27 April 2016 Fast Raman single bacteria identification: toward a routine in-vitro diagnostic
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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, Alice Douet, Quentin Josso, Quentin Josso, Adrien Marchant, Adrien Marchant, Bertrand Dutertre, Bertrand Dutertre, Delphine Filiputti, Delphine Filiputti, Armelle Novelli-Rousseau, Armelle Novelli-Rousseau, Isabelle Espagnon, Isabelle Espagnon, Meike Kloster-Landsberg, Meike Kloster-Landsberg, Frédéric Mallard, Frédéric Mallard, Francois Perraut, 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); doi: 10.1117/12.2227658; https://doi.org/10.1117/12.2227658
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