Abstract

   Tomato plants are attacked by a variety of herbivore pests and among
   them, the leafminer Tuta absoluta, which is currently a major threat to
   global tomato production. Although the commercial tomato is susceptible
   to T. absoluta attacks, a better understanding of the defensive plant
   responses to this pest will help in defining plant resistance traits
   and broaden the range of agronomic levers that can be used for an
   effective integrated pest management strategy over the crop cycle. In
   this study, we developed an integrative approach combining untargeted
   metabolomic and transcriptomic analyses to characterize the local and
   systemic metabolic responses of young tomato plants to T. absoluta
   larvae herbivory. From metabolomic analyses, the tomato response
   appeared to be both local and systemic, with a local response in
   infested leaves being much more intense than in other parts of the
   plant. The main response was a massive accumulation of phenolamides
   with great structural diversity, including rare derivatives composed of
   spermine and dihydrocinnamic acids. The accumulation of this family of
   specialized metabolites was supported by transcriptomic data, which
   showed induction of both phenylpropanoid and polyamine precursor
   pathways. Moreover, our transcriptomic data identified two genes
   strongly induced by T. absoluta herbivory, that we functionally
   characterized as putrescine hydroxycinnamoyl transferases. They
   catalyze the biosynthesis of several phenolamides, among which is
   caffeoylputrescine. Overall, this study provided new mechanistic clues
   of the tomato/T. absoluta interaction.

   Keywords: tomato, leafminer, Tuta absoluta, phenolamide, metabolomics,
   transcriptomics, herbivory

1. Introduction

   The co-evolution of plants and insect herbivores over hundreds of
   millions of years has shaped a complex and multifaceted defense system
   of plants against herbivory. Plant defense strategies include
   morphological and chemical, constitutive and inducible, local and
   systemic processes, driven by sophisticated pest detection and
   information signaling [[38]1,[39]2,[40]3,[41]4,[42]5]. In agronomy,
   understanding and taking advantage of these plant defense mechanisms
   are of major interest in order to develop pest control strategies
   alleviating or suppressing the use of pesticides.

   Tomato is a major horticultural crop producing over 180 million tons of
   fruit worldwide [[43]6]. Tomato plants can be attacked by a large array
   of herbivorous insects, including sap-feeding, chewing and leaf-mining
   pests. Among the latter, the South American tomato pinworm, Tuta
   absoluta (Meyrick) (Lepidoptera: Gelechiidae), is one of the main
   threats due to its recent and rapid expansion in the last 15 years from
   South America to the main world production areas. The pest can cause up
   to 80–100% yield losses when no control method is used
   [[44]7,[45]8,[46]9]. Recently, there have been major advances in the
   management of T. absoluta, allowing the deployment of several
   biocontrol levers to limit the impact of this pest, including essential
   oil based-pesticides, pheromone trapping and biological control under
   integrated pest management (IPM) practices [[47]7]. Despite strong
   fundamental advances in the understanding of tomato resistance traits
   against T. absoluta, this knowledge still needs to be improved before
   it can be converted into new practices in IPM strategies.

   Commercial tomatoes (Solanum lycopersicum L.) are highly susceptible to
   T. absoluta but recent screenings on tomato populations have led to
   identify moderately resistant cultivars [[48]10,[49]11,[50]12,[51]13].
   Some resistance traits have, however, been identified in wild tomato
   relatives. They correlate with the constitutive content of several leaf
   chemicals, namely methyl-ketones, sesquiterpenes and acyl sugars,
   produced by glandular trichomes, opening the door for genetic programs
   to introgress this resistance trait into cultivated tomatoes
   [[52]14,[53]15,[54]16]. In addition, during T. absoluta infestation,
   tomato plants can induce defense mechanisms mediated by the
   accumulation of defense enzymes (polyphenol oxidase and peroxidase) at
   the insect feeding site as well as in distant organs [[55]17] and also
   by changes in the composition of the blend of volatile organic
   compounds (VOCs) emitted by the infested plants [[56]18,[57]19,[58]20].
   Interestingly, some of these induced VOCs were found to attract natural
   enemies of T. absoluta, such as Macrolophus pygmaeus Rambur,
   Macrolophus basicornis Stal, Engytatus varians Distant,
   Campyloneuropsis infumatus Carvalho and Nesidiocoris tenuis Reuter,
   suggesting a functional indirect defense strategy
   [[59]21,[60]22,[61]23]. In addition, very recently, the (Z)-3-hexenyl
   propanoate, a green leaf volatile commonly emitted by plant submitted
   to herbivory, was found to induce a defense mechanism in tomato under
   lab conditions, by significantly impairing T. absoluta infestation, via
   both antixenosis and antibiosis mechanisms [[62]24]. Those authors
   demonstrated also the efficiency of (Z)-3-hexenyl propanoate
   application under a commercial greenhouse condition, thus defining a
   first proof of concept of the efficiency of the tomato defense
   induction strategy for the control of T. absoluta [[63]25].

   Since a plant’s response is usually pest specific, characterizing the
   response of tomato defense to T. absoluta herbivory seems essential to
   target the key metabolic pathways, metabolites or genes that are able
   to impact this pest. To the best of our knowledge, only one attempt was
   conducted through nuclear magnetic resonance (NMR) analyses with a
   targeted metabolomics approach following 18 metabolites. It led to
   identifying the accumulation of trigonellin in infested plants and
   highlighted a higher content of some phenylpropanoids in a tomato
   accession exhibiting less sensitivity to the T. absoluta herbivory
   [[64]26].

   In the present study, our main objective was to characterize the
   metabolic responses of young tomato plants to the herbivory of T.
   absoluta larvae. We combined untargeted metabolomic and transcriptomic
   analyses on several plant parts, reflecting both local and systemic
   responses, and at different harvest times. This multi-omics approach
   allowed a comprehensive analysis of the tomato response to T. absoluta
   herbivory and enabled the functional identification of tomato genes
   involved in plant defense.

2. Results

2.1. Metabolomics Analysis of Spatio-Temporal Responses of Tomato to
Herbivory

   In order to address the question of spatio-temporal induction of the
   tomato soluble defense against T. absoluta herbivory, we conducted an
   untargeted metabolomics study of five vegetative parts of tomato plants
   submitted or not to T. absoluta herbivory for 4 and 7 days. A total of
   2427 features were detected among all the samples. A two-way analysis
   of variance (ANOVA) conducted on the feature ion intensities of the
   datasets at 4 and 7 days revealed that the organ nature impacted
   significantly (p < 0.05) around 90% of the detected features
   ([65]Figure 1A; [66]Supplementary Data S1). T. absoluta herbivory
   affected only 190 and 148 features after 4 and 7 days, respectively,
   which represented 7% and 6% of the total features ([67]Figure 1A;
   [68]Supplementary Data S1). The large metabolic differences between
   roots, stems and leaves were demonstrated by the hierarchical
   clustering analysis that allowed also to identify a small cluster of
   features positively correlated to T. absoluta herbivory ([69]Figure 1B;
   [70]Supplementary Data S1). The strongest response occurred in the
   infested leaf analyzed after 4 days of herbivory. In this organ class
   and after 4 days of herbivory, the differential analysis between T.
   absoluta infested and control plant showed that 331 features
   over-accumulated and 43 decreased compared to the controls ([71]Figure
   1C). A same partitioning of up- and down-regulated features was
   observed after 7 days of herbivory, but with a smaller amplitude
   ([72]Figure 1C). The T. absoluta herbivory impacted also more distant
   plant parts, which are mainly characterized by an over-accumulation of
   features. Based on the number of features affected, the plant response
   appeared less marked in distant plant parts than in the infested leaf.
   The response was weak in the leaves below the infested leaf ([73]Figure
   1C).

Figure 1.

   [74]Figure 1
   [75]Open in a new tab

   Impact of the T. absoluta herbivory on the metabolome of tomato
   vegetative organs. (A) Venn diagram representing the number of features
   significantly affected by the organ nature, T. absoluta infestation and
   their interaction after 4 days of herbivory, determined by a two-way
   ANOVA (p < 0.05). (B) Heatmap plot and hierarchical clustering based on
   the feature intensities from the five vegetative parts of tomato plant
   submitted or not to T. absoluta herbivory for 4 days. Blue squares
   represent different clusters related to the organ nature. The red
   square represents the cluster of features affected by T. absoluta
   herbivory. (C) Number of differentially accumulated features per organ
   and per duration of herbivory by considering a log2 Fold Change > 1 and
   p < 0.05 (one-way ANOVA Tukey post-hoc test). The abbreviations for the
   organ are the following: Infested leaves (InfL), upper leaves (UpL),
   lower leaves (LowL), stem (St) and roots (R).

