γ-Aminobutyric acid (GABA) is one of the major inhibitory neurotransmitters in the central nervous system. It has multiple positive effects on mammalian physiology and is an important bioactive component of tea (Camellia sinensis). GABA generally occurs at a very low level in plants but GABA content increases substantially after exposure to a range of stresses, especially oxygen-deficiency. During processing of tea leaves, a combination of anoxic stress and mechanical damage are essential for the high accumulation of GABA. This is believed to be initiated by a change in glutamate decarboxylase activity, but the underlying mechanisms are unclear. In the present study we characterized factors regulating the expression and activity of three tea glutamate decarboxylase genes (CsGAD1, 2, and 3), and their encoded enzymes. The results suggests that, unlike the model plant Arabidopsis thaliana, there are dual mechanisms regulating the accumulation of GABA in tea leaves exposed to multiple stresses, including activation of CsGAD1 enzymatic activity by calmodulin upon the onset of the stress and accumulation of high levels of CsGAD2 mRNA induced by a combination of anoxic stress and mechanical damage.

The mechanistic systems in the body through which tea causes weight loss are complex and multi-dimensional. Additionally, the bioactive components in tea such as catechins, caffeine, and products of tea polyphenol oxidation vary greatly from one major tea type to the next. Green tea has been the primary subject of consideration for investigation into the preventative health effects of tea because it contains the highest levels of phenolic compounds and retains the highest antioxidant capabilities of any major tea type. However, recent research suggests decreasing body fat accumulation has little to do with antioxidant activity and more to do with enzyme inhibition, and gut microbiota interactions. This paper reviews several different tea polyphenol-induced weight-loss mechanisms, and purposes a way in which these mechanisms may be interrelated. Our original ‘short-chain fatty acid (SCFA) hypothesis’ suggests that the weight-loss efficacy of a given tea is determined by a combination of carbohydrate digestive enzyme inhibition and subsequent reactions of undigested carbohydrates with gut microbiota. These reactions among residual carbohydrates, tea polyphenols, and gut microbiota within the colon produce short-chain fatty acids, which enhance lipid metabolism through AMP-activated protein kinase (AMPK) activation. Some evidence suggests the mechanisms involved in SCFA generation may be triggered more strongly by teas that have undergone fermentation (black, oolong, and dark) than by non-fermented (green) teas. We discussed the mechanistic differences among fermented and non-fermented teas in terms of enzyme inhibition, interactions with gut microbiota, SCFA generation, and lipid metabolism. The inconsistent results and possible causes behind them are also discussed.

This article is a comprehensive review of the literature pertaining to the antidepressant effects and mechanisms of regular tea consumption. Meta-data supplemented with recent observational studies were first analyzed to assess the association between tea consumption and depression risk. The literature reported risk ratios (RR) were 0.69 with 95% confidence intervals of 0.62–0.77. Next, we thoroughly reviewed human trials, mouse models, and in vitro experiments to determine the predominant mechanisms underlying the observed linear relationship between tea consumption and reduced risk of depression. Current theories on the neurobiology of depression were utilized to map tea-mediated mechanisms of antidepressant activity onto an integrated framework of depression pathology. The major nodes within the network framework of depression included hypothalamic-pituitary-adrenal (HPA) axis hyperactivity, inflammation, weakened monoaminergic systems, reduced neurogenesis/neuroplasticity, and poor microbiome diversity affecting the gut–brain axis. We detailed how each node has subsystems within them, including signaling pathways, specific target proteins, or transporters that interface with compounds in tea, mediating their antidepressant effects. A major pathway was found to be the ERK/CREB/BDNF signaling pathway, up-regulated by a number of compounds in tea including teasaponin, L-theanine, EGCG and combinations of tea catechins and their metabolites. Black tea theaflavins and EGCG are potent anti-inflammatory agents via down-regulation of NF-κB signaling. Multiple compounds in tea are effective modulators of dopaminergic activity and the gut–brain axis. Taken together, our findings show that constituents found in all major tea types, predominantly L-theanine, polyphenols and polyphenol metabolites, are capable of functioning through multiple pathways simultaneously to collectively reduce the risk of depression.

Chemical compositions and infusion colour differences of seven pu-erh tea samples and their correlation to sensory quality were investigated. The results showed that the pu-erh tea contained 37.1 mg g −1 caffeine, 15.7 mg g −1 amino acids, 67.0 mg g −1 polyphenols and 8.41 mg g −1 total catechins, on average. Among the 17 tested volatile compounds, n-valeraldehyde was not detected. The most abundant volatile was β-ionone and the next was linalool oxide II. Infusion colour analysis showed that the pu-erh tea had deep hue with E ranging from 66.8 to 79.2. Spearman's linear correlation analysis showed that total quality score (TQS) of the pu-erh tea was significantly correlated to concentration of amino acids, linalool oxide II and infusion colour indicator E. Five components were extracted from the 34 tested indicators by principal component analysis and were regressed on the TQS to produce six Pearson's linear regression equations for estimating sensory quality of pu-erh tea, among which two were statistically significant, ie TQS = 57.47 − 0.18geraniol + 0.33polyphenols − 1.14n-caproaldehyde − 1.38linalool oxide I + 0.21caffeine (p < 0.01) and TQS = 57.42-0.03Citral + 0.33polyphenols − 1.14n − caproaldehyde − 1.40linalool oxide I + 0.20caffeine (p < 0.01).