Aphid (Myzus persicae ) feeding on the parasitic plant dodder (Cuscuta australis ) activates defense responses in both the parasite and soybean host

Introduction Like most plant parasites, aphids require intimate associations with their host plants to gain access to nutrients. Aphids predominantly feed from the plant phloem sieve elements, and use their stylets to navigate between the cells of different layers of leaf tissue during which plant defenses may be triggered. Indeed, aphid feeding induces responses such as clogging of phloem sieve elements and callose formation, which are suppressed by the aphid in successful interactions with plant hosts [1]. In addition, some aphid species can alter host plant phenotypes, by for example inducing the formation of galls or causing leaf curling [2] indicating that there is an active interplay between host and aphid at the molecular level. During probing and feeding, aphids secrete two types of saliva: gelling saliva, which is thought to protect stylets during penetration, and watery saliva, which is secreted into various plant host cell types and the phloem [3]. The secretion of aphid saliva directly into the host-stylet interface [4], suggests that molecules present in the saliva may perturb plant cellular processes while aphids progress through different feeding stages. Interestingly, the knock-down of the C002 salivary gene in Acyrthosiphon pisum (pea aphid) negatively impacts survival rates of this aphid on plant hosts [5], [6]. Furthermore, proteomics studies based on artificial aphid diets showed the presence of secreted proteins, including C002, in aphid saliva indicating that these proteins are delivered inside the host plant during feeding [7], [8]. However, whether and how these aphid salivary proteins function in the plant host remains elusive. Suppression of host defenses and altering host plant phenotypes is common in plant-pathogen interactions and involves secretion of molecules (effectors) that modulate host cell processes [9], [10]. Therefore it is likely that aphids, similar to plant pathogens, deliver effectors inside their hosts to manipulate host cell process enabling successful infestation of plants [9]. Effector-mediated suppression of plant defenses, such as Pathogen-Associated Molecular Pattern (PAMP)-triggered immunity (PTI), generally involves the targeting of a plant virulence target, or operative target [11]. However, plant pathogen effectors that are deployed to suppress host defenses are recognized by plant disease resistance (R) proteins in particular host genotypes, resulting in effector-triggered immunity (ETI) [12]. Interestingly, the R proteins that recognize plant pathogens and those that confer resistance to aphids, such as Mi-1.2 and Vat, share a similar structure, and contain a nucleotide binding site (NBS) domain and leucine rich repeat (LRR) regions [13]–[15]. The Mi-1.2 resistance gene confers resistance in tomato to certain clones of Macrosiphum euphorbiae (potato aphid), two whitefly biotypes, a psyllid, and three nematode species [16]–[19], indicating that there is significant overlap in plant pathogen and aphid recognition in plants. In addition, aphid resistance conferred by several resistance genes was shown to be race-specific [16], [20]. This suggests that depending on their genotype, certain aphid clones may be able to avoid and/or suppress plant defenses and fits with the gene-for-gene model in plant-pathogen interactions [21]. Therefore, it is likely that not only plant pathogens, but also aphids, secrete effectors that in addition to targeting host cell processes may trigger ETI depending on the host genotype. Plant pathogen effectors generally share the common feature of modulating host cell processes [22]. Various assays have been developed to identify the functions of effectors from bacterial and eukaryotic filamentous plant pathogens [22]–[24]. One important and common function of plant pathogen effectors is the suppression of PTI. This activity is especially common among type III secretion system (T3SS) effectors. For example, the large majority of Pseudomonas syringae DC3000 effectors can suppress PTI responses, including the oxidative burst [25]. However, effectors from eukaryotic filamentous plant pathogens can also suppress PTI, as demonstrated for the AVR3a effector from Phytophthora infestans, which suppresses cell death induced by the PAMP-like elicitor INF1 [26], [27]. Another activity of plant pathogen effectors is the induction of phenotypes in plants. For example, several effectors, including CRN2 and INF1, from the oomycete plant pathogen P. infestans induce cell death upon overexpression in planta [28], [29], whereas other effectors, like AvrB from P. syringae DC3000 induce chlorosis [30]. Also, overexpression of effector proteins from plant pathogenic nematodes in host plants can affect plant phenotypes, as shown for the Heterodera glycines CLE protein Hg-SYV46 that alters host cell differentiation [31]. As effectors exhibit functions important for pathogenicity, their deletion can have detrimental effects on pathogen virulence. However, due to redundancy, the knock-down or deletion of single effectors does not always impact virulence. On the other hand, overexpression of plant pathogen effectors can enhance pathogen virulence, as shown for active AvrPtoB, which enhances virulence to P. syringae DC3000 in Arabidopsis [32], and for the H. schachtii effector 10A06 that, in addition to altering host plant morphology, increases nematode susceptibility in Arabidopsis [33]. We exploited publicly available aphid salivary gland sequences to develop a functional genomics approach for the identification of candidate aphid effector proteins from the aphid species Myzus persicae (green peach aphid) based on common features of plant pathogen effectors. Data mining of salivary gland expressed sequences tags (ESTs) identified 46 M. persicae predicted secreted proteins. Functional analyses showed that one of these proteins, Mp10, induced chlorosis and weak cell death in Nicotiana benthamiana, and suppressed the oxidative burst induced by the bacterial PAMP flg22. In addition, we developed a medium-throughput assay, based on transient overexpression in N. benthamiana, that allows screening for effects of aphid candidate effectors on aphid performance. Using this screen, we identified two candidate effectors, Mp10 and Mp42, that reduced aphid performance and one effector candidate, MpC002, that enhanced aphid performance. In summary, we found aphid secreted salivary proteins that share features with plant pathogen effectors and therefore may function as aphid effectors by perturbing host cellular processes. Results Description of functional genomics screen We developed a functional genomics approach to identify candidate effectors from M. persicae using 3233 publicly available aphid salivary gland ESTs [34]. We hypothesized that aphid effectors are most likely secreted proteins that are delivered into the saliva through the classical eukaryotic endoplasmic reticulum (ER)-Golgi pathway of the salivary glands. A feature of proteins secreted through this pathway is the presence of an N-terminal signal peptide. Therefore, we used the SignalP v3.0 program [35] to predict the presence of signal peptides in the amino acid sequences encoded by the open reading frames (ORFs) found in salivary gland ESTs. Out of 5919 amino acid sequences corresponding to predicted ORFs, we identified 134 nonredundant sequences with signal peptide (Figure 1A). Out of these 134 proteins, 19 were predicted to contain a transmembrane domain in addition to the signal peptide, and are therefore likely to remain in the salivary gland membrane upon secretion. Hence, 115 predicted secreted proteins remained. In order to investigate the M. persicae candidate effector protein in functional assays, we started with the cloning of 46 candidates that corresponded to full-length sequences within the set of 115 candidates. Effectors are subject to diversifying selection because of the co-evolutionary arms race between host and pathogen proteins [36], [37]. Therefore, we used the presence of amino acid polymorphisms among alignments of deduced protein sequences of M. persicae and A. pisum ESTs as an additional criterion. Three candidates did not fulfill this criterion and were removed from our candidate set bringing the total to 43 candidates. 