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. 2023 Nov 17;11(11):2798.
doi: 10.3390/microorganisms11112798.

Metabolome and Transcriptome Combinatory Profiling Reveals Fluconazole Resistance Mechanisms of Trichosporon asahii and the Role of Farnesol in Fluconazole Tolerance

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Metabolome and Transcriptome Combinatory Profiling Reveals Fluconazole Resistance Mechanisms of Trichosporon asahii and the Role of Farnesol in Fluconazole Tolerance

Xiaoping Ma et al. Microorganisms. .

Abstract

Trichosporon asahii is a basidiomycete yeast that is pathogenic to humans and animals, and fluconazole-resistant strains have recently increased. Farnesol secreted by fungi is a factor that causes variations in fluconazole resistance; however, few studies have explored the underlying mechanisms. Therefore, this study aims to delineate the fluconazole resistance mechanisms of T. asahii and explore farnesol's effects on these processes. A comparative metabolome-transcriptome analysis of untreated fluconazole-sensitive (YAN), fluconazole-resistant (PB) T. asahii strains, and 25 μM farnesol-treated strains (YAN-25 and PB-25, respectively) was performed. The membrane lipid-related genes and metabolites were upregulated in the PB vs. YAN and PB-25 vs. PB comparisons. Farnesol demonstrated strain-dependent mechanisms underlying fluconazole tolerance between the YAN and PB strains, and upregulated and downregulated efflux pumps in PB-25 and YAN-25 strains, respectively. Membrane lipid-related metabolites were highly correlated with transporter-coding genes. Fluconazole resistance in T. asahii was induced by membrane lipid bio-synthesis activation. Farnesol inhibited fluconazole resistance in the sensitive strain, but enhanced resistance in the resistant strain by upregulating efflux pump genes and membrane lipids. This study offers valuable insights into the mechanisms underlying fungal drug resistance and provides guidance for future research aimed at developing more potent antifungal drugs for clinical use.

Keywords: Trichosporon asahii; farnesol; fluconazole resistance; metabolome; transcriptome.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
KEGG enrichment analysis of DEGs in (a) PB vs. YAN, (b) YAN-25 vs. YAN, (c) PB-25 vs. PB, and (d) PB-25 vs. YAN-25. The Y-axis represents the KEGG pathway, and the X-axis shows the number of DEGs in each pathway.
Figure 2
Figure 2
Heatmap of the DEGs implicated in efflux pump regulation among (A) PB vs. YAN, (B) YAN-25 vs. YAN, (C) PB-25 vs. PB, and (D) PB-25 vs. YAN-25. Blue indicates low expression levels, and red indicates high expression levels. Colored blocks along the Y-axis of the heatmap represent the family to which each gene belongs.
Figure 3
Figure 3
Heatmap of the DEGs implicated in membrane lipids based on the (a) PB vs. YAN and (b) PB-25 vs. PB comparisons. Blue indicates low expression levels, and red indicates high expression levels.
Figure 4
Figure 4
KEGG pathway assignment of differentially expressed metabolites among PB vs. YAN, YAN-25 vs. YAN, PB-25 vs. PB, and PB-25 vs. YAN-25. The dot color represents the p-value, and the dot size represents the number of differentially expressed metabolites.
Figure 5
Figure 5
Heatmap of the differentially expressed metabolites implicated in membrane lipids among (a) PB vs. YAN and (b) PB-25 vs. PB. Blue indicates low expression levels, and red indicates high expression levels.
Figure 6
Figure 6
Association analysis of transcriptomic and metabolomic variations. Connection network between screened differentially expressed metabolites and DEGs in (a) PB vs. YAN and (b) PB-25 vs. PB. Red and purple ovals in the nodes represent differentially expressed metabolites and DEGs, respectively. The size of each node indicates the degree of betweenness centrality. The lines represent the “relationships” between differentially expressed metabolites and DEGs; yellow and blue represent positive and negative correlations, respectively; and the thickness of the lines indicates the strength of the relationship.

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