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Applied Microbiology and Biotechnology

, Volume 103, Issue 21–22, pp 9091–9101 | Cite as

GC-IMS headspace analyses allow early recognition of bacterial growth and rapid pathogen differentiation in standard blood cultures

  • Carolin Drees
  • Wolfgang Vautz
  • Sascha Liedtke
  • Christopher Rosin
  • Kirsten Althoff
  • Martin Lippmann
  • Stefan Zimmermann
  • Tobias J. Legler
  • Duygu Yildiz
  • Thorsten Perl
  • Nils Kunze-SzikszayEmail author
Methods and protocols
First Online:

Abstract

Outcome of patients with blood stream infections (BSI) depends on the rapid initiation of adequate antibiotic therapy, which relies on the fast and reliable identification of the underlying pathogen. Blood cultures (BC) using CO2-sensitive colorimetric indicators and subsequent microbiological culturing are the diagnostic gold standard but turnaround times range between 24 and 48 h. The detection of volatile organic compounds of microbial origin (mVOC) has been described as a feasible method for identifying microbial growth and to differentiate between several microbial species. In this study, we aimed to investigate the ability of mVOC analyses using a gas chromatograph coupled to an ion mobility spectrometer (GC-IMS) for the recognition of bacterial growth and bacterial differentiation in BCs. Therefore, samples of whole blood and diluted bacterial suspension were injected into aerobic and anaerobic BC bottles and incubated for 8 h. Headspace samples from cultures of Escherichia coli (DSM 25944), Staphylococcus aureus (DSM 13661), and Pseudomonas aeruginosa (DSM 1117) were investigated hourly and we determined at which point of time a differentiation between the bacteria was possible. We found specific mVOC signals in the headspace over growing BCs of all three bacterial species. GC-IMS headspace analyses allowed faster recognition of bacterial growth than the colorimetric indicator of the BCs. A differentiation between the three investigated species was possible after 6 h of incubation with a high reliability in the principal component analysis. We concluded that GC-IMS headspace analyses could be a helpful method for the rapid detection and identification of bacteria in BSI.

Keywords

Rapid bacteria identification Sepsis Metabolomics Ion mobility spectrometry Volatile organic compounds Headspace analysis 
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Notes

Acknowledgements

The authors would like to thank Claudia Ottersbach for her dedicated work contributing to this study.

Funding information

This work was supported in part of the cooperation project FKZ 13GW0191A-E funded by the German Federal Ministry of Education and Research. Furthermore, the financial support is provided by the Ministerium für Innovation, Wissenschaft und Forschung des Landes Nordrhein-Westfalen

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

Studies with human participants or animals were not carried out in the frame of the present study by any of the authors. The blood samples were used in accordance with ethics committee of the University Medical Center Göttingen (approval number 43/2/19).

Supplementary material

253_2019_10181_MOESM1_ESM.pdf (350 kb)
ESM 1 (PDF 349 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V.DortmundGermany
  2. 2.ION-GAS GmbHDortmundGermany
  3. 3.G.A.S. - Gesellschaft für analytische Sensorsysteme GmbHDortmundGermany
  4. 4.Institut für Grundlagen der Elektrotechnik und MesstechnikLeibniz Universität HannoverHannoverGermany
  5. 5.Department of Transfusion MedicineUniversity Medical Center GöttingenGottingenGermany
  6. 6.Department of AnesthesiologyUniversity Medical Center GöttingenGottingenGermany
  7. 7.Department of General, Visceral and Pediatric SurgeryUniversity Medical Center GöttingenGottingenGermany

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