Differentiating organic and conventional sage by chromatographic and mass spectrometry flow injection fingerprints combined with principal component analysis

Metagenomics and untargeted metabolomics analyses to unravel the formation mechanism of characteristic metabolites in Cantonese soy sauce during different fermentation stages

Cantonese soy sauce (CSS) is an important Chinese condiment due to its distinctive flavor. Microorganisms play a significant role in the flavor formation of CSS during fermentation. However, the correlation between microbes and flavor compounds as well as the potential fermentation mechanism remained poorly uncovered. Here we revealed the dynamic changes of microbial structure and characteristics metabolites as well as their correlation of CSS during the fermentation process. Metagenomics sequencing analysis showed that Tetragenococcus halophilus, Weissella confusa, Weissella paramesenteroides, Aspergillus oryzae, Lactiplantibacillus plantarum, Weissella cibaria were top six dominant species from day 0 to day 120. Sixty compounds were either positively or tentatively identified through untargeted metabolomics profile and they were 27 peptides, amino acids and derivatives, 8 carbohydrates and conjugates, 14 organic acids and derivatives, 5 amide compounds, 3 flavonoids and 3 nucleosides. Spearman correlation coefficient indicated that Tetragenococcus halophilus, Zygosaccharomyces rouxii, Pediococcus pentosaceus and Aspergillus oryzae were significantly related with the formation of taste amino acids and derivatives, peptides and functional substances. Additionally, the metabolisms of flavor amino acids including 13 main free amino acids were also profiled. These results provided valuable information for the production practice in the soy sauce industry.

Integrative analysis of the effects of organic and conventional farming methods on peanut based on transcriptome and metabolomics

To elucidate the nutritional quality of peanut under different farming methods, we selected two cultivars, "jihua13" and "jihua4", to grow in organic and conventional environments, respectively. After harvest, we measured physiological parameters and differential metabolites. Metabolomics showed that most of the amino acids, carbohydrates, and secondary metabolites in organically grown jihua4 were downregulated, which was completely the opposite in jihua13. Fatty acids associated with heart disease and hypertension are reduced in organically grown peanuts. In particular, the highly statistically significant tryptophan betaine seems to be used as a reference to distinguish between organic and conventional cultivation. Mechanisms leading to differences in crop chemical composition are explained by transcriptome analysis. The results of the transcriptome analysis indicated that organic cultivation largely affects the synthesis of amino acids and carbohydrates in jihua13. Combined analysis of transcriptome and metabolomics found that variety jihua13 is more sensitive to farming methods and produces more unsaturated fatty acids than jihua4.

Ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry based untargeted metabolomics to reveal the characteristics of Dictyophora rubrovolvata from different drying methods

Dictyophora rubrovolvata is a highly valuable and economically important edible fungus whose nutrition and flavor components may vary based on drying methods. Herein, an untargeted ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) metabolomics method combined with multivariate analysis was first performed to characterize the metabolomics profiles of D. rubrovolvata upon different drying treatments, viz., coal burning drying (CD), electrothermal hot air drying (ED), and freeze drying (FD). The results indicated that 69 differential metabolites were identified, vastly involving lipids, amino acids, nucleotides, organic acids, carbohydrates, and their derivatives, of which 13 compounds were confirmed as biomarkers in response to diverse drying treatments. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis illustrated that differential metabolites were significantly assigned to 59, 55, and 60 pathways of CD vs. ED, CD vs. FD, and FD vs. ED groups, respectively, with 9 of the top 20 KEGG pathways shared. Specifically, most of lipids, such as fatty acyls, glycerophospholipids and sphingolipids, achieved the highest levels in D. rubrovolvata after the CD treatment. ED method substantially enhanced the contents of sterol lipids, nucleotides, organic acids and carbohydrates, while the levels of amino acids, prenol lipids and glycerolipids were elevated dramatically against the FD treatment. Collectively, this study shed light on metabolomic profiles and proposed biomarkers of D. rubrovolvata subjected to multiple drying techniques, which may contribute to quality control and drying efficiency in edible fungi production.