   We identified 76 metabolites from the cumulated 493 features
   highlighted from the differential analysis ([76]Table 1;
   [77]Supplementary Data S2). More than half of these identified
   compounds belonged to the phenolamide subfamily. They covered a high
   diversity of phenolamide structures with derivatives containing
   putrescine, agmatine, lysine and tyramine as amine moieties, but also
   fewer common forms consisting in spermine and spermidine chains
   substituted with cinnamic and dihydrocinnamic acid derivatives
   ([78]Figure 2). Among them, N,N,N-dihydrocaffeoylspermine, whose
   identity was confirmed by comparison with authentic chemically
   synthesized standard, appeared as the most accumulated phenolamide in
   the infested leaves. Taking advantage of the fragmentation data from
   some commercial standards, we were able to annotate some glycosylated
   phenolamides ([79]Table 1). All the phenolamides were significantly
   overaccumulated in the infested leaf after 4 days, 7 days or at both
   time with fold change (FC) varying from 2 (p-coumaroylputrescine at 7
   days) to 90 (dihydrocaffeoylputrescine at 4 days). In the other plant
   parts, phenolamide overaccumulation was restricted to only several
   structures and with lower amplitude (FC below 13 in all the other plant
   parts, [80]Table 1). Besides phenolamides, the other identified
   compounds were less structurally related each other ([81]Figure 2). The
   infested leaf accumulated 5′-S-methyl-5′-thioadenosine than the
   control. An increase in glycoalkaloid (dehydrotomatine) was detected
   specifically in stems after 7 days of herbivory. In addition, some
   metabolites were found exclusively in infested leaves, in the presence
   of the larvae (putatively annotated to proclavanic acid and
   butyryl-carnitine). They may be regarded, therefore, either as larvae
   specific compounds or larvae-metabolized tomato metabolites ([82]Table
   1).

Table 1.

