Aphid-induction of defence-related metabolites in Arabidopsis thaliana is dependent upon density, aphid species and duration of infestation


Plants display a wide range of chemical defence responses when challenged by sap feeding insects. In this study, we examined changes in leaf chemistry in Arabidopis thaliana when challenged by three species of aphid which were all able to grow and reproduce on Arabidopsis: a generalist with wide host range, Myzus persicae, and two brassica specialists Brevicoryne brassicae and Lipaphis pseudobrassicae. Most glucosinolates were reduced in concentration by aphid feeding, but Myzus persicae consistently increased the levels of 4-methoxy-indolyl-glucosinolate, which is a known feeding deterrent for M. persicae, whilst decreasing other indolyls, suggesting the plant is converting these compounds to the former. The foliar concentrations of jasmonic acid and salicyclic acid were increased by M. persicae but not by B. brasssicae and L. pseudobrassicae, whereas the phytoalexin camalexin and its precursor, the amino acid tryptophan, was induced after feeding by all three aphids. Many of the compounds induced by M. persicae (e.g., jasmonic acid; salicylic acid; camalexin; tryptophan; 4-methoxy-indolyl-glucosinolate) exhibited positive relationships with aphid density and the duration of feeding prior to harvest, indicating that they are responding to the overall level of herbivore challenge that has taken place. The study reinforces the need to consider components of the experimental system (e.g., insect density, insect species, duration of feeding prior to harvest) when making inter-study comparisons of the chemical responses of plants to aphid feeding.


The physiological, chemical and transcriptional responses induced in plants experiencing insect herbivory are now well documented, especially for systems involving model plant species such as Arabidopsis thaliana and Medicago truncatula (e.g., Goggin 2007; Kamphuis et al. 2013; Louis and Shah 2013; Jaouannet et al. 2014). Insect herbivores induce a wide range of chemical changes in plants which often involve the phytohormones jasmonic acid (JA), salicylic acid (SA) and abscisic acid (ABA), and secondary plant metabolites, such as glucosides, glucosinolates, alkaloids and phenolics (Bari and Jones 2009; Erb et al. 2012). JA plays multiple roles in plant defence to chewing insects and physical wounding (Zhu-Salzman et al. 2005; Thompson and Goggin 2006). When plants are attacked by phloem sap feeding insects such as aphids, penetration by the insect stylets is largely intercellular and, although some cells in the epidermis and mesophyll are punctured, physical damage to plant tissue is largely superficial (Jaouannet et al. 2014). This limited physical damage results in only minor JA-responses in the plant, and often produces chemical responses similar to that seen after challenge by pathogens (Moran and Thompson 2001; Moran et al. 2002; Zhang et al. 2015). Although SA can be induced by aphids, its induction does not occur in all aphid–plant interactions and does not always enhance plant resistance (Moran and Thompson 2001; Mewis et al. 2005; Pegadaraju et al. 2005). The effect of aphid feeding on ABA also appears inconsistent between studies: no effect on this hormone was reported for Myzus persicae feeding on tobacco or Acyrthosiphon pisum feeding on Medicago truncatula (Donovan et al. 2013; Stewart et al. 2016), but an increase in ABA was observed in soybean plants infested with soybean aphid (Studham and MacIntosh 2013) and an upregulation of ABA-associated genes in Arabidopsis was observed when the plant encountered feeding by Myzus persicae or was infiltrated by aphid saliva (Hillwig et al. 2016).

Phytoalexins are a heterogeneous group of compounds generally associated with host–plant resistance to microbial pathogens (Bennett and Wallsgrove 1994; Smith et al. 2009; Ahuja et al. 2012), although Stewart et al. (2016) found dramatic increases in foliar concentrations of medicarpin, a flavonoid phytoalexin, in M. truncatula leaves exposed to pea aphids, A. pisum. Pathogen infection and some molecular elicitors induce synthesis of camalexin (3-thiazol-2′-yl-indole), the main phytoalexin in Arabidopsis thaliana (Ahuja et al. 2012). Camalexin is synthesized from tryptophan via indole-3-acetaldoxime involving cytochrome P450 enzymes, although whether induction is linked to SA signalling, JA-signalling, ethylene concentration, auxins, H2O2, or some combination of these, is still not clear (Glawischnig 2007; Glawischnig et al. 2004; Ahuja et al. 2012). Defence against aphids in Arabidopsis is strongly linked to the PHYTOALEXIN DEFICIENT4 gene (PAD4), and increased expression of PAD4 can reduce aphid population size, feeding and settling behaviours (Louis and Shaw 2013; Rashid et al. 2017). The effects of camalexin on aphids, however, are not consistent among studies. Pegadaraju et al. (2005) reported that there was no effect of a pad3-1 Arabidopsis mutant on performance of M. persicae and so concluded that this aphid was not affected by camelexin synthesis. Camalexin has subsequently been found to reduce fecundity of M. persicae feeding on Arabidopsis genotypes containing camalexin, and inhibit M. persicae and B. brassicae when incorporated into artificial diet (Kuśnierczyk et al. 2008; Kettles et al. 2013). Mewis et al. (2012) found a difference in camalexin induction between aphid species: the specialist cabbage aphid, Brevicoryne brassicae induced camalexin accumulation in Arabidopsis, whereas the more generalist aphid Myzus persicae did not.

