GC-FID-MS Based Metabolomics to Access Plum Brandy Quality.

Plum brandy (Slivovitz (en); Sljivovica(sr)) is an alcoholic beverage that is increasingly consumed all over the world. Its quality assessment has become of great importance. In our study, the main volatiles and aroma compounds of 108 non-aged plum brandies originating from three plum cultivars, and fermented using different conditions, were investigated. The chemical profiles obtained after two-step GC-FID-MS analysis were subjected to multivariate data analysis to reveal the peculiarity in different cultivars and fermentation process. Correlation of plum brandy chemical composition with its sensory characteristics obtained by expert commission was also performed. The utilization of PCA and OPLS-DA multivariate analysis methods on GC-FID-MS, enabled discrimination of brandy samples based on differences in plum varieties, pH of plum mash, and addition of selected yeast or enzymes during fermentation. The correlation of brandy GC-FID-MS profiles with their sensory properties was achieved by OPLS multivariate analysis. Proposed workflow confirmed the potential of GC-FID-MS in combination with multivariate data analysis that can be applied to assess the plum brandy quality.

Interpretation of omics data analyses.

Omics studies attempt to extract meaningful messages from large-scale and high-dimensional data sets by treating the data sets as a whole. The concept of treating data sets as a whole is important in every step of the data-handling procedures: the pre-processing step of data records, the step of statistical analyses and machine learning, translation of the outputs into human natural perceptions, and acceptance of the messages with uncertainty. In the pre-processing, the method by which to control the data quality and batch effects are discussed. For the main analyses, the approaches are divided into two types and their basic concepts are discussed. The first type is the evaluation of many items individually, followed by interpretation of individual items in the context of multiple testing and combination. The second type is the extraction of fewer important aspects from the whole data records. The outputs of the main analyses are translated into natural languages with techniques, such as annotation and ontology. The other technique for making the outputs perceptible is visualization. At the end of this review, one of the most important issues in the interpretation of omics data analyses is discussed. Omics studies have a large amount of information in their data sets, and every approach reveals only a very restricted aspect of the whole data sets. The understandable messages from these studies have unavoidable uncertainty.

[Examination of Analytical Methods for Methanol, Trichloroethylene, and Tetrachloroethylene to Revise the Official Methods Based on the Act on the Control of Household Products Containing Harmful Substances].

In Japan, the use of methanol, trichloroethylene, and tetrachloroethylene in aerosol household products is banned under the Act on the Control of Household Products Containing Harmful Substances. As the official analytical methods for testing for these substances have not been revised for over 35 years, several issues have been pointed out. Thus, we developed a new method to revise the official method in our previous study. In this study, validation of the proposed method for detecting the target substances was conducted using two aerosol-product samples (A and B), which contained methanol, trichloroethylene, and tetrachloroethylene. Sample A comprised regulated values of these compounds, while sample B comprised one-tenth of the regulated amounts. They also contained several volatile compounds that served as interfering substances. Subsequently, the samples were analyzed using head space/gas chromatography-mass spectrometry, and it was confirmed that the three target substances were separated from the other chemicals on chromatograms. Validation tests were conducted at seven laboratories to evaluate the proposed method using the prepared samples. In one laboratory, the recovery of trichloroethylene and tetrachloroethylene in sample B was slightly higher at 120%, while the recoveries obtained from the other tests were between 70% and 120%. Relative standard deviation at each laboratory was less than 10%. Furthermore, the relative standard deviations between the validation tests with respect to each chemical were less than 15%. Therefore, the method validated in this study was considered to be effective as a revised method for testing for methanol, trichloroethylene, and trichloroethylene in household aerosol products.

Unraveling the chemosensory characteristics of strong-aroma type Baijiu from different regions using comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry and descriptive sensory analysis.