   List of annotated metabolites whose accumulation is impacted by the
   herbivory of T. absoluta. The identification followed the Metabolomics
   Standard Initiative (MSI) notation [[83]27]. For each metabolite, the
   foldchange (FC) of the base peak intensity from herbivory treated vs.
   control was calculated in each organ class and harvest. Statistically
   significant FC are in bold. Metabolite name followed by an asterisk (*)
   indicated metabolites presented solely in the T. absoluta infested
   leaf, meaning they could be specific to the presence of the larvae.
   Name Formula MSI Identification Metabolite Family Calc. MW m/z RT [min]
   FC T. absoluta Herbivory/Control
   LowL_4d InfL_4d UpL_4d R_4d St_4d LowL_7d InfL_7d UpL_7d R_7d St_7d
   p-coumaroyltyramine C[17]H[17]NO[3] L2 Phenolamide 283.121 284.12834
   18.4 1.2 11 0.9 0.7 1.0 1.4 5.0 0.7 0.6 1.7
   p-coumaroylputrescine C[13]H[18]N[2]O[2] L1 Phenolamide 234.1369
   235.14417 6.8 1.2 31 1.9 2.1 1.0 1.7 9.3 1.3 0.7 1.7
   p-coumaroylputrescine C[13]H[18]N[2]O[2] L1 Phenolamide 234.1369
   235.14413 7.2 1.3 17 1.0 1.0 1.3 0.9 1.8 1.3 0.9 1.6
   p-coumaroylputrescine C[13]H[18]N[2]O[2] L1 Phenolamide 234.137
   235.14424 3.8 1.1 4.8 1.2 1.3 1.4 1.3 2.4 1.6 0.8 1.6
   p-coumaroyloctopamine C[17]H[17]NO[4] L2 Phenolamide 299.1159 300.12324
   17.5 1.3 9.7 1.2 1.5 0.9 4.1 1.1 1.1 1.3 1.0
   N-feruloyltyramine C[18]H[19]NO[4] L2 Phenolamide 313.1315 314.13881
   18.6 1.1 10 0.9 0.8 1.2 1.5 7.0 0.8 0.9 2.0
   N-feruloyltyramine C[18]H[19]NO[4] L2 Phenolamide 313.1315 314.13878
   15.9 1.2 3.0 1.4 1.0 1.3 1.3 1.6 1.3 1.0 1.2
   N-feruloylputrescine C[14]H[20]N[2]O[3] L1 Phenolamide 264.1473
   265.15461 9.6 1.2 23 1.3 1.0 1.2 1.0 4.2 1.3 0.7 0.9
   N-feruloylputrescine C[14]H[20]N[2]O[3] L1 Phenolamide 264.1474
   265.1547 5.5 1.4 13 1.2 1.0 1.1 1.8 5.9 1.4 0.7 1.2
   N-feruloyl-O-methyl-dehydrodopamine C[19]H[19]NO[5] L2 Phenolamide
   341.1264 342.13364 17.3 2.7 12 1.1 0.7 0.8 3.9 4.2 1.0 1.2 0.9
   N-feruloyllysine C[16]H[22]N[2]O[5] L2 Phenolamide 322.153 323.16024
   7.7 1.2 21 1.4 1.0 1.3 2.4 6.1 2.8 1.4 1.5
   N-feruloyllysine C[16]H[22]N[2]O[5] L2 Phenolamide 322.1529 323.16018
   12.2 3.3 8.4 2.3 1.9 3.2 2.4 16 1.4 2.5 1.7
   N-feruloyllysine C[16]H[22]N[2]O[5] L2 Phenolamide 322.1529 323.16019
   9.2 2.0 3.0 1.9 1.7 1.9 2.3 7.4 1.4 1.7 2.1
   N-feruloyl dehydrotyramine C[18]H[17]NO[4] L2 Phenolamide 311.1159
   312.12321 17.1 0.9 53 0.9 0.9 0.8 1.8 34 1.1 0.9 1.0
   N-feruloylagmatine C[15]H[22]N[4]O[3] L1 Phenolamide 306.1692 307.17645
   12.5 1.2 4.8 1.2 1.1 1.1 1.2 1.9 1.0 1.1 1.2
   N-feruloylagmatine C[15]H[22]N[4]O[3] L1 Phenolamide 306.1692 307.17649
   9.0 1.1 4.0 1.3 1.2 1.0 1.1 1.7 1.2 1.0 1.1
   N-feruloyl O-methyldopamine C[19]H[21]NO[5] L2 Phenolamide 343.1421
   344.14936 18.8 1.2 9.0 1.0 1.1 1.1 2.0 4.2 0.9 0.9 1.8
   N-feruloyl dehydrotyramine C[18]H[17]NO[4] L2 Phenolamide 311.1159
   312.12318 15.6 1.1 8.3 1.0 1.0 1.0 2.1 4.3 0.9 0.9 1.1
   N-dihydroferuloylputrescine C[14]H[22]N[2]O[3] L1 Phenolamide 266.1631
   267.17036 5.2 1.4 19 1.5 1.5 1.6 1.2 9.8 1.5 1.0 1.6
   N-dihydrocaffeoylspermine C[19]H[34]N[4]O[3] L2 Phenolamide 366.263
   367.27031 7.6 1.5 7.3 1.5 1.2 2.4 1.4 2.9 1.8 1.2 1.8
   N-dihydrocaffeoylputrescine C[13]H[20]N[2]O[3] L1 Phenolamide 252.1474
   253.15468 2.7 2.2 90 2.5 2.4 2.0 1.4 24 2.8 1.3 1.6
   N-dihydrocaffeoyl, N-caffeoylspermidine C[25]H[33]N[3]O[6] L2
   Phenolamide 471.2369 472.24416 13.0 2.3 20 3.8 1.1 2.4 1.8 9.4 2.8 1.5
   2.2
   p-coumaroylagmatine C[14]H[20]N[4]O[2] L1 Phenolamide 276.1588
   277.16603 11.1 1.1 10 1.5 1.4 2.0 1.4 2.6 1.4 0.9 1.7
   p-coumaroylagmatine C[14]H[20]N[4]O[2] L1 Phenolamide 276.1587 277.166
   7.1 1.2 6.4 1.3 2.6 1.4 0.9 3.5 1.0 0.5 1.2
   N-cis-(dihydrocaffeoyl-O-hexoside)-putrescine C[19]H[30]N[2]O[8] L2
   Phenolamide 414.2003 415.20757 2.7 1.2 1.6 1.3 0.8 1.7 0.6 4.5 4.2 2.0
   1.4
   N-cis-(Caffeoyl-O-hexoside)-putrescine C[19]H[28]N[2]O[8] L2
   Phenolamide 412.1844 413.19171 4.5 1.6 14 0.9 1.4 1.4 1.0 11 1.9 0.9
   1.1
   N-cis-(caffeoyl-O-hexoside)-putrescine C[19]H[28]N[2]O[8] L2
   Phenolamide 412.1846 413.19192 3.5 0.9 2.7 0.8 1.5 1.2 1.3 2.2 1.0 1.6
   1.4
   N-cis-(caffeoyl-O-hexoside)-putrescine C[19]H[28]N[2]O[8] L2
   Phenolamide 412.1846 413.19188 2.8 1.2 2.0 1.0 1.3 1.0 1.2 5.5 2.2 0.9
   1.4
   N-cinnamoylputrescine C[13]H[18]N[2]O L2 Phenolamide 218.142 219.14926
   12.3 1.3 8.3 1.3 0.9 1.3 1.6 8.0 1.8 1.0 1.3
   N-caffeoylputrescine C[13]H[18]N[2]O[3] L1 Phenolamide 250.1316
   249.12424 4.3 1.4 29 1.5 1.3 1.3 1.0 17 1.3 0.9 1.2
   N-caffeoylputrescine C[13]H[18]N[2]O[3] L1 Phenolamide 250.1317 251.139
   2.7 1.2 7.1 1.3 1.0 1.1 1.5 3.3 1.6 1.0 1.6
   N-caffeoyllysine C[15]H[20]N[2]O[5] L2 Phenolamide 308.1372 309.14447
   8.0 4.2 8.2 4.7 1.0 7.8 3.7 14 1.8 0.9 3.2
   N-caffeoylagmatine C[14]H[20]N[4]O[3] L1 Phenolamide 292.1537 293.16097
   9.2 1.2 12 1.8 1.8 1.3 1.2 3.9 1.7 1.1 1.5
   N-caffeoyl,N-dihydrocaffeoylspermidine C[25]H[33]N[3]O[6] L2
   Phenolamide 471.2369 472.24418 13.5 2.3 20 2.5 0.9 2.2 1.0 13 3.2 2.4
   2.1
   N,N-dihydrocaffeoylspermidine C[25]H[35]N[3]O[6] L2 Phenolamide
   473.2524 474.25965 12.0 3.2 48 4.3 3.0 2.6 2.1 11 4.3 2.4 1.7
   N,N-bis-dihydrocaffeoyl,N-caffeoylspermine C[37]H[48]N[4]O[9] L2
   Phenolamide 692.3417 693.34895 14.9 1.2 16 2.1 1.0 2.4 2.2 13 13 0.8
   3.4
   N,N,N tri-dihydrocaffeoylspermine C[37]H[50]N[4]O[9] L1 Phenolamide
   694.357 695.36422 15.8 2.1 17 3.4 2.8 2.0 2.0 7.1 3.1 2.1 1.7
   N, N bis-dihydrocaffeoyl, N-caffeoylspermine C[37]H[48]N[4]O[9] L2
   Phenolamide 692.3419 693.34916 16.4 2.9 48 5.2 1.1 3.7 1.6 20 6.8 2.5
   5.5
   N, N bis-dihydrocaffeoyl, N-caffeoylspermine C[37]H[48]N[4]O[9] L2
   Phenolamide 692.3417 693.34899 16.0 1.6 11 3.3 1.6 1.6 1.1 5.5 3.1 2.3
   2.6
   N, N bis-caffeoyl, N-dihydrocaffeoylspermine C[37]H[46]N[4]O[9] L2
   Phenolamide 690.3263 691.33353 16.5 2.7 11 3.5 1.1 3.1 1.2 18 4.5 1.4
   1.7
   caffeoyl-lysine glucoside C[21]H[30]N[2]O[10] L2 Phenolamide 470.1898
   471.19706 8.6 0.8 1.2 1.3 1.6 8.4 0.7 1.1 5.0 1.4 4.8
   3-(4-hydroxyphenyl)-N-[(1E)-2-(4-hydroxyphenyl)ethenyl]-(2E)-2-propenam
   ide C[17]H[15]NO[3] L2 Phenolamide 281.1055 282.11278 16.6 1.5 88 1.2
   1.1 0.7 1.1 28 1.0 0.7 1.0
   (2E)-N-(4-acetamidobutyl)-3-(4-hydroxy-3-methoxyphenyl)prop-2-enamide
   C[16]H[22]N[2]O[4] L3 Phenolamide 306.1581 307.16533 13.3 1.0 0.8 2.7
   1.1 5.2 1.2 0.8 3.5 0.9 3.8
   Putative feruloyl-N[6]-methylagmatine C[16]H[24]N[4]O[3] L2 Phenolamide
   320.1849 321.19217 13.3 1.3 5.1 1.2 1.1 1.2 1.3 2.3 1.2 1.1 1.2
   Putative feruloyl-N[6]-methylagmatine C[16]H[24]N[4]O[3] L2 Phenolamide
   320.1849 321.19213 10.3 1.4 3.0 1.3 1.2 0.8 1.3 1.5 1.0 1.1 1.1
   Methyl-(10R)-hydroxy-(11S,12S)-epoxy-(5Z,8Z,14Z)-eicosatrienoate
   C[21]H[34]O[4] L3 Lipid 350.2458 351.25302 22.9 0.8 1.8 0.8 0.4 1.0 0.9
   1.2 1.3 2.8 1.3
   hydroxyprogesterone caproate C[27]H[40]O[4] L3 Lipid 428.2906 429.29786
   23.8 0.8 0.6 1.2 1.0 0.7 2.9 1.0 0.4 0.9 1.0
   [FA(18:4)]6Z_9Z_12Z_15Z-octadecatetraenoicacid C[18]H[28]O[2] L3 Lipid
   276.2092 277.21647 23.8 0.7 3.8 0.7 1.0 0.8 0.9 1.4 0.8 0.8 1.1
   [FA(18:3)]13S-hydroperoxy-9Z_11E_14Z-octadecatrienoicacid
   C[18]H[30]O[4]L3 Lipid 310.2144 309.20711 22.0 0.9 14 0.6 1.1 1.1 0.8
   4.7 1.5 0.9 0.8
   [FA(18:3)]13S-hydroperoxy-9Z_11E_14Z-octadecatrienoicacid
   C[18]H[30]O[4]L3 Lipid 310.2144 309.20703 22.2 1.1 5.3 0.8 1.0 1.1 0.9
   3.8 0.9 1.0 1.2
   (12Z)-9,10,11-trihydroxyoctadec-12-enoic acid C[18]H[34]O[5] L3 Lipid
   352.2228 353.23006 21.8 0.7 4.7 2.0 1.2 1.1 1.5 6.5 1.1 1.7 0.9
   Solasodin C[27]H[43]NO[2] L2 Glycoalkaloid 413.3293 414.33655 19.4 1.0
   0.9 1.0 1.0 1.3 1.2 1.0 1.1 1.0 2.0
   Solasodin C[27]H[43]NO[2] L2 Glycoalkaloid 413.3296 414.33683 20.9 1.0
   2.3 1.2 0.7 1.1 1.8 2.2 1.2 0.8 2.3
   Dehydrotomatine C[50]H[81]NO[21] L2 Glycoalkaloid 2063.058 1032.5365
   19.4 1.3 1.1 1.2 1.0 1.5 1.3 1.2 1.5 0.9 2.5
   Gossypetin 7,4′-dimethyl ether 8-acetate C[19]H[16]O[9] L3 Flavonoïd
   388.0796 389.08683 15.5 1.1 0.3 0.7 1.0 1.0 1.6 1.3 1.6 1.1 1.2
   Proclavaminic acid * C[8]H[14]N[2]O[4] L3 Carboxylic acid 202.0953
   203.10259 2.4 1.0 101 1.0 2.4 0.5 1.3 33 1.0 1.6 0.9
   Decylubiquinone C[19]H[30]O[4] L3 Benzoquinone 322.2146 323.22185 21.8
   0.9 5.4 0.5 0.9 1.0 1.3 2.3 3.0 1.2 1.0
   Decylubiquinone C[19]H[30]O[4] L3 Benzoquinone 322.2145 323.22182 22.0
   1.1 6.4 0.7 0.8 1.2 1.3 2.6 1.7 0.3 1.3
   Guanine C[5]H[5]N[5]O L2 Amino purine 151.0494 152.0567 3.9 0.9 4.4 1.0
   0.7 0.8 0.6 1.5 1.0 0.9 1.3
   Phenyl-butyryl-glutamine C[15]H[20]N[2]O[4] L2 Amino acid 292.1424
   293.14972 6.8 1.4 4.0 4.6 0.8 6.0 5.5 13 2.8 0.7 4.4
   Phenyl-butyryl-glutamine C[15]H[20]N[2]O[4] L2 Amino acid 292.1425
   293.14974 10.4 7.4 6.2 7.2 0.9 9.5 4.5 7.5 3.7 0.9 4.1
   N-decanoyl histidine C[16]H[27]N[3]O[3] L2 Amino acid 309.2054
   310.21263 7.6 1.6 5.4 1.9 1.2 2.4 1.7 2.2 1.5 1.1 1.4
   N-acetyltyramine C[10]H[13]NO[2] L3 Amino acid 179.0946 180.1019 7.0
   1.0 2.0 2.8 1.0 1.0 1.7 1.9 1.3 0.5 1.0
   N[6]_N[6]_N[6]-Trimethyl-L-lysine C[9]H[20]N[2]O L2 Amino acid 172.1576
   173.16488 3.2 1.3 2.4 1.0 0.9 1.2 1.2 2.9 1.0 0.8 1.3
   N[6]_N[6]_N[6]-Trimethyl-L-lysine C[9]H[20]N[2]O L3 Amino acid 172.1576
   173.16488 1.9 1.0 77 1.3 0.9 1.7 1.5 31 0.9 1.1 1.2
   Malonyltryptophan C[14]H[14]N[2]O[5] L1 Amino acid 290.0904 291.09769
   15.8 1.3 2.9 1.6 1.0 2.1 1.9 8.2 1.4 0.9 2.5
   Lysine C[6]H[14]N[2]O[2] L1 Amino acid 146.1055 147.11281 8.0 1.6 1.5
   3.2 1.0 7.1 3.2 1.8 1.7 0.8 3.5
   Capryloylglycine C[10]H[19]NO[3] L3 Amino acid 201.1365 202.1438 4.2
   1.1 0.7 1.0 0.5 1.8 1.1 0.8 1.3 0.1 1.0
   Butyryl-carnitine * C[11]H[21]NO[4] L3 Amino acid 231.1471 232.15434
   3.1 0.8 98 1.0 1.2 1.3 0.7 52 2.5 2.1 1.5
   9-amino-nonanoic acid C[9]H[19]NO[2] L3 Amino acid 173.1416 174.14892
   10.1 1.0 2.4 1.3 1.0 1.3 1.4 2.0 0.9 1.0 1.6
   2-Acetamido-2-deoxy-3-O-beta-D-galactopyranosyl-1-O-L-threonyl-alpha-D-
   galactopyranose C[18]H[32]N[2]O[13] L3 Unknown 484.1923 485.19958 17.7
   0.9 5.0 1.6 1.4 0.8 0.8 2.0 1.1 1.0 1.2
   19-Nortestosterone C[18]H[26]O[2] L3 Terpenoid 274.1935 275.2008 22.0
   0.7 8.1 1.1 1.0 1.2 0.8 2.4 1.3 1.2 0.7
   5′-S-Methyl-5′-thioadenosine C[11]H[15]N[5]O[3]S L2 Ribonucleoside
   297.0896 298.09688 8.3 1.3 0.1 1.2 1.0 0.9 2.0 0.8 0.4 0.8 1.0
   O-feruloylquinate C[17]H[20]O[9] L2 Phenolic acid 368.1107 369.11793
   12.5 3.2 1.1 1.0 0.9 1.1 1.2 0.2 1.1 1.1 1.5
   Ferulic acid C[10]H[10]O[4] L1 Phenolic acid 194.058 195.06521 12.6 1.3
   0.5 0.8 1.1 0.8 1.1 1.0 0.8 0.9 0.9
   1-O-feruloyl-beta-D-glucose C[16]H[20]O[9] L2 Phenolic acid 356.1107
   355.1032 11.3 2.0 6.7 2.2 0.9 1.6 0.9 2.0 2.0 1.0 1.2
   [84]Open in a new tab

