Research article Special Issues

Altered Levels of Aroma and Volatiles by Metabolic Engineering of Shikimate Pathway Genes in Tomato Fruits

  • The tomato (Solanum lycopersicum) fruit is an excellent source of antioxidants, dietary fibers, minerals and vitamins and therefore has been referred to as a “functional food”. Ripe tomato fruits produce a large number of specialized metabolites including volatile organic compounds. These volatiles serve as key components of the tomato fruit flavor, participate in plant pathogen and herbivore defense, and are used to attract seed dispersers. A major class of specialized metabolites is derived from the shikimate pathway followed by aromatic amino acid biosynthesis of phenylalanine, tyrosine and tryptophan. We attempted to modify tomato fruit flavor by overexpressing key regulatory genes in the shikimate pathway. Bacterial genes encoding feedback-insensitive variants of 3-Deoxy-D-Arabino-Heptulosonate 7-Phosphate Synthase (DAHPS; AroG209-9) and bi-functional Chorismate Mutase/Prephenate Dehydratase (CM/PDT; PheA12) were expressed under the control of a fruit-specific promoter. We crossed these transgenes to generate tomato plants expressing both the AroG209 and PheA12 genes. Overexpression of the AroG209-9 gene had a dramatic effect on the overall metabolic profile of the fruit, including enhanced levels of multiple volatile and non-volatile metabolites. In contrast, the PheA12 overexpression line exhibited minor metabolic effects compared to the wild type fruit. Co-expression of both the AroG209-9 and PheA12 genes in tomato resulted overall in a similar metabolic effect to that of expressing only the AroG209-9 gene. However, the aroma ranking attributes of the tomato fruits from PheA12//AroG209-9 were unique and different from those of the lines expressing a single gene, suggesting a contribution of the PheA12 gene to the overall metabolic profile. We suggest that expression of bacterial genes encoding feedback-insensitive enzymes of the shikimate pathway in tomato fruits provides a useful metabolic engineering tool for the modification of fruits aroma and the generation of new combinations of tomato flavors.

    Citation: Vered Tzin, Ilana Rogachev, Sagit Meir, Michal Moyal Ben Zvi, Tania Masci, Alexander Vainstein, Asaph Aharoni, Gad Galili. Altered Levels of Aroma and Volatiles by Metabolic Engineering of Shikimate Pathway Genes in Tomato Fruits[J]. AIMS Bioengineering, 2015, 2(2): 75-92. doi: 10.3934/bioeng.2015.2.75

    Related Papers:

    [1] Liwei Chen, Jaslyn Lee, Wei Ning Chen . The use of metabolic engineering to produce fatty acid-derived biofuel and chemicals in Saccharomyces cerevisiae: a review. AIMS Bioengineering, 2016, 3(4): 468-492. doi: 10.3934/bioeng.2016.4.468
    [2] Edwige Arnold, Iness Hammami, Jingkui Chen, Sachin Gupte, Yves Durocher, Mario Jolicoeur . Overexpression of G6PDH does not affect the behavior of HEK-293 clones stably expressing interferon-α2b. AIMS Bioengineering, 2016, 3(3): 319-336. doi: 10.3934/bioeng.2016.3.319
    [3] George H McArthur IV, Pooja P Nanjannavar, Emily H Miller, Stephen S Fong . Integrative metabolic engineering. AIMS Bioengineering, 2015, 2(3): 93-103. doi: 10.3934/bioeng.2015.3.93
    [4] Tutuka Dlume, Nonso E. Nnolim, Uchechukwu U. Nwodo . Exiguobacterium acetylicum transformed poultry feathers into amino acids through an extracellular secretion of keratinolytic enzymes. AIMS Bioengineering, 2024, 11(4): 489-505. doi: 10.3934/bioeng.2024022
    [5] Adam B Fisher, Stephen S Fong . Lignin biodegradation and industrial implications. AIMS Bioengineering, 2014, 1(2): 92-112. doi: 10.3934/bioeng.2014.2.92
    [6] Bashir Sajo Mienda, Mohd Shahir Shamsir . Model-driven in Silico glpC Gene Knockout Predicts Increased Succinate Production from Glycerol in Escherichia Coli. AIMS Bioengineering, 2015, 2(2): 40-48. doi: 10.3934/bioeng.2015.2.40
    [7] Firoz Ahmed . Deciphering the gene regulatory network associated with anti-apoptosis in the pancreatic islets of type 2 diabetes mice using computational approaches. AIMS Bioengineering, 2023, 10(2): 111-140. doi: 10.3934/bioeng.2023009
    [8] Mingyong Xiong, Ping Yu, Jingyu Wang, Kechun Zhang . Improving Engineered Escherichia coli strains for High-level Biosynthesis of Isobutyrate. AIMS Bioengineering, 2015, 2(2): 60-74. doi: 10.3934/bioeng.2015.2.60
    [9] Murtaza Shabbir Hussain, Gabriel M Rodriguez, Difeng Gao, Michael Spagnuolo, Lauren Gambill, Mark Blenner . Recent advances in bioengineering of the oleaginous yeast Yarrowia lipolytica. AIMS Bioengineering, 2016, 3(4): 493-514. doi: 10.3934/bioeng.2016.4.493
    [10] Sayuri Yoshikawa, Kurumi Taniguchi, Haruka Sawamura, Yuka Ikeda, Ai Tsuji, Satoru Matsuda . Promising probiotics for the treatment of nephrotoxicity induced during immune-checkpoint therapy against cancers. AIMS Bioengineering, 2022, 9(3): 283-292. doi: 10.3934/bioeng.2022019
  • The tomato (Solanum lycopersicum) fruit is an excellent source of antioxidants, dietary fibers, minerals and vitamins and therefore has been referred to as a “functional food”. Ripe tomato fruits produce a large number of specialized metabolites including volatile organic compounds. These volatiles serve as key components of the tomato fruit flavor, participate in plant pathogen and herbivore defense, and are used to attract seed dispersers. A major class of specialized metabolites is derived from the shikimate pathway followed by aromatic amino acid biosynthesis of phenylalanine, tyrosine and tryptophan. We attempted to modify tomato fruit flavor by overexpressing key regulatory genes in the shikimate pathway. Bacterial genes encoding feedback-insensitive variants of 3-Deoxy-D-Arabino-Heptulosonate 7-Phosphate Synthase (DAHPS; AroG209-9) and bi-functional Chorismate Mutase/Prephenate Dehydratase (CM/PDT; PheA12) were expressed under the control of a fruit-specific promoter. We crossed these transgenes to generate tomato plants expressing both the AroG209 and PheA12 genes. Overexpression of the AroG209-9 gene had a dramatic effect on the overall metabolic profile of the fruit, including enhanced levels of multiple volatile and non-volatile metabolites. In contrast, the PheA12 overexpression line exhibited minor metabolic effects compared to the wild type fruit. Co-expression of both the AroG209-9 and PheA12 genes in tomato resulted overall in a similar metabolic effect to that of expressing only the AroG209-9 gene. However, the aroma ranking attributes of the tomato fruits from PheA12//AroG209-9 were unique and different from those of the lines expressing a single gene, suggesting a contribution of the PheA12 gene to the overall metabolic profile. We suggest that expression of bacterial genes encoding feedback-insensitive enzymes of the shikimate pathway in tomato fruits provides a useful metabolic engineering tool for the modification of fruits aroma and the generation of new combinations of tomato flavors.


    Abbreviations

    AAA = aromatic amino acids; VOCs = volatile organic compounds;

    DAHPS = 3-deoxy-D-arabino-heptulosonate7-phosphate synthase;

    CM = chorismate mutase; PDT = prephenatedehydratase; FDR = false discovery rate.

