A genetic algorithm-Bayesian network approach for the analysis of metabolomics and spectroscopic data: application to the rapid detection of Bacillus spores and identification of Bacillus species

Background The rapid identification of Bacillus spores and bacterial identification are paramount because of their implications in food poisoning, pathogenesis and their use as potential biowarfare agents. Many automated analytical techniques such as Curie-point pyrolysis mass spectrometry (Py-MS) have been used to identify bacterial spores giving use to large amounts of analytical data. This high number of features makes interpretation of the data extremely difficult We analysed Py-MS data from 36 different strains of aerobic endospore-forming bacteria encompassing seven different species. These bacteria were grown axenically on nutrient agar and vegetative biomass and spores were analyzed by Curie-point Py-MS. Results We develop a novel genetic algorithm-Bayesian network algorithm that accurately identifies sand selects a small subset of key relevant mass spectra (biomarkers) to be further analysed. Once identified, this subset of relevant biomarkers was then used to identify Bacillus spores successfully and to identify Bacillus species via a Bayesian network model specifically built for this reduced set of features. Conclusions This final compact Bayesian network classification model is parsimonious, computationally fast to run and its graphical visualization allows easy interpretation of the probabilistic relationships among selected biomarkers. In addition, we compare the features selected by the genetic algorithm-Bayesian network approach with the features selected by partial least squares-discriminant analysis (PLS-DA). The classification accuracy results show that the set of features selected by the GA-BN is far superior to PLS-DA

Effect of cultural conditions on deep UV resonance raman spectra of bacteria

Bacteria grown on trypticase soy agar (TSA), trypticase soy broth (TSB), and Davis minimal media, and harvested at times ranging from 4.5 to 48 h have been excited at 242.54 and 222.65 nm for the purpose of generating resonance Raman spectra. When excitation with 242.54-nm light occurs, simple spectra of tyrosine and tryptophan and various nucleic acids are observed. Large changes in the relative intensities of major nucleic acid peaks at 1485 and 1575 cm -~, on the one hand, as compared to a prominent protein tyrosine + tryptophan peak at 1616 cm -~, on the other, have been attributed to very large variations in the RNA content of bacterial cells from culture to culture. The spectral changes are observed whenever differences in growth rates or variations in cultural media result in substantial changes in the amount of ribosomal RNA. In spite of very large cultural effects on peak intensities it has been possible to obtain bacterial G+C/A+T ratios from these spectra. Specifically, the ratio of the intensity of the C (1530 cm -~) peak to the intensity of the A+G peak (1485 cm -~) when plotted against the known molar percent G+C of the corresponding bacterial DNA produces a straight line. Plots have been shown to be very nearly growth-time and media independent for fourteen different types of bacteria, which range in DNA G+C content from 32 to 66%. Spectra obtained with 222.65- nm light, in contrast with spectra obtained with 242.54-nm excitation, have been found to be nearly growth-rate and media independent. The excitation wavelength, 222.65 nm, appears to be the best yet found for use in rapid Raman identification of bacteria. All strong peaks which have been assigned have been attributed to protein modes. Relative intensities of 1556-cm ~ tryptophan and 1616-cm -~ tryptophan + tyrosine bands have been found to be strongly correlated with bacterial Gram type and nearly independent of cultural media or stage of growth. © 1993 Society for Applied Spectroscopy

UV resonance Raman spectra of bacteria, bacterial spores, protoplasts and calcium dipicolinate

Resonance Raman spectra have been obtained with 222.65, 230.72, 242.39 and 250.96 nm excitation for Bacillus subtilis, Enterobacter cloacae, Pseudomonas fluorescens and Staphylococcus epidermids. Endospores of Bacillus cereus and protoplasts of Bacillus megaterium have been studied also. With 251 nm excitation, bacterial nucleic acid spectra are obtained selectively. Nucleic acid also strongly excited by 242 nm light while at that wavelength aromatic amino acid spectra just begin to be detected. Aromatic amino acid spectra are observed exclusively at 231 nm and appear along with some new strong nucleic acid peaks with 222 nm excitation. Calcium dipicolinate has been excited selectively in Bacillus spores at 242 nm. Large characteristic spectral differences can be explained as due to the selective excitation of various UV-absorbing cell components. Large intensity differences seen in the tryptophan-associated 1556 cm-1 peak excited at 222 and 231 nm appear to be strongly correlated with Gram type. Results suggest that UV-absorbing bacterial taxonomic markers can be selectively excited to give rise to characteristics resonance Raman bacterial spectral fingerprints which have the potential to be used as the basis for methods of rapid identification. © 1990