Pseudomonas aeruginosa biofilm dispersion by the mouse antimicrobial peptide CRAMP.
Yang ZhangPeng ChengShiyuan WangXiaofen LiLianci PengRendong FangJing XiongHui LiCui MeiJiye GaoZhenhui SongDengfeng XuLizhi FuChenghong LiXueqing WuYuzhang HeHongwei ChenPublished in: Veterinary research (2022)
Pseudomonas aeruginosa (P. aeruginosa) is a known bacterium that produces biofilms and causes severe infection. Furthermore, P. aeruginosa biofilms are extremely difficult to eradicate, leading to the development of chronic and antibiotic-resistant infections. Our previous study showed that a cathelicidin-related antimicrobial peptide (CRAMP) inhibits the formation of P. aeruginosa biofilms and markedly reduces the biomass of preformed biofilms, while the mechanism of eradicating bacterial biofilms remains elusive. Therefore, in this study, the potential mechanism by which CRAMP eradicates P. aeruginosa biofilms was investigated through an integrative analysis of transcriptomic, proteomic, and metabolomic data. The omics data revealed CRAMP functioned against P. aeruginosa biofilms by different pathways, including the Pseudomonas quinolone signal (PQS) system, cyclic dimeric guanosine monophosphate (c-di-GMP) signalling pathway, and synthesis pathways of exopolysaccharides and rhamnolipid. Moreover, a total of 2914 differential transcripts, 785 differential proteins, and 280 differential metabolites were identified. A series of phenotypic validation tests demonstrated that CRAMP reduced the c-di-GMP level with a decrease in exopolysaccharides, especially alginate, in P. aeruginosa PAO1 biofilm cells, improved bacterial flagellar motility, and increased the rhamnolipid content, contributing to the dispersion of biofilms. Our study provides new insight into the development of CRAMP as a potentially effective antibiofilm dispersant.
Keyphrases
- candida albicans
- biofilm formation
- pseudomonas aeruginosa
- staphylococcus aureus
- cystic fibrosis
- single cell
- escherichia coli
- ms ms
- big data
- climate change
- electronic health record
- cell proliferation
- deep learning
- signaling pathway
- risk assessment
- high resolution
- cell cycle arrest
- drug induced
- data analysis
- tissue engineering