Comprehensive analysis of yeast metabolite GC x GC-TOFMS data: combining discovery-mode and deconvolution chemometric software

The first extensive study of yeast metabolite GC x GC-TOFMS data from cells grown under fermenting, R, and respiring, DR, conditions is reported. In this study, recently developed chemometric software for use with three-dimensional instrumentation data was implemented, using a statistically-based Fisher ratio method. The Fisher ratio method is fully automated and will rapidly reduce the data to pinpoint two-dimensional chromatographic peaks differentiating sample types while utilizing all the mass channels. The effect of lowering the Fisher ratio threshold on peak identification was studied. At the lowest threshold (just above the noise level), 73 metabolite peaks were identified, nearly three-fold greater than the number of previously reported metabolite peaks identified (26). In addition to the 73 identified metabolites, 81 unknown metabolites were also located. A Parallel Factor Analysis graphical user interface (PARAFAC GUI) was applied to selected mass channels to obtain a concentration ratio, for each metabolite under the two growth conditions. Of the 73 known metabolites identified by the Fisher ratio method, 54 were statistically changing to the 95% confidence limit between the DR and R conditions according to the rigorous Student's t-test. PARAFAC determined the concentration ratio and provided a fully-deconvoluted (i.e. mathematically resolved) mass spectrum for each of the metabolites. The combination of the Fisher ratio method with the PARAFAC GUI provides high-throughput software for discovery-based metabolomics research, and is novel for GC x GC-TOFMS data due to the use of the entire data set in the analysis (640 MB x 70 runs, double precision floating point).     

Detection of verapamil drug by fluorescence and trilinear decomposition techniques

A three-way analytical methodology experimentally based on fluorescence excitation emission matrix (EEM) and in PARAFAC and TLD chemometric analysis was assessed for the quantification of verapamil drug in a tablet formulation. A standard addition procedure generates experimental information compatible with the chemometric data analysis model allowing the estimation of verapamil with a detection limit of about 0.04 mg/l using methanol as solvent. The structure of the verapamil EEM follows a trilinear model, but background signals (first- and second-order scatter bands) did not—a trilinear three-factor model is necessary to describe experimental datasets. The comparison of a three-factor PARAFAC model with a United States Pharmacopoeia (USP) standard chromatographic method showed similar results.     

Photoinduced spectrofluorimetric determination of fluoroquinolones in human urine by using three- and two-way spectroscopic data and multivariate calibration

Multivariate methods comprise of a group of chemometric tools allowing the analysis of different analytical data, i.e., spectroscopic, chromatographic obtained from multichannel detector systems. Second-way data are widely used in analytical applications in combination with multivariate calibration methods, but three- and higher-way data are yet not as widely applied. In complex biological samples, the employment of the three-way data is of special interest, as they may be combined with methods that exploit the second-order advantage allowing calculating individual concentrations of the analytes of interest in the presence of unknown interferences in untreated samples. A very sensitive and selective method is proposed, by coupling photoinduced fluorescence and multivariate analysis of the three-way data excitation-emission fluorescence matrices (EEMs), of the photoproducts obtained from UV irradiation of three fluoroquinolones: enoxacin (ENO), norfloxacin (NOR) and ofloxacin (OFLO). The application of a previous photoirrradiation process allows the determination of mixtures of ENO, NOR and OFLO, in urine samples at biological levels without sample pretreatments. The resolution ability of N-way partial least squares (N-PLS), parallel factor analysis (PARAFAC) and self weighted alternating trilinear decomposition (SWATLD), is compared with partial least squares (PLS) and unfolded-PLS (U-PLS), in the analysis of ENO, NOR and OFLO in human urine samples.     

