Identification of Antibacterial Peptide Candidates Encrypted in Stress-Related and Metabolic Saccharomyces cerevisiae Proteins.
Maria Fernanda da Silva SantosCyntia Silva FreitasGiovani Carlo Verissimo da CostaPatricia Ribeiro PereiraVania Margaret Flosi PaschoalinPublished in: Pharmaceuticals (Basel, Switzerland) (2022)
The protein-rich nature of Saccharomyces cerevisiae has led this yeast to the spotlight concerning the search for antimicrobial peptides. Herein, a <10 kDa peptide-rich extract displaying antibacterial activity was obtained through the autolysis of yeast biomass under mild thermal treatment with self-proteolysis by endogenous peptidases. Estimated IC 50 for the peptide pools obtained by FPLC gel filtration indicated improved antibacterial activities against foodborne bacteria and bacteria of clinical interest. Similarly, the estimated cytotoxicity concentrations against healthy human fibroblasts, alongside selective indices ≥10, indicates the fractions are safe, at least in a mixture format, for human tissues. Nano-LC-MS/MS analysis revealed that the peptides in FPLC fractions could be derived from both induced-proteolysis and proteasome activity in abundant proteins, up-regulated under stress conditions during S. cerevisiae biomass manufacturing, including those coded by TDH1/2/3 , HSP12 , SSA1/2 , ADH1/2 , CDC19 , PGK1 , PPI1 , PDC1 , and GMP1 , as well as by other non-abundant proteins. Fifty-eight AMP candidate sequences were predicted following an in silico analysis using four independent algorithms, indicating their possible contribution to the bacterial inactivation observed in the peptides pool, which deserve special attention for further validation of individual functionality. S. cerevisiae -biomass peptides, an unconventional but abundant source of pharmaceuticals, may be promissory adjuvants to treat infectious diseases that are poorly sensitive to conventional antibiotics.
Keyphrases
- saccharomyces cerevisiae
- endothelial cells
- infectious diseases
- wastewater treatment
- amino acid
- heat shock protein
- high glucose
- anaerobic digestion
- induced pluripotent stem cells
- machine learning
- heat stress
- gene expression
- anti inflammatory
- protein protein
- working memory
- deep learning
- heat shock
- drug induced
- staphylococcus aureus
- combination therapy
- binding protein
- replacement therapy
- protein kinase
- molecular dynamics simulations