10.1371/journal.pgen.1001216.g001 Figure 1 Overview of functional genomics pipeline to identify candidate effectors from M. persicae. (A) Bioinformatics pipeline for data mining of M. persicae salivary gland expressed sequence tags (ESTs). (B) Cloning and functional analyses of candidates to identify effector activities. i) PCR amplification was performed on M. persicae cDNA. ii) Amplicons were cloned in the pCB302-3 vector under control of a 35S promoter and constructs were transformed into Agrobacterium tumefaciens. iii) Multiple clones were sequenced to identify polymorphic candidates. Clones were stored and cultured for subsequent functional assays. iv) Candidate effectors were overexpressed in Nicotiana benthamiana by agroinfiltration to determine whether they induce a phenotype in planta, such as cell death, suppress basal plant defences, PAMP-triggered immunity (PTI), and affect aphid performance. We applied a similar data mining approach as described above to 4517 publicly available salivary gland ESTs from A. pisum, thereby identifying 24 candidates (Table S1). In the A. pisum salivary gland ESTs we predicted only 1751 ORFs, explaining the relatively low number of A. pisum candidates. A total of three candidates were found in both M. persicae and A. pisum datasets (combinations Mp1/Ap1, Mp5/Ap7 and Mp16/Ap4). The remaining 21 non-overlapping A. pisum candidates were subjected to BLAST searches (E value 0.9 and a predicted cleavage site within the amino acid region 1–30. As some predicted secreted proteins were represented multiple times within the M. persicae salivary gland EST dataset, we used BLASTP searches to remove redundant sequences. Alignments were inspected manually and sequences that showed >95% identity throughout most of the alignment with an E value<10−10 were classified as being redundant. To remove sequences that in addition the signal peptide also contained a transmembrane domain we used TMHMM v.2.0. The remaining sequences were searched using TBLASTN (E value<10−5) against all M. persicae and A. pisum ESTs in our datasets as well as the A. pisum genome sequence to assess whether they encoded full-length proteins. Criteria for selecting full-length sequences were: 1) the presence of a conserved start and stop site in ESTs within the alignments; 2) the absence of a methionine within the alignments upstream of the methionine predicted to be the start of the ORF; 3) similarity to a predicted full-length A. pisum protein, when available. The remaining predicted secreted protein sequences were then assessed for the presence of polymorphisms within the alignments described above. Sequences not showing any sequence variation in alignments with M. persicae sequences and that contained up to one amino acid difference in alignments of the mature protein regions with A. pisum sequences were removed from the candidate list. The 4517 salivary gland ESTs from A. pisum were analyzed with the same procedures except that no analyses was performed for the presence of polymorphisms. The amino acid sequences of the predicted secreted proteins (Table S1) were searched using BLASTP (E value of <10−5) against the amino acid sequences of the M. persicae candidates to identify overlap in the datasets. A. pisum candidates without a hit were then searched using TBLASTN against all available M. persicae ESTs (E value of <10−5) to identify M. persicae predicted secreted proteins with sequence similarity. The M. persicae candidates identified using our pipeline and subjected to cloning were designated MpC002, Mp1-12, Mp14-17, Mp19-24, Mp28-33, Mp35-37, Mp39-47, Mp49-51, Mp53-54, wherein Mp stands for M. persicae (Table S2). Aphids The M. persicae colony of lineage RRes (genotype O) was maintained in cages on N. tabacum plants. Cages were located in a contained growth room at 18°C under 16 hours of light. Microbial strains and growth conditions A. tumefaciens strain GV3101 was used in molecular cloning and agroinfiltration experiments and were routinely cultured at 28°C in Luria-Bertani (LB) media using appropriate antibiotics [68]. All bacterial DNA transformations were conducted by electroporation using standard protocols [68]. Cloning of Mp candidates Primers were designed for amplification of sequences corresponding to the ORFs encoding the mature proteins (after the signal peptide encoding sequences) (Table S3). To confirm the 3′ end of the ORFs, we designed, where possible, the 3′-primer in the 3′UTR sequence. Sequences were amplified from M. persicae cDNA using Phusion polymerase (Finnzymes) and ligated into SpeI/BamHI, SpeI/BglII or BglII/BamHI digested pCB302-3 vector [69] to generate 35S-constructs. To assess whether sequences were polymorphic within the M. persicae clonal lineage used in our studies, we performed sequence analyses of 4 clones per construct. To generate constructs for PVX-based expression, we amplified