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Rapid urinary tract infection diagnostics by surface-enhanced Raman spectroscopy (SERS): identification and antibiotic susceptibilities

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Abstract

SERS spectra of 12 bacterial strains of urinary tract infection (UTI) clinical isolates grown and enriched from urine are reported. A partial least squares-discriminant analysis (PLS-DA) classification treatment of these SERS spectra results in strain level identification with >95% sensitivity and >99% specificity. The classification model successfully identified the SERS spectra of a urine-cultured strain not used to build this statistical model. Enrichment was accomplished by a filtration and centrifugation protocol. The predetermined drug susceptibility profiles of these clinical isolates thus allowed the SERS methodology to provide appropriate UTI antibiotic information in less than 1 h. Most of this time was used for sample preparation procedures (enrichment and washing) for this proof of principle study. SERS spectra of the enriched bacterial samples are dominated by nucleotide degradation metabolites: adenine, hypoxanthine, xanthine, guanine, uric acid, AMP, and guanosine. Strain-specific specificity is due to the different relative amounts of these purines contributing to the corresponding SERS spectra of these clinical isolates. All measurements were made at the minimal bacterial concentration in urine for UTI diagnosis (105 cfu/mL).

The relative contribution of each of the seven purines found to contribute to the bacterial SERS spectra are summarized in this bar graph. Although strain specific differences are evident, it can be see how the pattern of contributing purines is more different between the four species than between strains of a given species

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Acknowledgements

We thank BD Life Sciences for providing the clinical isolates used in this study and for running the antimicrobial susceptibility testing on these clinical isolates (BD and BD Phoenix are trademarks of Becton, Dickinson and Company. © 2016 BD). The support of the NSF I/UCRC Collaborative Research Award Grant# 1068070 is gratefully acknowledged.

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  1. Department of Chemistry and The Photonics Center, Boston University, 8 St Mary’s Street, Boston, MA, 02215, USA

    W. R. Premasiri, Ying Chen, P. M. Williamson, D. C. Bandarage, C. Pyles & L. D. Ziegler

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  1. W. R. Premasiri
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  2. Ying Chen
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Correspondence to W. R. Premasiri or L. D. Ziegler.

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We state that all anonymized urine samples were collected from individual participants who were informed and voluntarily participated in this research work in accordance with Boston University ethical guidelines and relevant IBC protocols.

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The authors declare that they have no conflicts of interest.

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Premasiri, W.R., Chen, Y., Williamson, P.M. et al. Rapid urinary tract infection diagnostics by surface-enhanced Raman spectroscopy (SERS): identification and antibiotic susceptibilities. Anal Bioanal Chem 409, 3043–3054 (2017). https://doi.org/10.1007/s00216-017-0244-7

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  • DOI: https://doi.org/10.1007/s00216-017-0244-7

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