Details
| Original language | English |
|---|---|
| Pages (from-to) | 9091-9101 |
| Number of pages | 11 |
| Journal | Applied Microbiology and Biotechnology |
| Volume | 103 |
| Issue number | 21-22 |
| Early online date | 30 Oct 2019 |
| Publication status | Published - Nov 2019 |
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 CO 2-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
- Headspace analysis, Ion mobility spectrometry, Metabolomics, Rapid bacteria identification, Sepsis, Volatile organic compounds, Staphylococcus aureus/classification, Escherichia coli/classification, Gas Chromatography-Mass Spectrometry, Blood Culture, Humans, Volatile Organic Compounds/analysis, Bacteremia/diagnosis, Pseudomonas aeruginosa/classification, Bacterial Typing Techniques/methods, Principal Component Analysis
ASJC Scopus subject areas
- Immunology and Microbiology(all)
- Applied Microbiology and Biotechnology
- Biochemistry, Genetics and Molecular Biology(all)
- Biotechnology
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In: Applied Microbiology and Biotechnology, Vol. 103, No. 21-22, 11.2019, p. 9091-9101.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - GC-IMS headspace analyses allow early recognition of bacterial growth and rapid pathogen differentiation in standard blood cultures
AU - Drees, Carolin
AU - Vautz, Wolfgang
AU - Liedtke, Sascha
AU - Rosin, Christopher
AU - Althoff, Kirsten
AU - Lippmann, Martin
AU - Zimmermann, Stefan
AU - Legler, Tobias J.
AU - Yildiz, Duygu
AU - Perl, Thorsten
AU - Kunze-Szikszay, Nils
N1 - 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.
PY - 2019/11
Y1 - 2019/11
N2 - 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 CO 2-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.
AB - 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 CO 2-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.
KW - Headspace analysis
KW - Ion mobility spectrometry
KW - Metabolomics
KW - Rapid bacteria identification
KW - Sepsis
KW - Volatile organic compounds
KW - Staphylococcus aureus/classification
KW - Escherichia coli/classification
KW - Gas Chromatography-Mass Spectrometry
KW - Blood Culture
KW - Humans
KW - Volatile Organic Compounds/analysis
KW - Bacteremia/diagnosis
KW - Pseudomonas aeruginosa/classification
KW - Bacterial Typing Techniques/methods
KW - Principal Component Analysis
UR - http://www.scopus.com/inward/record.url?scp=85074726964&partnerID=8YFLogxK
U2 - 10.1007/s00253-019-10181-x
DO - 10.1007/s00253-019-10181-x
M3 - Article
C2 - 31664484
AN - SCOPUS:85074726964
VL - 103
SP - 9091
EP - 9101
JO - Applied Microbiology and Biotechnology
JF - Applied Microbiology and Biotechnology
SN - 0175-7598
IS - 21-22
ER -