Quantitative Sampling of Indoor Air Biomass by Signature Lipid Biomarker Analysis: Feasibility Studies in a Model System

Characterization of non-discriminating tetramethylammonium hydroxide-induced thermochemolysis–capillary gas chromatography–mass spectrometry as a method for profiling fatty acids in bacterial biomasses

Thermochemolysis using tetramethylammonium hydroxide (TMAH) as a method for profiling fatty acids (FAs) as methyl esters (FAMEs) was studied with respect to discrimination of bacterial fatty acid patterns in Gram-negative Pseudomonas putida in comparison with patterns obtained by classical preparation schemes (pressurized solvent extraction, alkaline saponification). A new, non-discriminating pyrolysis approach was used in these experiments. In this method, pyrolysis is carried out inside a deactivated stainless steel capillary constituting a part of the column train. This approach made it possible to distinguish analyte discrimination brought about by (i) the pyrolyzer set-up in conventional pyrolysis and (ii) chemical thermochemolysis reaction itself. Our results showed no significant discrimination for saturated, monounsaturated and cyclopropane FAs when using thermochemolysis temperatures up to 550 degrees C with the non-discriminating, capacitive-discharged based approach. Likewise, the cis/trans ratio of monounsaturated FAs was preserved. This is in sharp contrast to conventional pyrolysis systems (both Curie-point or flash pyrolyzers) using much longer thermochemolysis times. When using these systems, artificial monounsaturated FAMEs were formed during heat treatment resulting in biased species identification/classification. Hydroxy-FAs, chiefly bound covalently in lipopolysaccharides, could be almost quantitatively liberated by TMAH using non-discriminating pyrolysis (beyond 90%), whereas the recoveries were lower with conventional approaches. The new method makes it possible to profile fatty acids in very small amounts of both solid and liquid samples without significant sample preparation. This was exemplified by the results of TMAH-thermochemolysis of a fermentation broth taken from an in situ bioremediation reactor to monitor enhanced natural attenuation processes, and tomato roots which were subjected to cellulolytic bacteria attacks (Streptomyces), resulting in adsorption of these carboxymethyl-cellulose decomposing bacteria onto the root.

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

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.