify potential antifungal targets in Candida albicans |
| title_full_unstemmed | Transcriptomic meta-analysis to identify potential antifungal targets in Candida albicans |
| title_short | Transcriptomic meta-analysis to identify potential antifungal targets in Candida albicans |
| title_sort | transcriptomic meta analysis to identify potential antifungal targets in candida albicans |
| topic | Candida albicans High-throughput sequencing Differentially expressed genes GO enrichment Antifungal targets |
| url | https://doi.org/10.1186/s12866-024-03213-8 |
| work_keys_str_mv | AT zeinababdelmoghishefny transcriptomicmetaanalysistoidentifypotentialantifungaltargetsincandidaalbicans AT boyangji transcriptomicmetaanalysistoidentifypotentialantifungaltargetsincandidaalbicans AT ibrahimeelsemman transcriptomicmetaanalysistoidentifypotentialantifungaltargetsincandidaalbicans AT jensnielsen transcriptomicmetaanalysistoidentifypotentialantifungaltargetsincandidaalbicans AT patrickvandijck transcriptomicmetaanalysistoidentifypotentialantifungaltargetsincandidaalbicans |