Effects of pressure drop on absolute retention matching in comprehensive two-dimensional gas chromatography

Comprehensive two-dimensional gas chromatography (GC x GC) analysis has the capability to resolve many more components of complex mixtures than traditional single column GC analysis. There is an increasing need to provide reliable identification of these separated components; time-of-flight mass spectrometry (TOFMS) is the most appropriate technology to achieve this task. Rather than require MS for all GC x GC separations, it is desirable to assign peak identities to specific peak positions in the GC x GC separation space, and this necessitates matching peak retentions in the two experiments - GC x GC-FID and GC x GC-TOFMS. The atmospheric vs. vacuum outlet conditions confound this task. It is shown here that by employing a supplementary gas supply, provided to a T-union between the column outlet and the MS interface, it is possible to generate 2D chromatograms for GC x GC-FID and GC x GC-TOFMS that are essentially exactly matched. There is no degradation in separation performance or efficiency in the second column in the system interfaced to the T-union. Since the GC x GC-FID experiment uses hydrogen for maximum efficiency, and GC x GC-TOFMS uses helium carrier, translation of (conditions/retentions) must account for the different viscosities of the carrier gases. Translation of conditions is based on well-known principles established in single column analysis. Tabulated data illustrate that retention reproducibility was of the order of better than 4 s for the average first dimension retention difference, and about 40 ms for the average second dimension retention difference when comparing GC x GC-FID and GC x GC-TOFMS results. This should provide considerable support for identification in routine GC x GC-FID analysis of specific sample types, once the peaks in 2D separation space have been assigned identities through GC x GC-TOFMS analysis.     

Multivariate curve resolution based chromatographic peak alignment combined with parallel factor analysis to exploit second-order advantage in complex chromatographic measurements

In the present contribution, a new combination of multivariate curve resolution-correlation optimized warping (MCR-COW) with trilinear parallel factor analysis (PARAFAC) is developed to exploit second-order advantage in complex chromatographic measurements. In MCR-COW, the complexity of the chromatographic data is reduced by arranging the data in a column-wise augmented matrix, analyzing using MCR bilinear model and aligning the resolved elution profiles using COW in a component-wise manner. The aligned chromatographic data is then decomposed using trilinear model of PARAFAC in order to exploit pure chromatographic and spectroscopic information. The performance of this strategy is evaluated using simulated and real high-performance liquid chromatography-diode array detection (HPLC-DAD) datasets. The obtained results showed that the MCR-COW can efficiently correct elution time shifts of target compounds that are completely overlapped by coeluted interferences in complex chromatographic data. In addition, the PARAFAC analysis of aligned chromatographic data has the advantage of unique decomposition of overlapped chromatographic peaks to identify and quantify the target compounds in the presence of interferences. Finally, to confirm the reliability of the proposed strategy, the performance of the MCR-COW-PARAFAC is compared with the frequently used methods of PARAFAC, COW-PARAFAC, multivariate curve resolution-alternating least squares (MCR-ALS), and MCR-COW-MCR. In general, in most of the cases the MCR-COW-PARAFAC showed an improvement in terms of lack of fit (LOF), relative error (RE) and spectral correlation coefficients in comparison to the PARAFAC, COW-PARAFAC, MCR-ALS and MCR-COW-MCR results.     

Characterization and pattern recognition of oil-sand naphthenic acids using comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry

Oil-sand naphthenic acids (NAs) are organic wastes produced during the oil-sand digestion and extraction processes and are very difficult to separate and analyze as individual components due to their complex compositions. A comprehensive two-dimensional gas chromatography/time of flight mass spectrometry (GC x GC/TOF-MS) system was applied for the characterization of two commercial mixtures of naphthenic acids (Fluka and Acros) and a naphthenic acid sample extracted from the Syncrude tailings. Contour plots of chromatographic distributions of different Z homologous series of the Fluka, Acros and Syncrude NAs were constructed using fragment ions that were characteristic of the NA's molecular structures. Well-ordered patterns were observed for NAs of Z= 0 and -2 which corresponded to acyclic acids and monocyclic acids, respectively. For NAs of Z= -4, -6, and -8, specific zones were observed which would allow the pattern recognition of these NAs obtained from different origins. As expected, gas chromatographic retention times increase with the number of the carbons and the number of rings in the molecules. Little signal was obtained for NAs with Z numbers of -10, or lower. Deconvoluted mass spectra of various NA isomers were derived from the reconstructed GC x GC chromatogram, permitting detailed structural elucidations for NAs in the future. The current study demonstrated that the combination of GC x GC and the TOF-MS is a powerful to identify origins of the NAs in an effective manner. GC x GC/TOF-MS alone, however, may not be enough to characterize each individual isomer in a complex mixture such as NAs. The use of mass deconvolution software followed by library search have thus become necessary to separate and study the mass spectrum of each individual NA component, allowing a detailed identification of the toxic components within the NAs mixture.     