Comprehensive 2D gas chromatography-time-of-flight mass spectrometry was combined with descriptive sensory analysis to elucidate the specificity of strong-aroma type Baijiu (Chinese liquor) from different regions, based on regionally distinct flavor characterized by chemical and sensory profiles. Numerous potential aroma compounds (262) were identified, among which 58 aroma compounds were significantly different between the samples from Sichuan and Jianghuai regions. Relationships between these potential aroma compounds and sensory attributes were investigated by partial least squares regression and network analysis. The compounds that dominantly contributed to the important sensory attributes were identified. The high pyrazines, furanoids, and carbonyls amounts contributed to the high intensities of the cellar, toasted, and grain aroma profiles of the Sichuan region samples, while the high ester and alcohol levels contributed to the fruity and floral aroma profiles of the Jianghuai region samples. This approach may have practical application in flavor characterization of other alcoholic beverages.

Discrimination of Cultivated Regions of Soybeans (Glycine max) Based on Multivariate Data Analysis of Volatile Metabolite Profiles.

Soybean (Glycine max) is a major crop cultivated in various regions and consumed globally. The formation of volatile compounds in soybeans is influenced by the cultivar as well as environmental factors, such as the climate and soil in the cultivation areas. This study used gas chromatography-mass spectrometry (GC-MS) combined by headspace solid-phase microextraction (HS-SPME) to analyze the volatile compounds of soybeans cultivated in Korea, China, and North America. The multivariate data analysis of partial least square-discriminant analysis (PLS-DA), and hierarchical clustering analysis (HCA) were then applied to GC-MS data sets. The soybeans could be clearly discriminated according to their geographical origins on the PLS-DA score plot. In particular, 25 volatile compounds, including terpenes (limonene, myrcene), esters (ethyl hexanoate, butyl butanoate, butyl prop-2-enoate, butyl acetate, butyl propanoate), aldehydes (nonanal, heptanal, (E)-hex-2-enal, (E)-hept-2-enal, acetaldehyde) were main contributors to the discrimination of soybeans cultivated in China from those cultivated in other regions in the PLS-DA score plot. On the other hand, 15 volatile compounds, such as 2-ethylhexan-1-ol, 2,5-dimethylhexan-2-ol, octanal, and heptanal, were related to Korean soybeans located on the negative PLS 2 axis, whereas 12 volatile compounds, such as oct-1-en-3-ol, heptan-4-ol, butyl butanoate, and butyl acetate, were responsible for North American soybeans. However, the multivariate statistical analysis (PLS-DA) was not able to clearly distinguish soybeans cultivated in Korea, except for those from the Gyeonggi and Kyeongsangbuk provinces.

Untargeted and targeted metabolomics strategy for the classification of strong aroma-type baijiu (liquor) according to geographical origin using comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry.

A metabolomics strategy was developed to differentiate strong aroma-type baijiu (SAB) (distilled liquor) from the Sichuan basin (SCB) and Yangtze-Huaihe River Basin (YHRB) through liquid-liquid extraction coupled with GC×GC-TOFMS. PCA effectively separated the samples from these two regions. The PLS-DA training model was excellent, with explained variation and predictive capability values of 0.988 and 0.982, respectively. As a result, the model demonstrated its ability to perfectly differentiate all the unknown SAB samples. Twenty-nine potential markers were located by variable importance in projection values, and twenty-four of them were identified and quantitated. Discrimination ability is closely correlated to the characteristic flavor compounds, such as acid, esters, furans, alcohols, sulfides and pyrazine. Most of the marker compounds were less abundant in the SCB samples than in the YHRB samples. The quantitated markers were further processed using hierarchical cluster analysis for targeted analysis, indicating that the markers had great discrimination power to differentiate the SAB samples.

Targeted toxicometabolomics of endosulfan sulfate in adult zebrafish (Danio rerio) using GC-MS/MS in multiple reaction monitoring mode.