    1. Introduction

    Tomato fruits are an important source of vitamins, dietary fibers, minerals, and antioxidants in the human diet [1]. During the ripening stage, tomatoes produce a large number of specialized metabolites, including volatile organic compounds [2,3], which serve as key components of the tomato fruit flavor [4,5]. These compounds are utilized to attract seed dispersers [6], as part of the plant defense mechanisms against herbivores [7] and in plant-plant communication. They are derived from a diverse set of precursors including amino acids, fatty acids and carotenoids [4]. The taste of a tomato is a result of the interactions of sugars, acids and a set of 20-30 volatile compounds. Among the several hundred volatile compounds accumulating in ripe tomato fruits, almost all of those related to flavor are derived from the essential amino acids phenylalanine (Phe), leucine (Leu) or isoleucine (Ile) [8]. It has also been proposed that volatile compounds produced in the ripe tomato fruits act as sensory cues for nutritional and health values [4,6].

    One of the major biosynthetic pathways in plants is the shikimate pathway which leads to the synthesis of three aromatic amino acids (AAA) Phe, tyrosine (Tyr) and tryptophan (Trp) [9]. The shikimate pathway is a metabolic bridge between central carbon metabolism and specialized metabolism with regard to the regulation of AAA biosynthesis (Figure 1; [10,11]). In the last decade, many researches focused on exploring the enzymatic steps of the shikimate pathway, as well as the regulation of shikimate pathway enzymes. However, the carbon allocation towards the complex network of specialized metabolites that are derived from the AAA is not well understood [12,13]. One of the major regulatory mechanisms of flux through metabolic pathways is enzyme feedback inhibition loops, in which the end product metabolite of a given metabolic pathway feedback inhibits the activity of one of the enzymes of this pathway. Such enzyme feedback inhibition loops are common in metabolic pathways of amino acids [14], and are used to balance the metabolic homeostasis of the cell, to reduce toxicity and to promote plant development [15,16,17]. Plants containing modified, feedback-insensitive enzymes have been used to study the operation of metabolic pathways under uncontrolled conditions, and to produce plants tolerant to toxic combinations of amino acids or amino acid analogues, such as glyphosate (commercially known as Roundup; [18]). This also led to the identification of mutations in specific enzymes rendering them insensitive to feedback inhibition [14,17].

    Figure 1. Scheme of the shikimate and AAA biosynthesis pathways in plants. Dashed gray lines represent post-transcriptional regulation of the DAHPS (bacterial AroG) and CM/PDT (bacterial PheA) by the AAA. Dashed black lines represent multiple enzymatic steps. Solid gray line represents biosynthetic pathway suggested by Kaminaga et al. 2006.

    Overexpression of these feedback-insensitive genes allowed the plants to overcome the feedback inhibition of the native plant genes, “open” fluxes and change the carbon flow toward production of specialized metabolites. One such enzyme that was used encodes the first key enzyme of the shikimate pathway, namely, 3-Deoxy-D-Arabino-Heptulosonate 7-Phosphate Synthase (DAHPS; E. coli AroG) [19]. Another gene encodes a bi-functional Chorismate Mutase/Prephenate Dehydratase (CM/PDT; E. coli PheA), that converts chorismate via prephenate into phenylpyruvate (Figure 1, [20]). Previously, we overexpressed a bacterial gene encoding a mutant feedback-insensitive DHAPS (AroG209) in Arabidopsis thaliana plants as well as in tomato fruits. In general, overexpression of the bacterial feedback-insensitive AroG increased the synthesis of all AAA, causing considerable enhancements in the levels of multiple specialized metabolites in both Arabidopsis and tomato [19,21]. In Arabidopsis vegetative tissues, constitutive expression of the bacterial AroG209 caused massive metabolic changes and enhanced levels of phenylpropanoids, glucosinolates and phytohormones [19]. In tomato fruits, on the other hand, expression of AroG209 under a fruit specific E8 promoter led to enhanced levels of multiple volatile and nonvolatile compounds derived from phenylpropanoids, in addition to volatiles and carotenoids derived from terpenoids. These results demonstrate the complex network between those metabolic pathways [21]. Furthermore, expression of the bacterial feedback-insensitive AroG in Petunia × hybrida cv “Mitchell Diploid” as well as expression of the endogenous PhDAHP1, resulted in dramatically increased levels of Phe and fragrant benzenoid-phenylpropanoid volatiles [12,22].

    Phe is synthesized predominantly via the arogenate pathway [23], but the participation of the phenylpyruvate route in Phe biosynthesis has been previously suggested in Arabidopsis [24] and petunia [25]. The PheA gene converts chorismate via prephentate into phenylpyruvate. Previously, expression of a gene encoding a mutated E. coli feedback-insensitive PheA in Arabidopsis plants was shown to impact the synthesis of AAA and the specialized metabolites derived from them [24]. The PheA-expression lines had increased levels of specialized metabolites derived from Phe and Tyr, but reduced levels of specialized metabolites derived from Trp. These results imply regulatory cross-interactions between the flux of AAA biosynthesis from chorismate and their metabolism into various Phe specialized metabolites [24]. However, the possibility of using feedback-insensitive PheA in fragrant rich tissues such as tomato fruits or petunia petals has yet to be investigated. The significant variation between the specialized metabolites accumulating in Arabidopsis suggested that both feedback-insensitive AroG and PheA can function as excellent metabolic engineering tools for the production of specialized metabolites.

    We aimed to study the metabolic pathways involved in determining the tomato fruit flavor. The ultimate goal of our research was to identify genes that control the synthesis of the flavor volatiles and use this knowledge to produce a better-tasting tomato. We hypothesize that manipulating the DAHPS and CM/PDT key enzymes will have different effects on the carbon flux and will allow identification of metabolites that are usually below detection level. Our previous studies suggested that massive metabolic changes occur in the AroG209-9 transgenic tomatoes. Here we first tested the metabolic changes of tomato fruits expressing the PheA gene or both the AroG209-9 and PheA12 genes (PheA12//AroG209-9) crossed plants. We discovered that plants expressing both of the bacterial genes showed a unique metabolic profile that was predominantly impacted by expression of the AroG209-9 gene, while the PheA12 tomato line showed only minor metabolic differences. Our results suggest that this approach is suitable for altering tomato volatiles and aroma in a combinatorial manner. Furthermore, this method can be used for the discovery of new metabolic networks by increasing the abundance of compounds that are usually below detection levels in the wild type fruit.

    2. Materials and Methods

    2.1. Plant material and growth condition

    Flowers of greenhouse-grown tomato plants were marked at anthesis, and ripe red fruits were harvested approximately 48 days post anthesis. Eachbiological repeat was a mixture of 3-5 individual fruits. After harvesting, the peel and flesh (without the gel and seeds) were manually dissected and frozen in liquid nitrogen [26]. Homozygous plants of AroG209-9 and PheA12 were crossed and self-pollinated to generate the double transgenic cross line PheA12//AroG209-9 (F1 generation).

    2.2. Plasmid construction and tomato stable transformation.

    Genomic DNA was isolated from Escherichia coli (K-12 strain) and two genes, the 3-Deoxy-D-arabino-Heptulosonate 7-Phosphate Synthase isoform G (DAHPS; AroG) and the Chorismate Mutase/Prephenate Dehydratase (CM/PDT; PheA) were amplified and cloned as previously described [19,21,24]. The AroG and PheA genes were each fused to the tomato fruit-specific promoter E8 [27], whose expression is spatially and temporally regulated in mature tomato fruit [28]. The genes were fused at the 5’-end to a plastid targeting signal peptide originated from RUBISCO small subunit [29]. Primers are listed in Supplementary Table S1. Each of the chimeric genes was introduced into Agrobacterium tumefacies strain EHA-105 and used for plant transformation. Wild type tomato plants (M82 cultivar) were inoculated by submersing cotyledons in the transformed A. tumefacies culture as previously described [30,31]. Tomato transformation and genotyping were performed by Hazera Ltd (www.hazera.co.il/).