sequences encoding mature ORFs and ligated these into ClaI/NotI digested pGR106 vector. The PTV vectors used in this study have been described previously [40]. Gene expression analyses by semi-quantitative RT-PCR Aphids were dissected in PBS and tissues stored in RNA later. We collected 25 salivary glands, 10 guts, 5 heads and 5 whole aphids. RNA extractions were performed with the NucleoSpin RNA XS kit (Macherey-Nagel, Germany). cDNA was synthesized from 80 ng total RNA per sample using expand reverse transcriptase (Roche Diagnostics Ltd). RT-PCR was performed with gene specific primers for each effector candidate indicated in Table S3. MpActin primers were used as a control for equal cDNA template amounts. For RT-PCR on plant tissues, 50 mg leaf tissue was ground in liquid nitrogen and RNA was extracted with the RNeasy Plant minikit (Qiagen). cDNA was synthesized from 500ng DNase treated RNA and subjected to PCR reactions with primer pairs Mp10-pvx-F/R and Mp42-pvx-F/R (Table S3) for amplification of Mp10 and Mp42 expressed in PVX, respectively. For amplification of the PVX coat protein we used primer pair PVX-CP-F/R and for amplification of plant tubulin we used the primer pair Tub-F/R (Table S3). Primers used for RT-PCR on RNA extracted from SGT- and HSP90-silenced plants were described elsewhere [26]. PVX agroinfection and agroinfiltration assays Recombinant A. tumefaciens strains were grown as described elsewhere [70] except that the culturing steps were performed in LB media supplemented with 50 µg/mL of kanamycin. Agroinfiltration experiments were performed on 4–6 week-old N. benthamiana plants. Plants were grown and maintained throughout the experiments in a growth chamber with an ambient temperature of 22°–25°C and high light intensity. For transient overexpression of candidate effectors by agroinfiltration, leaves of N. benthamiana were infiltrated with A. tumefaciens strain GV3101 carrying the respective constructs at a final OD600 of 0.3 in induction buffer (10mM MES, 10mM MgCl2, 150 µM acetosyringone, pH = 5.6). For agroinfection assays, cotelydons of N. benthamiana, N. tabacum (cv Petite Gerard) or S. lycopersicum (MoneyMaker) were wound-inoculated with candidate effector clones using P200 pipette tips. Each strain was assayed on 2 replicated plants. As a control, plants were wound-inoculated with A. tumefaciens strains carrying pGR106-Δgfp [26]. Systemic PVX symptoms were scored 14 days post inoculation. TRV-induced gene silencing We performed gene silencing as described elsewhere [40]. A. tumefaciens suspensions expressing the binary TRV-RNA 1 construct, pBINTRA6, and the TRV-RNA2 vector, PTV00 or PTV-SGT1 were mixed in 1∶1 ratio (RNA1- RNA2) in induction buffer (final OD600 is 0.6). Leaves were challenged with Agrobacterium strains carrying 35S-Mp10 and 35S-INF1 or the 35S vector. Aphid fecundity assays in 24-well plates We developed a medium-throughput 24-well assay to test whether overexpression in planta of effector candidates affects aphid nymph production rates. For this purpose, we overexpressed the candidates (35S-constructs) by agroinfiltration in N. benthamiana at a final OD600 of 0.3. One day after infiltration, leaf discs were collected using a cork borer (No. 7) from the infiltration sites and placed upside-down on top of 1ml water agar in 24-well plates. A total of 6 infiltration sites, from 6 different leaves, were used per construct and a total of 4 different constructs per 24-well plate. In initial screens, we infiltrated multiple sets of 4 candidate effectors at the same time, with one set including the vector and GFP controls (two candidate effectors plus the two controls). The 4 candidates within a set were infiltrated side-by-side on the same 6 leaves. Leaf discs from each set of candidates were placed in one 24-well plate (6 discs times 4 candidates). For the confirmation assays, we performed infiltrations of each candidate effector with the vector control side-by-side on the same 6 leaves, and leaf discs were placed in one 24-wells plate. On each leaf disc, we placed 4 M. persicae first-instar nymphs. The wells in the plate were individually sealed off using a cap of a 5ml BD Falcon round bottomed test tub with the top of the cap removed and covered with mesh. After 6 days, the nymphs were moved to a new 24-wells plate with fresh leaf discs infiltrated with the candidate effector constructs. Another 6 days later, the now adult aphids