Mass Spectrometry-Based Nontargeted and Targeted Analytical Approaches in Fingerprinting and Metabolomics of Food and Agricultural Research

Mass spectrometry (MS)-based techniques have been extensively applied in food and agricultural research. This review aims to address the advances and applications of MS-based analytical strategies in nontargeted and targeted analysis and summarizes the recent publications of MS-based techniques, including flow injection MS fingerprinting, chromatography-tandem MS metabolomics, direct analysis using ambient mass spectrometry, as well as development in MS data deconvolution software packages and databases for metabolomic studies. Various nontargeted and targeted approaches are employed in marker compounds identification, material adulteration detection, and the analysis of specific classes of secondary metabolites. In the newly emerged applications, the recent advances in computer tools for the fast deconvolution of MS data in targeted secondary metabolite analysis are highlighted.

Quality changes and deterioration mechanisms in three parts (belly, dorsal and tail muscle) of tilapia fillets during partial freezing storage

The quality changes in tilapia belly muscle (BM), dorsal muscle (DM) and tail muscle (TM) were studied and the hypothesis of browning of the fillets was revealed during partial freezing. Compared with DM and TM groups, BM samples had higher thiobarbituric acid reactive substances (TBARS) (0.41 mg malondialdehyde eq/kg at 49 d) and K values (61.81% at 42 d) (P < 0.05). The microstructure of the BM group deteriorated most obviously during storage. Therefore, the BM group was considered to be the fastest to oxidize and deteriorate. In addition, 54 different micromolecular metabolites were identified from tilapia fillets by UHPLC-Q-TOF-MS analysis, and there were significant differences in the micromolecular metabolites in the three parts of tilapia. Therefore, proteins and lipids were degraded by the action of enzymes and microorganisms to produce some amines and small molecular acids, leading to the deterioration of the quality of tilapia fillets.

Effects of enzymolysis and fermentation on the antioxidant activity and functional components of a coarse cereal compound powder based on principal component analysis and microstructure study

Abstract

In this study, a coarse cereal compound powder (CCCP) was prepared through enzymolysis, fermentation, and joint treatment with 10 coarse cereal types as raw materials. Using 10 evaluation indices, namely the scavenging capacity of 1,1‐diphenyl‐2‐picrylhydrazyl (DPPH•), 2,2′‐azino‐bis‐(3‐ethylbenzthiazoline‐6‐sulfonic acid) (ABTS⁺), hydroxyl (OH•) and superoxide anion (O₂^–), the Fe²⁺ chelating capacity, the content of anthocyanin, flavone, soluble dietary fiber, reducing sugar and protein, antioxidant activity, and functional components of CCCP prepared by different methods were compared. Principal component analysis (PCA) was performed to establish a quality evaluation model of CCCP. Then, the effects of different treatments on the microstructure of CCCP were investigated. Two principal components (PCs) were extracted from PCA, with a cumulative contribution rate of 97.014%. In addition, the analysis of thermodynamic properties indicated that the initial gelatinization temperature of CCCP decreased after enzymolysis and fermentation and that it was easier to gelatinize. Particle size analyses revealed that different treatments could reduce the sample particles to different degrees. The average particle size in the three study groups decreased. Scanning electron microscopy (SEM) revealed that after different treatments, the samples were destroyed to different extents, which facilitated easy dissolution of active substances. Fourier‐transformed‐infrared spectroscopy (FTIR) revealed that the changes of CCCP functional groups after fermentation and joint treatment were more significant than those after enzymolysis.

Practical Application

In this study, enzymolysis and fermentation techniques were used to improve the antioxidant activity and functional components of CCCP, and the effects of different treatments on the microstructure of CCCP were investigated. The bioavailability and nutrient composition of CCCP could be significantly improved by pretreatment, provide useful reference for the development of beneficial ingredients in cereal meal products and the application of different pretreatment methods.

