Automated detection of mixed cultures of micro-organisms using MALDITOFMS
Abstract number: P1783
Wenzel T., Klepel S., Maier T., Stumpf S., Wegemann B., Kostrzewa M.
Objectives: MALDI-TOF mass spectrometry fingerprint analysis for identification of microorganisms recently has emerged as a powerful tool in clinical microbiology diagnostics. Starting with a single colony characteristic profile spectra are acquired for an unknown microbe and identification is performed by bioinformatic comparison with a dedicated database. One current drawback of the technology is that in the case of mixed cultures, e.g. in case of contaminations, generally only one of the microorganisms is detected in automated analyses. Sometimes even any identification is hampered by the mix of profiles in the mass spectra. On the other hand, careful evaluation of the mass spectra derived from two or even three different bacteria in a mixture can be unravelled after inspection by eye, frequently. We present a bioinformatic approach to check automatically spectra for the probable existence of such contaminations.
Methods: Mixtures of different bacterial cultures were prepared in different ratios. Further, several blood cultures spiked with different bacteria were prepared. The blood cultures were incubated for several hours at 35 deg C. Next, they were harvested under standard conditions, purified and prepared for MALDI-TOF MS analysis according to a protocol developed in our lab. Bacteria were analysed after extraction using a microflex benchtop mass spectrometer according to standard procedures. Resulting spectra were automatically analysed using the MALDI Biotyper 2.0 software package and, in parallel, with a novel algorithm which is calculating the possibility of a mixed-culture spectrum.
Results: Several two compound-mixed cultures, from artificial mixtures as well as from spiked blood cultures were unambiguously recognised as mixed-cultures using the novel algorithm. For some mixes, in particular from blood culture experiments, only one species was detected or the analysis failed at all. No false mixture alarm appeared from blood cultures, also no wrong identification was observed. Two compound mixed cultures spiking experiments using other body fluids (e.g. human urine) are under current investigation.
Conclusion: The principle applicability of automated mixed culture identification, even for positively flagged blood cultures, could be demonstrated. The novel algorithm enables a rapid spectra check of real-life samples for probable existence of mixed cultures. Potential of further improvement of sensitivity of the method and algorithm is being investigated.
|Session name:||Abstracts 20th European Congress of Clinical Microbiology and Infectious Diseases|
|Location:||Vienna, Austria, 10 - 13 April 2010|
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