Selected article for: "pathogenic bacteria and statistical analysis"

Author: Madonna, Angelo J.; Voorhees, Kent J.; Hadfield, Ted L.
Title: Rapid detection of taxonomically important fatty acid methyl ester and steroid biomarkers using in situ thermal hydrolysis/methylation mass spectrometry (THM-MS): implications for bioaerosol detection
  • Cord-id: 4fou5yy1
  • Document date: 2001_10_8
  • ID: 4fou5yy1
    Snippet: Implications for the rapid interrogation of biological materials collected from the atmosphere using a simple, one step, sample preparation technique was explored. For this purpose, various samples of whole bacteria, fungi, pollen, media contaminated with viruses, and proteins were treated with an aliquot of methanolic tetramethylammonium hydroxide prior to thermal introduction into the ion source of a triple quadrupole mass spectrometer. Molecular and fragment ions, consistent with fatty acid m
    Document: Implications for the rapid interrogation of biological materials collected from the atmosphere using a simple, one step, sample preparation technique was explored. For this purpose, various samples of whole bacteria, fungi, pollen, media contaminated with viruses, and proteins were treated with an aliquot of methanolic tetramethylammonium hydroxide prior to thermal introduction into the ion source of a triple quadrupole mass spectrometer. Molecular and fragment ions, consistent with fatty acid methyl esters (FAMEs) and steroids (non-methylated and methylated), generated during electron ionization (70 eV) of the volatile hydrolysates were subsequently detected. The varying distributions and relative intensities of these ions were used to discriminate between the different biological samples. More specifically, it was found that polyunsaturated FAMEs and steroids could be used to differentiate eukaryotic cells from prokaryotic cells since the latter do not generally synthesize either of these lipid membrane constituents. Further discrimination of the different eukaryotic samples was made based on the detection of ergosterol for fungi, cholesterol for the viral media, and C18:3Me for pollen. Multivariate statistical analysis was employed to evaluate and compare the large set of mass spectra generated during the study and to build a trained model for predicting the class membership of test samples entered as unknowns. Of 132 different samples subjected to the model as unknowns, 131 were correctly classified into their proper biological categories. Moreover, 29 out of 30 bacteria test samples representing five species of pathogenic bacteria were correctly classified at the species level.

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