Integrated metabolomic and transcriptomic analyses reveal the molecular mechanism of amino acid transport between source and sink during tea shoot development.

KEY MESSAGE: The weighted gene co-expression network analysis and antisense oligonucleotide-mediated transient gene silencing revealed that CsAAP6 plays an important role in amino acid transport during tea shoot development. Nitrogen transport from source to sink is crucial for tea shoot growth and quality formation. Amino acid represents the major transport form of reduced nitrogen in the phloem between source and sink, but the molecular mechanism of amino acid transport from source leaves to new shoots is not yet clear. Therefore, the composition of metabolites in phloem exudates collected by the EDTA-facilitated method was analyzed through widely targeted metabolomics. A total of 326 metabolites were identified in the phloem exudates with the richest variety of amino acids and their derivatives (93), accounting for approximately 39.13% of the total metabolites. Moreover, through targeted metabolomics, it was found that the content of glutamine, glutamic acid, and theanine was the most abundant, and gradually increased with the development of new shoots. Meanwhile, transcriptome analysis suggested that the expression of amino acid transport genes changed significantly. The WGCNA analysis identified that the expression levels of CsAVT1, CsLHTL8, and CsAAP6 genes located in the MEterquoise module were positively correlated with the content of amino acids such as glutamine, glutamic acid, and theanine in phloem exudates. Reducing the CsAAP6 in mature leaves resulted in a significant decrease in the content of glutamic acid, aspartic acid, alanine, leucine, asparagine, glutamine, and arginine in the phloem exudates, indicating that CsAAP6 played an important role in the source to sink transport of amino acids in the phloem. The research results will provide the theoretical basis and genetic resources for the improvement of nitrogen use efficiency and tea quality.

Proteomics and phosphoproteomics reveal the different drought-responsive mechanisms of priming with (Z)-3-hexenyl acetate in two tea cultivars.

Drought is an important abiotic stress that constrains the quality and quantity of tea plants. The green leaf volatiles Z-3-hexenyl acetate (Z-3-HAC) have been reported to play an essential role in stress responses. However, the underlying mechanisms of drought tolerance in tea plants remain elusive. This study investigated the physiological, proteomic, and phosphoproteomic profiling of two tea plant varieties of Longjingchangye (LJCY) and Zhongcha 108 (ZC108) with contrasting drought tolerance characteristics under drought stress. Physiological data showed that spraying Z-3-HAC exhibited higher activities of superoxide dismutase (SOD) and catalase (CAT) in both LJCY and ZC108 but lower content of malondialdehyde (MDA) in LJCY under drought stress. The proteomic and phosphoproteomic analysis suggested that the drought tolerance mechanism of Z-3-HAC in LJCY and ZC108 was different. Proteomic analyses revealed that Z-3-HAC enhanced the drought tolerance of LJCY by fructose metabolism while enhancing the drought tolerance of ZC108 by promoting glucan biosynthesis and galactose metabolism. Furthermore, the differential abundance phosphoproteins (DAPPs) related to intracellular protein transmembrane transport and protein transmembrane transport were enriched in LJCY, and the regulation of response to osmotic stress and regulation of mRNA processing were enriched in ZC108. In addition, protein-phosphoprotein interactions (PPI) analyses suggested that energy metabolism and starch and sucrose metabolic processes might play critical roles in LJCY and ZC108, respectively. These results will help to understand the mechanisms by which Z-3-HAC enhances the drought resistance of tea plants at the protein level. SIGNIFICANT: Green leaf volatiles (GLVs) are important volatile organic compounds that play essential roles in plant defense against biotic and abiotic stresses. To understand the mechanisms of Z-3-HAC in improving the drought tolerance of tea plants, two contrasting drought tolerance varieties (LJCY and ZC108) were comparatively evaluated by proteomics and phosphoproteomics. This analysis evidenced changes in the abundance of proteins involved in energy metabolism and starch and sucrose metabolic processes in LJCY and ZC108, respectively. These proteins may elucidate new molecular aspects of the drought resistance mechanism of Z-3-HAC, providing a theoretical basis for drought resistance breeding of tea plants.

