Rapid Screening of Complex Matrices: Utilizing Kendrick Mass Defect to Enhance Knowledge-Based Group Type Evaluation of Multidimensional Gas Chromatography-High-Resolution Time-of-Flight Mass Spectrometry Data

Organic compound characterization of highly complex matrices involves scientific challenges, such as the diversity of "true" unknowns, the concentration ranges of various compound classes, and limited available amounts of sample. Therefore, discovery-based multidimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry (GC×GC-HRToFMS) is increasingly applied. Nevertheless, most studies focus on target analysis and tend to disregard important details of the sample composition. The increased peak or separation capacity of GC×GC-ToFMS allows for in-depth chemical analysis of the molecular composition. However, high amounts of data, containing several thousands of compounds per experiment, are generally acquired during such analyses. Coupling GC×GC to high-resolution mass spectrometry further increases the amount of data and therefore requires advanced data reduction and mining techniques. Commonly, the main approach for the evaluation of GC×GC-HRToFMS data sets either focuses on the chromatographic separation (e.g., group type analysis), or utilizes exact mass data applying Kendrick mass defect analysis or van Krevelen plots. The presented approach integrates the accurate mass data and the chromatographic information by combining Kendrick mass defect information and knowledge-based rules. This combination allows for fast, visual data screening as well as quantitative estimation of the sample's composition. Moreover, the resulting sample classification significantly reduces the number of variables, allowing distinct chemometric analysis in nontargeted studies, such as detailed hydrocarbon analyses and environmental and forensic investigations. Copyright © 2019 American Chemical Society

Comprehensive Two-dimensional gas-chromatography to study the human exposome: Current trends and perspectives

In context of the exposome paradigm, the ‘exposure’ describes all individual and global environmental influences an individual throughout its entire lifetime. Cause, effect and their causality are the central research objectives, which require interdisciplinary research strategies. The core benefits of comprehensive two-dimensional gas chromatography (GC×GC) make it a versatile technique for both, exposure and response driven approaches, especially when combined with appropriate sample preparation and MS detection. In this article, the potentials and recent advances of GC×GC in the field of human exposome research is critically discussed

Rapid screening of complex biological matrices: Utilizing kendrick mass defect for group type evaluation of GC×GC-HR(EI)ToF/MS data

Characterization of highly complex matrices implicates scientific challenges such as wide presence of “true” unknowns, concentration ranges of various compound classes and limited, available amounts of sample. Cutting-edge, discovery based separation techniques such as multidimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry (GCxGC-HRToF/MS), are commonly applied to such analytical challenges. Nevertheless, most studies focus on target analysis and tend to disregard important details of the sample composition. The high separation capacity of GCxGC-ToF/MS allows for in-depth chemical analysis of the molecular composition. However, high amounts of data, containing several thousands of compounds per experiment, are generally acquired during such analyzes. Coupling GCxGC to high-resolution mass spectrometry (HRMS) further increases the amount of data and therefore requires advanced data reduction and mining techniques. Commonly, the main approach for the evaluation of dense data sets either focuses on the chromatographic separation for e.g. group type analysis, or utilizes exact mass data applying Kendrick Mass Defect (KMD) analysis or van Krevelen plots. The presented approach integrated the accurate mass data into the chromatographic information by combining KMD information and knowledge-based rules. This combination allows for fast, visual data screening as well as first quantitative estimation of the sample's composition. Moreover, the resulted sample classification significantly reduces the number of variables, allowing distinct chemometric analysis in non-targeted studies such as detailed hydrocarbon analysis (DHA), environmental and forensic investigations

Establishing a Unique Open-Source Benchmark Dataset for the Comprehensive Evaluation of GC×GC Software

Two-dimensional gas chromatography is amongst the most powerful separation technologies currently available. Since its advent in 1990, it has become an established method which is readily available. However, one of its most challenging aspects, especially in hyphenation with mass spectrometry, is the high amount of chemical information it provides for each measurement. The GC×GC community agrees that there the highest demand for action [1–3]. In response, the number of software packages allowing for in-depth data analysis of GC×GC data has risen over the last couple of years. These packages provide sophisticated tools and algorithms allowing for more streamlined data evaluation. However, the tools/algorithms and their functionality differ drastically within the available software packages. This study focuses on two main objectives: first, establishing an open-source dataset for benchmarking, and second, streamlined evaluation guidelines for comprehensive comparison for GC×GC software. Thereby, the benchmark data includes, a set of standard compound measurements and a set of chocolate aroma profiles. On this foundation, eight readily available GC×GC software packages were investigated for fundamental and advanced functionality.Chimi

Can Increased Instrumental Sensitivity Replace Extensive Sample Preparation?