Figure 2.

   [85]Figure 2
   [86]Open in a new tab

   Molecular network of up- and down-regulated features in the tomato
   organs in response to T. absoluta herbivory. The molecular network was
   obtained using Compound Discoverer 3.3 and was visualized with
   Cytoscape 3.9.1 following the procedure described at
   [87]https://github.com/Florent-1/Molecular-Networks-from-Compound-Disco
   verer-to-Cytoscape (accessed on 10 April 2022). The pie chart in each
   node represent the relative abundance of the feature in T.absoluta
   treated (grey) vs. control (white). These abundances are presented in
   priority in InfLat 4 days of herbivory, identified by a dark green
   circle surrounding the node. When the feature is not affected in InfL,
   the relative abundance is represented for the most impacted organ, with
   the following nomenclature: Light green, InfL at 7 days; purple: St at
   4 days; pink, St at 7 days; dark blue, LowL at 4 days; light blue, LowL
   at 7 days; red, R at 4 days; orange, R at 7 days. The structures of
   some formally identified nodes are surrounded in blue, and those of
   putative compounds are surrounded in yellow.

2.2. Transcriptomics Analyses

   The transcriptomic response was determined by comparing the
   transcriptome of T. absoluta infested leaves after 5 h and 24 h of
   herbivory with leaves from control plants. RNA sequencing produced an
   average of 30 million reads for each of the 12 samples (triplicates for
   T. absoluta infested vs. control at two dates). Approximately 18,200
   transcripts were mapped to the tomato reference genome (ITAG2.4)
   ([88]Supplementary Data S3). Differentially expressed genes (DEGs) were
   identified by comparing the T. absoluta infested vs. control at each
   time. The herbivory of T. absoluta led to 2456 DEGs after 5 h and 4269
   DEGs after 24 h. After 5 h of herbivory, the proportion of up-regulated
   DEGs was slightly higher than the down-regulated one. This proportion
   was similar after 24 h ([89]Figure 3). Among the 1318 DEGs common to 5
   h and 24 h of herbivory, two third corresponded to up-regulation. The
   list of the up- and down-regulated DEGs at each date is given in
   [90]Supplementary Data S4.

Figure 3.

   [91]Figure 3
   [92]Open in a new tab

   Venn diagram representing the DEGs in tomato leaf after 5 h and 24 h
   herbivory. The proportion of up- and down-regulated DEGs is shown by
   the proportion of pink/red and blue respectively. The number of up- and
   down-regulated DEGs is also indicated. The left circle represents DEGs
   after 5 h, the right circle, DEGs after 24 h, and the intersection
   between the two circles the DEGs common to 5 h and 24 h of herbivory.

   We applied gene set enrichment analysis (GSEA) based on the gene
   ontology (GO) of the DEGs in order to identify which pathways are
   affected by T. absoluta herbivory. About 111 GO categories were
   significantly affected by herbivory ([93]Supplementary Data S5). Since
   a lot of GO categories were highly redundant, a refined list was
   established to limit the redundancy and to highlight the metabolic
   processes diversity affected by herbivory ([94]Figure 4). GSEA
   highlighted a clear time-dependent tomato response to the herbivory
   with only two GO categories being commonly over-represented in the
   up-regulated DEGs after 5 h and 24 h. The first one, labelled «response
   to wounding», includes 11 and 12 genes annotated as proteinase and
   chymotrypsin inhibitors. The second one, «aromatic amino acid family
   metabolism», gathers genes involved in the biosynthesis of
   phenylalanine and tyrosine (dehydroquinate synthase, Solyc02g083590;
   chorismate mutase, Solyc02g088460; prephenate dehydratases,
   Solyc06g074530 and Solyc11g066890) but also 5 phenylalanine ammonia
   lyase (PAL) genes which catalyzes the initial step leading to the
   phenylpropanoid pathway (Solyc09g007890, Solyc09g007900,
   Solyc09g007910, Solyc09g007920, Solyc10g086180).

Figure 4.

   [95]Figure 4
   [96]Open in a new tab

   Gene ontology (GO) terms enrichment at p < 0.05 for up- and
   down-regulated genes after 5 h and 24 h of herbivory. The size of the
   circles represents the number of differentially expressed genes (DEG)
   in each GO category. The position of the circles represents the ratio
   between the number of DEGs in the GO category to the total number of
   genes associated to the GO category. The color of the circles
   represents the statistical significance.