Endosulfan sulfate is a major oxidative metabolite of the chlorinated insecticide endosulfan. In this study, a targeted metabolomics approach was used to investigate the toxic mechanisms of endosulfan sulfate in adult zebrafish using the multiple reaction monitoring mode of a GC-MS/MS. The LC50 of endosulfan sulfate in adult zebrafish was determined and then zebrafish were exposed to endosulfan sulfate at one-tenth the LC50 (0.1LC50) or the LC50 for 24 and 48 h. After exposure, the fish were extracted, derivatized and analyzed by GC-MS/MS for 379 metabolites to identify 170 metabolites. Three experimental groups (control, 0.1LC50 and LC50) were clearly separated in PLS-DA score plots. Based on the VIP, ANOVA, and fold change results, 40 metabolites were selected as biomarkers. Metabolic pathways associated with those metabolites were identified using MetaboAnalyst 4.0 as follows: aminoacyl-tRNA biosynthesis, valine/leucine/isoleucine biosynthesis, citrate cycle, glycerolipid metabolism, and arginine/proline metabolism. Gene expression studies confirmed the activation of citrate cycle and glycerolipids metabolism. MDA levels of the exposed group significantly increased in oxidative toxicity assay tests. Such significant perturbations of important metabolites within key biochemical pathways must result in biologically hazardous effects in zebrafish.

Chemical typicality of South American red wines classified according to their volatile and phenolic compounds using multivariate analysis.

In this study, 83 wines representating four commercial categories: "Argentinean Malbec", "Brazilian Merlot", "Uruguayan Tannat" and "Chilean Carménère" were analyzed according to their phenolic and volatile compounds. The objective was to identify the chemical compounds that would typify each category. From approximately about 600 peaks obtained by chromatographic techniques, 169 were identified and 53 of them were selected for multivariate statistical analysis. Chilean Carménère was the best discriminated group by the methods applied in our study, followed by Argentinean Malbec. Brazilian Merlot mixed mainly with some Carménère, whileTannat mixed with all wines categories, especially Malbec. In general, Chilean Carménère wines can be characterized by a bluish color, higher amounts of sulphur dioxide, higher content of octanoic acid, isobutanol, ethyl isoamyl succinate and catechin and a smaller amount of quercetin. These data can contribute for further process of authenticity or typification of South American red wines.

ADAP-GC 4.0: Application of Clustering-Assisted Multivariate Curve Resolution to Spectral Deconvolution of Gas Chromatography-Mass Spectrometry Metabolomics Data.

We report a multivariate curve resolution (MCR)-based spectral deconvolution workflow for untargeted gas chromatography-mass spectrometry metabolomics. As an essential step in preprocessing such data, spectral deconvolution computationally separates ions that are in the same mass spectrum but belong to coeluting compounds that are not resolved completely by chromatography. As a result of this computational separation, spectral deconvolution produces pure fragmentation mass spectra. Traditionally, spectral deconvolution has been achieved by using a model peak approach. We describe the fundamental differences between the model peak-based and the MCR-based spectral deconvolution and report ADAP-GC 4.0 that employs the latter approach while overcoming the associated computational complexity. ADAP-GC 4.0 has been evaluated using GC-TOF data sets from a 27-standards mixture at different dilutions and urine with the mixture spiked in, and GC Orbitrap data sets from mixtures of different standards. It produced the average matching scores 960, 959, and 926 respectively. Moreover, its performance has been compared against MS-DIAL, eRah, and ADAP-GC 3.2, and ADAP-GC 4.0 demonstrated a higher number of matched compounds and up to 6% increase of the average matching score.

Performance Evaluation of a Nontargeted Platform Using Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry Integrating Computer-Assisted Structure Identification and Automated Semiquantification for the Comprehensive Chemical Characterization of a Complex Matrix.

Nontargeted screening methodologies are powerful approaches for comprehensive chemical characterization of complex matrixes. In order to maximize chemical space coverage, three analytical methods using two-dimensional gas chromatography with time-of-flight mass spectrometry for nonpolar, polar, and volatile compounds have been established. The structural identification process was streamlined with an in-house developed computer-assisted structure identification platform, which facilitated the identification of novel compounds and also delivered semiquantitative concentrations for all compounds. Key performance parameters for this nontargeted platform, including chemical space coverage, confidence for structural identification, accuracy of semiquantification, and performance of differential analysis, were evaluated. The automated structural identification process was assessed using a subset of 243 compounds (out of 2990), which were confirmed to be present in cigarette smoke using reference standards. Consistently high true positive identification rates between 88.2% and 96.2% across the different concentration ranges investigated were demonstrated. Accuracy for semiquantification was assessed by comparison with quantitative data from literature, where a maximum 4-fold deviation from available targeted analysis values was estimated.

