Advertisement

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

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 

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)

References

  1. Andrade SS, Bispo PJ, Gales AC (2008) Advances in the microbiological diagnosis of sepsis. Shock 30(Suppl 1):41–46.  https://doi.org/10.1097/SHK.0b013e3181819f6c CrossRefPubMedGoogle Scholar
  2. Avolio M, Diamante P, Modolo ML, De Rosa R, Stano P, Camporese A (2014) Direct molecular detection of pathogens in blood as specific rule-in diagnostic biomarker in patients with presumed sepsis: our experience on a heterogeneous cohort of patients with signs of infective systemic inflammatory response syndrome. Shock 42(2):86–92.  https://doi.org/10.1097/shk.0000000000000191 CrossRefPubMedGoogle Scholar
  3. Bunge M, Araghipour N, Mikoviny T, Dunkl J, Schnitzhofer R, Hansel A, Schinner F, Wisthaler A, Margesin R, Märk TD (2008) On-Line Monitoring of Microbial Volatile Metabolites by Proton Transfer Reaction-Mass Spectrometry Appl. Environ. Microbiol 74(7):2179–86.  https://doi.org/10.1128/AEM.02069-07 CrossRefGoogle Scholar
  4. Chen J, Tang J, Shi H, Tang C, Zhang R (2017) Characteristics of colatile organic compounds produced from five pathogenic bacterua by headspace-solid phase micro-extraction/gas chromatography-mass spectrometry. J. Basic Microbiol 57:228–237.  https://doi.org/10.1002/jobm.201600505 CrossRefGoogle Scholar
  5. Chouinard CD, Wei MS, Beekman CR, Kemperman RH, Yost RA (2016) Ion mobility in clinical analysis: current progress and future perspectives. Clin Chem 62(1):124–133.  https://doi.org/10.1373/clinchem.2015.238840 CrossRefPubMedGoogle Scholar
  6. Cumeras R, Figueras E, Davis CE, Baumbach JI, Gràcia I (2015) Review on Ion Mobility Spectrometry. Part 1: current instrumentation. Analyst 140(5):1376–1390.  https://doi.org/10.1039/C4AN01100G CrossRefPubMedPubMedCentralGoogle Scholar
  7. Effmert U, Kalderas J, Warnke R, Piechulla B (2012) Volatile mediated interactions between bacteria and fungi in the soil. J Chem Ecol 38(6):665–703.  https://doi.org/10.1007/s10886-012-0135-5 CrossRefPubMedGoogle Scholar
  8. Eiceman GA, Karpas Z, Hill HH Jr (2013) Ion mobility spectrometry. CRC pressGoogle Scholar
  9. Goff DA, Jankowski C, Tenover FC (2012) Using rapid diagnostic tests to optimize antimicrobial selection in antimicrobial stewardship programs. Pharmacotherapy 32(8):677–87.  https://doi.org/10.1002/j.1875-9114.2012.01137.x CrossRefGoogle Scholar
  10. Hettinga KA, van Valenberg HJ, Lam TJ, van Hooijdonk AC (2008) Detection of mastitis pathogens by analysis of volatile bacterial metabolites. J. Dairy Sci 91(10):3834–9.  https://doi.org/10.3168/jds.2007-0941 CrossRefGoogle Scholar
  11. Junger M, Vautz W, Kuhns M, Hofmann L, Ulbricht S, Baumbach JI, Quintel M, Perl T (2012) Ion mobility spectrometry for microbial volatile organic compounds: a new identification tool for human pathogenic bacteria. Appl Microbiol Biotechnol 93(6):2603–2614.  https://doi.org/10.1007/s00253-012-3924-4 CrossRefPubMedPubMedCentralGoogle Scholar
  12. Koczulla R, Hattesohl A, Schmid S, Bödeker B, Maddula S, Baumbach JI (2011) MCC/IMS as potential noninvasive technique in the diagnosis of patients with COPD with and without alpha 1-antitrypsin deficiency. Int J Ion Mobil Spectrom 14(4):177–185.  https://doi.org/10.1007/s12127-011-0070-0 CrossRefGoogle Scholar
  13. Kunze N, Göpel J, Kuhns M, Jünger M, Quintel M, Perl T (2013) Detection and validation of volatile metabolic patterns over different strains of two human pathogenic bacteria during their growth in a complex medium using multi-capillary column-ion mobility spectrometry (MCC-IMS). Appl Microbiol Biotechnol 97:3665–76.CrossRefGoogle Scholar
  14. Laupland KB (2013) Incidence of bloodstream infection: a review of population-based studies. Clin Microbiol Infect 19(6):492–500.  https://doi.org/10.1111/1469-0691.12144 CrossRefPubMedGoogle Scholar
  15. Lawal O, Muhamadali H, Ahmed WM, White IR, Nijsen TME, Goodacre R, Fowler SJ (2018) Headspace volatile organic compoundsfrom bacteria implicated in ventilator-associated pneumonia analysed by TD-GC/MS. J. Breath Res 12(2):026002.  https://doi.org/10.1088/1752-7163/aa8e
  16. Lemfack MC, Gohlke B-O, Toguem SMT, Preissner S, Piechulla B, Preissner R (2018) mVOC 2.0: a database of microbial volatiles. Nucleic Acids Res 46(D1):D1261–D1265.  https://doi.org/10.1093/nar/gkx1016 CrossRefPubMedGoogle Scholar