Glucosinolates (GSs) are hydrophilic compounds hydrolyzed by myrosinase enzymes (β-thioglucoside glycohydrolases) into isothyocyanates, thiocyanates and nitriles (Bones and Rossiter 1996; Rohr et al. 2009). The GS profiles of brassica species or ecotypes influences their resistance to insect herbivores, such as lepidopteran larvae and aphids (Pfalz et al. 2009; Rohr et al. 2009), and GSs can act as both feeding deterrents and as positive cues for host plant selection by aphids (Nault and Styer 1972; Powell et al. 2006). Feeding by aphids can increase or reduce foliar GSs (Kim and Jander 2007) and the effects of GSs on aphids are often dependent upon whether the aphid specialises on brassica host plants or has more generalist host use tendencies. For example, the brassica specialist B. brassicae can use GSs as host cues, show enhanced performance in plant varieties that have higher concentrations of some GSs, and can also sequester GSs for use in its own chemical defences against predators (Cole 1997; Powell et al. 2006; Pratt et al. 2008; but see; Mewis et al. 2005). Conversely, the generalist aphid M. persicae has shown decreases in fecundity, growth, population size and settling when encountering high GS concentrations (Mewis et al. 2005; Kim and Jander 2007; Kim et al. 2008; Pfalz et al. 2009).

Although many insect-induced plant responses appear consistent across different studies, discrepancies relating to which signalling pathways and secondary compounds are involved in defence still occur. Differences in plant responses to insect attack transpire because of a number of factors, including: herbivore functional guild (e.g., ‘chewers’ v ‘suckers’; Mewis et al. 2005); generalist or specialist host–plant interactions (Ali and Agrawal 2012; Mewis et al. 2012); interaction compatibility in terms of plant susceptibility and/or insect virulence (Stewart et al. 2009; Jaouannet et al. 2015); insect density (Donovan et al. 2013); insect feeding duration (Mai et al. 2014); and whether more than one herbivore species is present (Kroes et al. 2015). Variation in the effects of plant defence products on the plant itself can also vary depending on the age of the plant, genotype, and which plant tissue is considered (e.g., Wentzell and Kliebenstein 2008). Differences among experimental protocols are, therefore, often implicated in causing variation in plant responses among studies (Mewis et al. 2005; Kuśnierczyk et al. 2008; Stewart et al. 2016). The primary aim of this investigation was to explore how plant metabolites in Arabidopsis (hormones; amino acids; camalexin; GSs) are affected by a number of aspects of experimental design: aphid density, aphid feeding duration, and challenge by generalist and specialist brassica-feeding aphid species. We have focused on responses to the generalist aphid M. persicae and compared plant responses to challenge by the brassica specialists, B. brasssicae and L. pseudobrassicae. By doing multiple trials to address this aim, we have produced sufficient data to assess the repeatability of results, and identify groups of compounds that respond similarly to different aspects of aphid challenge.

Materials and methods


Arabidopsis thaliana seeds (Arabidopsis; Columbia 0; Nottingham Arabidopsis Stock Centre, UK) were sown in Levington F2 compost and stratified for 2 days at 4 °C. Seedlings were pricked out 2 weeks after stratification and transferred to individual 4 × 4 × 5 cm plastic plant cells. The plants were then maintained in a controlled environment chamber and grown under short day conditions (12:12 h dark:light at 125 µmol m−2 s−1, 22 °C day, 20 °C night) to encourage large leaf area and discourage bolting. Plants were used in experiments 6 weeks after stratification. All experiments were performed in the same growth chamber under the same environmental conditions.

For analysis of leaf material, leaves were cut from plants at the base of the lamina (to prevent inclusion of petiole tissue) using a razor blade and any aphids present gently removed using a paint brush. The leaves were snap-frozen in liquid nitrogen and freeze-dried for 3 days before storage at − 80 °C. Each independent experimental replicate for chemical analysis consisted of the pooled material from at least six leaves from each of two plants.

Aphid cultures

Three species of aphids were used in experiments: the peach-potato aphid Myzus persicae (Sulzer) (MP), the cabbage aphid Brevicoryne brassicae (L.) (BB) and the turnip aphid Lipaphis pseudobrassicae (Kaltenbach) (LP). All aphids were reared at low density on spring cabbage (Brassica oleracea L. cv. ‘Pixie’) and maintained in an insect-culturing facility where temperature was regulated at 19 ± 1 °C, relative humidity ranged between 50 and 80% and lighting was provided by racks of six 65 W fluorescent tubes (16:8 h light:dark).

