Trypsin/ethylenediaminetetraacetic acid (EDTA) treatment and cell scraping in a buffer solution were compared for harvesting adherently growing mammalian SW480 cells for metabolomics studies. In addition, direct scraping with a solvent was tested. Trypsinated and scraped cell pellets were extracted using seven different extraction protocols including pure methanol, methanol/water, pure acetone, acetone/water, methanol/chloroform/water, methanol/isopropanol/water, and acid-base methanol. The extracts were analyzed by GC-MS after methoximation/silylation and derivatization with propyl chloroformate, respectively. The metabolic fingerprints were compared and 25 selected metabolites including amino acids and intermediates of energy metabolism were quantitatively determined. Moreover, the influence of freeze/thaw cycles, ultrasonication and homogenization using ceramic beads on extraction yield was tested. Pure acetone yielded the lowest extraction efficiency while methanol, methanol/water, methanol/isopropanol/water, and acid-base methanol recovered similar metabolite amounts with good reproducibility. Based on overall performance, methanol/water was chosen as a suitable extraction solvent. Repeated freeze/thaw cycles, ultrasonication and homogenization did not improve overall metabolite yield of the methanol/water extraction. Trypsin/EDTA treatment caused substantial metabolite leakage proving it inadequate for metabolomics studies. Gentle scraping of the cells in a buffer solution and subsequent extraction with methanol/water resulted on average in a sevenfold lower recovery of quantified metabolites compared with direct scraping using methanol/water, making the latter one the method of choice to harvest and extract metabolites from adherently growing mammalian SW480 cells.

Milk production in dairy cows has dramatically increased over the past few decades. The selection for higher milk yield affects the partitioning of available nutrients, with more energy being allocated to milk synthesis and less to physiological processes essential to fertility and fitness. In this study, the abundance of numerous milk metabolites in early and late lactation was systematically investigated, with an emphasis on metabolites related to energy metabolism. The aim of the study was the identification and correlation of milk constituents to the metabolic status of the cows. To investigate the influence of lactation stage on physiological and metabolic variables, 2 breeds of different productivity were selected for investigation by high-resolution nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry. We could reliably quantify 44 different milk metabolites. The results show that biomarkers such as acetone and beta-hydroxybutyrate are clearly correlated to the metabolic status of the individual cows during early lactation. Based on these data, the selection of cows that cope well with the metabolic stress of early lactation should become an option.

A suite of untargeted methods has been applied for the characterization of aerosol from the Tobacco Heating System 2.2 (THS2.2), a heated tobacco product developed by Philip Morris Products S.A. and commercialized under the brand name IQOS®. A total of 529 chemical constituents, excluding water, glycerin, and nicotine, were present in the mainstream aerosol of THS2.2, generated by following the Health Canada intense smoking regimen, at concentrations ≥ 100 ng/item. The majority were present in the particulate phase (n = 402), representing more than 80% of the total mass determined by untargeted screening; a proportion were present in both particulate and gas-vapor phases (39 compounds). The identities for 80% of all chemical constituents (representing > 96% of the total determined mass) were confirmed by the use of authentic analytical reference materials. Despite the uncertainties that are recognized to be associated with aerosol-based untargeted approaches, the reported data remain indicative that the uncharacterized fraction of TPM generated by THS2.2 has been evaluated to the fullest practicable extent. To the best of our knowledge, this work represents the most comprehensive chemical characterization of a heated tobacco aerosol to date.

One of the major objectives in metabolomics is the identification of subtle changes in metabolite profiles as affected by genetic or environmental factors. Comprehensive two-dimensional gas chromatography (GC × GC) hyphenated to a fast-acquisition mass spectrometer is a well-established analytical technique to study the composition of complex samples due to its enhanced separation capacity, sensitivity, peak resolution, and reproducibility. This review reports applications of GC × GC to metabolomics studies of sample of different types (biofluid, cells, tissue, bacteria, yeast, plants), and discusses its advantages and limitations.

Comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC x GC-TOF-MS) was applied to the comparative metabolic fingerprinting of a wild-type versus a double mutant strain of Escherichia coli lacking the transhydrogenases UdhA and PntAB. Using peak lists generated with the Leco ChromaTOF software as input, we developed retention time correction and data alignment tools (INCA). The accuracy of peak alignment and detection of 1.1- to 4-fold changes in metabolite concentration was validated by a spike-in experiment with 20 standard compounds. A list of 48 significant features that differentiated the two E. coli strains was obtained with an estimated false discovery rate (FDR) of <0.05. A total of 27 metabolites, mainly from the citrate cycle, were identified. That the signal intensity of the m/z 73 trace of the trimethylsilyl (TMS) group reflected true differences in metabolite abundance was confirmed by quantification of pyruvate, fumarate, malate, succinate, alpha-ketoglutarate, citrate, cis-aconitate, myo-inositol, and glucose-6-phosphate using compound specific fragment ions and stable isotope labeled standards. Relative standard deviations for metabolite extraction and GC x GC-TOF-MS analysis of those analytes ranged from 13.2 to 26.3% for the universal m/z 73 trace and 7.4 to 24.5% for the analyte specific fragment ion trace.