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

Citation
Aj. Madonna et al., 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, J AN AP PYR, 61(1-2), 2001, pp. 65-89
Citations number
41
Categorie Soggetti
Spectroscopy /Instrumentation/Analytical Sciences
Journal title
JOURNAL OF ANALYTICAL AND APPLIED PYROLYSIS
ISSN journal
01652370 → ACNP
Volume
61
Issue
1-2
Year of publication
2001
Pages
65 - 89
Database
ISI
SICI code
0165-2370(200111)61:1-2<65:RDOTIF>2.0.ZU;2-Q
Abstract
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, p ollen, media contaminated with viruses, and proteins were treated with an a liquot of methanolic tetramethylammonium hydroxide prior to thermal introdu ction into the ion source of a triple quadrupole mass spectrometer. Molecul ar and fragment ions, consistent with fatty acid methyl esters (FAMEs) and steroids (non-methylated and methylated), generated during electron ionizat ion (70 eV) of the volatile hydrolysates were subsequently detected. The va rying distributions and relative intensities of these ions were used to dis criminate between the different biological samples. More specifically, it w as found that polyunsaturated FAMEs and steroids could be used to different iate eukaryotic cells from prokaryotic cells since the latter do not genera lly synthesize either of these lipid membrane constituents. Further discrim ination 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 comp are 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, 1 31 were correctly classified into their proper biological categories. Moreo ver, 29 out of 30 bacteria test samples representing five species of pathog enic bacteria were correctly classified at the species level. (C) 2001 Else vier Science B.V. All rights reserved.