A deep learning model for rapid classification of tea coal disease.

BACKGROUND: The common tea tree disease known as "tea coal disease" (Neocapnodium theae Hara) can have a negative impact on tea yield and quality. The majority of conventional approaches for identifying tea coal disease rely on observation with the human naked eye, which is labor- and time-intensive and frequently influenced by subjective factors. The present study developed a deep learning model based on RGB and hyperspectral images for tea coal disease rapid classification. RESULTS: Both RGB and hyperspectral could be used for classifying tea coal disease. The accuracy of the classification models established by RGB imaging using ResNet18, VGG16, AlexNet, WT-ResNet18, WT-VGG16, and WT-AlexNet was 60%, 58%, 52%, 70%, 64%, and 57%, respectively, and the optimal classification model for RGB was the WT-ResNet18. The accuracy of the classification models established by hyperspectral imaging using UVE-LSTM, CARS-LSTM, NONE-LSTM, UVE-SVM, CARS-SVM, and NONE-SVM was 80%, 95%, 90%, 61%, 77%, and 65%, respectively, and the optimal classification model for hyperspectral was the CARS-LSTM, which was superior to the model based on RGB imaging. CONCLUSIONS: This study revealed the classification potential of tea coal disease based on RGB and hyperspectral imaging, which can provide an accurate, non-destructive, and efficient classification method for monitoring tea coal disease.

Different changes of bacterial diversity and soil metabolites in tea plants-legume intercropping systems.

As an essential agroforestry, intercropping legumes can improve the physical, chemical, and biological fertility of the soil in tea plantations. However, the effects of intercropping different legume species on soil properties, bacterial communities, and metabolites remain elusive. In this study, the 0-20 cm and 20-40 cm soils of three planting patterns (T1: tea plants/mung bean intercropping, T2: tea plants/adzuki bean intercropping, T3: tea plants/mung bean and adzuki bean intercropping) were sampled to explore the diversity of the bacterial community and soil metabolites. The findings showed that, as compared to monocropping, intercropping systems had greater concentrations of organic matter (OM) and dissolved organic carbon (DOC). Notably, pH values were significantly lower, and soil nutrients increased in intercropping systems compared with monoculture in 20-40 cm soils, especially in T3. In addition, intercropping resulted in an increased relative abundance of Proteobacteria but a decreased relative abundance of Actinobacteria. 4-methyl-Tetradecane, acetamide, and diethyl carbamic acid were key metabolites mediating the root-microbe interactions, especially in tea plants/adzuki intercropping and tea plants/mung bean, adzuki bean mixed intercropping soils. Co-occurrence network analysis showed that arabinofuranose, abundant in tea plants and adzuki bean intercropping soils, showed the most remarkable correlation with the soil bacterial taxa. Our findings demonstrate that intercropping with adzuki beans is better at enhancing the diversity of soil bacteria and soil metabolites and is more weed-suppressing than other tea plants/legume intercropping systems.

Metabolic Variations among Three New Tea Varieties Cultivated in Shandong, China.

Cultivar identification is a necessary step in tea breeding programs. Rapid identification methods would greatly improve these breeding processes. To preliminarily identify the three new Lucha tea varieties (LC6, LC7, and LC17) cultivated in Shandong, we measured their main agronomic characters and biochemical components. Then, we analyzed the metabolic profiles of these tea varieties and Fuding Dabaicha (FD) using a UPLC-ESI-MS/MS system. Their biochemical components indicated that the Lucha varieties had excellent varietal characteristics, with higher amino acid contents. Furthermore, secondary metabolism changed a lot in the Lucha tea varieties compared with that in the FD, with their accumulations of flavonoids and phenolic acids showing significant differences. These differential flavonoids were dominated by flavones and flavanone, flavonols, flavonoid carbonosides, and flavanols monomer. Flavanols especially, including epicatechin glucoside, epicatechin-3-(3″-O-methyl)gallate, epigallocatechin-3-O-(3,5-O-dimethyl)gallate, and epitheaflavic acid-3-O-Gallate, showed higher levels in the Lucha varieties. The phenolic acids containing caffeoyl groups showed higher levels in the Lucha varieties than those in the FD, while those containing galloyl groups showed a reverse pattern. Nitrogen metabolism, including amino acids, also showed obvious differences between the Lucha varieties and FD. The differential amino acids were mainly higher in the Lucha varieties, including 5-L-glutamyl-L-amino acid, N-monomethyl-L-arginine, and N-α-acetyl-L-ornithine. By using these approaches, we found that LC6, LC7, and LC17 were excellent varieties with a high yield and high quality for making green teas in Shandong.