    2.3. LC-MS Metabolomics analysis

    Non-targeted metabolic analysis was performed using 500 mg of tomato peel and flesh, extracted in 80% methanol. Sample preparation and injection conditions were performed as previously described [32]. The analysis of the raw LC-MS (UPLC-qTOF-MS) data was performed using the XCMS software from the Bioconductor package (v. 2.1) for the R statistical language (v. 2.6.1) that performs chromatogram alignment, mass signal detection and peak integration [33]. XCMS was used with the following parameters: fwhm = 10.8, step = 0.05, steps = 4, mzdiff = 0.07, snthresh = 8, max = 1000. Injections of samples in the positive and negative ionization modes were performed in separate injection sets and pre-processing was done for each ionization mode independently. Differential mass ions were determined using a Student’s t-test (JMP software) and 17 differential metabolites were subsequently assigned. Principal Component Analysis (PCA) plot and ANOVA tests were performed by the T-MEV4 software [34,35]. A Student’s t-test analysis was performed on metabolites level using the JMP software (SAS).

    2.4. Detection and profiling of volatile aroma compounds using GC-MS

    GC-MS analysis of polar volatile compounds was carried out as previously described [21,36]. Briefly, a mix of 2-5 fruits (10 g) were harvested at the ripening stage (flesh and peel) and extracted with 30 ml MTBE:hexane (1:1) containing 2 mg isobutylbenzene as an internal standard. Following overnight incubation with shaking at 150 rpm, the extract was centrifuged at 10,500 g for 10 min and the supernatant was passed through a 0.2 μm filter. Samples were evaporated, using nitrogen, to a final volume of 200 μl before injection into a GC-MS instrument [19]. Identification of the compounds was based on a comparison of mass spectra and retention times with those of authentic standards (Sigma, Milwaukee, WI, USA) analyzed under similar conditions [21,37]. Statistical analysis was performed using the JMP software (SAS).

    2.5. Sensory panel and evaluation of samples

    A panel of 10 trained flavor specialists evaluated the aroma of samples by smelling the fruits as previously described [21]. Preliminary tests were carried out to improve the ability of the assessors to recognize odor changes and consistently quantify sensory properties. The panelists had been trained in the quantitative description of tomato attributes according to selection trials based on French norms (ISO8586-1, AFNOR V09-003). For each fruit sample, cut sections containing all fruit tissues were used for aroma evaluation by the panel. Values of individual fruits were ranked from zero (none) to 5 (very strong). The professional attributes considered were the following: acidic, floral, fresh, green, metallic musty, ripe, spicy, sweet and overall aroma intensity.

    3. Results

    3.1. Generating tomato fruits expressing feedback insensitive enzymes of the shikimate pathway

    Our aim was to direct the central carbon metabolism through the shikimate pathway into specialized metabolites derived from the AAA. Therefore, our focus was on the first enzyme of the shikimate pathway, DAHPS, and the first and the second enzymes of Phe biosynthesis, CM/PDT. However, these enzymes are post translationally feedback regulated by their AAA products (Figure 1). To overcome this regulation, we isolated, engineered and cloned two bacterial orthologues genes from Escherichia coli, and manipulated them to generate feedback insensitive isoforms of the genes. The E. coli, DAHPS gene, AroG, was point mutated in position 209. This mutation completely abolishes the Phe inhibition of the AroG allosteric site [38]. In the second enzyme, the E. coli bi-functional CM/PDT, PheA, the catalytic activities of the CM and PDT domains are located at amino acids 1-300 while the C-terminal domain is responsible for the allosteric feedback inhibition by Phe [39]. A truncated CM/PDT protein lacking the C terminus allosteric site retained the CM and PDT activities but did not exhibit feedback inhibition by Phe, and resulted in over accumulation of Phe [24,39]. A chimeric gene encoding the bacterial PheA under a tomato E8 fruit specific promoter was constructed and transformed into tomato plants. After selection of kanamycin resistant plants, the expression of the PheA gene in tomato fruit was verified by semi-quantitative RT-PCR (Figure S1). For each transgene, five independent transformation events were collected and subjected to LC-MS analysis, using both the negative and positive ion modes. This analysis revealed 5,723 and 7,125 mass signals, respectively. As shown in the PCA plots in Supplementary Figure S1, the most separated PheA transformation event was PheA12 in both the negative and positive ion modes (Figure S2A and S2B respectively). As shown in Table S2, Phe level was significantly induced by more than two fold in PheA6 and PheA12 while Tyr and Trp were not changed. In addition, we selected unknown mass signals that were significantly altered mainly in PheA6 and PheA12 lines. Based on these results, the PheA12 line was chosen for further work. As for the AroG gene, point mutation isoform 209, was fused to the E8 promoter and transformed in M82 tomato and transformation event number 9 was selected as previously characterized [21]. In order to detect the combined effect of the two shikimate pathway enzymes on tomato flavor, the AroG209-9 and PheA12 lines were crossed. AroG209-9, PheA12 and the cross PheA12//AroG209-9 line were analyzed and compared to the wild type (WT) M82 control.

    3.2. Effect of the AroG209-9 and PheA12 genes on the level of non-volatile metabolites in tomato fruit tissues

    Fleshy tomato fruits develop in several marked stages, each possessing a characteristic metabolic profile [40]. Dramatic metabolic alteration of central metabolites occurs during fruit maturation [21,41] followed by induction of fruit flavor [4]. Therefore, we focused our study on ripe red tomato, which has the highest level of flavor volatiles. Fruits were separated into two tissues: (i) peel, which is typically composed of multiple cell types, including epidermis, collenchyma, and some parenchyma, and (ii) flesh, which refers to the pericarp material from which the peel has been removed and therefore is predominantly composed of parenchyma and collenchyma [32]. The transgenic tomato plants did not exhibit any morphological differences, and their course of development, including color breaking and ripening time was similar to that of the control plants (data not shown). Ripe fruits were harvested from AroG209-9, PheA12, PheA12//AroG209-9 and WT plants and analyzed by an established high-resolution LC-MS-based metabolomics platform (negative ion-mode; [42]). To get a global view on the metabolic effects, the LC-MS mass signals dataset was analyzed using PCA plots. As shown in Figure 2, the samples clustered into four groups: (i) flesh samples of the AroG209-9 and PheA12//AroG209-9 lines; (ii) flesh samples of the PheA12 and WT lines; (iii) peel samples of the AroG209-9 and PheA12//AroG209-9 lines and, (iv) peel samples of the PheA12 and WT lines. The AroG209-9 and PheA12//AroG209-9 samples were closer to each other than to WT andPheA12 but still did not overlap. This suggested that the major metabolic effects in the transgenic fruits are due to the presence or absence of the AroG209 gene, while the PheA12 gene has a minor contribution to the overall metabolic profile.

    Figure 2. A PCA plot of LC-MS dataset obtained from the AroG209-9 PheA12 PheA12//AroG209-9, and wild type (WT) fruits. LC-MS analysis (negative ion mode) was performed on the peel and flesh tissues of the tomato red fruit (n = 5). PCA analysis was performed on the Log10 values of the mass signals (1, 402) using the T-MEV4 software. Transgenic plants: PheA12 (T3 generation) homozygote; AroG209-9 (T2 generation) homozygote, and PheA12//AroG209-9 (F1 heterozygote).

