Transcriptome analysis reveals a common adaptive transcriptional response of Candida glabrata to diverse environmental stresses.

Candida glabrata, an opportunistic fungal pathogen, causes superficial and life-threatening infections in humans. In the host microenvironment, C. glabrata encounters a variety of stresses, and its ability to cope with these stresses is crucial for its pathogenesis.

Dysregulating PHO Signaling via the CDK Machinery Differentially Impacts Energy Metabolism, Calcineurin Signaling, and Virulence in Cryptococcus neoformans.

Fungal pathogens uniquely regulate phosphate homeostasis via the cyclin-dependent kinase (CDK) signaling machinery of the phosphate acquisition (PHO) pathway (Pho85 kinase-Pho80 cyclin-CDK inhibitor Pho81), providing drug-targeting opportunities. Here, we investigate the impact of a PHO pathway activation-defective Cryptococcus neoformans mutant (Δ) and a constitutively activated PHO pathway mutant (Δ) on fungal virulence. Irrespective of phosphate availability, the PHO pathway was derepressed in Δ with all phosphate acquisition pathways upregulated and much of the excess phosphate stored as polyphosphate (polyP).

FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery.

Bioinformatics analysis and visualization of high-throughput gene expression data require extensive computer programming skills, posing a bottleneck for many wet-lab scientists. In this work, we present an intuitive user-friendly platform for gene expression data analysis and visualization called FungiExpresZ. FungiExpresZ aims to help wet-lab scientists with little to no knowledge of computer programming to become self-reliant in bioinformatics analysis and generating publication-ready figures.

Transcription in fungal conidia before dormancy produces phenotypically variable conidia that maximize survival in different environments.

Fungi produce millions of clonal asexual conidia (spores) that remain dormant until favourable conditions occur. Conidia contain abundant stable messenger RNAs but the mechanisms underlying the production of these transcripts and their composition and functions are unknown. Here, we report that the conidia of three filamentous fungal species (Aspergillus nidulans, Aspergillus fumigatus, Talaromyces marneffei) are transcriptionally active and can synthesize mRNAs.

Deep-AmPEP30: Improve Short Antimicrobial Peptides Prediction with Deep Learning.

Antimicrobial peptides (AMPs) are a valuable source of antimicrobial agents and a potential solution to the multi-drug resistance problem. In particular, short-length AMPs have been shown to have enhanced antimicrobial activities, higher stability, and lower toxicity to human cells. We present a short-length (≤30 aa) AMP prediction method, Deep-AmPEP30, developed based on an optimal feature set of PseKRAAC reduced amino acids composition and convolutional neural network.

Transcriptomic analysis reveals global and temporal transcription changes during Candida glabrata adaptation to an oxidative environment.

The ability to survive host-elicited oxidative stress is critical for microbial pathogens to cause infection. The human fungal pathogen C.glabrata can tolerate high levels of oxidative stress and proliferate inside phagocytes.