Surface-Enhanced Raman Spectroscopy (SERS) for the Characterization of Biofilm Forming and Non-Biofilm Forming Klebsiella pneumoniae Strains DOI

Hirra Sattar,

Tayyaba Ijaz,

Haq Nawaz

et al.

Analytical Letters, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 20

Published: Jan. 3, 2025

Surface-enhanced Raman spectroscopy (SERS) is an effective technique for identifying the biochemical composition of biofilm forming bacterial strains which exhibit strong antibiotic resistance and present major challenges in healthcare settings. Klebsiella pneumoniae, opportunistic pathogen known its ability to form biofilms, responsible a variety nosocomial community-infections, highlighting critical need precise detection. In this study, nine different K. pneumoniae were selected categorized according their capacity (non-biofilm, medium biofilm, biofilm). The silver nanoparticles (Ag-NPs) based SERS approach was used analyze differences between cell mass (pellets) these strains. Principal component analysis (PCA) partial least squares discriminant applied classify differentiate spectral datasets, achieving 100% specificity 81.82% sensitivity. This enables accurate rapid identification strains, along with detailed profiling matrix.

Language: Английский

Surface-Enhanced Raman Spectroscopy (SERS) for the Characterization of Biofilm Forming and Non-Biofilm Forming Klebsiella pneumoniae Strains DOI

Hirra Sattar,

Tayyaba Ijaz,

Haq Nawaz

et al.

Analytical Letters, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 20

Published: Jan. 3, 2025

Surface-enhanced Raman spectroscopy (SERS) is an effective technique for identifying the biochemical composition of biofilm forming bacterial strains which exhibit strong antibiotic resistance and present major challenges in healthcare settings. Klebsiella pneumoniae, opportunistic pathogen known its ability to form biofilms, responsible a variety nosocomial community-infections, highlighting critical need precise detection. In this study, nine different K. pneumoniae were selected categorized according their capacity (non-biofilm, medium biofilm, biofilm). The silver nanoparticles (Ag-NPs) based SERS approach was used analyze differences between cell mass (pellets) these strains. Principal component analysis (PCA) partial least squares discriminant applied classify differentiate spectral datasets, achieving 100% specificity 81.82% sensitivity. This enables accurate rapid identification strains, along with detailed profiling matrix.

Language: Английский

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