    To identify compounds whose levels differed between the transgenic lines, we compared the LC-MS mass signals to known chemical standards and libraries. As summarized in Table 1, 17 compounds were identified in the flesh and peel of the tomato fruits. In the flesh tissue (Table 1A), the levels of Phe and Tyr were increased in both AroG209-9 and PheA12//AroG209-9 compared to the WT fruits. Trp level was increased only in the AroG209-9 but not in the PheA12//AroG209-9 line. In addition, the level of isopropylmalic acid was increased in the flesh of both the AroG209-9 and PheA12//AroG209-9 lines. The levels of caffeic acid-hexose and dicaffeoylquinic acid were significantly decreased in the flesh of both AroG209-9 and PheA12//AroG209-9 transgene fruits.

    Table 1. List of the metabolites identified by LC-MS in the peel (A) and flesh (B) of the AroG209-9, Phe12, PheA12//AroG209-9 and WT tomato fruits. Numbers in bold font indicate statistically significant differences between each of the lines compared to the WT (mean ± standard error) using multiple comparison Dunnett's test with WT as control
    A) ES(-) m/z Molecular Formula Flesh-WT Flesh-PheA Flesh-AroG Flesh- Cross, PheA12//AroG209-9
    Name Mean ± sterr Mean ± sterr Mean ± sterr Mean ± sterr
    Phenylalanine (S) 164.071 C9H11NO2 1.00 ± 0.04 1.16 ± 0.03 7.68 ± 0.35 5.39 ± 0.19
    Tyrosine (S) 180.067 C9H11NO3 1.00 ± 0.11 1.23 ± 0.09 23.26 ± 0.87 9.54 ± 0.93
    Tryptophan (S) 203.083 C11H12N2O2 1.00 ± 0.07 1.16 ± 0.06 1.66 ± 0.18 1.38 ± 0.14
    2-Isopropylmalic acid (S) 175.061 C7H12O5 1.00 ± 0.18 1.43 ± 0.14 3.80 ± 0.40 4.62 ± 1.39
    3-Caffeoylquinic acid (S) 353.087 C16H18O9 1.00 ± 0.17 1.01 ± 0.04 1.47 ± 0.15 1.93 ± 0.53
    Acetoxyhydroxytomatine- FA 1152.539 (C52H85NO24)HCOOH 1.00 ± 0.36 1.02 ± 0.27 0.67 ± 0.18 1.18 ± 0.32
    Caffeic acid-hexose 341.089 C15H18O9 1.00 ± 0.08 1.21 ± 0.11 0.51 ± 0.04 0.44 ± 0.06
    Coumaric acid-hexose I 325.092 C15H18O8 1.00 ± 0.17 0.91 ± 0.18 0.85 ± 0.12 0.90 ± 0.11
    Coumaric acid-hexose II 325.092 C15H18O8 1.00 ± 0.22 1.09 ± 0.19 1.03 ± 0.16 1.22 ± 0.22
    Dicaffeoylquinic acid 515.119 C25H24O12 1.00 ± 0.10 1.07 ± 0.05 0.61 ± 0.11 0.61 ± 0.13
    Ferulic acid-hexose 355.104 C16H20O9 1.00 ± 0.20 1.09 ± 0.18 0.39 ± 0.09 1.14 ± 0.60
    Hydroxylated naringenin chalcone 287.057 C15H12O6 1.00 ± 0.13 1.84 ± 0.63 0.89 ± 0.11 1.35 ± 0.28
    Hydroxylated naringenin-hexose (Eriodictyol-hexose) 449.108 C21H22O11 1.00 ± 0.21 2.57 ± 1.14 1.39 ± 0.37 4.08 ± 1.12
    Naringenin chalcone-hexose 433.113 C21H22O10 1.00 ± 0.20 1.17 ± 0.33 0.15 ± 0.03 0.43 ± 0.12
    Naringenin hexose 433.113 C21H22O10 1.00 ± 0.12 1.48 ± 0.63 2.45 ± 0.61 3.38 ± 0.94
    Phloretin-di-C-hexose 597.1825 C27H34O15 1.00 ± 0.14 1.00 ± 0.13 0.47 ± 0.06 0.69 ± 0.12
    Tricaffeoylquinic acid 677.152 C34H30O15 1.00 ± 0.13 1.02 ± 0.28 0.96 ± 0.08 1.54 ± 0.67
    B) ES(-) Found m/z Molecular Formula Peel-WT Peel-PheA Peel-AroG Peel- Cross, PheA12//AroG209-9
    Name Mean ± sterr Mean ± sterr Mean ± sterr Mean ± sterr
    Phenylalanine (S) 164.071 C9H11NO2 1.00 ± 0.10 1.57 ± 0.11 15.94 ± 0.03 12.22 ± 0.85
    Tyrosine (S) 180.067 C9H11NO3 1.00 ± 0.12 1.45 ± 0.31 51.52 ± 5.90 21.51 ± 3.81
    Tryptophan (S) 203.083 C11H12N2O2 1.00 ± 0.17 1.11 ± 0.08 2.37 ± 0.09 1.68 ± 0.10
    2-Isopropylmalic acid (S) 175.061 C7H12O5 1.00 ± 0.11 0.82 ± 0.12 3.50 ± 0.70 3.86 ± 0.73
    3-Caffeoylquinic acid (S) 353.087 C16H18O9 1.00 ± 0.14 0.81 ± 0.04 2.48 ± 0.06 1.71 ± 0.45
    Acetoxyhydroxytomatine- FA 1152.539 (C52H85NO24)HCOOH 1.00 ± 0.13 0.96 ± 0.07 0.46 ± 0.15 0.52 ± 0.26
    Caffeic acid-hexose 341.089 C15H18O9 1.00 ± 0.17 1.00 ± 0.13 0.81 ± 0.10 0.57 ± 0.12
    Coumaric acid-hexose I 325.092 C15H18O8 1.00 ± 0.11 0.85 ± 0.09 9.21 ± 1.79 5.61 ± 0.88
    Coumaric acid-hexose II 325.092 C15H18O8 1.00 ± 0.11 1.00 ± 0.10 0.84 ± 0.08 0.57 ± 0.04
    Dicaffeoylquinic acid 515.119 C25H24O12 1.00 ± 0.10 1.28 ± 0.09 1.41 ± 0.08 1.00 ± 0.07
    Ferulic acid-hexose 355.104 C16H20O9 1.00 ± 0.20 0.80 ± 0.07 0.22 ± 0.06 0.21 ± 0.05
    Hydroxylated naringenin chalcone 287.057 C15H12O6 1.00 ± 0.09 1.08 ± 0.09 0.13 ± 0.02 0.16 ± 0.03
    Hydroxylated naringenin-hexose (Eriodictyol-hexose) 449.108 C21H22O11 1.00 ± 0.10 1.42 ± 0.13 1.46 ± 0.37 3.10 ± 1.14
    Naringenin chalcone-hexose 433.113 C21H22O10 1.00 ± 0.11 1.02 ± 0.07 0.34 ± 0.04 0.56 ± 0.23
    Naringenin hexose 433.113 C21H22O10 1.00 ± 0.16 1.12 ± 0.19 3.80 ± 1.05 10.01 ± 4.73
    Phloretin-di-C-hexose 597.1825 C27H34O15 1.00 ± 0.04 0.92 ± 0.02 0.34 ± 0.06 0.50 ± 0.07
    Tricaffeoylquinic acid 677.152 C34H30O15 1.00 ± 0.12 1.13 ± 0.10 3.23 ± 0.04 1.81 ± 0.10
     | Show Table
    DownLoad: CSV

    The levels of naringenin chalcone-hexose and phloretin-di-C-hexose were significantly decreased in the AroG209-9 while the levels of hydroxylated naringenin-hexose and naringenin hexose were significantly increased in PheA12//AroG209-9 only. None of the identified compounds were significantly changed in the flesh of the PheA12 line relative to the WT.

