GC-MS in space research: decoding complex isothermal chromatograms recovered from space missions

An analytical procedure is described to study GC-MS isothermal chromatograms simulating those recovered from space missions: in fact GC plays a predominant role in space missions devoted to characterizing the chemical composition of extra-terrestrial atmospheres. SIM (selected ion monitoring) detection was used for monitoring selected chemical classes: a simplified chromatogram can be obtained giving information on the chemical composition of the complex mixture. Since only isothermal GC chromatograms are allowed by flight constraints, a time axis transformation is required to make them homogeneous: i.e., constant retention increments for CH2 additions in terms of a homologous series. The order in the linearized chromatogram can be simply singled out with a chemometric approach based on the study of the Autocovariance Function (ACVF) computed on the digitized chromatogram: the plot of the experimental autocorrelation function (EACF) shows well-shaped peaks if constant interdistances are repeated in different regions of the chromatogram. The method was applied to standard mixtures representative of planetary atmospheres--hydrocarbons, nitriles and oxygenated compounds with between 3 and 12 carbon atoms--analyzed in flight simulating conditions. The coupling of the selectivity of SIM detection with the interpretation power of the EACF procedure proves to be a powerful tool for interpreting data recovered from space missions: the chemical composition of the mixture can be identified by handling the raw SIM chromatograms.     

Signal processing of GC-MS data of complex environmental samples: characterization of homologous series

Identification and characterization of homologous series by GC-MS analysis provide very relevant information on organic compounds in complex mixtures. A chemometric approach, based on the study of the autocovariance function, EACVF_tot, is described as a suitable tool for extracting molecular-structural information from the GC signal, in particular for identifying the presence of homologous series and quantifying the number of their terms. A data pre-processing procedure is introduced to transform the time axis in order to display a strictly homogenous retention pattern: n-alkanes are used as external standard to stretch or shrink the original chromatogram in order to build up a linear GC retention scale. This addition can be regarded as a further step in the direction of a signal processing procedure for achieving a systematic characterization of complex mixture from experimental chromatograms. The EACVF_tot was computed on the linearized chromatogram: if the sample presents terms of homologous series, the EACVF_tot plot shows well-defined deterministic peaks at repeated constant interdistances. By comparison with standard references, the presence of such peaks is diagnostic for the presence of the ordered series, their position can be related to the chemical structure of the compounds, their height is the basis for estimating the number of terms in the series. The power of the procedure can be magnified by studying SIM chromatograms acquired at specific m/z values characteristic of the compounds of interest: the EACVF_tot on these selective signals makes it possible to confirm the results obtained from an unknown mixture and check their reliability.The procedure was validated on standard mixtures of known composition and applied to an unknown gas oil sample. In particular, the paper focuses on the study of two specific classes of compounds: n-alkanes and oxygen-containing compounds, since their identification provides information useful for characterizing the chemical composition of many samples of different origin. The robustness of the method was tested in experimental chromatograms obtained under unfavorable conditions: chromatograms acquired in non-optimal temperature program conditions and chromatographic data affected by signal noise.     

Utilizing a constant peak width transform for isothermal gas chromatography

A computational approach to partially address the general elution problem (GEP), and better visualize, isothermal gas chromatograms is reported. The theoretical computational approach is developed and applied experimentally. We report a high speed temporally increasing boxcar summation (TIBS) transform that, when applied to the raw isothermal GC data, converts the chromatographic data from the initial time domain (in which the peak widths in isothermal GC increase as a function of their retention factors, k), to a data point based domain in which all peaks have the same peak width in terms of number of points in the final data vector, which aides in preprocessing and data analysis, while minimizing data storage size. By applying the TIBS transform, the resulting GC chromatogram (initially collected isothermally), appears with an x-axis point scale as if it were instrumentally collected using a suitable temperature program. A high speed GC isothermal separation with a test mixture containing 10 compounds had a run time of ～25 s. The peak at a retention factor k ～0.7 had a peak width of ～55 ms, while the last eluting peak at k ～89 (i.e., retention time of ～22 s) had a peak width of ～2000 ms. Application of the TIBS transform increased the peak height of the last eluting peak 45-fold, and S/N ～20-fold. All peaks in the transformed test mixture chromatogram had the width of an unretained peak, in terms of number of data points. A simulated chromatogram at unit resolution, studied using the TIBS transform, provided additional insight into the benefits of the algorithm.     