Effect of shading on physiological attributes and comparative transcriptome analysis of Camellia sinensis cultivar reveals tolerance mechanisms to low temperatures.

Tea is a vital beverage crop all over the world, including in China. Low temperatures restrict its growth, development, and terrestrial distribution, and cold event variability worsens cold damage. However, the physiological and molecular mechanisms of Camellia sinensis under shade in winter remain unclear. In our study, tea leaves were utilized for physiological attributes and transcriptome analysis in November and December in three shading groups and no-shade control plants. When compared to the no-shade control plants, the shading group protected tea leaves from cold damage, increased photochemical efficiency (Fv/Fm) and soil plant analysis development (SPAD), and sustained chlorophyll a, chlorophyll b, chlorophyll, and carotenoid contents by physiological mean. Then, transcriptome analysis revealed 20,807 differentially expressed genes (DEGs) and transcription factors (TFs) in November and December. A comparative study of transcriptome resulted in 3,523 DEGs and many TFs under SD0% vs. SD30%, SD0% vs. SD60%, and SD0% vs. SD75% of shading in November and December. Statistically, 114 DEGs were downregulated and 72 were upregulated under SD0% vs. SD30%. SD0% vs. SD60% resulted in 154 DEGs, with 60 downregulated and 94 upregulated. Similarly, there were 505 DEGs of which 244 were downregulated and 263 were upregulated under SD0% vs. SD75% of shading throughout November. However, 279 DEGs were downregulated and 105 were upregulated under SD0% vs. SD30%. SD0% vs. SD60% resulted in 296 DEGs, with 172 downregulated and 124 upregulated. Finally, 2,173 DEGs were regulated in December, with 1,428 downregulated and 745 upregulated under SD0% vs. SD75%. These indicate that the number of downregulated DEGs in December was higher than the number of upregulated DEGs in November during low temperatures. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of differentially expressed genes were highly regulated in the photosynthesis, plant hormone signal transduction, and mitogen-activated protein kinase (MAPK) signaling pathways. However, qRT-PCR and RNA-seq relative expression of photosynthetic (DEGs) Lhcb2 in both November and December, plant hormone (DEGs) BRI1 and JAZ in November and IAA and ERF1 in December, and key DEGs of MAPK signal transduction FLS2, CHIB, and MPK4 in November and RBOH, MKK4_5, and MEKK1 in December in three shading groups and no-shade control plants responded to tea cold tolerance. The enhanced expression of light-harvesting photosystem I gene Lhca5, light-harvesting photosystem II gene Lhcb2, and mitogen-activated protein kinases MEKK1 and MPK4/6 enhance the cold-tolerance mechanism of C. sinensis. These comprehensive transcriptomic findings are significant for furthering our understanding of the genes and underlying regulatory mechanisms of shade-mediated low-temperature stress tolerance in horticultural crops.

Low temperature response index for monitoring freezing injury of tea plant.