Search criteria and rules for comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry analysis of airborne particulate matter

Direct thermal desorption-gas chromatography-time-of-flight mass spectrometry (DTD-GC-TOFMS) and comprehensive two-dimensional (2D) gas chromatography-time-of-flight mass spectrometry (GC x GC-TOFMS) was applied for characterisation of semi-volatile organic compounds (SVOC) in fine particulate matter (PM), with a diameter of up to 2.5 microm (PM2.5), from ambient air in Augsburg, Germany. DTD-GC-TOFMS measurements on the SVOC in PM2.5 are done on a daily basis (time series over several years). The data will be used in an epidemiological study questioning the influence of SVOC in PM2.5 on ambient aerosol related health effects. The outcome of the first measurements periods is that the organic inventory in the ambient aerosol can undergo drastic fluctuations, e.g. due to meteorological influences or specific emission sources. This includes also the large fraction of chromatographically not resolved peaks (unresolved carbonaceous matter (UCM)). The UCM fraction contains about 70% of the SVOC mass in PM2.5. GC x GC-TOFMS is a suited technique to study the nature of the yet unidentified compounds forming the UCM. The considerably increased chromatographic resolution in GC x GC allows separation of many UCM compounds while the TOFMS supplies mass spectral data of all separated compounds. However, the data sets are getting enormously complex. In a typical PM2.5 sample from Augsburg more than 15,000 peaks can be detected. Thus, it is important to classify the observed GC x GC peaks by rational means. A classification procedure based on GC x GC retention times and the fragmentation patterns is suggested. With a preliminary classification procedure it is already possible to group compounds with some certainty into substance classes. After some further development, this approach can be used for classifying GC x GC data, e.g. for environmental and epidemiological studies.     

Direct determination of free amino acids and sugars in green tea by anion-exchange chromatography with integrated pulsed amperometric detection

Solutes analysed with LC-MS are characterised by their retention times and mass spectra, and quantified by the intensities measured. This highly selective information can be extracted by multiway modelling. However, for full use and interpretability it is necessary that the assumptions made for the model are valid. For PARAFAC modelling, the assumption is a trilinear data structure. With LC-MS, several factors, e.g. non-linear detector response and ionisation suppression may introduce deviations from trilinearity. The single largest problem, however, is the retention time shifts not related to the true sample variations. In this paper, a time warping algorithm for alignment of LC-MS data in the chromatographic direction has been examined. Several refinements have been implemented and the features are demonstrated for both simulated and real data. With moderate time shifts present in the data, pre-processing with this algorithm yields approximately trilinear data for which reasonable models can be made.     

Enhancing the selectivity of liquid chromatography–mass spectrometry by using trilinear decomposition on LC‐MS data: An application to three‐way calibration of coeluting analytes in human plasma

The high selectivities of liquid chromatography and mass spectrometry make liquid chromatography–mass spectrometry one of the most popular tools for quantitative analysis in complex chemical, biological, and environmental systems, while the potential mathematical selectivity of liquid chromatography–mass spectrometry is rarely investigated. This work discussed the mathematical selectivity of liquid chromatography–mass spectrometry by three‐way calibration based on the trilinear model, with an application to quantitative analysis of coeluting aromatic amino acids in human plasma. By the trilinear decomposition of the constructed liquid chromatography–mass spectrometry‐sample trilinear model and individual regression of the decomposed relative intensity versus concentration, the proposed three‐way calibration method successfully achieved quantitative analysis of coeluting aromatic amino acids in human plasma, even in the presence of uncalibrated interferent(s) and a varying background. This analytical method can ease the requirements for sample preparation and complete chromatographic separation of components, reduce the use of organic solvents, decrease the time of chromatographic separation, and increase the peak capacity of liquid chromatography–mass spectrometry. As a “green analytical method”, the liquid chromatography–mass spectrometry three‐way calibration method can provide a promising tool for direct and fast quantitative analysis in complex systems containing uncalibrated spectral interferents, especially for the situation where the coelution problem is difficult to overcome.     

