Development of a Gas Chromatography-Time-of-Flight Method for Detecting Glucosinolate Metabolites and Volatile Organic Compounds in Kimchi.
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ABSTRACT:
SUBMITTER: Kim HJ
PROVIDER: S-EPMC8233085 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Volatile organic compounds (VOCs) are byproducts from metabolic pathways that can be detected in exhaled breath and have been reported as biomarkers for different diseases. The gold standard for analysis is gas chromatography-mass spectrometry (GC-MS), which can be coupled with various sampling methods. The current study aims to develop and compare different methods for sampling and preconcentrating VOCs using solid-phase microextraction (SPME). An in-house sampling method, direct-breath SPME (DB-SPME), was developed to directly extract VOCs from breath using a SPME fiber. The method was optimized by exploring different SPME types, the overall exhalation volume, and breath fractionation. DB-SPME was quantitatively compared to two alternative methods involving the collection of breath in a Tedlar bag. In one method, VOCs were directly extracted from the Tedlar bag (Tedlar-SPME) and in the other, the VOCs were cryothermally transferred from the Tedlar bag to a headspace vial (cryotransfer). The methods were verified and quantitatively compared using breath samples (n = 15 for each method respectively) analyzed by GC-MS quadrupole time-of-flight (QTOF) for compounds including but not limited to acetone, isoprene, toluene, limonene, and pinene. The cryotransfer method was the most sensitive, demonstrating the strongest signal for the majority of the VOCs detected in the exhaled breath samples. However, VOCs with low molecular weights, including acetone and isoprene, were detected with the highest sensitivity using the Tedlar-SPME. On the other hand, the DB-SPME was less sensitive, although it was rapid and had the lowest background GC-MS signal. Overall, the three breath-sampling methods can detect a wide variety of VOCs in breath. The cryotransfer method may be optimal when collecting a large number of samples using Tedlar bags, as it allows the long-term storage of VOCs at low temperatures (-80 °C), while Tedlar-SPME may be more effective when targeting relatively small VOCs. The DB-SPME method may be the most efficient when more immediate analyses and results are required.
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Project description:BackgroundNon-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer.MethodsTo investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxen-polydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 50°C for 60 min using samples with high ionic strengths (17% sodium chloride, w v(-1)) and under agitation.ResultsA total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (P<0.05). A significant increase in the peak area of 2-methyl-3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients.ConclusionsGas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved.
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Project description:BackgroundA needle trap device (NTD) was packed with Carbotrap/silica composite sorbent and applied for field sampling of halogenated volatile organic compounds (HVOCs) followed by gas chromatography/mass spectrometry (GC/MS) separation and determination.MethodsCarbotrap B, as a highly pure surface sorbent, was prepared using sol-gel method to improve its surface properties for adsorption/desorption of the target analytes. The effects of important experimental variables on the sampling and determination of trichloroethylene (thrCE) and tetrachloroethylene (tetCE) using the proposed NTD-GC/MS strategy were evaluated and optimized.ResultsThe results showed that sampling temperature and relative humidity interfered with sampling efficiency of the developed method and peak area responses of the analytes decreased with increasing temperature and relative humidity. The peak areas of the analytes increased with raising desorption temperature from 180 to 250 °C, and increasing desorption time from 1 to 3 min. The carryover experiments showed that the carryover effect disappeared after 3 min of desorption time. The Limits of Detection (LODs) and Limits of Quantitation (LOQs) of the analytes were in the range 0.01-0.03 and 0.05-0.09, respectively.ConclusionsThe results indicated that the developed NTD-GC/MS procedure can be used as a technology with high sensitivity for the field sampling and determination of HVOCs.
| S-EPMC6985406 | biostudies-literature
Project description:IntroductionHeadspace gas chromatography-mass spectrometry (HS-GC-MS) is widely considered the gold standard of quantitative fecal VOC analysis. However, guidelines providing general recommendations for bioanalytical method application in research and clinical setting are lacking.ObjectivesTo propose an evidence-based research protocol for fecal VOC analysis by HS-GC-MS, based on extensive testing of instrumental and sampling conditions on detection and quantification limits, linearity, accuracy and repeatability of VOC outcome.MethodsThe influence of the following variables were assessed: addition of different salt solutions, injection temperature, injection speed, injection volume, septum use, use of calibration curves and fecal sample mass. Ultimately, the optimal sample preparation was assessed using fecal samples from healthy preterm infants. Fecal VOC analysis in this specific population has potential as diagnostic biomarkers, but available amount of feces is limited here, so optimization of VOC extraction is of importance.ResultsWe demonstrated that addition of lithium chloride enhanced the release of polar compounds (e.g. small alcohols) into the headspace. Second, a linear relationship between injection volume, speed and temperature, and fecal sample mass on the abundance of VOC was demonstrated. Furthermore, the use of a septum preserved 90% of the non-polar compounds. By application of optimal instrumental and sampling conditions, a maximum of 320 unique compounds consisting of 14 different chemical classes could be detected.ConclusionsThese findings may contribute to standardized analysis of fecal VOC by HS-GC-MS, facilitating future application of fecal VOC in clinical practice.
| S-EPMC7547966 | biostudies-literature