Freezing damage has been a common natural disaster for tea plantations. Quantitative detection of low temperature stress is significant for evaluating the degree of freezing injury to tea plants. Traditionally, the determination of physicochemical parameters of tea leaves and the investigation of freezing damage phenotype are the main approaches to detect the low temperature stress. However, these methods are time-consuming and laborious. In this study, different low temperature treatments were carried out on tea plants. The low temperature response index (LTRI) was established by measuring seven low temperature-induced components of tea leaves. The hyperspectral data of tea leaves was obtained by hyperspectral imaging and the feature bands were screened by successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS) and uninformative variable elimination (UVE). The LTRI and seven indexes of tea plant were modeled by partial least squares (PLS), support vector machine (SVM), random forests (RF), back propagation (BP) machine learning methods and convolutional neural networks (CNN), long short-term memory (LSTM) deep learning methods. The results indicated that: (1) the best prediction model for the seven indicators was LTRI-UVE-CNN (R2 = 0.890, RMSEP=0.325, RPD=2.904); (2) the feature bands screened by UVE algorithm were more abundant, and the later modeling effect was better than CARS and SPA algorithm; (3) comparing the effects of the six modeling algorithms, the overall modeling effect of the CNN model was better than other models. It can be concluded that out of all the combined models in this paper, the LTRI-UVE-CNN was a promising model for predicting the degree of low temperature stress in tea plants.

Glycine-Induced Phosphorylation Plays a Pivotal Role in Energy Metabolism in Roots and Amino Acid Metabolism in Leaves of Tea Plant.

Phosphorylation is the most extensive post-translational modification of proteins and thus regulates plant growth. However, the regulatory mechanism of phosphorylation modification on the growth of tea plants caused by organic nitrogen is still unclear. In order to explore the phosphorylation modification mechanism of tea plants in response to organic nitrogen, we used glycine as the only nitrogen source and determined and analyzed the phosphorylated proteins in tea plants by phosphoproteomic analysis. The results showed that the phosphorylation modification induced by glycine-supply played important roles in the regulation of energy metabolism in tea roots and amino acid metabolism in tea leaves. In roots, glycine-supply induced dephosphorylation of proteins, such as fructose-bisphosphate aldolase cytoplasmic isozyme, glyceraldehyde-3-phosphate dehydrogenase, and phosphoenolpyruvate carboxylase, resulted in increased intensity of glycolysis and decreased intensity of tricarboxylic acid cycle. In leaves, the glycine-supply changed the phosphorylation levels of glycine dehydrogenase, aminomethyltransferase, glutamine synthetase, and ferredoxin-dependent glutamate synthase, which accelerated the decomposition of glycine and enhanced the ability of ammonia assimilation. In addition, glycine-supply could improve the tea quality by increasing the intensity of amino acids, such as theanine and alanine. This research clarified the important regulatory mechanism of amino acid nitrogen on tea plant growth and development through protein phosphorylation.

Effect of Shading on Physiological Attributes and Proteomic Analysis of Tea during Low Temperatures.

Shading is an important technique to protect tea plantations under abiotic stresses. In this study, we analyzed the effect of shading (SD60% shade vs. SD0% no-shade) on the physiological attributes and proteomic analysis of tea leaves in November and December during low temperatures. The results revealed that shading protected the tea plants, including their soil plant analysis development (SPAD), photochemical efficiency (Fv/Fm), and nitrogen content (N), in November and December. The proteomics analysis of tea leaves was determined using tandem mass tags (TMT) technology and a total of 7263 proteins were accumulated. Further, statistical analysis and the fold change of significant proteins (FC < 0.67 and FC > 1.5 p < 0.05) revealed 14 DAPs, 11 increased and 3 decreased, in November (nCK_vs_nSD60), 20 DAPs, 7 increased and 13 decreased, in December (dCK_vs_dSD60), and 12 DAPs, 3 increased and 9 decreased, in both November and December (nCK_vs_nSD60). These differentially accumulated proteins (DAPs) were dehydrins (DHNs), late-embryogenesis abundant (LEA), thaumatin-like proteins (TLPs), glutathione S-transferase (GSTs), gibberellin-regulated proteins (GAs), proline-rich proteins (PRPs), cold and drought proteins (CORA-like), and early light-induced protein 1, which were found in the cytoplasm, nucleus, chloroplast, extra cell, and plasma membrane, and functioned in catalytic, cellular, stimulus-response, and metabolic pathways. In conclusion, the proliferation of key proteins was triggered by translation and posttranslational modifications, which might sustain membrane permeability in tea cellular compartments and could be responsible for tea protection under shading during low temperatures. This study aimed to investigate the impact of the conventional breeding technique (shading) and modern molecular technologies (proteomics) on tea plants, for the development and protection of new tea cultivars.

