Background & Aims: Infrared spectroscopy is an increasingly common method for bacterial strains' testing. For the analysis of bacterial IR spectra, advanced mathematical methods such as artificial neural networks must be used. The combination of these two methods has been used previously to analyze taxonomic affiliation of bacteria. The aim of this study was the classification of Escherichia coli strains in terms of susceptibility/resistance to cephalothin on the basis of their infrared spectra. The infrared spectra of 109 uropathogenic E. coli strains were measured. These data are used for classification of E. coli strains by using designed artificial neural networks. Results: The most efficient artificial neural networks classify the E. coli sensitive/resistant strains with an error of 5%. Conclusions: Bacteria can be classified in terms of their antibiotic susceptibility by using infrared spectroscopy and artificial neural networks.
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Laser interferometry is a measurement technique used in physical sciences, with a potential for new applications in microbiology. Our previously studies, focused on the quantitative analysis of antibiotics diffusion through membranes or their releasing from gel structure, indicate that this method might be useful in analysis of substances diffusion across the bacterial biofilms. As antibiotic - biofilm interaction model, we tested above method for determination of ciprofloxacin or gentamicin diffusion through Proteus mirabilis O18 biofilm. Laser interferometry analysis of antibiotics diffusion showed that the amount of ciprofloxacin transported through mature biofilm is 1.9 times higher than gentamicin. It was correlated with lower level of gentamicin in compare to the level of ciprofloxacin in biofilm, which amounts were predicted in biofilm during diffusion process by laser interferometry method. We suggest that the analysis of antibiotic diffusion in biofilm might by helpful in evaluation of effectiveness of antibacterial agents.
The bacterial pan-genome is a relatively new concept that refers to the number of genes observed in a given set of bacterial genome sequences, either at the intra- or inter-species level. Determining the pan-genome of a given species of bacteria using a large number of strains allows one to compare multiple genes and to determine evolutionary links between isolates. This information can help to determine population structure, diversity in terms of prevalence in a given environment and pathogenicity of microorganisms. Within this review, we explain the most important issues related to pan-genome studies. We also include a brief description of some selected bacterial pan-genomes. Finally, we propose an easy-toperform workflow to study bacterial pan-genomes that will facilitate nonexperts in a pan-genome-based investigation.
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