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Milani NBL, van Gilst E, Pirok BWJ, Schoenmakers PJ. Comprehensive two-dimensional gas chromatography- A discussion on recent innovations. J Sep Sci 2023; 46:e2300304. [PMID: 37654057 DOI: 10.1002/jssc.202300304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 08/16/2023] [Accepted: 08/19/2023] [Indexed: 09/02/2023]
Abstract
Although comprehensive 2-D GC is an established and often applied analytical method, the field is still highly dynamic thanks to a remarkable number of innovations. In this review, we discuss a number of recent developments in comprehensive 2-D GC technology. A variety of modulation methods are still being actively investigated and many exciting improvements are discussed in this review. We also review interesting developments in detection methods, retention modeling, and data analysis.
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Affiliation(s)
- Nino B L Milani
- Van't Hoff Institute for Molecular Science (HIMS), University of Amsterdam, Amsterdam, the Netherlands
| | - Eric van Gilst
- Van't Hoff Institute for Molecular Science (HIMS), University of Amsterdam, Amsterdam, the Netherlands
| | - Bob W J Pirok
- Van't Hoff Institute for Molecular Science (HIMS), University of Amsterdam, Amsterdam, the Netherlands
| | - Peter J Schoenmakers
- Van't Hoff Institute for Molecular Science (HIMS), University of Amsterdam, Amsterdam, the Netherlands
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2
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Sorochan Armstrong MD, Hinrich JL, de la Mata AP, Harynuk JJ. PARAFAC2×N: Coupled decomposition of multi-modal data with drift in N modes. Anal Chim Acta 2023; 1249:340909. [PMID: 36868765 DOI: 10.1016/j.aca.2023.340909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 01/23/2023] [Accepted: 01/30/2023] [Indexed: 02/04/2023]
Abstract
Analysis of GC×GC-TOFMS data for large numbers of poorly-resolved peaks, and for large numbers of samples remains an enduring problem that hinders the widespread application of the technique. For multiple samples, GC×GC-TOFMS data for specific chromatographic regions manifests as a 4th order tensor of I mass spectral acquisitions, J mass channels, K modulations, and L samples. Chromatographic drift is common along both the first-dimension (modulations), and along the second-dimension (mass spectral acquisitions), while drift along the mass channel is for all practical purposes nonexistent. A number of solutions to handling GC×GC-TOFMS data have been proposed: these involve reshaping the data to make it amenable to either 2nd order decomposition techniques based on Multivariate Curve Resolution (MCR), or 3rd order decomposition techniques such as Parallel Factor Analysis 2 (PARAFAC2). PARAFAC2 has been utilised to model chromatographic drift along one mode, which has enabled its use for robust decomposition of multiple GC-MS experiments. Although extensible, it is not straightforward to implement a PARAFAC2 model that accounts for drift along multiple modes. In this submission, we demonstrate a new approach and a general theory for modelling data with drift along multiple modes, for applications in multidimensional chromatography with multivariate detection. The proposed model captures over 99.9% of variance for a synthetic data set, presenting an extreme example of peak drift and co-elution across two modes of separation.
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Affiliation(s)
| | - Jesper Løve Hinrich
- Department of Food Science, University of Copenhagen, Rolighedsvej 26, Copenhagen, DK-1958, Denmark
| | - A Paulina de la Mata
- Department of Chemistry, University of Alberta, 11227 Saskatchewan Dr NW, Edmonton, T6G 2G2, Alberta, Canada
| | - James J Harynuk
- Department of Chemistry, University of Alberta, 11227 Saskatchewan Dr NW, Edmonton, T6G 2G2, Alberta, Canada.
