Volatile Organic Compound Metabolism on Early Earth.

Biogenic volatile organic compounds (VOCs) constitute a significant portion of gas-phase metabolites in modern ecosystems and have unique roles in moderating atmospheric oxidative capacity, solar radiation balance, and aerosol formation. It has been theorized that VOCs may account for observed geological and evolutionary phenomena during the Archaean, but the direct contribution of biology to early non-methane VOC cycling remains unexplored. Here, we provide an assessment of all potential VOCs metabolized by the last universal common ancestor (LUCA). We identify enzyme functions linked to LUCA orthologous protein groups across eight literature sources and estimate the volatility of all associated substrates to identify ancient volatile metabolites. We hone in on volatile metabolites with confirmed modern emissions that exist in conserved metabolic pathways and produce a curated list of the most likely LUCA VOCs. We introduce volatile organic metabolites associated with early life and discuss their potential influence on early carbon cycling and atmospheric chemistry.

Advancing accuracy in breath testing for lung cancer: strategies for improving diagnostic precision in imbalanced data.

BACKGROUND: Breath testing using an electronic nose has been recognized as a promising new technique for the early detection of lung cancer. Imbalanced data are commonly observed in electronic nose studies, but methods to address them are rarely reported. OBJECTIVE: The objectives of this study were to assess the accuracy of electronic nose screening for lung cancer with imbalanced learning and to select the best mechanical learning algorithm. METHODS: We conducted a case‒control study that included patients with lung cancer and healthy controls and analyzed metabolites in exhaled breath using a carbon nanotube sensor array. The study used five machine learning algorithms to build predictive models and a synthetic minority oversampling technique to address imbalanced data. The diagnostic accuracy of lung cancer was assessed using pathology reports as the gold standard. RESULTS: We enrolled 190 subjects between 2020 and 2023. A total of 155 subjects were used in the final analysis, which included 111 lung cancer patients and 44 healthy controls. We randomly divided samples into one training set, one internal validation set, and one external validation set. In the external validation set, the summary sensitivity was 0.88 (95% CI 0.84-0.91), the summary specificity was 1.00 (95% CI 0.85-1.00), the AUC was 0.96 (95% CI 0.94-0.98), the pAUC was 0.92 (95% CI 0.89-0.96), and the DOR was 207.62 (95% CI 24.62-924.64). CONCLUSION: Electronic nose screening for lung cancer is highly accurate. The support vector machine algorithm is more suitable for analyzing chemical sensor data from electronic noses.

Non-targeted metabolomic analysis reveals the mechanism of quality formation of citrus flower-green tea.

BACKGROUND: Citrus flower-green tea (CT) is a scented tea processed from green tea (GT) and fresh citrus flower, which is favored by consumers due to its potential health benefits and unique citrus flavor. This study evaluated the quality of CT and revealed the mechanism of its quality formation. RESULTS: The CT had a significant citrus flavor and a good antioxidant activity, and its sensory quality was superior to that of GT. Headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) analysis revealed that the scenting process resulted in a significant increase of alkenes such as ß-pinene, trans-ß-ocimene, α-farnesene, isoterpinolene, and γ-terpinene, as well as a significant decrease of alcohols such as α-terpineol, l-menthol, and linalool in CT in comparison with GT. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis revealed that the levels of flavonoids (such as neohesperidin, hesperidin, tangeritin, hesperetin 5-O-glucoside, and nobiletin) and alkaloids (such as trigonelline and theobromine) in CT increased significantly after scenting process, while the levels of amino acids (such as valine and l-phenylalanine) and organic acids (such as ascorbic acid) decreased significantly. CONCLUSION: These observations showed that the scenting process promoted the absorption of aroma from citrus flowers by GT and the changes in its non-volatile metabolites, leading to the formation of citrus flavor quality in CT. © 2024 Society of Chemical Industry.

Comparison of volatile metabolic profiles in fermented milk of Streptococcus thermophilus during the postripening period at different incubation temperatures.

