Metabolomics and Transcriptomics Analyses Reveal Nitrogen

Article Cite This: J. Agric. Food Chem. XXXX, XXX, XXX−XXX

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Metabolomics and Transcriptomics Analyses Reveal Nitrogen Influences on the Accumulation of Flavonoids and Amino Acids in Young Shoots of Tea Plant (Camellia sinensis L.) Associated with Tea Flavor Hui Huang,† Qiuyang Yao,† Enhua Xia,† and Lizhi Gao*,†,‡

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†

Plant Germplasm and Genomics Center, Germplasm Bank of Wild Species in Southwestern China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China ‡ Institution of Genomics and Bioinformatics, South China Agricultural University, Guangzhou 510642, China S Supporting Information *

ABSTRACT: Tea-specialized metabolites contribute to rich flavors and healthy function of tea. Their accumulation patterns and underlying regulatory mechanism are significantly different under different nitrogen (N) conditions during adaptation stage. Here, we find that flavonoids associated with tea flavor are dominated by different metabolic and transcriptional responses among the four N conditions (N-deficiency, nitrate, ammonia, and nitric oxide). Nitrogen-deficiency tea plants accumulate diverse flavonoids, corresponding with higher expression of hub genes including F3H, FNS, UFGT, bHLH35, and bHLH36. Compared with N-deficiency, N-supply tea plants significantly increase proline, glutamine, and theanine, which are also associated with tea flavor, especially under NH4+-supply. As NH4+-tolerant species, tea plant exploits the adaptive strategy by substantial accumulation of amino acids including theanine to adapt excess NH4+, which attributes to, at least in part, efficient N transport and assimilation, and active protein degradation. A distinct divergence of N reallocation in young shoots of tea plant under different N sources contributes to diverse tea flavor. KEYWORDS: metabolite profiling, transcriptome, Camellia sinensis, flavonoids, amino acids, tea flavor

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forms (NH4+ and/or NO3−). For a perennial leaf-harvested crop, levels and forms of N not only regulate the biological processes of tea plant as other plant species but also impact directly and indirectly on the biosynthesis and metabolism of primary and secondary metabolites, leading to different contents and ratios, which finally determine the quality and flavor of tea. Previous studies indicated that a suitable application of N fertilizer could efficiently increase the production and improve the quality of tea.5−7 Compared with NO3− supply, NH4+ supply was found to more effectively enhance biosynthesis of catechins and free amino acids in tea plant leave and roots, resulting from significantly increased glutamine synthetase (GS) activity and expression of N transporter genes.6,8 Nitric oxide (NO), forming during N assimilation, can control NO3 − and NH4 + assimilation9,10 and also impacts the metabolites contents in woody plants.11 Chen et al. demonstrated that NO induced a rapid accumulation of L-theanine in roots and epigallocatechin gallate (EGCG) in leaves of tea plant (unpublished data). Although there is significant influence of N on tea plant, the regulatory mechanisms of differential accumulation of important metabolites related to tea flavor responding to different N levels and forms remain largely unknown. For NH4+-tolerance plant, the

INTRODUCTION Tea plant, Camellia sinensis L., is an important nonalcoholic beverage crop in the world and is beneficial in the prevention and treatment of chronic diseases. Tea-specialized metabolites, an important natural source of high-value chemicals, contribute to the rich flavors and healthy function of tea. Flavonoids are the major secondary metabolites with diverse biological activities in leaves of tea plants and play an important role in determining the quality of tea, especially catechins, which are the most important representative component of flavonoids constituting more than 70−80% of all polyphenol contents.1 The modifications and conversions (e.g., glycosylation, acylation, galloylation, polymerization, and fermentation) of flavonoids can affect their properties, such as stability, solubility, and biological activities,2 impacting the quality of tea. Besides flavonoids, free amino acids also have been recognized as essential constituents to qualify green tea and are the principal contributors to freshness and mellowness. Free amino acids that contribute to the formation of volatile organic compounds (VOCs) are responsible for the aroma of green tea by reacting with catechins and soluble sugars under heated conditions during tea-processing.3,4 Thus, the concentration and ratio of these metabolites significantly impact the taste and flavor of tea products and, indeed, the economic values of production. As a part of the adaptation mechanism, these metabolites contents are sensitive to biotic and abiotic cues. Nitrogen (N) is an essential environmental factor involved in many biological processes in terms of different levels and © XXXX American Chemical Society

Received: April 18, 2018 Revised: August 28, 2018 Accepted: August 31, 2018

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DOI: 10.1021/acs.jafc.8b01995 J. Agric. Food Chem. XXXX, XXX, XXX−XXX