   After 5 h of herbivory, the two categories «isoprenoid biosynthetic
   process» and «steroid metabolic process» appeared as being
   over-represented in the up-regulated DEGs. This suggests an activation
   of the whole terpenoid pathway, starting from the first steps common to
   all terpenoid subclasses (mevalonate kinase, Solyc01g098840;
   3-hydroxy-3-methylglutarylCoA reductase, Solyc02g082260; isopentenyl
   diphosphate isomerase, Solyc05g055760; hydroxymethylglutaryl-CoA
   synthase, Solyc08g080170; farnesyl pyrophosphate synthase,
   Solyc12g015860) to more specific steps involved in the steroid backbone
   formation crucial for the widely distributed sterols but also the
   solanaceous-specific glycoalkaloids (squalene monooxygenase,
   Solyc04g077440; sterol reductases, Solyc06g074090 and Solyc09g009040).
   The “lipid metabolism” category appeared overrepresented in both the
   up- and down-regulated genes. Regarding the up-regulated genes of this
   category, half of them were related to the terpenoid metabolism and
   overlapped with the categories mentioned above. The other half
   contained a majority of genes associated to (i) lipid catabolism, with
   notably 17 genes annotated as lipase or lipase-like (Solyc01g079600,
   Solyc02g077420, Solyc11g065530, Solyc08g006850, etc.), (ii) lipid
   modification (diacylglycerol O-acyltransferase, Solyc01g095960;
   O-acyltransferase WSD1 Solyc07g053890, phosphatidylcholine-sterol
   O-acyltransferase, Solyc09g072710…) and (iii) one gene, Solyc02g085730,
   coding for an allene oxide cyclase involved in the jasmonic acid
   pathway. The down-regulated genes were mainly associated to the
   phosphatidic acid metabolism (phosphatidylinositol-specific
   phospholipase C, Solyc01g111260, Solyc10g055240; phospholipase D,
   Solyc02g083340; phosphatidylinositol-4-phosphate 5-kinase family
   protein, Solyc11g013830, Solyc11g013180, Solyc06g065540) and also to
   the biosynthesis of very long chain fatty acid (VLCFA) (fatty acid
   elongase 3-ketoacyl-CoA synthase, Solyc03g005320, Solyc05g009270,
   Solyc08g067260, Solyc09g065780, Solyc10g009240).

   The tomato plant response after 24 h of herbivory was characterized by
   an over-representation of genes associated to signaling in up-regulated
   DEGs. Indeed, five genes were associated to ethylene signaling protein
   or ethylene receptor (Solyc05g055070, Solyc06g053710, Solyc09g007870,
   Solyc11g006180, and Solyc12g011330), whereas the over-represented GO
   category «phosphorylation» regrouped a majority of receptor-like
   kinases (RLK) whose role in signaling during the plant response to
   bio-aggressors is well known [[97]28]. In addition, numerous genes
   identified or annotated as mitogen-activated protein kinase (MAPK) or
   calcium-dependent protein kinase (CDPK) were also found in this
   category. This is the case for SlMPK1,3,4 and 5 (Solyc12g019460,
   Solyc06g005170, Solyc11g072630, and Solyc01g094960), which have been
   shown to contribute to the tomato defense response to Botrytis cinerea
   [[98]29]. After 24 h of herbivory, a large list of GO categories
   appeared linked to the down-regulated DEGs. These categories covered a
   large array of metabolic processes, including central metabolism, the
   major affected categories being linked to chloroplast metabolism
   (photosynthesis, tetrapyrrole metabolism and carotenoid metabolism).

   KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment pathway
   analysis was conducted in parallel and led to similar interpretation.
   Indeed, the phenylpropanoid pathway appeared as the only pathway
   up-regulated at 5 h and 24 h of herbivory, whereas the lipid,
   chlorophyll and riboflavin metabolisms were significantly
   over-represented in the down-regulated DEGs at 5 h and 24 h and
   photosynthesis specifically at 24 h ([99]Supplementary Data S6).

   In addition to the GSEA and KEGG enrichment pathway approaches,
   transcriptomics data were also explored in light of the metabolomics
   analysis, which highlights a large phenolamide accumulation in the
   infested tissues. Consequently, we focused our analysis specifically on
   pathways related to the polyamine biosynthesis and the phenylpropanoid
   biosynthesis. Seventeen genes were followed regarding the polyamine
   biosynthesis ([100]Supplementary Data S7). Five of them were strongly
   induced after both 5 h and 24 h of herbivory ([101]Figure 5). They
   correspond to arginases (Solyc01g091160, Solyc01g091170), arginine
   decarboxylase (Solyc01g110440), ornithine decarboxylase
   (Solyc04g082030) and spermine synthase (Solyc03g007240), which
   represents all the steps to produce agmatine and putrescine and four of
   the five necessary steps to produce spermine starting from arginine.
   Regarding the phenylpropanoid pathway, 58 genes covering the core
   pathway and also the flavonoid pathway were followed
   ([102]Supplementary Data S7). Thirteen genes were significantly
   up-regulated at 5 h or 24 h but only four genes were common to the
   two-time conditions. At 5 h, the induced genes covered mainly the
   phenylpropanoid core pathway, with PAL, 4-coumarate:coenzyme A ligase
   (4CL), p-coumaroyl-CoA 3′ hydroxylase (C3′H) and hydroxycinnamoyl
   transferase (HCT)-like genes. At 24 h, the induced genes were 3
   HCT-like and also 3 tyramine-hydroxycinnamoyl-transferase (THT)
   specifically involved in the biosynthesis of tyramine-containing
   phenolamides ([103]Figure 5). Interestingly, all the
   phenylpropanoid-related genes were only slightly induced with the
   exception of the two HCT-like genes Solyc11g071470 and especially
   Solyc11g071480 which was the most induced gene at 5 h. Despite their
   annotation, Blast analysis of Solyc11g071470 and Solyc11g071480
   revealed their high homology with AT1 a putrescine hydroxycinnamoyl
   transferase (PHT) functionally identified in Nicotiana attenuata
   [[104]30]. To confirm the nature of these two genes, we cloned them,
   heterologously expressed the protein in bacteria and assayed the
   purified proteins for PHT activity. The assays confirmed that
   Solyc11g071470 and Solyc11g071480 both exhibited the ability to
   synthesize caffeoylputrescine from caffeoyl-CoA and putrescine as a
   main activity ([105]Figure 6). Both enzymes were also able to
   synthesize feruloylputrescine, caffeoylagmatine and
   dihydrocaffeoylputrescine but with a lower efficacity. These enzymes
   were, however, unable to produce spermidine- nor spermine-based
   phenolamides.

Figure 5.

   [106]Figure 5

   [107]Figure 5
   [108]Open in a new tab

   Expression level of selected genes representing key steps in the
   polyamine (A) and phenylpropanoid (B) pathways. The heatmap represents
   the differential expression measured from the RNAseq analysis, between
   control and T. absoluta infested leaf at 5 h and 24 h. In addition, the
   expression level of several genes was measured by real-time PCR on cDNA
   prepared from leaves corresponding to the 4 conditions (control and T.
   absoluta infested after 5 h and 24 h). Statistical significance is
   indicated by * (p < 0.05), ** (p < 0.01) and *** (p < 0.001). ns means
   non significant.

Figure 6.

   [109]Figure 6
   [110]Open in a new tab

   Functional identification of Solyc11g071470 and Solyc11g071480 as
   putrescine hydroxycinnamoyl-CoA transferase. (A) Chromatogram of
   biochemical assays realized on the purified enzymes; (B) table showing
   the substrate preference measured from the consumption of the acyl-CoA
   substrate and normalized to the best reaction. CP, caffeoyl putrescine;
   coum-CoA, p-coumaroyl-CoA; Caf-CoA, caffeoyl-CoA; Fer-CoA,
   feruloyl-CoA; nd, no activity detected.

3. Discussion

   The combination of transcriptomics and metabolomics analyses, taken
   together with the study at different harvest times and on different
   plant parts, allowed to obtain an exhaustive picture of the tomato
   plant responses to T. absoluta herbivory. Based on the metabolomics
   data, these responses were both local and systemic, the local response
   in infested leaves being much more intense than in other plant parts.
   In addition, systemic responses were mostly a subset of the metabolites
   induced locally with the exception of the roots whose metabolome
   appeared clearly to be different from that of the above-ground parts.
   This feature of the tomato response to the leafminer T. absoluta is
   thus shared with that against chewing herbivores, such as Manduca sexta
   [[111]31]. Both responses promote also a massive induction of
   antinutritive proteinase inhibitors [[112]32].

