A fungal lytic polysaccharide monooxygenase is required for cell wall integrity, thermotolerance, and virulence of the fungal human pathogen Cryptococcus neoformans.
Corinna ProbstMagnus Hallas-MøllerJohan Ø IpsenJacob T BrooksKarsten AndersenMireille HaonJean-Guy BerrinHelle J MartensConnie B NicholsKatja S JohansenJ Andrew AlspaughPublished in: PLoS pathogens (2023)
Fungi often adapt to environmental stress by altering their size, shape, or rate of cell division. These morphological changes require reorganization of the cell wall, a structural feature external to the cell membrane composed of highly interconnected polysaccharides and glycoproteins. Lytic polysaccharide monooxygenases (LPMOs) are copper-dependent enzymes that are typically secreted into the extracellular space to catalyze initial oxidative steps in the degradation of complex biopolymers such as chitin and cellulose. However, their roles in modifying endogenous microbial carbohydrates are poorly characterized. The CEL1 gene in the human fungal pathogen Cryptococcus neoformans (Cn) is predicted by sequence homology to encode an LPMO of the AA9 enzyme family. The CEL1 gene is induced by host physiological pH and temperature, and it is primarily localized to the fungal cell wall. Targeted mutation of the CEL1 gene revealed that it is required for the expression of stress response phenotypes, including thermotolerance, cell wall integrity, and efficient cell cycle progression. Accordingly, a cel1Δ deletion mutant was avirulent in two models of C. neoformans infection. Therefore, in contrast to LPMO activity in other microorganisms that primarily targets exogenous polysaccharides, these data suggest that CnCel1 promotes intrinsic fungal cell wall remodeling events required for efficient adaptation to the host environment.
Keyphrases
- heat shock protein
- cell wall
- heat shock
- cell cycle
- endothelial cells
- copy number
- single cell
- genome wide
- escherichia coli
- cell proliferation
- genome wide identification
- induced pluripotent stem cells
- staphylococcus aureus
- magnetic resonance
- machine learning
- pluripotent stem cells
- candida albicans
- microbial community
- magnetic resonance imaging
- pseudomonas aeruginosa
- ionic liquid
- mesenchymal stem cells
- electronic health record
- risk assessment
- biofilm formation
- big data
- stem cells
- lymph node metastasis
- cystic fibrosis
- data analysis
- silver nanoparticles
- gene expression
- binding protein