Hyperspectral machine-learning model for screening tea germplasm resources with drought tolerance.

Drought tolerance and quality stability are important indicators to evaluate the stress tolerance of tea germplasm resources. The traditional screening method of drought resistant germplasm is mainly to evaluate by detecting physiological and biochemical indicators of tea plants under drought stresses. However, the methods are not only time consuming but also destructive. In this study, hyperspectral images of tea drought phenotypes were obtained and modeled with related physiological indicators. The results showed that: (1) the information contents of malondialdehyde, soluble sugar and total polyphenol were 0.21, 0.209 and 0.227 respectively, and the drought tolerance coefficient (DTC) index of each tea variety was between 0.069 and 0.81; (2) the comprehensive drought tolerance of different varieties were (from strong to weak): QN36, SCZ, ZC108, JX, JGY, XY10, QN1, MS9, QN38, and QN21; (3) by using SVM, RF and PLSR to model DTC (drought tolerance coefficient) data, the best prediction model was selected as MSC-2D-UVE-SVM (R2 = 0.77, RMSE = 0.073, MAPE = 0.16) for drought tolerance of tea germplasm resources, named Tea-DTC model. Therefore, the Tea-DTC model based on hyperspectral machine-learning technology can be used as a new screening method for evaluating tea germplasm resources with drought tolerance.

Dynamic changes in metabolic and lipidomic profiles of tea plants during drought stress and re-watering.

Tea (Camellia sinensis L.), as an evergreen plant, needs a humid environment. Water deficit would diminish tea yield and quality. We analyzed the dynamic changes in the metabolite and lipid profiling of tea leaves under various drought conditions and re-watering to determine the metabolic changes in tea leaves responding to drought challenges. In all, 119 metabolites showed substantial alterations in drought-stressed tea plants, including sugars and sugar alcohols, amino acids, and tricarboxylic acid cycle intermediates and lipids. We detected 29 lipids and they were classified into phosphatidylglycerol (PG), phosphatidic acid (PA), sulfoquinovosyl-diacylglycerol (SQDG), phosphatidylcholine (PC), lyso-phosphatidylcholine (LysoPC), and phosphatidylinositol (PI). The levels of sugar, sugar alcohol, and sugar precursors may change as a response to drought stress. Compared with these metabolites, the membrane lipids showed more dynamic changes in tea under drought stresses. Furthermore, metabolic recovery was only partial, with the majority of the examined metabolites exhibiting significantly different levels between samples from re-watered and well-watered tea plants. The findings also showed that comprehensive metabolomic and lipidomic approaches were efficient in elucidating the impacts of drought stress on tea plant metabolism. Our findings are valuable for understanding the mechanisms behind drought tolerance in tea plants from the metabolism perspective and utilizing the compounds to improve the drought tolerance of tea plants.

Red and Blue Light Affect the Formation of Adventitious Roots of Tea Cuttings (Camellia sinensis) by Regulating Hormone Synthesis and Signal Transduction Pathways of Mature Leaves.

Light is an important environmental factor which affects plant growth, through changes of intensity and quality. In this study, monochromatic white (control), red (660 nm), and blue (430 nm) light-emitting diodes (LEDs) were used to treat tea short cuttings. The results showed the most adventitious roots in blue light treated tea cuttings, but the lowest roots in that treated by red light. In order to explore the molecular mechanism of light quality affecting adventitious root formation, we performed full-length transcriptome and metabolome analyses of mature leaves under three light qualities, and then conducted weighted gene co-expression network analysis (WGCNA). Phytohormone analysis showed that Indole-3-carboxylic acid (ICA), Abscisic acid (ABA), ABA-glucosyl ester (ABA-GE), trans-Zeatin (tZ), and Jasmonic acid (JA) contents in mature leaves under blue light were significantly higher than those under white and red light. A crosstalk regulatory network comprising 23 co-expression modules was successfully constructed. Among them, the "MEblue" module which had a highly positive correlation with ICA (R = 0.92, P = 4e-04). KEGG analysis showed that related genes were significantly enriched in the "Plant hormone signal transduction (ko04075)" pathway. YUC (a flavin-containing monooxygenase), AUX1, AUX/IAA, and ARF were identified as hub genes, and gene expression analysis showed that the expression levels of these hub genes under blue light were higher than those under white and red light. In addition, we also identified 6 auxin transport-related genes, including PIN1, PIN3, PIN4, PILS5, PILS6, and PILS7. Except PILS5, all of these genes showed the highest expression level under blue light. In conclusion, this study elucidated the molecular mechanism of light quality regulating adventitious root formation of tea short cutting through WGCNA analysis, which provided an innovation for "rapid seedling" of tea plants.

