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Consequences of russet mite-induced tomato defenses for community interactions

Glas, J.J.

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Download date:24 Sep 2021 Consequences of russet mite-induced tomato defenses for community interactions mite-induced tomato defenses for community interactions Consequences of russet Uitnodiging Consequences of russet mite-induced Tot het bijwonen van de openbare tomato defenses for community verdediging van het proefschrift interactions Consequences of russet mite-induced tomato defenses for community interactions

door Joris Glas

Woensdag 02 juli 2014 om 12:00 uur in de Agnietenkapel Oudezijds Voorburgwal 231 te Amsterdam

Receptie na afloop van de verdediging

Joris Glas [email protected] 06-30238878

Paranimfen: Joris Glas 2014

Arie Glas [email protected] 06-13560469

Johan Bondt Joris Glas [email protected] 06-52463089 JorisGlas-voorwerk_Gerben-Voorwerk.qxd 26/05/2014 00:12 Page 1

Consequences of russet mite-induced tomato defenses for community interactions JorisGlas-voorwerk_Gerben-Voorwerk.qxd 26/05/2014 00:12 Page 2

J.J. Glas, 2014. Consequences of russet mite-induced tomato defenses for community interactions

PhD thesis, University of Amsterdam, The Netherlands

Publication of this thesis was financially supported by Koppert Biological Systems (www.koppert.nl)

ISBN: 978 94 91407 99 4

Cover design: Jan van Arkel (IBED) Lay-out: Jan Bruin (www.bred.nl) JorisGlas-voorwerk_Gerben-Voorwerk.qxd 26/05/2014 00:12 Page 3

Consequences of russet mite-induced tomato defenses for community interactions

ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. D.C. van den Boom ten overstaan van een door het college voor promoties ingestelde commissie, in het openbaar te verdedigen in de Agnietenkapel

op woensdag 2 juli 2014, te 12:00 uur

door

Joris Joachim Glas

geboren te Amsterdam JorisGlas-voorwerk_Gerben-Voorwerk.qxd 26/05/2014 00:12 Page 4

Promotiecommissie

Promotor: Prof. dr. M.W. Sabelis

Co-promotor: Dr. M. Kant

Overige leden: Dr. A.T. Groot Prof. dr. M.A. Haring Dr. A.R.M. Janssen Prof. dr. J.J.A. van Loon Prof. dr. S.B.J. Menken Prof. dr. C.M.J. Pieterse Dr. R.C. Schuurink

Faculteit der Natuurwetenschappen, Wiskunde en Informatica JorisGlas-voorwerk_Gerben-Voorwerk.qxd 26/05/2014 00:12 Page 5

Contents

6 Author addresses 7 1 General introduction

31 2 Tomato russet mites induce salicylic acid defenses but suppress jasmonic acid defenses in tomato 67 3 Russet mite-induced plant defenses increase tomato resistance to a phytopathogen but facilitate a competing herbivore

91 4 Analysis of transcriptome-wide changes in tomato during defense suppression by spider mites and russet mites reveals distinct differences in cell wall modification and hormone metabolism

141 5 Herbivory-associated degradation of tomato trichomes and its impact on biological control of Aculops lycopersici

157 6 General discussion

169 Summary 171 Samenvatting 173 Biography 174 Dankwoord / Acknowledgements JorisGlas-voorwerk_Gerben-Voorwerk.qxd 26/05/2014 00:12 Page 6

Author addresses

Institute for Biodiversity and Ecosystem Dynamics, Section Population Biology, Science Park 904, 1098 XH Amsterdam, The Netherlands Alba, Juan M. van Arkel, Jan Glas, Joris J. Kant, Merijn R. Sabelis, Maurice W. Stoops, Marije

Swammerdam Institute for Life Sciences, Department of Plant Physiology, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands Schuurink, Robert C. Villarroel, Carlos A.

Institute of Ecological Science, Department of Animal Ecology, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands Ooms, Astra

CRA-ABP Agricultural Research Council, Centre for Agrobiology and Pedobiology, via Lanciola 12/a, 50125 Florence, Italy Simoni, Sauro

Koppert Biological Systems, Veilingweg 14, Postbus 155, 2650 AD Berkel en Rodenrijs, The Netherlands Bolckmans, Karel J.F. Hoogerbrugge, Hans van Houten, Yvonne M. Rothe, Julietta JorisGlas-chap1_Gerben-chap2.qxd 26/05/2014 00:16 Page 7 1 General introduction

n nature and agriculture plants are attacked by a suite of different plant parasites, Iincluding insects, mites and plant pathogens. For insects, it is estimated that of the approximately 1 million described species ca. 45% are phytophagous (Schoonhoven et al., 2005). Therefore, it is not surprising that plant-herbivore interactions are among the most ubiquitous of all ecological interactions (Jander & Howe, 2008). Yet, despite this herbivore pressure, plants under natural conditions often still appear relatively ‘green’ and one rarely encounters plants that are completely defoliated (Hairston et al., 1960). This paradox may have an easy resolution as plants, rather than passively under- going consumption, have evolved traits that allow them to respond to herbivory, for instance by inducing defense responses that reduce growth and/or survival of plant enemies (Howe & Jander, 2008). However, these defenses may in turn select for counter-adaptations at the herbivore side, for instance the ability to suppress defenses, and this can escalate into a so-called evolutionary arms race involving cycles of adaptation and counter-adaptation between plants and herbivores (Berenbaum, 1998). Getting a better understanding of how plant defenses function as well as the strategies that plant attackers have evolved to cope with these defenses is important as it can possibly help to improve crop resistance in agriculture. In this thesis, I have specifically addressed the question whether herbivorous pest species that cause distinct plant defense responses can influence each other’s performance via their shared host.

Plant defenses: constitutive and induced, direct and indirect Plant defenses are usually divided in constitutive defenses, i.e., those that are always present on a plant, and induced defenses, i.e., those that are activated only in response to a herbivore or pathogen attack. Examples of constitutive defenses include physical barriers, like cell walls lignified to prevent pathogens from entering the plants (Bhuiyan et al., 2009), waxy cuticle layers reducing suitable feeding sites per leaf surface (Eigenbrode & Shelton, 1990) or trichomes, i.e., specialized hairs found on aerial parts of a plant, which function as mechanical barriers (Pott et al., 2012) but also play important roles in induced defenses (Glas et al., 2012). Trichomes, which can be classified as either non-glandular or glandular, have been studied in

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great detail, especially those of Solanum species because of their strong relationship with resistance against herbivores (Alba et al., 2009). They play an important role in this thesis as well (see CHAPTER 5). Glandular trichomes are usually multicellular, consisting of differentiated basal, stalk and apical cells and they share the capacity to produce, store and secrete large amounts of different classes of secondary metabolites (Schilmiller et al., 2008). On tomato, in total eight different types of trichomes are distinguished of which four (i.e., type I, IV, VI and VII) are glandular, whereas the other four (i.e., type II, III, V and VIII) are non-glandular (FIGURE 1.1). These trichome types differ in their morphology and the glandular types are known to differ as well in number of stalk and secretory cells and in their chemical contents (for a detailed description of the different tomato trichome types see Glas et al., 2012). Next to trichomes, also the herbivore-induced defense response of tomato plays a major role in this thesis (CHAPTERS 2 & 4). Induced defenses are commonly subdivided into direct and indirect defenses. Direct defenses include the production of toxins, anti- feedants and inhibitors of digestion that negatively affect the survival of herbivores and/or growth and development of individuals or populations (Howe & Jander, 2008). In contrast, indirect defenses refer to plant traits that enhance attraction of natural enemies of the herbivore, like predators and parasitoids, which can promote plant fitness (Van Loon et al., 2000; Schuman et al., 2012). In that sense, indirect defenses are on average more lethal to herbivores than direct defenses (see also section Induction and suppression of defenses of this introduction). Attraction of natural enemies is predominantly mediated via volatiles that are emitted by the plant in response to herbivore feeding and used by natural enemies to locate herbivores as prey (Kessler & Baldwin, 2001; Kant et al., 2004). Other ways of plants to attract or arrest natural enemies is to provide them with food, for instance extrafloral nectar (Pemberton & Lee, 1996) and food bodies (Fischer et al., 2002), or with shelter places, such as leaf domatia, i.e., small hair-tufts or pockets that provide refuges for predatory arthropods (Walter, 1996).

How do plants recognize herbivores? Plants are unable to run away from danger. This implies that they are strongly dependent on their constitutive and inducible defense system to protect themselves from being eaten by pathogens and herbivores. Notably, even before the herbivore starts consuming the plant, defensive responses can already be mounted. Evidence comes from the observation that the release of volatiles from herbivore-attacked plants ‘primes’ neighboring uninfested plants to elicit stronger and faster defense responses when these are attacked by herbivores (e.g., Baldwin et al., 2006; Heil & Bueno, 2007; Shiojiri et al., 2012). Moreover, it was found that the mere walking of small insects or the deposition of eggs by insects can trigger defense responses (Peiffer et al., 2009; Kim et al., 2012).

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FIGURE 1.1 Glandular trichomes in the section Lycopersicon. Wild tomato accessions have high densities of glandular trichomes that confer resistance to several pests. Panel A shows the leaflet surface of S. habrochaites acc. LA1777 with high densities of glandular trichome types IV, VI (B), and I (C). Surface of S. pennellii acc. LA716 is also covered by type IV trichomes (D, E) producing and secreting acyl sugars. This accession also has type VI trichomes but in low density (F). Panel G shows the surface of the cultivated tomato S. lycopersicum cv. Moneymaker. Cultivated tomato has low density of type VI trichomes (H) and type I trichomes. Sometimes type IV-like trichomes (I) are observed on stems, veins, and on the leaflet edges. White bars represent 500 µm in panel A, C, D, and G. In panels B, E, F, H, and I, bars represent 50 µm. Photos by Jan van Arkel, University of Amsterdam. Figure adapted from Glas et al., 2012.