FIA-HRMS fingerprinting subjected to chemometrics as a valuable tool to address food classification and authentication: Application to red wine, paprika, and vegetable oil samples

The rise of food fraud practices, affecting a wide variety of goods and their specific characteristics (e.g., quality or geographical origin), demands rapid high-throughput analytical approaches to ensure consumers protection. In this context, this study assesses flow injection analysis coupled to high-resolution mass spectrometry (FIA-HRMS), using a fingerprinting approach and combined with chemometrics, to address four food authentication issues: (i) the geographical origin of three Spanish red wines, (ii) the geographical origin of three European paprikas, (iii) the distinction of olive oil from other vegetable oils and (iv) the assessment of its quality category. In each case, negative and positive ionisation FIA-HRMS fingerprints, and two different data fusion strategies, were evaluated. After external validation, excellent classification accuracies were reached. Moreover, high-resolution mass spectrometry (HRMS) allowed sample matrices characterisation by the putative identification of the most common ions.

Effects of Paired Associative Stimulation on Metabolites in Ischemia Stroke Rats Model as Studied by Nuclear Magnetic Resonance Spectrum

Paired associated stimulation (PAS) has been confirmed to play a role in motor recovery after stroke, but the underlying mechanism has not been fully elucidated. In this study, we employed a comprehensive battery of measurements, including behavioral test, electrophysiology and 1H-NMR approaches, to investigate the therapeutic effects of PAS in rat model of cerebral ischemia and its underlying mechanism. Rats were randomly divided into a transient middle cerebral artery occlusion group (tMCAO group), a tMCAO + PAS group (PAS group), and a sham group. PAS was applied over 7 consecutive days in PAS group. The behavioral function of rats was evaluated by modified Garcia Scores and Rota-rod test. Electrophysiological changes were measured by motor evoked potentials (MEP). Metabolic changes of ischemic penumbra were detected by 1H-NMR. After PAS intervention, the performances on Rota-rod test and Garcia test improved and the amplitude of MEP increased significantly. The gamma-aminobutyric acid (GABA) in penumbra cortex was decreased significantly, whereas the glutamate showed the opposite changes. The results suggested that post-stroke recovery promoted by PAS may be related to the metabolites alteration in ischemic penumbra and also regulate the excitability of motor cortex.

Application of UHPLC-Q-TOF-MS/MS metabolomics approach to investigate the taste and nutrition changes in tilapia fillets treated with different thermal processing methods

Thermal processing is a common processing method for tilapia which has an important impact on the quality and characteristics of fish meat. This study aimed to investigate changes in the metabolites of tilapia fillets after thermal processing. In this work, we used a UHPLC-Q-TOF-MS/MS metabolomics method to identify and screen differential metabolites. A total of 249 metabolites were identified from tilapia fillet samples, 24, 29 and 24 differential metabolites were screened from steaming/raw, boiling/raw and air frying/raw groups, respectively. Thermal processing significantly changed the quality of tilapia fillets, and the contribution of amino acids, phospholipids and nucleotides to different metabolites was large and had important impacts on the taste and nutrition of tilapia fillets. Metabolomics is an effective method for quality detection of thermal processing in aquatic products. This study provides the theoretical basis for the selection of optimized processing methods for tilapia.

Detection of the effects of triclosan (TCS) on the metabolism of VOCs in HepG2 cells by SPI-TOFMS

Volatile organic compounds (VOCs) emitted by organisms and cell metabolism have demonstrated great physiological and pathological values. At present, there is a great interest in the study of volatile metabolome to determine whether VOCs can serve as potential diagnostic biomarkers. In view of the sensitivity of VOCs to physiological changes, the aim of this study was to investigate alterations in VOC profiles in the in vitro headspace of HepG2 cells after exposure to triclosan (TCS). Since the in vivo biological effects of TCS are clearly defined, several TCS-related VOCs may potentially be traced back to common cellular processes. In this study, HepG2 cells were cultured in TCS-containing medium for 2 h, and the emitted VOCs in the headspace of the culture flask were detected using a single photon ionization time-of-flight mass spectrometry instrument. The control group and the TCS-treated group could be well separated by differential VOC profiles, which were related to the physiological states of the HepG2 cells. Compared to the control group, eleven and ten specific VOCs were identified in the 20 μm and 50 μm TCS-treated groups, respectively. Among them, five specific VOCs (m/z 62, 64, 70, 121 and 146) were commonly observed in these two TCS-treated groups. These results indicate that TCS can cause changes in cellular metabolic VOCs, and different concentrations of TCS lead to different VOCs profiles. Based on the findings of the study, the detection of VOCs in cell metabolism can be used as an auxiliary tool to explore the mechanism of drug action, and also as an exploratory method to determine whether drugs play a role in disease treatment.

