Differentiation of whole bacterial cells based on high-throughput microarray chip printing and infrared microspectroscopic readout.

Using robotic automation, a microarray printing protocol for whole bacterial cells was developed for subsequent label-free and nondestructive infrared microspectroscopic detection. Using this contact microspotting system, 24 microorganisms were printed on zinc selenide slides; these were 6 species of Listeria, 10 species of Vibrio, 2 strains of Photobacterium damselae, Yersinia enterocolitica 289, Bacillus cereus ATCC 14529, Staphylococcus aureus, ATCC 19075 (serotype 104 B), Shigella sonnei 20143, Klebsiella pneumoniae KP73, Enterobacter cloacae, Citrobacter freundii 200, and Escherichia coli. Microarrays consisting of separate spots of bacterial deposits gave consistent and reproducible infrared spectra, which were differentiated by unsupervised pattern recognition algorithms. Two multivariate analysis algorithms, principal component analysis and hierarchical cluster analysis, successfully separated most, but not all, the bacteria investigated down to the species level.

Potential use of DNA barcodes in regulatory science: applications of the Regulatory Fish Encyclopedia.

The use of a DNA-based identification system (DNA barcoding) founded on the mitochondrial gene cytochrome c oxidase subunit I (COI) was investigated for updating the U.S. Food and Drug Administration Regulatory Fish Encyclopedia (RFE; http://www.cfsan.fda.gov/-frf/rfe0.html). The RFE is a compilation of data used to identify fish species. It was compiled to help regulators identify species substitution that could result in potential adverse health consequences or could be a source of economic fraud. For each of many aquatic species commonly sold in the United States, the RFE includes high-resolution photographs of whole fish and their marketed product forms and species-specific biochemical patterns for authenticated fish species. These patterns currently include data from isoelectric focusing studies. In this article, we describe the generation of DNA barcodes for 172 individual authenticated fish representing 72 species from 27 families contained in the RFE. These barcode sequences can be used as an additional identification resource. In a blind study, 60 unknown fish muscle samples were barcoded, and the results were compared with the RFE barcode reference library. All 60 samples were correctly identified to species based on the barcoding data. Our study indicates that DNA barcoding can be a powerful tool for species identification and has broad potential applications.

Determination of aflatoxins B1, B2, G1, and G2 and ochratoxin A in ginseng and ginger by multitoxin immunoaffinity column cleanup and liquid chromatographic quantitation: collaborative study.

The accuracy, repeatability, and reproducibility characteristics of a method using multitoxin immunoaffinity column cleanup with liquid chromatography (LC) for determination of aflatoxins (AF; sum of aflatoxins B1, B2, G1, and G2) and ochratoxin A (OTA) in powdered ginseng and ginger have been established in a collaborative study involving 13 laboratories from 7 countries. Blind duplicate samples of blank, spiked (AF and OTA added) at levels ranging from 0.25 to 16.0 microg/kg for AF and 0.25 to 8.0 microg/kg for OTA were analyzed. A naturally contaminated powdered ginger sample was also included. Test samples were extracted with methanol and 0.5% aqueous sodium hydrogen carbonate solution (700 + 300, v/v). The extract was centrifuged, diluted with phosphate buffer (PB), filtered, and applied to an immunoaffinity column containing antibodies specific for AF and OTA. After washing the column with water, the toxins were eluted from the column with methanol, and quantified by high-performance LC with fluorescence detection. Average recoveries of AF from ginseng and ginger ranged from 70 to 87% (at spiking levels ranging from 2 to 16 microg/kg), and of OTA, from 86 to 113% (at spiking levels ranging from 1 to 8 microg/kg). Relative standard deviations for within-laboratory repeatability (RSDr) ranged from 2.6 to 8.3% for AF, and from 2.5 to 10.7% for OTA. Relative standard deviations for between-laboratory reproducibility (RSDR) ranged from 5.7 to 28.6% for AF, and from 5.5 to 10.7% for OTA. HorRat values were < or = 2 for the multi-analytes in the 2 matrixes.

