Unravelling the composition of very complex samples by comprehensive gas chromatography coupled to time-of-flight mass spectrometry. Cigarette smoke

The potential and current limitations of comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC x GC-TOF-MS) for the analysis of very complex samples were studied with the separation of cigarette smoke as an example. Because of the large number of peaks in such a GC x GC chromatogram it was not possible to perform manual data processing. Instead, the GC-TOF-MS software was used to perform peak finding, deconvolution and library search in an automated fashion; this resulted in a peak table containing some 30000 peaks. Mass spectral match factors were used to evaluate the library search results. The additional use of retention indices and information from second-dimension retention times can substantially improve the identification. The combined separation power of the GC x GC-TOF-MS system and the deconvolution algorithm provide a system with a most impressive separation power.     

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.     

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).     

Identification of in vitro metabolites of indinavir by “intelligent automated LC-MS/MS” (INTAMS) utilizing triple quadrupole tandem mass spectrometry

In an effort to improve the efficiency of the TSQ 7000 LC-MS/MS system for identification of drug metabolites in biological matrices in support of drug discovery programs, a combination of instrument control language procedures for the Finnigan MAT TSQ 7000 mass spectrometer, referred to as INTAMS, were composed. INTAMS was designed to conduct unattended, automatic liquid chromatography/mass spectrometry (LC-MS) and LC-MS/MS analyses of drugs and metabolites in commonly encountered in vitro biological matrices. A novel peak detection algorithm was developed to automatically detect and record the pseudomolecular ions and retention times of chromatographic components, even if not fully resolved. This algorithm was used in combination with an automated technique for predicting the molecular weights of metabolites based on incremental changes of the molecular weight of the parent drug resulting from well-known biotransformation processes. When applied to a sample of an incubation mixture of the HIV protease inhibitor Indinavir with a rat liver S9 preparation, the results obtained by the automatic metabolite detection procedures for LC-MS and LC-MS/MS analyses in real time were the same as those which were determined manually, by a knowledgeable operator.     

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.     

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.     

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.     

Computerized separation of chromatographically unresolved peaks

A computerized peak deconvolution software and mass spectra were successfully applied for the deconvolution of overlapped peak cluster in the chromatogram obtained separating the complex mixture of pesticides by retention time locking gas chromatography-mass spectroscopy. The method based on the unique fragment ions in the spectra can be used for deconvolution of peak clusters if mass spectra of overlapped peaks differ. This method allows determining actual retention times of overlapped peaks. Peak areas found by this method however, cannot be used naturally for the quantitative purposes as the abundance of fragment ions used for this deconvolution procedure can dramatically differ. Computer assisted deconvolution of peaks in the peak clusters gives more realistic peak area ratios as at this method it is supposed equal response for all peaks overlapped in a cluster.     

Decoding of complex isothermal chromatograms recovered from space missions. Identification of molecular structure

A chemometric approach, based on the study of the autocovariance function, is described to study isothermal GC chromatograms of multicomponent mixtures: isothermal GC analysis is the method of choice in space missions since it is, to date, the only method compatible with flight constraints. Isothermal GC chromatograms look inhomogeneous and disordered with peak density decreasing at higher retention times: a time axis transformation is proposed to make retention an homogeneous process so that CH2 addition in terms of an homologous series yields a constant retention increment. The time axis is transformed into a new scale based on the retention times of n-alkanes, as they are the basis of the universal Kovats indices procedure. The order introduced into the chromatogram by retention time linearization can be simply singled out by the experimental autocorrelation function (EACF) plot: if constant inter-distances are repeated in different regions of the chromatogram, well-shaped peaks are evident in the EACF plot. By comparison, with a standard mixture it is possible to identify peaks diagnostic of specific molecular structures: study of the EACF plot provides information on sample chemical composition. The procedure was applied to standard mixtures containing compounds representative of the planetary atmospheres that will be investigated in the near future: in particular, those related to Titan's atmosphere (Cassini-Huygens mission) and cometary's nucleus (Rosetta mission). The employed experimental conditions simulated those applied to GC instruments installed on space probes and landers in space missions. The method was applied to two specific investigations related to space research, i.e., a comparison of retention selectivity of different GC columns and identification of the chemical composition of an unknown mixture.     

Development of a quantification methodology for polychlorinated biphenyls by using Kanechlor products as the secondary reference standard

Kanechlor (KC)-300, 400, 500 and 600, Japanese polychlorinated biphenyl (PCB) products, and their equivalent mixture were analyzed by using a gas chromatograph (GC) equipped with an SE-54 capillary column/electron capture detector (ECD) and a GC/mass spectrometer in the selected ion monitoring mode (MS-SIM). All peaks were assigned to the composing congeners based on the data on peak assignment of Clophen A-30, 40, 50, 60 and Aroclor 1016, 1242, 1254, 1260 [1] and on the relative retention time values of 209 PCB congeners [2]. The weight percentage of the congener(s) which corresponds to each peak in the mass chromatograms was calculated by comparison of its height with that of certified reference standard with the same molecular weight. Each weight percentage of PCB congener(s) corresponding to each ECD peak was obtained by summing up the percent contribution values of the PCB congeners co-eluting. The results showed that it was possible to use KC products and their equivalent mixture as secondary reference standards for congener-specific PCB quantification.     