The mechanism for improving the flesh quality of grass carp (Ctenopharyngodon idella) following the micro-flowing water treatment using a UPLC-QTOF/MS based metabolomics method

The micro-flowing water system can improve the flesh quality of freshwater fish using the traditional pond farming method. However, the mechanism of this phenomenon has not yet been explored. This study intends to examine the changes of metabolites in freshwater fish after treatment with the micro-flowing purification system (MFPS). The UPLC-QTOF/MS based metabolomics method was utilized to screen the metabolites and predict the major possible metabolic pathways after MFPS treatment. There were 377 types of metabolites identified in the fish muscle, of which 54-71 represented significant different metabolites identified during different stages of MFPS treatments. The main mechanism of MFPS treatment in improving the quality of grass carp fish muscle was investigated, and the MFPS treatment was shown to improve the flesh quality and the flavor of grass carp fish muscle. This study could provide the theoretical basis for improving the quality of aquatic products.

Multivariate classification of the geographic origin of Chinese cabbage using an electronic nose-mass spectrometry

An electronic nose-mass spectrometry (EN-MS) that profiles volatile compounds is a candidate device for identifying the geographic origin of cultivation of agricultural products when an adequate algorithm is derived. The objectives of this study were to apply two types of multivariate analysis, discriminant function analysis (DFA) and principal component analysis (PCA), to the volatile compounds detected by an EN-MS for the geographic classification of Chinese cabbage cultivated in Korea (42 samples) or in China (29 samples). DFA showed that Chinese cabbage from Korea were completely separable from those originating in China with 12 volatile compounds among the 151 detected. PCA revealed that Chinese cabbage data fell into two completely separable origins of Korea and China. This is the first study involving EN-MS data of volatile compounds with multivariate statistics to discriminate the geographical origin of Chinese cabbage, with further applications for other agricultural products.

Comparative evaluation of different cultivars of Flos Chrysanthemi by an anti-inflammatory-based NF-κB reporter gene assay coupled to UPLC-Q/TOF MS with PCA and ANN

ETHNOPHARMACOLOGICAL RELEVANCE

Flos Chrysanthemi (FC), a commonly used traditional Chinese medicine, has five major cultivars ("Boju", "Chuju", "Gongju", "Hangbaiju" and "Huaiju") from different sources. However, the active constituents of these cultivars have not been studied or characterized with respect to their bioactivity, which is a serious problem when considering quality and safety.

AIM OF THE STUDY

To evaluate the differences among the five cultivars of FC, and to establish a method for the standardization and quality control of FC related to its bioactivity.

MATERIALS AND METHODS

In this study, the different ingredients in five cultivars of FC were identified by UPLC-Q/TOF and PCA, and the anti-inflammatory ingredients of FC were predicted and screened by artificial neural network (ANN) and an NF-κB luciferase reporter gene assay system. Using this comprehensive method, we successfully screened the anti-inflammatory markers of different cultivars of FC.

RESULTS

Nineteen marker ingredients were confirmed to contribute strongly to the cluster, and eleven compounds in the five cultivars of FC were found to exert potential anti-inflammatory effects. Among these compounds, the NF-κB inhibitor activity of apigenin-7-O-6″-malonyl-glucoside, luteolin-7-O-rutinoside, quercetin-7-O-galactoside, quercetin-3-O-glucoside, apigenin-7-O-rutinoside and apigenin-7-O-glucoside were first reported here. Chlorogenic acid, luteolin-7-O-glucoside, 3,5-dicaffeoylquinic acid and luteolin were confirmed to be the most important anti-inflammatory marker ingredients useful for the quality control of FC.