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Plant responses differ according to the type of herbivore that is feeding from the plant. This specificity in plant response can be achieved because plants respond to specific patterns of feeding damage (Erb et al., 2012). Second, plants are able to tailor defenses because they recognize elicitors, i.e., compounds that stimulate plant defense and which are present in the saliva or other secretions (Schwartzberg & Tumlinson, 2014) of herbivores and come into contact with the plant during feeding (Schmelz et al., 2009). Elicitors have been intensely investigated and at least five different groups have been described (Alba et al., 2012). The first group comprises enzymes, such as β-glucosidase, originally found in the oral secretions of Pieris brassicae caterpillars. Application of β-glucosidase to leaves resulted in the emission of a blend of herbivore-induced plant volatiles that was similar to the blend emitted by plants that were mechanically damaged and then treated with caterpillar regurgitant, and in both cases this resulted in the attraction of parasitic wasps (Mattiaci et al., 1995). A second group constitutes the so-called ‘Fatty Acid Conjugates’ (FACs), which are formed in the insect gut by a conjugation reaction between plant-derived fatty acids and insect-derived amino acids (Bonaventure et al., 2011) and come into contact with the plant during regurgitation. The first FAC elicitor identified, N-(17-hydroxylinolenoyl)-L-glutamine (also named volicitin), was isolated from oral secretions of beet armyworm caterpillars. Application of volicitin to corn (Zea mays) seedlings resulted in emission of a similar blend of volatiles as when attacked by caterpillars (Alborn et al., 1997). Then, a third group is the ‘caeliferins’, which are sulfated fatty-acids, originally identified in the regurgitant of grasshoppers (Schistocerca americana), which induced the release of volatiles when applied to damaged leaves of corn seedlings (Alborn et al., 2007). A fourth group of elicitors are derived from plant enzymes, like the ‘inceptins’, which are fragments from chloroplas- tic ATP synthase found in the oral secretions of Spodoptera frugiperda larvae. Inceptins induced the accumulation of phytohormones, expression of defense genes and volatile emission in cowpea plants (Schmelz et al., 2006). Finally, elicitors can also be derived from cell wall fragments, such as oligogalacturonides which induce expression of defense genes in tomato plants (Doares et al., 1995) and it is thought that wound-inducible polygalacturonases play a role in the degradation of leaf pectin to generate oligogalacturonic acid fragments (Bergey et al., 1999). Not much is known about how plants perceive elicitors, but in maize (Zea mays) a plasma membrane protein has been identified that binds to the elicitor volicitin (Truitt et al., 2004).

Regulation of induced defenses Induced defenses are mainly regulated by a set of three phytohormones: jasmonic acid (JA), salicylic acid (SA) and ethylene (ET). Herbivorous insects and necrotrophic pathogens typically induce JA-dependent defenses (Howe & Jander, 2008), whereas

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defenses against biotrophic pathogens (Glazebrook, 2005) and phloem-feeders (Kaloshian & Walling, 2005) are mediated by SA. ET is generally considered to function together with JA in the induction of defense responses (Lorenzo et al., 2003), whereas acting antagonistically with SA (Diezel et al., 2009). However, exceptions to these patterns are known as well (reviewed by Adie et al., 2007). Mutants defective in JA-biosynthesis or signaling are generally much more susceptible to insect attack (e.g., Howe et al., 1996), thereby demonstrating the importance of the JA-pathway for herbivore resistance. Similarly, plants unable to produce or accumulate SA are generally more susceptible to pathogen infections (e.g., Delaney et al., 1994).

Jasmonic acid The JA-signaling pathway has been extensively reviewed (for a recent review see, e.g., Wasternack & Hause, 2013) and will be introduced only briefly here. In CHAPTERS 2 and 4 the JA-pathway will be discussed in more detail. Biosynthesis of JA in toma- to takes place in the chloroplast and peroxisomes of the phloem companion cells (Howe, 2004). Briefly, the first step comprises the formation of linolenic acid which is released from galactolipids of chloroplast membranes via the action of (a) phospholipase(s). Subsequently, linolenic acid is oxygenized by lipoxygenases (LOX), resulting in the formation of hydroperoxylinolenic acid, which is then converted by allene oxide synthase (AOS) and allene oxide cyclase (AOC) to produce oxophytodienoic acid (OPDA). In a next step, OPDA is exported from the chloroplast and imported into the peroxisomes where it is converted by OPDA reductase3 (OPR3) into cyclopentane-1-octanoic acid, followed by three cycles of β-oxidation to yield the final product JA. In the cytosol JA is conjugated to isoleucine, by the enzyme jasmonate resistant 1 (JAR1) (Suza et al., 2010) resulting in the formation of JA-Ile, which is the bioactive form of JA (Fonseca et al., 2009). Perception of JA-Ile occurs in the nucleus by the SCFCOI1 (Skip/Cullin/F-box) receptor complex, which ubiquitinates transcriptional suppressors [i.e., the Jasmonate ZIM domain (JAZ) proteins] after which these are degraded by the proteasome and downstream defense responses are activated, including, for instance, the synthesis of proteinase inhibitors (PIs) (Gimenez-Ibanez & Solano, 2013; FIGURE 1.2).

Salicylic acid Similar to the situation for JA, there is wealth of literature describing the role of SA in plant disease resistance (reviewed by Vlot et al., 2009) and only the most important points will be introduced here. SA in plants regulates defenses against pathogens, including bacteria, fungi and viruses. These defenses can be triggered locally but also systemically leading to enhanced resistance in uninfected parts of the plant, a phenomenon which is called Systemic Acquired Resistance (SAR). SAR includes the up- regulation of defense genes, including the Pathogenesis-Related proteins (PR-pro-

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teins), which play a role in resistance against microbes (Van Loon et al., 2006). In addition, the SA and JA signaling pathways operate together with reactive oxygen species (ROS) in the activation of the plant hypersensitive response (programmed cell death) (Bostock, 2005). SA is an aromatic compound derived from chorismate in the phenylpropanoid pathway and its biosynthesis has been proposed to occur via two distinct routes. The first route occurs via isochorismate synthase (ICS), which is responsible for the production of the SA-precursor isochorismic acid. In the second route, chorismic acid is converted via phenylalanine into cinnamic acid and then into SA via either benzoic acid or coumaric acid (Boatwright et al., 2013). Yet, it is good to note that the biosynthesis of SA has not been completely resolved in plants and some steps are still hypothetical in tomato (indicated by dashed lines in FIGURE 1.2). Accumulation of SA leads to the translocation of the regulatory protein NONEXPRESSOR OF PR GENES1 (NPR1) to the nucleus (Koornneef & Pieterse, 2008). Subsequently, in the nucleus, NPR1 interacts with the TGA transcription factors, resulting in the induction of PR- genes. Via which exact protein SA is perceived is still a matter of an ongoing debate: Wu et al. (2012) reported that SA binds to NPR1 but in another study it was found that SA, instead of NPR1, binds to NPR3 and NPR4 in Arabidopsis (Fu et al., 2012). SA is not only important for pathogen-induced responses but also for indirect plant defense, as it can be converted by the JA-induced enzyme SAMT into methyl salicylate (MeSA), a volatile of which the emission increases in response in response to spider mite feeding. Together with other herbivore-induced plant volatiles, such as terpenes, MeSA plays a role in the attraction of predatory mites to spider mite-infested tomato plants (Ament et al., 2010).

Other phytohormones Even though JA and SA are known as the primary regulators of plant defense, several others play regulatory roles as well, including not only ET (Adie et al., 2007) but also abscisic acid (ABA) (Dinh et al., 2013), auxin (Kazan & Manners, 2009), cytokinins (Choi et al., 2011), gibberellins (Yang et al., 2012) and brassinosteroids (Nakashita et al., 2003). This means that the defense signaling pathways that are primarily regulated by JA and SA can be modulated by additional signals as well. This implies that defense signaling pathways do not stand on their own but are connected to each other, forming complex networks, and with ample cross-communication occurring between them, leading to responses that can be either antagonistic or synergistic (Pieterse et al., 2009). Probably the best documented example of crosstalk is that between the SA and JA pathway, which have been frequently observed to antagonize each other (e.g., Niki et al., 1998). To date, several regulators mediating the antagonistic effect of SA on JA

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FIGURE 1.2 Schematic overview of the JA- and SA-signaling pathway as summarized in the text. Solid arrows indicate confirmed steps in tomato; dashed lines indicate multiple hypothetical or indirect steps. Red inhibition lines indicate the antagonistic effects between the SA and the JA-pathway. Abbrevations: Ch = chorismate; Ich = isochorismate; Phe = Phenylalanine; TF = Transcription Factor; other abbrevations are explained in the text.

have been identified in Arabidopsis, like NPR1, which was shown to be required for the SA-mediated suppression of JA-dependent responses (Spoel et al., 2003). Yet, NPR1 has diverse functions and its role may be different in different plant species as indicated by the finding that in tobacco (Nicotiana attenuata) NPR1 was found to down-regulate SA production, thereby preventing JA/SA-crosstalk and protecting the plant from becoming very susceptible to herbivores (Rayapuram & Baldwin, 2007). A second mediator of JA/SA-crosstalk is OCTADECANOID-RESPONSIVEARABIDOP- SIS59 (ORA59), a transcription factor whose accumulation was shown to be negative-

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ly regulated by SA in Arabidopsis (Van der Does et al., 2013). Additional regulators have been identified as well in Arabidopsis including WRKYs (e.g., WRKY70, WRKY50/51) as well as TGA transcription factors (e.g., Li et al., 2004; Zander et al., 2010; Pieterse et al., 2012). In contrast, regulators that mediate the antagonistic effect of JA on SA have not been identified yet (Pieterse et al., 2012). At present, the biological function (or the necessity) of JA/SA-crosstalk is not well understood. On the one hand, it has been suggested that crosstalk allows plants to ‘choose’ the best defensive strategy depending on the type of attacker encountered (Kunkel & Brooks, 2002) and to prioritize energy flows but, on the other hand, it clearly creates problems as well as it may, for example, also be abused by pathogens and herbivores (Zarate et al., 2007; El Oirdi et al., 2011). Hence, why plants benefit from the JA/SA-antagonism (assuming natural selection would otherwise have selected against this trait – if physiologically possible) remains a question to be addressed in the future (Thaler et al., 2012).

Induction and suppression of defenses Herbivores deal with induced plant defenses in distinct manners. First, they may avoid induced plants or plant parts, as observed, for instance, for Manduca sexta larvae and leafhoppers, which preferentially fed on plants that were impaired in JA- defenses (Paschold et al., 2007; Kallenbach et al., 2012). Second, herbivores may become tolerant or resistant to induced plant defenses, as reported for instance for spider mites (Kant et al., 2008) and Manduca sexta caterpillars (Wink & Theile, 2002). Third, herbivores may suppress induced defenses (reviewed by Alba et al., 2011). Since defense suppression is a major theme in this thesis, this phenomenon will be discussed in more detail here. Defense suppression is well known from plant pathogens, and many examples are known from plant pathogenic bacteria (e.g., Zhao et al., 2003), fungi (e.g., Weiberg et al., 2013), viruses (e.g., Hanley-Bowdoin et al., 2013) as well as nematodes (e.g., Haegeman et al., 2012). However, evidence is accumulating that also insects and mites can manipulate plant defenses. Herbivorous arthropods whose feeding activities are associated with concomitant suppression of plant defenses include phloem-feeders, i.e., whiteflies (Zarate et al., 2007; Zhang et al., 2009, 2013), aphids (Soler et al., 2012; Schwartzberg & Tumlinson, 2014) and mealybugs (Zhang et al., 2011), cell-content feeders, i.e., spider mites (Kant et al., 2008; Sarmento et al., 2011), as well as chewing insects including lepidopteran caterpillars (Weech et al., 2008; Consales et al., 2012; Savchenko et al., 2013) and beetles (Chung et al., 2013). Finally, it has been reported that also caterpillar eggs may suppress plant defenses (Bruessow et al., 2010). Defense suppression may occur in different manners. Some herbivores have found ways to make good use of the antagonistic effects between the JA- and SA-