Article

Journal of Agricultural and Food Chemistry

Figure 1. Impact of different N conditions on chlorophyll content, soluble sugars and protein, C, and N contents, and C/N ratio of young tea shoots. Different letters above the bars indicate significant differences at P < 0.05. in Porra et al.14 The soluble sugar and protein contents were determined from three biological replicates based on the methods of Irigoyen et al. (1992)15 and Bradford (1976),16 respectively. The carbon (C) and N contents were determined on the dried material from three biological replicates. These samples were dried at 80 °C until the weight was constant and ground through a 20-mesh screen. Then, the total N and C content were quantified with a Vario MAX CN analyzer (Elementar Analysensysteme GmbH, Hanau, Germany). Metabolomic Profiling Analysis. Freeze-dried sample powder was extracted in 75% methanol containing 1% formic acid. After 16,000g centrifugation at 4 °C and filtering, metabolite profiling was conducted using an ESI-QTOF/MS coupled to ACQUITY UPLC IClass system (Waters, Manchester, UK) and the ACQUITY UPLC BEH Amide Column 1.7 μm, 2.1 mm × 150 mm reverse phase analytical column. A blank (75% methanol) was run after every five samples to identify and minimize sample carryover. Mass spectrometry (MS) was recorded under both positive and negative electrospray ionization (ESI) modes. For metabolomics analysis, MassLynx software version 4.1 (Waters, Manchester, UK) was used for data acquisition and analysis. The peak annotation and normalization (total ion chromatogram normalization, TIC normalization) of MS raw data and metabolite identification through database search were performed by Progenesis QI software (Waters, Manchester, UK). The data were centered and Pareto-scaled to reduce the influence of noisy variables on the modeling results and analyzed through projections methods as principal component analysis (PCA) using Progenesis QI software and R software (http://www.r-project.org/; R package pcaMethods). The top 10 metabolites were selected by PCA according to a variable importance in projection (VIP) score. In GC−MS analysis, samples were extracted by homogenizing tissue with chloroform/methanol/water (1:3:1). After derivatization, methoximation, and silylation, samples were analyzed by using a Thermo Scientific Q Exactive GC hybrid quadrupole-Orbitrap mass spectrometer with three replicates. Sample chromatographic separation was obtained using a Thermo Scientific TRACE 1310 GC and a

early responses of tea plant to N conditions are systemic and less selective because of the need for the cells to triage constituents and induce metabolic readjustments to permit essential growth and development, prior to the induction of stress responses and leaf senescence.12,13 In the present study, we investigated the metabolomic and transcriptomic responses in young shoots of tea plants under the four N conditions for 7 days and then examined different signal pathways involved in accumulation patterns of flavonoids and amino acids that ultimately determine the tea flavor.

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MATERIALS AND METHODS

Plant Materials and Treatments. One-year-old tea plant (C. sinensis var. assamica) seedlings with 4−5 leaves, germinated from seeds of cultivar “Yunkang 10#”, were used in this study. HalfHoagland nutrient solution was used as hydroponic growth medium, and 1.5 mMCa (NO3)2, 1.5 mM (NH4)2SO4 and 10 μM sodium nitroprusside (SNP, NO donator) were used as N sources. N free nutrient solution was used as the control. Plants were planted in plastic bottles filled with fine sand and solutions. A space (about 3−5 cm) was kept between the planting board and the solution surface. The bottles were sealed with Parafile. Plants were grown in the greenhouse under natural daylight conditions for 4 and 7 days in June 2015 at Kunming, Yunnan Province, China. The solutions were refreshed every two days. Young shoots of one bud and two leaves (as for the harvested products) were collected from five individuals, considered as one sample, and each treatment consisted of six biological replicates. These materials were harvested and immediately frozen in liquid nitrogen. Chlorophyll, Soluble Sugars and Proteins, Carbon, and Nitrogen Content Determination. Chlorophylls were extracted and quantified with absorbance at 647 and 664 nm from three biological replicates. Chlorophyll content was calculated as reported B


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Figure 2. PCA of all detected peaks in young shoots of tea plants under different N conditions by LC−MS/MS. PCA score plots were derived from the relative contents of all detected metabolites by LC−MS/MS with six replicates per treatment. The heat maps of metabolites with the top ten most positive and negative loading from PC1 and PC2 are shown according to log2-transformed values of relative contents. Red and blue colors indicate higher or lower metabolite contents, respectively. The Y-axis designates the classes and names of metabolites. TraceGOLD TG-5SilMS 0.25 μm film capillary column. The relative content of metabolite was calculated as metabolite peak area normalized by the peak area of the internal standard, benzoic-d5 acid, and the fresh weight of the sample. The customized reference spectrum databases, including the National Institute of Standards and Technology and the Wiley Registry, were utilized for the identification and annotation of the metabolites recorded by GC− MS based on retention indices and mass spectral similarities. The data processed by MetAlign17 were corrected by the unique mass-to-charge ratio value of internal standard metabolites, and then the sum values of retention time was normalized by Z-score transformation for further analysis. Transcriptome Sequencing and Analysis. Two independent biological replicates of mixed RNA pools from five plants with equal amount RNA were used to sequence on the IlluminaHiseq 2000 platform. The clean reads were de novo assembled using Trinity