Streptococcus thermophilus has been extensively applied in fermented milk. This study used gas chromatography-ion mobility spectroscopy to determine and evaluate the volatile metabolites in raw milk, milk fermented at 37°C, and milk fermented at 42°C. Ten discriminatory volatile metabolites were identified at different incubation temperatures: acetone, 2-heptanone, 2-pentanone, 2-hexanone, butanal, hexanal, ethyl acetate, 3-methylbutanal, 3-methylbutanoic acid, and 2-methylpropanoic acid, indicating that fermentation temperature affected the spectrum of volatiles in milk fermented by different strains of S. thermophilus. Specifically, fermentation at 37°C led to accumulation of short-chain fatty acids, whereas fermentation at 42°C enriched ketones and other flavor substances in the fermented milk, enhancing the flavor of the product. This work examined the differences between the volatile metabolites produced by different S. thermophilus strains fermented at different temperatures to evaluate the effect of temperature on the metabolic pathways.

An in vitro collagen perfusion wound biofilm model; with applications for antimicrobial studies and microbial metabolomics.

BACKGROUND: The majority of in vitro studies of medically relevant biofilms involve the development of biofilm on an inanimate solid surface. However, infection in vivo consists of biofilm growth on, or suspended within, the semi-solid matrix of the tissue, whereby current models do not effectively simulate the nature of the in vivo environment. This paper describes development of an in vitro method for culturing wound associated microorganisms in a system that combines a semi-solid collagen gel matrix with continuous flow of simulated wound fluid. This enables culture of wound associated reproducible steady state biofilms under conditions that more closely simulate the dynamic wound environment. To demonstrate the use of this model the antimicrobial kinetics of ceftazidime, against both mature and developing Pseudomonas aeruginosa biofilms, was assessed. In addition, we have shown the potential application of this model system for investigating microbial metabolomics by employing selected ion flow tube mass spectrometry (SIFT-MS) to monitor ammonia and hydrogen cyanide production by Pseudomonas aeruginosa biofilms in real-time. RESULTS: The collagen wound biofilm model facilitates growth of steady-state reproducible Pseudomonas aeruginosa biofilms under wound like conditions. A maximum biofilm density of 1010 cfu slide- 1 was achieved by 30 h of continuous culture and maintained throughout the remainder of the experiment. Treatment with ceftazidime at a clinically relevant dose resulted in a 1.2-1.6 log reduction in biofilm density at 72 h compared to untreated controls. Treatment resulted in loss of complex biofilm architecture and morphological changes to bacterial cells, visualised using confocal microscopy. When monitoring the biofilms using SIFT-MS, ammonia and hydrogen cyanide levels peaked at 12 h at 2273 ppb (±826.4) and 138 ppb (±49.1) respectively and were detectable throughout experimentation. CONCLUSIONS: The collagen wound biofilm model has been developed to facilitate growth of reproducible biofilms under wound-like conditions. We have successfully used this method to: (1) evaluate antimicrobial efficacy and kinetics, clearly demonstrating the development of antimicrobial tolerance in biofilm cultures; (2) characterise volatile metabolite production by P. aeruginosa biofilms, demonstrating the potential use of this method in metabolomics studies.

A powerful approach to explore the potential of medicinal plants as a natural source of odor and antioxidant compounds.

In this study an efficient and reliable method based on dynamic headspace solid-phase microextraction (HS-SPME) followed by gas chromatography-mass spectrometry (GC-qMS), was developed to establish the volatile metabolomic pattern of Thymus vulgaris L., Rosmarinus officinalis L. and Ruta chalepensis L. medicinal plants. The HS-SPME influencing parameters were investigated and the results indicated that the best extraction capability, was obtained using DVB/CAR/PDMS coating fiber at 40 °C for 45 min. Under optimal conditions, a total of 99 volatile metabolites were identified, including 53 terpenoids, 19 carbonyl compounds, 7 esters, 6 alcohols, among others. The main volatile metabolites identified in T. vulgaris include thymol (67 %), 3-octanone (9 %) and 1-octen-3-ol (7 %), while in R. officinalis the most dominant volatiles were eucalyptol (40 %), 2-decanone (20 %) and bornyl acetate (10 %). 2-Undecanone (53 %), (E)-2-octenal (28 %) and 2-nonanone (10 %) were the most relevant volatile metabolites identified in R. chalepensis. The results suggested that the HS-SPME/GC-qMS methodology is a powerful approach to establish the volatile metabolomic fingerprint of medicinal plants and providing a reliable tool for the complete characterization of these biologically active medicinal plants.

