Fast Chromatographic Method for Explosive Profiling

peer reviewe

Volatile organic compound profiling to explore primary graft dysfunction after lung transplantation

Primary graft dysfunction (PGD) is a major determinant of morbidity and mortality following lung transplantation. Delineating basic mechanisms and molecular signatures of PGD remain a fundamental challenge. This pilot study examines if the pulmonary volatile organic compound (VOC) spectrum relate to PGD and postoperative outcomes. The VOC profiles of 58 bronchoalveolar lavage fluid (BALF) and blind bronchial aspirate samples from 35 transplant patients were extracted using solid-phase-microextraction and analyzed with comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry. The support vector machine algorithm was used to identify VOCs that could differentiate patients with severe from lower grade PGD. Using 20 statistically significant VOCs from the sample headspace collected immediately after transplantation (< 6 h), severe PGD was differentiable from low PGD with an AUROC of 0.90 and an accuracy of 0.83 on test set samples. The model was somewhat effective for later time points with an AUROC of 0.80. Three major chemical classes in the model were dominated by alkylated hydrocarbons, linear hydrocarbons, and aldehydes in severe PGD samples. These VOCs may have important clinical and mechanistic implications, therefore large-scale study and potential translation to breath analysis is recommended

The diagnostic purpose of odorant patterns for clinical applications using GC×GC

The advances in hardware components and software tools which characterized the youth of comprehensive two-dimensional gas chromatography (GC × GC) are, as a natural evolution of a novel technique, more and more associated with application-oriented studies covering a wide range of fields. In addition, the high-selectivity and separation power of GC × GC have made the technique one of the most powerful tool for untargeted analysis, especially when coupled with mass spectrometry (MS). It is in this context that this chapter is placed, and specifically in the use of odorant patterns in clinical applications, with these intended as the subset of small volatile metabolites which characterize biological samples. During the last decade, the significance of testing of volatile organic compounds (VOCs) in clinical samples has become high, holding a great potential in offering perspectives of non-invasiveness, availability, and time-effectiveness. Depending on the application, the VOCs emitted from clinical matrices can represent (I) metabolites from the altered physiological status (e.g. cancer), (II) metabolites of the infecting pathogen, (III) reflect the pathogen-induced host responses, or (IV) a combination of both. An initial examination of the analytical challenges which characterize the complexity of the samples will be described. Dedicated sample preparation techniques, as well as multidimensional chromatographic configurations hyphenated to MS will be reported. A collection on milestone papers, sorted by biomedical sample type, will also be discussed, showing the potential of the GC × GC technique in unravelling the complexity of the odorant patterns in clinical application

SPME-GC×GC-TOF MS fingerprint of virally-infected cell culture: Sample preparation optimization and data processing evaluation

Untargeted metabolomics study of volatile organic compounds produced by different cell cultures is a field that has gained increasing attention over the years. Solid-phase microextraction has been the sampling technique of choice for most of the applications mainly due to its simplicity to implement. However, a careful optimization of the analytical conditions is necessary to obtain the best performances, which are highly matrix-dependent. In this work, five different solid-phase microextraction fibers were compared for the analysis of the volatiles produced by cell culture infected with the human respiratory syncytial virus. A central composite design was applied to determine the best time-temperature combination to maximize the extraction efficiency and the salting-out effect was evaluated as well. The linearity of the optimized method, along with limits of detection and quantification and repeatability was assessed. Finally, the effect of i) different normalization techniques (i.e. z-score and probabilistic quotient normalization), ii) data transformation (i.e. in logarithmic scale), and iii) different feature selection algorithms (i.e. Fisher ratio and random forest) on the capability of discriminating between infected and not-infected cell culture was evaluated

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

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-and-trap, 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&nbsp;(&lt;&nbsp;7&nbsp;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

Deeper investigation of oxygen-containing compounds in oleaginous feedstock (animal fat) by preparative column chromatography and comprehensive two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry

The production of renewable fuels as biodiesel and bio-jet fuel is usually originated by the transformation and processing of oleaginous feedstocks, mainly composed of triacylglycerols. Currently, a significant part of the triacylglycerol production relies on grassy oil crops or other woody oil plants, representing more than 120 million metric tons every year. Considering that the worldwide triacylglycerol demand is expected to rise in the future, alternative routes are necessary to ensure a sustainable biodiesel industry and limit diesel price volatility. In this context, the use of animal fats could be an interesting alternative for biodiesel production as the production of animal byproducts represents nearly 17 million tons per year in the European Union only (2020). Animal fats, however, contain large amounts of no-esterified fatty acids and other oxygen compounds, reducing the yield of biodiesel. Therefore, a specific pretreatment is needed before the trans-esterification process. The setup of such appropriate pretreatments requires detailed upstream characterization of the minor components present in the feedstock. For this purpose, the minor component profile of animal fat was investigated by comprehensive two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry. This was preceded by an innovative sample fractionation and focalization of these minor components by a preparative liquid chromatographic column method. The overall method permitted to extract different levels of information from the two-dimensional chromatograms, leading to a tentative identification of more than 150 compounds, mainly oxygenated, belonging to different chemical classes

Analysis of mixed plastic pyrolysis oil by comprehensive two-dimensional gas chromatography coupled with low- and high-resolution time-of-flight mass spectrometry with the support of soft ionization

According to the annual production of plastics worldwide, in 2020 about 370 million tons of plastic were pro-duced in the world. Chemical recycling, particularly pyrolysis of plastic wastes, could be a valuable solution to resolve these problems and provide an alternative pathway to produce "recycled " chemical products for the petrochemical industry. Nevertheless, the pyrolysis oils need a detailed characterization before the upgrading test to re-use them to generate new recycled products. Multidimensional gas chromatography coupled with both low-and high-resolution time-of-flight mass spectrometers was employed for a detailed investigation among and within different chemical classes present in bio-plastic oil. The presence of several isomeric species as well as homologs series did not allow a reliable molecular identification, except for a few compounds that showed both MS similarity &gt; 800/1000 and retention index within &amp; PLUSMN;20. Indeed, the identification of several isomeric species was assessed by high-resolution mass spectrometry equipped with photoionization interface. This soft ionization mode was an additional filter in the identification step allowing unambiguous identification of analytes not identified by the standard electron ionization mode at 70 eV. The injection method was also optimized using a central composite design to successfully introduce a wide range of carbon number compounds without discrimination of low/high boiling points

A benchmarking protocol for breath analysis: The peppermint experiment

Sampling of volatile organic compounds (VOCs) has shown promise for detection of a range of diseases but results have proved hard to replicate due to a lack of standardization. In this work we introduce the 'Peppermint Initiative'. The initiative seeks to disseminate a standardized experiment that allows comparison of breath sampling and data analysis methods. Further, it seeks to share a set of benchmark values for the measurement of VOCs in breath. Pilot data are presented to illustrate the standardized approach to the interpretation of results obtained from the Peppermint experiment. This pilot study was conducted to determine the washout profile of peppermint compounds in breath, identify appropriate sampling time points, and formalise the data analysis. Five and ten participants were recruited to undertake a standardized intervention by ingesting a peppermint oil capsule that engenders a predictable and controlled change in the VOC profile in exhaled breath. After collecting a pre-ingestion breath sample, five further samples are taken at 2, 4, 6, 8, and 10 h after ingestion. Samples were analysed using ion mobility spectrometry coupled to multi-capillary column and thermal desorption gas chromatography mass spectrometry. A regression analysis of the washout data was used to determine sampling times for the final peppermint protocol, and the time for the compound measurement to return to baseline levels was selected as a benchmark value. A measure of the quality of the data generated from a given technique is proposed by comparing data fidelity. This study protocol has been used for all subsequent measurements by the Peppermint Consortium (16 partners from seven countries). So far 1200 breath samples from 200 participants using a range of sampling and analytical techniques have been collected. The data from the consortium will be disseminated in subsequent technical notes focussing on results from individual platforms