software18 and mapped to the reference sequence of tea plant (http:// www.plantkingdomgdb.com/tea_tree/) using tophat (version 2.0.9),19 setting allowed two mismatches and multihits ≤ 1, and resulting assemblies were merged together to give rise to the final transcriptome assembly using CD-HIT-EST v4.6.20 Homology searches were performed against databases (e-value ≤ 1 × 10−5), and gene expression analysis was the same as Yao et al.21 Differentially expressed genes (DEGs) were defined with a threshold of |log2FC| > 1 and false discovery rate (FDR) ≤ 0.001. Enrichment analyses of DEG sets in the GO database (FDR < 0.05) or KEGG pathways (P < 0.05) were performed using the OmicShare tools (www.omicshare.com/ tools). The raw transcriptome sequencing data are available in the NCBI Sequence Read Archive (SRA) under the BioProject accession ID PRJNA473228. qRT-PCR. qRT-PCR assay was performed as described by Yao et al.21 The EF1α gene was used as a reference in all experiments. C


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Figure 3. (A) Relationship of transcriptomes. (B) Significantly enriched KEGG pathways of all DEGs (P < 0.05). Primers used for qRT-PCR were listed in Table S1. The qRT-PCR results were performed from three repeat reactions for each gene and sample. Fold change was calculated by means of the formula 2−ΔΔCt. Statistical Analysis. Comparisons between different treatments and the control were made using the one-way ANOVA test using Sigmaplot 12.0 (Systat Software Inc.), and P < 0.05 was considered the significant difference. Integrative analysis of metabolome and transcriptome was performed by R software, and the relationships were visualized using Cytoscape (version 3.3.0).

of all detected peaks by LC−MS/MS separated samples by PC1 (69.6%) and PC2 (18.5%) (Figure 2 and Table S2). The accumulation profiles of these main metabolites in young shoots of tea plants treated under the four N conditions were considerably different from each other, especially between NO3 and NH4 (Figure 2). The separation of conditions along PC1 showed that NH4 contained higher contents of EGCG, which is the most abundant metabolite in this study, seven flavonoid glycosides, one glycerophospholipid, and one oligosaccharide (Figure 2 and Table S2) than ND and NO3, whereas ND and NO3 accumulated higher contents of two proanthocyanidins (PAs), three flavonoids, and one isoflavonoids and their derivatives. Additionally, NO3 contained higher levels of malvin, hydroxy-oxohexadecanoic acid, hydroxy-diisopropyl-dimethyl-biphenylquinone (HDDB), and 2-phenylethyl glucosinolate followed by NO. According to PC2, diverse metabolites were enriched in NO3. ND significantly accumulated diverse flavonoids (Figure 2). Our results showed that flavonoids were significantly overrepresented in these metabolites corresponding to separating four N treatments. Transcriptional Responses. The transcript profile comparisons were performed using the same experimental materials as metabolic profiling. A total of 73,391 unigenes (52.3 Mb of sequences) with a mean length of 712 bp and an N50 length of 1,284 bp were obtained (Table S3). Analysis of variance indicated that a large transcriptome reprogramming took place in response to different N conditions with 2,833 DEGs (FDR < 0.001, |log2FC| > 1) (Table S4). RNA-Seq data were validated by expression patterns of 14 genes through qPCR experiments. We found a high correlation between both RNA-Seq and qPCR data sets, thus corroborating the transcriptomic data (Figure S2). The hierarchical clustering of DEGs showed that NH4 is far from ND, NO3, and NO with a small correlation coefficient, indicating that the provision of NH4+ triggers a unique transcriptional response as compared with the other N conditions (Figure 3A). Then, GO enrichment analysis of DEGs indicated that the translation and secondary metabolic processes dominated the difference in biological processes among the four N conditions (Figure S3 and Table S4). Furthermore, KEGG enriched pathways of DEGs were mainly related to many secondary metabolite biosyntheses in which flavonoids biosynthesis was included with the smallest P-value

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RESULTS Chlorophyll, Soluble Sugars and Protein, Carbon, and Nitrogen Contents. The seedlings of C. sinensis var. assamica that were cultivated in the four N solutions (ND for nitrogen deficiency; NO3 for NO3−; NH4 for NH4+; and NO for nitric oxide) for 7 days showed marked differences in chlorophyll contents in young shoots. The chlorophyll contents were significantly higher in NH4 (7.53 mg g−1 DW) than NO3 (5.64 mg g−1 DW), ND (5.02 mg g−1 DW), and NO (4.90 mg g−1 DW) (Figure 1). However, the chlorophyll contents of young shoots were marginally different among four N treatments for 4 days (Figure S1). The soluble protein contents showed significantly higher in NO3 (6.24 mg g−1 FW) and NH4 (7.71 mg g−1 FW) than NO (4.04 mg g−1 FW), but the soluble sugars concentrations were slightly different among four N treatments (Figure 1). Unexpectedly, the total N content of shoots from NH4 was marginally higher than three other treatments. The total carbon (C) contents of shoots were similar among seedlings cultivated in the four N solutions (Figure 1). Hence, the C/N ratios were only a little lower in NH4 than those of ND, NO3, and NO. According to the results of chlorophyll and soluble protein contents (Figure 1 and Figure S1), tea plants showed different physiological symptoms while cultivated under different N conditions for 7 days, we chose the 7 day time-point for the following metabolomic and transcritpomic profiling analyses because it would capture the relatively early response of tea plant, as a NH4+-tolerance plant, to different N levels and forms rather than the later responses, which would be largely dominated by features associated with senescence and cell death. Metabolomic Profiling. The specific impact of different N conditions on the metabolomic profiling was investigated using untargeted metabolomics approach. A PCA of relative amount D


