Indeed, even though most ribosomal proteins are highly conserved within a bacterial species, some of these proteins are subject to slight variations at the strain level. Ribosomal proteins are good candidates for such an approach as they are universal amongst cellular life. (ii) We next aimed at identifying markers specific of strain and/or groups of strains and compare them to reliable epidemiological methods. (i) Although many studies have showed that peaks used for identification species of bacteria are ribosomal protein ( Lay, 2001 Pineda et al., 2003 Ryzhov and Fenselau, 2001 Teramoto et al., 2007a, 2007b), we wanted to identify the exact nature of the biomarkers empirically used to build the Andromas database for bacterial species identification. In this work, we aimed at answering two questions regarding the implementation of mass spectrometry in clinical laboratories. The failure to identify some specimens is explained by small protein variations among isolates of the same species, or by the fact that some peaks of the database cannot be observed because of the poor quality of spectra obtained from whole bacteria grown in primary culture. With the Andromas database, accurate species identification is obtained if at least 68% of the species-specific peaks are present in the spectrum of the subject isolate. For each strain, only those peaks with a relative intensity above 0.07, and which that were constantly present in all 10 sets of data obtained for a given strain, were retained. Briefly, to engineer the database, a set of reference isolates was chosen, and ten subcultures of each of these selected isolates, grown on different media, were analyzed. The Andromas database was engineered using an algorithm that identifies a limited number of species-specific peaks for each entry ( Carbonnelle et al., 2007 Degand et al., 2008). This identification relies on comparison of the spectra of the sample with those of reference databases. Whole-cell matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) generates a spectrum based on proteins detected directly from intact microorganisms ( Holland et al., 1996 Williams et al., 2003), allowing the rapid identification of bacterial isolates. Their detection by MALDI-TOF allows therefore a quick typing of N. Since the molecular weight of three of the variable ribosomal proteins (元0, 元1 and 元2) was included in the spectral window observed by MALDI-TOF MS in clinical microbiology, i.e., 3640–12000 m/z, we were able by analyzing the molecular weight of these three ribosomal proteins to classify each strain in one of six subgroups, each of these subgroups corresponding to specific STs and/or CCs. The analysis of the ribosomal protein patterns of 100 isolates for which whole genome sequences were available, confirmed the presence of inter-strain variability in the molecular weight of 29 ribosomal proteins, thus establishing a correlation between the sequence type (ST) and/or clonal complex (CC) of each strain and its ribosomal protein pattern. Remarkably, one biomarker, ribosomal protein 元2, was subject to inter-strain variability. Using Neisseria meningitidis as a model organism, we showed that in one of the available databases, the Andromas database, 10 of the 13 species-specific biomarkers correspond to ribosomal proteins. This identification is based on the comparison of the tested isolate mass spectrum with reference databases. Whole-cell matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) is a rapid method for identification of microorganisms that is increasingly used in microbiology laboratories.
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