CONCLUSIONS

The proposed efficient and systematic method is helpful for the standardization and quality control of FC. Moreover, this comprehensive strategy may prove to be a powerful technique for the rapid establishment of quality control procedures related to bioactivity for other herbal samples and foods.

Characterization of Fatty Acid, Amino Acid and Volatile Compound Compositions and Bioactive Components of Seven Coffee (Coffea robusta) Cultivars Grown in Hainan Province, China

Compositions of fatty acid, amino acids, and volatile compound were investigated in green coffee beans of seven cultivars of Coffearobusta grown in Hainan Province, China. The chlorogenic acids, trigonelline, caffeine, total lipid, and total protein contents as well as color parameters were measured. Chemometric techniques, principal component analysis (PCA), hierarchical cluster analysis (HCA), and analysis of one-way variance (ANOVA) were performed on the complete data set to reveal chemical differences among all cultivars and identify markers characteristic of a particular botanical origin of the coffee. The major fatty acids of coffee were linoleic acid, palmitic acid, oleic acid, and arachic acid. Leucine (0.84 g/100 g DW), lysine (0.63 g/100 g DW), and arginine (0.61 g/100 g DW) were the predominant essential amino acids (EAAs) in the coffee samples. Seventy-nine volatile compounds were identified and semi-quantified by HS-SPME/GC-MS. PCA of the complete data matrix demonstrated that there were significant differences among all cultivars, HCA supported the results of PCA and achieved a satisfactory classification performance.

Differentiating organically and conventionally grown oregano using ultraperformance liquid chromatography mass spectrometry (UPLC-MS), headspace gas chromatography with flame ionization detection (headspace-GC-FID), and flow injection mass spectrum (FIMS) fingerprints combined with multivariate data analysis

Ultraperformance liquid chromatography mass spectrometry (UPLC-MS), flow injection mass spectrometry (FIMS), and headspace gas chromatography (headspace-GC) combined with multivariate data analysis techniques were examined and compared in differentiating organically grown oregano from that grown conventionally. It is the first time that headspace-GC fingerprinting technology is reported in differentiating organically and conventionally grown spice samples. The results also indicated that UPLC-MS, FIMS, and headspace-GC-FID fingerprints with OPLS-DA were able to effectively distinguish oreganos under different growing conditions, whereas with PCA, only FIMS fingerprint could differentiate the organically and conventionally grown oregano samples. UPLC fingerprinting provided detailed information about the chemical composition of oregano with a longer analysis time, whereas FIMS finished a sample analysis within 1 min. On the other hand, headspace GC-FID fingerprinting required no sample pretreatment, suggesting its potential as a high-throughput method in distinguishing organically and conventionally grown oregano samples. In addition, chemical components in oregano were identified by their molecular weight using QTOF-MS and headspace-GC-MS.

Characterisation of organic and conventional sweet basil leaves using chromatographic and flow-injection mass spectrometric (FIMS) fingerprints combined with principal component analysis

Sweet basil, Ocimum basilicum, is one of the most important and wildly used spices and has been shown to have antioxidant, antibacterial, and anti-diarrheal activities. In this study, high performance liquid chromatographic (HPLC) and flow-injection mass spectrometric (FIMS) fingerprinting techniques were used to differentiate organic and conventional sweet basil leaf samples. Principal component analysis (PCA) of the fingerprints indicated that both HPLC and FIMS fingerprints could effectively detect the chemical differences in the organic and conventional sweet basil leaf samples. This study suggested that the organic basil sample contained greater concentrations of almost all the major compounds than its conventional counterpart on a per same botanical weight basis. The FIMS method was able to rapidly differentiate the organic and conventional sweet basil leaf samples (1min analysis time), whereas the HPLC fingerprints provided more information about the chemical composition of the basil samples with a longer analytical time.