Analysis of methoxypyrazines in wine using headspace solid phase microextraction with isotope dilution and comprehensive two-dimensional gas chromatography

This study reports an optimized headspace-solid phase microextraction (HS-SPME) method for the determination of methoxypyrazines in wine. Analysis was performed by using comprehensive two-dimensional gas chromatography with novel detection capabilities, including nitrogen phosphorus detection (GC x GC-NPD) and time-of-flight mass spectrometry (GC x GC-TOFMS). In the latter, stable isotope dilution was performed for the quantitation of 2-methoxy-3-(2-methylpropyl) pyrazine (IBMP), using labelled 2-(2H3)methoxy-3-(2-methylpropyl)pyrazine (d3-IBMP) as the internal standard, and resolution of the two analogues was facilitated using the deconvolution capabilities of the TOFMS. This research represents the first report of HS-SPME with isotope dilution and GC x GC-TOFMS (GC x GC-IDTOFMS). Analysis by GC x GC-NPD enabled detection limits of 0.5 ng/L for the quantitation of IBMP, which was superior to that obtained using GC x GC-IDTOFMS (1.95 ng/L). Nevertheless, both methods were adequately sensitive for real wine analysis, yielding highly comparable IBMP concentrations of 26.1 and 27.8 ng/L, respectively, from a Sauvignon blanc wine. The complexity of the real wine headspace was simplified as a result of selective detection using GC x GC-NPD and, in the case of GC x GC-IDTOFMS, the use of extracted ion chromatograms (EICs).     

Flexible Implementation of the Trilinearity Constraint in Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) of Chromatographic and Other Type of Data

Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) can analyze three-way data under the assumption of a trilinear model using the trilinearity constraint. However, the rigid application of this constraint can produce unrealistic solutions in practice due to the inadequacy of the analyzed data to the characteristics and requirements of the trilinear model. Different methods for the relaxation of the trilinear model data requirements have been proposed, like in the PARAFAC2 and in the direct non-trilinear decomposition (DNTD) methods. In this work, the trilinearity constraint of MCR-ALS is adapted to different data scenarios where the profiles of all or some of the components of the system are shifted (not equally synchronized) or even change their shape among different slices in one of their data modes. This adaptation is especially useful in gas and liquid chromatography (GC and LC) and in Flow Injection Analysis (FIA) with multivariate spectroscopic detection. In a first data example, a synthetic LC-DAD dataset is built to investigate the possibilities of the proposed method to handle systematic changes (shifts) in the retention times of the elution profiles and the results are compared with those obtained using alternative methods like ATLD, PARAFAC, PARAFAC2 and DNTD. In a second data example, multiple wine samples were simultaneously analyzed by GC-MS where elution profiles presented large deviations (shifts) in their peak retention times, although they still preserve the same peak shape. Different modelling scenarios are tested and the results are also compared. Finally, in the third example, sample mixtures of acid compounds were analyzed by FIA under a pH gradient and monitored by UV spectroscopy and also examined by different chemometric methods using a different number of components. In this case, however, the departure of the trilinear model comes from the acid base speciation of the system depending on the pH more than from the shifting of the FIA diffusion profiles.     

