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Bacterial strain discrimination using a low-cost laser-induced breakdown spectroscopy technique under optimized growth conditions
, Vivek Sivakumar, Unni S.N., Srikanth P., Arumugam I.
Published in SPIE
2020
Volume: 11362
   
Abstract
The Laser-Induced Breakdown Spectroscopy (LIBS) technique has been utilized in several studies for the identification of pathogenic bacterial strains based on their characteristic spectral fingerprint. Currently used LIBS techniques for discrimination of bacterial strains belonging to the same species require sophisticated methodology and expensive instrumentation. In this study, we present the strategies adopted to achieve this goal using a low-cost LIBS methodology. Time-resolved LIBS experiments were carried out using a nanosecond pulsed Nd: YAG laser (1064 nm, 6 ns, 10 Hz) for ablating the bacterial samples, and the resulting emission spectra were recorded using a portable and non-intensified Charge Coupled Device (CCD) detector. The bacterial strains used for this study were two clinical isolates of Escherichia coli (E. coli) - a pathogen causing severe infections in humans. The individual bacterial strains were cultured using a standard optimized protocol, and their respective chemical fingerprints were captured using the LIBS technique. We also investigate the efficacy of standardizing the growth environment and its role in modulating the chemical composition of the bacterial strains. A bacterial growth study was performed to assess the influence of regulating growth environment (concentration of sodium and potassium in the nutrient media), on the growth phases of the two bacterial strains. The spectral lines corresponding to sodium (589.5 nm), and potassium (766.5 nm, 769.9 nm) were found to be significant among the characteristic LIBS emission of the bacterial strains. The sodium to potassium ratio (Na/K), calculated from the elemental line intensities in the LIBS spectrum of bacteria, was found to be a highly significant feature for discrimination of bacterial strains with a classification accuracy >90%. © 2020 SPIE.
About the journal
JournalData powered by TypesetProceedings of SPIE - The International Society for Optical Engineering
PublisherData powered by TypesetSPIE
ISSN0277786X
Open AccessNo