A methodological approach to screen diverse cheese-related bacteria for their ability to produce aroma compounds.

Microorganisms play an important role in the development of cheese flavor. The aim of this study was to develop an approach to facilitate screening of various cheese-related bacteria for their ability to produce aroma compounds. We combined i) curd-based slurry medium incubated under conditions mimicking cheese manufacturing and ripening, ii) powerful method of extraction of volatiles, headspace trap, coupled to gas chromatography-mass spectrometry (HS-trap-GC-MS), and iii) metabolomics-based method of data processing using the XCMS package of R software and multivariate analysis. This approach was applied to eleven species: five lactic acid bacteria (Leuconostoc lactis, Lactobacillus sakei, Lactobacillus paracasei, Lactobacillus fermentum, and Lactobacillus helveticus), four actinobacteria (Brachybacterium articum, Brachybacterium tyrofermentans, Brevibacterium aurantiacum, and Microbacterium gubbeenense), Propionibacterium freudenreichii, and Hafnia alvei. All the strains grew, with maximal populations ranging from 7.4 to 9.2 log (CFU/mL). In total, 52 volatile aroma compounds were identified, of which 49 varied significantly in abundance between bacteria. Principal component analysis of volatile profiles differentiated species by their ability to produce ethyl esters (associated with Brachybacteria), sulfur compounds and branched-chain alcohols (H. alvei), branched-chain acids (H. alvei, P. freudenreichii and L. paracasei), diacetyl and related carbonyl compounds (M. gubbeenense and L. paracasei), among others.

Utilizing metabolomics and network analysis to explore the effects of artificial production methods on the chemical composition and activity of agarwood.

Introduction: Agarwood is a traditional aromatic southern medicine. It has a long history of being used in traditional Chinese aromatherapy to treat insomnia, anxiety and depression. Due to the scarcity of wild resources, people have planted trees successfully and begun to explore various agarwood-inducing techniques. This study comparative analysis of volatile metabolites in agarwood produced by various inducing techniques and its potential sleep-promoting, anti-anxiety and anti-depressant network pharmacological activities. Methods: A total of 23 batches of two types of agarwood were collected, one of which was produced by artificial techniques, including 6 batches of TongTi (TT) agarwood produced by "Agar-Wit" and 6 batches of HuoLao (HL) agarwood produced by "burning, chisel and drilling", while the other was collected from the wild, including 6 batches of BanTou (BT) agarwood with trunks broken due to natural or man-made factors and 5 batches of ChongLou (CL) agarwood with trunks damaged by moth worms. The study employed metabolomics combined with network analysis to compare the differences in volatile metabolites of agarwood produced by four commonly used inducing techniques, and explored their potential roles and possible action targets in promoting sleep, reducing anxiety, and alleviating depression. Results: A total of 147 volatile metabolites were detected in agarwood samples, mainly including small aromatic hydrocarbons, sesquiterpenes and 2-(2-phenylethyl) chromone and their pyrolysis products. The results showed composition of metabolites was minimally influenced by the agarwood induction method. However, their concentrations exhibited significant variations, with 17 metabolites showing major differences. The two most distinct metabolites were 6-methoxy-2-(2-phenylethyl) chromone and 6,7-dimethoxy-2-(2-phenylethyl) chromone. Among the volatile metabolites, 142 showed promising potential in treating insomnia, anxiety, and depression, implicating various biological and signaling pathways, predominantly ALB and TNF targets. The top three active metabolites identified were 2-(2-phenylethyl) chromone, 1,5-diphenylpent-1-en-3-one, and 6-methoxy-2-[2-(4'-methoxyphenyl) ethyl] chromone, with their relative content in the four types of agarwood being TT>HL>CL>BT. Conclusion: The differences in the content of 2-(2-phenylethyl) chromones suggest that they may be responsible for the varying therapeutic activities observed in different types of agarwood aromatherapy. This study offers theoretical support for the selection of agarwood in aromatherapy practices.

