Pathogen identification with laser-induced breakdown spectroscopy: the effect of bacterial and biofluid specimen contamination.

In this paper, the potential use of laser-induced breakdown spectroscopy (LIBS) for the rapid discrimination and identification of bacterial pathogens in realistic clinical specimens is investigated. Specifically, the common problem of sample contamination was studied by creating mixed samples to investigate the effect that the presence of a second contaminant bacterium in the specimen had on the LIBS-based identification of the primary pathogen. Two closely related bacterial specimens, Escherichia coli strain ATCC 25922 and Enterobacter cloacae strain ATCC 13047, were mixed together in mixing fractions of 10:1, 100:1, and 1000:1. LIBS spectra from the three mixtures were reliably classified as the correct E. coli strain with 98.5% accuracy when all the mixtures were withheld from the training model and classified against spectra from pure specimens. To simulate a rapid test for the presence of urinary tract infection pathogens, LIBS spectra were obtained from specimens of Staphylococcus epidermidis obtained from distilled water and sterile urine. LIBS spectra from the urine-harvested bacteria were classified as S. epidermidis with 100% accuracy when classified using a model containing only spectra from other Staphylococci species and with 88.5% accuracy when a model containing five genera of bacteria was utilized. Bacterial specimens comprising five different genera and 13 classifiable taxonomic groups of species and strains were compiled in a library that was tested using external validation techniques. The importance of utilizing external validation techniques where the library is tested with data withheld from all previous testing and training of the model was revealed by comparing the results against "leave-one-out" cross-validation results. Last, the effect of using sequential models for the classification of a single unknown spectrum was investigated by comparing the misclassification of two closely related bacteria, E. coli and E. cloacae, when the classification was first performed using the five-genus bacterial library and then with a smaller model consisting only of E. coli and E. cloacae specimens. This result shows the utility of using successively more targeted analyses and models that use preliminary classifications from more general models as input.

Nano-Magnetic NiFe2O4 and Its Photocatalytic Oxidation of Vanillyl Alcohol-Synthesis, Characterization, and Application in the Valorization of Lignin.

Here, we report on a phyto-mediated bimetallic (NiFe2O4) preparation using a Boswellia carterii extract, which was characterized by XRD, FT-IR, TGA, electron microscopy, magnetic spectroscopy, and Mössbauer spectroscopy measurements. The prepared nano-catalysts were tested for oxidation of lignin monomer molecules-vanillyl alcohol and cinnamyl alcohol. In comparison with previously reported methods, the nano NiFe2O4 catalysts showed high photocatalytic activity and selectivity, under visible light irradiation with a nitroxy radical initiator (2,2,6,6-tetramethylpiperidinyloxy or 2,2,6,6-tetramethylpiperidine 1-oxyl; TEMPO) at room temperature and aerobic conditions. The multifold advantages of the catalyst both in terms of reduced catalyst loading and ambient temperature conditions were manifested by higher conversion of the starting material.

Sensitive and specific discrimination of pathogenic and nonpathogenic Escherichia coli using Raman spectroscopy-a comparison of two multivariate analysis techniques.

The determination of bacterial identity at the strain level is still a complex and time-consuming endeavor. In this study, visible wavelength spontaneous Raman spectroscopy has been used for the discrimination of four closely related Escherichia coli strains: pathogenic enterohemorrhagic E. coli O157:H7 and non-pathogenic E. coli C, E. coli Hfr K-12, and E. coli HF4714. Raman spectra from 600 to 2000 cm(-1) were analyzed with two multivariate chemometric techniques, principal component-discriminant function analysis and partial least squares-discriminant analysis, to determine optimal parameters for the discrimination of pathogenic E. coli from the non-pathogenic strains. Spectral preprocessing techniques such as smoothing with windows of various sizes and differentiation were investigated. The sensitivity and specificity of both techniques was in excess of 95%, determined by external testing of the chemometric models. This study suggests that spontaneous Raman spectroscopy with visible wavelength excitation is potentially useful for the rapid identification and classification of clinically-relevant bacteria at the strain level.

The effect of bacterial environmental and metabolic stresses on a laser-induced breakdown spectroscopy (LIBS) based identification of Escherichia coli and Streptococcus viridans.

In this paper we investigate the effect that adverse environmental and metabolic stresses have on the laser-induced breakdown spectroscopy (LIBS) identification of bacterial specimens. Single-pulse LIBS spectra were acquired from a non-pathogenic strain of Escherichia coli cultured in two different nutrient media: a trypticase soy agar and a MacConkey agar with a 0.01% concentration of deoxycholate. A chemometric discriminant function analysis showed that the LIBS spectra acquired from bacteria grown in these two media were indistinguishable and easily discriminated from spectra acquired from two other non-pathogenic E. coli strains. LIBS spectra were obtained from specimens of a nonpathogenic E. coli strain and an avirulent derivative of the pathogen Streptococcus viridans in three different metabolic situations: live bacteria reproducing in the log-phase, bacteria inactivated on an abiotic surface by exposure to bactericidal ultraviolet irradiation, and bacteria killed via autoclaving. All bacteria were correctly identified regardless of their metabolic state. This successful identification suggests the possibility of testing specimens that have been rendered safe for handling prior to LIBS identification. This would greatly enhance personnel safety and lower the cost of a LIBS-based diagnostic test. LIBS spectra were obtained from pathogenic and non-pathogenic bacteria that were deprived of nutrition for a period of time ranging from one day to nine days by deposition on an abiotic surface at room temperature. All specimens were successfully classified by species regardless of the duration of nutrient deprivation.