Secretion of the fungal toxin candidalysin is dependent on conserved precursor peptide sequences.
Rita MüllerAnnika KönigSabrina GrothRobert ZarnowskiCorissa VisserTom HandrianzCorinne MaufraisThomas KrügerMaximilian HimmelSejeong LeeEmily L PriestDeniz YildirimJonathan P RichardsonMatthew G BlangoMarie-Elisabeth BougnouxOlaf KniemeyerChristophe D'EnfertAxel A BrakhageDavid R AndesVerena TrümperChristian NehlsLydia KasperSelene MogaveroThomas GutsmannJulian R NaglikStefanie AllertBernhard HubePublished in: Nature microbiology (2024)
The opportunistic fungal pathogen Candida albicans damages host cells via its peptide toxin, candidalysin. Before secretion, candidalysin is embedded in a precursor protein, Ece1, which consists of a signal peptide, the precursor of candidalysin and seven non-candidalysin Ece1 peptides (NCEPs), and is found to be conserved in clinical isolates. Here we show that the Ece1 polyprotein does not resemble the usual precursor structure of peptide toxins. C. albicans cells are not susceptible to their own toxin, and single NCEPs adjacent to candidalysin are sufficient to prevent host cell toxicity. Using a series of Ece1 mutants, mass spectrometry and anti-candidalysin nanobodies, we show that NCEPs play a role in intracellular Ece1 folding and candidalysin secretion. Removal of single NCEPs or modifications of peptide sequences cause an unfolded protein response (UPR), which in turn inhibits hypha formation and pathogenicity in vitro. Our data indicate that the Ece1 precursor is not required to block premature pore-forming toxicity, but rather to prevent intracellular auto-aggregation of candidalysin sequences.
Keyphrases
- candida albicans
- escherichia coli
- induced apoptosis
- mass spectrometry
- biofilm formation
- oxidative stress
- cell cycle arrest
- transcription factor
- endoplasmic reticulum stress
- signaling pathway
- machine learning
- liquid chromatography
- staphylococcus aureus
- pseudomonas aeruginosa
- mesenchymal stem cells
- living cells
- single molecule
- bone marrow
- cell proliferation
- artificial intelligence
- ms ms
- genetic diversity
- small molecule
- data analysis
- gas chromatography