Black Goji Berry (Lycium ruthenicum) Juice Fermented with Lactobacillus rhamnosus GG Enhances Inhibitory Activity against Dipeptidyl Peptidase-IV and Key Steps of Lipid Digestion and Absorption.

With the global increase in hyperglycemia and hyperlipidemia, there is an urgent need to explore dietary interventions targeting the inhibition of dipeptidyl peptidase-IV (DPP-IV) and lipid digestion and absorption. This study investigated how Lactobacillus rhamnosus GG (LGG) affects various aspects of black goji berry (BGB) (Lycium ruthenicum Murr.) juice, including changes in physicochemical and functional properties, as well as microbiological and sensory attributes. Throughout the fermentation process with 2.5-10% (w/v) BGB, significantly improved probiotic viability, lactic acid production, and decreased sugar content. While total flavonoids increase, anthocyanins decrease, with no discernible change in antioxidant activities. Metabolite profiling reveals elevated phenolic compounds post-fermentation. Regarding the inhibition of lipid digestion and absorption, fermented BGB exhibits improved bile acid binding, and disrupted cholesterol micellization by approximately threefold compared to non-fermented BGB, while also increasing pancreatic lipase inhibitory activity. Furthermore, a decrease in cholesterol uptake was observed in Caco-2 cells treated with fermented BGB (0.5 mg/mL), with a maximum reduction of 16.94%. Fermented BGB also shows more potent DPP-IV inhibition. Sensory attributes are significantly improved in fermented BGB samples. These findings highlight the potential of BGB as a bioactive resource and a promising non-dairy carrier for LGG, enhancing its anti-hyperglycemic and anti-hyperlipidemic properties.

Metabolomics and electronic-tongue analysis reveal differences in color and taste quality of large-leaf yellow tea under different roasting methods.

Roasting is a key process in the production of large-leaf yellow tea (LYT). In this study, we synthesized metabolomics and electronic-tongue analysis to compare the quality of charcoal-roasted, electric-roasted and drum-roasted LYT. Charcoal-roasted LYT had the highest yellowness and redness, drum-roasted LYT had a more prominent umami and brightness, and electric roasting reduced astringency. A total of 48 metabolites were identified by metabolomics. Among these, leucocyanidin, kaempferol, luteolin-7-lactate, and apigenin-7-O-neohesperidoside might affect the brightness and yellowness. Theanine, aspartic acid, and glutamic acid contents significantly and positively correlated with umami levels, and the high retention of flavonoid glycosides and catechins in drum-roasted LYT contributed to its astringency. These findings elucidate the contribution of the roasting method to the quality of LYT and provide a theoretical basis for LYT production.

Volabolomic Fingerprinting for Post-Mortem Interval Estimation: A Novel Physiological Approach.

Death is a multifaceted process wherein each individual cell and tissue has a metabolic homeostasis and a time of functional cessation defined by the dying process as well as by intrinsic and extrinsic factors. Decomposition is physiologically associated with the release of different types of volatile organic compounds (VOCs), and these form volaboloma mortis. The main purpose of this study was to record the volabolomic fingerprint produced by volatile molecules during the physiological decomposition process of human tissue and muscle cells. The volatile chemical signature has important implications for an open issue in forensics and pathology, namely the estimation of the postmortem interval (PMI), which decreases in accuracy with the passage of time. Volatile metabolites emitted from human tissues and muscle cells at 0, 24, 48, and 72 h were recorded in real time with an electronic nose sensor device. The key findings were the continuous sampling of VOCs emitted from tissues and cells. These showed a common behavior as time progressed; particularly, after 48 h the distributions became dispersed, and after 72 h they became more variable. Volabolomic fingerprinting associated with time progression relevant to the study of PMIs was reconstructed. Additionally, there may be broader applications, such as in dog training procedures for detecting human remains, and perhaps even for studying scavenger and insect attractants.

