Classification of Select Category A and B Bacteria by Fourier Transform Infrared Spectroscopy

Abstract

Fourier transform infrared (FT-IR) spectroscopy historically is a powerful tool for the taxonomic classification of bacteria by genus, species, and strain when they are grown under carefully controlled conditions. Relatively few reports have investigated the determination and classification of pathogens such as the National Institute of Allergy and Infectious Diseases (NIAID) Category A Bacillus anthracis spores and cells (BA), Yersinia species, Francisella tularensis (FT), and Category B Brucella species from FT-IR spectra. We investigated the multivariate statistics classification ability of the FT-IR spectra of viable pathogenic and non-pathogenic NIAID Category A and B bacteria. The impact of different growth media, growth time and temperature, rolling circle filter of the data, and wavelength range were investigated for their microorganism differentiation capability. Viability of the bacteria was confirmed by agar plate growth after the FT-IR experimental procedures were performed. Principal component analysis (PCA) was reduced to maps of two PC vectors in order to distill the FT-IR spectral features into manageable, visual presentations. The PCA results of the strains of BA, FT, Brucella, and Yersinia spectra from conditions of varying growth media and culture time were readily separable in two-dimensional (2D) PC plots. FT spectra were separated from those of the three other genera. The BA pathogenic spore strains 1029, LA1, and Ames were clearly differentiated from the rest of the dataset. Yersinia rhodei, Y. enterocolitica, and Y. pestis species were distinctly separated from the remaining dataset and could also be classified by growth media. Different growth media produced distinct subsets in the FT, BA, and Yersinia spp. regions in the 2D PC plots. Various 2D PC plots provided differential degrees of separation with respect to the four viable bacterial genera including the BA sub-categories of pathogenic spores, vegetative cells, and nonpathogenic vegetative cells. This work provided evidence that FT-IR spectroscopy can indeed separate the four major pathogenic bacterial genera of NIAID Category A and B biological threat agents including details according to the growth conditions and statistical parameters.

Identification of carbapenem‐resistant Acinetobacter baumannii clones using infrared spectroscopy

“…Spectroscopic based methods such as with those based on infrared and Raman spectroscopy are quick, low cost, environmentally friendly and have been applied with good results in several microorganisms [10][11][12][13] including Acinetobacter spp. [14,15].…”

Identification of Trueperella pyogenes Isolated from Bovine Mastitis by Fourier Transform Infrared Spectroscopy

“…FT-IR spectroscopy, a promising technique for rapid and reliable identification of bacterial microorganisms, had already been used as tool for classification of Listeria and Yersinia species [16]–, coryneform bacteria [14] and for a large number of other clinically relevant pathogens [15]–[22]–[23]. This spectroscopic technique had also been approved to investigate the most common mastitis-inducing bacteria from genera Staphylococcus [24] and Streptococcus [25]–[26] and to determine the predominant bacterial flora in raw milk [27].…”

The use of microfluidics and dielectrophoresis for separation, concentration, and identification of bacteria

“…Along with Raman spectroscopy, other methods generate complex spectra such as Fourier transform infrared spectroscopy (FT-IR) [34,98,99] and surface-enhanced Raman spectroscopy [61,71,94,100]. Due to the complex nature of the spectra, many researchers ease data processing by truncating data using principal component analysis (PCA) prior to classifying bacteria [34,92,[101][102][103][104][105][106].…”