To collect nymphs for experiments, apterous adult female aphids were allowed to produce offspring overnight (approx. 14 h) on detached cabbage leaves held in plastic Petri dishes with a moist filter paper in the base. The nymphs were maintained on these detached leaves for a further 2 days before being used in experiments. Nymphs were transferred into the central leaf rosette of Arabidopsis plants using a soft paint brush, and then restrained to the plant using a perforated plastic bag fastened around the plastic cell using an elastic band (control treatments not involving aphids were bagged in a similar fashion). Thus the aphids could roam over the entire plant and distribute themselves between leaves as they wished.

Response of Arabidopsis to aphid feeding

To examine how aphid feeding affected plant metabolites, and to investigate how any observed effects were influenced by aphid density, duration of aphid feeding and aphid species, four experiments were performed.

  1. (1)

    To gain an initial insight into the repeatability of plant responses induced by the aphids, we examined the effect of a single species of aphid, MP, at a single initial density (20 aphids per plant) and harvested plants at a single time point (80 h) after the aphids were introduced. Five experimental replicates (i.e., ten plants) of the aphid treatment and no-aphid control were set up. This combination of aphid species and density was then repeated (four replicates per treatment) to identify which plant responses occurred consistently between trials.

  2. (2)

    To examine the effect of aphid density on plant chemistry, MP were added to Arabidopsis with initial populations of 10, 20, 50 or 100 individuals placed into the central leaf rosette. The leaves were harvested from the plants 80 h after the aphids were introduced. Four experimental replicates were set up per density treatment, including a no-aphid (zero density) control.

  3. (3)

    To examine the effect of the duration of aphid feeding, 20 MP nymphs were added to Arabidopsis and the plants harvested 6 h, 30 h, 55 h and 80 h after the aphids were introduced. Control plants with no aphids were also harvested at the same time points. There were three replicates per treatment per time point.

  4. (4)

    To examine the effect of aphid species on plant chemistry, 20 nymphs of BB, LP or MP were added to Arabidopsis plants, and leaves harvested 80 h after the aphids were introduced. Four experimental replicates were set up per aphid species in addition to a no-aphid control.

Quantification of metabolites by liquid chromatography–mass spectrometry (LC–MS)

Procedures for chemical extraction from dried leaves followed Forcat et al. (2008). Ground leaf material (10 mg) was placed into a 2 ml round-bottomed microfuge tube along with a 3 mm tungsten bead, and two extractions performed. The first extraction used 400 µl of a 10% MeOH (LC–MS grade) and 1% acetic acid solution into which internal standards had been added to each sample: 2 μl each of JA (5 μg/ml), SA (6.9 μg/ml) and ABA (0.5 μg/ml) and 20 μl of sinigrin (2 mg/ml). For camalexin and the other metabolites no internal standards were used, and results were obtained as relative arbitrary units relating to the area of the analyte peak. The samples were homogenized using a Tissuelyser (QIAGEN Ltd, Crawley, UK) for 2 min at 30 Hz, placed on ice for 30 min before spinning down in a centrifuge at 13,200 rpm at 4 °C for 10 min. The supernatant from each sample was removed and placed in a centrifuge tube and kept on ice while the pellet was re-suspended in 400 µl of 10% MeOH and 1% acetic acid solution for the second extraction. The supernatant was then pooled with the previous sample.

All samples were then spun for a final 10 min at 13,200 rpm and 300–400 µl of the supernatant pipetted into 2 ml autosampler glass vials (Agilent Technologies, Stockport, UK) for HPLC-electrospray ionisation/MS–MS analysis (HPLC–MS). Targeted LC–MS analysis was used to measure concentrations of a number of metabolites related to defence responses in Arabidopsis (abbreviation are listed in Table 1). Analysis was carried out using an Agilent 1100 HPLC coupled to an Applied Biosystems Q-TRAP 2000 (Applied Biosystems, California, USA). The columns used for chromatographic separation at 35 °C were Phenomenex Luna 3 µm C18(2) 100 mm × 2 mm.

Table 1 Summary, classification and abbreviated codes of compounds extracted and measured from Arabidopsis foliage

Statistical analysis

From HPLC–MS analysis, relative concentrations of compounds were obtained in arbitrary units related to the area of the analyte peak. These relative concentrations were then standardized so that each lay on a percentage scale between the minimum and maximum concentration (in each experiment), using an equation adapted from Legendre and Legendre (1998):

$${\text{Relative}}\;{\text{concentration}}\;=\;\frac{{({\text{Sample}}\;{\text{conc}}.~ - ~\hbox{min} .\;{\text{conc}}.)~}}{{(\hbox{Max} .\;{\text{conc}}.~\; - \;\hbox{min} .\;{\text{conc}}.)}}~ \times 100\%$$

The metabolite profiles of the treatments within each experiment were compared by principal component analysis (PCA) based on a correlation matrix obtained from the transformed data, and then by analysis of similarity (ANOSIM) [Community Analysis Package Software; Clarke 1993; Henderson and Seaby 2008)]. The ANOSIM procedure examines whether samples from our pre-defined treatment groups are more similar in composition than samples from different groups, using an overall comparison and then by pairwise comparison of treatments (Henderson and Seaby 2008). To visualize which compounds were responding in a similar manner to challenge by aphids, a hierarchical cluster analysis was performed for each experiment, using a similarity matrix based on Pearson’s correlation coefficient and a group average clustering process (StatistiXL v2 add-on for Microsoft Excel).