Prediction of Drought-Induced Components and Evaluation of Drought Damage of Tea Plants Based on Hyperspectral Imaging.

Effective evaluation of physiological and biochemical indexes and drought degree of tea plant is an important technology to determine the drought resistance ability of tea plants. At present, the traditional detection method of tea drought stress is mainly based on physiological and biochemical detection, which is not only destructive to tea plants, but also time-consuming and laborious. In this study, through simulating drought treatment of tea plant, hyperspectral camera was used to obtain spectral data of tea leaves, and three machine learning models, namely, support vector machine (SVM), random forest (RF), and partial least-squares (PLS) regression, were used to model malondialdehyde (MDA), electrolyte leakage (EL), maximum efficiency of photosystem II (Fv/Fm), soluble saccharide (SS), and drought damage degree (DDD) of tea leaves. The results showed that the competitive adaptive reweighted sampling (CARS)-PLS model of MDA had the best effect among the four physiological and biochemical indexes (Rcal = 0.96, Rp = 0.92, RPD = 3.51). Uninformative variable elimination (UVE)-SVM model was the best in DDD (Rcal = 0.97, Rp = 0.95, RPD = 4.28). Therefore, through the establishment of machine learning model using hyperspectral imaging technology, we can monitor the drought degree of tea seedlings under drought stress. This method is not only non-destructive, but also fast and accurate, which is expected to be widely used in tea garden water regime monitoring.

Fulvic acid enhances drought resistance in tea plants by regulating the starch and sucrose metabolism and certain secondary metabolism.

The aim of this work was to gain insight into the molecular mechanisms underlying the effect of fulvic acid on drought-exposed tea plants. We performed proteomic analysis of fulvic acid-treated tea leaves from the target plants using tandem mass tag quantitative labeling technology and compared the results with those of a previous transcriptomic analysis. We identified 48 and 611 differentially abundant proteins in the leaves of tea plants treated with fulvic acid compared with the control under mild and severe drought, respectively. Comparative analysis showed that, under severe drought, 55 genes had similar expression patterns at the transcriptome and proteome levels, such as PAL, GBE, GBSS and bAS. Bioinformatic analysis revealed that those genes were mainly related to the starch and sucrose metabolism, phenylpropanoid biosynthesis and triterpenoid biosynthesis. SIGNIFICANCE: This study broadens the understanding of the molecular mechanisms underlying the improved drought resistance seen in tea plants in the presence of fulvic acid and provides a basis for further research on the genomics of drought tolerance in these plants. In addition, these findings could be used to develop new guidance strategies for improved drought management systems in tea plantation.

Genome-wide identification, characterization and expression analysis of the amino acid permease gene family in tea plants (Camellia sinensis).

Amino acid permeases (AAPs) are involved in transporting a broad spectrum of amino acids and regulating physiological processes in plants. In this study, 19 AAP genes were identified from the tea plants genome database and named CsAAP1-19. Based on phylogenetic analysis, the CsAAP genes were classified into three groups, having significantly different structures and conserved motifs. In addition, an expression analysis revealed that most of CsAAP genes were specifically expressed in different tissues, especially CsAAP19 was expressed only in root. These genes also were significantly expressed in the Baiye 1 and Huangjinya cultivars. Nitrogen treatments indicated that the CsAAPs were obviously expressed in root. CsAAP2, -6, -12, -13 and - 16 were significantly expressed at 6 d after the glutamate treatment, while the expression trend at 24 h after contained the ammonium. These results improve our understanding of the CsAAP genes and their functions in nitrogen utilization in tea plants.