Comparative Analysis of Volatile and Non-Volatile Metabolites Derived from Bacillus subtilis Strains Producing Different Levels of Biogenic Amines.

Biogenic amines (BAs), which are mainly generated by the microbial decarboxylation of amino acids, are important nitrogen compounds in fermented foods because of their toxicology. However, amino acids, the precursors of BAs, also play an important role in generating volatile and non-volatile metabolites, which are strongly associated with quality indicators for foods. Bacillus subtilis is one of dominant fermentative microorganism in various fermented foods and is well known as a BA-producing bacterium. In this study, B. subtilis strains which have different BAs-producing capacities, higher level of BAs production strain (BH) and lower level of BAs production strain (BL), were applied to compare the formations of volatile and non-volatile metabolite profiles according to cultivation times. In this study, histamine, putrescine, and spermidine were detected in all strains, however, 2-phenylethylamine was detected only in BH. Partial least squares discriminant analysis (PLS-DA) was applied to investigate the difference of metabolic profiles according to strains. In BH, some amino acids (phenylalanine, leucine, and threonine) and related volatile metabolites (3-methylbutanoic acid, pyrazines, styrene, and 1H-indole) were produced higher levels. On the other hand, BL produced significantly higher contents of metabolites associated with metabolism of fatty acids and nucleotides. It is necessary to consider the formation of metabolites in terms of quality as well as that of BAs during fermentation.

Automating methods for estimating metabolite volatility.

The volatility of metabolites can influence their biological roles and inform optimal methods for their detection. Yet, volatility information is not readily available for the large number of described metabolites, limiting the exploration of volatility as a fundamental trait of metabolites. Here, we adapted methods to estimate vapor pressure from the functional group composition of individual molecules (SIMPOL.1) to predict the gas-phase partitioning of compounds in different environments. We implemented these methods in a new open pipeline called volcalc that uses chemoinformatic tools to automate these volatility estimates for all metabolites in an extensive and continuously updated pathway database: the Kyoto Encyclopedia of Genes and Genomes (KEGG) that connects metabolites, organisms, and reactions. We first benchmark the automated pipeline against a manually curated data set and show that the same category of volatility (e.g., nonvolatile, low, moderate, high) is predicted for 93% of compounds. We then demonstrate how volcalc might be used to generate and test hypotheses about the role of volatility in biological systems and organisms. Specifically, we estimate that 3.4 and 26.6% of compounds in KEGG have high volatility depending on the environment (soil vs. clean atmosphere, respectively) and that a core set of volatiles is shared among all domains of life (30%) with the largest proportion of kingdom-specific volatiles identified in bacteria. With volcalc, we lay a foundation for uncovering the role of the volatilome using an approach that is easily integrated with other bioinformatic pipelines and can be continually refined to consider additional dimensions to volatility. The volcalc package is an accessible tool to help design and test hypotheses on volatile metabolites and their unique roles in biological systems.

Factors affecting bacterial community dynamics and volatile metabolite profiles of Thai traditional salt fermented fish.

Bacterial diversity of the Thai traditional salt fermented fish with roasted rice bran (Pla-ra) was investigated using classical and molecular approaches. Bacterial population of Pla-ra ranged from 102-106 in solid-state (SSF) and 106-109 CFU/g in submerged (SMF) fermentation types. Halanaerobium spp. and Lentibacillus spp. were the main genera particularly detected when rRNA analysis was applied. Tetragenococcus halophillus were dominant during the final stage in sea salt-recipe samples while Bacillus spp. were found in those rock salt recipes. In contrast, cultural plating demonstrated that Bacillus spp., generally B. amyloliquefaciens, were the dominant genera. In addition, B. pumilus, B. autrophaeus, B.subtilis and B. velezensis shown some relations with rock salt-recipe samples. The main volatile metabolites in all samples were butanoic acid and its derivatives. Key factors affected bacterial profiles and volatile compounds of salt fermented fish were type of salt, addition of roasted rice bran, and fermenting conditions.

