N-acetylglucosamine transporter, Ngt1, undergoes sugar-responsive endosomal trafficking in Candida albicans

N-acetylglucosamine sensing in the filamentous soil fungus Trichoderma reesei

N-acetylglucosamine (GlcNAc) is involved in diverse signaling pathways in dimorphic yeasts and bacteria and is related to morphogenetic switching, mating, stress, virulence, and cell death. Recently, GlcNAc has been shown to promote plant growth by shaping the bacterial soil community. However, the role of GlcNAc sensing in filamentous soil fungi has not been investigated. By using Trichoderma reesei as a model organism, we show here that GlcNAc impacts the expression of around 2100 genes. Carbohydrate metabolism, amino acid metabolism, and secondary metabolism were the three most strongly affected classes of eukaryotic orthologous groups (KOG classes). Two key regulators of GlcNAc catabolism, the NDT80 domain-containing transcriptional regulator RON1, and a GlcNAc sensor, NGS1, are needed for differential regulation of two-thirds of these genes. In silico structural modeling of NGS1 identified a domain with homology to the GCN5-related histone acetyltransferase from Candida albicans, which serves as a GlcNAc catabolism regulator and GlcNAc sensor. Finally, we characterized the third regulator of GlcNAc sensing in T. reesei, which is the highly specific GlcNAc transporter N-acetylglucosamine transporter (NGT1). Using a deletion mutant of ngt1, we demonstrate that GlcNAc has to enter the cell to activate the GlcNAc catabolic gene expression. Interestingly, in contrast to dimorphic yeasts, the pathways for defense and pathogenicity seem to be induced in T. reesei by external GlcNAc. Given the ancestral role of Trichoderma spp. in the fungal kingdom and the highly conserved GlcNAc catabolism cluster that includes their regulators in many species of fungi, we propose a regulatory network for GlcNAc sensing in soil fungi.

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

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.

Role of cellulose response transporter-like protein CRT2 in cellulase induction in Trichoderma reesei

BACKGROUND

Induction of cellulase in cellulolytic fungi Trichoderma reesei is strongly activated by cellulosic carbon sources. The transport of cellulosic inducer and the perception of inducing signal is generally considered as the critical process for cellulase induction, that the inducing signal would be perceived by a sugar transporter/transceptor in T. reesei. Several sugar transporters are coexpressed during the induction stage, but which function they serve and how they work collaboratively are still difficult to elucidate.

RESULTS

In this study, we found that the constitutive expression of the cellulose response transporter-like protein CRT2 (previously identified as putative lactose permease TRE77517) improves cellulase induction on a cellulose, cellobiose or lactose medium. Functional studies indicate that the membrane-bound CRT2 is not a transporter of cellobiose, lactose or glucose in a yeast system, and it also does not affect cellobiose and lactose utilization in T. reesei. Further study reveals that CRT2 has a slightly similar function to the cellobiose transporter CRT1 in cellulase induction. Overexpression of CRT2 led to upregulation of CRT1 and the key transcription factor XYR1. Moreover, overexpression of CRT2 could partially compensate for the function loss of CRT1 on cellulase induction.

CONCLUSIONS

Our study uncovers the novel function of CRT2 in cellulase induction collaborated with CRT1 and XYR1, possibly as a signal transductor. These results deepen the understanding of the influence of sugar transporters in cellulase production.