PCB separation by HRGC-MS. Fourier analysis for characterizing Aroclor chromatograms

Aroclor and Aroclor mixture chromatograms obtained using temperature programmed high resolution capillary GC coupled with mass spectrometric selective detection have been investigated by Fourier analysis developed for the study of multicomponent chromatograms. The experimental autocorrelation function (EACF), i.e. peak shape and position correlation, showed a retention - structure pattern which could be associated with both the type of Aroclor and the ion used for selective ion monitoring (m/z value). In particular, o-m and m-m isomerization effects were singled out by EACF analysis. By fitting EACF with previously developed theoretical models, it was possible to characterize a specific Aroclor in terms of the number of PCB congeners present in it. The results obtained agreed closely with the typical Aroclor content. For the Aroclor mixture, the distribution of inter-distance between successive peaks was derived. The two first distribution moments obtained agreed with those derived from retention data reported in the literature. The consequences on the separation performance, i.e. the number of singlets, doublets, etc. in the chromatogram, are discussed.     

High-speed peak matching algorithm for retention time alignment of gas chromatographic data for chemometric analysis

A rapid retention time alignment algorithm was developed as a preprocessing utility to be used prior to chemometric analysis of large datasets of diesel fuel profiles obtained using gas chromatography (GC). Retention time variation from chromatogram-to-chromatogram has been a significant impediment against the use of chemometric techniques in the analysis of chromatographic data due to the inability of current chemometric techniques to correctly model information that shifts from variable to variable within a dataset. The alignment algorithm developed is shown to increase the efficacy of pattern recognition methods applied to diesel fuel chromatograms by retaining chemical selectivity while reducing chromatogram-to-chromatogram retention time variations and to do so on a time scale that makes analysis of large sets of chromatographic data practical. Two sets of diesel fuel gas chromatograms were studied using the novel alignment algorithm followed by principal component analysis (PCA). In the first study, retention times for corresponding chromatographic peaks in 60 chromatograms varied by as much as 300 ms between chromatograms before alignment. In the second study of 42 chromatograms, the retention time shifting exhibited was on the order of 10 s between corresponding chromatographic peaks, and required a coarse retention time correction prior to alignment with the algorithm. In both cases, an increase in retention time precision afforded by the algorithm was clearly visible in plots of overlaid chromatograms before and then after applying the retention time alignment algorithm. Using the alignment algorithm, the standard deviation for corresponding peak retention times following alignment was 17 ms throughout a given chromatogram, corresponding to a relative standard deviation of 0.003% at an average retention time of 8 min. This level of retention time precision is a 5-fold improvement over the retention time precision initially provided by a state-of-the-art GC instrument equipped with electronic pressure control and was critical to the performance of the chemometric analysis. This increase in retention time precision does not come at the expense of chemical selectivity, since the PCA results suggest that essentially all of the chemical selectivity is preserved. Cluster resolution between dissimilar groups of diesel fuel chromatograms in a two-dimensional scores space generated with PCA is shown to substantially increase after alignment. The alignment method is robust against missing or extra peaks relative to a target chromatogram used in the alignment, and operates at high speed, requiring roughly 1 s of computation time per GC chromatogram.     

In situ analysis of the Martian soil by gas chromatography: decoding of complex chromatograms of organic molecules of exobiological interest

Gas chromatography-mass spectrometry (GC-MS) will be used in future space exploration missions, in order to seek organic molecules at the surface of Mars, and especially potential chemical indicators of life. Carboxylic acids are among the most expected organic species at the surface of Mars, and they could be numerous in the analysed samples. For this reason, a chemometric method was applied to support the interpretation of chromatograms of carboxylic acid mixtures. The method is based on AutoCovariance Function (ACVF) in order to extract information on the sample--number and chemical structure of the components--and on separation performance. The procedure was applied to standard samples containing targeted compounds which are among the most expected to be present in the Martian soil: n-alkanoic and benzene dicarboxylic acids. ACVF was computed on the obtained chromatograms and plotted versus retention time: peaks of the ACVF plot can be related to specific molecular structures and are diagnostic for chemical identification of compounds.     