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pathway. Probably the best known example is that of whiteflies which suppress the JA-dependent responses, to which they are susceptible, by inducing SA-defenses (Zarate et al., 2007; Zhang et al., 2013). However, in whitefly-infested bean plants that had been co-infested with spider mites not only JA but also SA accumulation was reduced, suggesting that in this system suppression of JA-defenses is not due to ele- vated SA levels (Zhang et al., 2009). Other herbivores, like spider mites, were found to suppress both the JA- and SA-defense signaling pathway (Sarmento et al., 2011). Suppression may also occur independent from the JA- and SA-pathway as observed for Spodoptera littoralis caterpillars (Consales et al., 2012). Much remains to be learned about the causal mechanisms underlying defense suppression by herbivores. However, similar to plant pathogens and nematodes, herbivores have been found to produce and secrete effector molecules that suppress induced plant defenses (Walling, 2009). Notably, effectors have identified in evolutionary distant species, including pathogens, spider mites, insects and nematodes. As an example, spider mites belong to the chelicerates and insects to the unirami- ans and is estimated that these two groups have diverged already early in the evolution of arthropods, probably over 400 million years ago from a common aquatic ancestor (Weygoldt, 1998). Hence, this suggests that effectors may have evolved independently in different lineages of plant parasites. The first reported example was glucose oxidase (GOX), a salivary enzyme that, depending on the host plant, can counteract JA-dependent accumulation of nicotine induced by herbivore feeding (e.g., Eichenseer et al., 1999, 2010; Musser et al., 2002). However, this response may well benefit the host plant rather than the herbivore and hence may not be adaptive from the herbivore’s point of view (Voelckel et al., 2001). Following the discovery of GOX, more examples of herbivore effectors have been found, which are present in the saliva and eggs of herbivores. Effectors functionally characterized to date have been isolated from lepidopteran caterpillars (Schmelz et al., 2012) as well as from aphids (e.g., Bos et al., 2010; Atamian et al., 2013) and nematodes (Mitchum et al., 2013). In spider mites, effectors have been identified as well which are currently being characterized (C. Villarroel, University of Amsterdam, unpublished data). With the increasing availability of genome and transcriptome sequencing data I expect that more examples of herbivore effectors will become available in the near future. Finally, an alternative strategy of herbivores to circumvent plant defenses is to vector pathogens, like viruses or bacteria, which also may cause suppression of induced defenses. For example, the western flower thrips (Frankliniella occidentalis) was found to transmit the tomato spotted wilt virus, which exploits the antagonism between the JA and SA pathway and thereby benefits its vector (Abe et al., 2012). Viruses transmitted by whiteflies have been reported to suppress JA-defenses as

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well, implying that is still unclear whether suppression of defenses is caused by the whiteflies themselves (Zarate et al., 2007; Zhang et al., 2009) or by the viruses they transmit (Zhang et al., 2012). In addition, oral secretions of the Colorado potato beetle (Leptinotarsa decemlineata) were reported to contain bacteria that induce SA accumulation thereby suppressing JA-responses to which the beetles are susceptible (Chung et al., 2013). Hence, it seems that most herbivores that suppress defenses via the JA/SA- antagonism seem to do this with the help of microbes. Finally, an effector protein called SAP11 which suppresses JA-defenses in Arabidopsis was identified from a phytoplasma, and this enhanced the reproduction of its insect vector, the leafhopper Macrosteles quadrilineatus (Sugio et al., 2011).

Experimental system For this thesis research, I have focused on the interaction between the cultivated tomato (Solanum lycopersicum) and one of its main herbivorous pests, the tomato russet mite (Aculops lycopersici). Experiments I did early during my PhD project showed that these mites suppress tomato defenses, which was the major reason to start this project. This suppression and its consequences for the russet mite’s natural community are the main topics of this thesis. The cultivated tomato belongs to the family of the Solanaceae, which have their origin in South-America. For my experiments I used the tomato S. lycopersicum cultivar Castlemart as well as Moneymaker. Castlemart is the genetic background of two plants altered in the JA-defense pathway, i.e., the mutant defenseless-1 (def-1), which is deficient in the induced expression of JA-dependent defense genes (Howe et al., 1996), and 35S::prosys+, in which the prosystemin gene is overexpressed resulting in a constitutively activated JA-dependent defense response (Chen et al., 2006). I also used transgenic tomato plants that express a gene of the bacterium Pseudomonas putida, called salicylate hydroxylase (nahG), which converts SA into catechol. Hence, nahG plants are unable to display SA-mediated defense and exhibit increased susceptibility to viral and bacterial pathogens (Brading et al., 2000). nahG plants are in the genetic background of the S. lycopersicum cultivar Moneymaker. In several key-experiments in this thesis, I have used three other important pests of tomato: (1) the two-spotted spider mite (Tetranychus urticae), (2) its relative the red tomato spider mite (Tetranychus evansi) and (3) the plant pathogenic bacterium Pseudomonas syringae pv. tomato DC3000. Hence, these species will be briefly introduced as well here. The reason to include these species is that they have been well characterized in terms of the defenses they elicit, as well as with respect to their sensitivity to these defenses, and, hence, they were included as a benchmark (or reference) in my experiments. In addition, T. urticae and P. syringae were used to investigate the ecological consequences of russet mite-induced defenses.

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Tomato russet mites Tomato russet mites belong to the family of Eriophyidae (superfamily Eriophyoidea). FIGURE 1.3 shows a picture of a russet mite residing together with an adult female of T. urticae on a tomato leaflet. It is thought that the natural host of the tomato russet mite was a wild solanaceous plant somewhere in South-America and that its association with the cultivated tomato is only recent (Oldfield, 1996). When tomato was domesticated is unknown but the oldest records date from 500 BC from southern Mexico (Smith, 1994). Approximately 3000 species of eriophyoids have been described, but it is estimated that this number is less than 10% of the actual number of species existing in this family (Lindquist et al., 1996). Eriophyoid mites are the smallest arthropods that feed on plants, and they cannot be seen without magnification. Their worm-like bodies are between 140-300 µm long (Sabelis & Bruin, 1996). Eriophyoids are yellow to white in color and do not seem to accumulate chlorophyll from plants, like spider mites. They disperse primarily by means of the wind but some species also by attaching themselves to larger animals, like aphids, for phoretic transport (Sabelis & Bruin, 1996). Adult eriophyoid mites have only two pairs of legs, unlike tetranychid mites, which possess four pairs of legs. Eriophyoid mites have a female based sex ratio and an

FIGURE 1.3 An adult female of the two-spotted spider mite (Tetranychus urticae) (left) residing together with the tomato russet mite (Aculops lycopersici) (right, inset; the blue scale bar indicates 30 μm) on a tomato (Solanum lycopersicum) leaflet. Picture by J. van Arkel (University of Amsterdam).

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arrhenotokous parthenogenic mode of reproduction, meaning that males are haploid and females are diploid. Hence, unfertilized eggs develop into males, whereas fertil- ized eggs can develop into either males or females. Sperm transfer in eriophyoid mites occurs via spermatophores: these are little sacks on a stick which contain sperm cells and which are placed by the males on the plant surface after which they are picked up by the females. The life-cycle of most eriophyoids is rather simple: it consists of the egg, two nymphal stages and the adult. Eriophyoid mites are considered as the second most important family of mite plant pests after the Tetranychidae (Lindquist et al., 1996). Plants of economic importance that are damaged include citrus, apple, pear, grapes, tomato, wheat, sugarcane, tea, coffee, olive, coconut as well as ornamental plants. Eriophyoid mites are often host specific and damage occurs on all the above-ground plant parts, including the reproductive tissues and fruits. For this reason, eriophyoids are sometimes used as biological agents for control of weeds or invasive plants (Sabelis & Bruin, 1996). Many eriophyoids cause the formation of galls in which they live and which can have various shapes (for a description see Westphal & Manson, 1996). Other plant malformations induced by eriophyoids include abnormal development of hairs (‘erinea’), blisters, rolling of the leaves, swelling of buds or excessive branching (‘witches’ brooms’) (Westphal & Manson, 1996). Eriophyoid mites are cell-content feeders: they possess a stylet (typically about 7-30 µm long), with which they pierce plant cells to ingest the watery cytoplasma (Royalty & Perring, 1996). Due to their small size, the mites are usually not able to penetrate the cells below the epidermis. Unlike many tetranychid mite species, which usually kill their host plant, eriophyoids generally leave their host intact (Sabelis & Bruin, 1996), even though they do cause damage by destroying the epidermal cell layer, thereby reducing gas exchange and photosynthesis (Royalty & Perring, 1988). Remarkably, eriophyoid mites are the only Acari known to vector plant pathogens, mostly viruses (Oldfield & Proeseler, 1996). A well-known example is the wheat curl mite (Aceria tulipae), which transmits the wheat streak mosaic virus. However, trans- mission of plant diseases has never been reported for the tomato russet mite. Tomato russet mites occur worldwide and they feed on solanaceous plants only (TABLE 1.1, FIGURE 1.4). Feeding occurs on the foliage, the stem and also the inflorescence and young fruits. Early indications of russet mite damage include silvering of the underside of the leaves. In later stages of the infestation, the leaves turn bronze colored (‘russet’) after which they dry out and drop from the plant. Furthermore, the stem loses its trichomes, becomes rusty brown and sometimes develops small cracks. Just like other eriophyoids, russet mites usually don’t kill their host, with the exception of the cultivated tomato on which they cause severe damage, including wilting and death of the plant (Perring, 1996) (FIGURE 1.5).

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Death of the plant is thought to occur because of the destruction of the epidermis which leads to the collapse of the underlying mesophyll cells and desiccation of the plant (Royalty & Perring, 1988). Cells adjacent to the destroyed cells typically have thickened, lignified, cell walls (Royalty & Perring, 1988), which might be an effective plant response to prevent desiccation. However, it is clear that in several cultivated

TABLE 1.1 Reported hosts of the tomato russet mite (Aculops lycopersici) [source: http://www.cabi.org; accessed October 2013] Latin name Common name Browallia americana - Capsicum annuum Bell pepper Convolvulus sp. Morning glory Convolvulus arvensis Bindweed Datura innoxia Downy thornapple Datura stramonium Jimsonweed Ipomoea batatas Sweet potato Lycopersicon peruvanium - Lycopersicon pimpinellifolium Currant tomato Nicotiana tabacum Tobacco Petunia hybrid - Physalis minima Sunberry Physalis peruviana Cape gooseberry Solanum lycopersicum Tomato Solanum melongena Aubergine Solanum muricatum Melon pear Solanum nigrum Black nightshade Solanum pseudocapsicum Jerusalem-cherry Solanum tuberosum Potato

FIGURE 1.4 Distribution map of the tomato russet mite (Aculops lycopersici). Black dots = Present, no further details; blue dot = Widespread; red dots = Localised; yellow dot = Occasional or few reports [source: http:// www.cabi.org; accessed February 2014].

