Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry was used for the identification of forty doping agents. The improvement in the specificity was remarkable, allowing the resolution of analytes that could not be done by one-dimensional chromatographic systems. The sensitivity observed for different classes of prohibited substances was clearly below the value required by the World Anti-Doping Agency. In addition time-of-flight mass spectrometry gives full spectrum for all analytes without any interference from the matrix, resulting in selectivity improvements. These results could support the implementation of an exhaustive monitoring approach for hundreds of doping agents in a single injection.
Comprehensive two-dimensional gas chromatography coupled to time of flight mass spectrometry (GC × GC-TOFMS) was applied to evaluate the CO2 effect on distribution of n-alkanes, branched alkanes, alkenes and oxygen-containing compounds in Fischer-Tropsch products. GC × GC-TOFMS was able to resolve the unresolved compounds observed in conventional GC.
Comprehensive two-dimensional gas chromatography with time of flight mass spectrometry (GC×GC-TOFMS) is an appropriate technique for the elucidation of molecular composition of petrochemical samples, such as biodegraded oils. Biomarkers were separated and identified, and conventional biomarker ratios were determined via gas chromatography-mass spectrometry (GC-MS) and GC×GC-TOFMS. In the extracted ion chromatogram m/z 123 + 177 + 191, coelutions between tricyclic terpanes, hopanes and 25-nor-hopanes with secohopanes were resolved by GC×GC-TOFMS. GC×GC-TOFMS allowed the identification of complete series of 25-nor-hopanes, nor-gammacerane, C29 28-nor-spergulanes and oleanane not identified by using GC-MS. The biomarker ratios from the studied oils indicated that they derived from marine source rock deposited under anoxic conditions. The higher chromatographic resolution and sensitivity achieved by using GC×GC-TOFMS allowed for three new parameters to characterize biodegraded oils. These results indicated the superiority of GC×GC-TOFMS for separation and identification of individual and non-target compounds in severely biodegraded oils.
Comprehensive two-dimensional gas chromatography with time-of- flight mass spectrometry (GCxGC-TOFMS) coupled with rapid chemometric analysis were used to identify chemical differences in metabolite extracts isolated from yeast cells either metabolizing glucose (repressed (R) cells) via fermentation, or metabolizing ethanol by respiration (derepressed (DR) cells). Principal component analysis (PCA) followed by Parallel Factor Analysis (PARAFAC) in concert with the LECO ChromaTOF software located and identified the differences in composition between the two types of cell extracts and provided a reliable ratio of the metabolite concentrations. In this report, we demonstrate the analytical method developed to provide relatively rapid analysis of three selective mass channels (m/z 73, 205, 387), although in principle all collected mass channels could be analyzed. Twenty-six metabolites that differentiate repressed cells from derepressed cells were identified. The DR/R ratio of metabolite concentrations ranged from 0.02 for glucose to 67 for trehalose. The average biological variation of the sample extracts was 31%. This analysis demonstrates the utility and benefit of using PCA combined with PARAFAC and ChromaTOF software on extremely complex samples to derive useful information from complex three-dimensional chromatographic data objectively and relatively rapidly.
Complementary methods using liquid chromatography - tandem quadrupole mass spectrometry (LC-MS/MS) and comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOF-MS) were developed and applied to determine targeted metabolites involved in central carbon metabolism [including tricarboxylic acid cycle, serine cycle, ethylmalonyl-coenzyme A (ethylmalonyl-CoA) pathway and poly-β-hydroxybutyrate cycle] of the bacterium Methylobacterium extorquens AM1 grown on two carbon sources, ethylamine (C2) and succinate (C4). Nucleotides, acyl-CoAs and a few volatile metabolites in cell extracts of M. extorquens AM1 were readily separated using either hydrophilic interaction liquid chromatography or reversed-phase liquid chromatography, and detected with good sensitivity by MS/MS. However, volatile intermediates within a low mass range (<300 m/z), especially at low abundance (such as glyoxylic acid and others <500 nM), were more effectively analyzed by GC × GC-TOF-MS which often provided better sensitivity, resolution and reproducibility. The complementary nature of the LC-based and GC-based methods allowed the comparison of 39 metabolite concentrations (the lowest level was at 139.3 nM). The overlap between the LC and GC-based methods of 7 metabolites provided a basis to check for consistency between the two methods...
