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

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: Headspace analysis; Ion mobility spectrometry; Metabolomics; Rapid bacteria identification; Sepsis; Volatile organic compounds.