Quantification of naphthalenes in jet fuel with GC x GC/Tri-PLS and windowed rank minimization retention time alignment

Comprehensive, two-dimensional gas chromatography (GC x GC) is used in conjunction with trilinear partial least squares (Tri-PLS) to quantify the percent weight of naphthalenes (two-ring aromatic compounds) in jet fuel samples. The increased peak capacity and selectivity of GC x GC makes the technique attractive for the rapid, and possibly less tedious analysis of jet fuel. The analysis of complex mixtures by GC x GC is further enhanced through the use of chemometric techniques, including those designed for use on 2-D data such as Tri-PLS. Unfortunately, retention time variation, unless corrected, can be an impediment to chemometric analysis. Previous work has demonstrated that the effects of retention time variation can be mitigated in sub-regions of GC x GC chromatograms through the application of an objective retention time alignment algorithm based on rank minimization. Building upon this previous work, it is demonstrated here that the effects of retention time variation can be mitigated throughout an entire GC x GC chromatogram with an objective retention time alignment algorithm based on windowed rank minimization alignment. A significant decrease in calibration error is observed when the algorithm is applied to chromatograms prior to construction of Tri-PLS models. Fourteen jet fuel samples with known weight percentages of naphthalenes (ASTM D1840) were obtained. Each sample was subjected to five replicate five-minute GC x GC separations over a period of two days. A subset of nine samples spanning the range of weight percentages of naphthalenes was chosen as a calibration set and Tri-PLS calibration models were subsequently developed in order to predict the naphthalene content of the samples from the GC x GC chromatograms of the remaining five samples. Calibration models constructed from GC x GC chromatograms that were retention time corrected are shown to exhibit a root mean square error of prediction of roughly half that of calibration models constructed from uncorrected chromatograms. The error of prediction is lowered further to a value that nearly matches the uncertainty in the standard percent weight values (ca. 1% of the median percent volume value) when the aligned chromatograms are truncated to include only regions of the chromatogram populated by naphthalenes and compounds of similar polarity and boiling point.     

Three-dimensional ion mass chromatograms of oil hydrocarbon and heteroatomic compound types

The type composition of oil and oil products is usually determined by either the summation of all individuals of this compound type found from GC or GC/MS data or using appropriate generalized analytical features specific for a compound type as a whole. The specific representation of mass spectra of a complex mixture as a table of 14 homological series allows the analyst to visualize characteristic ion clusters specific for the compound types. These ion clusters form a “type mass spectrum” for each compound type. In the mass chromatograms of ions of a homologous ion series, these ion clusters form peculiar three-dimensional chromatographic peaks, whose width along the retention time axis corresponds to the isomer distribution for the homologue, molecular mass distribution (if molecular ions are considered), or structural features of the system of fused rings (for fragment ions) and “volume,” the concentration of the compound type. Three-dimensional chromatographic peaks for compound types are similar to usual peaks for individual compounds in ion mass chromatograms.     

Retention time alignment of LC/MS data by a divide-and-conquer algorithm

Liquid chromatography-mass spectrometry (LC/MS) has become the method of choice for characterizing complex mixtures. These analyses often involve quantitative comparison of components in multiple samples. To achieve automated sample comparison, the components of interest must be detected and identified, and their retention times aligned and peak areas calculated. This article describes a simple pairwise iterative retention time alignment algorithm, based on the divide-and-conquer approach, for alignment of ion features detected in LC/MS experiments. In this iterative algorithm, ion features in the sample run are first aligned with features in the reference run by applying a single constant shift of retention time. The sample chromatogram is then divided into two shorter chromatograms, which are aligned to the reference chromatogram the same way. Each shorter chromatogram is further divided into even shorter chromatograms. This process continues until each chromatogram is sufficiently narrow so that ion features within it have a similar retention time shift. In six pairwise LC/MS alignment examples containing a total of 6507 confirmed true corresponding feature pairs with retention time shifts up to five peak widths, the algorithm successfully aligned these features with an error rate of 0.2%. The alignment algorithm is demonstrated to be fast, robust, fully automatic, and superior to other algorithms. After alignment and gap-filling of detected ion features, their abundances can be tabulated for direct comparison between samples.     