Two methods were used to identify individual plant metabolites that had been affected by aphid feeding. The first method used Cohen’s d as an indicator of effect size by standardizing the difference between the mean concentration for each treatment and the mean of the relevant control, and dividing this difference by the pooled standard deviation (SD) (Cumming 2012):

$${\text{Cohen's}}\;d=\frac{{({\text{Mean}}\;{\text{treatment}} - {\text{Mean}}\;{\text{control}})\;}}{{{\text{Pooled}}\;{\text{SD}}}}$$

where for samples of size N:

$${\text{Pooled}}\;{\text{SD}}=~\sqrt {\frac{{\left( {{N_{{\text{treatment}}}} - 1} \right){\text{SD}}_{{{\text{treatment}}~}}^{2}+({N_{{\text{control}}~}} - 1){\text{SD}}_{{{\text{control}}}}^{2}}}{{({N_{{\text{treatment}}}}+~{N_{{\text{control~}}}} - 2)}}}$$

Secondly, for some compounds that were identified as showing strong responses to aphid feeding in terms of Cohen’s d, a conventional analysis of variance (ANOVA) was used to identify significant differences among treatment groups, and then treatments separated from the appropriate control group using Fisher’s least significant differences (LSDs; p < 0.05).


Principal component analysis and ANOSIM

For each trial, there was generally a distinct separation of samples based on leaf tissue chemistry of the different treatment groups (Fig. 1). The exception to this occurred in the time course experiment where separation of aphid-treated plants and control plants was less clear, mainly through the number of different time points considered (Fig. 1c). The combined variation explained by the first two PCA axes in the different trials was fairly low, ranging from 45.6 to 50.5% (Fig. 1). Nevertheless, for each trial, the ANOSIM procedure resulted in an overall significance probability of p < 0.001, providing strong evidence of statistically significant differences in the chemical compositions of leaves harvested from different treatments (Fig. 1).

Fig. 1

Plots of PCA Axis 2 versus Axis 1 scores based on the chemistry of Arabidopsis leaves exposed to different aphid treatments; a control versus infested with Myzus persicae, b infested with different initial densities of M. persicae, c not infested (circles) or infested (squares) by Myzus persicae for different durations; degree of shading indicates hpi d uninfested versus infested by either M. persicae (M.p), Brevicoryne brassicae (B.b) or Lipaphis pseudobrassicae (L.p). Vectors have been scaled to fit onto PCA axes. Variation explained by each axis are given in brackets. Codes for compounds can be found in Table 1

In the trials using only MP, there was well-defined separation of the aphid-exposed and the control plants from both repeats of the experiment (ANOSIM, p < 0.015) (Fig. 1a). The control plants from the first and second repeats were not separated (p = 0.5), whereas there was some indication of separation of the aphid-treated plants from the two trials (p = 0.048). The aphid-treated plants were associated with relatively high concentrations of JA, SA, CAM, TRP, 4MIND and KGR, whereas the uninfested plants had relatively higher levels of the methyl sulphinyl GSs, especially 4MSUL (see Table 1 for full names of abbreviated compounds).

ANOSIM separated the highest aphid density (100 MP) from control (0 aphids), 10 aphids and 20 aphid treatments (p < 0.02), but not 50 aphids (p = 0.443) (Fig. 1b). The 10 aphid treatment was not significantly different from the no-aphid control (p = 0.214). The composition of the leaves in the 50 aphid treatment was quite variable and only moderate evidence was provided (p = 0.07) that this group was different from the control group of plants. In general, the plants subjected to high aphid densities were associated with high levels of CAM, SA and TRP, whereas those plants subjected to low aphid infestation (10 aphids or fewer) were associated with relatively higher levels of 3MIND, 4HIND and 4MSUL.

In the time course experiment, although clear patterns did not emerge, the 80-h aphid feeding duration group was different from all the control groups and from the 6-h and 30-h feeding duration groups (p < 0.05), but not the 55-h feeding group (p = 0.14) (Fig. 1c). At 6 h and 30 h, the aphid treatment did not separate from the same-time control groups (p > 0.25), whereas at 55 h the aphid group did separate from the control group (p < 0.05). The uninfested plants also changed in chemical composition over the trial, with the 6-h and 80-h control groups being designated as significantly different (p = 0.03). The plants subjected to the longer durations of aphid feeding (55 h and 80 h) were associated with elevated CAM, JA and TRP.

