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Optical forward-scattering for identification of bacteria within microcolonies

Abstract : The development of methods for the rapid identification of pathogenic bacteria is a major step towards accelerated clinical diagnosis of infectious diseases and efficient food and water safety control. Methods for identification of bacterial colonies on gelified nutrient broth have the potential to bring an attractive solution, combining simple optical instrumentation, no need for sample preparation or labelling, in a non-destructive process. Here, we studied the possibility of discriminating different bacterial species at a very early stage of growth (6 hours of incubation at 37°C), on thin layers of agar media (1mm of Tryptic Soy Agar), using light forward-scattering and learning algorithms (Bayes Network, Continuous Naive Bayes, Sequential Minimal Optimisation). A first database of more than 1000 scatterograms acquired on seven Gram-negative strains yielded a recognition rate of nearly 80%, after only 6 hours of incubation. We investigated also the prospect of identifying different strains from a same species through forward scattering. We discriminated thus four strains of Escherichia coli with a recognition rate reaching 82%. Finally, we show the discrimination of two species of coagulase-negative Staphylococci (S. haemolyticus and S. cohnii), on a commercial selective pre-poured medium used in clinical diagnosis (ChromID MRSA, bioMérieux), without opening lids during the scatterogram acquisition. This shows the potential of this method – non-invasive, preventing cross-contaminations and requiring minimal dish handling – to provide early clinically-relevant information in the context of fully automated microbiology labs.
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Submitted on : Wednesday, April 1, 2020 - 6:40:25 PM
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Pierre R. Marcoux, Mathieu Dupoy, Antoine Cuer, Joe-Loïc Kodja, Arthur Lefebvre, et al.. Optical forward-scattering for identification of bacteria within microcolonies. Applied Microbiology and Biotechnology, Springer Verlag, 2014, 98 (5), pp.2243-2254. ⟨10.1007/s00253-013-5495-4⟩. ⟨cea-02528456⟩



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