Differentiation of key biomarkers in tea infusions using a target/nontarget gas chromatography/mass spectrometry workflow

Combined LC-MS-based metabolomics and GC-IMS analysis reveal changes in chemical components and aroma components of Jujube leaf tea during processing

Making tea from jujube leaves changed the chemical composition and aroma composition of jujube leaves. Here, Through LC-MS, GC-IMS, and GC-MS technology, we have revealed the effect of jujube leaf processing changes on metabolites. LC-MS identified 468 non-volatile metabolites, while GC-IMS and GC-MS detected 52 and 24 volatile metabolites, respectively. 109 non-volatile metabolites exhibiting more pronounced differences were screened. Most lipids and lipid-like molecules, organic acids, amino acids, and flavonoids increased significantly after processing. GC-IMS and GC-MS analysis revealed that the contents of aldehydes and ketones were significantly increased, while esters and partial alcohols were decreased after processing into jujube leaf tea. The main flavor substances of fresh jujube leaf and jujube leaf tea were eugenol and (E) - 2-Hexenal, respectively. Furthermore, amino acids and lipids were closely linked to the formation of volatile metabolites. Our study provided new insights into the changes in metabolites of jujube leaves processed into jujube leaf tea, and had great potential for industrial application. It laid a foundation for further research on fruit tree leaf tea.

Characterization of the Key Aroma Compounds of Shandong Matcha Using HS-SPME-GC/MS and SAFE-GC/MS

Shandong matcha has the quality characteristics of bright green color, seaweed-like aroma and strong, fresh and brisk taste. In order to identify the characteristic aroma components and clarify the contribution of the grinding process to the aroma of Shandong matcha. Three grades of Shandong matcha and corresponding tencha material were firstly tested with sensory evaluation, and the volatile components were extracted with headspace solid-phase microextraction (HS-SPME) and solvent-assisted flavor evaporation (SAFE) and analyzed using GC–MS. The sensory evaluation results showed that high-grade matcha (M-GS) had prominent seaweed-like, fresh and roasted notes, whereas medium and low-grade matcha (M-G1, M-G2) were gradually coupled with grassy, fatty and high-fired aromas. GC–MS results showed that in the HS-SPME method, heterocyclic compounds (45.84–65.35%) were the highest in Shandong matcha, followed by terpenoids (7.44–16.92%) and esters (6.91–15.27%), while in the safe method, esters were the highest (12.96–24.99%), followed by terpenoids (10.76–25.09%) and heterocyclic compounds (12.12–17.07%). As a whole, the composition of volatile components between M-G1 and M-G2 is relatively close, and there are more differences in volatile components between them and M-GS. The volatile components unique to M-GS were screened using the odor activity value (OAV) evaluation method, with components such as 3-methyl-2-butene-1-thiol, 3-ethyl-Phenol, 2-thiophenemethanethiol, 2,4-undecadienal, (E,E)-2,6-nonadienal, (E,Z)- being evaluated. There were other differentially volatile components, that is, volatile components that coexist in the three grades of matcha, but with different concentrations and proportions. M-G1 and M-G2 contained more volatile substances with high-fired aroma, such as 2-ethyl-3-methyl-pyrazine, coumarin and 5,6,7,8-tetrahydroquinoxaline. The grinding process not only changes the appearance of tencha, but also increases the content of volatile components of matcha as a whole, enhancing the aroma and flavor characteristics of matcha. In this study, the contents of 24 volatile components in matcha were mainly increased, such as benzene, (2,2-dimethoxyethyl)-, cis-7-decen-1-al, safranal and fenchyl acetate. The dual factors of material tencha and matcha grinding technology are indispensable in forming the differences in aroma and flavor of Shandong matcha at different levels.