Perinatal asphyxia is a leading cause of brain injury in infants, occurring in 2–4 per 1000 live births. The clinical response to asphyxia is variable and difficult to predict with current diagnostic tests. Reliable biomarkers are needed to help predict the timing and severity of asphyxia, as well as response to treatment. Two-dimensional gas chromatography-time-of-flight-mass spectrometry (GC x GC-TOFMS) was used herein, in conjunction with chemometric data analysis approaches for metabolomic analysis in order to identify significant metabolites affected by birth asphyxia. Blood was drawn before and after 15 or 18 minutes of cord occlusion in a Macaca nemestrina model of perinatal asphyxia. Postnatal samples were drawn at 5 minutes of age (n=20 subjects). Metabolomic profiles of asphyxiated animals were compared to four controls delivered at comparable gestational age. Fifty metabolites with the greatest change pre- to post-asphyxia were identified and quantified. The metabolic profile of post-asphyxia samples showed marked variability compared to the pre-asphyxia samples. Fifteen of the 50 metabolites showed significant elevation in response to asphyxia, ten of which remained significant upon comparison to the control animals. This metabolomic analysis confirmed lactate and creatinine as markers of asphyxia and discovered new metabolites including succinic acid and malate (intermediates in the Krebs cycle) and arachidonic acid (a brain fatty acid and inflammatory marker) as potential biomarkers. GC × GC-TOFMS coupled with chemometric data analysis are useful tools to identify acute biomarkers of brain injury. Further study is needed to correlate these metabolites with severity of disease...
A method was developed to calculate the second dimension retention index of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOF-MS) data using n-alkanes as reference compounds. The retention times of the C7-C31 alkanes acquired during 24 isothermal experiments cover the 0 – 6 s retention time area in the second dimension retention time space, which makes it possible to calculate the retention indices of target compounds from the corresponding retention time values without the extension of the retention space of the reference compounds. An empirical function was proposed to show the relationship among the second dimension retention time, the temperature of the second dimension column, and the carbon number of the n-alkanes. The proposed function is able to extend the second dimension retention time beyond the reference n-alkanes by increasing the carbon number. The extension of carbon numbers in reference n-alkanes up to two more carbon atoms introduces less than 10 retention index units (iu) of deviation. The effectiveness of using the proposed method was demonstrated by analyzing a mixture of compound standards in temperature programmed experiments using 6 different initial column temperatures. The standard deviation of the calculated retention index values of the compound standards fluctuated from 1 to 12 iu with a mean standard deviation of 5 iu.
A comprehensive two-dimensional gas chromatography (GC×GC) time-of-flight mass spectrometry method was developed for determination of fatty acids (irrespective of origin i.e., both free fatty acids and fatty acids bound in sources such as triglycerides) in cultured mammalian cells. The method was applied to INS-1 cells, an insulin-secreting cell line commonly used as a model in diabetes studies. In the method, lipids were extracted and transformed to fatty acid methyl esters for analysis. GC×GC analysis revealed the presence of 30 identifiable fatty acids in the extract. This result doubles the number of fatty acids previously identified in these cells. The method yielded linear calibrations and an average relative standard deviation of 8.4 % for replicate injections of samples and 12.4 % for replicate analysis of different samples. The method was used to demonstrate changes in fatty acid content as a function of glucose concentration on the cells. These results demonstrate the utility of this method for analysis of fatty acids in mammalian cell cultures.
Soon after death, the decay process of mammalian soft tissues begins and leads to the release of cadaveric volatile compounds in the surrounding environment. The study of postmortem decomposition products is an emerging field of study in forensic science. However, a better knowledge of the smell of death and its volatile constituents may have many applications in forensic sciences. Domestic pigs are the most widely used human body analogues in forensic experiments, mainly due to ethical restrictions. Indeed, decomposition trials on human corpses are restricted in many countries worldwide. This article reports on the use of comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GCxGC-TOFMS) for thanatochemistry applications. A total of 832 VOCs released by a decaying pig carcass in terrestrial ecosystem, i.e. a forest biotope, were identified by GCxGC-TOFMS. These postmortem compounds belong to many kinds of chemical class, mainly oxygen compounds (alcohols, acids, ketones, aldehydes, esters), sulfur and nitrogen compounds, aromatic compounds such as phenolic molecules and hydrocarbons. The use of GCxGC-TOFMS in study of postmortem volatile compounds instead of conventional GC-MS was successful.