    In the peel tissue (Table 1B), the levels of all AAA, but most noticeably Phe and Tyr were increased in both the AroG209-9 and the PheA12//AroG209-9 lines, as well as isopropylmalic acid, coumaric acid-hexose-I, and tricaffeoylquininc acid. The levels of caffeic acid-hexose, ferulic acid hexose and phloretin-di hexose were significantly decreased in both AroG209-9 and PheA12//AroG209-9 lines. The levels of 3-caffeoylquinic acid, dicaffeoylquinic acid and naringenin chalcone-hexose were altered in the AroG209-9 only. The level ofnaringenin hexosehighly increased while coumaric acid hexose II deceased in PheA12//AroG209-9 only. Similarly to the flesh tissues (Table A1), none of the identified compounds were significantly changed in PheA12 line. Interestingly, the induction of AAA in both flesh and peel was higher in the AroG209-9 line compared to the PheA12//AroG209-9 line. In contrast, naringenin hexose levels were higher in the PheA12//AroG209-9 than in the AroG209-9 line. These findings suggest that although no major changes were found in the level of the identified compounds in the PheA12 line, its combined expression with AroG209-9 in the PheA12//AroG209-9 line does affect the metabolic flux.

    3.3. Effects of the expression of the AroG209-9, the PheA12 gene or both genes on volatile metabolites and fruit aroma

    Our aim was to detect the changes in the level of volatile compounds in ripe red fruits expressing the AroG209-9, the PheA12 gene or both genes. To that end, volatile metabolites accumulating in the tissue were extracted and analyzed by GC-MS as presented in Figure 3. The volatile compounds benzaldehyde, phenylacetaldehyde and phenylacetic acid were significantly increased in the AroG209-9and PheA12//AroG209-9 lines, compared to PheA12 and WT. However, the level of phenylacetaldehyde was higher in the PheA12//AroG209-9 line than in the AroG209-9 line. The levels of five other volatiles, eugenol (derived from p-coumaric acid; Figure 1), geranylacetone, β-ionone and limonene (derived from terpenoid) as well as benzaldehyde-4-methyl were reduced in theAroG209-9 line, compared to the PheA12 line and the WT. The PheA12//AroG209-9 line showed similar reduction of eugenol, geranylacetone, benzaldehyde-4-methyl and limonene, (derived from terpenoid) but no significant reduction in β-ionone and limonene compared to WT. Except for a slight increase in the eugenol and limonene levels, the PheA12 tomato line showed no differences in the identified volatile compounds relative to the WT tomato fruits.

    Figure 3. Internal pools of volatile compounds altered in red tomato fruits expressing the AroG209-9(AroG), PheA12 (PheA) or both genes PheA12//AroG209-9 (Cross) line. Fruit samples were analyzed by GC-MS. Bars on top of the histograms indicate standard errors (n = 4). Letters indicate statistically significant differences between the three lines and WT using ANOVA all pairs comparison Tukey-Kramer HSD test. The AroG209-9 data was previously published in Tzin et al. 2013.

    Tomato aroma was also evaluated by a sensory panel. This test provides human insight into the flavor experience, where sensory attributes, preferences, and decisions can be statistically related to the chemical components in foods [43]. The organoleptic test was performed by a group of professionals trained in the quantitative description of tomatoes. Whole red fruits from each line were cut in half and evaluated by the various panel members by sniffing the samples (Figure 4). As shown in Figure 4, the panel suggested that the “acidic” aroma attribute was increased in the PheA12//AroG209-9 tomato fruits. The floral aroma attribute was increased only in the AroG209-9tomato as previously described [21], but not in the PheA12 or PheA12//AroG209-9 fruits. In addition, it was suggested that the global aroma intensity of both PheA12 and PheA12//AroG209-9 tomato fruits was decreased as compared to the AroG209-9 tomato but not in comparison to the WT fruits. The other attributes were similar between the lines.

    Figure 4. A sensory profile of red ripe tomatoes expressing the AroG209-9(AroG), PheA12 (PheA) and both PheA12//AroG209-9 genes (Cross) line. Each attribute was scored on a scale between zero (none) to five (very strong). Bars on top of the histograms indicate standard errors (n = 4). Letters indicate statistically significant differences between the three lines and the WT using ANOVA all pairs comparison Tukey-Kramer HSD test. The AroG209-9 data was previously published in Tzin et al. 2013.

    4. Discussion

    The results presented in this study suggest that overexpression of feedback insensitive mutants of AroG209-9//PheA12 genes generated new tomato aroma composition (Figure 4). Previous research used ectopic expression of the petunia MYB transcription factor ODORANT1 to alter the expression of a set of genes related to Phe metabolism in tomato fruits including DAHPS, CM and Arogenate/Prephenate Dehydratase [44]. This increased metabolic activity, was coupled to a considerably enhanced flux through part of the phenylpropanoid pathway, but did not result in induction of Phe-derived flavor volatiles, suggesting that factors beyond substrate availability limit their synthesis such as post-transcriptional regulation [44]. We chose a different approach using bacterial feedback-insensitive variants of biosynthetic enzymes in order to bypass enzyme feedback inhibition loops of the shikimate and AAA biosynthesis pathways (Figure 1). In general, the expression of these genes resulted in alteration in the production of several volatile as well as non-volatile compounds and in changes in fruit aroma. This emphasizes the importance of using ectopic expression of feedback-insensitive enzymes for metabolic engineering.

    PheA12, which is a feedback-insensitive isoform of the first and second enzymatic steps of the Phe biosynthesis, caused only minor metabolic changes in tomato (Figure 2-4 and Table 1). Although PCA analysis showed separation between PheA12 and WT samples in either flesh or peel tissue (Figure 2), none of the identified compounds were differentially changed in this line (Table 1). This may be due to the small subset of metabolites that we were able to identify (17 non volatiles and 9 volatiles, see Table 1 and Figure 3, respectively). Volatile analysis suggested slight induction of eugenol and limonene compared to control plants, although the induction was not significant (Figure 4). Taken together, these results suggest that feedback-insensitive PheA does not play a major role in AAA metabolism and specialized metabolite derived from it in tomato fruits.

    On the other hand, AroG209-9, which is a feedback-insensitive form of the first enzymatic step of the shikimate pathway, caused massive metabolic changes in tomato (Figure2-4 and Table 1). Similar results were previously shown in Arabidopsis vegetative tissues and petuniapetals [12,21]. In order to enhance the carbon flux of AAA biosynthesis and direct it toward Phe derived volatiles, we crossed PheA12 and AroG209 tomato plants. The PCA plot separation showed close clustering of AroG209-9 with the PheA12//AroG209-9 samples of peel and flesh tissue however, the PCA samples did not overlap in either tissue (Figure2). Interestingly, several compounds had different levels in the AroG209-9 fruits compared to the crossed tomato line (Figure 3 and Table 1). This implies that tomato fruits expressing both the PheA12 and AroG209-9 genes have a metabolic profile that is predominantly, but not solely, impacted by the expression of the AroG209-9 gene.