Characterization of the oral breakdown, sensory properties, and volatile release during mastication of white bread.

The oral breakdown, sensory properties, and volatile release during mastication of white bread were investigated. The results of correlation analysis for white bread's physical properties and it's oral physiological parameters during chewing have elucidated that bread's physical properties determined the oral processing behavior. During chewing of white bread, 15 dominant ions with regularly changing patterns were monitored by proton transfer reaction-mass spectrometry (PTR-MS). These dominant ions derived from 32 volatile compounds were further confirmed by pure standards. Partial least squares regression (PLSR) analysis was used to explore the positive correlations between the sensory analysis and the dominant aroma compounds. Results have shown that 9 aroma compounds were predicted as the potent odorants contributing to the changes in aroma profiles. Finally, 3-hydroxy-2-butanone, 2-methyl-1-propanol, and heptanoic acid were confirmed as the key aroma compounds contributing to the changes in aroma profiles of white bread before and after chewing.

Analysis and determination of phytosterols and triterpenes in different inbred lines of Djulis (Chenopodium formosanum Koidz.) hull: A potential source of novel bioactive ingredients.

Djulis (Chenopodiun formosaneum Koidz.,), pseudo-cereal crop emerged as a potential source of functional ingredients, was used to identify phytosterols and triterpenes from seven inbred lines of Djulis hull using GC-MS. Key bioactive compounds were identified including 6 phytosterols (34.73-59.48 mg/100 g), 6 triterpenes (30.56-57.47 mg/100 g), and 5 other unsaponifiable compounds (15.89-22.50 mg/100 g). Moreover, principal component analysis (PCA) was conducted and explored the variation among Djulis hull samples with two clusters based on the surface color that reflected the content of phytosterols and triterpenes. These results confirmed that the color might be used as an indicator for estimation of phytosterol and triterpene contents in Djulis hull. Overall, this is the first study that identified novel unsaponifiable compounds in Djulis hull, which might contribute to the development of phytosterols and/or triterpenes enriched functional foods.

Application of different chromatographic techniques and chemometric analysis in authenticity testing of plant protection products containing azoxystrobin as an active substance.

Azoxystrobin (methyl(2E)-2-{2-[6-(2-cyanophenoxy)pyrimidin-4-yloxy] phenyl}-3-methoxyacrylate) is an active ingredient used to protect crops against fungal diseases. The experience of the Polish control laboratory indicates relatively frequent cases of counterfeit plant protection products (PPPs) containing this active substance. The present study aimed to use chemometric methods to model chemical fingerprints obtained by different chromatographic techniques to verify the original formulation of PPPs containing the active substance azoxystrobin. The pesticides used in the study came from different sources (including stores and warehouses), were manufactured at a different time and came from different production batches. The results obtained with the HPLC-DAD and HS-GC-MS techniques were then modeled using principal component analysis (PCA) and soft independent modeling by class analogy (SIMCA) classifier. The proposed approach has been confirmed as useful for verifying the authenticity of PPPs and can be used in the routine control testing of SC pesticides containing azoxystrobin.

An integration of UPLC-DAD/ESI-Q-TOF MS, GC-MS, and PCA analysis for quality evaluation and identification of cultivars of Chrysanthemi Flos (Juhua).

BACKGROUND: Chrysanthemi Flos (CF), as a popular traditional Chinese medicine (TCM), has five main cultivars in China, namely "Chuju", "Boju", "Gongju", "Huaiju" and "Hangju". Due to their habitats and processing methods, great quality variations occur yet no systematical study has ever been carried out to evaluate such variations. PURPOSE: In this study, we aim to establish a new approach that can serve both as a quality control method and as an identification method for cultivars of CF. METHOD: The components in CF samples were identified by a combination of UPLC-ESI-Q-TOF/MS and GC/MS. Furthermore, a multimodal quantitative method was established by UPLC-UV coupled with principal component analysis (PCA) and the similarity evaluation system (SES), which was used to control and identify four cultivars of CF. RESULTS: 18 compounds of flavonoids and caffeoylquinic acids were identified and ten of them were quantified using UPLC-ESI-Q-TOF/MS. Different cultivars of CF could be clearly distinguished with the fingerprints evaluation and principal component analysis (PCA). A total of 74 volatile compounds were detected by GC/MS. The distinctness of volatile components was observed. By the combination of UPLC-ESI-Q-TOF/MS and GC/MS, an identification and quality control method for CF was successfully established. CONCLUSION: The combination of UPLC-ESI-Q-TOF/MS and GC/MS could act as a comprehensive multimodal method for both identification and quality control of herbal medicines. This study provided new insights into the overall evaluation method for herbal medicines possessing different cultivars.

