Identification of Bacillus anthracis by Using Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry and Artificial Neural Networks

This report demonstrates the applicability of a combination of matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry (MS) and chemometrics for rapid and reliable identification of vegetative cells of the causative agent of anthrax, Bacillus anthracis. Bacillus cultures were prepared under standardized conditions and inactivated according to a recently developed MS-compatible inactivation protocol for highly pathogenic microorganisms. MALDI-TOF MS was then employed to collect spectra from the microbial samples and to build up a database of bacterial reference spectra. This database comprised mass peak profiles of 374 strains from Bacillus and related genera, among them 102 strains of B. anthracis and 121 strains of B. cereus. The information contained in the database was investigated by means of visual inspection of gel view representations, univariate t tests for biomarker identification, unsupervised hierarchical clustering, and artificial neural networks (ANNs). Analysis of gel views and independent t tests suggested B. anthracis- and B. cereus group-specific signals. For example, mass spectra of B. anthracis exhibited discriminating biomarkers at 4,606, 5,413, and 6,679 Da. A systematic search in proteomic databases allowed tentative assignment of some of the biomarkers to ribosomal protein or small acid-soluble proteins. Multivariate pattern analysis by unsupervised hierarchical cluster analysis further revealed a subproteome-based taxonomy of the genus Bacillus. Superior classification accuracy was achieved when supervised ANNs were employed. For the identification of B. anthracis, independent validation of optimized ANN models yielded a diagnostic sensitivity of 100% and a specificity of 100%.Members of the genus Bacillus are rod-shaped bacteria that exhibit catalase activity and can be characterized as endospore-forming obligate or facultative aerobes. The genus Bacillus contains two important groups of bacteria named after B. subtilis and B. cereus. The best-characterized member of the former group is B. subtilis, a renowned model organism for genetic research. Other group members, like B. pumilis, B. licheniformis, B. atrophaeus, and B. amyloliquefaciens, exhibit a high degree of phenotypic similarity and are thus not easily distinguishable (15).The B. cereus group comprises a number of closely related bacteria, some of which interfere with human health. Bacteria classified as B. cereus are occasionally associated with food poisoning (16, 28), while B. thuringiensis is primarily an insect pathogen because of its ability to produce toxins that have been widely used for the biocontrol of insect pests (28, 30). A third member of the B. cereus group, B. anthracis, is the causative agent of anthrax and is highly relevant to human and animal health. Other members of the B. cereus group are B. mycoides, B. pseudomycoides, and B. weihenstephanensis (4, 15).B. anthracis is a possible agent in biological warfare and bioterrorism. Its applicability as a biological warfare agent was made apparent by an accidental release from a Soviet military facility in Sverdlovsk (1, 10). Also, the well-publicized mailing of B. anthracis spores in the United States, which caused 18 confirmed cases of cutaneous and inhalational anthrax and an additional 4 suspected cases of cutaneous anthrax (3, 22), demonstrated that B. anthracis may become a threat from terrorist groups (10).Rapid detection of B. anthracis may be challenging because of its great genetic similarity to other species of the B. cereus group (10) and the difficulties of phenotypic differentiation of B. cereus group members (15). There is some controversy in the literature regarding the taxonomy of the B. cereus group. Indeed, some authors state that B. anthracis, B. cereus, and B. thuringiensis are one species with various virulence plasmids for the toxin pXO1 and the capsule pXO2 of B. anthracis and the insecticidal toxin of B. thuringiensis (10, 19). Other authors do not support this opinion and suggest the presence of even more species within the group (21).Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) intact-cell mass spectrometry (ICMS) has been suggested as a rapid, objective, and reliable technique for bacterial identification (8, 13, 23, 25, 38). As a proteomic technique, ICMS of whole bacterial cells, or cell lysates, relies on the reproducible detection of microbial protein patterns and thus delivers information complementary to genotypic or phenotypic test methods. With the pattern-matching approach, microbial identification is achieved by comparing experimental mass spectra with a collection of mass spectra of known organisms. This requires the compilation of large databases of bacterial reference spectra but has the advantage that an extensive knowledge of biomarker identities is not required. Another advantage of the pattern-matching approach is that genus- and species-specific procedures or consumables are not required, i.e., the same methodology can in principle be applied to all kinds of microorganisms (multiplex advantage).It is thus believed that ICMS offers the possibility to systematically investigate the diversity of bacterial subproteomes, complementing existing methodologies of bacterial characterization. This potential and the need for a rapid, objective, and reliable microbial identification technique that does not rely on nucleic acid detection and the availability of an MS-compatible inactivation protocol for highly pathogenic biosafety level 3 microorganisms and bacterial endospores (26) prompted us to systematically study the MALDI-TOF MS profiles of Bacillus strains and to establish a database of bacterial mass spectra. In the present work, we describe strategies of spectral analysis that allow the identification and validation of group- and species-specific sets of biomarkers. Using unsupervised hierarchical cluster analysis (UHCA) and supervised artificial neural network (ANN) analysis, we also demonstrate how microbial spectra can be employed to establish an MS-based methodology for rapid, objective, and reliable identification of the target species, B. anthracis.