Genome-Wide Analysis Reveals Stress and Hormone Responsive Patterns of JAZ Family Genes in Camellia Sinensis.

JAZ (Jasmonate ZIM-domain) proteins play pervasive roles in plant development and defense reaction. However, limited information is known about the JAZ family in Camellia sinensis. In this study, 12 non-redundant JAZ genes were identified from the tea plant genome database. Phylogenetic analysis showed that the 12 JAZ proteins belong to three groups. The cis-elements in promoters of CsJAZ genes and CsJAZ proteins interaction networks were also analyzed. Quantitative RT-PCR analysis showed that 7 CsJAZ genes were preferentially expressed in roots. Furthermore, the CsJAZ expressions were differentially induced by cold, heat, polyethylene glycol (PEG), methyl jasmonate (MeJA), and gibberellin (GA) stimuli. The Pearson correlations analysis based on expression levels showed that the CsJAZ gene pairs were differentially expressed under different stresses, indicating that CsJAZs might exhibit synergistic effects in response to various stresses. Subcellular localization assay demonstrated that CsJAZ3, CsJAZ10, and CsJAZ11 fused proteins were localized in the cell nucleus. Additionally, the overexpression of CsJAZ3, CsJAZ10, and CsJAZ11 in E. coli enhanced the growth of recombinant cells under abiotic stresses. In summary, this study will facilitate the understanding of the CsJAZ family in Camellia sinensis and provide new insights into the molecular mechanism of tea plant response to abiotic stresses and hormonal stimuli.

Transcriptomic and metabolomic profiling of Camellia sinensis L. cv. 'Suchazao' exposed to temperature stresses reveals modification in protein synthesis and photosynthetic and anthocyanin biosynthetic pathways.

To determine the mechanisms in tea plants responding to temperature stresses (heat and cold), we examined the global transcriptomic and metabolomic profiles of the tea plant cultivar 'Suchazao' under moderately low temperature stress (ML), severely low temperature stress (SL), moderately high temperature stress (MH) and severely high temperature stress (SH) using RNA-seq and high performance liquid chromatography tandem mass spectrometry/mass spectrometry (HPLC-MS/MS), respectively. The identified differentially expressed genes indicated that the synthesis of stress-resistance protein might be redirected to cope with the temperature stresses. We found that heat shock protein genes Hsp90 and Hsp70 played more critical roles in tea plants in adapting to thermal stress than cold, while late embryogenesis abundant protein genes (LEA) played a greater role under cold than heat stress, more types of zinc finger genes were induced under cold stress as well. In addition, energy metabolisms were inhibited by SH, SL and ML. Furthermore, the mechanisms of anthocyanin synthesis were different under the cold and heat stresses. Indeed, the CsUGT75C1 gene, encoding UDP-glucose:anthocyanin 5-O-glucosyl transferase, was up-regulated in the SL-treated leaves but down-regulated in SH. Metabolomics analysis also showed that anthocyanin monomer levels increased under SL. These results indicate that the tea plants share certain foundational mechanisms to adjust to both cold and heat stresses. They also developed some specific mechanisms for surviving the cold or heat stresses. Our study provides effective information about the different mechanisms tea plants employ in surviving cold and heat stresses, as well as the different mechanisms of anthocyanin synthesis, which could speed up the genetic breeding of heat- and cold-tolerant tea varieties.

Conserved MicroRNA Act Boldly During Sprout Development and Quality Formation in Pingyang Tezaocha (Camellia sinensis).