were again moved to a new 24-well plate with freshly infiltrated leaf discs. The numbers of adults (initially first-instar nymphs) were counted 6, 12, 14 and 17 days after setting up the first 24-wells plate and the number of newly produced nymphs were counted on day 12, 14 and 17. The newly produced nymphs were removed from the wells during counting. Wells wherein all 4 aphids that were initially placed on the discs died were taken out of the analyses. To calculate the production of nymphs per adult aphid, we calculated the average number of nymphs produced per adult by combining the average production rates throughout the experiment. These average production rates were obtained by dividing the number of nymphs on day 12 by the number of adults on day 6 (calculated per well), dividing the number of nymphs on day 14 by the number of adults on day 12, and dividing the number of nymphs on day 17 by the number of adults on day 14. To obtain the total average production rate, we calculated the sum of the average production rates for days 12, 14 and 17. Measurements of reactive oxygen species N. benthamiana leaf discs transiently overexpressing the effector candidates were subjected to a luminescence-based assay [41]. Leaf discs were floated overnight in 200ul water in a 96-well plate. The production of ROS was measured after replacing the water with a solution of luminol (20uM) and horseradish peroxidase (1ug) supplemented with either flg22 peptide (100nM) or chitin (100 µg/ml). Luminescence was measured using a Varioskan Flash plate reader. A total of 8 discs per construct, obtained from 4 different infiltration sites, were used per replicate. Assays with flg22 to screen the 48 candidates for suppression activity were repeated two times. The assays with chitin and flg22 were repeated three times. Statistical analyses All statistical analyses were conducted using Genstat 11. ROS assay was analysed using a two-sample t-test. Leaf discs fecundity assays were analysed using one-way ANOVA with “construct” as the treatment and “repeat” as the block. Data was checked for approximate normal distribution by visualising the residuals. Supporting Information Figure S1 Gene expression analyses of candidate effectors in various aphid tissues. RT-PCR was performed on cDNA prepared from whole aphids fed on N. benthamiana, dissected heads, guts, salivary glands and on H2O (control). Candidates were amplified using gene specific primers. Actin primers were used as a control for equal template amounts. (5.23 MB TIF) Click here for additional data file. Figure S2 Mp10 induces weak local cell death in N. benthamiana. (A–D) Symptoms of N. benthamiana agroinfiltration sites expressing the 35S empty vector (control) or Mp10 under bright and ultraviolet (UV) light. Symptoms induced by the control (A) and Mp10 (B) were analyzed under a dissecting microscope. Accumulation of autofluorescent phenolic compounds associated with local cell death induced Mp10 (D), but not the control (C) were visualized under ultraviolet (UV) light (480/40 nm excitation filter; 510 barrier nm). Photographs were taken 5 days post infiltration. The black arrow heads indicate foci associated with autofluorescent phenolic compounds as a result of local cell death. (E) Percentages of infiltration sites showing induction of local macroscopic cell death upon expression of the Mp10 in N. benthamiana plants. Leaves were agroinfiltrated with Agrobacterium strains carrying 35S-Mp10 or PVX-Mp10 in the presence or absence of strains carrying p19 at an OD600 of 0.3 or 0.6. NS indicates no symptoms, CHL indicates chlorosis and CHL+CD indicates cell death. Symptoms were scored 4 days post infiltration. The average number of infiltration sites was based on 3 replicated experiments (n = 8 sites per experiment). Error bars indicate the standard error. (2.59 MB TIF) Click here for additional data file. Figure S3 Symptoms of PVX-Mp10 infected Solanum lycopersicum (tomato) and N. tabacum plants. (A) Symptoms on a tomato plant infected with PVX-Δgfp (control) (left panel) and PVX-Mp10 (right panel). (B) Symptoms on a N. tabacum plant infected with PVX-Δgfp (control) (left panel) and PVX-Mp10 (right panel). Pictures were taken 14 days after inoculation. (8.70 MB TIF) Click here for additional data file. Figure S4 PVX-based expression of Mp42 in various plant species. Leaf tissues from N. benthamiana (Nb), N. tabacum (Nt), and Solanum lycopersicon (Sl) were collected for RNA extractions 14 days post wound-inoculation (dpwi). For semi-quantitative RT-PCR primers were used to amplify sequences corresponding to the PVX virus coat protein (CP) and Mp42. The plant tubulin gene (Tub) was used as a control for equal RNA amounts. (0.79 MB TIF) Click here for additional data file. Figure S5 Expression of GFP in N. benthamiana leaf discs placed on water agar in a 24-well plate. Leaves were collected 24 after agroinfiltration with Agrobacterium strains expressing GFP and placed on top of water agar in a 24 wells plate. Leaf discs were collected every 24 hours from 1 to 7 days post infiltration (DPI) and ground in SDS-PAGE sample loading buffer to analyze the accumulation of GFP by western blotting with a GFP antibody. As a negative control (C) a 1-day old non-infiltrated N. benthamiana leaf disc was used. Ponceau S staining (PS) showed equal loading. (0.26 MB TIF) Click here for additional data file. Figure S6 Overexpression of M. persicae candidate effector in N. benthamiana alters aphid reproductive performance (fecundity). Using the leaf disc-based assay, a set of 48 candidate effectors was expressed in N. benthamiana by agroinfiltration to screen for effects on aphid fecundity. Red dotted lines mark sets of candidates that were screened in parallel experiments. EV indicates the vector control and GFP indicates the GFP control. Nymph production was counted over a 17-day period. The average number of nymphs produced per adult was based on 3 replicated experiments. Error bars indicate the standard error. Asterisks indicate Mp candidates that were further tested in confirmation assays. (0.05 MB PDF) Click here for additional data file. Figure S7 Symptoms of N. benthamiana infiltration sites expressing Mp10 during the leaf disc 24-well plate assay. Photo was taken 5 days after infiltration. (0.84 MB TIF) Click here for additional data file. Table S1 List of candidate effectors of the pea aphid (Acyrthosiphon pisum). (0.04 MB XLS) Click here for additional data file. Table S2 List of candidate effectors of the green peach aphid (M. persicae). (0.06 MB XLS) Click here for additional data file. Table S3 Primer table. (0.11 MB DOC) Click here for additional data file.

Volatile communication between plants causing enhanced defence has been controversial. Early studies were not replicated, and influential reviews questioned the validity of the phenomenon. We collected 48 well-replicated studies and found overall support for the hypothesis that resistance increased for individuals with damaged neighbours. Laboratory or greenhouse studies and those conducted on agricultural crops showed stronger induced resistance than field studies on undomesticated species, presumably because other variation had been reduced. A cumulative analysis revealed that early, non-replicated studies were more variable and showed less evidence for communication. Effects of habitat and plant growth form were undetectable. In most cases, the mechanisms of resistance and alternative hypotheses were not considered. There was no indication that some response variables were more likely to produce large effects. These results indicate that plants of diverse taxonomic affinities and ecological conditions become more resistant to herbivores when exposed to volatiles from damaged neighbours. © 2013 John Wiley & Sons Ltd/CNRS.

The roots of most land plants are colonised by mycorrhizal fungi that provide mineral nutrients in exchange for carbon. Here, we show that mycorrhizal mycelia can also act as a conduit for signalling between plants, acting as an early warning system for herbivore attack. Insect herbivory causes systemic changes in the production of plant volatiles, particularly methyl salicylate, making bean plants, Vicia faba, repellent to aphids but attractive to aphid enemies such as parasitoids. We demonstrate that these effects can also occur in aphid-free plants but only when they are connected to aphid-infested plants via a common mycorrhizal mycelial network. This underground messaging system allows neighbouring plants to invoke herbivore defences before attack. Our findings demonstrate that common mycorrhizal mycelial networks can determine the outcome of multitrophic interactions by communicating information on herbivore attack between plants, thereby influencing the behaviour of both herbivores and their natural enemies. © 2013 John Wiley & Sons Ltd/CNRS.