The Chemistry of Green and Roasted Coffee by Selectable 1D/2D Gas Chromatography Mass Spectrometry with Spectral Deconvolution

Gas chromatography/mass spectrometry (GC/MS) is a long-standing technique for the analysis of volatile organic compounds (VOCs). When coupled with the Ion Analytics software, GC/MS provides unmatched selectivity in the analysis of complex mixtures and it reduces the reliance on high-resolution chromatography to obtain clean mass spectra. Here, we present an application of spectral deconvolution, with mass spectral subtraction, to identify a wide array of VOCs in green and roasted coffees. Automated sequential, two-dimensional GC-GC/MS of a roasted coffee sample produced the retention index and spectrum of 750 compounds. These initial analytes served as targets for subsequent coffee analysis by GC/MS. The workflow resulted in the quantitation of 511 compounds detected in two different green and roasted coffees. Of these, over 100 compounds serve as candidate differentiators of coffee quality, AAA vs. AA, as designated by the Coopedota cooperative in Costa Rica. Of these, 72 compounds survive the roasting process and can be used to discriminate green coffee quality after roasting.

The diversity and function of sourdough starter microbiomes

Humans have relied on sourdough starter microbial communities to make leavened bread for thousands of years, but only a small fraction of global sourdough biodiversity has been characterized. Working with a community-scientist network of bread bakers, we determined the microbial diversity of 500 sourdough starters from four continents. In sharp contrast with widespread assumptions, we found little evidence for biogeographic patterns in starter communities. Strong co-occurrence patterns observed in situ and recreated in vitro demonstrate that microbial interactions shape sourdough community structure. Variation in dough rise rates and aromas were largely explained by acetic acid bacteria, a mostly overlooked group of sourdough microbes. Our study reveals the extent of microbial diversity in an ancient fermented food across diverse cultural and geographic backgrounds.

Fungal volatiles mediate cheese rind microbiome assembly

In vitro studies in plant, soil, and human systems have shown that microbial volatiles can mediate microbe-microbe or microbe-host interactions. These previous studies have often used artificially high concentrations of volatiles compared to in situ systems and have not demonstrated the roles volatiles play in mediating community-level dynamics. We used the notoriously volatile cheese rind microbiome to identify bacteria responsive to volatiles produced by five widespread cheese fungi. Vibrio casei had the strongest growth stimulation when exposed to all fungi. In multispecies community experiments, fungal volatiles caused a shift to a Vibrio-dominated community, potentially explaining the widespread occurrence of Vibrio in surface-ripened cheeses. RNA sequencing identified activation of the glyoxylate shunt as a possible mechanism underlying volatile-mediated growth promotion and community assembly. Our study demonstrates how airborne chemicals could be used to control the composition of microbiomes and illustrates how volatiles may impact the development of cheese rinds.

Strain-Level Diversity Impacts Cheese Rind Microbiome Assembly and Function

Diversification can generate genomic and phenotypic strain-level diversity within microbial species. This microdiversity is widely recognized in populations, but the community-level consequences of microbial strain-level diversity are poorly characterized. Using the cheese rind model system, we tested whether strain diversity across microbiomes from distinct geographic regions impacts assembly dynamics and functional outputs. We first isolated the same three bacterial species (Staphylococcus equorum, Brevibacterium auranticum, and Brachybacterium alimentarium) from nine cheeses produced in different regions of the United States and Europe to construct nine synthetic microbial communities consisting of distinct strains of the same three bacterial species. Comparative genomics identified distinct phylogenetic clusters and significant variation in genome content across the nine synthetic communities. When we assembled each synthetic community with initially identical compositions, community structure diverged over time, resulting in communities with different dominant taxa. The taxonomically identical communities showed differing responses to abiotic (high salt) and biotic (the fungus Penicillium) perturbations, with some communities showing no response and others substantially shifting in composition. Functional differences were also observed across the nine communities, with significant variation in pigment production (light yellow to orange) and in composition of volatile organic compound profiles emitted from the rinds (nutty to sulfury).IMPORTANCE Our work demonstrated that the specific microbial strains used to construct a microbiome could impact the species composition, perturbation responses, and functional outputs of that system. These findings suggest that 16S rRNA gene taxonomic profiles alone may have limited potential to predict the dynamics of microbial communities because they usually do not capture strain-level diversity. Observations from our synthetic communities also suggest that strain-level diversity has the potential to drive variability in the aesthetics and quality of surface-ripened cheeses.