In the aphid species comparison, all groups were separated from each other (p < 0.05) except LP and MP (p = 0.10) (Fig. 1d). Infestation of Arabidopsis by LP and MP was associated with increased TRP, CAM and CAMA, whereas those plants challenged by BB had relatively higher levels of KGR and KRGR.

Cluster analysis and relative effect sizes

The results of the hierarchical cluster analyses from the four separate experiments indicated that certain compounds were behaving in a similar fashion when Arabidopsis was exposed to the different aphid challenges (Fig. 2). For example, the methyl sulphinyl GSs and methyl thiamine GSs each tended to form clusters in each trial. TRP, JA, PHE and ABA also tended to be grouped together, as did SA, CAM, and CAMA. The kaempferol-based compounds (KRR, KGR, KRRG) were grouped together in every trial, often along with the malates (SM or FM) (Fig. 2).

Fig. 2

Hierachical cluster analysis of the relative concentrations of compounds in Arabidopsis leaf tissue exposed to different aphid infestation treatments: a control versus infested with Myzus persicae, b infested with different initial densities of M. persicae, c infested for different durations by M. persicae and d uninfested versus infested by either M. persicae, Brevicoryne brassicae or Lipaphis pseudobrassicae. Codes for compounds can be found in Table 1

Examination of the effects of aphid feeding on the chemical profiles of the Arabidopsis leaves, as indicated by the magnitude and direction of Cohen’s d coefficient, illustrated why these clusters of compounds have been formed (Fig. 3). JA, CAM, CAMA and TRP were consistently increased after aphid challenge, regardless of density, feeding duration and species. These four compounds, together with SA, PHE and the GS 4MIND, which tended to show similar although not quite as consistent patterns, formed a group of compounds that were induced in Arabidopsis in response to aphid challenge (Fig. 3).

Fig. 3

Heatmap showing extent of increase (red) or decrease (blue) in relative concentrations of metabolites in Arabidopsis foliage when exposed to aphid challenge compared to uninfested plants. Darkest colour tones indicate Cohen’s d ≥ |3|. Codes for compounds can be found in Table 1. MP—Myzus persicae; BB—Brevicoryne brassicae; LP—Lipaphis pseudobrassicae

With the exception of 4MIND, the patterns for the other aromatic/indolyl GS exhibited inconsistent responses to aphid feeding. Although there were some clear exceptions, overall the methyl sulphyl GSs were generally decreased by the presence of aphids. The methyl thionine GSs were reduced by all three aphids in the multi-aphid trial, but tended to exhibit increases in concentration in response to MP feeding of short duration (≤ 30 h) and at low density (tenaphids per plant; Fig. 3). All four methyl thionine GSs showed similar responses across all four experiments (Fig. 3) which explains their tight grouping by the cluster analysis (Figs. 2, 3).

Aphid density

Concentrations of TRP and PHE in leaf foliage exhibited clear positive relationships with the initial density of MP (Fig. 4a). CAM (and CAMA) was massively induced by aphid challenge, with concentrations in plants subjected to the highest aphid density having levels more than ten times that seen in the controls. The mean concentration of SA exhibited a stepwise response to increasing density, whereas JA, being almost completely absent from the control plants in this trial, was increased by the presence of any number of aphids feeding on the plant, although the highest concentration still occurred at the highest aphid density (Fig. 4a).

Fig. 4

Response of concentrations of a defence-related metabolites and b glucosinolates in Arabidopsis foliage when exposed to different initial denisties of the aphid Myzus persicae (mean ± SE; n = 4). Plants were harvested 80 h after infestation commenced. Codes for compounds can be found in Table 1. *Separated from no-aphid control treatment by Fisher’s LSD (p < 0.05)

A number of GSs exhibited density-dependent responses to increasing aphid density: 3MSUL, 4MSUL, 3MIND and 4HIND exhibited negative relationships with density of MP, and were especially reduced at the highest levels of aphid infestation (Fig. 4b). Conversely, the relative level of 4MIND in the leaf tissue was increased in response to increased MP density (Fig. 4b).

Effects of duration of aphid infestation

Overall, very few of the measured metabolites exhibited clear patterns of induction or suppression over time by the presence of the aphids, with variability in metabolite concentration occurring both between aphid treatments and over time; very few statistically significant differences were identified among the aphid-infested and control plants (Fig. 5). For the aphid-induced metabolites, SA, JA, TRP and CAM concentrations diverged further from the levels in the control plants the longer the aphid feeding period (Fig. 5a). CAM concentrations rapidly increased, and were four times higher in the aphid-infested plants than in the control plants after 6 h. JA levels in the infested plants were around twice that in uninfested plants of the same age for the first two days, and then massively increased after 80 h. This latter result highlights a problem when working with response ratios, as this substantial relative increase was caused more by a lack of JA in the control plants harvested at 80 h than an actual increase in JA concentrations in the aphid-infested plants.