Identification of Africanized honeybees

Gas chromatography and pattern recognition methods were used to develop a potential method for differentiating European honeybees from Africanized honeybees. The test data consisted of 237 gas chromatograms of hydrocarbon extracts obtained from the wax glands, cuticle, and exocrine glands of European and Africanized honeybees. Each gas chromatogram contained 65 peaks corresponding to a set of standardized retention time windows. A genetic algorithm (GA) for pattern recognition was used to identify features in the gas chromatograms characteristic of the genotype. The pattern recognition GA searched for features in the chromatograms that optimized the separation of the European and Africanized honeybees in a plot of the two or three largest principal components of the data. Because the largest principal components capture the bulk of the variance in the data, the peaks identified by the pattern recognition GA primarily contained information about differences between gas chromatograms of European and Africanized honeybees. The principal component analysis routine embedded in the fitness function of the pattern recognition GA acted as an information filter, significantly reducing the size of the search space since it restricted the search to feature sets whose principal component plots showed clustering on the basis of the bees' genotype. In addition, the algorithm focused on those classes and/or samples that were difficult to classify as it trained using a form of boosting. Samples that consistently classify correctly are not as heavily weighted as samples that are difficult to classify. Over time, the algorithm learns its optimal parameters in a manner similar to a neural network. The pattern recognition GA integrates aspects of artificial intelligence and evolutionary computations to yield a "smart" one-pass procedure for feature selection and classification.     

Resolution prediction and optimization of temperature programme in comprehensive two-dimensional gas chromatography

A model is developed for predicting the resolution of interested component pair and calculating the optimum temperature programming condition in the comprehensive two-dimensional gas chromatography (GC x GC). Based on at least three isothermal runs, retention times and the peak widths at half-height on both dimensions are predicted for any kind of linear temperature-programmed run on the first dimension and isothermal runs on the second dimension. The calculation of the optimum temperature programming condition is based on the prediction of the resolution of "difficult-to-separate components" in a given mixture. The resolution of all the neighboring peaks on the first dimension is obtained by the predicted retention time and peak width on the first dimension, the resolution on the second dimension is calculated only for the adjacent components with un-enough resolution on the first dimension and eluted within a same modulation period on the second dimension. The optimum temperature programming condition is acquired when the resolutions of all components of interest by GC x GC separation meet the analytical requirement and the analysis time is the shortest. The validity of the model has been proven by using it to predict and optimize GC x GC temperature programming condition of an alkylpyridine mixture.     

Analysis of bacterial strains with pyrolysis-gas chromatography/differential mobility spectrometry

Eight vegetative bacterial strains and two spores were characterized by pyrolysis-gas chromatography with differential mobility spectrometry (py-GC/DMS) yielding topographic plots of ion intensity, retention time, and compensation voltage simultaneously for ions in positive and negative polarity. Biomarkers were found in the pyrolysate at characteristic retention times and compensation voltages and were confirmed by standard addition with GC/MS analyses providing discrimination between Gram negative and Gram positive bacterial types, but no recognition of individual strains within the Gram negative bacteria. Principal component analysis was applied using two dimensional data sets of ion intensity versus retention time at five compensation voltages including the reactant ion peaks all in positive and negative ion polarity. Clustering was observed with compensation voltage (CV) chromatograms associated with ion separation in the DMS detector and little or no clustering was observed with the reactant ion peaks or CV chromatograms where ion separation is poor. Consistent clustering of Gram positive B. odysseyi and Gram negative E. coli in both positive and negative polarities with the reactant ion peak chromatograms and key CV chromatograms suggests common but unknown common chemical compositions in the pyrolysate.     

