title: Gram-negative and -positive bacteria differentiation in blood culture samples by headspace volatile compound analysis.
abstract: BACKGROUND
  Identification of microorganisms in positive blood cultures still relies on standard techniques such as Gram staining followed by culturing with definite microorganism identification. Alternatively, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry or the analysis of headspace volatile compound (VC) composition produced by cultures can help to differentiate between microorganisms under experimental conditions. This study assessed the efficacy of volatile compound based microorganism differentiation into Gram-negatives and -positives in unselected positive blood culture samples from patients.
  
  
  METHODS
  Headspace gas samples of positive blood culture samples were transferred to sterilized, sealed, and evacuated 20 ml glass vials and stored at -30 °C until batch analysis. Headspace gas VC content analysis was carried out via an auto sampler connected to an ion-molecule reaction mass spectrometer (IMR-MS). Measurements covered a mass range from 16 to 135 u including CO2, H2, N2, and O2. Prediction rules for microorganism identification based on VC composition were derived using a training data set and evaluated using a validation data set within a random split validation procedure.
  
  
  RESULTS
  One-hundred-fifty-two aerobic samples growing 27 Gram-negatives, 106 Gram-positives, and 19 fungi and 130 anaerobic samples growing 37 Gram-negatives, 91 Gram-positives, and two fungi were analysed. In anaerobic samples, ten discriminators were identified by the random forest method allowing for bacteria differentiation into Gram-negative and -positive (error rate: 16.7 % in validation data set). For aerobic samples the error rate was not better than random.
  
  
  CONCLUSIONS
  In anaerobic blood culture samples of patients IMR-MS based headspace VC composition analysis facilitates bacteria differentiation into Gram-negative and -positive.
authors.affiliation: Department of Anaesthesiology, University Hospital Munich-Campus Großhadern, Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81366 Munich, Germany.
authors.forename: Michael E
authors.initials: ME
authors.lastname: Dolch
authors.affiliation: Department of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81366 Munich, Germany.
authors.forename: Silke
authors.initials: S
authors.lastname: Janitza
authors.affiliation: Department of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81366 Munich, Germany.
authors.forename: Anne-Laure
authors.initials: AL
authors.lastname: Boulesteix
authors.affiliation: Department of Anaesthesiology, University Hospital Munich-Campus Großhadern, Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81366 Munich, Germany.
authors.forename: Carola
authors.initials: C
authors.lastname: Graßmann-Lichtenauer
authors.affiliation: VF Services GmbH, Andreas-Hofer-Str. 15, Absam, Austria.
authors.forename: Siegfried
authors.initials: S
authors.lastname: Praun
authors.affiliation: Wolfden Scientific Consulting, Calle Rio Segura 26, 30600 Archena, Murcia, Spain.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Denzer
authors.affiliation: Department of Anaesthesiology, University Hospital Munich-Campus Großhadern, Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81366 Munich, Germany.
authors.forename: Gustav
authors.initials: G
authors.lastname: Schelling
authors.affiliation: Max von Pettenkofer-Institut für Hygiene und Medizinische Mikrobiologie, Ludwig-Maximilians-Universität München, Pettenkoferstraße 9a, 80336 Munich, Germany.
authors.forename: Sören
authors.initials: S
authors.lastname: Schubert
keywords: Blood culture; Chemical ionization; Gram identification; Mass spectrometry; Prediction rule; Volatile compound