Non-targeted analytical comparison of a heated tobacco product aerosol against mainstream cigarette smoke: does heating tobacco produce an inherently different set of aerosol constituents?

Smoking-related diseases remain a significant public health concern, and heated tobacco products (HTPs) have emerged as a potential alternative to cigarettes. While several studies have confirmed that HTP aerosols contain lower levels of harmful and potentially harmful constituents (HPHCs) than cigarette smoke, less is known about constituents that are intrinsically higher in HTP aerosols. This study provides a comprehensive comparative assessment of an HTP aerosol produced with Tobacco Heating System 2.2 (THS) and comparator cigarette (CC) smoke aiming at identifying all unique or increased compounds in THS aerosol by applying a broad set of LC-MS and GC × GC-MS methods. To focus on differences due to heating versus burning tobacco, confounding factors were minimized by using the same tobacco in both test items and not adding flavorants. Of all analytical features, only 3.5%-corresponding to 31 distinctive compounds-were significantly more abundant in THS aerosol than in CC smoke. A notable subset of these compounds was identified as reaction products of glycerol. The only compound unique to THS aerosol was traced back to its presence in a non-tobacco material in the test item and not a direct product of heating tobacco. Our results demonstrate that heating a glycerol-containing tobacco substrate to the temperatures applied in THS does not introduce new compounds in the resulting aerosol compared to CC smoke which are detectable with the method portfolio applied in this study. Overall, this study contributes to a better understanding of the chemical composition of HTP aerosols and their potential impact on human health.

Comprehensive chemical characterization of the aerosol generated by a heated tobacco product by untargeted screening.

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. Graphical abstract.

Performance Evaluation of a Nontargeted Platform Using Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry Integrating Computer-Assisted Structure Identification and Automated Semiquantification for the Comprehensive Chemical Characterization of a Complex Matrix.

Nontargeted screening methodologies are powerful approaches for comprehensive chemical characterization of complex matrixes. In order to maximize chemical space coverage, three analytical methods using two-dimensional gas chromatography with time-of-flight mass spectrometry for nonpolar, polar, and volatile compounds have been established. The structural identification process was streamlined with an in-house developed computer-assisted structure identification platform, which facilitated the identification of novel compounds and also delivered semiquantitative concentrations for all compounds. Key performance parameters for this nontargeted platform, including chemical space coverage, confidence for structural identification, accuracy of semiquantification, and performance of differential analysis, were evaluated. The automated structural identification process was assessed using a subset of 243 compounds (out of 2990), which were confirmed to be present in cigarette smoke using reference standards. Consistently high true positive identification rates between 88.2% and 96.2% across the different concentration ranges investigated were demonstrated. Accuracy for semiquantification was assessed by comparison with quantitative data from literature, where a maximum 4-fold deviation from available targeted analysis values was estimated.

Correlations between milk and plasma levels of amino and carboxylic acids in dairy cows.

The objective of this study was to investigate the relationship between the concentrations of 19 amino acids, glucose, and seven carboxylic acids in the blood and milk of dairy cows and their correlations with established markers of ketosis. To that end, blood plasma and milk specimens were collected throughout lactation in two breeds of dairy cows of different milk yield. Plasma concentrations of glucose, pyruvate, lactate, α-aminobutyrate, ß-hydroxybutyrate (BHBA), and most amino acids, except for glutamate and aspartate, were on average 9.9-fold higher than their respective milk levels. In contrast, glutamate, aspartate, and the Krebs cycle intermediates succinate, fumarate, malate, and citrate were on average 9.1-fold higher in milk than in plasma. For most metabolites, with the exception of BHBA and threonine, no significant correlations were observed between their levels in plasma and milk. Additionally, milk levels of acetone showed significant direct relationships with the glycine-to-alanine ratio and the BHBA concentration in plasma. The marked decline in plasma concentrations of glucose, pyruvate, lactate, and alanine in cows with plasma BHBA levels above the diagnostic cutoff point for subclinical ketosis suggests that these animals fail to meet their glucose demand and, as a consequence, rely increasingly on ketone bodies as a source of energy. The concomitant increase in plasma glycine may reflect not only the excessive depletion of protein reserves but also a potential deficiency of vitamin B6.

Comprehensive two-dimensional gas chromatography in metabolomics.

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.

Metabolic fingerprinting using comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry.

Comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOF-MS) is applied to the comparative metabolic fingerprinting of physiological fluids. Stable isotope-labeled internal standards plus norvaline serve as extraction standards and are added to the blanks, controls and patient samples prior to protein precipitation with methanol. The extracts are evaporated to complete dryness and derivatized in two steps using methoximation with methoxylamine hydrochloride (MeOx) and silylation with N-methyl-N-trimethylsily-trifluoroacetamide (MSTFA). Between derivatization steps a second internal standard containing odd-numbered, saturated straight chain fatty acids is added for quality control and to normalize retention time shifts. After GC × GC-TOF-MS analysis raw data are processed, aligned, and combined in one data matrix for subsequent statistical evaluation. Both a custom-made and the NIST 05 library are used to preliminarily identify significant metabolites. For verification purposes, commercial standards are run individually. Absolute quantification of selected metabolites is achieved by using a multi-point calibration curve and isotope-labeled internal standards.

Performance evaluation of gas chromatography-atmospheric pressure chemical ionization-time-of-flight mass spectrometry for metabolic fingerprinting and profiling.

