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

Hefny, Zeinab Abdelmoghis (author)
Katholieke Universiteit Leuven
Ji, Boyang (author)
BioInnovation Institute (BII)
El-Semman, Ibrahim, 1977 (author)
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Nielsen, Jens B, 1962 (author)
Chalmers tekniska högskola,Chalmers University of Technology,BioInnovation Institute (BII)
Van Dijck, Patrick (author)
Katholieke Universiteit Leuven
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 (creator_code:org_t)
2024
2024
English.
In: BMC Microbiology. - 1471-2180. ; 24:1
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • 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.

Subject headings

NATURVETENSKAP  -- Biologi -- Mikrobiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Microbiology (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Mikrobiologi inom det medicinska området (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Microbiology in the medical area (hsv//eng)
NATURVETENSKAP  -- Biologi -- Bioinformatik och systembiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cancer and Oncology (hsv//eng)

Keyword

Candida albicans
Differentially expressed genes
GO enrichment
Antifungal targets
High-throughput sequencing

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