Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography

Data processing and evaluation are critical steps of comprehensive two-dimensional gas chromatography (GCxGC), particularly when coupled to mass ...

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This paper investigates methods for comparing datasets produced by comprehensive two-dimensional gas chromatography (GC x GC). Chemical comparisons are useful for process monitoring, sample classification or identification, correlative determinations, and other important tasks. GC x GC is a powerful new technology for chemical analysis, but methods for comparative visualization must address challenges posed by GC x GC data: inconsistency and complexity. The approach extends conventional techniques for image comparison by utilizing specific characteristics of GC x GC data and developing new methods for comparative visualization and analysis. The paper describes techniques that register (or align) GC x GC datasets to remove retention-time variations; normalize intensities to remove sample amount variations; compute differences in local regions to remove slight misregistrations and differences in peak shapes; employ color (hue), intensity, and saturation to simultaneously visualize differences and values; and use tools for masking, three-dimensional visualization, and tabular presentation with controls for graphical highlights to significantly improve comparative analysis of GC x GC datasets. Experimental results indicate that the comparative methods preserve chemical information and support qualitative and quantitative analyses.

Comparative visualization for comprehensive two-dimensional gas chromatography.

Comprehensive two-dimensional gas chromatography (GC×GC) and high-resolution mass spectrometry (HRMS) offer the best possible separation of their respective techniques. Recent commercialization of combined GC×GC-HRMS systems offers new possibilities for the analysis of complex mixtures. However, such experiments yield enormous data sets that require new informatics tools to facilitate the interpretation of the rich information content. This study reports on the analysis of dust obtained from an electronics recycling facility by using GC×GC in combination with a new high-resolution time-of-flight (TOF) mass spectrometer. New software tools for (non-traditional) Kendrick mass defect analysis were developed in this research and greatly aided in the identification of compounds containing chlorine and bromine, elements that feature in most persistent organic pollutants (POPs). In essence, the mass defect plot serves as a visual aid from which halogenated compounds are recognizable on the basis of their mass defect and isotope patterns. Mass chromatograms were generated based on specific ions identified in the plots as well as region of the plot predominantly occupied by halogenated contaminants. Tentative identification was aided by database searches, complementary electron-capture negative ionization experiments and elemental composition determinations from the exact mass data. These included known and emerging flame retardants, such as polybrominated diphenyl ethers (PBDEs), hexabromobenzene, tetrabromo bisphenol A and tris (1-chloro-2-propyl) phosphate (TCPP), as well as other legacy contaminants such as polychlorinated biphenyls (PCBs) and polychlorinated terphenyls (PCTs). 

Non-targeted analysis of electronics waste by comprehensive two-dimensional gas chromatography combined with high-resolution mass spectrometry: Using accurate mass information and mass defect analysis to explore the data.

The capture of volatile patterns from food is a fingerprinting that opens access to a high level of information related to functional variables (origin, processing, shelf-life etc.) and their impact on sample composition and quality. When the focus is on food volatilome, comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC×GC-TOF MS) is undoubtedly the most effective technique to obtain a highly representative fingerprinting. A recently patented ion source, featuring variable-energy EI, when operated at low energies (10 eV, 12 eV, 14 eV), claims enhanced intensity of structure-indicating ions while minimizing the inherent loss of sensitivity due to low EI energies. The spectral acquisition is done by multiplexing between two ionization energies and generates tandem data streams in a single run. This study explores the potentials of combined untargeted/targeted (UT) fingerprinting with tandem signals to study the complex volatile metabolome of high quality cocoa. The quality of the spectra at 70 eV is confirmed by similarity match factors above a fixed threshold (950) while spectral differences between hard (70 eV) and soft (12 eV, 14 eV) ionization are computed in terms of spectral similarity and signal-to-noise ratio (SNR). Tandem signals are then processed independently and after fusion in a single stream (summed signal) by the UT fingerprinting work-flow; signal characteristics (SNR, detectable 2D peaks, spectral peak intensities) are then computed and adopted to define the best strategy to discriminate and classify samples. Classification performance, on processed cocoa from four different origins, is validated by cross-comparing results between single ionization channels and fused data streams and considering both targeted and untargeted features. Classification results indicate the potential for superior performances of UT fingerprinting with fused data streams (summed signals), while signal characteristics at low ionization energies not only offer additional elements to better discriminate and/or identify isomeric analytes but also to achieve wider dynamic range of exploration.

Comprehensive two-dimensional gas chromatography coupled with time of flight mass spectrometry featuring tandem ionization: Challenges and opportunities for accurate fingerprinting studies.

Qingping Tao

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Chromatographic Fingerprinting by Template Matching for Data Collected by Comprehensive Two-Dimensional Gas Chromatography