    Because volatiles are derived from a diverse set of precursors, including amino acids, fatty acids and carotenoids, changes in the level of these different precursors can impact tomato aroma. Phe and Tyr were significantly increased in the flesh of both the AroG209-9 and PheA12//AroG209-9 lines, however the increase in their levels was higher in the AroG209-9 line than in the cross line: Phe 7.68 and 5.39 and Tyr 23.2 and 9.34, fold changes respectively (Table 1A). This effect was also seen in the levels of AAA in the peel (Phe 15.94 and 12.22, Tyr 51.52 and 21.51 and Trp 2.37 and 1.68, fold changes respectively (Table 1B). The overall changes in Phe and Tyr are much more pronounced than in Trp in the peel and flesh of both the AroG209-9 and the PheA12//AroG209-9 lines. As the levels of Phe and Tyr were higher in the AroG209-9 line (Table 1), the effect on the aroma profile of the fruit might be different in these two lines, mainly due to Phe-derived volatiles (Figure 3-4). A Phe derived volatile compound, phenylacetaldehyde, was higher in the cross line than in the AroG209-9 line (Figure 3). This may indicate additional regulatory metabolic steps of the Phe derived metabolites. In petunia, it’s been demonstrated that phenylacetaldehyde is synthesized via Phe and phenylpyruvate [45]. Therefore, we suggest that in tomatoes the high induction of phenylacetaldehyde levels in the PheA12//AroG209-9 line might be due PheA contribution that drives Phe synthesis via phenylpyruvate (Figure 1). Carotenoids-derived precursor’s β-ionone and geranylacetone [4] were reduced in both AroG209-9 and PheA12//AroG209-9 lines (Figure 3) supporting cross-talk between phenylpropanoid and carotenoid (terpenoid) derived volatiles [46].

    While several hundred volatiles have been identified in tomato, only a set of 20-30 volatile compounds actively contribute to tomato flavor; they are present in sufficient quantities to noticeably stimulate the olfactory system [4]. This threshold is determined by both the concentration of the substance and the organism’s ability to detect it [47]. Flavor thresholds vary markedly between individuals and can be greatly influenced by the way in which the volatile is presented. The differences in volatile compounds between the lines (Figure 3) can give a varied tomato flavor (Figure4).

    5. Conclusion

    This work demonstrates the potential for using feedback-insensitive enzymes to modify fruit flavor. Expression of feedback-insensitive enzymes in a combinatorial manner generates new aroma and affect flavor attributes. This approach is suitable for the enhancement of tomato volatiles and aromas as well as for the discovery of new metabolites and their biosynthesis and can be used in other plant species.

    Acknowledgments

    We would like to thank Meirav Gordon and Dr. Naomi Ben Dom from Hazera Ltd for tomato transformation and growth, and NatalieDror from Frutarom Industries, Ltd. who organized the sensory panel and flavor evaluation of tomato samples. We thank Dr. Hadas Zehavi, Dr. Moran Oliva and Monica Franciscus for careful and critical reading of this manuscript. The research in Prof. Galili’s lab was supported by grants from the Magnet Program of the Israeli Ministry of Industry, Trade and Labor and the Israeli Bio-TOV Consortium including Hazera Ltd., Evogene Ltd., Frutarom Ltd., Rahan Meristem (1998) Ltd. and Zeraim Gedera Ltd; The Bi-national Agriculture Research and Development (BARD) foundation; and AERI, the “Alternative Sustainable Energy Research Initiative” of the Weizmann Institute of Science. The research in Prof. Aharoni’s laboratory was also supported by research grants from the European Research Council (ERC) project SAMIT (FP7 program), Sir Harry Djanogly, CBE, Mrs. Louise Gartner, Dallas, TX the Tom and Sondra Rykoff Family Foundation and Mr. and Mrs. Mordechai Segal, Israel. G.G. is an incumbent of the Bronfman Chair in Plant Sciences. A.A. is an incumbent of the Peter J. Cohn Professorial Chair.

    Conflict of Interest

    All authors disclose to have no conflict of interests.

