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A novel method for single bacteria identification by Raman spectroscopy

Abstract : In this paper we present results on single bacteria rapid identification obtained with a low-cost and compact Raman spectrometer. At present, we demonstrate that a 1 minute procedure, including the localization of single bacterium, is sufficient to acquire comprehensive Raman spectrum in the range of 600 to 3300 cm-1. Localization and detection of single bacteria is performed by means of lensfree imaging over a large field of view of 24 mm2. An excitation source of 532 nm and 30 mW illuminates single bacteria to collect Raman signal into a Tornado Spectral Systems prototype spectrometer (HTVS technology). The acquisition time to record a single bacterium spectrum is as low as 10 s owing to the high light throughput of this spectrometer. The spectra processing features different steps for cosmic spikes removal, background subtraction, and gain normalization to correct the residual inducted fluorescence and substrate fluctuations. This allows obtaining a fine chemical fingerprint analysis. We have recorded a total of 1200 spectra over 7 bacterial species (E. coli, Bacillus species, S. epidermis, M. luteus, S. marcescens). The analysis of this database results in a high classification score of almost 90 %. Hence we can conclude that our setup enables automatic recognition of bacteria species among 7 different species. The speed and the sensitivity (<30 minutes for localization and spectra collection of 30 single bacteria) of our Raman spectrometer pave the way for high-throughput and non-destructive real-time bacteria identification assays. This compact and low-cost technology can benefit biomedical, clinical diagnostic and environmental applications.
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Contributor : Léna Le Roy Connect in order to contact the contributor
Submitted on : Monday, July 16, 2018 - 10:05:58 AM
Last modification on : Saturday, June 25, 2022 - 9:11:40 PM





E. Schultz, A.-C. Simon, S.A. Strola, R. Perenon, I. Espagnon, et al.. A novel method for single bacteria identification by Raman spectroscopy. Proceedings Biomedical Vibrational Spectroscopy VI: Advances in Research and Industry, Feb 2014, San Francisco, CA, United States. ⟨10.1117/12.2039318⟩. ⟨cea-01839856⟩



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