Detection of Escherichia coli O157:H7 and Salmonella Typhimurium Using Filtration followed by Fourier-Transform Infrared Spectroscopy†

2006 ◽  
Vol 69 (8) ◽  
pp. 1777-1784 ◽  
Author(s):  
Y. BURGULA ◽  
D. KHALI ◽  
S. KIM ◽  
S. S. KRISHNAN ◽  
M. A. COUSIN ◽  
...  

Fourier-transform infrared spectroscopy has been successfully used as a nondestructive method for identifying, distinguishing, and classifying pathogens. In this study, a less time-consuming Fourier-transform infrared procedure was developed to identify Escherichia coli O157:H7 and Salmonella Typhimurium. Samples containing 109 CFU/ml were prepared in tryptic soy broth and then serially diluted (up to eight times) to obtain bacterial solutions of 109 to 10 CFU/ml. These dilutions were incubated at 37°C for 6 h, samples were filtered through a Metricel filter hourly (for 0 to 6 h), and spectra were obtained using a ZnSe contact attenuated total reflectance accessory on a Continuμm infrared microscope. Midinfrared spectra (4,000 to 700 cm−1)of Salmonella Typhimurium and E. coli O157:H7 were generated, and peak areas in the region of 1,589 to 1,493 cm−1 were used to detect the pathogens. Initially, detection limits were between 106 and 107 CFU/ml without preenrichment, and samples starting with 500 CFU/ml were detectable following incubation for 6 h, when counts reached at least 106 CFU/ml. Compared with results of previously published studies in which Fourier-transform infrared spectroscopy was used to identify select pathogens, this method is more rapid and less expensive for practical large-scale sample analysis.

2009 ◽  
Vol 92 (2) ◽  
pp. 518-526 ◽  
Author(s):  
Kakali Sharma ◽  
Shiba Prasad Sharma ◽  
SujitChandra Lahiri

Abstract Numerous methods are being used to identify and quantify methanol and ethanol in alcoholic beverages, including country liquors. Some of the known methods are density and refractive index measurements, and spectrophotometric measurements using Schiff's reagent or chromatropic acid. Other advanced techniques involve head space gas chromatography (GC), GCflame ionization detection, high-performance liquid chromatography, enzymatic reactions, and biosensors. However, identification and quantification of methanol and ethanol in beverages can be accurately done using GC-Fourier transform infrared spectroscopy (FTIR) and horizontal attenuated total reflectance (HATR)-FTIR. Identification of alcohols is possible from library matching of the IR spectra obtained from GC-FTIR. In water, methanol and ethanol show a very strong peak for CO, stretching at 1015.3 and 1044.2 cm1, respectively. The strong absorption of vibrational stretching frequency of CO present in alcohols was used for quantification purposes. The absorptions of CO group frequency of alcohols in water mixtures were measured using HATR-FTIR with a zincselenide crystal. Samples were placed directly on the HATR crystal, with alcohol concentrations ranging from 0.2 to 50.0 (v/v). The plot of absorptions against concentrations of methanol and ethanol obeyed Beer's law (r2 0.9998 and 0.9987, respectively), from which alcohol in the mixtures was quantified. Propan-2-ol and n-butanol showed no interference. The method is validated from absorption measurements of known mixtures of standard ethanol in water. This is a simple, specific, rapid, accurate, and nondestructive method of identification and quantification of methanol and ethanol in mixtures. It can be used to ascertain methanol contamination in alcoholic beverages that can lead to death or methanol poisoning by alcohol consumption.


Author(s):  
A. Yu. Suntsova ◽  
R. R. Guliev ◽  
D. A. Popov ◽  
T. Yu. Vostrikova ◽  
D. V. Dubodelov ◽  
...  

The need for novel techniques of rapid identification of pathogenic microorganisms arises from the massive spread of drug-resistant nosocomial strains and the emergence of centers for biohazard control. Fourier-transform infrared spectroscopy is a promising alternative to mass spectrometry as it is cost-effective, fast and suitable for field use. The aim of this work was to propose an algorithm for the identification of microorganisms in pure cultures based on the analysis of their Fourier transform infrared spectra. The algorithm is based on the automated principal component analysis of infrared spectra. Unlike its analogues described in the literature, the algorithm is capable of identifying bacteria regardless of the culture medium or growth phase. The training sample included the most prevalent causative agents of infections and sepsis in humans: Staphylococcus aureus (n = 67), Enterococcus faecalis (n = 10), Enterococcus faecium (n = 10), Klebsiella pneumoniae (n = 10), Escherichia coli (n = 10), Serratia marcescens (n = 10), Enterobacter cloacae (n = 10), Acinetobacter baumannii (n = 10), Pseudomonas aeruginosa (n = 10), and Candida albicans (n = 10). The model we built successfully passed a series of blind tests involving clinical isolates of 10 methicillin-resistant (MRSA) and 10 methicillin-sensitive (MSSA) Staphylococcus aureus strains as well as pair mixes of these cultures with clinical isolates of Pseudomonas aeruginosa, Escherichia coli, and Klebsiella pneumoniae.


FEBS Journal ◽  
2005 ◽  
Vol 272 (8) ◽  
pp. 1855-1866 ◽  
Author(s):  
Erik Schleicher ◽  
Benedikt Heßling ◽  
Viktoria Illarionova ◽  
Adelbert Bacher ◽  
Stefan Weber ◽  
...  

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