Qualitative evaluation of thermal desorption-programmable temperature vaporization-comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry for the analysis of selected halogenated contaminants

The separation of 38 toxic and predominant polychlorinated biphenyl (PCB) congeners, 11 persistent halogenated pesticides, 1 brominated biphenyl (BB), and 8 polybrominated diphenyl ethers (PBDEs) has been optimized using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC x GC-TOFMS). A thermal desorption-programmable temperature vaporization (TD-PTV) step was used for the injection. Different column sets were investigated, and a 100% dimethylpolysiloxane (15 m x 0.25 mm i.d. x 0.25 microm film thickness) narrowbore capillary column coupled to a high temperature (8% phenyl)-polycarborane-siloxane (2 m x 0.10 mm i.d. x 0.10 microm film thickness) microbore column set was selected. Of the 58 compounds investigated, only one pair of PCBs was not resolved. All other analytes were either baseline separated into the chromatographic plane or were virtually separated using the deconvolution capability of the TOFMS.     

Gas chromatography with spectroscopic detectors.

In recent years, capillary gas chromatography (GC) with Fourier Transform Infrared (FT-IR) and/or mass spectral (MS) detection has become a primary analytical tool for qualitative and quantitative analysis of complex mixtures. Because of the wide range of applications, the analytical requirements have motivated a variety of chromatographic and detection developments. This review examines those, illustrating with applications that demonstrate the power of GC and multidimensional GC-MS, GC-FT-IR and GC-FT-IR-MS systems for solving a variety of analytical problems. In addition, the article discusses the integrated performance of such analytical systems with the aid of recent sample introduction and computer data analysis advances.     

Analysis of gin essential oil mixtures by multidimensional and one-dimensional gas chromatography/mass spectrometry with spectral deconvolution

The composition of essential oils and their mixtures used to formulate gin is usually too complex to separate all sample components by standard capillary gas chromatography (GC). In particular, minor constituents that possess important organoleptic properties can be masked by co-elution with major sample components. A solution is provided that combines gas chromatography/mass spectrometry (GC/MS) with "interactive" spectral deconvolution software. Sequential two-dimensional (2D) GC/MS is used to produce a target compound library, with orthogonal GC-GC providing the separation power required to obtain peak retention times and the corresponding mass spectra needed for the deconvolution database. The combination of these two techniques, mass spectral deconvolution and automated sequential 2D-GC/MS, offers a very effective synergy for both identifying key constituents that determine the perception of flavor and aroma and the quality control needed to analyze mixtures of complex essential oils.     

Mitigating model deficiency in three-way data analysis by the combination of background constraining and iterative correcting techniques

PARAFAC is a popular model for trilinear data analysis in analytical chemistry. The prerequisite for the successful application of PARAFAC in analytical chemistry is that the three-way data array should follow a trilinear model, which is always violated by the presence of deviations such as Rayleigh scattering in fluorescence spectroscopy. In order to mitigate the influence of model deviations, background constraining and iterative correcting techniques are advocated in this contribution. The method established on these two techniques can nearly eliminate the effect of model deviation on the chemical loading parameters estimated. Compared with other methods for mitigating model deviations, the proposed method requires no prior knowledge about the chemical loading parameters. It is also unnecessary to assign weights to data entities as the weighted PARAFAC of Anderson does. Its implementation is comparable to PARAFAC-ALS and can be programmed to be completely automatic. Its performance has been demonstrated by fluorescent and chromatographic experiments.     

Separation of Isomers on Nematic Liquid Crystal Stationary Phases in Gas Chromatography: A Review

Understanding the composition of complex hydrocarbon mixtures is important for environmental studies in diverse fields, but many prevalent compounds cannot be confidently identified using traditional gas chromatography (GC) techniques. Increasing requirements on analyses of isomeric compounds and the problems encountered in their separation demand a study of more efficient systems which exhibit a high selectivity. Kelker and Fresenius first used nematic liquid crystals as stereospecific stationary phases in GC. Nematic liquid crystal has shown this particular selectivity and sensitivity as stationary phases for the separation of isomers having similar volatilities. Because of their unique selectivity towards rigid solute isomers, liquid crystal stationary phases were considered at one time to be a very promising class of materials that give gas chromatographic separations very different from those that can be obtained with any other stationary phase. Since then, a great deal of attention has been paid to the separation properties of this relatively wide group of substances. Liquid crystal can be used to separate a variety of compounds including isomer mixtures which cannot be separated on conventional stationary phases. This paper aims to review all specific experimental results and presents a comparative analytical study of monomeric nematic liquid crystal stationary phases used in GC. A further contribution of this review is in the field of isomeric compounds separation.     

