Table 4. A short exemplary list of SNP genotypes of the galE gene detected by MALDI mass spectrometry. Microorganism E. amylovora 273 ATCC 49946 E. amylovora isolate E. amylovora isolate E. amylovora isolate E. amylovora 1/79 DSM 17948 E. amylovora isolate E. amylovora CFBP1430 E. amylovora isolate galE gene SNP 175 A A A A C C C C Origin of isolates USA Washington, USA California, USA Niagara region (CDN) Germany Stuttgart region (D) North of France Egypt The SNP distinguishes E. amylovora strains of North American origin from the European/Mediterranean origin. The reference sequences are deposited as Figure S1. doi:10.1371/journal.pone.0002843.t004 Cell culturing on agar: For cell culturing on agar plates, all dilutions were incubated for 2 days at 28uC. Bacteria were suspended from cell lawns in 1 ml water to a density of approximately 1 (light absorption at 600 nm) and centrifuged. The pellets were washed with 1 ml water and then the liquid was discarded. The presence of culture medium adhering to the bacterial colonies cells from agar had no visible effect on the mass signal patterns. The bacteria were inactivated as described below. Culturing in liquid media: Bacteria grown on agar were inoculated into LB liquid medium with 1% glucose for the generation of reference spectra and in many cases for identification of unknown samples. The medium was autoclaved and then filtrated through a 0.2 mm nitrocellulose filter to remove particles. Replacement of LB-glucose by LB-glycerol showed little effect in the peak pattern distribution. Identification of bacteria grown on different media was reliably achieved as shown in Table 1. Once the bacteria have entered the stationary phase, the method is robust against growth times. However, other (minimal) media might have a stronger influence on the mass peak patterns. For the generation of reference spectra, we used LB-glucose as standard medium because most Erwinia bacteria grew well in this medium and resulted in very good mass spectra in terms of sensitivity and resolution. Inactivation of bacteria: The bacteria were suspended in 300 ml water and inactivated by the addition of 800 ml ethanol at room temperature. The samples could be stored at room temperature for several days or at 4–8uC for several weeks. To assay for viability, we applied dilutions to agar plates and found no surviving E. amylovora cells already after an hour of storage in ethanol. Protein extraction: This step was performed at room temper- ature. The solution was centrifuged at 25,0006g for 2 minutes and the supernatant was discarded. Again, centrifugation was per- formed for 2 minutes at 25,0006g and residual supernatant was discarded. Five to 20 ml of 70% formic acid were added to the ‘‘pellet’’ (1 to 5 mg, or less bacterial material), and mixed to re- suspend the bacteria. Then 5–20 ml acetonitrile were added, accordingly, and the sample was mixed carefully. The solution was centrifuged at 25,0006g for 2 minutes. The supernatant (,5– 20 ml) was transferred to a new tube immediately. MALDI preparation: This step was performed at room temperature and at 20–80% air humidity. One microliter of the supernatant was placed onto a stainless steel target plate and led dry in air. Then, 1 ml of matrix (3 mg/ml solution of alpha-cyano- 4-hydroxycinnamic acid in 50% acetonitrile/2.5% trifluor acetic Bacteria/Mass Spectrometry acid) was overlaid onto the dried sample and led dry in air. This simple preparation method provided homogenous samples to enable automated measurements and sufficiently reproducible mass spectra. To increase data reliability, we applied each bacterial sample six times onto the target plate. Mass spectrometry detection: Mass spectra were acquired using an Ultraflex I MALDI-TOF mass spectrometer (Bruker Daltonics, Bremen, Germany). Alternatively, a simpler MALDI-TOF instrument such as the benchtop Microflex (Bruker Daltonics) can be used without loosing data quality. We performed measurements in linear positive ion detection mode, using a Nd:YAG laser at maximum frequency of 66 Hz. Pulsed ion extraction (PIE) was set to zero. Acceleration voltage (IS1) was set to 20 kV. The mass range of spectra was from 2,000 to 20,000 m/ z. The final resolution in the mass range of 7,000–10,000 m/z was optimized to be higher than 600 and absolute signal intensities were about 103. Automated spectrum acquisition was performed using the Auto Execute software with fuzzy control of laser intensity. At least 107 bacterial cells were required for high quality mass spectra. For reference spectra we measured six spots on the MALDI target. On each spot, four spectra with 10 times 100 laser shots were accumulated. Twenty spectra were stored for the reference spectra library. For identification we generally acquired spectra by accumulating 1000 laser shots in ten 100 shot portions. Factors influencing the intensities of signal peaks comprise concentration and location of proteins in the bacterial cell and biophysical properties of proteins such as solubility, hydrophobic- ity, basicity, and compatibility with MALDI. In general, most of the proteins detected by MALDI protein bacterial profiling derive from highly abundant, basic ribosomal proteins [11]. Data analysis: Mass spectra were analyzed with Flex Analysis software 2.4 (Bruker Daltonics). Further bacterial data analysis was performed by software developed and tested by us that we termed BioTyper. The mass spectral input data can be listed in generic data formats such as the extensible markup language (XML) to make them independent from the hardware used. Spectra were pre- processed using default parameters for reference spectra libraries that we call main spectra libraries (MSPs). A maximum of 100 peaks with a signal-to-noise (S/N) ratio of 3 were selected in the range of 3,000–15,000 Da. Afterwards the main spectra were generated as a reference using all spectra given for a single microorganism. In general, 75 peaks were picked automatically, which occurred in at least 25% of the spectra and with a mass deviation of 200 ppm. For the evaluation of mass spectra reproducibility, we loaded the spectra into the ClinProTools 2.1 software (Bruker Daltonics). Through this process mass spectra were firstly normalized before we applied baseline subtraction, peak detection, realignment, and peak-area calculation. The optimal settings resulted in an S/N ratio of 5, a Top Hat baseline subtraction with 10% as the minimal baseline width, and a 3-cycle Savitsky-Golay smoothing with a 10 Da-peak width filter. For the example shown in Figure 3 the coefficient of variation (CV) of each of the individual peak areas was determined; 100 peaks were taken for intra run assessment detected in 18 measurements and 75 peaks for inter run detected in 5 biological replicates. The mean CV for all of the signals from the same replicate sample was calculated to provide a measure of intra- and inter-run reproducibility. Using the bacterial analysis software (Biotyper) and taking a list of mass signals and their intensities into consideration, dendro- grams were generated by similarity scoring of a set of mass spectra. Dendrograms shown in this article had graphical distance values between species constructed from their reference spectra. A correlation function was used for calculating distance values. For graphical correlations an average statistical algorithm was applied PLoS ONE | www.plosone.org 9 July 2008 | Volume 3 | Issue 7 | e2843