Geographic Authentication of Eucommia ulmoides Leaves Using Multivariate Analysis and Preliminary Study on the Compositional Response to Environment

To explore the influences of different cultivated areas on the chemical profiles of Eucommia ulmoides leaves (EUL) and rapidly authenticate its geographical origins, 187 samples from 13 provinces in China were systematically investigated using three data fusion strategies (low, mid, and high level) combined with two discrimination model algorithms (partial least squares discrimination analysis; random forest, RF). RF models constructed by high-level data fusion with different modes of different spectral data (Fourier transform near-infrared spectrum and attenuated total reflection Fourier transform mid-infrared spectrum) were most suitable for identifying EULs from different geographical origins. The accuracy rates of calibration and validation set were 92.86% and 93.44%, respectively. In addition, climate parameters were systematically investigated the cluster difference in our study. Some interesting and novel information could be found from the clustering tree diagram of hierarchical cluster analysis. The Xinjiang Autonomous Region (Region 5) located in the high latitude area was the only region in the middle temperate zone of all sample collection areas in which the samples belonged to an individual class no matter their distance in the tree diagram. The samples were from a relatively high elevation in the Shennongjia Forest District in Hubei Province (>1200 m), which is the main difference from the samples from Xiangyang City (78 m). Thus, the sample clusters from region 9 are different from the sample clusters from other regions. The results would provide a reference for further research to those samples from the special cluster.

Changes in Tea Plant Secondary Metabolite Profiles as a Function of Leafhopper Density and Damage

Insect herbivores have dramatic effects on the chemical composition of plants. Many of these induced metabolites contribute to the quality (e.g., flavor, human health benefits) of specialty crops such as the tea plant (Camellia sinensis). Induced chemical changes are often studied by comparing plants damaged and undamaged by herbivores. However, when herbivory is quantitative, the relationship between herbivore pressure and induction can be linearly or non-linearly density dependent or density independent, and induction may only occur after some threshold of herbivory. The shape of this relationship can vary among metabolites within plants. The tea green leafhopper (Empoasca onukii) can be a widespread pest on tea, but some tea farmers take advantage of leafhopper-induced metabolites in order to produce high-quality "bug-bitten" teas such as Eastern Beauty oolong. To understand the effects of increasing leafhopper density on tea metabolites important for quality, we conducted a manipulative experiment exposing tea plants to feeding by a range of E. onukii densities. After E. onukii feeding, we measured volatile and non-volatile metabolites, and quantified percent damaged leaf area from scanned leaf images. E. onukii density had a highly significant effect on volatile production, while the effect of leaf damage was only marginally significant. The volatiles most responsive to leafhopper density were mainly terpenes that increased in concentration monotonically with density, while the volatiles most responsive to leaf damage were primarily fatty acid derivatives and volatile phenylpropanoids/benzenoids. In contrast, damage (percent leaf area damaged), but not leafhopper density, significantly reduced total polyphenols, epigallocatechin gallate (EGCG), and theobromine concentrations in a dose-dependent manner. The shape of induced responses varied among metabolites with some changing linearly with herbivore pressure and some responding only after a threshold in herbivore pressure with a threshold around 0.6 insects/leaf being common. This study illustrates the importance of measuring a diversity of metabolites over a range of herbivory to fully understand the effects of herbivores on induced metabolites. Our study also shows that any increases in leafhopper density associated with climate warming, could have dramatic effects on secondary metabolites and tea quality.