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Table 1. Co-upregulated and Co-downregulated DEGs in N-Supply (NO3, NH4, and NO) Compared with N-Free (ND)a Unigene ID

NCBI ID

Co-upregulated Ntea24031 XP_009604432 Ntea26817 ACM43505 Ntea40930 XP_002879769 Ntea4148 XP_002265200 Ntea4708 ACM43505 Ntea47162 XP_007038270 Ntea47285 XP_007038696 Ntea53820 XP_002270251 Ntea67127 XP_007213669 Co-downregulated Ntea16117 WP_045973632 Ntea17320 CBI26770 Ntea17978 CBL58464 Ntea19798 XP_008231923 Ntea20505 AIS71930 Ntea24556 XP_010025837 Ntea26155 XP_002278211 Ntea2776 XP_010665057 Ntea35900 XP_008223340 Ntea36919 AIU47276 Ntea38150 XP_008809771 Ntea47790 XP_012072392 Ntea48519 XP_011468177 Ntea50299 BAO87435 Ntea51297 CBI37905 Ntea59563 XP_012084367 Ntea71224 XP_010940856

description

ND

F-box/LRR-repeat protein polyphenoloxidase guanylate-binding family protein folate-biopterin transporter 7 Polyphenoloxidase disease resistance family protein/LRR family protein disease resistance family protein/LRR family protein shikimate O-hydroxycinnamoyltransferase leucine-rich repeat receptor-like protein chromatin target of PRMT1 protein nonfunctional NADPH-dependent codeinonereductase 2 ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit ribonuclease HI 23 kDa jasmonate-induced protein Proline-rich extensin-like protein EPR1 trans-resveratrol di-O-methyltransferase laccase-14-like heterogeneous nuclear ribonucleoprotein A3-like amaranthin-like lectin cell division control protein 2 homologue nonfunctional NADPH-dependent codeinonereductase 2-like anthocyanidin 3-O-glucosyltransferase 2-like putative membrane protein amidase amidase GPN-loop GTPase 2

NO3

NH4

NO

−1.87 −5.94 −1.20 −2.26 −5.80 −1.19 −2.59 −2.72 −2.77

0.67 2.10 0.24 1.03 2.18 0.25 0.59 1.99 0.69

0.13 2.49 0.91 0.48 2.34 0.52 1.59 0.20 1.49

1.07 1.35 0.05 0.76 1.28 0.42 0.40 0.53 0.60

3.94 3.68 2.77 1.93 2.41 2.44 2.10 3.25 7.57 6.13 2.29 4.12 2.35 2.83 3.04 2.66 3.27

−2.38 −1.49 −1.33 −0.53 −0.80 −0.88 −0.72 −1.98 −3.15 −1.93 −0.76 −1.44 −0.99 −0.64 −0.94 −0.97 −1.21

1.13 −0.44 −1.48 −0.70 −0.80 −0.48 −0.17 −1.02 −3.15 −1.98 −0.76 −0.77 −0.66 −1.13 −1.17 −1.23 −0.68

−2.70 −1.75 0.04 −0.70 −0.80 −1.07 −1.20 −0.25 −1.28 −2.22 −0.76 −1.91 −0.70 −1.06 −0.93 −0.46 −1.38

a

The values are log2-fold change of FPKM values of genes.

Seventeen structural genes and eight transcript factors (TFs) were identified as DEGs involved in flavonoids biosynthesis pathway (Figure 4B). Many of these orthologous DEGs were highly expressed in ND, including f lavanone 3-dioxygenase (F3H), f lavonoid 3′ hydroxylase (F3′H), f lavonoid 3′,5′hydroxylase (F3′5’H_b), UDPG-f lavonidsglucosyltransferase (UFGT), f lavone synthase (FNS), bHLH35, bHLH36, and MYB4. The other group of genes in this pathway, namely, chalcone synthase (CHS), F3′5’H_a, f lavonol synthase (FLS), anthocyanidin reductase (ANR), anthocyanidin synthase (ANS), dihydrof lavonol 4-reductase (DFR_b), and bHLH137, were upregulated in NO. In NH4, besides four up-regulated structural genes (4-coumarate-CoA ligase, 4CL; DFR_a, F3′H, and F3′5’H_b), the majority of identified DEGs encoding TFs were highly expressed, namely, MYB4, MYB86, bHLH79, bHLH92, and bHLH137. However, the bHLH116 was abundant in NO3. Then, we carried out network analysis of 42 flavonoids and orthologous 25 DEGs in the flavonoids biosynthesis pathway mentioned above. The interaction networks were organized between these genes and metabolites with R2 > 0.9 (Figure 4C and Table S5). In the networks, these most connected genes were F3H, FNS, UFGT_a, UFGT_b, bHLH35, and bHLH36, and they were expressed higher in ND than those of three other N conditions. N and C Metabolism. Compared with N-supply tea plant (NO3, NH4, and NO), N-deficiency tea plant (ND) significantly accumulated mannitol-1P, sucrose, galactinol, trehalose, and Myo-inositol, and contained slightly high contents of raffinose. By contrast, levels of maltose, sorbitol6P, and glucose-1P were low in ND. Among them, the