Development of an algorithm for peak detection in comprehensive two-dimensional chromatography

A method for peak detection in two-dimensional chromatography is presented. The algorithm applies first the methods developed for peak detection in one-dimensional chromatography to detect peaks in one dimension. In a second step, a decision tree is applied to decide which one-dimensional peaks are originated from the same compound and have to be 'merged' into one two-dimensional peak. To this end, different features of the peaks (second-dimension peak regions and second-dimension retention times) are compared and different criteria (common peak regions, retention time differences, unimodality in the first dimension) are applied. Different options can be used, depending on the nature of the data. The user controls this decision tree by establishing several options and "switches". The algorithm was tested with GCxGC chromatograms obtained for a commercial air-freshener sample, detecting and merging the modulated peaks belonging to the same compound. Recommendations for the set of options and switches are given. A utility that calculates and sums peak areas from merged peaks is added to facilitate automated quantification. Although the algorithm was developed for GCxGC, its application to comprehensive two-dimensional liquid chromatography (LCxLC) data should at most require minor modifications.     

Comparative analysis of peak-detection techniques for comprehensive two-dimensional chromatography

Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful technology for separating complex samples. The typical goal of GC×GC peak detection is to aggregate data points of analyte peaks based on their retention times and intensities. Two techniques commonly used for two-dimensional peak detection are the two-step algorithm and the watershed algorithm. A recent study [4] compared the performance of the two-step and watershed algorithms for GC×GC data with retention-time shifts in the second-column separations. In that analysis, the peak retention-time shifts were corrected while applying the two-step algorithm but the watershed algorithm was applied without shift correction. The results indicated that the watershed algorithm has a higher probability of erroneously splitting a single two-dimensional peak than the two-step approach. This paper reconsiders the analysis by comparing peak-detection performance for resolved peaks after correcting retention-time shifts for both the two-step and watershed algorithms. Simulations with wide-ranging conditions indicate that when shift correction is employed with both algorithms, the watershed algorithm detects resolved peaks with greater accuracy than the two-step method.     

硒芳香杂环化合物的GC/MS分析

本文对合成的7种含硒芳香杂环化合物进行了GC／MS分析研究。结果表明：BS、MB、BBS和DBBS等4个化合物在色谱柱内的保留时间与它们的相对分子质量呈线性关系。所有化合物均可获得特征质谱,表现出含单个硒原子的分子离子或碎片离子特征峰簇,硒的两种主要同位素在峰簇中表现为主要峰M与（M-2）的相对丰度比约为2：1,可为鉴定含硒分子离子或碎片离子提供重要信息。新化合物1,2,5-硒二唑并[3,4-d]嘧啶-5,7-（4H,6H）二酮（SPDO）在色谱柱内出现11．83min和7．96min两个具有相同的质谱的色谱峰,被认为是互变异构体的峰。     

Peak pattern variations related to comprehensive two-dimensional gas chromatography acquisition

Identifying compounds of interest for peaks in data generated by comprehensive two-dimensional gas chromatography (GC x GC) is a critical analytical task. Manually identifying compounds is tedious and time-consuming. An alternative is to use pattern matching. Pattern matching identifies compounds by matching previously observed patterns with known peaks to newly observed patterns with unidentified peaks. The fundamental difficulty of pattern matching comes from peak pattern distortions that are caused by differences in data acquisition conditions. This paper investigates peak pattern variations related to varying oven temperature ramp rate and inlet gas pressure and evaluates two types of affine transformations for matching peak patterns. The experimental results suggest that, over the experimental ranges, the changes in temperature ramp rate generate non-linear pattern variations and changes in gas pressure generate nearly linear pattern variations. The results indicate the affine transformations can largely remove the pattern variations and can be used for applications such as pattern matching and normalizing retention times to retention indices.     

An ultrasonication-assisted extraction and derivatization protocol for GC/TOFMS-based metabolite profiling

Conventional chemical derivatization of metabolites in biological specimens is time-consuming, which limits the throughput and efficiency of metabolite profiling using a gas chromatography/time-of-flight mass spectrometry (GC/TOFMS) platform. We report an ultrasonication-assisted protocol which reduces the derivatization time from hours to about 30 min and significantly enhances the derivatization efficiency prior to a GC/TOFMS analysis. The protocol was evaluated using 40 compounds representing different classes of human metabolites, and demonstrated good analytical precision and accuracy. In comparison with the conventional method, the new protocol was able to increase the intensity of most of the identified peaks (71.0%) in the GC/TOFMS chromatograms of human serum samples. The detected compounds with increased intensity include most amino acids, keto-containing organic acids, carbonyl-containing carbohydrates, and unsaturated fatty acids. We applied this protocol in a metabolomic study of human serum samples obtained from 34 patients diagnosed with hypertension and 29 age- and gender-matched healthy subjects. Metabolite markers associated with hypertension, including glucosamine, D-sorbitol, 1-stearoylglycerol, and homocysteine, were identified and validated by statistical methods and use of reference standards. Our work highlights the potential of this novel approach for the large-scale metabolite profiling of samples generated from plant, animal, and clinical and epidemiological studies.     