HS-SPME-GC-MS/olfactometry combined with chemometrics to assess the impact of germination on flavor attributes of chickpea, lentil, and yellow pea flours.

In this study, volatile component changes of germinated chickpea, lentil, and yellow pea flours over the course of 6 days germination were characterized by HS-SPME-GC-MS/O. In total, 124 volatile components were identified involving 19 odor active components being recorded by GC-O exclusively. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) revealed that lentil and yellow pea flours had the similar aromatic attributes, while the decrease of beany flavor compounds along with the occurrence of unpleasant flavors was detected in chickpea flours upon germination. Six beany flavor markers, including hexanal, (E,E)-2,4-nonadienal, (E,E)-2,4-decadienal, 3-methyl-1-butanol, 1-hexanol, and 2-pentyl-furan, were employed to quantify beany flavor formation in the flours over the course of germination. The results suggested that no significant beany flavor formation or mitigation was appeared after 1 day of germination. The findings are crucial for tailing pulse germination process to enhance the macronutrients without increasing undesirable beany flavor.

Chemical diversity and anti-proliferative activity of marine algae.

The chemical diversity of three macroalgae (Ulva reticulata, Sargassum wightii, Gracilaria sp) were determined using the GC-MS method with principal component analysis (PCA) and their potential efficacy against human pathogens and cervical carcinoma cells evaluated using MTT bioassay method. Our results showed that >30 metabolites were detected in three seaweeds, among these, steroids and fatty acids are the most dominant chemical group that highly contributes to discriminate this species. The PCA of GC-MS mass spectral variables showed a clear discrimination between three different species based on the phytochemical diversity of seaweeds. The extracts of U. reticulata exhibited anti-microbial activity with Pseudomonas aeruginosa (6.00 mm) and showed potential anti-proliferative activity against the HeLa cells (IC50 37 µmol/L) at concentration 1-50 µM treatment. Results of this study concluded that PCA analysis of mass spectral variables could be utilized as a reliable tool for species discrimination and chemotaxonomic classification of seaweeds.

Evolution of Volatile Compounds and Spoilage Bacteria in Smoked Bacon during Refrigeration Using an E-Nose and GC-MS Combined with Partial Least Squares Regression.

The changes in the concentration of volatile organic compounds (VOCs) and biogenic amines (BAs) in smoked bacon during 45-day refrigerated storage is investigated using solid-phase micro-extraction coupled with gas chromatography-mass spectrometry and high-performance liquid chromatography. In total, 56 VOCs and 6 BAs were identified and quantified. The possible pathways leading to their formation are analyzed and considered as the potential signs of microbial activity, especially by specific spoilage microorganisms (SSOs). Leuconostoc and Lactobacillus, which levels increased markedly with the extension of storage time, were recognized as SSOs. An electronic nose (e-nose) was employed to determine the changes in concentration of the odor components per sample present within half an hour. Partial least squares regression was then carried out to analyze the correlation between SSO growth, metabolite concentration, BA accumulation, and e-nose response. The results show that ten VOCs (ethanol, 2-furanmethanol, 1-hexanol, 1-propanol, phenol, 2-methoxyphenol, acetic acid, 3-ethyl-2-cyclopenten-1-one, furfural, and ethyl hexanoate) and three BAs (putrescine, cadaverine, and tyramine) can be associated with the growth of SSOs. Thus, they can be adopted as potential indicators to evaluate and monitor the quality of the bacon and develop appropriate detection methods. E-noses can used to recognize odors and diagnose quality of bacon.

