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 (pho81Δ) and a constitutively activated PHO pathway mutant (pho80Δ) on fungal virulence. Irrespective of phosphate availability, the PHO pathway was derepressed in pho80Δ with all phosphate acquisition pathways upregulated and much of the excess phosphate stored as polyphosphate (polyP). Elevated phosphate in pho80Δ coincided with elevated metal ions, metal stress sensitivity, and a muted calcineurin response, all of which were ameliorated by phosphate depletion. In contrast, metal ion homeostasis was largely unaffected in the pho81Δ mutant, and Pi, polyP, ATP, and energy metabolism were reduced, even under phosphate-replete conditions. A similar decline in polyP and ATP suggests that polyP supplies phosphate for energy production even when phosphate is available. Using calcineurin reporter strains in the wild-type, pho80Δ, and pho81Δ background, we also demonstrate that phosphate deprivation stimulates calcineurin activation, most likely by increasing the bioavailability of calcium. Finally, we show that blocking, as opposed to permanently activating, the PHO pathway reduced fungal virulence in mouse infection models to a greater extent and that this is most likely attributable to depleted phosphate stores and ATP, and compromised cellular bioenergetics, irrespective of phosphate availability. IMPORTANCE Invasive fungal diseases cause more than 1.5 million deaths per year, with an estimated 181,000 of these deaths attributable to Cryptococcal meningitis. Despite the high mortality, treatment options are limited. In contrast to humans, fungal cells maintain phosphate homeostasis via a CDK complex, providing drug-targeting opportunities. To investigate which CDK components are the best targets for potential antifungal therapy, we used strains with a constitutively active (pho80Δ) and an activation-defective (pho81Δ) PHO pathway, to investigate the impact of dysregulated phosphate homeostasis on cellular function and virulence. Our studies suggest that inhibiting the function of Pho81, which has no human homologue, would have the most detrimental impact on fungal growth in the host due to depletion of phosphate stores and ATP, irrespective of phosphate availability in the host.

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. To gain insights into how C. glabrata adapts to adverse environmental conditions, we examined its transcriptional landscape under heat, osmotic, cell wall, oxidative, and genotoxic stresses using RNA sequencing and reveal that C. glabrata displays a diverse transcriptional response involving ∼75% of its genome for adaptation to different environmental stresses. C. glabrata mounts a central common adaptation response wherein ∼25% of all genes (n = 1370) are regulated in a similar fashion at different environmental stresses. Elevated cellular translation and diminished mitochondrial activity-associated transcriptional signature characterize the common adaptation response. Transcriptional regulatory association networks of common adaptation response genes revealed a set of 29 transcription factors acting as potential activators and repressors of associated adaptive response genes. Overall, the current work delineates the adaptive responses of C. glabrata to diverse environmental stresses and reports the existence of a common adaptive transcriptional response upon prolonged exposure to environmental stresses.

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. The platform contains many commonly used data analysis tools and an extensive collection of pre-processed public ribonucleic acid sequencing (RNA-seq) datasets of many fungal species, including important human, plant and insect pathogens. Users may analyse their data alone or in combination with public RNA-seq data for an integrated analysis. The FungiExpresZ platform helps wet-lab scientists to overcome their limitations in genomics data analysis and can be applied to analyse data of any organism. FungiExpresZ is available as an online web-based tool (https://cparsania.shinyapps.io/FungiExpresZ/) and an offline R-Shiny package (https://github.com/cparsania/FungiExpresZ).

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. We find that transcription in fully developed conidia is modulated in response to changes in the environment until conidia leave the developmental structure. Environment-specific transcriptional responses can alter conidial content (mRNAs, proteins and secondary metabolites) and change gene expression when dormancy is broken. Conidial transcription affects the fitness and capabilities of fungal cells after germination, including stress and antifungal drug (azole) resistance, mycotoxin and secondary metabolite production and virulence. The transcriptional variation that we characterize in fungal conidia explains how genetically identical conidia mature into phenotypically variable conidia. We find that fungal conidia prepare for the future by synthesizing and storing transcripts according to environmental conditions present before dormancy.

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. On a balanced benchmark dataset of 188 samples, Deep-AmPEP30 yields an improved performance of 77% in accuracy, 85% in the area under the receiver operating characteristic curve (AUC-ROC), and 85% in area under the precision-recall curve (AUC-PR) over existing machine learning-based methods. To demonstrate its power, we screened the genome sequence of Candida glabrata-a gut commensal fungus expected to interact with and/or inhibit other microbes in the gut-for potential AMPs and identified a peptide of 20 aa (P3, FWELWKFLKSLWSIFPRRRP) with strong anti-bacteria activity against Bacillus subtilis and Vibrio parahaemolyticus. The potency of the peptide is remarkably comparable to that of ampicillin. Therefore, Deep-AmPEP30 is a promising prediction tool to identify short-length AMPs from genomic sequences for drug discovery. Our method is available at https://cbbio.cis.um.edu.mo/AxPEP for both individual sequence prediction and genome screening for AMPs.

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. Previous studies had successfully identified a transcription response to oxidative stress including induction of a core set of detoxification genes. However, the findings only represent an early snapshot of a highly dynamic process lacking temporal resolution. Here, we compare the transcriptome of C. glabrata at various points after exposure to hydrogen peroxide in order to study its adaptation to an oxidative environment. Our results reveal global and temporal gene expression changes during an immediate response; up-regulating genes related to peroxide detoxification, while down-regulating genes essential for growth. As cells adapt to the oxidative environment, a dramatic transcriptome reprogramming occurred to restore key cellular functions, protein homeostasis and biosynthesis of trehalose, carbohydrate, fatty acid and ergosterol. Interestingly, biofilm and drug transporter genes as well as many genes implicated in virulence, were induced during the adaptation stage. Our finding, therefore, suggests a role of oxidative stress adaptation in promoting virulence and drug resistance traits of C. glabrata during infection.