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3
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Hantao LW. Revisiting the Fundamentals of Untargeted Data Analysis with Comprehensive Two-Dimensional Gas Chromatography (GC×GC): With Great Peak Capacity, There Must Also Come Great Responsibility. LCGC NORTH AMERICA 2023. [DOI: 10.56530/lcgc.na.yz7686f4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2023]
Abstract
This article provides a general overview of untargeted analysis using comprehensive two-dimensional gas chromatography (GC×GC), while revisiting some fundamental aspects of method development. The original definition of chemometrics is also revised according to the latest developments of the field. We discuss how GC×GC has become an important backbone for new strategies in separation science, especially in multivariate data analysis. The concept of pixel is also revisited, as an important pixel-based data processing method, namely the Fisher ratio proposed by Synovec and coworkers, has been successfully implemented in important software for GC×GC.
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Affiliation(s)
- Leandro Wang Hantao
- University of Campinas and the National Institute of Science and Technology in Bioanalytics
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4
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Nolvachai Y, Amaral MSS, Marriott PJ. Foods and Contaminants Analysis Using Multidimensional Gas Chromatography: An Update of Recent Studies, Technology, and Applications. Anal Chem 2023; 95:238-263. [PMID: 36625115 DOI: 10.1021/acs.analchem.2c04680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Affiliation(s)
- Yada Nolvachai
- Australian Centre for Research on Separation Science, School of Chemistry, Monash University, Wellington Road, Clayton, Victoria 3800, Australia
| | - Michelle S S Amaral
- Australian Centre for Research on Separation Science, School of Chemistry, Monash University, Wellington Road, Clayton, Victoria 3800, Australia
| | - Philip J Marriott
- Australian Centre for Research on Separation Science, School of Chemistry, Monash University, Wellington Road, Clayton, Victoria 3800, Australia
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Trinklein TJ, Cain CN, Ochoa GS, Schöneich S, Mikaliunaite L, Synovec RE. Recent Advances in GC×GC and Chemometrics to Address Emerging Challenges in Nontargeted Analysis. Anal Chem 2023; 95:264-286. [PMID: 36625122 DOI: 10.1021/acs.analchem.2c04235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Affiliation(s)
- Timothy J Trinklein
- Department of Chemistry, University of Washington, Box 351700, Seattle, Washington 98195-1700, United States
| | - Caitlin N Cain
- Department of Chemistry, University of Washington, Box 351700, Seattle, Washington 98195-1700, United States
| | - Grant S Ochoa
- Department of Chemistry, University of Washington, Box 351700, Seattle, Washington 98195-1700, United States
| | - Sonia Schöneich
- Department of Chemistry, University of Washington, Box 351700, Seattle, Washington 98195-1700, United States
| | - Lina Mikaliunaite
- Department of Chemistry, University of Washington, Box 351700, Seattle, Washington 98195-1700, United States
| | - Robert E Synovec
- Department of Chemistry, University of Washington, Box 351700, Seattle, Washington 98195-1700, United States
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Gaida M, Franchina FA, Stefanuto PH, Focant JF. Top-Down Approach to Retention Time Prediction in Comprehensive Two-Dimensional Gas Chromatography-Mass Spectrometry. Anal Chem 2022; 94:17081-17089. [PMID: 36444996 DOI: 10.1021/acs.analchem.2c03107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
In this contribution, we describe a novel modeling approach to predicting retention times (tr) in comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-ToF-MS) with a particular emphasis on the second-dimension (2D) retention time predictions (2tr). This approach is referred to as a "top-down" approach in that it breaks down the complete GC × GC separation into two independent one-dimensional gas chromatography separations (1D-GC). In this regard, both dimensions, that is, first dimension (1D) and second dimension (2D) are treated separately, and the cryogenic modulator is simply considered as a second consecutive injection device. Separate 1D-GC tr predictions are performed on both dimensions using the same flow rate as the one deployed in the conventional GC × GC system. The separate tr predictions are then combined to account for the two-dimensional separation. This model was applied to 24 analytes from 2 standard mixtures (Grob Test Mix and Fragrance Materials Test Mix) and assessed across 9 GC × GC chromatographic conditions. The experimental and predicted chromatographic retention space occupations were assessed by using the convex hull approach defined by the Delaunay triangulation. The predicted percentage of space occupation corresponded favorably with the experimental values. Furthermore, the top-down approach enabled an accurate prediction of the 2tr of all investigated analytes, providing an average 2tr modeling error of 0.26 ± 0.01 s.
