Characterization and classification of pathogenic bacteria using native fluorescence and spectral deconvolution

Identification and classification of pathogenic bacterial strains is of current interest for the early treatment of diseases. In this work, protein fluorescence from eight different pathogenic bacterial strains were characterized using steady state and time resolved fluorescence spectroscopy. The sp...

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Bibliographic Details
Published in:Journal of biophotonics 2024-07, Vol.17 (7), p.e202300566-n/a
Main Authors: Sundaramoorthy, Anandh, Bharanidharan, Ganesan, Prakasarao, Aruna, Ganesan, Singaravelu
Format: Article
Language:English
Subjects:
Bacteria
Chemical compounds
Classification
Deconvolution
Discriminant analysis
Emission analysis
Emission spectra
Emissions
Excitation spectra
Fluorescence
fluorescence lifetime
Fluorescence spectroscopy
Fluorophores
Line spectra
Medical treatment
native fluorescence spectroscopy
Parameter identification
protein fluorescence
Proteins
redox ratio
spectral deconvolution
Spectral emissivity
stepwise multiple linear discriminant analysis
Strains (organisms)
Citations: Items that this one cites
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Summary:Identification and classification of pathogenic bacterial strains is of current interest for the early treatment of diseases. In this work, protein fluorescence from eight different pathogenic bacterial strains were characterized using steady state and time resolved fluorescence spectroscopy. The spectral deconvolution method was also employed to decompose the emission contribution from different intrinsic fluorophores and extracted various key parameters, such as intensity, emission maxima, emission line width of the fluorophores, and optical redox ratio. The change in average lifetime values across different bacterial strains exhibits good statistical significance (p ≤ 0.01). The variations in the photophysical characteristics of bacterial strains are due to the different conformational states of the proteins. The stepwise multiple linear discriminate analysis of fluorescence emission spectra at 280 nm excitation across eight different bacterial strains classifies the original groups and cross validated group with 100% and 99.5% accuracy, respectively. Explored the possibility of rapid detection of UTI causing bacteria by analyzing protein fluorescence by steady and excited state kinetics of eight bacteria at 280 nm excitation. The deconvolution of emission spectrum reveals the presence of tryptophan 1, tryptophan 2, NADH, and FAD in bacteria. Stepwise multiple linear discriminant analysis classified the original group and cross‐validated group with 100% and 99.5% accuracy, respectively.
ISSN:1864-063X
1864-0648
1864-0648
DOI:10.1002/jbio.202300566