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novel host plants this defense mechanism does not prevent the plant from dying (FIGURE 1.5; Sabelis & Bruin, 1996). Serious reductions in yield in cultivated tomatoes have been reported due to russet mite infestations with losses of up to 50% in South Africa (Perring, 1996). In contrast to most vagrant eriophyoids, which feed only on the abaxial side of the leaves, russet mites feed on all green surfaces as well as the fruits, suggesting that they are not harmed by direct sunlight (Bailey & Keifer, 1943). Under optimal conditions of 27ºC and 30% RH, russet mites can develop from egg to adult in just 6 or 7 days. Each female produces around 30-50 eggs during her lifetime, which is between 17 and 30 days, depending on temperature (Kawai & Haque, 2004). Upon death of the host plant or at the end of the tomato growing season, mites disperse by wind to nearby alternative host plants where they overwinter. Several natural enemies have been reported to feed and reproduce on russet mites in the laboratory (see, e.g., Park et al., 2010) but on whole plants biological control is often unsuccessful (Trottin-Caudal et al., 2003; Fischer et al., 2005; Van Houten et al., 2013).

FIGURE 1.5 Russet mites (Aculops lycopersici) cause death of tomato (Solanum lycopersicum) plants. Habitus of tomato plants at different time-points after infestations. Plants were 21 days old when infested with russet mites (ca. 1500 mixed stages) at the basis of the main stem and photos were taken on day 0, 4, 7, 11, 14 and 18 after infestation. Pictures by J. van Arkel (University of Amsterdam).

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Spider mites Spider mites are small herbivorous arthropods (the adult females are ca. 0.5 mm long) belonging to the family of the Tetranychidae, which consists of about 1200 species in total. The two-spotted spider mite T. urticae is a polyphagous pest species, with an extremely broad host range consisting of 1100 different plant species (Dermauw et al., 2012). Tetranychus urticae is a worldwide pest of greenhouse and field crops, including tomatoes, potatoes, beans, maize, cucumbers, pep- pers, strawberries, apples, grapes and citrus as well as ornamental plants such as roses and gerbera (Helle & Sabelis, 1985). From the same genus is the red tomato spider mite T. evansi which is a specialist on solanaceous plants. Tetranychus evansi originates in Brazil but has been introduced in Africa somewhere in the 1970s and since about 20 years the species has made its entry into southern Europe as well (Boubou et al., 2012; Navajas et al., 2013). In Spain, T. evansi is replacing native T. urticae populations on several host plant species (Ferragut et al., 2013). Like russet mites, spider mites are cell-content feeders. The adult females possess ca. 150 µm long stylets which they use to lacerate-and-flush feed from the spongy parenchyma and palisade parenchyma cells (Park & Lee, 2002). Symptoms of spider mite feeding are visible as small chlorotic lesions on the leaf surface. Depending on the temperature, adult females produce on average 5-12 eggs per day on tomato, which develop in reproducing adults themselves within a period of 2 weeks (Sarmento et al., 2011; Alba et al., submitted). Similar to eriophyoid mites, spider mites possess an arrhenotokous parthenogenic mode of reproduction but males transfer sperm directly to the female instead of using spermatophores and under favourable conditions mite populations increase exponentially to very high densities overexploiting the host. Spider mites produce silken web, which at high mite densities covers the leaf surface and protects them from predation (Lemos et al., 2010). Spider mites are difficult to control chemically because they quickly develop resistance to acaricides (Van Leeuwen et al., 2012). Biological control is applied successfully in most crops for T. urticae using the predatory mite Phytoseiulus persimilis, whereas Phytoseiulus longipes has been identified as an effective predator of T. evansi (Ferrero et al., 2011). Note, however, that in general biological control using predatory mites on tomato remains troublesome because of the trichomes which hinder not only the spider mites, but also the predators (Van Haren et al., 1987; Van Houten et al., 2013).

Pseudomonas syringae The hemibiotrophic pathogen P. syringae pv. tomato DC3000 is a bacterial plant pathogen that is widely used as a model organism to understand pathogenesis in

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plants (reviewed by Xin & He, 2013). Pseudomonas syringae causes bacterial speck disease on tomato as well as on Arabidopsis (Xin & He, 2013). Symptoms of P. syringae infection are visible as small, dark lesions on leaves which sometimes can be surrounded by chlorotic halos (Hirano & Upper, 2000). Bacteria enter the plant through stomata or wounds and multiplication occurs in the apoplast of the leaf. All aerial parts of the plant, such as leaves and fruits, can be infected (Xin & He, 2013). Notably, DC3000 is known to produce the toxin coronatine, which a mimic of the phytohormone JA-isoleucine (JA-Ile). By producing coronatine, P. syringae induces JA-dependent defenses thereby repressing SA-dependent defenses to which the bacterium is sensitive (Glazebrook, 2005).

General outline of this thesis Russet mites have an extremely destructive effect on their tomato host, as evidenced by rapid degradation of the trichomes, strong stress responses and mortality of the plant (FIGURE 1.5). Why russet mites, unlike spider mites, cause these severe disease- like symptoms and what the consequences are for the mites and its community is not known. A great deal of the experiments described in this thesis were performed with the aim to shed light on this question. First, in CHAPTER 2, tomato defense responses induced by russet mites are described and compared with those induced by the spider mite T. urticae, as they have been well characterized for the latter species. Second, in CHAPTER 3, the results of performance experiments are presented that were aimed at revealing the effectiveness of tomato’s inducible defense system against russet mites. These experiments were done using mutants that are impaired in the JA- and SA-signaling pathway. In addition, the consequences of russet mite-induced responses for the performance of the spider mite T. urticae, and for the bacterial phytopathogen, P. syringae, are described here, as well as the reciprocal effects of spider mites and bacteria on russet mite growth. Subsequently, in CHAPTER 4 transcriptome-wide responses induced by russet mites are compared with those induced by T. urticae and T. evansi, which have been identified as, respectively, ‘inducers’ and ‘suppressors’ of plant defenses. Then, in CHAPTER 5, a description is given of the degradation of glandular trichomes that is associated with russet mite herbivory as well as the consequences this has for biological control of the russet mite. Finally, the switch is made from the ‘ask-the-plant’ to the ‘ask-the-mite’ approach and a brief overview is presented of some results that have been obtained from sequencing the russet mite’s genome and transcriptome. From the sequencing data, a list has been compiled of putative secreted proteins, of which some could function as elicitors and/or effectors of plant defense responses. These results are discussed in the general discussion (CHAPTER 6) in the

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context of the other findings described in this thesis. In this chapter, I also discuss the implications of my findings as well as some possible directions for future research.

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Lemos, F., Sarmento, R.A., Pallini, A., Dias, C.R., Sabelis, M.W. & Janssen, A. (2010) Spider mite web mediates anti-predator behaviour. Exp. Appl. Acarol. 52, 1-10. Li, J., Brader, G. & Palva, E.T. (2004) The WRKY70 transcription factor: a node of convergence for jasmonate-mediated and salicylate-mediated signals in plant defense. Plant Cell 16, 319-331. Lindquist, E.E. (1996) External anatomy and systematics. In: Lindquist, E.E., Sabelis, M.W. & Bruin, J. (eds.) (1996) Eriophyoid mites – Their biology, natural enemies and control. World Crop Pests Vol. 6. Elsevier, Amsterdam, The Netherlands, pp. 3-31. Lindquist, E.E., Sabelis, M.W. & Bruin, J. (1996) Preface. In: Lindquist, E.E., Sabelis, M.W. & Bruin, J. (eds.) (1996) Eriophyoid mites – Their biology, natural enemies and control. World Crop Pests Vol. 6. Elsevier, Amsterdam, The Netherlands, pp. v-vii. Lorenzo, O., Piqueras, R., Sánchez-Serrano, J.J. & Solano, R. (2003) ETHYLENE RESPONSE FACTOR1 inte- grates signals from ethylene and jasmonate pathways in plant defense. Plant Cell 15, 165-178. Manson, D.C.M. & Oldfield, G.N. (1996) Life forms, deuterogyny, diapause and seasonal development. In: Lindquist, E.E., Sabelis, M.W. & Bruin, J. (eds.) Eriophyoid mites – Their biology, natural enemies and control. World Crop Pests Vol. 6. Elsevier, Amsterdam, The Netherlands, pp. 173-182. Mattiacci, L., Dicke, M. & Posthumus, M.A. (1995) β-glucosidase: an elicitor of herbivore-induced plant odor that attracts host-searching parasitic wasps. Proc. Natl. Acad. Sci. USA 92, 2036-2040. Martin, J.W. & Davis, G.E. (2001) An updated classification of the recent Crustacea. Natural History Museum of Los Angeles County. 132 pp. Mitchum, M.G., Hussey, R.S., Baum, T.J., Wang, X., Elling, A.A. & Wubben, M. & Davis, E.L. (2013) Nematode effector proteins: an emerging paradigm of parasitism. New Phytol. 199, 879-894. Musser, R.O., Hum-Musser, S.M., Eichenseer, H., Peiffer, M., Ervin, G., Murphy, J.B. & Felton, G.W. (2002) Herbivory: caterpillar saliva beats plant defences – A new weapon emerges in the evolutionary arms race between plants and herbivores. Nature 416, 599-600. Nakashita, H., Yasuda, M., Nitta, T., Asami, T., Fujioka, S., Arai, Y., Sekimata, K., Takatsuto, S., Yamaguchi, I. & Yoshida, S. (2003) Brassinosteroid functions in a broad range of disease resistance in tobacco and rice. Plant J. 33, 887-898. Navajas, M., De Moraes, G.J., Auger, P. & Migeon, A. (2013) Review of the invasion of Tetranychus evansi: biology, colonization pathways, potential expansion and prospects for biological control. Exp. Appl. Acarol. 59, 43-65. Niki, T., Mitsuhara, I., Seo, S. Ohtsubo, N. & Ohashi, Y. (1998) Antagonistic effect of salicylic acid and jasmonic acid on the expression of pathogenesis-related (PR) protein genes in wounded mature tobacco leaves. Plant Cell Physiol. 39, 500-507. Oldfield, G.N. (1996) Diversity and host plant specificity. In: Lindquist E.E., Sabelis M.W., Bruin J. (eds) Eriophyoid mites – Their biology, natural enemies and control. World Crop Pests Vol. 6. Elsevier, Amsterdam, The Netherlands, pp. 199–216. Oldfield, G.N. & Proeseler, G. (1996) Eriophyoid mites as vectors of plant pathogens. In: Lindquist E.E., Sabelis M.W., Bruin J. (eds) Eriophyoid mites – Their biology, natural enemies and control. World Crop Pests Vol. 6. Elsevier, Amsterdam, The Netherlands, pp. 259–275. Park, Y.L. & Lee, J.H. (2002) Leaf cell and tissue damage of cucumber caused by two spotted spider mite (Acari: Tetranychidae). J. Econ. Entomol. 95, 952-957. Park, H.-H., Shipp, L. & Buitenhuis, R. (2010) Predation, development, and oviposition by the predatory mite Amblyseius swirskii (Acari: Phytoseiidae) on tomato russet mite (Acari: Eriophyidae). J. Econ. Entomol. 103, 563–569. Paschold, A., Halitschke, R. & Baldwin, I.T. (2007) Co(i)-ordinating defenses: NaCOI1 mediates herbivore- induced resistance in Nicotiana attenuata and reveals the role of herbivore movement in avoiding defenses. Plant J. 51, 79-91. Peiffer, M., Tooker, J.F., Luthe, D.S. & Felton, G.W. (2009) Plants on early alert: glandular trichomes as sensors for insect herbivores. New Phytol. 184, 644-656. Pemberton, R.W. & Lee, J.-H. (1996) The influence of extrafloral nectaries on parasitism of an insect herbivore. Am. J. Bot. 83, 1187-1194.

