Advances in the application of comprehensive two-dimensional gas chromatography in metabolomics

Keppler, Emily A. Higgins; Jenkins, Carrie L.; Davis, Thomas J.; Bean, Heather D.

doi:10.1016/j.trac.2018.10.015

Cited by 111 publications

(62 citation statements)

References 75 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, these techniques are not easy to apply on the complex mixtures. Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful technique that is capable of separating hundreds of thousands of chemicals in complex mixtures 24 . Scientists were able to identify known skin penetrants in environmental samples such as the household dust using comprehensive two-dimensional liquid chromatography coupled with time-of-flight mass spectrometry 25 .…”

Section: Introductionmentioning

confidence: 99%

Development and Evaluation of Two-Parameter Linear Free Energy Models for the Prediction of Human Skin Permeability Coefficient of Neutral Organic Chemicals

Naseem¹,

Zushi

Nabi

2020

Preprint

View full text Add to dashboard Cite

The experimental values of skin permeability coefficients, required for dermal exposure assessment, are not readily available for many chemicals. The existing estimation approaches are either less accurate or require many parameters that are not readily available. Furthermore, current estimation methods are not easy to apply to complex environmental mixtures. We present two models to estimate the skin permeability coefficients of neutral organic chemicals. The first model, referred to here as the 2-parameter partitioning model (PPM), exploits a linear free energy relationship (LFER) of skin permeability coefficient with a linear combination of partition coefficients for octanol-water and air-water systems. The second model is based on the retention time information of nonpolar analytes on comprehensive two-dimensional gas chromatography (GC×GC). The PPM successfully explained variability in the skin permeability data (n = 175) with R2 = 0.82 and root mean square error (RMSE) = 0.47 log unit. In comparison, the US-EPA’s model DERMWIN exhibited an RMSE of 0.78 log unit. The Zhang model T a 5-parameter LFER equation based on experimental Abraham solute descriptors (ASDs) h performed slightly better with an RMSE value of 0.44 log unit. However, the Zhang model is limited by the scarcity of experimental ASDs. The GC×GC model successfully explained the variance in skin permeability data of nonpolar chemicals (n = 79) with R2 = 0.90 and RMSE = 0.23 log unit. The PPM can easily be implemented in US-EPA’s Estimation Program Interface Suite (EPI Suite™). The GC×GC model can be applied to the complex mixtures of nonpolar chemicals.

show abstract

Section: Introductionmentioning

confidence: 99%

Development and Evaluation of Two-Parameter Linear Free Energy Models for the Prediction of Human Skin Permeability Coefficient of Neutral Organic Chemicals

Naseem¹,

Zushi

Nabi

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Introduced nearly three decades ago, comprehensive 2D GC increases enormously the separation and identification capability compared to conventional systems, especially when coupled with MS. Nowadays, GC × GC–MS represents the most powerful tool for VOC and semi‐VOC determination, especially in untargeted analysis . In recent years, thanks in part to a common intent to make the use of GC × GC less expensive and more accessible, cryogenic‐free or pneumatic modulators have gained attention .…”

Section: Introductionmentioning

confidence: 99%

Investigating aroma diversity combining purge‐and‐trap, comprehensive two‐dimensional gas chromatography, and mass spectrometry

Franchina

Zanella

Lazzari

et al. 2019

J of Separation Science

View full text Add to dashboard Cite

Headspace gas chromatography is frequently used for aroma profiling thanks to its ability to naturally exploit the volatility of aroma compounds, and also to provide chemical information on sample composition. Its main advantages rely on simplicity, no use of solvent, amenability to automation, and the cleanliness of the extract.In the present contribution, the most effective sampling (dynamic extraction), separation (multidimensional gas chromatography), and detection (mass spectrometry) techniques for untargeted analysis are exploited in combination, showing their potential in unraveling aroma profiles in fruit beers. To complete the overall analytical process, a neat workflow for data analysis is discussed and used for the successful characterization and identification of five different beer flavors (berries, cherry, banana, apple, and peach). From the technical viewpoint, the coupling of purge-andtrap, comprehensive two-dimensional gas chromatography, and mass spectrometry makes the global methodology unique, and it is for the first time discussed. A (low-)flow modulation approach allowed for the full transfer into the second dimension with mass-spectrometry compatible flow (< 7 mL/min), avoiding the need of splitting before detection and making the overall method sensitive (1.2-5.2-fold higher signal to noise ratio compared to unmodulated gas chromatography conditions) and selective. K E Y W O R D S dynamic headspace sampling, flow modulation GC × GC, food authenticity, time-of-flight mass spectrometry, untargeted analysis 1790

show abstract

“…The difficulty of detecting and identifying analytes in data from comprehensive two-dimensional gas chromatography with mass spectrometry (GC×GC-MS) ranges from simple, for resolved analytes that have clear spectral signals matched in mass-spectral libraries, to challenging, for coeluted and trace analytes that have obscure or faint signals and ambiguous matching with mass-spectral libraries [1][2][3][4][5]. This case study examines a combination of time-tested and new peak detection techniques, beginning with the 2D drain algorithm that is highly effective for resolved peaks, filtering of those peaks, followed by a new method for predicting true and false peak detections, and combined with a new tool that detects collections of coincident ion-peaks.…”

Section: Introductionmentioning

confidence: 99%

A Data-Challenge Case Study of Analyte Detection and Identification with Comprehensive Two-Dimensional Gas Chromatography with Mass Spectrometry (GC×GC-MS)

et al. 2019

View full text Add to dashboard Cite

This case study describes data analysis of a chromatogram distributed for the 2019 GC×GC Data Challenge for the Tenth Multidimensional Chromatography Workshop (Liege, Belgium). The chromatogram resulted from chemical analysis of a terpene-standards sample by comprehensive two-dimensional chromatography with mass spectrometry (GC×GC-MS). First, several aspects of the data quality are assessed, including detector saturation and oscillation, and operations to prepare the data for analyte detection and identification are described, including phase roll for modulation-cycle alignment and baseline correction to account for the non-zero detector baseline. Then, the case study presents operations for analyte detection with filtering, a new method to flag false detections, interactive review to confirm detected peaks, and ion-peaks detection to reveal peaks that are obscured by noise or coelution. Finally, the case study describes analyte identification including mass-spectral library search with a new method for optimizing spectra extraction, retention-index calibration from preliminary identifications, and expression-based identification checks. Processing of the first 40 min of data detected 144 analytes, 21 of which have at least one percent response, plus an additional 20 trace and/or coeluted analytes.

show abstract

Advances in the application of comprehensive two-dimensional gas chromatography in metabolomics

Cited by 111 publications

References 75 publications

Development and Evaluation of Two-Parameter Linear Free Energy Models for the Prediction of Human Skin Permeability Coefficient of Neutral Organic Chemicals

Development and Evaluation of Two-Parameter Linear Free Energy Models for the Prediction of Human Skin Permeability Coefficient of Neutral Organic Chemicals

Investigating aroma diversity combining purge‐and‐trap, comprehensive two‐dimensional gas chromatography, and mass spectrometry

A Data-Challenge Case Study of Analyte Detection and Identification with Comprehensive Two-Dimensional Gas Chromatography with Mass Spectrometry (GC×GC-MS)

Contact Info

Product

Resources

About