Abstract
BackgroundHospital-acquired pneumonia (HAP) is a common problem in intensive care medicine and the patient outcome depends on the fast beginning of adequate antibiotic therapy. Until today pathogen identification is performed using conventional microbiological methods with turnaround times of at least 24 h for the first results. It was the aim of this study to investigate the potential of headspace analyses detecting bacterial species-specific patterns of volatile organic compounds (VOCs) for the rapid differentiation of HAP-relevant bacteria.MethodsEleven HAP-relevant bacteria (Acinetobacter baumanii, Acinetobacter pittii, Citrobacter freundii, Enterobacter cloacae, Escherichia coli, Klebsiella oxytoca, Klebsiella pneumoniae, Pseudomonas aeruginosa, Proteus mirabilis, Staphylococcus aureus, Serratia marcescens) were each grown for 6 hours in Lysogeny Broth and the headspace over the grown cultures was investigated using multi-capillary column-ion mobility spectrometry (MCC-IMS) to detect differences in the VOC composition between the bacteria in the panel. Peak areas with changing signal intensities were statistically analysed, including significance testing using one-way ANOVA or Kruskal-Wallis test (p < 0.05).Results30 VOC signals (23 in the positive ion mode and 7 in the negative ion mode of the MCC-IMS) showed statistically significant differences in at least one of the investigated bacteria. The VOC patterns of the bacteria within the HAP panel differed substantially and allowed species differentiation.ConclusionsMCC-IMS headspace analyses allow differentiation of bacteria within HAP-relevant panel after 6 h of incubation in a complex fluid growth medium. The method has the potential to be developed towards a feasible point-of-care diagnostic tool for pathogen differentiation on HAP.
Highlights
Hospital-acquired pneumonia (HAP) is a common problem in intensive care medicine and the patient outcome depends on the fast beginning of adequate antibiotic therapy
Significant changes in signal intensity in at least one of the bacterial species of the HAP panel were observed in 30 volatile organic compounds (VOCs) signals (23 in the positive ion mode, 7 in the negative ion mode)
Besides genomic techniques and proteomic applications (e.g. MALDI-TOF-MS), the metabolomic approach by using VOCs of microbial origin has been proposed for bacterial species differentiation [9]
Summary
Hospital-acquired pneumonia (HAP) is a common problem in intensive care medicine and the patient outcome depends on the fast beginning of adequate antibiotic therapy. Until today pathogen identification is performed using conventional microbiological methods with turnaround times of at least 24 h for the first results. It was the aim of this study to investigate the potential of headspace analyses detecting bacterial species-specific patterns of volatile organic compounds (VOCs) for the rapid differentiation of HAP-relevant bacteria. About one-quarter of all infections in intensive care medicine are episodes of hospital-acquired pneumonia (HAP) [1]. Behind central line-associated bloodstream infections, HAP is the second common infectious condition in the intensive care unit (ICU) [2]. Rapid and adequate antibiotic therapy contributes to improved outcomes in these patients [5, 6]
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