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- Clustered regularly interspaced short palindromic repeats-mediated surface-enhanced Raman scattering assay for multidrug-resistant bacteria
- Hongki Kim; Soohyun Lee; Hwi Won Seo; Byunghoon Kang; Jeong Moon; K G. Lee; D Yong; Hyunju Kang; Juyeon Jung; Eun-Kyung Lim; Jinyoung Jeong; H G Park; Choong-Min Ryu; Taejoon Kang
- Bibliographic Citation
- ACS Nano, vol. 14, pp. 17241-17253
- Publication Year
- Antimicrobial resistance and multidrug resistance are slower-moving pandemics than the fast-spreading coronavirus disease 2019; however, they have potential to cause a much greater threat to global health. Here, we report a clustered regularly interspaced short palindromic repeats (CRISPR)-mediated surface-enhanced Raman scattering (SERS) assay for multidrug-resistant (MDR) bacteria. This assay was developed via a synergistic combination of the specific gene-recognition ability of the CRISPR system, superb sensitivity of SERS, and simple separation property of magnetic nanoparticles. This assay detects three multidrug-resistant (MDR) bacteria, species Staphylococcus aureus, Acinetobacter baumannii, and Klebsiella pneumoniae, without purification or gene amplification steps. Furthermore, MDR A. baumannii-infected mice were successfully diagnosed using the assay. Finally, we demonstrate the on-site capture and detection of MDR bacteria through a combination of the three-dimensional nanopillar array swab and CRISPR-mediated SERS assay. This method may prove effective for the accurate diagnosis of MDR bacterial pathogens, thus preventing severe infection by ensuring appropriate antibiotic treatment.
- CRISPR/dCas9Surface-enhanced Raman scattering: Antimicrobial-resistanceBacteriaNanoparticle
- Amer Chem Soc
- Appears in Collections:
- Division of Research on National Challenges > Infectious Disease Research Center > 1. Journal Articles
Division of Research on National Challenges > Bionanotechnology Research Center > 1. Journal Articles
Division of Research on National Challenges > Environmental diseases research center > 1. Journal Articles
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