Qualitative mass spectrometric analysis of the volatile fraction of creosote-treated railway wood sleepers by using comprehensive two-dimensional gas chromatography

The volatile composition of 20-year-old out-of-service creosote-treated railway wood sleepers was studied. The emitted volatile fraction was collected by means of dynamic purge-and-trap concentration at ambient temperature, and analyzed by comprehensive two-dimensional gas chromatography (GC x GC) hyphenated with mass spectrometric detection systems, using quadrupole (GC x GC/qMS) and time-of-flight (GC x GC/ToF-MS) mass analyzers and selective nitrogen-phosphorus detection (GC x GC-NPD). The analysis of mass spectrometry data and GC x GC retention time allowed the tentative identification of about 300 compounds based on spectrometric data and positioning of each compound in the GC x GC plot. Major important headspace components are polyaromatic hydrocarbons, phenols and benzene derivatives, hydrocarbons and heterocyclic compounds containing nitrogen, sulphur or oxygen atoms. Many of the reported compounds are listed as belonging to toxicological substance classes which have been related to harmful health effects. GC x GC provides greater speciation and evidence of composition heterogenicity of the sample than one-dimensional GC analysis, thus allowing to better demonstrate its potential toxicity. Data obtained by specific detection systems for N-heterocycles assisted mass data interpretation assignments. The enhanced separation power obtained after GC x GC compared to one-dimensional gas chromatography (1D-GC) together with spectral deconvolution and correlation with physical-chemical data, allowed the identification of complex isomer clusters, as demonstrated for alkylquinolines, and applied also to alkylphenols, alkylbenzenes and alkylnaphthalenes.     

Application of parallel factor analysis to total synchronous fluorescence spectrum of dilute multifluorophoric solutions: Addressing the issue of lack of trilinearity in total synchronous fluorescence data set

In recent years, total synchronous fluorescence (TSF) spectroscopy has become popular for the analysis of multifluorophoric systems. Application of PARAFAC, a popular deconvolution tool, requires trilinear structure in the three-way data array. The present work shows that TSF based three-way array data set of dimension sample × wavelength × Δλ does not have trilinear structure and hence it should not be subjected to PARAFAC analysis. This work also proposes that a TSF data set can be converted to an excitation–emission matrix fluorescence (EEMF) like data set which has trilinear structure, so that PARAFAC analysis can be performed on it. This also enables the retrieval of PARAFAC-separated component TSF spectra.     

Handling within run retention time shifts in two-dimensional chromatography data using shift correction and modeling

The use of PARAFAC for modeling GC × GC-TOFMS peaks is well documented. This success is due to the trilinear structure of these data under ideal, or sufficiently close to ideal, chromatographic conditions. However, using temperature programming to cope with the general elution problem, deviations from trilinearity within a run are more likely to be seen for the following three cases: (1) compounds (i.e., analytes) severely broadened on the first column hence defined by many modulation periods, (2) analytes with a very high retention factor on the second column and likely wrapped around in that dimension, or (3) with fast temperature program rates. This deviation from trilinearity is seen as retention time-shifted peak profiles in subsequent modulation periods (first column fractions). In this report, a relaxed yet powerful version of PARAFAC, known as PARAFAC2 has been applied to handle this shift within the model step by allowing generation of individual peak profiles in subsequent first column fractions. An alternative approach was also studied, utilizing a standard retention time shift correction to restore the data trilinearity structure followed by PARAFAC. These two approaches are compared when identifying and quantifying a known analyte over a large concentration series where a certain shift is simulated in the successive first column fractions. Finally, the methods are applied to real chromatographic data showing severely shifted peak profiles. The pros and cons of the presented approaches are discussed in relation to the model parameters, the signal-to-noise ratio and the degree of shift.