Fig. 5

The effect of feeding by Myzus persicae for different durations on the concentrations of a defence-related metabolites and b glucosinolates in Arabidopsis foliage. The y axis represents the ratio of concentrations in aphid:control plants and is plotted on a log2 scale. The initial density of aphids was 20 per plant. Codes for compounds can be found in Table 1. *Difference between aphid-infested and control plants identified at this time point using Fisher’s LSD (p < 0.05)

The leaf concentrations of GSs (relative to the control values) were variable over time (Figs. 3, 5b). There seemed a spurious spike in relative concentrations in the plants exposed to MP after 30 h for the methyl sulphate GSs, and the methyl thionine GSs flipped from being induced by aphid feeding at 6 h and 30 h, to being decreased at 55 h and 80 h. (Fig. 3). For the GSs that showed relationships with aphid density (Fig. 4b), only 4MIND exhibited a consistent trend over time, and was increased after just 6 h of exposure to the aphids and then remained higher than control levels throughout the 80-h assay.

Induction of metabolites by different aphid species

In this trial, SA and PHE were not significantly affected by aphid feeding, whereas TRP, JA and CAM concentrations were increased by feeding by LP and, even more so, by MP (Fig. 6a). Conversely, 4MSUL was decreased by feeding by MP and LP (Fig. 6b). The indolyl GSs 3MIND and 4MIND were not affected by aphid feeding (at this density), but 4HIND exhibited a considerable increase in concentration when the plants were challenged by BB.

Fig. 6

Relative concentrations of a defence-related metabolites and b glucosinolates in Arabidopsis foliage when exposed to three different aphid species (MP—Myzus persicae, BB—Brevicoryne brassicae, LP—Lipaphis pseudobrassicae) (mean ± SE; n = 4). The initial density of aphids was 20 per plant and plants were harvested after 80-h feeding. Codes for compounds can be found in Table 1. Treatments sharing a letter code were not identified as being significantly different by Fisher’s LSD (p < 0.05)


Aphid induced changes in leaf chemistry

The cluster analyses identified a group of compounds (JA, CAM, TRP, SA, PHE and the GS 4MIND) that tended to be increased in response to aphid feeding. SA induction has been observed in many other plant-aphid interactions (e.g. Mohase and van der Westhuizen 2002; de Ilarduya et al. 2003; Li et al. 2008; Donovan et al. 2013) and was identified as responding positively to aphid density by Stewart et al. (2016) in Medicago truncatula when challenged by A. pisum. The induction of SA by aphids in Arabidopsis foliage by MP and BB has been reported previously (Moran and Thompson 2001; Kuśnierczyk et al. 2008), although in our study only MP significantly induced foliage SA, and most noticeably at high aphid density.

The effects of aphids on foliar JA concentrations can be highly variable and difficult to establish unequivocally (e.g. Stewart et al. 2016). For example, after 72 h feeding on Arabidopsis, de Vos et al. (2005) found no change in JA in plants exposed to MP and Kroes et al. (2015) found no change in expression of genes associated with JA accumulation in plants challenged by BB. However, we observed an aphid-associated increase in leaf JA fairly consistently over all the trials. An antagonism between JA and SA has been previously implied, along with a suggestion that aphids may induce SA in order to inhibit JA-based defence pathways (e.g. Zhu-Salzman et al. 2005; de Vos et al. 2007; Louis and Shah 2013; Zhang et al. 2015). However, in many of our experiments both hormones were clearly increased in the same leaf tissue at the same time (see also Stewart et al. 2016).

Previously, no effect of aphid feeding on ABA concentration was described for MP feeding on tobacco (Donovan et al. 2013) and A. pisum feeding on Medicago truncatula (Stewart et al. 2016). However, Studham and MacIntosh (2013) observed an increase in ABA in soybeans infested with soybean aphid, and recently Hillwig et al. (2016) reported that ABA-regulated genes in Arabidopsis were induced by MP saliva infiltration, and that this induction of ABA may benefit aphids by reducing concentrations of the aphid deterrent GS 4MIND. This inconsistency of results emphasizes that the combination of factors that lead to aphid-induction of ABA still requires clarification. Although we found no statistically significant effects of aphid treatment on ABA when using conventional ANOVA, the heat-map approach based on effects sizes suggested ABA was being modified by aphid feeding, and three of the four cluster analyses positioned ABA within the group of aphid-induced compounds. Thus even within our study the perceived relationship between aphid feeding and ABA was inconsistent and depended on the statistical/analytical approach used.

