A Transposon-Associated CRISPR/Cas9 System Specifically Eliminates both Chromosomal and Plasmid-Borne mcr-1 in Escherichia coli.
Yu-Zhang HeJin-Ru YanBing HeHao RenXu KuangTeng-Fei LongCai-Ping ChenXiao-Ping LiaoYa-Hong LiuJian SunPublished in: Antimicrobial agents and chemotherapy (2021)
The global spread of antimicrobial-resistant bacteria has been one of the most severe threats to public health. The emergence of the mcr-1 gene has posed a considerable threat to antimicrobial medication since it deactivates one last-resort antibiotic, colistin. There have been reports regarding the mobilization of the mcr-1 gene facilitated by ISApl1-formed transposon Tn6330 and mediated rapid dispersion among Enterobacteriaceae species. Here, we developed a CRISPR/Cas9 system flanked by ISApl1 in a suicide plasmid capable of exerting sequence-specific curing against the mcr-1-bearing plasmid and killing the strain with chromosome-borne mcr-1. The constructed ISApl1-carried CRISPR/Cas9 system either restored sensitivity to colistin in strains with plasmid-borne mcr-1 or directly eradicated the bacteria harboring chromosome-borne mcr-1 by introducing an exogenous CRISPR/Cas9 targeting the mcr-1 gene. This method is highly efficient in removing the mcr-1 gene from Escherichia coli, thereby resensitizing these strains to colistin. The further results demonstrated that it conferred the recipient bacteria with immunity against the acquisition of the exogenous mcr-1 containing the plasmid. The data from the current study highlighted the potential of the transposon-associated CRISPR/Cas9 system to serve as a therapeutic approach to control the dissemination of mcr-1 resistance among clinical pathogens.
Keyphrases
- escherichia coli
- crispr cas
- klebsiella pneumoniae
- genome editing
- copy number
- public health
- biofilm formation
- genome wide
- multidrug resistant
- highly efficient
- staphylococcus aureus
- healthcare
- risk assessment
- dna methylation
- machine learning
- amino acid
- deep learning
- drug induced
- big data
- artificial intelligence
- quantum dots
- antimicrobial resistance
- data analysis
- acinetobacter baumannii