Validación de un método para cuantificar ácido-11-nor-9-carboxi-delta 9-tetrahidrocannabinol en orina por cromatografía gaseosa-espectrometría de masas previa extracción en fase sólida / Validation of a method for quantify 11-nor-9-carboxy-delta 9-tetrahydrocannabinol in human urine using solid phase extraction and gas chromatography-mass spectrometry

El cannabis es una de las drogas ilegales más usadas a nivel mundial. Su consumo se relaciona con diferentes hechos en el ámbito forense, laboral, deportivo y clínico. Para su detección se utilizan métodos con diferentes fundamentos y alcances (inmunológicos, cromatográficos). En este trabajo se describe un método preciso, reproducible y validado, para la cuantificación del principal metabolito urinario del Δ9-tetrahidrocannabinol, el ácido-11-nor-9-carboxi- Δ 9-tetrahidrocannabinol (THC-COOH), por cromatografía gaseosa-espectrometría de masas (GC-MS). Se efectuó una extracción en fase sólida (SPE) a partir de la orina, previa hidrólisis alcalina. Se utilizó el análogo deuterado (THC-COOH D3) como estándar interno. El análisis por GC-MS se realizó en modo SIM. La curva de calibración fue lineal en el rango de trabajo (10-100 ng/ml, r > 0,999) y el límite de cuantificación fue de 10 ng/ml. La recuperación absoluta estuvo comprendida entre el 91,0 y 99,0 %. La precisión intra e inter ensayo fue de 1,06 a 1,26 y 3,59 a 9,80 %, respectivamente. El método fue aplicado a muestras reales, positivas por test inmunológico, resultando ser muy útil y fiable en el análisis de rutina de THC-COOH en orina humana con fines toxicológicos.

Cannabis is one of the most widely used illegal drug in the world. Its consumption is related to different forensic, work, sports and clinical events. In order to determinate the presence of cannabis, different methods with distinct fundamentals and scopes (immunoassay and chromatography) are applied. This report described an accurate, reproducible, and validated gas chromatography-mass spectrometry (GC-MS) method for the quantitation of 11-nor-9-carboxy- Δ9-tetrahydrocannabinol (THCCOOH), the major metabolite of Δ9-tetrahydrocannabinol in urine. A solid phase extraction (SPE), previous alkaline hydrolysis, was performed on the urine sample. Its deuterated analog (THC-COOH D3) was used as internal standard. The GC-MS analysis made by selected ion monitoring (SIM). Calibration curve was linear over the specified range (10 -100 ng/ml; r > 0.999) and limit of quantitation was 10 ng/ml. Absolute recoveries ranged from 91.0 to 99.0. Intra-assay and inter assay precision ranged from 1.06 to 1.26 and 3.59 to 9.80 %, respectively. The method has been applied to real samples, positive to immunological screening test, resulting to be very useful and reliable in routine analysis of THC-COOH in human urine for toxicological purposes.

Simultaneous quantification of Aroclor mixtures in soil samples by gas chromatography/mass spectrometry with solid phase microextraction using partial least-squares regression.

Multivariate partial least-squares (PLS) method was applied to the quantification of two complex polychlorinated biphenyls (PCBs) commercial mixtures, Aroclor 1254 and 1260, in a soil matrix. PCBs in soil samples were extracted by headspace solid phase microextraction (SPME) and determined by gas chromatography/mass spectrometry (GC/MS). Decachlorinated biphenyl (deca-CB) was used as internal standard. After the baseline correction was applied, four data representations including extracted ion chromatograms (EIC) for Aroclor 1254, EIC for Aroclor 1260, EIC for both Aroclors and two-way data sets were constructed for PLS-1 and PLS-2 calibrations and evaluated with respect to quantitative prediction accuracy. The PLS model was optimized with respect to the number of latent variables using cross validation of the calibration data set. The validation of the method was performed with certified soil samples and real field soil samples and the predicted concentrations for both Aroclors using EIC data sets agreed with the certified values. The linear range of the method was from 10µgkg(-1) to 1000µgkg(-1) for both Aroclor 1254 and 1260 in soil matrices and the detection limit was 4µgkg(-1) for Aroclor 1254 and 6µgkg(-1) for Aroclor 1260. This holistic approach for the determination of mixtures of complex samples has broad application to environmental forensics and modeling.