   The tomato response to T. absoluta herbivory was characterized by a
   large and transient modulation of the terpene and lipid metabolic
   pathways. The induction of a wide array of genes involved in the
   terpenoid backbone biosynthesis, together with some terpene
   synthase-annotated genes and SlMYC1 (Solyc08g076930) involved in the
   type VI trichome biosynthesis and terpene emission [[113]33], suggest
   an induction of the synthesis/emission of volatile organic compounds
   (VOCs) in response to herbivory. In addition, the massive induction of
   lipase-annotated genes may illustrate the activation of the green leaf
   volatiles (GLVs) biosynthesis, initiated through the lipase-mediated
   degradation of galactolipids to release linoleic and α-linolenic acids.
   Although the emission of VOCs was not monitored in our study, this
   interpretation is coherent with many recent studies
   [[114]18,[115]19,[116]20,[117]34,[118]35] reporting enhanced emissions
   of tomato VOCs in response to T. absoluta attacks. Moreover, the
   lipase-associated production of linoleic acid together with the
   induction of the allene oxide cyclase may suggest the induction of the
   jasmonic acid biosynthesis.

   Another set of genes associated to the lipid metabolism was, however,
   largely down regulated. They corresponded, for one part, to genes
   associated to the biosynthesis of phosphatidic acid (phospholipases C
   and D) and, for the other part, to genes mainly associated to fatty
   acid elongases, which are involved in the biosynthesis of cuticle and
   waxes. Phosphatidic acid signaling contributes to the rapid systemic
   plant response against biotic and abiotic stresses [[119]36]. It is
   tempting to connect this apparent PA down-regulation to the low
   systemic response highlighted by the metabolomic analyses in rice
   [[120]37]. Indeed, this recent study compared the systemic response to
   herbivores with different feeding guilds and identified a low systemic
   induction of secondary metabolites that was accompanied by a decrease
   in the PA associated lipid in spider mite-fed plants. Waxes and cuticle
   represent physical barriers that may affect plant digestive ability and
   also the mobility of the insects [[121]38,[122]39]. Overall, the
   apparent down-regulation of these two components of the plant defense
   could be the consequence of the leafminer ability to reprogram its host
   physiology. Such manipulations of the host plant physiology have been
   well described for galls and are known for leafminers [[123]40]. To the
   best of our knowledge, the tomato/T. absoluta model has not been
   studied on this aspect; however, investigation on this question may be
   very helpful in understanding the determinants of the tomato
   susceptibility to this pest.

   At the metabolite level, one striking consequence of T. absoluta
   herbivory was the massive accumulation of phenolamides in tomato
   tissues. Although phenolamide accumulation has already been described
   in Solanaceae and Poaceae in response to chewing and sucking insects
   [[124]30,[125]41,[126]42,[127]43], it has not been reported before in
   this specific pathosystem [[128]26,[129]44,[130]45], highlighting the
   potential of untargeted High Resolution Mass Spectrometry (HRMS)
   analyses in this kind of study. A characteristic of this phenolamine
   accumulation was the structural diversity of the metabolites composing
   this family. Besides caffeoylputrescine found in healthy tomato tissues
   [[131]46], as well as tyramine, dopamine or spermidine derivatives,
   which are classically accumulated in attacked tomato or other
   solanaceous species [[132]42,[133]47,[134]48,[135]49], our analyses
   identified more atypical metabolites, such as spermine and spermidine
   derivatives associated to dihydroxycinnamoyl moities. These compounds,
   usually referred to as kukoamines, have been mostly reported in
   different plant parts of Lycium sp. [[136]50,[137]51] but also in
   potato tubers and tomato fruits [[138]52]. To the best of our
   knowledge, these compounds have never been associated in the plant
   response to herbivory.

   The accumulation of phenolamides was supported by transcriptomic data,
   which highlighted the induction of the phenylpropanoid and the
   polyamine pathways, providing, respectively, the (di)hydroxycinnamoyl
   and the amine moieties ([139]Figure 7). Interestingly, the
   phenylpropanoid pathway induction was much lighter than that of the
   polyamine, suggesting that the latter could be rate limiting for
   phenolamide accumulation. A key step for the phenolamide accumulation
   is the association of the (di)hydroxycinnamoyl and amine moieties that
   is mostly catalyzed by N-hydroxycinnamoyltransferases [[140]53].
   Solyc11g071470 and Solyc11g071480, which were highly overexpressed in
   response to the T. absoluta herbivory, were functionally characterized
   as putrescine hydroxycinnamoyl transferases. They complete the
   collection of PHT initially identified in Nicotiana attenuata (one gene
   AT1; [[141]30]) and in Oryza sativa (three genes Os04g0664600,
   Os09g0544000, Os09g0543900; [[142]54]). The genes Solyc11g071470 and
   Solyc11g071480 had comparable specificity with caffeoyl-CoA and
   putrescine as preferred acyl donor and acceptor, but also substantial
   activity with feruloyl-CoA, dihydrocaffeoyl-CoA and agmatine. Regarding
   their position in the tomato genome and their high nucleotide sequence
   identity, these two genes were probably duplicates as observed for two
   rice genes, Os09g0544000 and Os09g0543900, exhibiting differences in
   their substrate preference and their expression level in different
   plant organs. This indicates that the two duplicates have evolved in
   different ways (neo-functionalization) [[143]54]. However,
   Solyc11g071470 and Solyc11g071480 exhibited no significant difference
   in their substrate preference nor their stress induction. Complementary
   experiments on the spatial expression of these two genes in the tomato
   plant may help understanding the role of each gene.

Figure 7.

   [144]Figure 7
   [145]Open in a new tab

   Schematic representation of the main modulations, at the metabolite and
   transcript levels, of the phenolamide biosynthesis in response to the
   herbivory of T. absoluta. Genes in orange were shown to be up-regulated
   upon T. absoluta herbivory through RNAseq and/or qPCR. The three
   phenolamide categories in red were shown to be over-accumulated upon T.
   absoluta herbivory. The blue arrows in solid line represent metabolic
   steps in the phenylpropanoid and polyamine/monoamine pathways. The
   light-blue arrows in dashed lines connect the phenylpropanoid and
   polyamine/monoamine substrates to lead to the synthesis of the three
   categories of phenolamides catalyzed by three types of enzymes, THT,
   PHT and a yet unknown enzyme. ADC, arginine decarboxylase; ODC,
   ornithine decarboxylase; SPDS, spermidine synthase; SPMS, spermine
   synthase; PAL, phenylalanine ammonia lyase; C4H,
   cinnamate-4-hydroxylase; 4CL, 4-coumarate CoEnzyme A ligase; HCT,
   hydroxycinnamoyl quinate/shikimate hydroxycinnamoyl transferase; C3′H,
   coumaroyl-3′-hydroxylase; HQT, hydroxycinnamoyl quinate
   hydroxycinnamoyl transferase; TYDC, tyrosine decarboxylase; PHT,
   putrescine hydroxycinnamoyl transferase; THT, tyramine hydroxycinnamoyl
   transferase.

   The functional identification of Solyc11g071470 and Solyc11g071480
   together with their high induction upon herbivory provide chemical
   support for their role in the accumulation of putrescine- and
   agmatine-related phenolamides ([146]Figure 8). The question remains
   opened regarding the accumulation of derivatives composed by
   spermine/spermidine and dihydroxycinnamoyl moieties. A specific
   research in the transcriptomic data of tomato orthologs of reported
   spermidine and spermine transferases
   [[147]30,[148]55,[149]56,[150]57,[151]58,[152]59,[153]60] followed by
   the functional characterization of candidates did not allow us yet to
   identify this crucial step (not shown).

Figure 8.

   [154]Figure 8
   [155]Open in a new tab

   Scheme of plant parts harvested. Twelve larvae of T. absoluta were
   deposited on the 3 terminal leaflets of the 4th leaf. After 4 and 7
   days of herbivory, these 3 infested leaflets were harvested (InfL). The
   other plant parts were harvested as indicated: upper leaves (UpL),
   lower leaves (LowL), stem (St) and roots (R).

   Even if this was not the scope of this study, the question remains as
   to whether or not this phenolamide accumulation is a resistance trait
   of tomato plants to the T. absoluta herbivory. On the one hand, several
   phenolamides have been shown to have a negative impact on larval
   development [[156]42], to increase insect mortality [[157]43] or to
   deter insect oviposition [[158]61]. On the other hand, other examples
   showed that phenolamides have no detectable impact on some insect pests
   [[159]43] or were beneficial to the larval development probably because
   of the nitrogen feed during their digestion and assimilation [[160]62].
   Like almost all domesticated varieties, the tomato plants used for this
   study (cv. Better Bush) were susceptible to the herbivory of T.
   absoluta, which indicates that the phenolamide accumulation was not
   sufficient enough to prevent the deleterious impact of this pest.
   Interesting questions remain open regarding how this specialist pest
   bypasses the plant defense traits. Focusing on the phenolamide
   accumulation, the identification of genes specifically involved in
   their biosyntheses offers a promise to modulate the phenolamide
   composition and concentration in tomato lines and assess their control
   effects on the insects.

4. Materials and Methods

4.1. Plant and Insect Materials

   Tomato seeds (Solanum lycopersicum L.) of the early and dwarf cultivar
   “Better Bush” (VFN Hybrid, breeder: Tomato Growers) were sown and grown
   using a hydroponic system under controlled conditions.

   T. absoluta adults, provided by INRAE-ISA Sophia-Antipolis (France)
   were reared on tomato plants grown under insectarium conditions in
   climatic chambers. After mating, the females laid eggs on leaves and
   larvae hatched out. They were selected at stage 3 (scale 1–4) to infest
   young tomato plants.

4.2. Conditions for Plant Growth

   Eleven days after sowing, the seedlings were transplanted into a
   Nutrient Film Technique system set in a growth chamber (16 h
   photoperiod, 23 °C/18 °C day/night in air and 23 °C in nutrient
   solutions, 60% air humidity). Before the experiment, all temperature
   sensors (air and solution) were calibrated in a water bath with 0.01 °C
   precision (Haake model C35/F6, Karlsruhe, Germany).

   The plants received a full nutrient solution supplying N-NO[3]^− at a
   concentration of 1 mM, which was found to be non-limiting for tomato
   growth [[161]63]. Nitrogen concentration was continuously (i.e., every
   hour) regulated at its fixed set-points using the automated Totomatix
   setup [[162]64]. The pH was monitored and regulated by Totomatix to
   5.5. The detailed composition of the nutrient solution is given in
   [163]Supplementary Data S8.

4.3. Plant Infestation by T. absoluta Larvae, Harvest and Sample Preparation

   For the metabolomics analyses, 20 plants were grown. Half of them were
   infested 14 days after transplantation with 12 larvae laid on the three
   terminal leaflets of the 4th true leaf ([164]Figure 8). The other half
   constituted the group of control plants, which were subjected to mock
   depositions of larvae, performed with a paintbrush. The plants were
   sampled 4 days and 7 days after larvae deposit. Leaves, stems and roots
   were separated ([165]Figure 8). On the infested leaf, only the three
   terminal leaflets were sampled after removing the larvae. Roots were
   rinsed with deionized water. Organ fresh weights (FW, 0.1 mg precision)
   were measured, and samples were frozen in liquid N[2] and stored at −80
   °C until freeze-drying. Dry weights (DW, 0.1 mg precision) were
   determined, and the samples were ground to a fine powder and stored at
   −20 °C.

   For the transcriptomics analyses, 6 plants were infested with 6 larvae
   deposited on the three terminal leaflets of the 4th true leaf and 6
   other plants were subject to mock deposition. Two harvests were
   conducted after 5 h and 24 h of herbivory. At both harvest time, the
   infested leaflets from which the larvae had been removed (and the
   corresponding leaflets in the control plants) were sampled, immediately
   frozen in liquid nitrogen and stored at −80 °C until RNA extraction.

4.4. Extraction of Metabolites from Tomato Organs

   Metabolites were extracted from 30 mg dry powder of leaves, stems and
   roots as described in [[166]65]. The dry powder was extracted in 1 mL
   60% aqueous methanol to which 50 μL of taxifolin were added (internal
   standard, 2 mg·mL^−1 methanol), then blended (1 min) and centrifuged
   (10 min, 2800× g). The extraction was repeated, and the supernatants
   pooled and vacuum-dried. The residue was dissolved in 500 µL of 70%
   aqueous methanol, filtered (0.22 μm) and transferred to vials before
   MS^1 analyses. One additional vial was prepared with a pool of each
   sample (2 µL each) for the MS^2 analyses.

4.5. UHPLC-ESI-HRMS Analysis

   Chromatographic analyses were performed on a Vanquish UHPLC system
   equipped with a binary pump, an autosampler and a
   temperature-controlled column. Metabolites contained in the extracts
   (10 µL) were separated on a XB-C18 Kinetex (150 × 2.1 mm, 2.6 µm)
   (Phenomenex Inc., Torrance, CA, USA) using a gradient of mobile phase
   composed of water + 0.1% formic acid (A) and methanol + 0.1% formic
   acid (B) at a flow rate of 200 μL·min^−1. The elution program consisted
   in starting with 10% B for 2 min, then linearly increasing from 10 to
   30% B in 8 min, then to 95% B in 10 min. The column was rinsed for 5
   min with 95% B and re-equilibrated to the initial conditions for 4 min
   prior to the next run. The samples were analyzed randomly.

   HRMS^1 detection was performed on an Orbitrap IDX^TM (ThermoFisher
   Scientific, Bremen, Germany) mass spectrometer in positive and negative
   electrospray ionization (ESI) modes. The capillary voltages were set at
   3.5 kV and 2.5 kV for positive and negative modes, respectively. The
   source gases were set (in arbitrary unit min^−1) to 40 (sheath gas), 8
   (auxiliary gas) and 1 (sweep gas) and the vaporizer temperature was 320
   °C. Full scan MS^1 spectra were acquired from 120 to 1200 m/z at a
   resolution of 60,000. MS^2 analysis was performed on the pooled-samples
   vial using the data dependent acquisition (DDA) mode. For this
   analysis, the AcquireX data acquisition workflow developed by
   ThermoFisher was applied. Briefly, this workflow increases the number
   of MS^2 acquisition, especially on low-intensity ions, through the
   creation of an inclusion list after a first injection of the sample and
   the establishment of a dynamic exclusion list occurring by the
   iterative sample analysis (involving 5–6 successive injections).

4.6. Metabolomics Data Processing

   The raw UHPLC-HRMS files were uploaded on the Compound Discoverer 3.3
   software (ThermoFisher Scientific, Bremen, Germany) for metabolomics
   analysis. The detailed analytic workflow is given in [167]Supplementary
   Data S9. Briefly, it includes peak detection, chromatogram alignment
   and peak grouping in features. Each feature corresponds to a specific
   m/z at a given retention time. Compounds were identified through (i)
   elemental composition prediction, (ii) search in mass/formula
   databases, including local database and 11 public databases of which
   Chemspider, FoodDB, HMDB, LipidMaps and (iii) with the MS^2
   information, search in homemade and public spectral databases of which
   mzCloud, Mona, GNPS. When possible, the identification of metabolites
   was confirmed by comparison with authentic commercial standards. This
   was notably the case for rutin, caffeoyl-, feruloyl- and coumaroyl-
   putrescine and agmatine. The nature of
   N,N,N-tri-dihydrocaffeoylspermine was confirmed by comparison to the
   chemically synthesized compound. In a first attempt, we tried to
   prepare it as reported by [[168]66] using solid-phase synthesis.
   Despite careful following of the procedure, in our hands the final
   compound was always contaminated by side-products, exhibiting more than
   three dihydrocaffeoyl moieties as shown by LC-HRMS. Alternatively, we
   prepared it by classical liquid phase synthesis. Briefly, we first
   protected the catechol moiety of dihydrocaffeic acid as an acetonide by
   standard conditions [[169]67]. As reported by [[170]66], we protected
   both ends of spermine with Dde protecting group, then one of both
   secondary amine group was selectively Boc-protected. Removal of Dde
   groups let both primary amino groups and one secondary amine free.
   Coupling with three equivalents of cathecol-protected dihydrocaffeic
   acid gave the target compound as a protected form. Final acidic
   treatment afforded the desired compound whose identity and purity were
   proven by ^1H and ^13C NMR spectroscopy and HRMS. Complete protocol
   will be given elsewhere.