Gas chromatography-atmospheric-pressure chemical ionization-time-of-flight mass spectrometry (GC-APCI-TOFMS) was compared to GC × GC-electron ionization (EI)-TOFMS, GC-EI-TOFMS, GC-chemical ionization (CI)-quadrupole mass spectrometry (qMS), and GC-EI-qMS in terms of reproducibility, dynamic range, limit of detection, and quantification using a mix of 43 metabolites and 12 stable isotope-labeled standards. Lower limits of quantification for GC-APCI-TOFMS ranged between 0.06 and 7.81 µM, and relative standard deviations for calibration replicates were between 0.4% and 8.7%. For all compounds and techniques, except in four cases, R(2) values were above 0.99. Regarding limits of quantification, GC-APCI-TOFMS was inferior to only GC × GC-EI-TOFMS, but outperformed all other techniques tested. GC-APCI-TOFMS was further applied to the metabolic fingerprinting of two Escherichia coli strains. Of 45 features that differed significantly (false discovery rate < 0.05) between the strains, 25 metabolites were identified through highly accurate and reproducible (Δm ± SD below 5 mDa over m/z 190-722) mass measurements. Starting from the quasimolecular ion, six additional metabolites were identified that had not been found in a previous study using GC × GC-EI-TOFMS and an EI mass spectral library for identification purposes. Silylation adducts formed in the APCI source assisted the identification of unknown compounds, as their formation is structure-dependent and is not observed for compounds lacking a carboxylic group.

Comparison of two algorithmic data processing strategies for metabolic fingerprinting by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry.

The alignment algorithm Statistical Compare (SC) developed by LECO Corporation for the processing of comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS) data was validated and compared to the in-house developed retention time correction and data alignment tool INCA (Integrative Normalization and Comparative Analysis) by a spike-in experiment and the comparative metabolic fingerprinting of a wild type versus a double mutant strain of Escherichia coli (E. coli). Starting with the same peak lists generated by LECO's ChromaTOF software, the accuracy of peak alignment and detection of 1.1- to 4-fold changes in metabolite concentration was assessed by spiking 20 standard compounds into an aqueous methanol extract of E. coli. To provide the same quality input signals for both alignment routines, the universal m/z 73 trace of the trimethylsilyl (TMS) group was used as a quantitative measure for all features. The performance of data processing and alignment was evaluated and illustrated by ROC curves. Statistical Compare performed marginally better at the lower fold changes, while INCA did so at the higher fold changes. Using SC, quantitative precision could be improved substantially by exploiting the signal intensities of metabolite-specific unique (U) m/z ion traces rather than the universal m/z 73 trace. A list of 56 features that distinguished the two E. coli strains was obtained by the SC alignment using m/z U with an estimated false discovery rate (FDR) of <0.05. Ultimately, 23 metabolites could be identified, one additional and five less than with INCA due to the failure of SC to extract unitized m/z U's across all fingerprints with suitable spectral intensities for the latter metabolites.

Improved enantiomer resolution and quantification of free D-amino acids in serum and urine by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry.

The potential of comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS) in the quantitative analysis of amino acid enantiomers (AAEs) as their methyl chloroformate (MCF) derivatives in physiological fluids was investigated. Of the two column sets tested, the combination of an Rt-γDEXsa chiral column with a polar ZB-AAA column provided superior selectivity. Twenty AAEs were baseline resolved including L-Leu and D-Ile, which had failed separation by one-dimensional chiral GC-quadrupole-MS (GC-qMS). Lower limits of quantification (LLOQ) were in the range of 0.03-2 µM. Reproducibility of the analysis of a serum specimen in octaplicate ranged from 1.3 to 16.6%. The GC×GC-TOFMS method was validated by analyzing AAEs in 48 urine and 43 serum specimens, respectively, and by comparing the results with data obtained by a previously validated GC-qMS method. Mean recoveries ranged from 78.4% for D-Leu to 116.4% for D-Pro in urine and 72.2% for L-Thr to 129.4% for L-Ile in serum. The method was applied to the comparison of AAE serum levels in patients suffering from liver cirrhosis to a control group. Significantly increased D-AA concentrations were found for the patient group, whereas L-AA levels were slightly decreased.

Metabolite extraction from adherently growing mammalian cells for metabolomics studies: optimization of harvesting and extraction protocols.

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.

Comparison of serum versus plasma collection in gas chromatography--mass spectrometry-based metabolomics.

Bovine serum, EDTA-plasma and EDTA-plasma fortified with acetylsalicylic acid (ASA) as antioxidant were compared with regard to their suitability for metabolomic studies. Metabolic fingerprints were generated from GC-TOF-MS data using the Leco ChromaTOF software in combination with the in-house retention time correction and data alignment tool INCA. A total of 6, 9 and 21 significant features with a false discovery rate of <0.05 were identified by INCA upon comparing EDTA- versus EDTA-ASA-plasma, EDTA-plasma versus serum and EDTA-ASA-plasma versus serum, respectively. To confirm that the observed signal intensities in the GC-TOF-MS fingerprints reflected true metabolite abundances, 19 amino acids, glucose and 6 organic acids were quantified by means of GC-MS using stable-isotope-labeled internal standards. As observed with the fingerprints, only the concentrations of lactate and citrate were found to be significantly lower in EDTA-plasma and serum, respectively, whereas the concentrations of the other metabolites were similar among the three sample types investigated.

Integrative normalization and comparative analysis for metabolic fingerprinting by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry.

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.