Broad-Spectrum Antimicrobial Action of Cell-Free Culture Extracts and Volatile Organic Compounds Produced by Endophytic Fungi Curvularia Eragrostidis.

Endophytes are the mutualistic microorganisms that reside within the host plant and promote plant growth in adverse conditions. Plants and their endophytes are engaged in a symbiotic relationship that enables endophytes to access bioactive genes of the ethnomedicinal plants, and, as a result, endophytes are constantly addressed in the sector of pharmaceuticals and agriculture for their multidomain bio-utility. The gradual increase of antimicrobial resistance can be effectively countered by the endophytic metabolites. In these circumstances, in the present investigation, endophytic Curvularia eragrostidis HelS1 was isolated from an ethnomedicinally valuable plant Helecteris isora from East India's forests. The secondary volatile and non-volatile metabolites are extracted from HelS1 and are found to be effective broad-spectrum antimicrobials. A total of 26 secondary metabolites (9 volatiles and 17 non-volatiles) are extracted from the isolate, which exhibits effective antibacterial [against six Gram-positive and seven Gram-negative pathogens with a minimum inhibitory concentrations (MIC) value ranging from 12.5 to 400 µg ml-1] and antifungal (against seven fungal plant pathogens) activity. The secondary metabolite production was optimised by one variable at a time technique coupled with the response surface methodology. The results revealed that there was a 34% increase in antibacterial activity in parameters with 6.87 g L-1 of fructose (as a carbon source), 3.79 g L-1 of peptone (as a nitrogen source), pH 6.75, and an inoculation period of 191.5 h for fermentation. The volatile metabolite production was also found to be optimum when the medium was supplemented with yeast extract and urea (0.2 g L-1) along with dextrose (40 g L-1). Amongst extracted volatile metabolites, 1-H-indene 1 methanol acetate, tetroquinone, N, N-diphenyl-2-nitro-thio benzamide, Trans 1, 2-diethyl-trans-2-decalinol, naphthalene, and azulene are found to be the most effective. Our investigation opens up opportunities in the sector of sustainable agriculture as well as the discovery of novel antimicrobials against dreadful phyto and human pathogens.

Effect of fermentation by Pediococcus pentosaceus and Staphylococcus carnosus on the metabolite profile of sausages.

A multi-omics approach was applied to investigate the differences and correlations between characteristic volatile flavor substances and non-volatile metabolites in sausages fermented by Pediococcus pentosaceus (P. pentosaceus) and Staphylococcus carnosus (S. carnosus) alone and in a mixture. Twenty-seven volatile metabolites were identified by headspace solid-phase microextraction/gas chromatography-mass. According to orthogonal projections to latent structures-differential analysis, 17 characteristic volatile metabolites were detected in the sausages of different treatments. Utilizing ultra-high-performance liquid chromatography coupled with a mass spectrometer to analyze metabolite profiles, 42.03% of the non-volatile metabolites were classified as lipids and lipid-like molecules, 25.00% of organic acids and derivatives, and others. Seventeen characteristic flavor substances were significantly correlated with twenty differential non-volatile metabolites, and the non-volatile metabolites changed significantly. Differences in the characteristics and combinations of microorganisms themselves have a decisive role in the development of flavor substances and non-volatile metabolites in sausages.

Sampling and Analysis of Low-Molecular-Weight Volatile Metabolites in Cellular Headspace and Mouse Breath.