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J.J. Glas, J.M. Alba, A. Ooms, R.C. Schuurink, M.W. Sabelis & M.R. Kant

When attacked by herbivores, plants defend themselves by synthesizing toxins and defensive proteins. However, some herbivores have adapted to suppress induced defenses in plants. Little is known on the mechanism underlying defense suppression, and about its effects on defense responses induced by other attackers on the same plant. Here, we report on an eriophyoid mite, the tomato russet mite Aculops lycopersici, which induces salicylic acid (SA) defenses but suppresses jasmonic acid (JA) defenses in tomato (Solanum lycopersicum). Phytohormone measurements revealed that russet mites induce the accumulation of SA as well as JA in leaflets. However, several of the key JA-responsive defense genes were not or only marginally upregulated by russet mites, despite the upstream phytohormone accumulation. In contrast, the expression of the same JA-responsive defense-genes was strongly upregulated by spider mites (Tetranychus urticae), a natural food competitor of russet mites, whereas SA and defenses downstream of SA were induced to levels similar to those induced by russet mites. Strikingly, plants infested with the two mite species together displayed strongly reduced JA- responses, yet a doubled SA-response. To test if suppression of JA-defenses could be attributed to negative cross-talk via SA-signaling, we assessed induced defenses in SA-deficient nahG plants as well. The spider mite-induced JA- response in the presence of russet mites was no longer significant on nahG, but russet mites alone still did not induce JA-responses on nahG plants. This shows that russet mites suppress JA-defenses independent from SA. Moreover, once sharing a leaflet with spider mites, the russet mite-induced SA-response adds on to the spider mite-induced SA-response thereby antagonizing the spider mite- induced JA-response as a secondary effect. Taken together, we conclude that suppression of JA-defenses and simultaneous induction of SA-defenses may evoke secondary cross-talk when competing herbivores induce both responses simultaneously.

n nature, plants are exposed to multiple biotic agents, such as insect herbivores, Imites and/or microbial pathogens. To protect themselves against these, they possess a wide variety of defensive chemicals, many of which are rapidly produced after an attacker has been detected and correlate with increased plant resistance (Howe & Jander, 2008). The activation of these inducible defenses is regulated by a set of phytohormones that mediate between herbivore signal (elicitor) recognition and

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defense activation. Three phytohormones play a main role in regulating defense responses: jasmonic acid (JA), salicylic acid (SA) and ethylene (ET) (Pieterse et al., 2009). Typically, feeding by herbivores and infection by necrotrophic pathogens induces the accumulation of JA, as well as that of its active derivative jasmonic acid- isoleucine (JA-Ile), whereas defenses against biotrophic pathogens (Glazebrook, 2005) and phloem-feeders (Kaloshian & Walling, 2005) are mediated by SA. ET is known to modulate both JA- and SA-dependent defenses (Adie et al., 2007). Additionally, other phytohormones, like abscisic acid (ABA), brassinosteroids, gibberellic acid (GA) and cytokinins, play important regulatory roles in plant defense as well (Pieterse et al., 2012). Importantly, the defense-signaling pathways regulated by these phytohormones interact within a complex network and have often been found to operate not simply additive but non-linearly via cross-talk in antagonistic or synergistic manners. It is frequently suggested that cross-talk allows plants to fine-tune the balance between different defensive strategies and growth (Koornneef & Pieterse, 2008), depending on the type of attacker that is encountered, or in the case that the plant is attacked by multiple attackers, depending on the timing and sequence of infestation (Pieterse & Dicke, 2007; Pieterse et al., 2012). Yet, the biological necessity for prioritizing one defense over the other is not always immediately evident. Of all signal interactions that can occur between hormonal pathways, cross-talk between the JA and SA pathway has received most of the experimental attention. SA has frequently been observed to antagonize JA-signaling, and these effects may take place upstream as well as downstream of JA-biosynthesis (Leon- Reyes et al., 2010). Although less often documented, it is known that JA-signaling can negatively impact the SA-pathway as well (Niki et al., 1998; Thaler et al., 1999). Notably, the net outcome of JA/SA signal interactions depends on the relative concentrations of each hormone, as synergistic, rather than antagonistic, interactions have been observed under low concentrations of JA and SA (Mur et al., 2006). Plant defensive measures may sometimes fail to fend off herbivores, and this depends on the nature and magnitude of the response as well as the degree of susceptibility of the herbivore to this response. For instance, herbivores may avoid host plants that are potentially harmful (Bleeker et al., 2011), or develop resistance to plant-produced allelochemicals (Després et al., 2007). Alternatively, some herbivores can suppress the plant’s induced response to which they are susceptible. For instance, Kant et al. (2008) reported on a ‘suppressor’ strain of the two-spotted spider mite Tetranychus urticae which suppresses JA-defense responses in tomato, resulting in a higher performance of ‘inducer’ mites co-inhabiting the same leaflet. Suppressor mites performed equally well on wild-type (WT) and def-1 mutant plants, but had a lower performance on transgenic plants that overproduced the otherwise suppressed JA-defenses (Kant et al., 2008). Similarly, the red tomato spider mite

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(Tetranychus evansi) was found to suppress both the JA- and SA-pathways in toma- to (Sarmento et al., 2011), and this suppression was shown to occur downstream of phytohormone accumulation and independent from JA-SA cross-talk (Alba et al., manuscript submitted). Although it is not known how spider mites establish this suppression there is reason to believe that, similar to plant pathogens (Abramovitch et al., 2006) and some herbivores (Musser et al., 2002; Bos et al., 2010; Wu et al., 2012), they produce and secrete effector proteins via their saliva that interfere with the establishment of induced responses (C. Villarroel, J. Liu & T. Van Leeuwen, unpublished data). An alternative strategy for herbivores to block/manipulate induced plant defenses is to take advantage of cross-talk between defense-signaling pathways. Several studies suggest that herbivores can manipulate the plant’s JA-SA antagonism in a manner that benefits them (Zarate et al., 2007; Weech et al., 2008; Zhang et al., 2013). A well-known example is that of whiteflies which induce SA-defenses in Arabidopsis thaliana thereby suppressing JA-responses and this improves their performance (Zarate et al., 2007; Zhang et al., 2013). Yet, cross-talk may operate differently in different plant species (Halim et al., 2009; Rayapuram & Baldwin, 2007) which might explain why Zhang et al. (2012) found that on tobacco (Nicotiana tabacum) plants suppression of JA-defenses by whiteflies was mediated independently from SA. Furthermore, Zhang et al. (2009) reported that while co-infesting spider mite- infested Lima bean (Phaseolus lunatus) plants with whiteflies resulted in a decreased expression of two JA-associated genes and increased spider mite performance, this effect was not due to enhanced SA levels. Taken together, although the JA/SA antagonism potentially allows plants to tailor their defenses to different attackers, and hence may be adaptive (Thaler et al., 2012), it may also be a target vulnerable for manipulation by herbivores. Moreover, in situa- tions where the plant is attacked by multiple attackers, conflicts between SA-mediated resistance to biotrophic pathogens and JA-induced defense against herbivores can occur as a result of JA/SA-cross-talk (Bostock, 2005; Spoel et al., 2007; Verhage et al., 2010). For instance, induction of the SA pathway in Arabidopsis plants by the biotrophic pathogen Pseudomonas syringae lead to a suppression of JA-defenses and consequently leaves became more susceptible to the necrotrophic pathogen Alternaria brassicicola (Spoel et al., 2007). Hence, it is expected that in nature, where plants are exposed to a variety of attackers, such conflicts in plant defenses may occur frequently (Bostock, 2005; Thaler et al., 2010). Here, we investigated how the cultivated tomato (Solanum lycopersicum) responds to attack by two different mite (Acari) species, i.e., the generalist two-spotted spider mite (Tetranychus urticae) and an eriophyoid mite, the tomato russet mite (Aculops lycopersici). Adult female spider mites are ca. 0.5 mm long, whereas adult

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russet mites are about 125 μm long (Lindquist et al., 1996). Spider mites produce on average 4-10 eggs per day per adult female on tomato (Kant et al., 2004; Alba et al., submitted), depending on the temperature, which develop in reproducing adults themselves within a period of 2 weeks. Russet mites complete an entire life-cycle within 7 days, again depending on the temperature, and lay between 30-50 eggs during their life. The intrinsic rate of natural increase between A. lycopersici has been estimated to be nearly equal to that of T. urticae (Kawai & Haque, 2004). This means that both mite species display a rapid and exponential population buildup causing them to easily develop into pests on economically important crops, such as tomato (Lange & Bronson, 1981). Spider mites can be controlled relatively well in greenhouses and in the field using their natural enemy, the predatory mite Phytoseiulus persimilis (Helle & Sabelis, 1985). In contrast, russet mites are difficult to control as they hide in forests of glandular leaf hairs on leaves and stems (Van Houten et al., 2013). Interestingly, in open fields and greenhouses, spider mites and russet mites have frequently been observed together on tomato plants (CHAPTER 3). Furthermore, it was found that spider mites have a higher reproductive performance on tomatoes pre- infested with russet mites as compared to clean plants (CHAPTER 3). This prompted the question if russet mites affect the tomato plant’s induced defense response in such a way that spider mites may benefit. To test this we used a common genotype of the two-spotted spider mite which induces JA- and SA-dependent defenses in tomato and is vulnerable to the JA-defenses it induces (Kant et al., 2008; Alba et al., submitted). We hypothesized that russet mite infestations may alter the interaction between the spider mite and its host plant, thereby affecting spider mite reproductive performance. To investigate this, we first applied the ‘ask-the-plant’ approach, i.e., we studied defense responses in tomato plants that had been infested with spider mites, russet mites or the combination of spider mites and russet mites. As indi- cators for the defense response, we measured the accumulation of the phytohormones JA, JA-Ile and SA, the transcriptional responses of four established JA-marker genes as well as an SA-marker gene. Also, we determined the activity of the enzyme polyphenol oxidase (PPO), which is induced in tomatoes in response to wounding and treatment with systemin or methyl jasmonate (Constabel et al., 1995) and therefore often used as a marker for JA-regulated responses.