A yeast metabolome exhibiting oscillatory behavior was analyzed using comprehensive two-dimensional gas chromatography - time-of-flight mass spectrometry (GC × GC–TOF-MS) and in-house developed data analysis software methodology, referred to as a signal ratio method (Sratio method). In this study 44 identified unique metabolites were found to exhibit cycling, with a depth-of-modulation amplitude greater than three. After the initial locations are found using the Sratio software, and identified preliminarily using ChromaTOF software, the refined mass spectra and peak volumes were subsequently obtained using parallel factor analysis (PARAFAC). The peak volumes provided by PARAFAC deconvolution provide a measurement of the cycling depth-of-modulation amplitude that is more accurate than the initial Sratio information (which serves as a rapid screening procedure to find the cycling metabolites while excluding peaks that do not cycle). The Sratio reported is a rapid method to determine the depth-of-modulation while not constraining the search to specific cycling frequencies. The phase delay of the cycling metabolites ranged widely in relation to the oxygen consumption cycling pattern.
Motivation: Due to the high complexity of metabolome, the comprehensive 2D gas chromatography time-of-flight mass spectrometry (GC×GC-TOF MS) is considered as a powerful analytical platform for metabolomics study. However, the applications of GC×GC-TOF MS in metabolomics are not popular owing to the lack of bioinformatics system for data analysis.
We report a novel peak sorting method for the two-dimensional gas chromatography/time-of-flight mass spectrometry (GC×GC/TOF-MS) system. The objective of peak sorting is to recognize peaks from the same metabolite occurring in different samples from thousands of peaks detected in the analytical procedure. The developed algorithm is based on the fact that the chromatographic peaks for a given analyte have similar retention times in all of the chromatograms. Raw instrument data are first processed by ChromaTOF (Leco) software to provide the peak tables. Our algorithm achieves peak sorting by utilizing the first and second dimension retention times in the peak tables and the mass spectra generated during the process of electron impact ionization. The algorithm searches the peak tables for the peaks generated by the same type of metabolite using several search criteria. Our software also includes options to eliminate non-target peaks from the sorting results, e.g., peaks of contaminants. The developed software package has been tested using a mixture of standard metabolites and another mixture of standard metabolites spiked into human serum. Manual validation demonstrates high accuracy of peak sorting with this algorithm.
We develop a novel peak detection algorithm for the analysis of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOF MS) data using normal-exponential-Bernoulli (NEB) and mixture probability models. The algorithm first performs baseline correction and denoising simultaneously using the NEB model, which also defines peak regions. Peaks are then picked using a mixture of probability distribution to deal with the co-eluting peaks. Peak merging is further carried out based on the mass spectral similarities among the peaks within the same peak group. The algorithm is evaluated using experimental data to study the effect of different cut-offs of the conditional Bayes factors and the effect of different mixture models including Poisson, truncated Gaussian, Gaussian, Gamma, and exponentially modified Gaussian (EMG) distributions, and the optimal version is introduced using a trial-and-error approach. We then compare the new algorithm with two existing algorithms in terms of compound identification. Data analysis shows that the developed algorithm can detect the peaks with lower false discovery rates than the existing algorithms, and a less complicated peak picking model is a promising alternative to the more complicated and widely used EMG mixture models.
Bacteria produce unique volatile mixtures that could be used to identify infectious agents to the species, and possibly the strain level. However, due to the immense variety of human pathogens, and the close relatedness of some of these bacteria, the robust identification of the bacterium based on its volatile metabolome is likely to require a large number of volatile compounds for each species. We applied comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (GC×GC-TOFMS) to the identification of the headspace volatiles of P. aeruginosa PA14 grown for 24 h in lysogeny broth. This is the first reported use of GC×GC-TOFMS for the characterization of bacterial headspace volatiles. The analytical purity that is afforded by this chromatographic method facilitated the identification of 28 new P. aeruginosa-derived volatiles, nearly doubling the list of volatiles for this species.
Luzhoulaojiao liquor is a type of Chinese liquor that dates back hundreds of years, but whose precise chemical composition remains unknown. This paper describes the screening of the liquor and the identification of its compounds using comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GC × GC/TOF-MS). Samples were prepared by both liquid-liquid extraction and solid-phase microextraction, which facilitated the detection of thousands of compounds in the liquor, thus demonstrating the superior performance of the proposed method over those reported in previous studies. A total of 320 compounds were common to all 18 types of Luzhoulaojiao liquor studied here, and 13 abundant and potentially bioactive compounds were further quantified. The results indicated that the high-performance method presented here is well suited for the detection and identification of compounds in liquors. This study also contributes to enriching our knowledge of the contents of Chinese liquors.
Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC/TOF-MS) has been applied to metabolomics analyses recently. However, retention time shifts in the two-dimensional gas chromatography will introduce difficulty to compare compound profiles obtained from multiple samples. In this work, a novel two-stage peak alignment algorithm has been developed for data analysis of GC×GC/TOF-MS. In the first stage, our algorithm detects and merges multiple peak entries of the same metabolite into one peak entry. After a z-score transformation of metabolite retention times, landmark peaks will be selected from all samples based on both two-dimensional retention times and mass spectrum similarity of fragment ions measured by Pearson's correlation coefficient. In the second stage, the original two-dimensional retention time shift will be corrected using a local linear fitting method. A progressive retention time map searching method is used to align peaks in all samples together based on the parameters optimized in the first stage. Our algorithm can avoid defining a threshold of retention time window and spectrum similarity, which is very difficult for the users since the experimental condition is always changed in different experimental runs...
An analytical methodology based on headspace solid phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography—time-of-flight mass spectrometry (GC × GC–ToFMS) was developed for the identification and quantification of the toxic contaminant ethyl carbamate (EC) directly in fortified wines. The method performance was assessed for dry/medium dry and sweet/medium sweet model wines, and for quantification purposes, calibration plots were performed for both matrices using the ion extraction chromatography (IEC) mode (m/z 62). Good linearity was obtained with a regression coefficient (r2) higher than 0.981. A good precision was attained (R.S.D. <20%) and low detection limits (LOD) were achieved for dry (4.31 μg/L) and sweet (2.75 μg/L) model wines. The quantification limits (LOQ) and recovery for dry wines were 14.38 μg/L and 88.6%, whereas for sweet wines were 9.16 μg/L and 99.4%, respectively. The higher performance was attainted with sweet model wine, as increasing of glucose content improves the volatile compound in headspace, and a better linearity, recovery and precision were achieved. The analytical methodology was applied to analyse 20 fortified Madeira wines including different types of wine (dry...
We develop a novel peak detection algorithm for the analysis of comprehensive
two-dimensional gas chromatography time-of-flight mass spectrometry
(GC$\times$GC-TOF MS) data using normal-exponential-Bernoulli (NEB) and mixture
probability models. The algorithm first performs baseline correction and
denoising simultaneously using the NEB model, which also defines peak regions.
Peaks are then picked using a mixture of probability distribution to deal with
the co-eluting peaks. Peak merging is further carried out based on the mass
spectral similarities among the peaks within the same peak group. The algorithm
is evaluated using experimental data to study the effect of different cutoffs
of the conditional Bayes factors and the effect of different mixture models
including Poisson, truncated Gaussian, Gaussian, Gamma and exponentially
modified Gaussian (EMG) distributions, and the optimal version is introduced
using a trial-and-error approach. We then compare the new algorithm with two
existing algorithms in terms of compound identification. Data analysis shows
that the developed algorithm can detect the peaks with lower false discovery
rates than the existing algorithms, and a less complicated peak picking model
is a promising alternative to the more complicated and widely used EMG mixture
models.; Comment: Published in at http://dx.doi.org/10.1214/14-AOAS731 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org)
Allergic asthma represents an important public health issue, most common in the paediatric population, characterized by airway inflammation that may lead to changes in volatiles secreted via the lungs. Thus, exhaled breath has potential to be a matrix with relevant metabolomic information to characterize this disease. Progress in biochemistry, health sciences and related areas depends on instrumental advances, and a high throughput and sensitive equipment such as comprehensive two-dimensional gas chromatography–time of flight mass spectrometry (GC × GC–ToFMS) was considered. GC × GC–ToFMS application in the analysis of the exhaled breath of 32 children with allergic asthma, from which 10 had also allergic rhinitis, and 27 control children allowed the identification of several hundreds of compounds belonging to different chemical families. Multivariate analysis, using Partial Least Squares-Discriminant Analysis in tandem with Monte Carlo Cross Validation was performed to assess the predictive power and to help the interpretation of recovered compounds possibly linked to oxidative stress, inflammation processes or other cellular processes that may characterize asthma. The results suggest that the model is robust, considering the high classification rate...
Multi-channel polydimethylsiloxane rubber traps were used to sample the headspace of rosemary samples (two essential oils from different sources, one oleoresin and one dried herb) followed by comprehensive two-dimensional gas chromatography -time of flight mass spectrometry (GCxGC-TOFMS) or GC-MS analyses. The aroma of different headspace samples was characterized using a custom-built olfactory apparatus. The differences between the aroma profiles were evident from bubble plots of the perceived aroma at different temperatures. The samples were heat-treated to simulate cooking of food products, and were then reassessed to determine any changes in the aroma profile. It was found that the intense menthol and cooling aromas subsided in all the samples with heating. GCxGC-TOFMS allowed for separation of the numerous components in the headspace samples. Many terpenes and aliphatics were thus tentatively identified and the relative peak areas were compared to better understand the mixture that contributes to the rosemary aroma.