Tea tree [Camellia sinensis (L.) O. Kuntze] is an important leaf (sometimes tender stem)-using commercial plant with many medicinal uses. The development of newly sprouts would directly affect the yield and quality of tea product, especially significant for Pingyang Tezaocha (PYTZ) which takes up a large percent in the early spring tea market. MicroRNA (miRNA), particularly the conserved miRNAs, often position in the center of subtle and complex gene regulatory systems, precisely control the biological processes together with other factors in a spatio-temporal pattern. Here, quality-determined metabolites catechins, theanine and caffeine in PYTZ sprouts including buds (sBud), different development stages of leaves (sL1, sL2) and stems (sS1, sS2) were quantified. A total of 15 miRNA libraries of the same tissue with three repetitions for each were constructed to explore vital miRNAs during the biological processes of development and quality formation. We analyzed the whole miRNA profiles during the sprout development and defined conserved miRNA families in the tea plant. The differentially expressed miRNAs related to the expression profiles buds, leaves, and stems development stages were described. Twenty one miRNAs and eight miRNA-TF pairs that most likely to participate in regulating development, and at least two miRNA-TF-metabolite triplets that participate in both development and quality formation had been filtered. Our results indicated that conserved miRNA act boldly during important biological processes, they are (i) more likely to be linked with morphological function in primary metabolism during sprout development, and (ii) hold an important position in secondary metabolism during quality formation in tea plant, also (iii) coordinate with transcription factors in forming networks of complex multicellular organism regulation.

Physiological and iTRAQ-based proteomic analyses reveal the function of exogenous γ-aminobutyric acid (GABA) in improving tea plant (Camellia sinensis L.) tolerance at cold temperature.

BACKGROUND: Internal γ-Aminobutyric Acid (GABA) interacting with stress response substances may be involved in the regulation of differentially abundant proteins (DAPs) associated with optimum temperature and cold stress in tea plants (Camellia sinensis (L.) O. Kuntze). RESULTS: Tea plants supplied with or without 5.0 mM GABA were subjected to optimum or cold temperatures in this study. The increased GABA level induced by exogenous GABA altered levels of stress response substances - such as glutamate, polyamines and anthocyanins - in association with improved cold tolerance. Isobaric tags for relative and absolute quantification (iTRAQ) - based DAPs were found for protein metabolism and nucleotide metabolism, energy, amino acid transport and metabolism other biological processes, inorganic ion transport and metabolism, lipid metabolism, carbohydrate transport and metabolism, biosynthesis of secondary metabolites, antioxidant and stress defense. CONCLUSIONS: The iTRAQ analysis could explain the GABA-induced physiological effects associated with cold tolerance in tea plants. Analysis of functional protein-protein networks further showed that alteration of endogenous GABA and stress response substances induced interactions among photosynthesis, amino acid biosynthesis, and carbon and nitrogen metabolism, and the corresponding differences could contribute to improved cold tolerance of tea plants.

Zn, Ni, Mn, Cr, Pb and Cu in soil-tea ecosystem: The concentrations, spatial relationship and potential control.

Excessive accumulation of heavy metals in tea has certain health risk to the consumers. To discuss the spatial relationship between heavy metals in tea leaves and soil in a county scale, 74 samples of tea leaves and corresponding subsoil (15-30 cm) were collected in the tea plantations of Lishui, Nanjing, China. The total Zn, Ni, Mn, Cr, Pb and Cu in both tea leaves and soil samples, as well as pH value in soil were analyzed. The results of regression showed that the Mn and Cr in tea leaves were increased when the Mn and Cr in soil were at high levels, and higher pH decreased Zn, Ni, Mn and Cu contents in tea leaves. Moreover, distance to village and metal industry had negative impacts on the Mn level in soil. It is necessary to control the pH of soil in tea plantations which are close to villages or metal industries, as well as, to search more appropriate areas, where are far away from villages or metal industries, to plant tea should be taken into consideration. In addition, 17.57% of the samples have higher concentration of Pb than the maximum limits was found in tea plantation of Lishui. Heavy metals (Cr) standards regarding leafy vegetables is used for reference in this study, as there are no maximum levels of contaminants (MLC) in tea. It is significant to construct a targeted standard of heavy metals contents that could applicable throughout the world for reduce the health risks to the consumers.