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Affiliation(s)
- Meriem Gaida
- Molecular Systems, Organic and Biological Analytical Chemistry Group, University of Liège, Allée du Six Août, 11, B6c, 4000Liège, Belgium
| | - Flavio A Franchina
- Department of Chemistry, Pharmaceutical, and Agricultural Sciences, University of Ferrara, via L. Borsari 46, 44121Ferrara, Italy
| | - Pierre-Hugues Stefanuto
- Molecular Systems, Organic and Biological Analytical Chemistry Group, University of Liège, Allée du Six Août, 11, B6c, 4000Liège, Belgium
| | - Jean-François Focant
- Molecular Systems, Organic and Biological Analytical Chemistry Group, University of Liège, Allée du Six Août, 11, B6c, 4000Liège, Belgium
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Trinklein TJ, Synovec RE. Simulating comprehensive two-dimensional gas chromatography mass spectrometry data with realistic run-to-run shifting to evaluate the robustness of tile-based Fisher ratio analysis. J Chromatogr A 2022; 1677:463321. [PMID: 35853427 DOI: 10.1016/j.chroma.2022.463321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 07/01/2022] [Accepted: 07/07/2022] [Indexed: 10/17/2022]
Abstract
Untargeted analysis of comprehensive two-dimensional (2D) gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) data has the potential to be hindered by run-to-run retention time shifting. To address this challenge, tile-based Fisher ratio (F-ratio) analysis (FRA) has been developed, which utilizes a supervised, untargeted approach involving a chromatographic segmentation routine termed "tiling" combined with the ANOVA F-ratio statistic to discover class-distinguishing analytes while minimizing false positives arising from shifting. The tiling algorithm is designed to account for retention shifting in both separation dimensions. Although applications of FRA have been reported, there remains a need to thoroughly evaluate the robustness of FRA for different levels of run-to-run retention shifting in order to broaden the scope of its application. To this end, a novel method of simulating GC×GC-TOFMS chromatograms with realistic run-to-run shifting is presented by random generation of low-frequency "shift functions". The dimensionless retention-time precision, <δr>, which is four times the standard deviation in retention time normalized to the peak width-at-base is used as a key modeling variable along with the 2D chromatographic saturation, αe,2D, and within-class relative standard deviation in peak area, RSDwc. We demonstrate that all three of these variables operate together to impact true positive discovery. To quantify the "success" of true positive discovery, GC×GC-TOFMS datasets for various combinations of <δr>, αe,2D, and RSDwc were simulated and then analyzed by FRA using a wide range of relative tile areas (RTA), which is a dimensionless measure of tile size. Since each hit in the FRA hit list was known a priori as either a true or false positive based on the simulation inputs, receiver operating characteristic (ROC) curves were readily constructed. Then, the area under the ROC curve (AUROC) was used as a metric for discovery "success" for various combinations of the modeling variables. Based on the results of this study, recommendations for tile size selection and experimental design are provided, and further supported by comparison to previous tile-based FRA applications. For instance, values for <δr>, αe,2D, and RSDwc obtained from a GC×GC-TOFMS dataset of yeast metabolites suggested an optimum RTA of 6.25, corresponding closely to the RTA of 4.00 employed in the study, implying the simulation results obtained here can be generalized to real datasets.
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Affiliation(s)
- Timothy J Trinklein
- Department of Chemistry, Box 351700, University of Washington, Seattle, WA 98195, USA
| | - Robert E Synovec
- Department of Chemistry, Box 351700, University of Washington, Seattle, WA 98195, USA.
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