and FDR (Figure 3B). In addition, pairwise comparison found that DEGs between any two of four N nutrients also enriched in different pathways that were mainly occupied by secondary metabolites biosynthesis (Figure S4). These results demonstrate that the secondary metabolite biosynthesis, especially flavonoid biosynthesis, was significantly reprogrammed when tea plants were treated under different N conditions, in line with our analysis of metabolite profiles. In more specific analyses, we found that compared with Nfree condition (ND), nine co-upregulated and 17 co-downregulated DEGs exhibited the induction and repression in Napplication conditions (NO3, NH4, and NO), respectively (Table 1). Many DEGs exhibit exclusively responses to NH4+ and NO3− that are two important inorganic N sources in soils, in NH4 or NO3, and these DEGs are listed in Table S4. Regulation Metabolism Underlying Differentially Accumulated Flavonoids. In terms of the importance of flavonoids, we thus investigated the pattern of differentially accumulated flavonoids with fold change ≥2 between any two treatments (P < 0.05), the flavonoids belong to the top ten most positive and negative loadings from PC1 and PC2, their relevant DEGs (|log2FC| > 1, FDR < 0.001) among the four N sources, and their network relationships. Among peaks considered as differentially accumulated metabolites, 32 of them were identified as flavonoids. Of these, flavonoid glycoside accounted for the highest proportion (Table S2). Most of these flavonoids were abundant in ND and were low in NO (Figure 4A). Although the most common glycoside of flavonoid was kaempferol, some quercetins and other derivatives were also detected. E


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Figure 4. (A) Hierarchical cluster analysis of differentially accumulated flavonoids (fold change ≥2 between any two treatments with P < 0.05) according to log2-transformed values of relative contents in six replicates per treatment. (B) Expression profiles of DEGs (|log2FC| > 1, FDR < 0.001) involved in the flavonoid biosynthesis pathway. The color of grids in a row indicates FPKM values of the transcripts in ND, NO3, NH4, and NO, respectively. The number of columns indicates the number of transcripts. a, b, and c indicate different transcripts. In the top right corner, the cluster shows the expression profiling of genes encoding transcript factors under four treatments. (C) The connection network between 42 flavonoids and 25 DEGs mentioned above. Green indicates genes, red denotes catechin gallates, yellow indicates flavonoid glycosides, and pink denotes other metabolites.

concentration of maltose, a degradation product of starch, strongly increased in NH4 and NO relative to ND (Figure S5). Alanine (Aln), aspartate (Asp), asparagine (Asn), glutamate (Glu), serine (Ser), and GABA markedly increased in ND, with the exception for the Ser and Glu in NO, and cystine (Cys) and allantoin contents were slightly higher in ND compared with N-supply tea plant. Asn and Asp increase significantly in ND corresponding to markedly high expression level of the orthologous asparagine synthetase (ASN) and low expression level of Asp aminotransferase (AspAT) catalyzing the interconversion of Asp and Glu, whereas the contents of theanine, proline (Pro), glutamine (Gln), and citruline strongly increased in N-supply tea plant. The change fold (log2) of Pro content in NH4 relative to ND was more than seven. The contents of isoleucine (Ile), phenylalanine (Phe), and Smethylmethionine were marginally changed among the four N treatments. With regard to N forms, Pro, theanine, Gln, and Asn had markedly high levels in NH4 relative to NO3 and NO. There was more Glu in NO than in NH4 and more Pro in NO3 than in NO.

With regard to the N uptake and transport system, the four orthologous nitrate transporter or peptide transporter (NRT1/ PTR, also named NFP) genes including NPF2.7, NPF4.3, NPF7.3_a, and NPF7.3_b, were significantly highly expressed in NH4 and NO. Two orthologous NRT2 genes, NRT2.4 and NRT2.5, were abundant in NO3 and ND. One orthologous nitrate assimilation-related 2 (NAR2) subfamily gene, NRT3.2, was found and markedly up-regulated in NO3, almost 8-fold higher than that of NH4. The two orthologous ammonium transporter 1 (AMT1) genes were highly expressed in NH4. In addition, these orthologous genes encoding chloride channel (CLC)_b, NIN-LIKE (NLP)6, and NLP7 proteins were highly expressed in ND. Then, the CLC_a orthologous gene accumulated in NH4. Remarkably, 11 orthologous genes encoding the proton pumps vacuolar H+-ATPae (V-ATPase) were significantly highly expressed in NH4 as compared with three other N conditions (Table 2), and there was no exception for all 11 identified DEGs encoding V-ATPase. For N assimilation, the orthologous genes of nitrate reductase (NR), nitrite reductase (NiR)_b, and glutamate synthase F