Mewis et al. (2005, 2006) reported that total GS levels were increased in Arabidopsis foliage after feeding by MP and BB, largely because of significant increases in 3MSUL and 4MSUL. In our study, however, the leaf concentrations of many GS were reduced after aphid feeding, although the induction of 4MIND by MP was seen consistently, similar to the findings reported by Kim and Jander (2007). The induction of 3MSUL and 4MSUL by BB reported by Mewis et al. (2006) was not seen in this study, although the increase in 5MSUL observed by Mewis et al. (2005) did occur, along with an increase in 6MSUL. BB also increased levels of all the indolyl GSs measured, with the exception of 4MIND, the GS induced by both MP and LP. Kuśnierczyk et al. (2008) described a somewhat similar effect of BB on Arabidopsis GS, in that total indolyl GS were increased, including 3MIND, although they also reported that 4MIND and that one aliphatic GS, 7MSUL, were also increased 48 h post infection (hpi). In comparison, Ponzio et al. (2017) found that total leaf GS concentration of black mustard (Brassica nigra) was not affected by BB.

A decrease in 3MIND in plants exposed to MP was also observed by Kim and Jander (2007), who showed that other indolyl GSs might be converted to 4MIND because the latter compound has greater aphid feeding deterrent properties against MP. Our findings support these suggestions, in that the induction of 4MIND by MP was time dependent and most strongly observed at 80 hpi, which coincided with a strong reduction in concentration of two other indolyl GS, 4HIND and 3MIND. This complementary relationship was also seen in the aphid density trial: 4HIND and 3MIND decreasing with increasing density, as 4MIND concentration increased. 4MIND was reported to be associated with callose deposition in Arabidopsis by Clay et al. (2009) which is a well-described plant defence mechanism against aphids. Pfalz et al. (2009) described the gene CYP81F2, encoding a cytochrome P450 monooxygenase, as being responsible for the accumulation of 4MIND and 4HIND and concluded that this gene was associated with Arabidopsis defence against MP.

The induction of camalexin in Arabidopsis by the specialist brassica aphid BB has been reported previously (Kuśnierczyk et al. 2008; Mewis et al. 2012). Mewis et al. (2012) suggested the generalist aphid MP did not affect camalexin concentrations, whereas in our study foliar concentrations of camalexin exhibited substantial increases following feeding by MP; increases that were density dependent and positively related to the duration of aphid feeding. The other aphid species we examined also induced camalexin, although relative concentrations were lowest in the plants challenged by one brassica specialist, BB, and highest in other, LP.

Aphid species, density and duration of feeding

A number of metabolites exhibited positive or negative relationships with the size of the founding population of Myzus persicae. Concentrations of TRP, PHE, CAM, SA, JA and 4MIND were positively associated with aphid density, whereas 3MSUL, 4MSUL, 3MIND and 4HIND were negatively related to aphid density. A number of studies are now highlighting that plant metabolic processes are affected by the number or density of aphids challenging the plant. Foliar concentrations of SA have been shown to exhibit strong positive relationships with aphid density in Medicago truncatula (Stewart et al. 2016) and in tobacco (Donovan et al. 2013). PHE concentration in the foliage of pea plants exposed to the pea aphid (A) pisum exhibited a positive relationship with aphid density (Mai et al. 2014), and the phytoalexin medicarpin also exhibited strong positive relationship with density of the same aphid on M. truncatula (Stewart et al. 2016). In the Myzus persicae-Arabidopsis system used here, accumulation of trehalose and the composition and concentrations of volatiles can both be dependent upon aphid density (Hodge et al. 2013; Truong et al. 2014). In dual-herbivore experiments, the overall plant defence profile induced by a second herbivore can be influenced in a density dependent manner by simultaneous feeding by (B) brassicae (Kroes et al. 2015; Ponzio et al. 2017).

The results of our study illustrate that metabolites can still be modified by the presence of aphids but that concentrations do not have a monotonic relationship with aphid density (see also Mai et al. 2014). The lack of density dependent responses may, in some cases, be a result of differences in the ranges of initial densities used in different studies. In this study on Arabidopsis, we used a range of densities from 10 to 100 aphids, along with a no-aphid control. In other studies of the effects of aphid density on plant responses, by comparison: Donovan et al. (2013) used densities of 5 and 10 aphids on tobacco; Kroes et al. (2015) 5 and 25 aphids on Arabidopsis; Mai et al. (2014) 10, 20 and 30 aphids on peas; Ponzio et al. (2017) 50 and 100 aphids on black mustard; Truong et al. (2014) 30, 70 and 100 aphids on Arabidopsis; Stewart et al. (2016) 10, 25, 50 and 100 aphids on Medicago truncatula. Clearly the size/age of the plant, and the size/age of the aphids used to initiate the challenge, will influence the intensity of challenge the plant experiences and relative damage caused by ingestion of phloem sap and loss of photosynthates. It could be speculated that, as the density of aphids increases, the plant’s responses gradually switch from being orientated towards defence and repulsion of the aphids, to being orientated to maintenance of basic functions and then to actual survival. Analysis of the concentrations of metabolites around aphid feeding sites, although technically challenging, would help to resolve these issues.