Differentiation of Enterobacter sakazakii from closely related Enterobacter and Citrobacter species using fatty acid profiles.

Capillary gas chromatography with flame ionization detection (GC-FID) was used to determine the cellular fatty acid (CFA) profiles of 134 Enterobacter sakazakii strains, and these were compared to the CFA profiles of other closely related Enterobacter and Citrobacter species. For GC-FID analysis, whole cell fatty acid methyl esters (FAMEs) from cells cultured on brain heart infusion (BHI) agar at 37 degrees C for 24 h were obtained by saponification, methylation, and extraction into hexane/methyl tert-butyl ether. A database for E. sakazakii was prepared using fatty acid profiles from the 134 strains. Major fatty acids of E. sakazakii strains evaluated in this study were straight-chain 12:0, 14:0, and 16:0, unsaturated 18:1 omega7c, and 17:0 omegacyclo 7-8. Principal component analysis (PCA) based on CFA profiles for E. sakazakii strains shows separation of E. sakazakii subgroups A and B. The CFA profiles for E. sakazakii and Enterobacter cloacae show that there are several fatty acids, 14:0, 17:0 omegacyclo 7-8, 18:1 omega7c, and summed 16:1 omega6c/16:1 omega7c, that differ significantly between these two species. A PCA model based on CFA profiles for E. sakazakii strains clearly shows separation of E. sakazakii from closely related Enterobacter and Citrobacter species. Analysis of FAMEs from E. sakazakii strains grown on BHI agar by a rapid GC-FID method can provide a sensitive procedure for the identification of this organism, and this analytical method provides a confirmatory procedure for the differentiation of E. sakazakii strains from closely related Enterobacter and Citrobacter species.

Evaluating the use of fatty acid profiles to identify Francisella tularensis.

Rapid capillary gas chromatography (GC) with flame-ionization detection was used to determine the cellular fatty acid profiles of Francisella tularensis. Two subspecies of F. tularensis, the live vaccine strain (LVS) derived from holarctica and a novicida strain Utah 112 (U112), were used to compare the extracted fatty acid methyl esters (FAMEs). A data set for the 2 subspecies was prepared using fatty acid profiles of bacteria grown on 2 types of media, Mueller-Hinton and cysteine heart agar supplemented with 5% rabbit blood (CHAB), and harvested at various time intervals (Day 1 through Day 4) with replicates prepared on different days. A total of 204 samples were analyzed. The results showed that these fatty acid quantitative profiles were unique for each of the subspecies and could be used as a fingerprint for the organism. It was determined by this rapid method that approximately 88% of the fatty acids in both the LVS and U112 strains included 6 saturated fatty acids: 10:0, 12:0, 14:0, 16:0, 18:0, and 20:0; and 4 hydroxy fatty acids 10:0 2OH, 16:0 3OH, 17:0 3OH, and 18:0 3OH. Data analysis and determination of clustering were performed by principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA). Both PCA and SIMCA showed clear separation of the LVS and U112 strain and would be useful for prediction of unknowns. It was determined that the incubation time can be reduced from 48 to 24 h, and results are highly predictive for the identification of F. tularensis. In summary, analysis of FAMEs from F. tularensis subspecies LVS and U112 grown on CHAB or Mueller-Hinton media, and using a rapid GC method can provide a sensitive procedure for identification of these organisms.

A discriminant based charge deconvolution analysis pipeline for protein profiling of whole cell extracts using liquid chromatography-electrospray ionization-quadrupole time-of-flight mass spectrometry.

A discriminant based charge deconvolution analysis pipeline is proposed. The molecular weight determination (MoWeD) charge deconvolution method was applied directly to the discrimination rules obtained by the fuzzy rule-building expert system (FuRES) pattern classifier. This approach was demonstrated with synthetic electrospray ionization-mass spectra. Identification of the tentative protein biomarkers by bacterial cell extracts of Salmonella enterica serovar typhimurium strains A1 and A19 by liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS) was also demonstrated. The data analysis time was reduced by applying this approach. In addition, this method was less affected by noise and baseline drift.