Biomedical subjects

John B Sutherland

Publications and source records attributed to John B Sutherland.

8 recordsLinked to original sources

PubMed2006

Biotransformation of flumequine by the fungus Cunninghamella elegans.

The metabolism of the antibacterial fluoroquinolone drug flumequine by Cunninghamella elegans was investigated using cultures grown in Sabouraud dextrose broth with 308microM flumequine. The cultures were extracted with ethyl acetate; metabolites were separated by high-performance liquid chromatography and identified by mass spectrometry and proton nuclear magnetic resonance spectroscopy. Flumequine was transformed to two diastereomers of 7-hydroxyflumequine (23 and 43% of the total chromatographic peak area at 280nm) and 7-oxoflumequine (11% of the total peak area). This is the first time that the two 7-hydroxy diastereomers have been characterized structurally; the hydroxyflumequines are known to have less antimicrobial activity than flumequine.

Biotransformation↗

PubMed2006

Pyrolysis mass spectrometry for distinguishing potential hoax materials from bioterror agents.

Pyrolysis mass spectrometry (PyMS) was investigated as a rapid tool to distinguish potential bioterror hoax materials from samples containing pathogenic bacteria. A pyrolysis time-of-flight (TOF) mass spectrometer equipped with an alternative ionization technique, metastable atom bombardment (MAB), was used to produce sample spectra. These spectra were analyzed by principal component and discriminant analysis for pattern recognition. Materials investigated were two strains of Vibrio parahaemolyticus, one of which produced the tdh toxin, two Salmonella enterica serotypes, a biological mosquito control product containing spores of Bacillus thuringiensis, and several white to off-white powders (which could be used as hoax materials), such as flour, corn starch, methyl cellulose, and xanthan gum. PyMS distinguished bacterial samples from hoax materials. Furthermore, pattern analysis differentiated Vibrios from Salmonellae, Salmonella enterica Anatum from S. enterica Heidelberg, and the two V. parahaemolyticus strains from each other. The B. thuringiensis mixture was distinguished from other bacteria and powders, suggesting that PyMS with pattern recognition may differentiate samples containing pathogens, including Bacillus spp., from nonbiological agents and that it can be a rapid method for detection of bacteria. MS data acquisition took only 7 min for each sample.

Bacillus thuringiensis↗

PubMed2006

Transformation of the antibacterial agent norfloxacin by environmental mycobacteria.

Because fluoroquinolone antimicrobial agents may be released into the environment, the potential for environmental bacteria to biotransform these drugs was investigated. Eight Mycobacterium sp. cultures in a sorbitol-yeast extract medium were dosed with 100 microg ml(-1) of norfloxacin and incubated for 7 days. The MICs of norfloxacin for these strains, tested by an agar dilution method, were 1.6 to 25 microg ml(-1). Cultures were extracted with ethyl acetate, and potential metabolites in the extracts were purified by high-performance liquid chromatography. The metabolites were identified using mass spectrometry and nuclear magnetic resonance spectroscopy. N-Acetylnorfloxacin (5 to 50% of the total absorbance at 280 nm) was produced by the eight Mycobacterium strains. N-Nitrosonorfloxacin (5 to 30% of the total absorbance) was also produced by Mycobacterium sp. strain PYR100 and Mycobacterium gilvum PYR-GCK. The MICs of N-nitrosonorfloxacin and N-acetylnorfloxacin were 2- to 38- and 4- to 1,000-fold higher, respectively, than those of norfloxacin for several different bacteria, including the two strains that produced both metabolites. Although N-nitrosonorfloxacin had less antibacterial activity, nitrosamines are potentially carcinogenic. The biotransformation of fluoroquinolones by mycobacteria may serve as a resistance mechanism.

Anti-Bacterial Agents↗

PubMed2005

Rapid phenotypic characterization of Vibrio isolates by pyrolysis metastable atom bombardment mass spectrometry.

Pyrolysis mass spectrometry was investigated for rapid characterization of food-borne bacterial pathogens. Nine isolates of Vibrio parahaemolyticus and one isolate each of Vibrio fluvialis, Vibrio hollisae, and Vibrio vulnificus were analyzed. Pyrolysis mass spectra, generated via an alternative ionization method, metastable atom bombardment, were subject to principal component-discriminant analysis. The spectral patterns were used to distinguish Vibrio isolates differing in species, serotype and expression of the thermostable direct hemolysin gene. The patterns of similarity and dissimilarity amongst spectra in the Vibrio test set generally reflected those associated with species, serotype or hemolysin-producing genes, though the combined influence of these and other variables in the multi-dimensional data did not produce a simple clustering with respect to any one of these characteristics. These results suggested that with enough examples to model the most common combinations, the method should be able to characterize Vibrio isolates according to their phenotypic characteristics. Pyrolysis-mass spectrometry with metastable atom bombardment and pattern recognition appeared suitable for rapid infraspecific comparison of Vibrio isolates. This integrated analytical, pattern-recognition system should be examined further for potential utility in clinical and public health diagnostic contexts.