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Journal of Agricultural and Food Chemistry Table 2. DEGs Encoding V-Type Proton ATPase, Proteasome, and Ubiquitin-Modifying Enzymesa Unigene ID

NCBI ID

annotation

V-Type Proton ATPase (V-ATPase) Ntea14616 XP_008548378 PREDICTED: V-type proton ATPase subunit B Ntea37555 XP_975026 PREDICTED: V-type proton ATPase 21 kDaproteolipid subunit Ntea38027 XP_008470054 PREDICTED: V-type proton ATPase subunit e 2-like Ntea53847 ABD98763 vacuolar ATPase G subunit-like protein Ntea54375 AAT01085 putative vacuolar ATP synthase subunit E Ntea55040 XP_011303601 PREDICTED: V-type proton ATPase subunit F isoform X2 Ntea5948 XP_004534551 PREDICTED: V-type proton ATPase 16 kDaproteolipid subunit Ntea65248 BAN20547 V-type proton ATPase catalytic subunit A Ntea67719 AAT01084 putative vacuolar ATP synthase subunit D Ntea6998 XP_001949116 PREDICTED: V-type proton ATPase subunit H Ntea7945 KDR18876 V-type proton ATPase subunit S1 Proteasome and Ubiquitin-Modifying Enzymes Ntea4720 XP_011868366 PREDICTED: proteasome subunit beta type-1 Ntea18184 KDR12542 proteasome subunit beta type-4 Ntea27877 XP_011565776 PREDICTED: 26S protease regulatory subunit 6A-B Ntea6747 XP_970194 PREDICTED: proteasome subunit beta type-5 Ntea68960 XP_008543695 PREDICTED: proteasome subunit alpha type-6-like Ntea17869 KDR19741 26S proteasome non-ATPase regulatory subunit 4 Ntea44643 KDR07186 proteasome subunit alpha type-2 Ntea53216 XP_001948523 PREDICTED: 26S protease regulatory subunit 4 Ntea6096 XP_972389 PREDICTED: 26S protease regulatory subunit 7 Ntea12474 KDR17906 ubiquitin carboxyl-terminal hydrolase isozyme L5 Ntea25690 XP_969056 ubiquitin carboxyl-terminal hydrolase 14 Ntea58100 Ntea58100 Ubiquitin-conjugating enzyme E2−17 kDa

ND

NO3

NH4

NO

−0.89 −0.61 −0.97 −1.20 −0.99 −0.76 −1.24 −0.93 −0.94 −0.67 −0.58

−0.60 −0.61 −0.33 −0.60 −0.49 −0.56 −0.47 −0.75 −0.60 −0.58 −0.58

2.38 1.83 2.27 3.00 2.46 2.08 2.90 2.61 2.47 1.93 1.74

−0.89 −0.61 −0.97 −1.20 −0.99 −0.76 −1.19 −0.93 −0.94 −0.67 −0.58

−0.66 −0.72 −0.60 −0.83 −0.82 −0.75 −0.73 −0.85 −0.69 −0.66 −0.62 −0.90

−0.66 −0.57 −0.52 −0.66 −0.66 −0.54 −0.73 −0.48 −0.61 −0.66 −0.55 −0.81

1.99 2.02 1.72 2.33 2.29 2.03 2.20 2.31 1.99 1.97 1.80 2.62

−0.66 −0.72 −0.60 −0.83 −0.82 −0.75 −0.73 −0.99 −0.69 −0.66 −0.62 −0.90

a

The values are log2-fold change of FPKM values of genes.

Figure 5. Expression pattern of DEGs and profile changes of metabolites related to N and C metabolism. Log2-fold change of relative contents of metabolites and FPKM values of DEGs are presented in associated pathways. Asterisks indicate values determined to be significantly different (P < 0.05).

glutamate dehydrogenase (GDH)_a, GDH_b, GOGAT_a, and GOGAT_c (Figure 5). Although almost all identified TCA cycle-related genes were highly expressed in NH4, several

(GOGAT)_b were markedly up-regulated in NO3. Hence, other orthologous genes involved in N assimilation were significantly highly expressed in NH4, including NiR_a, GS2, G