  17. Perl T, Jünger M, Vautz W, Nolte J, Kuhns M, Borg-von Zepelin M, Quintel M (2011) Detection of characteristic metabolites of Aspergillus fumigatus and Candida species using ion mobility spectrometry–metabolic profiling by volatile organic compounds. Mycoses 54(6):e828–e837.  https://doi.org/10.1111/j.1439-0507.2011.02037.x CrossRefGoogle Scholar
  18. Schulz S, Dickschat JS (2007) Bacterial volatiles: the smell of small organisms. Nat Prod Rep 24(4):814–842.  https://doi.org/10.1039/b507392h CrossRefPubMedPubMedCentralGoogle Scholar
  19. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, Bellomo R, Bernard GR, Chiche J-D, Coopersmith CM, Hotchkiss RS, Levy MM, Marshall JC, Martin GS, Opal SM, Rubenfeld GD, van der Poll T, Vincent J-L, Angus DC (2016) The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 315(8):801–810.  https://doi.org/10.1001/jama.2016.0287 CrossRefPubMedPubMedCentralGoogle Scholar
  20. Stevenson LG, Drake SK, Murray PR (2010) Rapid identification of bacteria in positive blood culture broths by matrix-assisted laser desorption ionization-time of flight mass spectrometry. J Clin Microbiol 48(2):444–447.  https://doi.org/10.1128/JCM.01541-09 CrossRefPubMedGoogle Scholar
  21. Tabak YP, Vankeepuram L, Ye G, Jeffers K, Gupta V, Murray PR (2018) Blood culture turnaround time in U.S. acute care hospitals and implications for laboratory process optimization. J Clin Microbiol 56(12).  https://doi.org/10.1128/JCM.00500-18
  22. Thorn RM, Reynolds DM, Greenman J (2011) Multivariate analysis of bacterial volatile compound profiles for discrimination between selected species and strains in vitro. J. Microbiol. Methods 84(2):258–64.  https://doi.org/10.1016/j.mimet.2010.12.001 CrossRefGoogle Scholar
  23. Thorpe TC, Wilson ML, Turner JE, DiGuiseppi JL, Willert M, Mirrett S, Reller LB (1990) BacT/Alert: an automated colorimetric microbial detection system. J Clin Microbiol 28(7):1608–1612PubMedPubMedCentralGoogle Scholar
  24. Umber BJ, Shin HW, Meinardi S, Leu SY, Zaldivar F, Cooper DM, Blake DR (2013) Gas signatures from Escherichia coli and Escherichia coliinoculated human whole blood. Clin. Transl. Med 2:13.  https://doi.org/10.1186/2001-1326-2-13 CrossRefGoogle Scholar
  25. Vautz W, Schmäh M (2009) HovaCAL®—a generator for multi-component humid calibration gases. Int J Ion Mobil Spectrom 12(4):139–147.  https://doi.org/10.1007/s12127-009-0030-0 CrossRefGoogle Scholar
  26. Vautz W, Nolte J, Bufe A, Baumbach JI, Peters M (2010) Analyses of mouse breath with ion mobility spectrometry: a feasibility study. J Appl Physiol (1985) 108(3):697–704.  https://doi.org/10.1152/japplphysiol.00658.2009 CrossRefGoogle Scholar
  27. Vautz W, Baumbach JI, Jung J (2006a) Beer fermentation control using ion mobility spectrometry — results of a pilot study. J Inst Brew 112(2):157–164.  https://doi.org/10.1002/j.2050-0416.2006.tb00245.x CrossRefGoogle Scholar
  28. Vautz W, Zimmermann D, Hartmann M, Baumbach JI, Nolte J, Jung J (2006b) Ion mobility spectrometry for food quality and safety. Food Addit Contam 23(11):1064–1073.  https://doi.org/10.1080/02652030600889590 CrossRefPubMedGoogle Scholar
  29. Vautz W, Nolte J, Fobbe R, Baumbach JI (2009) Breath analysis—performance and potential of ion mobility spectrometry. J Breath Res 3(3):036004.  https://doi.org/10.1088/1752-7155/3/3/036004 CrossRefPubMedGoogle Scholar
  30. Warhurst G, Dunn G, Chadwick P, Blackwood B, McAuley D, Perkins GD, McMullan R, Gates S, Bentley A, Young D, Carlson GL, Dark P (2015) Rapid detection of health-care-associated bloodstream infection in critical care using multipathogen real-time polymerase chain reaction technology: a diagnostic accuracy study and systematic review. Health Technol Assess 19(35):1–142.  https://doi.org/10.3310/hta19350 CrossRefPubMedPubMedCentralGoogle Scholar
  31. Weinstein MP (2003) Blood culture contamination: persisting problems and partial progress. J Clin Microbiol 41(6):2275–2278.  https://doi.org/10.1128/jcm.41.6.2275-2278.2003 CrossRefPubMedPubMedCentralGoogle Scholar
  32. Westh H, Lisby G, Breysse F, Böddinghaus B, Chomarat M, Gant V, Goglio A, Raglio A, Schuster H, Stuber F, Wissing H, Hoeft A (2009) Multiplex real-time PCR and blood culture for identification of bloodstream pathogens in patients with suspected sepsis. Clin Microbiol Infect 15(6):544–51.  https://doi.org/10.1111/j.1469-0691.2009.02736.x. CrossRefGoogle Scholar

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

Personalised recommendations