Many of the aphid-induced plant responses observed in this study were most apparent after the longest duration of aphid feeding. It is possible that the effects of aphid density and of the duration of a sustained feeding attack are interlinked, and constitute some general measure of the ‘intensity’ or ‘amount’ of herbivore damage inflicted upon the plant (Rosa-Gomes et al. 2008; Studham and MacIntosh 2013; Stewart et al. 2016). Studies assessing plant responses at a single harvest will miss trends or fluctuations that occur over time, especially as some changes may not occur until many days after feeding has been initiated (Kusniercyk et al. 2008). However, if aphids are at high densities the detection of plant responses may be accelerated, and thus more readily observed within a short-term study (Kroes et al. 2017).

Differences in results obtained between studies could clearly be due to differences in the time frames used to detect changes in plant chemistry. As described above, the GS profiles obtained in the current study in Arabidopsis (Col 0) challenged by MP were similar in many regards to those obtained on the same plant–aphid system by Kim and Jander (2007) but generally differed from those reported by Mewis et al. (2005, 2006). The similarities and differences among the three studies may in part be related to the experimental protocols used. Kim and Jander (2007) infested plants with 30 aphids, and harvested at 72 hpi, similar to the 20 aphids and 80 h feeding duration in our study. This contrasts with the 10 aphids and 7 days duration used in the experiments of Mewis et al. (2005, 2006). Mewis et al. (2005, 2006) also initiated their plants with adult or late instar nymphs, and by the time of leaf harvest 7 days later, the final populations of MP were on average approximately five times greater than this (on Col 0). Thus, the results of Mewis et al. (2005, 2006) actually represent the plant responses to considerably higher densities of aphids, and after more than double the feeding duration, as that used in the current study.

In the light of the results obtained when examining the effects of aphid density, we conceded that in the aphid species comparison aphids may not have been at high enough densities for some plant responses to be induced. Nevertheless, feeding by the different aphid species did produce some distinct changes for a number of individual metabolites, and the PCA analysis suggested that overall foliage chemical profiles were dissimilar. There was no clear separation between the generalist MP and the brassica specialist LP. In fact, chemical profiles induced by MP and LP were more similar to each other than those induced by LP and BB. Other work has also found that generalist and specialist aphids may induce comparable changes in plant metabolism, for example Kuzniercyk et al. (2008) reported that changes in glucosinolate levels induced by B. brassicae were similar to those upon M. persicae infestation.

It should be noted that, in our study, all of the interactions were compatible, in the sense that all of the aphid species were able to feed and grow on the Col-0 ecotype of Arabidopsis. Thus, the different responses in plant chemistry induced by the feeding aphids are either not involved with defence against aphids, or the responses are defence related but the aphids are sufficiently virulent to overcome them. Ali and Agrawal (2012) implied that many studies comparing plant responses to generalist and specialist insect herbivores used too few cases—often only one—of each feeding type. In many plant species, including Arabidopsis, the defences induced by aphid feeding are also dependent upon the aphid clone challenging the plant, and the resistance of the plant genotypes being studied (Kuśnierczyk et al. 2008; Mewis et al. 2012; Stewart et al. 2016). To gain full understanding of this aspect of plant–aphid interactions, a substantial nested study design may need to be employed, whereby a number of species of generalists and specialist aphids, each represented by different clones, are tested simultaneously using both susceptible and resistant host plants.


Our findings reinforce that the phytohormones SA and JA, the phytoalexin camalexin, and a number of GSs, are involved in the biochemical responses of Arabidopsis to feeding by aphids, and that variation in the aphid induction of these can occur due to aphid species, the density of aphids and the duration of aphid feeding. While some of our findings are consistent with previous reports, we also identified a number of discrepancies with other studies, which we believe is due, at least in part, to differences in experimental protocols used (Kim and Jander 2007; Kuzniercyk et al. 2008; Wentzell and Kliebenstein 2008). Alternative methods of data analysis, such as the use of effect sizes and cluster analysis, may help identify consistent patterns among treatments, especially when replicate numbers are small and the power of conventional null hypothesis significance tests is low. To gauge the repeatability of plant responses to aphid feeding, we recommend that researchers consider the inclusion of multiple aphid species and/or clones in their studies, and use pilot studies to optimize methods in terms of aphid density and feeding duration.

Change history

  • 26 August 2019

    The authors would like to include the following changes in the published article.


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This work was funded by a research Grant from the Biotechnology and Biological Sciences Research Council, UK. Our thanks go to Martin Selby for technical support, and Colin Turnbull, John Rossiter and Murray Grant for advice throughout this study. We thank three anonymous referees for their helpful comments on an earlier draft of this manuscript.

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Hodge, S., Bennett, M., Mansfield, J.W. et al. Aphid-induction of defence-related metabolites in Arabidopsis thaliana is dependent upon density, aphid species and duration of infestation. Arthropod-Plant Interactions 13, 387–399 (2019). https://doi.org/10.1007/s11829-018-9667-0

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  • Brevicoryne brassicae
  • Camalexin
  • Glucosinolates
  • Jasmonic acid
  • Lipaphis pseudobrassicae
  • Myzus persicae
  • Salicylic acid