    Supplementary data

    Table S1. Primers used in the research.
    Gene name Origin Description Purpose Restriction site Oligonucleotides
    PheA FW PheA (from start codon) Cloning HinD III , SphI GCCAAGCTTATGGGCATGCCATCGGAAAACCCGTTACTGGC
    PheA RV PheA (no stop codon) Cloning EcoRI CCCCGGAATTCCAACGTCGTTTTCGCCGGAACCTG
    E8 tomato promoter FW E8 promoter Cloning KpnI GGGGTACCTAGAAGGAATTTCACGAAA
    E8 tomato promoter RV E8 promoter Cloning SalI ACGCGTCGACCTTCTTTTGCACTGTGAA
    PheA FW 375bp product size RT-PCR - CATGCCACTTGTCCAATTGTTG
    PheA RV 375bp product size RT-PCR - GCCAGTAACGGGTTTTCCGATG
    AroG FW 700bp product size RT-PCR - CATGCCACTTGTCCAATTGTTG
    AroG RV 700bp product size RT-PCR - TCGTCGTTCTGATAATTCATCA
     | Show Table
    DownLoad: CSV
    Table S2. List of the selected putative metabolites detected by LC -MS positive ion mode in five events of Phe transformation and WT tomato fruits. Numbers in bold font indicatestatistically significant differences between each of the lines compared to WT (mean ± standard error) using Student t-test.
     | Show Table
    DownLoad: CSV
    Figure S1. Semi-quantitative RT-PCR of PheA transformation events. Control, tomato fruits that were not transformed with the PheA gene. ASR1, Abscisic, Stress, Ripening gene used as positive control. RT, Reverse transcriptase.
    Figure S2. PCA plot of the five transformation events of PheA (T1) homozygous lines of tomato. Mass signals of chemical compounds were obtained by UPLC-QTOF-MS in the negative and positive ion modes (5, 723 and 7, 125 mass signals, respectively) from the tomato red fruit (n = 4-7; T1 generation). The PCA plot was done on the Log10 values and generated using the T-MEV4 software.
    [1] Ioannidi E, Kalamaki MS, Engineer C, et al. (2009) Expression profiling of ascorbic acid-related genes during tomato fruit development and ripening and in response to stress conditions. J Exp Bot 60: 663-678. doi: 10.1093/jxb/ern322
    [2] Petro-Turza M (1987) Flavor of tomato and tomato products. Food Rev Int 2: 309-351.
    [3] Buttery R, Takeoka G, Teranishi R, et al. (1990) Tomato aroma components: identification of glycoside hydrolysis volatiles. J Agr Food Chem 38: 2050-2053. doi: 10.1021/jf00101a010
    [4] Klee HJ, Giovannoni JJ (2011) Genetics and control of tomato fruit ripening and quality attributes. Annu Rev Genet 45: 41-59. doi: 10.1146/annurev-genet-110410-132507
    [5] Zanor MI, Rambla JL, Chaib J, et al. (2009) Metabolic characterization of loci affecting sensory attributes in tomato allows an assessment of the influence of the levels of primary metabolites and volatile organic contents. J Exp Bot 60: 2139-2154. doi: 10.1093/jxb/erp086
    [6] Goff SA, Klee HJ (2006) Plant volatile compounds: sensory cues for health and nutritional value? Science (New York, N Y ) 311: 815-819. doi: 10.1126/science.1112614
    [7] Dudareva N, Pichersky E, Gershenzon J (2004) Biochemistry of plant volatiles. Plant Physiol 135: 1893-1902. doi: 10.1104/pp.104.049981
    [8] Tikunov Y, Lommen A, De Vos R, et al. (2005) A novel approach for non targeted data analysis for metabolomics: large-scale profiling of tomato fruit volatiles. Plant Physiology: 1125-1137.
    [9] Vogt T (2010) Phenylpropanoid biosynthesis. Mol Plant 3: 2-20. doi: 10.1093/mp/ssp106
    [10] Tzin V, Galili G, Aharoni A (2012) Shikimate pathway and aromatic amino acid biosynthesis. eLS ohn Wiley & Sons Ltd.
    [11] Tzin V, Galili G (2010) New insights into the shikimate and aromatic amino acids biosynthesis pathways in plants. Mol Plant 3: 956-972. doi: 10.1093/mp/ssq048
    [12] Oliva M, Ovadia R, Perl A, et al. (2015) Enhanced formation of aromatic amino acids increases fragrance without affecting flower longevity or pigmentation in Petunia × hybrida. Plant Biotechnology Journal 13: 125-136. doi: 10.1111/pbi.12253
    [13] Colquhoun TA, Clark DG (2011) Unraveling the regulation of floral fragrance biosynthesis. Plant Signal Behav 6: 378-381. doi: 10.4161/psb.6.3.14339
    [14] Pratelli R, Pilot G (2014) Regulation of amino acid metabolic enzymes and transporters in plants. J Exp Bot 65: 5535-5556. doi: 10.1093/jxb/eru320
    [15] Voll LM, Allaire EE, Fiene G, et al. (2004) The Arabidopsis phenylalanine insensitive growth mutant exhibits a deregulated amino acid metabolism. . Plant Physiology 136: 3058-3069. doi: 10.1104/pp.104.047506
    [16] Pratelli R, Voll LM, Horst RJ, et al. (2010) Stimulation of nonselective amino acid export by glutamine dumper proteins. Plant Physiol 152: 762-773. doi: 10.1104/pp.109.151746
    [17] Galili G, Amir R (2013) Fortifying plants with the essential amino acids lysine and methionine to improve nutritional quality. Plant Biotechnol J 11: 211-222. doi: 10.1111/pbi.12025
    [18] Vivancos PD, Driscoll SP, Bulman CA, et al. (2011) Perturbations of amino Acid metabolism associated with glyphosate-dependent inhibition of shikimic Acid metabolism affect cellular redox homeostasis and alter the abundance of proteins involved in photosynthesis and photorespiration. Plant Physiology 157: 256-268. doi: 10.1104/pp.111.181024
    [19] Tzin V, Malitsky S, Ben Zvi MM, et al. (2012) Expression of a bacterial feedback-insensitive 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase of the shikimate pathway in Arabidopsis elucidates potential metabolic bottlenecks between primary and secondary metabolism. New Phytol 194: 430-439. doi: 10.1111/j.1469-8137.2012.04052.x
    [20] Baldwin GS, Davidson BE (1981) A kinetic and structural comparison of chorismate mutase/prephenate dehydratase from mutant strains of Escherichia coli K 12 defective in the PheA gene. Arch Biochem Biophys 211: 66-75. doi: 10.1016/0003-9861(81)90430-6
    [21] Tzin V, Rogachev I, Meir S, et al. (2013) Tomato fruits expressing a bacterial feedback-insensitive 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase of the shikimate pathway possess enhanced levels of multiple specialized metabolites and upgraded aroma. J Exp Bot 64: 4441-4452. doi: 10.1093/jxb/ert250
    [22] Langer KM, Jones CR, Jaworski EA, et al. (2014) PhDAHP1 is required for floral volatile benzenoid/phenylpropanoid biosynthesis in Petunia × hybrida cv ‘Mitchell Diploid’. Phytochemistry 103: 22-31. doi: 10.1016/j.phytochem.2014.04.004
    [23] Maeda H, Shasany AK, Schnepp J, et al. (2010) RNAi Suppression of Arogenate Dehydratase1 Reveals That Phenylalanine Is Synthesized Predominantly via the Arogenate Pathway in Petunia Petals. Plant Cell 22: 832-849. doi: 10.1105/tpc.109.073247
    [24] Tzin V, Malitsky S, Aharoni A, et al. (2009) Expression of a bacterial bi-functional chorismate mutase/prephenate dehydratase modulates primary and secondary metabolism associated with aromatic amino acids in Arabidopsis. Plant J 60: 156-167. doi: 10.1111/j.1365-313X.2009.03945.x
    [25] Yoo H, Widhalm JR, Qian YC, et al. (2013) An alternative pathway contributes to phenylalanine biosynthesis in plants via a cytosolic tyrosine:phenylpyruvate aminotransferase. Nature Communications 4.
    [26] Adato A, Mandel T, Mintz-Oron S, et al. (2009) Fruit-surface flavonoid accumulation in tomato is controlled by a SlMYB12-regulated transcriptional network. PLoS Genetics 5: e1000777. doi: 10.1371/journal.pgen.1000777
    [27] Deikman J, Kline R, Fischer RL (1992) Organization of Ripening and Ethylene Regulatory Regions in a Fruit-Specific Promoter from Tomato (Lycopersicon esculentum). Plant Physiology 100: 2013-2017. doi: 10.1104/pp.100.4.2013
    [28] Zhao L, Lu L, Zhang L, et al. (2009) Molecular evolution of the E8 promoter in tomato and some of its relative wild species. J Biosciences 34: 71-83. doi: 10.1007/s12038-009-0010-x
    [29] Shaul O, Galili G (1993) Concerted regulation of lysine and threonine synthesis in tobacco plants expressing bacterial feedback-insensitive aspartate kinase and dihydrodipicolinate synthase. Plant Molecular Biology 23: 759-768. doi: 10.1007/BF00021531
    [30] McCormick S (1991) Transformation of tomato with Agrobacterium tumefaciens; Lindsey K, editor: Kluwer.
    [31] Filati J, Kiser J, Rose R, et al. (1987) Efficient transfer of a glyphosphate tolerance gene into tomato using a binary Agrobacterium tumefaciens vector. Biotechnology 5: 726-730. doi: 10.1038/nbt0787-726
    [32] Mintz-Oron S, Mandel T, Rogachev I, et al. (2008) Gene expression and metabolism in tomato fruit surface tissues. Plant Physiology 147: 823-851. doi: 10.1104/pp.108.116004
    [33] Smith CA, Want EJ, O'Maille G, et al. (2006) XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal Chem 78: 779-787. doi: 10.1021/ac051437y
    [34] Saeed AI, Sharov V, White J, et al. (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34: 374-378.
    [35] Scholz M, Gatzek S, Sterling A, et al. (2004) Metabolite fingerprinting: detecting biological features by independent component analysis. Bioinformatics 20: 2447-2454. doi: 10.1093/bioinformatics/bth270
    [36] Spitzer-Rimon B, Marhevka E, Barkai O, et al. (2010) EOBII, a Gene Encoding a Flower-Specific Regulator of Phenylpropanoid Volatiles' Biosynthesis in Petunia. Plant Cell 22: 1961-1976. doi: 10.1105/tpc.109.067280
    [37] Davidovich-Rikanati R, Sitrit Y, Tadmor Y, et al. (2007) Enrichment of tomato flavor by diversion of the early plastidial terpenoid pathway. Nat Biotechnol 25: 899-901. doi: 10.1038/nbt1312
    [38] Hu C, Jiang P, Xu J, et al. (2003) Mutation analysis of the feedback inhibition site of phenylalanine-sensitive 3-deoxy-D-arabino-heptulosonate 7-phosphate synthase of Escherichia coli. J Basic Microb 43: 399-406. doi: 10.1002/jobm.200310244
    [39] Zhang S, Pohnert G, Kongsaeree P, et al. (1998) Chorismate mutase-prephenate dehydratase from Escherichia coli. Study of catalytic and regulatory domains using genetically engineered proteins. J Biol Chem 273: 6248-6253.
    [40] Carrari F, Baxter C, Usadel B, et al. (2006) Integrated analysis of metabolite and transcript levels reveals the metabolic shifts that underlie tomato fruit development and highlight regulatory aspects of metabolic network behavior. Plant Physiology 142: 1380-1396. doi: 10.1104/pp.106.088534
    [41] Osorio S, Vallarino JG, Szecowka M, et al. (2013) Alteration of the interconversion of pyruvate and malate in the plastid or cytosol of ripening tomato fruit invokes diverse consequences on sugar but similar effects on cellular organic acid, metabolism, and transitory starch accumulation. Plant Physiol 161: 628-643. doi: 10.1104/pp.112.211094
    [42] Rogachev I, Aharoni A (2012) UPLC-MS-based metabolite analysis in tomato. Methods Mol Biol (Clifton, N J ) 860: 129-144.
    [43] Baldwin E, Scott J, Einstein M, et al. (1998) Relationship between sensory and instrumental analysis for tomato flavor. J Am Soc Hortic Sci 906-915.
    [44] Dal Cin V, Tieman DM, Tohge T, et al. (2011) Identification of Genes in the Phenylalanine Metabolic Pathway by Ectopic Expression of a MYB Transcription Factor in Tomato Fruit. Plant Cell 23: 2738-2753. doi: 10.1105/tpc.111.086975
    [45] Kaminaga Y, Schnepp J, Peel G, et al. (2006) Plant phenylacetaldehyde synthase is a bifunctional homotetrameric enzyme that catalyzes phenylalanine decarboxylation and oxidation. J Biol Chem 281: 23357-23366. doi: 10.1074/jbc.M602708200
    [46] Zvi MMB, Shklarman E, Masci T, et al. (2012) PAP1 transcription factor enhances production of phenylpropanoid and terpenoid scent compounds in rose flowers. New Phytol 195: 335-345. doi: 10.1111/j.1469-8137.2012.04161.x
    [47] Baldwin EA, Scott JW, Shewmaker CK, et al. (2000) Flavor trivia and tomato aroma: Biochemistry and possible mechanisms for control of important aroma components. Hortscience 35: 1013-1022.
  • This article has been cited by:

    1. Delphine M. Pott, Sonia Osorio, José G. Vallarino, From Central to Specialized Metabolism: An Overview of Some Secondary Compounds Derived From the Primary Metabolism for Their Role in Conferring Nutritional and Organoleptic Characteristics to Fruit, 2019, 10, 1664-462X, 10.3389/fpls.2019.00835
    2. Archana Bhardwaj, Yogeshwar Vikram Dhar, Mehar Hasan Asif, Sumit K Bag, In Silico identification of SNP diversity in cultivated and wild tomato species: insight from molecular simulations, 2016, 6, 2045-2322, 10.1038/srep38715
    3. Ru Wang, Sangram Keshari Lenka, Varun Kumar, Kelem Gashu, Noga Sikron-Persi, Irena Dynkin, David Weiss, Avichai Perl, Aaron Fait, Michal Oren-Shamir, Metabolic Engineering Strategy Enables a Hundred-Fold Increase in Viniferin Levels in Vitis vinifera cv. Gamay Red Cell Culture, 2021, 69, 0021-8561, 3124, 10.1021/acs.jafc.0c08086
    4. Sagar S. Arya, Divyani D. Kumari, James E. Rookes, David M. Cahill, Sangram K. Lenka, Rice cell suspension culture as a model for producing high-value recombinant proteins and plant specialized metabolites, 2021, 0167-6857, 10.1007/s11240-021-02028-z
    5. Hadas Peled-Zehavi, Moran Oliva, Qingjun Xie, Vered Tzin, Michal Oren-Shamir, Asaph Aharoni, Gad Galili, Metabolic Engineering of the Phenylpropanoid and Its Primary, Precursor Pathway to Enhance the Flavor of Fruits and the Aroma of Flowers, 2015, 2, 2306-5354, 204, 10.3390/bioengineering2040204
    6. Itay Maoz, Rachel Davidovich Rikanati, Daniel Schlesinger, Einat Bar, Itay Gonda, Elena Levin, Tatiana Kaplunov, Noa Sela, Amnon Lichter, Efraim Lewinsohn, Concealed ester formation and amino acid metabolism to volatile compounds in table grape (Vitis vinifera L.) berries, 2018, 274, 01689452, 223, 10.1016/j.plantsci.2018.05.020
    7. Moran Oliva, Einat Bar, Rinat Ovadia, Avichai Perl, Gad Galili, Efraim Lewinsohn, Michal Oren-Shamir, Phenylpyruvate Contributes to the Synthesis of Fragrant Benzenoid–Phenylpropanoids in Petunia × hybrida Flowers, 2017, 8, 1664-462X, 10.3389/fpls.2017.00769
    8. Dhriti Kapoor, Savita Bhardwaj, Neeta Raj Sharma, Fragrance Stimulation Mechanisms of Flowers and their Regulation Under Environmental Constraints, 2023, 42, 0721-7595, 60, 10.1007/s00344-021-10555-4
    9. Oded Skaliter, Yarin Livneh, Shani Agron, Sharoni Shafir, Alexander Vainstein, A whiff of the future: functions of phenylalanine‐derived aroma compounds and advances in their industrial production, 2022, 20, 1467-7644, 1651, 10.1111/pbi.13863
    10. Silvia Massa, Riccardo Pagliarello, Alessia Cemmi, Ilaria Di Sarcina, Aureliano Bombarely, Olivia Costantina Demurtas, Gianfranco Diretto, Francesca Paolini, H. Earl Petzold, Mattijs Bliek, Elisabetta Bennici, Antonella Del Fiore, Patrizia De Rossi, Cornelis Spelt, Ronald Koes, Francesca Quattrocchio, Eugenio Benvenuto, Modifying Anthocyanins Biosynthesis in Tomato Hairy Roots: A Test Bed for Plant Resistance to Ionizing Radiation and Antioxidant Properties in Space, 2022, 13, 1664-462X, 10.3389/fpls.2022.830931
    11. Ru Wang, Sangram Keshari Lenka, Varun Kumar, Noga Sikron-Persi, Irena Dynkin, David Weiss, Avichai Perl, Aaron Fait, Michal Oren-Shamir, A Synchronized Increase of Stilbenes and Flavonoids in Metabolically Engineered Vitis vinifera cv. Gamay Red Cell Culture, 2021, 69, 0021-8561, 7922, 10.1021/acs.jafc.1c02119
    12. Yogesh K. Ahlawat, Manjeet Singh, K. Manorama, Nita Lakra, Abbu Zaid, Faisal Zulfiqar, Plant phenolics: neglected secondary metabolites in plant stress tolerance, 2023, 1806-9959, 10.1007/s40415-023-00949-x
    13. Anita Kumari, Varun Kumar, Rinat Ovadia, Michal Oren-Shamir, Phenylalanine in motion: A tale of an essential molecule with many faces, 2023, 68, 07349750, 108246, 10.1016/j.biotechadv.2023.108246
    14. Kun Ma, Yuan Yuan, Caochuang Fang, Mainstreaming production and nutrient resilience of vegetable crops in megacities: pre-breeding for terrace cultivation, 2023, 14, 1664-462X, 10.3389/fpls.2023.1237099
    15. Himani Singh, Pradeep Lamichhane, Ravi Gupta, Neha Kaushik, Eun Ha Choi, Nagendra Kumar Kaushik, Enhancing crop health and sustainability: exploring the potential of secondary metabolites and non-thermal plasma treatment as alternatives to pesticides, 2023, 1863-5466, 10.1007/s11816-023-00883-0
  • Reader Comments
  • © 2015 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(7738) PDF downloads(1376) Cited by(15)

Article outline

Figures and Tables

Figures(6)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog