Next Article in Journal
Dynamic Entropy of Two-Dimensional Active Brownian Systems in Colloidal Plasmas
Next Article in Special Issue
Research on Very Volatile Organic Compounds and Odors from Veneered Medium Density Fiberboard Coated with Water-Based Lacquers
Previous Article in Journal
Characterization and Valorization of the Agricultural Waste Obtained from Lavandula Steam Distillation for Its Reuse in the Food and Pharmaceutical Fields
Previous Article in Special Issue
Effects of Defoliation Treatments of Babica Grape Variety(Vitis vinifera L.) on Volatile Compounds Content in Wine
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Molecules
Volume 27
Issue 5
10.3390/molecules27051612
molecules-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Exploring the Volatiles Released from Roots of Wild and Domesticated Tomato Plants under Insect Attack

by
Ana Shein Lee Díaz
1,*,†,
Muhammad Syamsu Rizaludin
1,*,†,
Hans Zweers
1,
Jos M. Raaijmakers
1,2 and
Paolina Garbeva
1
1
Department of Microbial Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Droevendaalsesteeg 10, 6708 PB Wageningen, The Netherlands
2
Institute of Biology, Leiden University, 2333 BE Leiden, The Netherlands
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Molecules 2022, 27(5), 1612; https://doi.org/10.3390/molecules27051612
Submission received: 23 December 2021 / Revised: 18 February 2022 / Accepted: 24 February 2022 / Published: 28 February 2022
(This article belongs to the Special Issue Recent Advances in Volatile Organic Compounds Analysis in Various Matrices)
Browse Figures
Versions Notes

Abstract

:
Plants produce volatile organic compounds that are important in communication and defense. While studies have largely focused on volatiles emitted from aboveground plant parts upon exposure to biotic or abiotic stresses, volatile emissions from roots upon aboveground stress are less studied. Here, we investigated if tomato plants under insect herbivore attack exhibited a different root volatilome than non-stressed plants, and whether this was influenced by the plant’s genetic background. To this end, we analyzed one domesticated and one wild tomato species, i.e., Solanum lycopersicum cv Moneymaker and Solanum pimpinellifolium, respectively, exposed to leaf herbivory by the insect Spodoptera exigua. Root volatiles were trapped with two sorbent materials, HiSorb and PDMS, at 24 h after exposure to insect stress. Our results revealed that differences in root volatilome were species-, stress-, and material-dependent. Upon leaf herbivory, the domesticated and wild tomato species showed different root volatile profiles. The wild species presented the largest change in root volatile compounds with an overall reduction in monoterpene emission under stress. Similarly, the domesticated species presented a slight reduction in monoterpene emission and an increased production of fatty-acid-derived volatiles under stress. Volatile profiles differed between the two sorbent materials, and both were required to obtain a more comprehensive characterization of the root volatilome. Collectively, these results provide a strong basis to further unravel the impact of herbivory stress on systemic volatile emissions.

1. Introduction

Plant volatiles have been extensively studied due to their wide range of chemical classes and ecological functions [1]. Furthermore, the plant volatilome is considered as an extended metabolome, reflecting the plant’s physiological status. Often, the term volatilome refers to the totality of volatile compounds emitted by an organism under specific conditions [2]. Of particular ecological relevance are the volatile organic compounds (VOCs), small molecules with low molecular weight (<300 Da), lipophilic character and high-vapor pressure. VOCs emitted by a plant constitute a wide range of chemical classes including terpenes, terpenoids, alcohols, carbonyl compounds, aliphatic hydrocarbons, aromatic, sulfur and nitrogen containing compounds [3]. The rich chemical diversity of the plant’s volatilome is of ecological relevance, in particular for chemical communication with other (micro)organisms. For instance, plants emit volatiles to indicate the presence of open flowers, attack by herbivores, production of ripe fruit, and pathogen infection [4]. The emission of plant volatiles can significantly differ under non-stressed conditions (constitutive emission) or stressed conditions (induced emission). For example, upon fungal infection, the roots of Carex arenaria emitted different terpenes (e.g., the monoterpene (Z)-limonene oxide than roots of noninfected plants [5]. Plants are constantly challenged by different biotic and abiotic stresses and the emission of induced volatiles can directly reduce the intensity of the stress or act as indirect defense by attracting natural enemies (predators, parasitoids) of insect herbivores [6]. However, chemical-ecological studies have focused mostly on plant volatiles in aboveground interactions, whereas the chemical diversity and importance of volatiles in belowground communication has received much less attention.
Similar to aboveground plant tissues, stress-related responses involving secondary metabolites occur belowground. Compared to soluble compounds that accumulate around the root epidermal cells, volatiles can readily diffuse via air- and gas-filled pores in the soil matrix and play a role in long-distance interactions [7]. A recent study in our lab revealed differences in root-emitted volatiles between roots of healthy tomato plants and those infected by the root pathogenic fungus Fusarium oxysporum [8]. Root volatiles are not only produced locally upon infection by root pathogens but can also be induced systemically belowground upon stress aboveground [9]. For example, in Brassicaceae plants, roots release sulfurous volatiles in response to aboveground herbivory [10]. Plant volatile production upon stress is regulated by plant hormones, with jasmonic acid (JA) as a key hormone in plant defense against insect herbivores and in the production of terpenes [11]. Upon local or systemic stress, root volatiles can play multiple roles in indirect defense, serving as chemoattractant or as a carbon source for root-associated beneficial microbes [12].
The trade-off between constitutive and induced plant defenses has been proposed to be affected by plant domestication [13]. For example, several modern tomato cultivars have less tolerance to insect pests than their wild relatives [14]. Contrarily, it has been observed that the modern species S. lycopersicum cv Better Boy has a higher ability of induced defenses compared to wild tomato species, and increased volatile production upon herbivory stress [15]. Nonetheless, the relationship between domestication and root volatile emissions remains largely elusive.
The aim of our study is to explore the root volatilome of a wild and a modern tomato species under herbivory stress. We trapped the root volatiles from the headspace in a compartmentalized setup using two different sorbent materials: polydimethylsiloxane (PDMS) in silicon-based tubes and commercial coated probes (HiSorbTM). These materials have been reported to be widely used for passive sampling of volatiles from soil and roots [16,17,18]. Combining these two trapping methods, we compared the root volatilome of the domesticated tomato Solanum lycopersicum cv Moneymaker with that of its wild relative Solanum pimpinellifolium under attack of the leaf herbivore insect Spodoptera exigua. Our hypothesis is that upon the same stress, the two tomato species have a different capacity of mounting defenses that is reflected in a different root volatile profile.

2. Results

We investigated the root volatilome of the two tomato species S. pimpinellifolium and S. lycopersicum cv Moneymaker (hereafter referred to as S. lycopersicum) under stress in an in vitro setup (Figure S1). For that purpose, five replicates (n = 5) of each species were subjected to leaf-chewing herbivore insect S. exigua. (S. exigua = SE). Two trapping materials, PDMS and HiSorb, were placed in the root headspace compartment 24 h after insect exposure. Similarly, five replicates of each species without insect pest were used as non-stressed control plants (Control S. exigua = CSE).

2.1. Root Volatile Compound Detection Is Trapping-Material Dependent

By employing two trapping materials (HiSorb and PDMS), a total of 17 volatile compounds were detected in the S. lycopersicum root headspace and 16 compounds in that of S. pimpinellifolium (Figure 1). More volatile compounds were detected with HiSorb than with PDMS traps in both tomato species. From the 17 compounds detected in S. lycopersicum, seven compounds (41.2%) were commonly detected by HiSorb and PDMS. The remaining ten compounds were detected either with HiSorb (eight) or PDMS (two). In a similar way, for S. pimpinellifolium, the two trapping materials commonly detected only four (25%) out of the total compounds (Figure 1). The majority of the remaining volatile compounds were detected by HiSorb (nine) in comparison to PDMS (three). In conclusion, the detection of root-volatile compounds is highly trapping-material dependent.
The differences between trapping materials, therefore, did not only affect the number of identified volatile compounds, but also the volatilome of each tomato species exposed (or not) to insect stress. The volatilome of each sample consists of the number of volatile compounds and their relative concentration or intensity in the volatile profile. The principal component analysis (PCA) showed that the root volatilome of control (CSE) and stressed (SE) plants differed between species (Figure 2) and these differences were also affected by the trapping materials. Regardless of the species, the root volatilome detected by HiSorb presented a clearer separation between CSE and SE than the volatilome detected by PDMS (Figure 2a–d).

2.2. Effects of Leaf Herbivory on Root Volatilome

To obtain a more comprehensive view of the root volatilome, we analyzed the combination of compounds detected by both trapping materials for qualitative analysis. This analysis aimed to find differences in the type of volatile compounds induced by insect herbivory on S. lycopersicum and on S. pimpinellifolium. S. pimpinellifolium presented the largest difference between control (CSE) and insect stress (SE). Stress-related compounds were those present in three or more replicates in stressed (SE) plants and less than three replicates in control (CSE) plants. Following these criteria, 2-nonenal was identified as a stress-related compound in S. lycopersicum, whereas dimethyl disulfide (DMDS), methyl salicylate (MESA), and benzyl alcohol were identified as stress-related compounds in S. pimpinellifolium (Figure 3). Contrarily, some compounds were not found in stressed plants but only in control plants, thus were considered as nonstress-related compounds. Those were the unknown 974 in S. lycopersicum and α-phellandrene and α-terpinene in S. pimpinellifolium (Figure 3).
Despite their different volatilomes, the wild and modern tomato species shared ten common volatile compounds: a group of six terpenes (α-phellandrene, α-pinene, α-terpinene, β-phellandrene, D-limonene, and p-cymene), benzyl alcohol, methyl salicylate and the unknown compounds Unknown 1087 and Unknown 1114 (Table 1 and Table 2).
Considering the two trapping materials, 17 compounds were identified in the S. lycopersicum root headspace (Table 1). These compounds represented six different chemical classes: seven monoterpenes (α-pinene, 2-carene, α-phellandrene, α-terpinene, p-cymene, d-limonene, and β-phellandrene), two oxygenated aliphatic compounds (heptanal, 2-nonenal), an aliphatic hydrocarbon (3-nonene), an alcohol (benzyl alcohol), an aromatic ketone (1-(2-hydroxyphenyl)-ethanone) and an aromatic ester (methyl salicylate). Most compounds were commonly identified in both treatments; only 2-nonenal was considered as a stress-related compound. Also, benzyl alcohol and unknown 1172 were considered as stress-related compounds but only according to one trapping material (Hisorb and PDMS, respectively) (Table 1).
We performed a quantitative analysis to determine differences in compound intensity upon stress. Univariate analysis (T-test) confirmed that in S. lycopersicum, three compounds presented a significantly different peak area between control and stressed plants. Benzyl alcohol and unknown 1172 presented an increased emission in SEMON plants (p-value: benzyl alcohol = 0.008 *, unknown 1172 = 0.046 *), whereas 3-nonene was higher in CSEMON plants (p-value 3-nonene = 0.026 *) (Figure 4). Although there was no statistical significance, a decrease in terpene production under stress conditions was observed; e.g., 2-carene, D-limonene, and α-pinene, present in both treatments, showed higher peak areas in CSEMON plants. Similarly, 1-(2-hydroxyphenyl)-ethanone peak area was also reduced upon stress. Despite 2-nonenal was only detected in stressed SEMON plants, it did not present statistical differences in peak area between treatments (Figure 4).
In S. pimpinellifolium plants, 16 compounds were detected considering both trapping materials (Table 2). The compounds represented four chemical classes: monoterpenes (α-pinene, camphene, β-pinene, α-phellandrene, α-terpinene, p-cymene, D-limonene, β-phellandrene, and γ-terpinene), one sulfur compound (DMDS), an aromatic ester (MESA), and an alcohol (benzyl alcohol). Despite representing fewer chemical classes than its modern relative S. lycopersicum, this species showed more qualitative differences between stressed and non-stressed volatilomes by emitting three stress-related compounds and three nonstress-related compounds (β-phellandrene only when detected with HiSorb).
From a quantitative perspective, eight compounds presented a significantly different peak area between control and stressed plants (Figure 5). Univariate analysis (T-test) confirmed that in S. pimpinellifolium, seven terpene compounds presented a significantly higher peak area in control CSEPIM plants (p-values: α-terpinene = 0.006 **, D-limonene = 0.01 **, camphene = 0.016 *, γ-terpinene = 0.016 *, β-pinene = 0.023 *, α-phellandrene = 0.027 * and α-pinene = 0.027 *). Hence, upon leaf-herbivory stress, a significant reduction of terpene emission was observed in the wild tomato species. In particular, α-phellandrene and α-terpinene were uniquely present in control (as previously shown in Table 2 and Figure 3), whereas α-pinene, β-pinene, camphene, D-limonene, and γ-terpinene were present in both treatments but with different peak areas (normalized peak area). Dimethyl disulfide, benzyl alcohol, and methyl salicylate emissions were increased under stress conditions (SEPIM), but only DMDS was statistically significant (p-value dimethyl disulfide = 0.02 *).

3. Discussion

Plants release a vast array of primary and secondary metabolites from their roots including, volatile organic compounds. However, studies on root volatiles remain challenging due to the complexity of belowground volatile-trapping and sample preparation [20,21]. Factors like the compound volatility, soil pore diameter, composition of the solid soil matrix phase, and the relative humidity of the soil matrix can impact the diffusion and thus detectability of the compounds [7]. Therefore, we developed a compartmental system allowing root-volatile collection in a controlled in vitro design (Supplementary Figure S1). This system enables the passive trapping of the volatiles through a headspace in a sterile, nondestructive and scalable system. By employing this two-compartment system, we also ensure that the compounds trapped are only volatiles released by roots. In addition to the experimental design, the selection and comparison of the trapping materials is often overlooked and rarely included in the experimental setup. Recently, Diez-Simon et al. [22] have shown that measuring the same sample with different trapping methods can provide different volatile profiles; some extracted a broad spectrum of chemical classes, while others presented higher affinity for certain chemical classes. This study exemplifies the importance of including different trapping methods or materials and selecting the most appropriate for the study.
In our experiments, we compared and combined the trapping capacity of PDMS tubes versus commercial HiSorb probes. In general, each material presented a different trapping capacity with HiSorb traps detecting more compounds than PDMS. The number of commonly detected compounds ranged from 25% to 41% (in S. pimpinellifolium and S. lycopersicum, respectively) of the overall volatilome (considered here as the sum of volatiles detected by both trapping materials). Thus, if the trapping relies only on one sorbent material, the representativity of the volatilome might be incomplete, leading to possible misinterpretations or biased conclusions. Although HiSorb probes contain the same extraction phase (polydimethylsiloxane) as the PDMS tubes, they showed a higher trapping capacity. It might be possible that the coating of the extraction phase in HiSorb probes improves the sensitivity of the trap, whereas, in PDMS tubes, there might be a greater compound competition for the extraction phase. It is known that volatile competition for the phase is a disadvantage of solid-phase microextraction (SPME) and that the most concentrated compounds can saturate the phase’s surface [21,22,23]. Therefore, despite having the same extraction phase material, HiSorb probes and PDMS tubes can have different volatile concentration equilibria and capacity of compound retention.
We combined the compounds detected by the two trapping materials to obtain a more comprehensive root volatilome for each species. Both species differed in the number and type of stress-associated compounds. The compound detectability and therefore results interpretation, was affected by the sensitivity of trapping materials. Regardless of the species, PCA analysis showed that volatile profiles detected with HiSorb presented a clearer difference between CSE and SE treatments than those trapped with PDMS. Such differences may be due to the higher efficiency of HiSorb than PDMS.
In general, the wild species S. pimpinellifolium presented the largest volatilome differences between control and herbivore-stressed plants; for instance, stressed SEPIM plants emitted the sulfur compound dimethyl disulfide (DMDS). Plant production of DMDS upon systemic damage has been documented [8,10] but to our knowledge, the induced production of DMDS in tomato roots upon aboveground herbivory has not been yet reported. Other stress-related compounds found in S. pimpinellifolium were methyl salicylate and benzyl alcohol. Methyl salicylate (MESA) is the methyl ester of the phytohormone salicylic acid (SA), which has a crucial role in plant defense. MESA, a volatile version of SA, might be produced by the plant to control the pool of active SA [24] and as a systemic messenger of defense signals [25]. However, MESA has been related to susceptibility in tomato to Fusarium oxysporum f. sp. lycopersicum [26] and attraction of root nematodes [27]. Although the exact role of MESA is not fully understood, it is possible that MESA levels can be an indirect marker of plant defense activation. Similar to MESA, benzyl alcohol has also been detected as stress-related in S. lycopersicum roots, being the only common stress-related compound between the two species. Benzyl alcohol has been reported as a volatile compound related to drought-stress in tea plants and emitted upon the release of glycosides during cell destruction [28]. The same compound was also emitted by P. trichocarpa leaves upon the infestation by the poplar leaf beetle (Chrysomela populi) [29]. Recently, a study has associated benzyl alcohol emission with fragrance absence in flowers from apricot trees [30]. Through transcriptomic analysis, the authors found a correlation between the activation of the phenylalanine ammonia-lyase (PAL) enzyme and the conversion of the scented volatile benzyl acetate into benzyl alcohol in nonfragrant flowers. While such volatile was documented aboveground, the evidence for the emission belowground remains elusive. In S. lycopersicum plants, in addition to benzyl alcohol, 2-nonenal and the unknown 1172 (possibly an aliphatic hydrocarbon) were also emitted under insect stress conditions. The volatile compound 2-nonenal is derived from fatty acid peroxidation in tomato leaves [31]. This compound has also been reported to impair spore germination of pathogenic fungi [32] and was associated with susceptibility to Fusarium oxysporum f. sp. lycopersicum [26].
Some volatiles were mainly detected under nonstress conditions (CSE). For both species, we observed an overall reduction of monoterpene production upon stress, which can be related to the trade-off between constitutive and induced defense [33,34]. Particularly, in S. pimpinellifolium, seven terpenes were significantly reduced upon stress. The systemic volatile emission is regulated by a complex phytohormonal balance. Studies have shown a positive correlation in leaves for jasmonic acid (JA)-terpene production: e.g., JA-deficient tomato plants were more susceptible to S. exigua due to lower production of terpenes [11]. Another study showed that upon Botrytis cinerea infection, tomato plants increase the production of terpenes derived from the lipoxygenase pathway (LOX) [35]. However, a root-specific monoterpene synthase was shown to be unaffected by herbivore wounding or JA application [36]. To date, the complex regulation of terpene production in the roots and particularly how it is affected by the aboveground stresses remains unknown.
The relationship between domestication and plant defense is still largely unknown. However, there is evidence about the link between aboveground stresses and genotype-dependent root volatile production. It has been shown that domestication negatively impacted the emission of the root volatile compound (E)-β-caryophyllene by maize plants, hence their ability to attract natural enemies (entomopathogenic nematodes) of the insect pest Diabrotica virgifera virgifera [34,37]. The domestication of tomato plants has been studied in the context of microbial recruitment and community assembly in the rhizosphere [38,39]. However, the impact of domestication on the root metabolome and in particular, on the root volatilome is still understudied. In our simplified in vitro system, we demonstrated that the root volatilome differs between a wild and a domesticated tomato species. It should be emphasized that the number of species tested is too small and should be extended to identify the impact of domestication on root volatilomes. Nevertheless, our survey did reveal that the genetic background of the host plant affects the root volatilome in response to leaf herbivory, both quantitatively and qualitatively. This study paves the way for further functional analyses to unravel the impact of plant domestication on the production of root volatiles under biotic stresses.

4. Materials and Methods

4.1. Plant Growth and Herbivory Stress Induction

Two tomato species, Solanum lycopersicum cv Moneymaker (hereafter referred to as S. lycopersicum) (purchased from Bingenheimmer Saatgut AG, Echzell, Germany) and Solanum pimpinellifolium (provided by Wageningen University, Wageningen, The Netherlands), were used. Tomato seeds were surface sterilized for 2 min in 70% (v/v) ethanol followed by 15 min in 1.5% (v/v) aqueous sodium hypochlorite soln. and then washed three times with sterile distilled water. Then, sterile seeds were sown in one side of two-compartment Petri dishes (UV-sterilized) containing 20 mL of 0.5 Murashige and Skoog (MS) medium (1% agar, 1% sucrose, pH 5.7). The other compartment remained empty for volatile trapping (Figure S1). The plates were sealed with parafilm and each set of replicates (n = 5) from a treatment was put in an individual large plastic box and incubated in a climate chamber. The incubation condition was set constantly at 23 °C, 16/8 h light/dark photoperiod (180 mmol PAR) until harvest. After reaching 3–4 true leaves, five replicates of each tomato species were stressed by Spodoptera exigua. Briefly, S. exigua eggs (obtained from Entocare N.V., Netherlands) and hatched larvae were reared with artificial diet (Table S2) in a growth chamber (20 °C) for 10 days prior to their introduction to plants. After the rearing period, two larvae at third-instar stage (L3) were put inside a mesh bag that covered each plant replicate (SE) for 24 h (Figure S1). Control plants were covered with the mesh bag but did not contain any caterpillar (CSE).

4.2. Trap conditioning (PDMS and HiSorb)

Polydimethylsiloxane (PDMS) tubes (internal diameter 1 mm, external diameter 1.8 mm, Carl Roth, Karlsruhe, Germany) were cut into pieces with a length of 5 mm. For each sample, two pieces were inserted in a sterile needle for easy handling. For conditioning, the tubes were fully immersed on a mixture acetonitrile/methanol (4/1, v/v) and incubated for 16 h (overnight) at room temperature. The tubes were then dried under pure nitrogen (N2) flow (5 L min−1) and heated at 210 °C for 1.5 h under helium flow (5 L min−1). The conditioned tubes along with the needles were then stored in clean glass vials (previously flushed with argon for 10 s). For conditioning the HiSorb material (model H1-AXABC, Markes International Ltd., Llantrisant, UK), probes were preconditioned at 280 °C for 1 h using a U-CTE micro-chamber/thermal extractor (Markes International Ltd., Llantrisant, UK) prior to insertion into a clean, empty metal holder with screw caps at both ends (Markes International Ltd., Llantrisant, UK). The metal holders containing HiSorb probe were then stored in a well-ventilated laboratory at room temperature until usage.

4.3. Root Volatile Collection

The in vitro cultivation of tomato plants using sterile two-compartment Petri dishes allows passive collection of root volatiles while minimizing interfering volatiles originating from contaminants. Passive trapping was done by introducing HiSorb and PDMS traps in the empty side of the two-compartment Petri dish. All compounds trapped in the root headspace with a passive diffusion method were considered volatiles. To maintain system in sterility, the plates were opened under the flow cabinet and subsequently the traps were placed into each empty compartment. For plants from experiment two (S. exigua infested) root volatiles of five replicates (SE n = 5, CSE n = 5) were collected simultaneously by one HiSorb and two PDMS tubes per plate after 24 h of stress introduction. Additionally, for the negative control, the traps were also placed in the empty side of the two-compartment plates containing only MS medium (without any plants). Plates were sealed again with parafilm and the traps stayed inside for approximately 3 h at the same conditions as the growth chamber (20 °C). Then, the plates were brought back again under the flow cabinet to extract the traps and stored them until measurement (HiSorb probes at room temperature and PDMS tubes in vials at −20 °C).

4.4. GC/Q-TOF Measurement

The volatile organic compounds were desorbed from PDMS tubes and from HiSorb probes using an automatic desorption unit (Unity TD-100, Markes International, Llantrisant, UK) with the helium gas at 50 mL min−1 at the temperature of 240 °C for 8 min. The released volatile compounds were then trapped with a cold trap at −10 °C and reheated at 280 °C for 5 min. The volatiles were then transferred splitless or with split 1:9 (280 °C transfer line) to the GC/Q-TOF (model Agilent 7890B GC and the Agilent 7200A Q-TOF, Santa Clara, CA, USA) with an DB-5 ms ultra-inert column (30 m length, 0.25 mm internal diameter, 0.25 μm film thickness, Agilent Technologies, Inc., Santa Clara, CA, United States) with a run time of 35.6 min and a flow of 1.2 mL/min (constant flow). The temperature program was set to 39 °C for 1 min followed by heating up to 315 °C with 10 °C/min and holding for 7 min. Then, volatile compounds were detected by the GC/Q-TOF system running at 70 eV in electron ionization (EI) mode with a temperature source of 230 °C. The mass spectra of the volatile compounds were acquired in full-scan-mode (m/z 30–400, 4 scans/s, 2 GHz Extended Dynamic Range). Calibration of retention index (RI) was calculated from a reference alkane standard solution; 1μl was injected in an empty Tenax trap and measured with the same parameters as described before.

4.5. GC/Q-TOF Data Analysis

GC/Q-TOF raw data (.D) were translated to content definition file (.cdf) format with GC AIA translator B.07.04 (Agilent Technologies, Santa Clara, CA, USA). Converted files were then imported into MzMine v2.53 [40,41] for further analysis. Briefly, Automated Data Analysis Pipeline (ADAP) algorithm was employed to perform chromatogram building, peak deconvolution, spectral deconvolution and alignment steps [42] (parameters details are provided in Table S2. The peak intensity (area) tables were then exported as comma-separated value (.csv) files. Subsequently, the mass features were manually checked and only selected for qualitative analysis when present at least in 3 out of 5 replicates to be considered as true features representing volatile compounds. Furthermore, mass features were further filtered by eliminating those that were also present in MS medium treatment, to ensure that the compounds are only emitted by roots. Volatile identification was performed using Mass Hunter (Qualitative Analysis v10, Agilent Technologies Inc.) by comparing their retention index (RI) and mass spectrum with the NIST 2020 V2.20 (National Institute of Standards and Technology, United States) which consists of more than 300,000 spectra representing more than 300,000 unique compounds. Further details on the mass spectra comparison are available in Supplementary information. Compounds with a RI differences larger than 10 index units were not considered [43]. Furthermore, compound identification was based on the metabolite identification categories described by Sumner et al. [19]: unknown compounds = level 4 (quantified and differentiated by spectral data), rest of compounds = level 2 (putatively annotated based on spectral similarity to public database). Briefly, we assigned a compound name when it matched to a mass spectrum and retention index (RI) of the NIST library, otherwise we described it as “unknown” for which identification level was not conclusive.

4.6. GC/Q-TOF Data Visualization and Statistical Analysis

To elaborate the graphs, we combined the compounds detected in both HiSorb and PDMS to obtain a comprehensive volatile list. The Euler plots were elaborated by assessing compound presence or absence based on a minimum detection level of 3 out of 5 replicates using R studio (R Studio 2021.09.0, build 351). The principal component analysis (PCA) plots were based on the peak intensity (area) tables of filtered mass features (minimum n = 3/5 replicates) obtained as explained in Section 4.5 and made with MetaboAnalyst v 5.0 [44]. For statistical analyses, the same peak area tables of the filtered mass features were normalized via logarithmic transformation and mean-centering using the MetaboAnalyst R package [44]. t-test was applied to analyze peak area differences between treatments.

5. Conclusions

Our study shows that the root volatilome of tomato can be impacted by domestication. The wild relative Solanum pimpinellifolium presented a different volatilome than its modern relative, Solanum lycopersicum cv Moneymaker. In addition, the two species reacted differently to herbivory stress, both quantitatively and qualitatively. The wild species revealed the largest differences between stressed and non-stressed volatilome in terms of the number of induced compounds detected and loss of or reduced emission of constitutively emitted compounds. Characterization of the root volatilome of the two species, both under stress and non-stressed condition, was trapping-material dependent. In particular, HiSorb was the sorbent material that presented the best trapping capacity across samples and treatments. Nonetheless, neither of the two trapping materials fully trapped the totality of the compounds detected. Thus, in order to improve the accuracy of volatile detection, the selection of the trapping material and use of more than one trapping material are crucial for reliable volatilome analyses and unbiased ecological conclusions about the role of volatiles.

Supplementary Materials

The following are available online. Figure S1: Schematic representation of the in vitro experimental set up of experiment; List of mass spectra of identified compounds; Table S1: Spodoptera exigua artificial diet; Table S2: Parameters used for data processing using MZmine 2.53 (ADAP); Figure S2: Comparison of root biomass (dry weight) between treatments; Figure S3: Correlation plot between root VOC (α-pinene) with root biomass.

Author Contributions

Conceptualization, M.S.R., A.S.L.D., P.G. and J.M.R.; methodology, M.S.R. and A.S.L.D.; formal analysis, H.Z.; data curation, M.S.R. and A.S.L.D.; writing—original draft preparation, M.S.R., A.S.L.D. and P.G.; writing—review and editing, M.S.R., A.S.L.D., P.G. and J.M.R.; visualization, M.S.R.; supervision, P.G. and J.M.R.; funding acquisition, P.G. and J.M.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the European Union’s Horizon 2020 research and innovation program (MiRA project), grant number 765290 and by the Dutch Research Council (NWO/OCW), as part of the MiCRop Consortium programme Harnessing the second genome of plants (grant number 024.004.14).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Raw data files (in .cdf fomat) can be found in the Zenodo database accession number 5788930 (https://doi.org/10.5281/zenodo.5788930).

Acknowledgments

We would like to thank Saskia Gerards for the technical support during the experiment and Haymanti Saha and Alex Lammers for the data analysis recommendations.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Maffei, M.E. Sites of Synthesis, Biochemistry and Functional Role of Plant Volatiles. S. Afr. J. Bot. 2010, 76, 612–631. [Google Scholar] [CrossRef] [Green Version]
  2. Yuan, H.; Cao, G.; Hou, X.; Huang, M.; Du, P.; Tan, T.; Zhang, Y.; Zhou, H.; Liu, X.; Liu, L.; et al. Development of a Widely Targeted Volatilomics Method for Profiling Volatilomes in Plants. Mol. Plant 2022, 15, 189–202. [Google Scholar] [CrossRef] [PubMed]
  3. Dudareva, N.; Negre, F.; Nagegowda, D.A.; Orlova, I. Plant Volatiles: Recent Advances and Future Perspectives. Crit. Rev. Plant Sci. 2006, 25, 417–440. [Google Scholar] [CrossRef]
  4. Baldwin, I.T. Plant Volatiles. Curr. Biol. 2010, 20, R392–R397. [Google Scholar] [CrossRef] [Green Version]
  5. Schulz-Bohm, K.; Gerards, S.; Hundscheid, M.; Melenhorst, J.; De Boer, W.; Garbeva, P. Calling from Distance: Attraction of Soil Bacteria by Plant Root Volatiles. ISME J. 2018, 12, 1252–1262. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Holopainen, J.K.; Gershenzon, J. Multiple Stress Factors and the Emission of Plant VOCs. Trends Plant Sci. 2010, 15, 176–184. [Google Scholar] [CrossRef]
  7. Porte, A.; Schmidt, R.; Yergeau, É.; Constant, P. A Gaseous Milieu: Extending the Boundaries of the Rhizosphere. Trends Microbiol. 2020, 28, 536–542. [Google Scholar] [CrossRef] [PubMed]
  8. Gulati, S.; Ballhausen, M.-B.; Kulkarni, P.; Grosch, R.; Garbeva, P. A Non-Invasive Soil-Based Setup to Study Tomato Root Volatiles Released by Healthy and Infected Roots. Sci. Rep. 2020, 10, 12704. [Google Scholar] [CrossRef]
  9. Hiltpold, I.; Erb, M.; Robert, C.A.M.; Turlings, T.C.J. Systemic Root Signalling in a Belowground, Volatile-Mediated Tritrophic Interaction. Plant Cell Environ. 2011, 34, 1267–1275. [Google Scholar] [CrossRef] [Green Version]
  10. Danner, H.; Brown, P.; Cator, E.A.; Harren, F.J.M.; Van Dam, N.M.; Cristescu, S.M. Aboveground and Belowground Herbivores Synergistically Induce Volatile Organic Sulfur Compound Emissions from Shoots but Not from Roots. J. Chem. Ecol. 2015, 41, 631–640. [Google Scholar] [CrossRef] [Green Version]
  11. Bosch, M.; Berger, S.; Schaller, A.; Stintzi, A. Jasmonate-Dependent Induction of Polyphenol Oxidase Activity in Tomato Foliage Is Important for Defense against Spodoptera Exigua but Not against Manduca Sexta. BMC Plant Biol. 2014, 14, 257. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Rizaludin, M.S.; Stopnisek, N.; Raaijmakers, J.M.; Garbeva, P. The Chemistry of Stress: Understanding the ‘Cry for Help’ of Plant Roots. Metabolites 2021, 11, 357. [Google Scholar] [CrossRef]
  13. Milla, R.; Osborne, C.P.; Turcotte, M.M.; Violle, C. Plant Domestication through an Ecological Lens. Trends Ecol. Evol. 2015, 30, 463–469. [Google Scholar] [CrossRef] [PubMed]
  14. Ferrero, V.; Baeten, L.; Blanco-Sánchez, L.; Planelló, R.; Díaz-Pendón, J.A.; Rodríguez-Echeverría, S.; Haegeman, A.; De la Peña, E. Complex Patterns in Tolerance and Resistance to Pests and Diseases Underpin the Domestication of Tomato. New Phytol. 2020, 226, 254–266. [Google Scholar] [CrossRef]
  15. Paudel, S.; Lin, P.-A.; Foolad, M.R.; Ali, J.G.; Rajotte, E.G.; Felton, G.W. Induced Plant Defenses Against Herbivory in Cultivated and Wild Tomato. J. Chem. Ecol. 2019, 45, 693–707. [Google Scholar] [CrossRef] [PubMed]
  16. Eilers, E.J.; Pauls, G.; Rillig, M.C.; Hansson, B.S.; Hilker, M.; Reinecke, A. Novel Set-Up for Low-Disturbance Sampling of Volatile and Non-Volatile Compounds from Plant Roots. J. Chem. Ecol. 2015, 41, 253–266. [Google Scholar] [CrossRef] [Green Version]
  17. Cheng, Z.; Mannion, D.T.; O’Sullivan, M.G.; Miao, S.; Kerry, J.P.; Kilcawley, K.N. Comparison of Automated Extraction Techniques for Volatile Analysis of Whole Milk Powder. Foods 2021, 10, 2061. [Google Scholar] [CrossRef]
  18. Tholl, D.; Hossain, O.; Weinhold, A.; Röse, U.S.R.; Wei, Q. Trends and Applications in Plant Volatile Sampling and Analysis. Plant J. 2021, 106, 314–325. [Google Scholar] [CrossRef]
  19. Sumner, L.W.; Amberg, A.; Barrett, D.; Beale, M.H.; Beger, R.; Daykin, C.A.; Fan, T.W.-M.; Fiehn, O.; Goodacre, R.; Griffin, J.L.; et al. Proposed Minimum Reporting Standards for Chemical Analysis. Metabolomics 2007, 3, 211–221. [Google Scholar] [CrossRef] [Green Version]
  20. Wardencki, W.; Curyło, J.; Namieśnik, J. Trends in Solventless Sample Preparation Techniques for Environmental Analysis. J. Biochem. Biophys. Methods 2007, 70, 275–288. [Google Scholar] [CrossRef]
  21. Brown, R.W.; Mayser, J.P.; Widdowson, C.; Chadwick, D.R.; Jones, D.L. Dependence of Thermal Desorption Method for Profiling Volatile Organic Compound (VOC) Emissions from Soil. Soil Biol. Biochem. 2021, 160, 108313. [Google Scholar] [CrossRef]
  22. Diez-Simon, C.; Ammerlaan, B.; Van den Berg, M.; Van Duynhoven, J.; Jacobs, D.; Mumm, R.; Hall, R.D. Comparison of Volatile Trapping Techniques for the Comprehensive Analysis of Food Flavourings by Gas Chromatography-Mass Spectrometry. J. Chromatogr. A 2020, 1624, 461191. [Google Scholar] [CrossRef] [PubMed]
  23. Pawliszyn, J. Theory of Solid-Phase Microextraction. J. Chromatogr. Sci. 2000, 38, 270–278. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Tieman, D.; Zeigler, M.; Schmelz, E.; Taylor, M.G.; Rushing, S.; Jones, J.B.; Klee, H.J. Functional Analysis of a Tomato Salicylic Acid Methyl Transferase and Its Role in Synthesis of the Flavor Volatile Methyl Salicylate. Plant J. 2010, 62, 113–123. [Google Scholar] [CrossRef] [PubMed]
  25. Forouhar, F.; Yang, Y.; Kumar, D.; Chen, Y.; Fridman, E.; Park, S.W.; Chiang, Y.; Acton, T.B.; Montelione, G.T.; Pichersky, E.; et al. Structural and Biochemical Studies Identify Tobacco SABP2 as a Methyl Salicylate Esterase and Implicate It in Plant Innate Immunity. Proc. Natl. Acad. Sci. USA 2005, 102, 1773–1778. [Google Scholar] [CrossRef] [Green Version]
  26. Hernández-Aparicio, F.; Lisón, P.; Rodrigo, I.; Bellés, J.M.; López-Gresa, M.P. Signaling in the Tomato Immunity against Fusarium Oxysporum. Molecules 2021, 26, 1818. [Google Scholar] [CrossRef]
  27. Murungi, L.K.; Kirwa, H.; Coyne, D.; Teal, P.E.A.; Beck, J.J.; Torto, B. Identification of Key Root Volatiles Signaling Preference of Tomato over Spinach by the Root Knot Nematode Meloidogyne Incognita. J. Agric. Food Chem. 2018, 66, 7328–7336. [Google Scholar] [CrossRef] [PubMed]
  28. Jin, J.; Zhao, M.; Gao, T.; Jing, T.; Zhang, N.; Wang, J.; Zhang, X.; Huang, J.; Schwab, W.; Song, C. Amplification of Early Drought Responses Caused by Volatile Cues Emitted from Neighboring Tea Plants. Hortic. Res. 2021, 8, 1–12. [Google Scholar] [CrossRef]
  29. Lackus, N.D.; Schmidt, A.; Gershenzon, J.; Köllner, T.G. A Peroxisomal β-Oxidative Pathway Contributes to the Formation of C6-C1 Aromatic Volatiles in Poplar. Plant Physiol. 2021, 186, 891–909. [Google Scholar] [CrossRef]
  30. Bao, F.; Zhang, T.; Ding, A.; Ding, A.; Yang, W.; Wang, J.; Cheng, T.; Zhang, Q. Metabolic, Enzymatic Activity, and Transcriptomic Analysis Reveals the Mechanism Underlying the Lack of Characteristic Floral Scent in Apricot Mei Varieties. Front. Plant Sci. 2020, 11, 1622. [Google Scholar] [CrossRef] [PubMed]
  31. Wang, C.; Xing, J.; Chin, C.K.; Ho, C.T.; Martin, C.E. Modification of Fatty Acids Changes the Flavor Volatiles in Tomato Leaves. Phytochemistry 2001, 58, 227–232. [Google Scholar] [CrossRef]
  32. Hamilton-Kemp, T.R.; McCracken, C.T.; Loughrin, J.H.; Andersen, R.A.; Hildebrand, D.F. Effects of Some Natural Volatile Compounds on the Pathogenic FungiAlternaria Alternata AndBotrytis Cinerea. J. Chem. Ecol. 1992, 18, 1083–1091. [Google Scholar] [CrossRef] [PubMed]
  33. Rasmann, S.; Chassin, E.; Bilat, J.; Glauser, G.; Reymond, P. Trade-off between Constitutive and Inducible Resistance against Herbivores Is Only Partially Explained by Gene Expression and Glucosinolate Production. J. Exp. Bot. 2015, 66, 2527–2534. [Google Scholar] [CrossRef] [PubMed]
  34. Köllner, T.G.; Held, M.; Lenk, C.; Hiltpold, I.; Turlings, T.C.J.; Gershenzon, J.; Degenhardt, J. A Maize (E)-β-Caryophyllene Synthase Implicated in Indirect Defense Responses against Herbivores Is Not Expressed in Most American Maize Varieties. Plant Cell 2008, 20, 482–494. [Google Scholar] [CrossRef] [Green Version]
  35. Jansen, R.M.C.; Miebach, M.; Kleist, E.; Van Henten, E.J.; Wildt, J. Release of Lipoxygenase Products and Monoterpenes by Tomato Plants as an Indicator of Botrytis Cinerea-Induced Stress. Plant Biol. 2009, 11, 859–868. [Google Scholar] [CrossRef] [PubMed]
  36. van Schie, C.C.N.; Haring, M.A.; Schuurink, R.C. Tomato Linalool Synthase Is Induced in Trichomes by Jasmonic Acid. Plant Mol. Biol. 2007, 64, 251–263. [Google Scholar] [CrossRef] [Green Version]
  37. Rasmann, S.; Köllner, T.G.; Degenhardt, J.; Hiltpold, I.; Toepfer, S.; Kuhlmann, U.; Gershenzon, J.; Turlings, T.C.J. Recruitment of Entomopathogenic Nematodes by Insect-Damaged Maize Roots. Nature 2005, 434, 732–737. [Google Scholar] [CrossRef]
  38. Pérez-Jaramillo, J.E.; Mendes, R.; Raaijmakers, J.M. Impact of Plant Domestication on Rhizosphere Microbiome Assembly and Functions. Plant Mol. Biol. 2016, 90, 635–644. [Google Scholar] [CrossRef] [Green Version]
  39. French, E.; Tran, T.; Iyer-Pascuzzi, A.S. Tomato Genotype Modulates Selection and Responses to Root Microbiota. Phytobiomes J. 2020, 4, 314–326. [Google Scholar] [CrossRef]
  40. Pluskal, T.; Castillo, S.; Villar-Briones, A.; Orešič, M. MZmine 2: Modular Framework for Processing, Visualizing, and Analyzing Mass Spectrometry-Based Molecular Profile Data. BMC Bioinform. 2010, 11, 395. [Google Scholar] [CrossRef] [Green Version]
  41. Pluskal, T.; Korf, A.; Smirnov, A.; Schmid, R.; Fallon, T.R.; Du, X.; Weng, J.-K. CHAPTER 7: Metabolomics Data Analysis Using MZmine. In Processing Metabolomics and Proteomics Data with Open Software; The Royal Society of Chemistry: London, UK, 2020; pp. 232–254. [Google Scholar]
  42. Du, X.; Smirnov, A.; Pluskal, T.; Jia, W.; Sumner, S. Metabolomics Data Preprocessing Using ADAP and MZmine 2. In Computational Methods and Data Analysis for Metabolomics; Li, S., Ed.; Methods in Molecular Biology; Springer US: New York, NY, USA, 2020; pp. 25–48. ISBN 978-1-07-160239-3. [Google Scholar]
  43. Babushok, V.I.; Linstrom, P.J.; Zenkevich, I.G. Retention Indices for Frequently Reported Compounds of Plant Essential Oils. J. Phys. Chem. Ref. Data 2011, 40, 043101. [Google Scholar] [CrossRef] [Green Version]
  44. Pang, Z.; Chong, J.; Zhou, G.; De Lima Morais, D.A.; Chang, L.; Barrette, M.; Gauthier, C.; Jacques, P.-É.; Li, S.; Xia, J. MetaboAnalyst 5.0: Narrowing the Gap between Raw Spectra and Functional Insights. Nucleic Acids Res. 2021, 49, W388–W396. [Google Scholar] [CrossRef] [PubMed]
Molecules 27 01612 g001 550
Figure 1. Percentage of volatile compounds detected from roots of wild (S. pimpinellifolium) and domesticated (S. lycopersicum) tomato by two different trapping materials (HiSorb and PDMS). From top to bottom: total number of volatile compounds detected, percentage of volatile compounds detected commonly by both trapping materials (Common), exclusively detected by HiSorb or exclusively detected by PDMS.
Figure 1. Percentage of volatile compounds detected from roots of wild (S. pimpinellifolium) and domesticated (S. lycopersicum) tomato by two different trapping materials (HiSorb and PDMS). From top to bottom: total number of volatile compounds detected, percentage of volatile compounds detected commonly by both trapping materials (Common), exclusively detected by HiSorb or exclusively detected by PDMS.
Molecules 27 01612 g001
Molecules 27 01612 g002 550
Figure 2. Differences in root volatilome profiles between stressed (SE-red) and control (CSE-green) upon 24 h leaf hebivory. Principle component (PC) plots of S. lycopersicum root volatilomes trapped with HiSorb (a) or PDMS (b) and of S. pimpinellifolium trapped with HiSorb (c) or PDMS (d). For each plot, a single coloured dot represents the volatilome of one sample. Distances between dots are equivalent to variation between replicates. The shadowed coloured cluster represents the 95% interval of confidence.
Figure 2. Differences in root volatilome profiles between stressed (SE-red) and control (CSE-green) upon 24 h leaf hebivory. Principle component (PC) plots of S. lycopersicum root volatilomes trapped with HiSorb (a) or PDMS (b) and of S. pimpinellifolium trapped with HiSorb (c) or PDMS (d). For each plot, a single coloured dot represents the volatilome of one sample. Distances between dots are equivalent to variation between replicates. The shadowed coloured cluster represents the 95% interval of confidence.
Molecules 27 01612 g002
Molecules 27 01612 g003 550
Figure 3. Qualitative overview of root volatiles present uniquely in stressed (SE), control plants (CSE) or in both. Each Euler plot (left S. lycopersicum Moneymaker (MON), right S. pimpinellifolium (PIM)) shows the stress-related compounds in red as SEMON and SEPIM respectively, in the beige intersection the common compound found in both treatments and in green as CSEMON and CSEPIM respectively the nonstress related compounds.
Figure 3. Qualitative overview of root volatiles present uniquely in stressed (SE), control plants (CSE) or in both. Each Euler plot (left S. lycopersicum Moneymaker (MON), right S. pimpinellifolium (PIM)) shows the stress-related compounds in red as SEMON and SEPIM respectively, in the beige intersection the common compound found in both treatments and in green as CSEMON and CSEPIM respectively the nonstress related compounds.
Molecules 27 01612 g003
Molecules 27 01612 g004 550
Figure 4. Peak areas of main compounds detected in control CSEMON (green) and herbivory-stressed SEMON (red) S. lycopersicum roots. All compounds were detected with HiSorb except for 3-nonene (PDMS). Each box-plot depicts the distribution and median (horizontal line) of normalized and log10 transformed peak area of five replicates per treatment. oxplots indicated with an asterisk (*) differ statistically (p < 0.05), whereas box-plots indicated with NS did not show statistically significant differences.
Figure 4. Peak areas of main compounds detected in control CSEMON (green) and herbivory-stressed SEMON (red) S. lycopersicum roots. All compounds were detected with HiSorb except for 3-nonene (PDMS). Each box-plot depicts the distribution and median (horizontal line) of normalized and log10 transformed peak area of five replicates per treatment. oxplots indicated with an asterisk (*) differ statistically (p < 0.05), whereas box-plots indicated with NS did not show statistically significant differences.
Molecules 27 01612 g004
Molecules 27 01612 g005 550
Figure 5. Peak areas of compounds detected by HiSorb in control CSEPIM (green) and herbivory-stressed SEPIM (red) S. pimpinellifolium roots. Each box-plot depicts the distribution and median (horizontal line) of normalized and log10 transformed peak areas of five replicates per treatment. Boxplots indicated with an asterisk (*) differ statistically (p < 0.05), whereas box-plots indicated with NS did not show statistically significant differences
Figure 5. Peak areas of compounds detected by HiSorb in control CSEPIM (green) and herbivory-stressed SEPIM (red) S. pimpinellifolium roots. Each box-plot depicts the distribution and median (horizontal line) of normalized and log10 transformed peak areas of five replicates per treatment. Boxplots indicated with an asterisk (*) differ statistically (p < 0.05), whereas box-plots indicated with NS did not show statistically significant differences
Molecules 27 01612 g005
Table
Table 1. List of root volatile compounds identified in S. lycopersicum cv Moneymaker in stressed (SEMON) and non-stressed (CSEMON) plants detected with PDMS and HiSorb. Compounds marked with an asterisk (*) in the Treatment column were uniquely detected in the stressed (SE) or non-stressed (CSE) treatments with the indicated trapping material.
Table 1. List of root volatile compounds identified in S. lycopersicum cv Moneymaker in stressed (SEMON) and non-stressed (CSEMON) plants detected with PDMS and HiSorb. Compounds marked with an asterisk (*) in the Treatment column were uniquely detected in the stressed (SE) or non-stressed (CSE) treatments with the indicated trapping material.
Compound 1RI 2RI DatabaseTreatmentSorbent MaterialMolecular FormulaCAS
Solanum lycopersicum cv Moneymaker CSEMONSEMONPDMSHiSorb
3-Nonene892896xxx C9H1820063-77-8
Heptanal903901xxx C7H14O111-71-7
α-Pinene936937xx xC10H1680-56-8
Unknown 974974NAx * xNANA
2-Carene10011002xxxxC10H16554-61-0
α-Phellandrene10091005xx xC10H1699-83-2
α-Terpinene10191017xx xC10H1699-86-5
P-Cymene10281025xxxxC10H1499-87-6
D-Limonene10321031xxxxC10H165989-27-5
β-Phellandrene10341031xxxxC10H16555-10-2
Benzyl alcohol10381036xx *xx *C7H8O100-51-6
Unknown 10871087NAxxxxNANA
Unknown 11141114NAxx xNANA
2-Nonenal11611162 x * xC9H16O18829-56-6
1-(2-Hydroxyphenyl)-ethanone11661167xx xC8H8O2118-93-4
Unknown 11721172NAxx *x *xNANA
Methyl salycilate11991192xx xC8H8O3119-36-8
1 Identification of compounds based on the metabolite identification categories described by Sumner et al. [19]. List of mass spectrum match profiles with NIST 2020 database provided in Supplementary information. 2 RI is the retention index calculated from retention time and a reference n-alkane mix: RI database is the reference retention index used for identification from NIST 2020 database.
Table
Table 2. List of root volatile compounds found in S. pimpinellifolium in stressed (SEPIM) and non-stressed (CSEPIM) plants detected with PDMS and HiSorb. Compounds marked with an asterisk (*) in the Treatment column were uniquely detected in the stressed (SE) or non-stressed (CSE) treatments with the indicated trapping material.
Table 2. List of root volatile compounds found in S. pimpinellifolium in stressed (SEPIM) and non-stressed (CSEPIM) plants detected with PDMS and HiSorb. Compounds marked with an asterisk (*) in the Treatment column were uniquely detected in the stressed (SE) or non-stressed (CSE) treatments with the indicated trapping material.
Compound 1RI 2RI DatabaseTreatmentSorbent MaterialMolecular FormulaCAS
Solanum pimpinellifolium CSEPIMSEPIMPDMSHiSorb
Dimethyl disulfide747746 x * xC2H6S2624-92-0
α-Pinene936937xxxxC10H1680-56-8
Camphene953952xx xC10H1679-92-5
β-Pinene981979xx xC10H16127-91-3
α-Phellandrene10091005x * xC10H1699-83-2
Unknown (1011)1011NAxx xNANA
α -Terpinene10191017x * xC10H1699-86-5
P-Cymene10281025xxxxC10H1499-87-6
D-Limonene10321031xxxxC10H165989-27-5
β-Phellandrene10341031x *xxx *C10H16555-10-2
Benzyl alcohol10381036 x *x C7H8O100-51-6
γ-Terpinene10611060xx xC10H1699-85-4
Unknown (1087)1087NAxxx NANA
Unknown (1114)1114NAxxx NANA
Unknown (1166)1166NAxx xNANA
Methyl salicylate11991192 x * xC8H8O3119-36-8
1 Identification of compounds based on the metabolite identification categories described by Sumner et al. [19]. List of mass spectrum match profiles with NIST 2020 database is provided in Supplementary information. 2 RI is the retention index calculated from retention time and a reference n-alkane mix: RI database is the reference retention index used for identification from NIST 2020 database.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Lee Díaz, A.S.; Rizaludin, M.S.; Zweers, H.; Raaijmakers, J.M.; Garbeva, P. Exploring the Volatiles Released from Roots of Wild and Domesticated Tomato Plants under Insect Attack. Molecules 2022, 27, 1612. https://doi.org/10.3390/molecules27051612

AMA Style

Lee Díaz AS, Rizaludin MS, Zweers H, Raaijmakers JM, Garbeva P. Exploring the Volatiles Released from Roots of Wild and Domesticated Tomato Plants under Insect Attack. Molecules. 2022; 27(5):1612. https://doi.org/10.3390/molecules27051612

Chicago/Turabian Style

Lee Díaz, Ana Shein, Muhammad Syamsu Rizaludin, Hans Zweers, Jos M. Raaijmakers, and Paolina Garbeva. 2022. "Exploring the Volatiles Released from Roots of Wild and Domesticated Tomato Plants under Insect Attack" Molecules 27, no. 5: 1612. https://doi.org/10.3390/molecules27051612

Article Metrics

Back to TopTop