Volatile compounds, abundant in breath, can be used to accurately diagnose and monitor a range of medical conditions. This offers a noninvasive, low-cost approach with screening applications; however, the uptake of this diagnostic approach has been limited by conflicting published outcomes. Most published reports rely on large scale screening of the public, at single time points and without reference to ambient air. Here, we present a novel approach to volatile sampling from cellular headspace and mouse breath that incorporates multi-time-point analysis and ambient air subtraction revealing compound flux as an effective proxy of active metabolism. This approach to investigating breath volatiles offers a new avenue for disease biomarker discovery and diagnosis. Using gas chromatography mass spectrometry (GC/MS), we focus on low molecular weight, metabolic substrate/by-product compounds and demonstrate that this noninvasive technique is sensitive (reproducible at ~1 µg cellular protein, or ~500,000 cells) and capable of precisely determining cell type, status and treatment. Isolated cellular models represent components of larger mammalian systems, and we show that stress- and pathology-indicative compounds are detectable in mice, supporting further investigation using this methodology as a tool to identify volatile targets in human patients.

Classification of gases around Pseudomonas aeruginosa and Acinetobacter baumannii by infrared spectroscopy.

Gas samples were collected from the air surrounding single and mixed laboratory cultures, and preliminary data on human breath samples were also obtained. The infrared spectra of a variety of gasses were measured at high resolution (0.5 cm-1) to obtain information about the infrared absorption bands to be used as indicators. These key bands enable bacterial classification, and the discrimination rates can be improved by observing multiple infrared absorptions. The air around Pseudomonas aeruginosa was distinguished from the other gas samples by the infrared absorptions at wavenumbers of 778.4 cm-1 and 2213.2 cm-1. For Acinetobacter baumannii, infrared absorptions at 1215.0 cm-1 and 2982.3 cm-1 were used; furthermore, adding those at 4768.7 cm-1 and 5353.8 cm-1 was shown to improve identification.

Analysis of volatile metabolite variations in strip green tea during processing and effect of rubbing degree using untargeted and targeted metabolomics.

Strip green tea (SGT) is widely distributed in China owing to its unique appearance and aroma but the evolution and formation mechanisms of volatile metabolites (VMs) during SGT processing, and especially in the unique process of rubbing, remain unclear. In this study, based on untargeted metabolomics, 217 VMs (8 categories) were identified, and fixation and rubbing processes were found to be key for SGT aroma formation. Moreover, targeted metabolomics was applied to obtain 38 differential VMs and their related substances, of which fatty acid-derived volatiles (14 VMs) and glycoside-derived volatiles (8 VMs) showed significant contributions to SGT aroma, and their derivation laws during SGT manufacturing were clarified. Furthermore, the effect of rubbing degree on volatile metabolite formation was explored, and 11 key differential VMs were screened by variable importance in projection, and odor activity value analyses. Appropriate rubbing promoted the loss of grassy VMs (such as 1-octanol and 2-pentyl-furan) and enrichment of floral/fruity VMs (such as trans-ß-ionone, nonanal, geraniol, citral, (Z)-3,7-dimethyl-2,6-octadien-1-ol, and (Z)-hexanoic acid, 3-hexenyl ester). Our study not only enriches the chemical theory of green tea processing but also provides technical support for the precision directional processing of high-quality SGT.

Comprehensive investigation on non-volatile and volatile metabolites in four types of green teas obtained from the same tea cultivar of Longjing 43 (Camellia sinensis var. sinensis) using the widely targeted metabolomics.

In this study, we produced roasted, baked, steamed, and sun-dried green tea products using the same batch of fresh tea leaves (FTL) of Longjing 43 (Camellia sinensis var. sinensis), and explored processing effects on the metabolic profiles of four types of green teas (FGTs) using the widely targeted metabolomics. Results showed that 146 differential metabolites including flavonoids, amino acids, lipids, and phenolic acids were screened among 1034 non-volatiles. In addition, nineteen differential metabolites were screened among 79 volatiles. Most of non-volatiles and volatiles metabolites changed notably in different manufacturing processes, whereas there were no significant differences (p＞0.05) in the levels of total catechins between FGTs and FTL. The transformation of metabolites was the dominant trend during green tea processing. The results contribute to a better understanding of how the manufacturing process influences green tea quality, and provide useful information for the enrichment of tea biochemistry theory.