The optimization of gas chromatographic separations is often a necessary step to push the limits of detection and quantitation to their utmost limits. Parameters controlling injection and separation conditions need to be adjusted and optimized thoroughly for rugged and reproducible conditions. Thereby, careful attention needs to be paid to the sample preparation stage, since it often enhances the instrumental sensitivity. Moreover, sample preparation is highly prone to error, as well as time-consuming[1]. For this reason, techniques that offer a reduction of the overall sample preparation procedure are of increasing interest. Two-dimensional comprehensive gas chromatography (GC×GC) offers a wide scope of advantages allowing for simplified sample preparation. For example, analytes of interest can be separated from the interfering matrix due to the increased separation capacity, while the cold zone compression allows for increased sensitivity and improved peak shapes. Especially the hyphenation of GC×GC and highly sensitive mass analyzers can potentially reduce steps needed in existing sample preparation procedures. In this study, the authors evaluate the performance of a GC×GC-ToF/MS for a detailed analysis of the volatile organic profile in Belgian chocolate. To evaluate the impact of the MS’s sensitivity a previously established sample preparation procedure was compared to a minimalistic sample preparation approach [2]. Although the majority of compounds could be determined in both approaches, initial findings indicate differences in between the two investigated approaches. Thereby, the differences are not only limited to the total number of compounds detected but also the detected compound classes differ within the compared approaches. Depending on the analytical challenge, the applied approach has to be chosen. References: [1] R.E. Majors, Overview of Sample Preparation, LCGC. (1991) 16–20. http://www.chromatographyonline.com/overview-sample-preparation. [2] C. Müller, F. Vetter, E. Richter, F. Bracher, Determination of caffeine, myosmine, and nicotine in chocolate by headspace solid-phase microextraction coupled with gas chromatography-tandem mass spectrometry, J. Food Sci. 79 (2014). doi:10.1111/1750-3841.12339.CHIMI

Optimization of a multidimensional gas chromatographic separation. Classical steps toward a better characterization of the separation space.

The chromatographic separation in multidimensional gas chromatography is significantly affected by the interactions between the involved experimental parameters[1]. In order to achieve the best separation possible, these parameters need to be thoroughly optimized. Chromatographic procedures are optimized by varying one parameter at a time, thereby disregarding interactions between the two separation dimensions and resulting in time- consuming procedures[2]. Moreover, the metrics of chromatographic optimization are sometimes not clearly defined or solely based on the user’s expertise and/or intuition. In the present study, chromatographic factors were measured from a designed set of GC×GC- ToF-MS analysis of standards. These factors were used to derive specific outcomes that allowed for a detailed characterization of the two-dimensional (2D) separation space. Furthermore, the result of a design of experiments approach allowed for a statistical investigation of commonly optimized factors, namely flow rate, modulation time, and temperature ramp based on the derived outcomes. Initial findings suggest that differences in chemical groups tend to impact the 2D separation. It also highlights a correlation between the influencing factors and the chemical composition of the studied compounds. Additionally, special attention was paid to the structural similarities between the studied compounds, as well as to wraparound effects and their consequences on the derived outcomes. References: [1] J. Harynuk and T. Górecki, “Experimental variables in GC×GC: A complex interplay,” Am. Lab., vol. 39, no. 4, pp. 36–39, 2007. [2] A. Mostafa, M. Edwards, and T. Górecki, “Optimization aspects of comprehensive two- dimensional gas chromatography,” J. Chromatogr. A, vol. 1255, pp. 38–55, 2012.The Chimic projec

Unconventional Kendrick Mass Defect as a visualization and rapid screening tool for GC×GC-HR-ToF/MS measurements

Characterization of complex matrices commonly implicates scientific challenges such as wide concentration ranges of various compound classes and/or the limited, available sample volume. Applying cutting-edge, discovery based separation techniques such as multidimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry (GCxGC-HRToF/MS) facilitate such analytical challenges. Nevertheless, the majority of studies is still focused on targeted analysis, which tend to disregard important details of the sample of interest. GCxGC-ToF/MS provides in-depth chemical insight in the molecular fingerprint of analyzed matrices. However, such analysis produces high amounts of data generally containing several thousands of compounds per experiment. The amount of data will further increase by coupling GCxGC to high-resolution mass spectrometry (HRT), which requires advanced data reduction and mining techniques. So far, GCxGC-HRToF/MS information is evaluated by focusing either on the chromatographic separation for e.g. group type analysis, or utilizing exact mass data applying Kendrick Mass Defect (KMD) analysis or van Krevelen. This study integrates high-resolution mass information directly into the multidimensional separation space, combining KMD data and knowledge-based rules. Combining of these approaches allows for fast, visual data screening as well as a first quantitative estimation of the samples composition. Additionally the obtained classification drastically reduces the number of variables allowing a clear and distinct chemometric analysis in e.g. environmental and forensic studies such as for detailed hydrocarbon analysis (DHA)

Unit duty-cycle differential flow modulation GC×GC-MS: insights on the modulation process

One of the major limitations of current-day flow-modulated comprehensive two-dimensional gas chromatography (FM GC×GC) is the generation of high gas flows (e.g., 20 mL/min) in the second analytical dimension, if unit sampling duty cycle is considered [1]. Even though such high flows are necessary to efficiently flush the content of the modulator onto the second dimension, they also greatly restrict the employment of mass spectrometry (MS), which is nowadays considered as the most powerful and informative detection tool. One way to enable the use of MS systems, in FM applications, is to divert a substantial part of the second-dimension flow to waste, with an obvious negative impact on sensitivity. The present contribution is focused on the development of unit sampling duty cycle methods using flow-modulated comprehensive two-dimensional gas chromatography in combination with mass spectrometry. Specifically, a FM GC×GC-MS approach was developed in which the flows necessary to efficiently flush the modulator were greatly reduced (<5 mL/min) [2]. The approach finely reconsiders the accumulation and injection phases of modulation and allows a full transfer onto the second dimension and the detector with no need to divert the flow [3]. The efficiency of the set-up is demonstrated on real-world samples (petrochemical and fragrance)