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UFGT_a, UFGT_b, bHLH35, and bHLH36 underlying the abundant flavonoids in ND. The bHLH35 has a high positive correlation coefficient with many genes in the phenylpropanoid and flavonoid biosynthesis pathways.29 The orthologous UFGT plays an important role in the glycosylation of flavonoids30 and is one of co-downregulated genes in Nsupply (Table 1). Additionally, two jasmonate (JA)/methyl jasmonate (MeJA)-induced orthologous genes encoding 23 kDa JA-induced protein and amaranthin-like lectin (LuALL)31 significantly accumulate in ND compared with N-supply tea plant (Table 1), which possibly suggests that JA/MeJA may be a contributing factor to the special physiological, metabolomics, and transcriptomic profiling of ND. JA has been shown to take part in flavonoid biosynthesis by inducing the expression of DFR, LAR, and UFGT.32 Indeed, NO3−, besides serving as a nutrient for plants, is a major signaling molecule and is involved in many pathways. Besides flavonoids, NO3−-supply tea plant accumulates high contents of HDDB and 2-phenylethyl glucosinolate, both of which are aromatic compounds,33,34 and fatty acids are one origin of VOCs.35 Those compounds might contribute to tea aroma. These results suggest that NO3− play an important role in many signal pathways, leading to the accumulation of abundant metabolites that contribute to diverse flavors of tea products. Interestingly, these metabolites accumulate at a median level in NO. Nitric oxide regulates many biological processes as a signaling molecule, including the flavonoid accumulation and phosphorus reutilization under NH4+ treatment.11,36 It is conceivable that there is a cross-talk between signaling pathway to regulate the accumulation of these secondary metabolites related to diverse tea flavors by NO3−, NH4+, and NO. Genes Related to N Assimilation, Transport, and Protein Degradation Involved in Different Amino Acid Accumulation Associated with Diverse Flavor of Tea. In tea plant, amino acid metabolism not only is the central role in N metabolism but also markedly impacts the tea flavor, especially theanine. Concentrations of theanine, Pro, and Gln are considerably higher in N-supply tea plants, especially in NH4+-fed plants, than that in ND. NH4+ as a sole N source, in addition to internal production of NH4+ by processes such as photorespiration, might prove toxic to the plant.37 The substantial increase of theanine and Pro accumulation in tea plants might be a strategy for the detoxification of excess NH4+.38 In many higher plants, Gln and Asn represent central intermediates in N metabolism and contribute to N transport.39 Our results indicate that N-supply and N-free tea plants individually choose Gln and Asn as the main intermediates for N transport and storage at the early stage of N adaption. The significant increase of Ala, a possible precursor of theanine synthesis,40 in ND, might suggest that N-deficiency impedes the theanine synthesis originated from Ala. Additionally, in Nsupply tea plants, the marked increase of citrulline indicates a higher activity of the ornithine−citrulline shuttle to transport NH4+ between mitochondria and chloroplast.41 In N-free tea plant, GABA responding to biotic and abiotic stress42 significantly increases. Similar with other plants, such as tobacco,43 several carbohydrates increase significantly under N-free (ND) in tea plants at the early stage of N adaption. Based on these results, we proposed a hypothesis that, at the early stage of N adaption, tea plant may employ specific N reallocation strategy to be acclimated in different N conditions

intermediates of TCA cycle, including succinate and succinylCoA, behaved similarly in young shoots under the four N conditions (Figure 5 and Table S2). The possibility of other metabolites related to TCA cycle displayed changes that cannot be excluded, which need further discerned in detail.

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DISCUSSION N Reallocation Occurs at an Early Stage of N Adaptation. Previous results showed that N starvation led to great decreases in the concentrations of chlorophyll and soluble protein in woody plants.6,22,23 In this study, a decrease of chlorophyll in ND and NO3 relative to NH4 indicates the repressed photosynthesis in ND and NO3 at an early stage of N adaption, consistent with a former study of Ruan et al.6 However, soluble protein levels are higher in NH4 and NO3 than ND and NO. Additionally, NH4 contains marginally larger total N concentration than other treatments. It is likely that N reallocation takes place in tea plant at the early stage of acclimation to the four N sources. The optimization of N allocation within leaves is a key adaptive mechanism under different N conditions.24 Mu et al.25 indicated that, under lowN stress, maize plants tended to invest relatively more N into bioenergetics to sustain electron transport and less N allocated to chlorophyll and light-harvesting proteins. Besides in shoots, N reallocation might also occur between shoots and roots.6,22 Howbeit, one orthologous gene encoding photosynthetic proteins RuBisCO is significantly highly expressed in ND, suggesting a regulated rearrangement of the photosynthetic system rather than a simple dismantling of the photosynthetic processed at an early stage of N-free. Flavonoids Are Dominated in Different Metabolic and Transcriptional Responses. Flavonoids contribute to both plant fitness and to the nutrition of consumers and are high concentrations in tea. The different modifications and conversions of flavonoids can affect their properties and determine the quality of tea. ND, NO3, NH4, and NO contain different contents of gallated catechins EGCG and polymerize products PAs, both which have close relationship with tea flavor. With the exception of galloylation and polymerization, the glycosylation of flavonoids is important for the transport and storage of many flavonoids and also can be important contributors to tea flavor.26 Two types of glycosylation, O- and C-linked glycosylation, are susceptible and resistant to hydrolysis, respectively.2 NH4, ND, and NO contained more C-linked flavonoid glycosides, such as orientin 2″-rhamnoside, 6″-caffeoylisoorientin, and luteolin 6-C-glucoside 8-C-arabinoside, than NO3. From a dietary perspective, C-linked glycosylation can enhance antidiabetic activity, while O-linked glycosylation improves antirotavirus and antiobesity activity.27,28 The findings in the present study suggest that the accumulation profiling of different classes and modifications of flavonoids are biased under the four N conditions, leading to different flavors and healthy functions of tea. The accumulation profiling of these flavonoids are regulated synergistically by key structural genes and TFs involved in the signaling pathway. NDeficiency and NH4+ simultaneously induce an increased expression of both structural genes and TFs. NO induces many highly expressed structural genes. However, these structural genes and TFs are lowly expressed in NO3 as compared with the three other N conditions. Our results demonstrate that different N conditions regulate flavonoid biosynthesis in tea plants by means of dissimilar signal pathways. The increased levels of the most connected hub genes encoding F3H, FNS, H