Material and methods Plants and mites Tomato seeds (Solanum lycopersicum cv. Castlemart (CM) and S. lycopersicum cv. Moneymaker (MM) as well as the transgenic line nahG, in the genetic background MM) were germinated in soil and grown in a greenhouse compartment at a temperature of 25ºC and a 15/9 h light/dark regime. One week prior to each experiment,

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plants were transferred to a climate room with day/night temperatures of 27ºC/25ºC, a 16/8 h light/dark regime and 60% RH. All experiments were performed on 21-day- old plants. nahG plants are transformed with the bacterial gene nahG encoding salicylate hydroxylase which removes endogenous SA by converting it into catechol (Brading et al., 2000). The nahG gene is under the control of the constitutively expressed CaMV 35S promoter. Experiments with WT and nahG plants were always carried out in parallel. Tomato russet mites (A. lycopersici, also referred to as russet mites or abbreviated as RM) were obtained from Koppert Biological Systems (Berkel en Rodenrijs, The Netherlands), who in turn had obtained them in the summer of 2008 from a natural infestation in a greenhouse in the Westland area (The Netherlands), and was since reared in insect cages (BugDorm-44590DH, Bug Dorm Store, MegaView Science, Taichung, Taiwan) in a climate room on tomato plants (cv. CM) that were between 3 and 5 weeks old. Two-spotted spider mites (T. urticae, also called spider mites or abbreviated as SM) were originally obtained in 2001 from a single European spindle tree (Euonymus europaeus), in the dunes near Santpoort (The Netherlands) (GPS coordinates: 52 26.503 N, 4 36.315 E). The strain we used has been identified as a JA-inducing mite genotype and as susceptible to these defenses (Kant et al., 2008). Since its collection from the field, the strain has been propagated on detached bean (Phaseolus vulgaris) leaves that were placed with the abaxial surface on wet cotton wool and maintained in a climate room (temperature of 25ºC, a 16/8 h light/dark and 60% RH).

Infestation and sampling of plants used for enzyme activity, gene expression, and phytohormone analyses At the start of the experiments, 21-day-old tomato plants were infested with spider mites (SM), russet mites (RM) or with the two species together. RM infestations were done by transferring the mites on small pieces of leaflets (ca. 0.5 cm²) to the leaflets of uninfested plants. These leaflet pieces had been cut from leaves picked from a well-infested tomato plant and each piece contained ca. 250 mobile stages of RM as determined with a stereomicroscope. Plants with spider mites received five spider mites per leaflet on each of three leaflets per plant. Thus, each plant received 15 spider mites in total. RM and SM were always introduced at the same time. To prevent mites from dispersing we applied a thin barrier of lanolin (Sigma-Aldrich Chemie, Zwijndrecht, The Netherlands) on the petioles of leaflets that were chosen for infestation. Uninfested control plants received lanolin, but no mites. In total, three leaflets per plant were infested which were pooled at the time of sampling. This sample was taken as one biological replicate. Sampled leaflets were flash-frozen in liquid nitrogen and stored at -80°C until total RNA or phytohormones were extracted. We

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always picked the same leaflets for infestation, i.e., one leaflet of the second compound leaf (counted from the bottom to the top of the plant), one from the third compound leaf and the terminal leaflet of the fourth compound leaf. Sampling was performed 7 days after infestation. Generally, starting with a density of ca. 250 RM per leaflet infection symptoms became visible 5-6 days after infestation. After 7 days of infestation (the time-point of sampling) symptoms of RM-infestation were clearly visible, but leaflets were not necrotic or senesced. The relative transcript levels presented in FIGURES 2.2 and 2.4 represent the mean of 11-13 biological replicates, obtained from three independent experiments that were carried out at different time-points. The PPO activity results are the mean of three biological replicates, from one experiment (FIGURE 2.3). The phytohormone levels presented in FIGURE 2.5 represent the mean of 9-10 biological replicates, obtained from two independent experiments that were carried out at different time-points. Because RM infestations frequently start at the basis of the stem (Jeppson et al., 1975) and because RM densities are often higher on petioles and stems than on leaves (J.J. Glas, personal observation), we decided to assess phytohormone levels in stems as well. For this experiment, 21-day-old tomato plants were infested with ca. 1500 RM (mixed stages) in total. RM were released at the basis of the main stem and stem sections were sampled 11 days after infestation. At this time-point, clear symptoms of RM damage were visible, as evidenced by the degradation of the plant’s glandular trichomes (Van Houten et al., 2013). From each plant, the upper part of the stem was harvested (i.e., the section between the points where the third and sixth true leaf, counted from the bottom of the plant, are attached to the stem) (FIGURE 2.1). After sampling, stem pieces were flash-frozen in liquid nitrogen and stored at -80°C until phytohormones were extracted.

Enzyme activity analysis PPO activity was determined as described by Thaler et al. (1996). Briefly, frozen and crushed leaf samples were weighed and enzymes were extracted by homogenizing approx. 200 mg leaf material in a 2 ml tube with 1.25 ml ice-cold 0.1M K Phosphate buffer (pH=8) containing 7% (w:v) polyvinylpolypyrrolidine and 400 μl of 10% Triton- X-100. The mixture was vortexed and centrifuged at 11.000 rpm at 4°C for 10 min. Of the resulting supernatant, 30 μl was added to 1 ml of a caffeic acid solution (2.92 mM in K Phosphate buffer, pH=8) and the increase in optical density (OD) at 470 nm was immediately measured, by means of a spectrophotometer (HITACHI-U2000, Tokyo, Japan). The change in absorbance was recorded every 15 s during a period of 2 min. The enzyme activity was recorded as ΔOD/min/g fresh leaf tissue but presented as relative to the mean activity of control plants (FIGURE 2.3).

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Quantification of gene expression via qRT-PCR Leaflets were cut at the base and three leaflets per plant were pooled in 50-ml tubes, flash frozen in liquid nitrogen, and stored at -80ºC. Leaflets were ground in liquid nitrogen, and total RNA was extracted using a phenol-LiCl-based method as described (Verdonk et al., 2003). The integrity of RNA was checked on 1% agarose gels and subsequently quantified using a NanoDrop 100 spectrophotometer (Fisher Scientific, Loughborough, UK). DNA was removed with DNAse (Ambion, Huntingdon, UK) according to the manufacturer’s instructions, after which a control PCR was carried out to confirm absence of genomic contaminations. cDNA was synthesized from 2 μg total RNA using a poly(dT) primer and M-MuLV Reverse Transcriptase (Fermentas, St. Leon-Rot, Germany) according to the manufacturer’s instructions. cDNA dilutions (10×) were used as template in quantitative Real-Time PCR (qRT- PCR). Reactions were carried out in a total volume of 20 μl containing 0.25 μM of each primer, 0.1 μl ROX reference dye and 1 μl of cDNA template. Two technical replicates were performed per measurement. qRT-PCR was performed with Platinum SYBR Green qPCRSuperMix (Invitrogen, Paisley, UK) using an ABI 7500 (Applied Biosystems) system. The program was set to 2 min 50°C, 10 min 95°C, 45 cycles of 15 s at 95°C and 1 min 60°C, followed by a melting curve analysis. Target gene

FIGURE 2.1 Schematic diagram of a tomato plant. Shown are the locations of the leaflets on leaf 2, 3 and 4 that were harvested for measurements of gene expression, PPO activity and phytohormones (reported in FIGURES 2.2- 2.5). In addition, the part of the stem is indicated that was used for phytohormone measurements (reported in FIGURE 2.6).

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expression levels were normalized to those of Actin. The normalized expression (NE) Δ Ct_target Ct_ref- data were calculated by the Ct method NE = [1/(PEtarget )]/[1/(PEreference erence)] (PE = primer efficiency; Ct = cycle threshold). The PEs were determined by fit- ting a linear regression line on the Ct-values of a standard cDNA dilution series. Specific amplification was ensured by melting curve analyses and generated ampli- cons were sequenced. For presenting the qRT-PCR data in the graphs we projected the data on a relative scale by dividing all values by the lowest average value (such that the lowest average is always 1). As markers for the JA pathway we used four genes: (1) Polyphenol oxidase-F (PPO- F) which is one of the seven members of the PPO gene family and expressed in toma- to leaves and also in type VI glandular trichomes (Thipyapong et al., 1997), (2) Threonine Deaminase-II (TD-II), involved in resistance against herbivores in tomato and tightly regulated by the JA-signaling pathway (Gonzales-Vigil et al., 2011), (3) Jasmonate-Inducible Protein 21 (JIP-21), also referred to as Cathepsin D inhibitor (CDI) or Tomato Chymotrypsin Inhibitor-21 (TCI-21) and inducible to high levels by wounding and methyl jasmonate in tomato leaves (Lisón et al., 2006) and (4) Wound-induced Proteinase Inhibitor II (WIPI-II) (Graham et al., 1985). JIP-21 and WIPI-II are induced in tomato by spider mites (Kant et al., 2004) and the latter two genes encode proteins that inhibit herbivore digestive proteinases (Hartl et al., 2011). As marker for the SA- pathway, we quantified expression levels of a fifth gene: Pathogenesis-related Protein 6 (PR-P6). Expression of PR-P6 is known to be induced in tomato by spider mites (Ament et al., 2004; Kant et al., 2004). The primers we used are listed in TABLE 2.1.

Quantification of phytohormones by means of LC-MS Phytohormones were extracted by homogenizing frozen leaf material (approx. 250

mg) in screw cap tubes containing 1 ml of ethyl acetate spiked with 100 ng of D6-SA and D5-JA (‘C/D/N Isotopes’, Pointe-Claire, Quebec, Canada) as internal standards. Samples were ground twice, using a GenoGrinder (Precellys24 Tissue Homogenizer, Bertin Technologies, Aix-en-Provence, France), at 6500 rpm for 45 s and centrifuged at 13.000 rpm (8 g) for 20 min at 4ºC. Supernatants from two extraction steps were pooled and evaporated until dryness in a vacuum concentrator (CentriVap Centrifugal Concentrator, Labconco, Kansas City, USA) at 30ºC. The dried residue was dissolved in 250 μl 70% methanol, vortexed and centrifuged and the supernatant was transferred to LC-MS vials (Fisher Scientific, Hampton, USA). Phytohormone measurements were conducted on a liquid chromatography tan- dem mass spectrometry system (Varian 320 Triple Quad LC/MS/MS). Twenty μl of each sample was injected onto a Pursuit 5 column (C18; 50 × 2.0 mm). The mobile phase comprised of solvent A (0.05% formic acid in water; Sigma-Aldrich, Zwijndrecht, The Netherlands) and solvent B (0.05% formic acid in methanol; Sigma-

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TABLE 2.1 Accession numbers of the transcripts quantified by qRT-PCR and their primer sequences. Target gene GenBank (GB) ID GenModel (ITAG2.3) Primer sequence ACT XM_004235020.1 Solyc03g078400.2 QF 5’-TTAGCACCTTCCAGCAGATGT-3’ QR 5’-AACAGACAGGACACTCGCACT-3’ PPO-F AK247126.1 Solyc08g074630.1.1 QF 5’-CGGAGTTTGCAGGGAGTTATAC-3’ QR 5’-TTGATCTCCACACTTTCAATGG-3’ TD-II M61915.1 Solyc09g008670.2 QF 5’-TGCCGTTAAAAATGTCACCA-3’ QR 5’-ACTGGCGATGCCAAAATATC-3’ JIP-21 AJ295638.1 Solyc03g098790.1 QF 5’-ACTCGTCCTGTGCTTTGTCC-3’ QR 5’-CCCAAGAGGATTTTCGTTGA-3’ WIPI-II AY129402.1 Solyc03g020080.2 QF 5’-GACAAGGTACTAGTAATCAATTATCC-3’ QR 5’-GGGCATATCCCGAACCCAAGA-3’ PR-P6 M69248.1 Solyc00g174340.1 QF 5’-GTACTGCATCTTCTTGTTTCCA-3’ QR 5’-TAGATAAGTGCTTGATGTCCA-3’

Aldrich). The program was set as follows: 95% solvent A for 1 min 30 s (flow rate 0.4 ml/min), followed by 6 min in which solvent B increased till 98% (0.2 ml/min) which continued for 2 min 30 s with the same flow rate, followed by 1 min 30 s with increased flow rate (0.4 ml/min), subsequently returning to 95% solvent A for 1 min until the end of the run. Compounds were detected in the electrospray ionization- negative mode. Molecular ions [M-H]– at m/z 137 and 209 and 141 and 213 generated from endogenous SA and JA and their internal standards, respectively, were fragmented under 12V collision energy. The ratios of ion intensities of their respec- tive daughter ions, m/z 93 and 97 and m/z 59 and 61, were used to quantify endogenous SA and JA, respectively. A standard dilution series of pure compounds of JA- Ile (OlChemIm, Czech Republic), JA and SA (Duchefa Biochemie, The Netherlands) was used to estimate the phytohormone concentrations and the retention time. The amounts were corrected for losses occurring during the extraction with a recovery rate, using the JA and SA internal standards.

Statistical analysis Gene expression data were statistically analyzed using a nested ANOVA. NE values were compared among treatments using ‘Treatment’ (with the levels ‘Control’, ‘SM’, ‘RM’ or ‘Both mites’) as fixed factor and with the factors ‘Experimental replicate’, ‘Biological replicate’ and ‘Technical replicate’ included as random factors in the model. The factor ‘Technical replicate’ (with levels 1 and 2) was nested to the factor ‘Biological replicate’. Phytohormone data were log-transformed and analyzed using ANOVA, with ‘Treatment’ as fixed factor and ‘Experimental Replicate’ included as random factor in the model. Means of each group were compared using Fisher’s LSD (Least Significant Difference) post hoc test. Student t-test was performed in Excel (Microsoft, Redmond, WA, USA) and ANOVA followed by Fisher’s LSD tests in SPSS 20.0 (SPSS, Chicago, IL, USA).

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Results Russet mites suppress expression of spider mite-induced JA-marker genes By using qRT-PCR, we quantified the transcript levels of five key defense genes in leaflets infested with spider mites, russet mites and leaflets infested with spider mites plus russet mites. As markers for the JA-pathway we tested four genes, i.e., PPO-F, TD-II, JIP-21 and WIPI-II. As compared to uninfested control plants, spider mites induced a significant accumulation of all four transcripts (P<0.001 for all four comparisons; FIGURE 2.2A-D). In contrast, russet mites did not cause a significant up-regulation of these genes (PPO-F, P=0.96; TD-II, P=0.060; JIP-21, P=0.73; WIPI-II, P=0.92; FIGURE 2.2A-D). It is important to note that the absence of gene induction can be due to several reasons, such as a low intensity of feeding, stealthy feeding (i.e., the herbivore feeds but somehow recognition by the plant is prevented; Walling, 2008), or to defense suppression. To discriminate among these possibilities, we decided to measure JA- marker gene expression also in plants co-infested with russet and spider mites. We reasoned that in the case of defense suppression additional infestation of spider mite-infested plants with russet mites should result in the inhibition of spider mite- induced JA-marker gene transcript levels, whereas we did this not expect to happen in the case that russet mites feed stealthy or do not feed at all. We found that in co-infested plants, the expression levels of all four spider mite- induced JA-defense marker genes were reduced to levels half of those measured in leaflets infested with spider mites only (PPO-F, P<0.001; TD-II, P<0.001; JIP-21, P<0.001; WIPI-II, P=0.010; FIGURE 2.2A-D). Hence, this result suggests that in plants co-infested with both mite species JA-defenses are suppressed, rather than not- induced. In contrast, expression of the SA-marker PR-P6 was significantly induced by russet mites (P<0.001) as well as by spider mites (P<0.001; FIGURE 2.2E). Furthermore, in co-infested plants the expression of PR-P6 was doubled as compared to the levels in plants infested with spider mites only (P<0.001) or russet mites only (P<0.001; FIGURE 2.2E).

Spider mites induce PPO activity but russet mites not First, a pilot experiment was carried out in which we treated 21-day old tomato plants with Methyl Jasmonate (MeJA). Overnight exposure of plants to a vapor of MeJA caused a significant increase in PPO activity as compared to untreated plants, thereby validating our method (data not shown). Subsequently, PPO activity was measured in mite-infested plants. Damage resulting from russet mite feeding did not lead to an increase in PPO activity, relative to uninfested control plants (P=0.33). In contrast, spider mite feeding caused a significant 4-fold increase in PPO activity

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FIGURE 2.2 Russet mites (RM) suppress spider mite (SM)-induced expression of JA-marker genes but induce expression of a SA-marker gene. Shown are the relative transcript levels of PPO-F (A), TD-II (B), JIP-21 (C), WIPI- II (D) and PR-P6 (E) in wild-type (‘WT’) (cv. MM) tomato leaflets infested with five SM, RM or both species (‘Both mites’) together. Values (+SEM) represent the mean of 11-13 plants from three independent experiments. Different letters above bars denote significant differences in expression levels between treatments (ANOVA followed by LSD test: P<0.05).

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(P=0.007). PPO activity in plants infested with both mite species was significantly induced compared to control and russet mite-infested plants (P=0.004 and P=0.02, respectively), but similar to that in plants infested with both mites together (P=0.77; FIGURE 2.3).

Suppression of spider mite-induced JA-marker gene expression is not significant anymore in nahG plants In WT plants, JA-marker genes were not, or only slightly, up-regulated by russet mites. Notably, the presence of russet mites on spider mite-infested plants caused a significant inhibition of spider mite-induced JA-marker gene expression (FIGURE 2.2A- D). In contrast, both spider mites as well russet mites caused an increase in expression of the SA-marker PR-P6 and this response was doubled in plants infested with both species simultaneously (FIGURE 2.2E). Therefore, considering the well-described cross-talk between JA and SA, we subsequently wanted to test if suppression of JA- marker genes by russet mites could be attributed to negative JA/SA-cross-talk. For these experiments we used SA-deficient transgenic nahG plants, which are unable to accumulate SA. On nahG plants, spider mite feeding caused a strong up-regulation of all four JA- marker genes (P<0.001 for all four comparisons; FIGURE 2.4), whereas the up-regula-

FIGURE 2.3 Russet mites (RM) do not induce PPO activity. Shown are the relative mean activities (+SEM) of the protein polyphenol oxidase (PPO) in response to damage resulting from spider mite (SM) or RM feeding on toma- to (cv. CM). Enzyme activities were determined after 7 days of infestation (n=3). Activities are expressed relative to the mean activity of control plants. Mean activities were divided by the mean activity of the control to obtain relative activities. Values presented are untransformed data. Different letters above bars denote significant differences in expression levels between treatments (ANOVA followed by Fisher’s LSD test: P<0.05).

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tion of these genes by russet mites was not significant (PPO-F, P=0.092; TD-II, P=0.22; JIP-21, P=0.71, WIPI-II, P=0.87; FIGURE 2.4), similar to the pattern in WT plants (FIGURE 2.2A-D). In contrast to WT plants, spider mite-induced PPO-F and TD- II expression was restored in nahG plants that had been co-infested with russet mites (comparison ‘SM’-’Both mites’, PPO-F; P=0.98; TD-II, P=0.53; FIGURE 2.4A,B). Also, suppression of spider mite-induced JIP-21 expression was not significant anymore in nahG plants that had been infested with both mite species simultaneously (comparison ‘SM’-‘Both mites’, JIP-21, P=0.068; FIGURE 2.4C). Spider mite-induced expression of WIPI-II was down-regulated in nahG plants infested with both mite

FIGURE 2.4 Russet mite (RM)-mediated suppression of the spider mite (SM)-induced JA-response depends on SA. Shown are the relative transcript levels of PPO-F (A), TD-II (B), JIP-21 (C) and WIPI-II (D) in nahG plants infested with five SM, RM or both species (‘Both mites’) together. Values (+SEM) represent the mean of 12-13 plants from three independent experiments. Different letters above bars denote significant differences in expression levels between treatments (ANOVA followed by LSD test: P<0.05).

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species simultaneously (comparison ‘SM’-‘Both mites’, WIPI-II, P=0.012; FIGURE 2.4D), similar to the pattern in WT plants.

Quantification of JA, JA-Ile and SA in WT and nahG plants Subsequently, to obtain further insight in defense responses induced by russet mites and spider mites we quantified phytohormone levels in plants infested with both species. To explore the possible role of SA in the inhibition of JA-defenses, we measured phytohormones in WT plants as well as in SA-deficient nahG plants. Leaflets were sampled 7 days after infestation, as in the gene expression experiments. In WT plants, spider mites induced a ca. 2.5-fold increase in accumulation of JA (P=0.001), whereas the amount of JA-Ile was 7× higher compared to uninfested control leaflets (P<0.001; FIGURE 2.5A,B). Russet mites also induced the accumulation of JA and JA-Ile, up to levels that were, respectively, 1.5 and 6× higher compared to uninfested leaflets (P=0.03 and P<0.001, respectively). In co-infested WT plants, levels of JA were significantly higher than in leaflets infested with spider mites only (P=0.013) or russet mites only (P<0.001). Similarly, JA-Ile content was significantly higher in co-infested plants than in plants infested with spider mites only (P=0.02) or russet mites only (P=0.001). Compared to uninfested control plants, the levels of SA were ca. 6× higher in spider mite- as well as in russet mite-infested tissue (P<0.001 for both comparisons; FIGURE 2.5C). In leaflets infested with both mite species, SA levels were ca. 8× higher than in uninfested control plants (P<0.001) and also higher than in plants that had been infested with spider mites only (P=0.018) or russet mites only (P=0.04). Both spider mites and russet mites induced a significant accumulation of JA (P<0.001 and P=0.025, respectively) as well as JA-Ile in nahG plants (P<0.001 and P=0.001, respectively). Spider mites induced significantly more JA and JA-Ile in nahG plants than russet mites (P=0.028 for JA and P=0.034 for JA-Ile). In co-infested nahG plants, levels of JA were significantly higher than in plants infested with spider mites only (P=0.027) or russet mites only (P<0.001). Similarly, the levels of JA-Ile were significantly higher in co-infested plants compared to nahG plants infested with spider mites only (P=0.003) or russet mites only (P<0.001). In general, nahG plants seemed to produce less JA than WT plants. In nahG plants, only marginal amounts of SA were detected (FIGURE 2.5C), which confirms that SA accumulation was effectively blocked due to degradation by the enzyme salicylate hydroxylase.

Quantification of JA, JA-Ile and SA in WT tomato stems In a next experiment, we also determined phytohormone levels in tomato stems, which is the tissue where russet mites under natural circumstances begin to feed (Jeppson et al., 1975). In this experiment, spider mites were excluded as a treatment

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FIGURE 2.5 Phytohormone levels in leaflets infested with spider mites (SM), russet mites (RM), and both species (Both mites) simultaneously. The figure shows the amounts of endogenous JA (A), JA-Ile (B) and SA (C) in uninfested and mite-infested wild-type (‘WT’) (cv. MM) and nahG leaflets (7 days after infestation). Values in the bars represent the means (+SEM) in nanogram (ng) per g fresh weight (g FW) of 9-10 plants, obtained in two independent experiments. Different lowercase letters denote significant differences for WT plants; uppercase letters denote significant differences for nahG plants (ANOVA followed by Fisher’s LSD test: P<0.05).

