Fast Raman single bacteria identification: toward a routine in-vitro diagnostic

Alice Douet; Quentin Josso; Adrien Marchant; Bertrand Dutertre; Delphine Filiputti; Armelle Novelli-Rousseau; Isabelle Espagnon; Meike Kloster-Landsberg; Frédéric Mallard; Francois Perraut

doi:10.1117/12.2227658

27 April 2016 Fast Raman single bacteria identification: toward a routine in-vitro diagnostic

Alice Douet, Quentin Josso, Adrien Marchant, Bertrand Dutertre, Delphine Filiputti, Armelle Novelli-Rousseau, Isabelle Espagnon, Meike Kloster-Landsberg, Frédéric Mallard, Francois Perraut

Author Affiliations +

Proceedings Volume 9887, Biophotonics: Photonic Solutions for Better Health Care V; 98871W (2016) https://doi.org/10.1117/12.2227658
Event: SPIE Photonics Europe, 2016, Brussels, Belgium

Abstract

Timely microbiological results are essential to allow clinicians to optimize the prescribed treatment, ideally at the initial stage of the therapeutic process. Several approaches have been proposed to solve this issue and to provide the microbiological result in a few hours directly from the sample such as molecular biology. However fast and sensitive those methods are not based on single phenotypic information which presents several drawbacks and limitations. Optical methods have the advantage to allow single-cell sensitivity and to probe the phenotype of measured cells. Here we present a process and a prototype that allow automated single-bacteria phenotypic analysis. This prototype is based on the use of Digital In-line Holography techniques combined with a specially designed Raman spectrometer using a dedicated device to capture bacteria. The localization of single-cell is finely determined by using holograms and a proper propagation kernel. Holographic images are also used to analyze bacteria in the sample to sort potential pathogens from flora dwelling species or other biological particles. This accurate localization enables the use of a small confocal volume adapted to the measurement of single-cell. Along with the confocal volume adaptation, we also have modified every components of the spectrometer to optimize single-bacteria Raman measurements. This optimization allowed us to acquire informative single-cell spectra using an integration time of 0.5s only. Identification results obtained with this prototype are presented based on a 65144 Raman spectra database acquired automatically on 48 bacteria strains belonging to 8 species.

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Alice Douet, Quentin Josso, Adrien Marchant, Bertrand Dutertre, Delphine Filiputti, Armelle Novelli-Rousseau, Isabelle Espagnon, Meike Kloster-Landsberg, Frédéric Mallard, and Francois Perraut "Fast Raman single bacteria identification: toward a routine in-vitro diagnostic", Proc. SPIE 9887, Biophotonics: Photonic Solutions for Better Health Care V, 98871W (27 April 2016); https://doi.org/10.1117/12.2227658

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