   Multivariate statistics on the metabolomics data were realized using
   the metaboanalyst platform ([171]https://www.metaboanalyst.ca/ accessed
   on 20 October 2021). A two-way analysis of variance (ANOVA, p < 0.05)
   was performed to identify metabolic features affected by herbivory and
   organ at each sampling date. In each case, a false discovery rate
   approach was performed as multiple testing correction. Features
   differentially affected by herbivory were determined by pair comparison
   considering the organ nature and the harvest date by using the
   differential analysis application of the Compound Discoverer 3.3
   software. The p-value of per group comparison was calculated by a
   one-way ANOVA, followed by the Tukey post-hoc test.

4.7. Extraction of Tomato Leaf RNA

   Total RNA extraction was realized from 100 mg frozen tissue (leaf, stem
   and root) using the E.Z.N.A. Plant RNA kit (Omega bio-tek, Norcross,
   GA, USA). An on-column-DNAse treatment (Qiagen, Hilden, Germany) was
   included during the RNA extraction. RNA quality was checked by
   electrophoresis on a 1% agarose gel. RNA samples were quantified using
   absorbance at 260 nm, their purity was evaluated by the 260/280 nm
   absorbance ratio and their integrity by determining and considering an
   RNA Integrity Number (RIN) > 7 (Agilent BioAnalyzer 2100).

4.8. Construction and Analysis of RNAseq Libraries

   A total of 12 RNAseq libraries were constructed, corresponding to two
   infestation treatments (T. absoluta infested leaf vs. control leaf) and
   two harvest times (5 h and 24 h after larval deposit) in triplicates.
   Following the manufacturer recommendations (Eurofins Genomics,
   Ebersberg, Germany), 3 µg of RNA per sample were used to generate the
   libraries which were sequenced on an Illumina Hiseq 2500 platform to
   generate paired end 125 bp reads. Reads were processed and filtered
   using the Trimmomatic software [[172]68]. They were mapped on the
   tomato genome (ITAG2.4) using the BWA-MEM software [[173]69]. Fragments
   per kilobase of transcript per million mapped reads (FPKM) were
   calculated using the FeatureCounts software (Version 1.6.4) [[174]70].
   Data were cleaned (only transcripts > 1 cpm on at least 3 samples were
   selected), normalized using the TMM (Trimmed Mean of M-values)
   procedure implemented in the Bioconductor edgeR (v3.32.1) package
   [[175]71]. The differential gene expression was conducted with the
   glmfit option within the edgeR package with the following parameters
   |log Fold Change (FC)| > 1.5 with p-adj value of FDR method < 0.05.
   Functional annotations, such as gene ontologies and interproscan
   features, were extracted from ITAG2.4_protein_functional.gff3 file with
   additional annotations on phenylpropanoid and polyamine pathways from
   Solgenomics ([176]https://solgenomics.net/ accessed on 12 September
   2021). Gene set enrichment analysis (GSEA) was realized using the
   GOfuncR (v1.10.0) [[177]72] thanks to the gene ontology (GO) data
   [[178]73,[179]74] with GO graph version of 2019/07/06
   ([180]https://zenodo.org/record/3267438, accessed on 22 February 2022).
   The over/under represented GO were selected with a hypergeometric test
   (FWER value ≤ 0.05). KEGG pathway enrichment analysis was realized with
   the GAGE R package (V2.40.2) [[181]55], and pathways were selected by
   Stouffer method with the q-value <= 0.05. A map viewer was used for the
   visualization of DEG associated to pathways [[182]75].

   The results of the RNAseq differential analysis were confirmed by
   following the expression level of a selection of 10 genes in leaves of
   T. absoluta-infested and control tomato. The list of targeted genes and
   primers used is given in [183]Supplementary Data S10. The expression
   level was followed by RT-qPCR. For that purpose, a total of 200 ng of
   DNA-free RNA samples was reverse transcribed in a final volume of 20 µL
   using the RNA to cDNA kit (Life technologies, Tokyo, Japan). cDNAs were
   then diluted 10 times. Gene expression was measured by qPCR on a
   StepOnePlus Realtime PCR System (ThermoFisher Scientific, Bremen,
   Germany). Each PCR reaction was made in 20 µL containing primer pairs
   at 0.3 µM, 40 ng of cDNAs in 1x SYBR^® Premix Ex Taq^TM (Takara, Shiga,
   Japan) and followed the amplification protocol consisting in a
   denaturing step at 95 °C for 30 s, 40 cycles at 95 °C for 5 s and 60 °C
   for 30 s. The gene expression of each sample was calculated with three
   analytical replicates and normalized to the two internal control genes
   CAC and TIP41 [[184]76].

4.9. Expression and Purification of Recombinant Proteins

   The two full-length sequences (Solyc11g071470 and Solyc11g071480) were
   cloned from tomato genomic DNA using the primers listed in
   [185]Supplementary Data 10. The PCR products were sub-cloned first in
   the pCR8 vector (Invitrogen, Carlsbad, CA, USA), prior to sequencing
   and then transferred into pET28b His-tag expression vector as a
   BamHI-NotI fragment. The four expression vectors were introduced into
   E. coli strain BL21-DE3 by heat shock transformation, and the
   transformants were selected on kanamycin. Protein expression was
   realized by growing 50 mL of culture at 37 °C until a DO[600] comprised
   between 0.4 and 0.6. Then 1 mM of IPTG was added, and the culture was
   incubated for 22 h at 18 °C. The bacteria were then harvested by a
   5000× g centrifugation for 15 min at 4 °C, then washed three times in 5
   mL of PBS buffer (8.1 mM Na[2]HPO[4], 1.76 mM KH[2]PO[4], 2.7 mM KCl,
   137 mM NaCl, pH 7.4) and finally resuspended in 1 mL of PBS. Bacterial
   lysis was realized by three 30 s runs of sonication (Bandelin Sonoplus
   HD 2010 MS73 probe with an intensity of 200 W/cm²). After a final
   centrifugation at 16,000× g for 10 min at 4 °C, the supernatant
   containing the protein of interest was collected and stored at −20 °C.
   His-tag proteins were purified using a Ni-NTA purification system
   (Qiagen) by following the specification of the manufacturer. Purified
   His-tag proteins were then used directly to perform enzymatic assays.

4.10. Enzymatic Characterization

   CoA esters of p-coumaric, caffeic, dihydrocaffeic and ferulic acids
   were synthesized using the recombinant 4-CL enzyme from N. tabacum
   [[186]77]. Enzymatic assays were performed in a total volume of 100 µL
   containing potential acyl donors (caffeoyl-, dihydrocaffeoyl-,
   feruloyl-, and p-coumaroyl-CoA) and polyamines (putrescine, cadaverine,
   agmatine, spermidine, spermine, tyramine, octopamine, dopamine, and
   noradrenaline) as acyl acceptors in 100 mM Tris-HCl buffer, pH 9,
   containing 5 mM EDTA. For testing enzyme activity, the reactions were
   initiated by the addition of purified enzymes, incubated at 35 °C for 5
   min, and stopped by adding 50 µL of acetonitrile containing 1% HCl. The
   reaction mix was then centrifuged 10 min at 14,000× g and filtrated on
   0.2 µm filter before being analyzed on UPLC-DAD-ESI-MS following the
   protocol described in [[187]46]. Products were characterized according
   to their mass and mass fragmentation spectra. Product accumulation was
   quantified by measuring the area under peak and converted with respect
   to caffeic, ferulic and p-coumaric acid standard curves.

5. Conclusions

   The present study aimed at characterizing the response of young tomato
   plants to the herbivory of T. absoluta larvae. We developed an
   integrative approach combining untargeted metabolomic and
   transcriptomic analyses to characterize both the local and systemic
   metabolic responses. Our results highlighted an intense local response
   of the plant to the herbivory of the larvae. In the opposite, the
   systemic response was far less intense. Regarding the local response,
   metabolomics analyses revealed a very important increase in the
   accumulation of a wide range of phenolamides, some of which are
   reported for the first time in tomato. The transcriptomic analyses
   indicated a coherent up-regulation of both the polyamine and the
   phenylpropanoid pathways from which phenolamides are synthesized. In
   addition, our analyses allowed identifying two genes that we
   functionally characterized as putrescine hydroxycinnamoyl transferase.
   Overall, this study brings new comprehensive elements regarding the
   tomato/T. absoluta interaction, which could be used in the development
   of new strategies to control this pest.

Acknowledgments