A micro-Raman and chemometric study of urinary tract infection-causing bacterial pathogens in mixed cultures

M. Yogesha, Kiran Chawla, Aseefhali Bankapur, Mahendra Acharya, Jacinta S. D’Souza, Santhosh Chidangil

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Abstract

Detection of urinary tract infection (UTI)-causing bacteria uses conventional time-consuming microbiological techniques. The current need is to use a fast and reliable method of bacterial identification. In order to unambiguously distinguish the UTI-causing five bacterial species used in the current study, micro-Raman spectra were obtained from a home-assembled micro-Raman system and analyzed by multivariate statistical techniques such as principal component analysis (PCA), partial least square-discriminate analysis (PLS-DA), and support vector machine (SVM). Also, the micro-Raman spectra recorded from samples containing two and three bacterial species were tested and validated against the aforementioned calibration models using PLS-DA and SVM. The prediction accuracies of up to 73 and 89% were achieved with PLS-DA and SVM, respectively. Taken together, the present study depicts the capturing of unique micro-Raman spectral features manifesting from the biochemical content of each bacterium. Also, micro-Raman spectroscopy combined with multivariate data analysis can therefore be a reliable and faster technique for the diagnosis of UTI-causing bacteria. [Figure not available: see fulltext.].

Original languageEnglish
Pages (from-to)3165-3177
Number of pages13
JournalAnalytical and Bioanalytical Chemistry
Volume411
Issue number14
DOIs
Publication statusPublished - 19-05-2019

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All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Biochemistry

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