A novel streptococcal cell-cell communication peptide promotes pneumococcal virulence and biofilm formation.
Rolando A CuevasRory EutseyAnagha KadamJacob A West-RobertsCarol A WoolfordAaron P MitchellKevin M MasonN Luisa HillerPublished in: Molecular microbiology (2017)
Streptococcus pneumoniae (pneumococcus) is a major human pathogen. It is a common colonizer of the human respiratory track, where it utilizes cell-cell communication systems to coordinate population-level behaviors. We reasoned that secreted peptides that are highly expressed during infection are pivotal for virulence. Thus, we used in silico pattern searches to define a pneumococcal secretome and analyzed the transcriptome of the clinically important PMEN1 lineage to identify which peptide-encoding genes are highly expressed in vivo. In this study, we characterized virulence peptide 1 (vp1), a highly expressed Gly-Gly peptide-encoding gene in chinchilla middle ear effusions. The vp1 gene is widely distributed across pneumococcus as well as encoded in related species. Studies in the chinchilla model of middle ear infection demonstrated that VP1 is a virulence determinant. The vp1 gene is positively regulated by a transcription factor from the Rgg family and its cognate SHP (short hydrophobic peptide). In vitro data indicated that VP1 promotes increased thickness and biomass for biofilms grown on chinchilla middle ear epithelial cells. Furthermore, the wild-type biofilm is restored with the exogenous addition of synthetic VP1. We conclude that VP1 is a novel streptococcal regulatory peptide that controls biofilm development and pneumococcal pathogenesis.
Keyphrases
- biofilm formation
- pseudomonas aeruginosa
- staphylococcus aureus
- candida albicans
- single cell
- escherichia coli
- transcription factor
- genome wide
- disease virus
- cell therapy
- endothelial cells
- rna seq
- cystic fibrosis
- genome wide identification
- antimicrobial resistance
- copy number
- gene expression
- machine learning
- stem cells
- wastewater treatment
- optical coherence tomography
- heat shock
- mesenchymal stem cells
- genome wide analysis
- data analysis
- induced pluripotent stem cells
- deep learning