基于气相色谱-质谱联用技术的水稻代谢轮廓分析方法的建立

开展了基于衍生化气相色谱-质谱联用的水稻代谢物分析方法的研究。采用D-最优试验设计对代谢物的提取溶剂进行优化,考察了水、甲醇、乙腈和异丙醇的提取效率,通过多元统计分析评价提取效能和溶剂配比的相关性,最终确立以80%(v/v)甲醇/水作为代谢物提取的最适溶剂。在此基础上对该方法的分析性能进行评价,发现绝大多数代谢物(＞90%)具有良好的精密度、重现性和稳定性(相对标准偏差小于30%),且占总峰面积88.0%的代谢物的响应值与其浓度间呈线性关系(相关系数＞0.9)。采用气相色谱-质谱联用方法从水稻种子中共鉴定出86个代谢物,涵盖糖、氨基酸、有机酸、甾体等多类浓度差异大的物质,适合于水稻的代谢表型差异研究。     

Multivariate selectivity as a metric for evaluating comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry subjected to chemometric peak deconvolution

Two-dimensional gas chromatography (GC x GC) coupled to time-of-flight mass spectrometry (TOFMS) [GC x GC-TOFMS)] is a highly selective technique well suited to analyzing complex mixtures. The data generated is information-rich, making it applicable to multivariate quantitative analysis and pattern recognition. One separation on a GC x GC-TOFMS provides retention times on two chromatographic columns and a complete mass spectrum for each component within the mixture. In this report, we demonstrate how GC x GC-TOFMS combined with trilinear chemometric techniques, specifically parallel factor analysis (PARAFAC) initiated by trilinear decomposition (TLD), results in a powerful analytical methodology for multivariate deconvolution. Using PARAFAC, partially resolved components in complex mixtures can be deconvoluted and identified without requiring a standard data set, signal shape assumptions or any fully selective mass signals. A set of four isomers (iso-butyl, sec-butyl, tert-butyl, and n-butyl benzenes) is used to investigate the practical limitations of PARAFAC for the deconvolution of isomers at varying degrees of chromatographic resolution and mass spectral selectivity. In this report, multivariate selectivity was tested as a metric for evaluating GC x GC-TOFMS data that is subjected to PARAFAC peak deconvolution. It was found that deconvolution results were best with multivariate selectivities over 0.18. Furthermore, the application of GC x GC-TOFMS followed by TLD/PARAFAC is demonstrated for a plant metabolite sample. A region of GC x GC-TOFMS data from a complex natural sample of a derivatized metabolic plant extract from Huilmo (Sisyrinchium striatum) was analyzed using TLD/PARAFAC, demonstrating the utility of this analytical technique on a natural sample containing overlapped analytes without selective ions or peak shape assumptions.     

Comparative evaluation of software for retention time alignment of gas chromatography/time-of-flight mass spectrometry-based metabonomic data

In chromatography-based metabonomic research, retention time (RT) alignment of chromatographic peaks poses a challenge for the accurate profiling of biomarkers. Although a number of RT alignment software has been reported, the performance of these software packages have not been comprehensively evaluated. This study aimed to evaluate the RT alignment accuracy of publicly available and commercial RT alignment software. Two gas chromatography/mass spectrometry (GC/MS) datasets acquired from a mixture of standard metabolites and human bladder cancer urine samples, were used to assess three publicly available software packages, MetAlign, MZmine and TagFinder, and two commercial applications comprising the Calibration feature and Statistical Compare of ChromaTOF software. The overall RT alignment accuracies in aligning standard compounds mixture were 93, 92, 74, 73 and 42% for Calibration feature, MZmine, MetAlign, Statistical Compare and TagFinder, respectively. Additionally, unique trends were observed for the individual software with regards to the different experimental conditions related to extent and direction of RT shifts. Conflicting performance was observed for human urine samples suggesting that RT misalignments still occurred despite the use of RT alignment software. While RT alignment remains an inevitable step in data preprocessing, metabonomic researchers are recommended to perform manual check on the RT alignment of important biomarkers as part of their validation process.     

Computer-assisted peak recognition for polychlorinated dibenzo-p-dioxins (PCDD) and polychlorinated dibenzofurans (PCDF) in environmental samples

A software has been developed for the peak recognition of 136 polychlorinated dibenzo-p-dioxins (PCDD) and polychlorinated dibenzofurans (PCDF) after high resolution gas chromatography coupled with mass spectrometry (HRGC/HRMS). Based on the retention times of ¹³C labelled 2,3,7,8-substituted PCDD/F internal standards, the retention times of all PCDD and PCDF can be calibrated automatically and accurately. Therefore, it is very convenient to identify the peaks by comparing the retention of samples and the calibrated retention times of their chromatograms. Hence, this approach is very significant because it is impossible to obtain always a standard chromatogram and PCDD/F analysis are very expensive and time consuming. The calibration results can be transferred to Excel for calculation. The approach is a first step to store costly and environmentally relevant data for future application.