Detailed analysis and group-type separation of natural fats and oils using comprehensive two-dimensional gas chromatography

Comprehensive gas chromatography (GC x GC) is an adequate methodology for the separation and identification of very complex samples. It is based on the coupling of two capillary columns that each give a different but substantial contribution to the unprecedented resolving power of this technique. The 2D space chromatograms that derive from GC x GC analysis have great potential for identification. This is due to the fact that the contour plot positions, pinpointed by two retention time coordinates, give characteristic patterns for specific families of compounds that can be mathematically translated. This investigation concerned the application of this principle to fatty acid methyl esters that were grouped on an equal double bond number basis. The ester samples were derived from various lipids and all underwent bidimensional analysis on two sets of columns. Peak attribution was supported by mass spectra, linear retention indices and information reported in the literature.     

Gas-Chromatographic Analysis of Mixtures of Hydrogen Isotopes

A simple method is proposed for the gas-chromatographic analysis of complex gas mixtures containing hydrogen isotopes; the method is based on the substantial difference in the thermal conductivity of these isotopes. The total peak of the isotopes is recorded in a chromatogram, and the calibration is performed by pure reference gases. The concentrations of impurity gases in the analyzed mixture and in reference samples for each of the hydrogen isotopes are determined simultaneously. The fractional concentrations of protium and deuterium are calculated by the equations involving the heights of the unresolved peaks of hydrogen isotopes in chromatograms and concentrations of impurity components.     

HRGC separation performance evaluation by a simplified fourier analysis approach

A simple procedure is presented for determining separation performance of HRGC analysis of multicomponent mixtures. The procedure is based on the computation of Autocovariance Function (EACVF) from the digitized experimental chromatogram. Graphic inspection of the EACVF plot permits easy computation of the width value of the single component peak, σ; from the EACVF value at t=O the number of component in the mixture, m, can be simply derived. From these two basic quantities all the other chromatographic performance attributes can be calculated. The consistency of the procedure is tested for different chromatograms and compared with the more complex EACVF fitting method. Several features of the multicomponent chromatogram, overloading effects included, are directly detected.     

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.     

Comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry peak sorting algorithm

We report a novel peak sorting method for the two-dimensional gas chromatography/time-of-flight mass spectrometry (GC x 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.     

Method for reducing the ambiguity of comprehensive two-dimensional chromatography retention times

Comprehensive two-dimensional chromatography generates a two-dimensional chromatogram from a one-dimensional signal array. This process can only be done unambiguously when the range of secondary retention times is less than the modulation period. However, complex samples often produce wider ranges of secondary retention times. Peaks with retention times that exceed the modulation period are said to be "wrapped-around". A simple algorithm has been developed that determines absolute retention times when wrap-around occurs. A sample is first analyzed under standard modulation conditions and then re-analyzed with a modulation period that is increased by an integer fraction of the original modulation period. Retention shifts along the secondary axis are used to determine absolute retention times. A theoretical analysis has been performed to optimize the implementation conditions and characterize the technique limitations. The efficacy of this algorithm has been tested through a series of isothermal GC x GC separations. This method has been found to be particularly useful during the initial stages of method development.     

Solid Phase Micro-extraction – Gas Chromatography–Mass Spectrometry to Characterize Pyrolysis Products from Textiles

Headspace solid phase micro-extraction gas chromatography–mass spectrometry (HS-SPME GC–MS) was used for identifying thermally labile volatile compounds from cotton, wool, polyester, olefin, silk, and acrylic. Volatile compounds were generated from the textiles using a pyrolysis apparatus prior to GC–MS. Pyrolysis temperatures ranged from 190 to 550°C. Each textile displayed a unique chromatogram containing compounds that were consistent with the chemical structure of the textile. Experimental parameters that were investigated included the temperature, sample size, and sampling time to determine their effect on the number and intensity of peaks in the chromatograms as well as to identify optimum conditions for analysis. Heating of each sample was achieved using a resistively heated Pt wire. Full pyrolysis at 550°C of the textiles appeared to give the best results in terms of peak height relative to background. A range of sample sizes (0.02–1.5?mg) were used and, generally, ≤0.02?mg was used for identifying the textiles. The reproducibility of retention times for selected compounds in the chromatograms was less than 1% relative standard deviation. The combination with mass spectrometry provided valuable structural information.