Animals↗

PubMed2005

Rapid phenotypic characterization of Salmonella enterica strains by pyrolysis metastable atom bombardment mass spectrometry with multivariate statistical and artificial neural network pattern recognition.

Pyrolysis mass spectrometry was investigated for rapid characterization of bacteria. Spectra of Salmonella were compared to their serovars, pulsed-field gel electrophoresis (PFGE) patterns, antibiotic resistance profiles, and MIC values. Pyrolysis mass spectra generated via metastable atom bombardment were analyzed by multivariate principal component-discriminant analysis and artificial neural networks (ANNs). Spectral patterns developed by discriminant analysis and tested with Leave-One-Out (LOO) cross-validation distinguished Salmonella strains by serovar (97% correct) and by PFGE groups (49%). An ANN model of the same PFGE groups was cross-validated, using the LOO rule, with 92% agreement. Using an ANN, thirty previously unseen spectra were correctly classified by serotype (97%) and at the PFGE level (67%). Attempts by ANN to model spectra grouped by resistance profile-but ignoring PFGE or serotype-failed (10% correct), but ANNs differentiating ten samples of the same serotype/PFGE class were more successful. To assess the information content of PyMS data serendipitously associated with or directly related to resistance character, the ten isolates were grouped into four, three, or two categories. The four categories corresponded to four resistance profiles. The four class and three class ANNs showed much improved but insufficient modeling power. The two-class ANN and a corresponding multivariate model maximized inferential power for a coarse antibiotic-resistance-related distinction. They each cross-validated by LOO at 90%. This is the first direct correlation of pyrolysis metastable atom bombardment mass spectrometry with immunological (e.g. serology) or molecular biology (e.g. PFGE) based techniques.

Bacterial Typing Techniques↗

PubMed2004

Fungal biotransformation of benzo[f]quinoline, benzo[h]quinoline, and phenanthridine.

Cultures of Umbelopsis ramanniana (=Mucor ramannianus) were grown in fluid Sabouraud medium for 3 days, dosed with 0.23 mM benzo[f]quinoline, benzo[h]quinoline, or phenanthridine (benzo[c]quinoline), and incubated for another 18 days. Cultures were extracted and metabolites (66-75% of the UV absorbance) were separated by high-performance liquid chromatography. They were identified by mass spectrometry and nuclear magnetic resonance spectroscopy. Benzo[f]quinoline was metabolized to benzo[f]quinoline trans-7,8-dihydrodiol, benzo[f]quinoline N-oxide, and 7-hydroxybenzo[f]quinoline, benzo[h]quinoline was metabolized to benzo[h]quinoline trans-5,6-dihydrodiol, benzo[h]quinoline trans-7,8-dihydrodiol, and 7-hydroxybenzo[h]quinoline, and phenanthridine was metabolized to phenanthridine N-oxide and phenanthridin-6(5H)-one. At least one of the metabolites produced from each compound was mutagenic and could not be considered detoxified.

Biotransformation↗

PubMed2002

Transformation of cinoxacin by Beauveria bassiana.

The ability of the fungus Beauveria bassiana ATCC 7159 to transform the antibacterial agent cinoxacin was investigated. Cultures in sucrose-peptone broth were dosed with cinoxacin, grown for 20 days, and then extracted with ethyl acetate. Two metabolites were detected and purified by high-performance liquid chromatography. The major metabolite was identified by mass and proton nuclear magnetic resonance spectra as 1-ethyl-1,4-dihydro-3-(hydroxymethyl)[1,3]dioxolo[4,5-g]cinnolin-4-one and the minor metabolite was identified as 1-ethyl-1,4-dihydro-6,7-dihydroxy-3-(hydroxymethyl)cinnolin-4-one. B. bassiana also reduced quinoline-3-carboxylic acid to 3-(hydroxymethyl)quinoline.

4-Quinolones↗

PubMed2002

Defining and using microbial spectral databases.

This work shows how fingerprints of mass spectral patterns from microbial isolates are affected by variations in instrumental condition, by sample environment, and by sample handling factors. It describes a novel method by which pattern distortions can be mathematically corrected for variations in factors not amenable to experimental control. One uncontrollable variable is "between-batch" differences in culture media. Another, relevant for determination of noncultured extracts, is differences between the cells' environmental experience (e.g., starved environmental extracts versus cultured standards). The method suggests that, after a single growth cycle on a solid medium (perhaps, a selective one), pyrolysis MS spectra of microbial isolates can be algorithmically compensated and an unknown isolate identified using a spectral database defined by culture on a different (perhaps, nonselective) medium. This reduces identification time to as few as 24 h from sample collection. The concept also proposes a possible way to compensate certain noncultured, nonisolated samples (e.g., cells concentrated from urine or impacted from aerosol or semi-selectively extracted by immunoaffinity methods from heavily contaminated matrices) for identification within half an hour. Using the method, microbial mass spectra from different labs can be assembled into coherent databases similar to those routinely used to identify pure compounds. This type of data treatment is applicable for rapid detection in biowarfare and bioterror events as well as in forensic, research, and clinical laboratory contexts.

Algorithms↗