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rather than simply result in the availability of the amino acid building blocks. As a NH4+-tolerance and -preference species, tea plants are able to well adapt to NH4+ over NO3−, which may be of special interest with regard to the increased growth and product quality of green tea concerning its effect on free amino acids. Our results and Ruan et al.7 showed that NH4+-supply tea plants significantly increased theanine, Pro, and Gln at the early stage, and almost all free amino acids after more than 20 weeks treatment, respectively, than NO3−-supply tea plants. Many signal pathways are involved in the marked increase of free amino acids in NH4 than NO3. First, we find that N uptake and transport genes express differentially between the two N conditions. NH4+ and NO3− induce highly expressed NPF genes and NRT2/NAR2 genes in shoots of tea plants, respectively. The NPF members and NRT2/NAR2 members can function as components of low-affinity transport system (LATS) and high-affinity transport system (HATS) during N uptake, acting when the external NO3− concentration is high and low, respectively.44 The result suggests that there is a low rate of NO3− absorption in NO3 and an obvious nitrification in NH4. Notably, the two family genes have been reported to also have key functions in NO3− allocation and serve as a longdistance transport of NO3− and diverse range of substrates, including peptides and amino acids.45,46 In tea plants, theanine content in tea plants considerably varies among different tissues.40 The different transport of theanine across different tissues may be involved in the change of theanine content in shoots. Additionally, previous studies showed that the VATPase and CLCs are mainly responsible for vacuole NO3− and amino acids short-distance transport (between vacuole and cytosol), as the main channel and power.47,48 The significant increase of expression of 11 V-ATPase and CLC_b in NH4 is observed compared to NO3. Second, NH4+ is assimilated principally via the glutamine synthetase-glutamine-oxoglutarate aminotransferase (GS-GOGAT) pathway, including individual iso-enzymes of GS, GOGAT, and GDH.49 Tea plants increase root GS activity substantially under conditions of high demand due to NH4+ supply.6 Tea plants also notably increase the expression of GS, GOGAT, and GDH in shoots, showing a high activity of the GS-GOGAT pathway under NH4+ treatment. Third, with the exception of NO3− reduction origin, NH4+ also comes from amino acid and protein recycling. The significant impact of N sources on protein degradation is witnessed by the increased abundance of genes encoding protease, together with ubiquitin-modifying enzymes in NH4 compared with NO3. In fact, the activation of antioxidant defense signaling for modulation of ROS homeostasis has been frequently considered a prerequisite for NH4+ tolerance.50 As a NH4+tolerance species, tea plants activate antioxidant defense by triggering proteolytic degradation during autophagy, which depends on a ubiquitin−proteasome system under NH4+condition. Furthermore, three co-upregulated genes encoding LRR proteins involved in protein degradation51 also expressed highly in NH4. Thus, it is reasonable to assume that an exquisite regulation of gene expression related to N assimilation, transport, and protein degradation together contributes to the amino acid metabolism in NH4+-supply tea plants. At present, our results demonstrate that the global metabolomic and transcriptomic reprogramming plays a key role in the acclimation of tea plants to different N conditions and thus contributes to diverse tea flavors.

Article

ASSOCIATED CONTENT

* Supporting Information S

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jafc.8b01995. Chlorophyll contents of young shoots of tea plants treated with different N conditions for 4 days; validation of transcriptome data by qPCR; GO enrichment (biological processes) of all DEGs; enrichment analysis of DEGs between any two of four N nutritious; metabolites and transcripts profiling of glycolysis; summary of transcriptomes; detail of metabolite profiling analysis (PDF) qPCR primers; all peaks and identified metabolites in this study; DEGs and enrichment analysis; information on DEGs (XLS)

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel: +86-871-65223277. ORCID

Hui Huang: 0000-0003-1212-496X Lizhi Gao: 0000-0002-6893-3064 Funding

This work was supported by the Project of Innovation Team of Yunnan Province, Top Talents Program of Yunnan Province (20080A009), Hundreds of Oversea Talents Program of Yunnan Province, and National Science Foundation of China (U0936603) to L.Z.G. and the National Science Foundation of China (31200515, 31501025) and Surface Project of Natural Science Foundation of Yunnan Province (2012FB179) to H.H. Notes

The authors declare no competing financial interest.

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REFERENCES

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Metabolomics and Transcriptomics Analyses Reveal Nitrogen

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