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Raman spectroscopic identification of single bacterial cells under antibiotic influence

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Abstract

The identification of pathogenic bacteria is a frequently required task. Current identification procedures are usually either time-consuming due to necessary cultivation steps or expensive and demanding in their application. Furthermore, previous treatment of a patient with antibiotics often renders routine analysis by culturing difficult. Since Raman microspectroscopy allows for the identification of single bacterial cells, it can be used to identify such difficult to culture bacteria. Yet until now, there have been no investigations whether antibiotic treatment of the bacteria influences the Raman spectroscopic identification. This study aims to rapidly identify bacteria that have been subjected to antibiotic treatment on single cell level with Raman microspectroscopy. Two strains of Escherichia coli and two species of Pseudomonas have been treated with four antibiotics, all targeting different sites of the bacteria. With Raman spectra from untreated bacteria, a linear discriminant analysis (LDA) model is built, which successfully identifies the species of independent untreated bacteria. Upon treatment of the bacteria with subinhibitory concentrations of ampicillin, ciprofloxacin, gentamicin, and sulfamethoxazole, the LDA model achieves species identification accuracies of 85.4, 95.3, 89.9, and 97.3 %, respectively. Increasing the antibiotic concentrations has no effect on the identification performance. An ampicillin-resistant strain of E. coli and a sample of P. aeruginosa are successfully identified as well. General representation of antibiotic stress in the training data improves species identification performance, while representation of a specific antibiotic improves strain distinction capability. In conclusion, the identification of antibiotically treated bacteria is possible with Raman microspectroscopy for diverse antibiotics on single cell level.

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Acknowledgments

U. M. highly acknowledges Dr. Eike T. Spielberg for helpful discussions on statistical problems. Thanks to Bernd Kampe for assistance with GNU R, Sophie Friedrich and the Seminarfach group “Sepsis” are acknowledged for the acquisition of parts of the spectral data. Financial support from Jena School for Microbial Communication (DFG) and funding of the research group “Jenaer Biochip Initiative 2.0” within the framework “Unternehmen Region—InnoProfile Transfer” from the Federal Ministry of Education and Research, Germany (BMBF) is gratefully acknowledged.

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Authors and Affiliations

  1. Institute of Physical Chemistry, Helmholtzweg 4, Friedrich Schiller University Jena, 07743, Jena, Germany

    Ute Münchberg, Petra Rösch & Jürgen Popp

  2. Jena School for Microbial Communication, Friedrich Schiller University Jena, Neugasse 23, 07743, Jena, Germany

    Ute Münchberg

  3. Abbe Center of Photonics, Friedrich Schiller University Jena, Max-Wien-Platz 1, 07743, Jena, Germany

    Ute Münchberg, Michael Bauer & Jürgen Popp

  4. Department of Anesthesiology and Intensive Care Medicine, Erlanger Allee 101, University Hospital Jena, 07747, Jena, Germany

    Michael Bauer

  5. Center for Sepsis Control and Care, University Hospital Jena, Erlanger Allee 101, 07747, Jena, Germany

    Michael Bauer & Jürgen Popp

  6. Leibniz-Institute of Photonic Technology, Albert-Einstein-Str. 9, 07745, Jena, Germany

    Jürgen Popp

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  1. Ute Münchberg
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  2. Petra Rösch
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  4. Jürgen Popp
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Correspondence to Jürgen Popp.

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Münchberg, U., Rösch, P., Bauer, M. et al. Raman spectroscopic identification of single bacterial cells under antibiotic influence. Anal Bioanal Chem 406, 3041–3050 (2014). https://doi.org/10.1007/s00216-014-7747-2

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  • DOI: https://doi.org/10.1007/s00216-014-7747-2

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