Plant-Climate Interaction Effects: Changes in the Relative Distribution and Concentration of the Volatile Tea Leaf Metabolome in 2014-2016

Climatic conditions affect the chemical composition of edible crops, which can impact flavor, nutrition and overall consumer preferences. To understand these effects, we sampled tea (Camellia sinensis (L.) Kuntze) grown in different environmental conditions. Using a target/nontarget data analysis approach, we detected 564 metabolites from tea grown at two elevations in spring and summer over 3 years in two major tea-producing areas of China. Principal component analysis and partial least squares-discriminant analysis show seasonal, elevational, and yearly differences in tea from Yunnan and Fujian provinces. Independent of location, higher concentrations of compounds with aromas characteristic of farmers' perceptions of high-quality tea were found in spring and high elevation teas. Yunnan teas were distinct from Fujian teas, but the effects of elevation and season were different for the two locations. Elevation was the largest source of metabolite variation in Yunnan yet had no effect in Fujian. In contrast seasonal differences were strong in both locations. Importantly, the year-to-year variation in chemistry at both locations emphasizes the importance of doing multi-year studies, and further highlights the challenge farmers face when trying to produce teas with specific flavor/health (metabolite) profiles.

Untargeted/Targeted 2D Gas Chromatography/Mass Spectrometry Detection of the Total Volatile Tea Metabolome

Identifying all analytes in a natural product is a daunting challenge, even if fractionated by volatility. In this study, comprehensive two-dimensional gas chromatography/mass spectrometry (GC×GC-MS) was used to investigate relative distribution of volatiles in green, pu-erh tea from leaves collected at two different elevations (1162 m and 1651 m). A total of 317 high and 280 low elevation compounds were detected, many of them known to have sensory and health beneficial properties. The samples were evaluated by two different software. The first, GC Image, used feature-based detection algorithms to identify spectral patterns and peak-regions, leading to tentative identification of 107 compounds. The software produced a composite map illustrating differences in the samples. The second, Ion Analytics, employed spectral deconvolution algorithms to detect target compounds, then subtracted their spectra from the total ion current chromatogram to reveal untargeted compounds. Compound identities were more easily assigned, since chromatogram complexities were reduced. Of the 317 compounds, for example, 34% were positively identified and 42% were tentatively identified, leaving 24% as unknowns. This study demonstrated the targeted/untargeted approach taken simplifies the analysis time for large data sets, leading to a better understanding of the chemistry behind biological phenomena.

The Blossoming of Technology for the Analysis of Complex Aroma Bouquets-A Review on Flavour and Odorant Multidimensional and Comprehensive Gas Chromatography Applications

Multidimensional approaches in gas chromatography have been established as potent tools to (almost) attain fully resolved analyses. Flavours and odours are important application fields for these techniques since they include complex matrices, and are of interest for both scientific study and to consumers. This article is a review of the main research studies in the above theme, discussing the achievements and challenges that demonstrate a maturing of analytical separation technology.

2014-2016 seasonal rainfall effects on metals in tea (Camelia sinensis (L.) Kuntze)

Plant-climate interactions affect the edible crop composition, impacting flavor, nutrition, and overall consumer liking. In this study, principal components analysis was used to assess the macro- and micronutrient metal concentrations in pre-monsoon (spring), monsoon (summer), and post-monsoon (autumn) tea (Camelia sinensis (L.) Kuntze) from Yunnan Province, China in 2014-2016. Statistical differences were observed (p = 1.35E-24). Fe, Ca, Mg, Mn, Al, and Ba concentrations were higher in June (monsoon) than in March (pre-monsoon) and September (post-monsoon) compared to Pb, K, Cu, Zn, and Na, which were higher in March and September. Although Fe, Ca, Mg, Mn, Al, and Ba concentrations increased during the monsoon season, sensory analysis did not detect metallic taste in either minimally processed or farmer-processed (commercial) teas. This finding shows the seasonal differences in flavor were due to striking differences in organic chemical composition and concentration.