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since they do normally not feed on stem tissue. Remarkably, russet mites caused an almost significant two-fold reduction in JA levels in the stem (Student t-test; P=0.069) (FIGURE 2.6A). The amount of JA-Ile in stems was very low compared to leaves and did not differ between infested and uninfested stems (P=0.28; FIGURE 2.6B). In contrast to leaves, where russet mites caused a significant increase in SA- levels (FIGURE 2.5C), the SA concentration was not increased in russet mite-infested stems as compared to uninfested stems (P=0.45; FIGURE 2.6C).

Discussion By combining assays to assess the activity of a defense enzyme, the accumulation levels of defense gene transcripts and phytohormone levels we have dissected the defense responses of tomato plants and their net dependency on JA and SA during infestation with spider mites, russet mites or the combination of spider mites plus russet mites. Even though both russet mites and spider mites induced the accumulation of JA and its active form JA-Ile in tomato leaflets (FIGURE 2.5A,B), we found that feeding by russet mites did not or only slightly upregulate the expression of JA-marker genes, whereas spider mites up-regulated these genes 3-30× more (FIGURE 2.2A- D). In contrast, both spider mites and russet induced a strong accumulation in transcript levels of the SA-marker gene PR-P6 and these levels were doubled in the presence of both mite species (FIGURE 2.2E). In line with this, the accumulation of SA was induced by each of the two mites as well (FIGURE 2.5C). Hence, this indicates that each of the two species activates the SA pathway, in spite of the fact that the two species feed from different tomato tissues.

FIGURE 2.6 Phytohormone levels in tomato stems. The amounts of endogenous JA (A), JA-Ile (B) and SA (C) in uninfested (control) and mite-infested (RM) tomato (cv. CM) stems, after 11 days of infestation. Bars represent means (+SEM) in nanogram (ng) per g fresh weight (g FW) (n=3). Statistical analysis was performed with Student t-test. NS = not significant.

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Concerning this latter point: even though both spider and russet mites are cell content feeders, they feed from different cells. Spider mites feed from leaf spongy parenchyma and the palisade parenchyma cells, which they pierce with their ca. 150 μm stylets to suck the contents (Park & Lee, 2002), resulting in the formation of small, white-coloured lesions, which is a typical symptom of spider mite feeding on toma- to. Probably because of their much shorter stylets (ca. 10 μm), russet mites do not damage cells in the mesophyll layer but instead they pierce epidermal cells on leaves, petioles and stems of tomato (Royalty & Perring, 1988). Russet mites have a particular mode of feeding which differs from that of spider mites. They start feeding on a single epidermal cell for a short time period, which usually rapidly collapses and dies in response to the attack. Subsequently, the mite moves away to attack distal cells, and this behavior causes a massive destruction of the epidermal cell layer. In response to this, a lignin layer is formed over the parenchyma, and oxidation of this layer causes the typical symptoms of damage resulting from russet mite feeding, visible as russeting, or silvering (Royalty & Perring, 1996). In conclusion, even though the two mite species attack different cell types and have different modes of feeding, this does not prevent the plant from activating SA-mediated defense in response to both species. By measuring enzyme activity, we found that feeding by russet mites did not lead to a significant increase in total PPO activity, whereas activity of PPOs was significantly induced upon spider mite feeding (FIGURE 2.3). PPOs constitute a class of enzymes that use molecular oxygen for the oxidation of mono- and O-diphenols to O-dihydroxyquinones. In tomato plants, PPOs are stored apart from their phenolic substrates, most likely to prevent spontaneous reactions. When leaf tissue is injured, for instance during feeding by herbivores, PPOs will mix with their phenolic substrates and rapidly oxidize O-dihydroxyphenolics to the corresponding O-quinones

(Felton et al., 1989). Quinones are highly reactive, and will bind to nucleophilic –NH2 and –SH groups of molecules, like amino acids and proteins, which can have a negative impact on herbivores, for instance by reducing the availability of essential amino acids or the digestibility of proteins, and this reduces the nutritive quality of leaves to herbivores (Felton et al., 1989, 1992). Our finding that russet mite feeding does not up-regulate PPO activity confirms previous results by Stout et al. (1994) who reported that activity of JA-dependent enzymes, including PPOs and PIs, was not induced by russet mites. In contrast, the same authors reported an induction in the activity of the JA-biosynthesis enzyme lipoxygenase (LOX), which aligns with our finding that russet mites induce accumulation of JA-related phytohormones, but not that of the downstream defense genes. In agreement with previous studies, spider mite feeding resulted in a strong activation of the JA-dependent defense response (Li et al., 2002; Kant et al., 2004), as

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indicated by a significant increase in JA-Ile accumulation (FIGURE 2.5A,B), in JA- marker gene expression (FIGURE 2.2) and in PPO activity (FIGURE 2.3). However, in co- infested plants the expression of JA-defense marker genes was reduced to levels significantly below the levels in leaflets infested with spider mites only (FIGURE 2.2A- D). From this result, we conclude that russet mites suppress JA-mediated defense responses. Unexpectedly, the levels of JA-related phytohormones remained strongly up-regulated in co-infested plants (FIGURE 2.5A,B), suggesting that russet mites interfere with JA-mediated defenses downstream of JA-biosynthesis. Russet mites did not cause the accumulation of PPO-F transcript levels (FIGURE 2.2A), and neither of total PPO-activity. In contrast, spider mites induced a significant increase of both. In the co-infestation treatment, however, PPO-F transcript levels were intermediate while the total activity was as high as during spider mite infestation. In tomato, PPOs are encoded by a seven member gene family (Thipyapong et al., 1997) so possibly in the combination treatment other PPOs were differentially regulated as well. For example, apart from PPO-F, at least one other PPO, i.e., PPO- D, is known to be induced by spider mites as well (Alba et al., submitted), but we did not measure the expression of this gene. Since we determined total PPO activity in our enzyme activity assay, it could be that other PPOs, for instance PPO-D, are induced by spider mites but not suppressed by russet mites, thereby augmenting the intermediate PPO-F levels and explaining why PPO activity was not significantly different between spider-mite infested and co-infested plants (FIGURE 2.3). Expression analysis of the different PPO genes could reveal whether other PPOs compensate for the decrease in PPO-F activity or maybe are expressed to much higher levels and responsible for the total activity altogether. It is important to note that the sampling point of day 7 after infestation was deliberately chosen. In preliminary experiments, we observed that at earlier time-points (i.e., at day 1 and 4 after infestation) russet mites induced JA-responses, whereas these responses were not significantly different anymore from control plants at day 7 after infestation. More important, significant suppression of spider mite-induced responses was observed at day 7 after infestation, whereas no differences were observed in JA-responses between plants infested with spider mites alone and plants infested with both russet mites and spider mites in the earlier time points (data not shown). Hence, this suggests that the effect of russet mites on the plant’s defense response strongly depends on the time that the mites have been feeding on the plant as well on mite density, i.e., using a higher or lower number of mites for the infestations at the start of the experiments may have resulted in a different outcome. Russet mites induced a significant increase in levels of SA (FIGURE 2.5C) and PR- P6 expression (FIGURE 2.2E). Moreover, in leaflets co-infested with both mite species SA-mediated defenses appeared to be stronger compared to leaflets with spider

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mites or russet mites only. Therefore, considering the well-described antagonistic cross-talk between JA and SA (Pieterse et al., 2009), we subsequently tested if suppression of JA-marker genes by russet mites could be attributed to the antagonistic interaction of SA onto JA. We observed that spider mite-induced JA-marker gene expression was restored in SA-deficient nahG plants that had been co-infested with russet mites (FIGURE 2.4), suggesting that indeed suppression of spider mite-induced JA-defenses is due to negative cross-talk with SA. However, in contrast, russet mites alone still only induced marginal JA-responses in nahG plants (FIGURE 2.4), similar to the situation in WT plants (FIGURE 2.2A-D). Hence, from this result we conclude that suppression of the downstream JA-response by russet mites is independent from SA, whereas in plants co-infested with both species suppression does depend on SA. Taken together, these findings imply that in leaflets infested with both mite species cross-talk is a consequence, and not the cause, of the primary suppression of JA-defenses by russet mites and that in plants infested with both species their induced SA-responses add up and antagonize the spider mite-induced JA-response as a secondary effect. Most notably, spider mites induced SA themselves to similar levels as russet mites. This raises an intriguing question: why does the russet mite-induced SA- response suppress spider mite-induced JA defenses but the SA induced by spider mites alone does not? Recall that spider mites induce JA- and SA-responses simultaneously, as seen in FIGURE 2.2 and 2.5. We think that actually also spider mite- induced SA antagonizes JA, albeit only to intermediate levels while only the total SA- response induced by the two mites together is powerful enough to suppress these intermediate levels to levels significantly below those in plants infested with spider mites only. This hypothesis is supported by the spider mite-induced JA-marker gene expression data in nahG: the relative expression of three of the four JA-defense markers was much stronger in nahG than in WT, i.e., relative expression of TD-II, JIP- 21 and WIPI-II was, respectively, ca. 40, 30 and 400% higher in nahG plants when compared to WT plants (FIGURE 2.2B-D vs. 2.4B-D), which suggests that the spider mite-induced JA-response may be partially suppressed down to a more moderate expression level by SA in WT plants. Hence, this also implies that on co-infested nahG plants JA-defenses could in fact be partly suppressed as well by russet mites (as also indicated by FIGURE 2.4D), although perhaps only to intermediate levels because of stronger JA-dependent defense responses in nahG plants. We did not find evidence for cross-talk at the phytohormone level as absence of SA did not lead to an extra increase in spider mite-induced JA or JA-Ile. In fact, levels of JA-related phytohormones tended to be lower in nahG plants compared to WT plants (FIGURE 2.5A,B). This differs from the result of a previous study where similar levels of JA were measured in WT and nahG plants under control conditions (Runyon

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et al., 2008). Related to this, it should be noted that nahG plants may be subject to considerable pleiotropy as it has been shown that, at least in Arabidopsis, accumulation of catechol may result in a loss of host resistance to the plant pathogenic bac-

terium Pseudomonas syringae, due to the inappropriate production of H2O2 (Van Wees & Glazebrook, 2003). Furthermore, it has been shown that the salicylate hydroxylase gene expressed in nahG plants may act on substrates other than SA (Heck et al., 2003), which can result in pleiotropic changes in the metabolism of nahG plants. Together, this suggests that data obtained from nahG plants should be han- dled with caution. To solve this problem, we attempted to create an independent tomato SA-mutant by silencing the gene Isochorismate Synthase (ICS) via callus transformation and regeneration using an inverted-repeat construct (FIGURES S2.1- S2.3). Unfortunately, this attempt was not successful: making the T0 transformants to flower took 1.5 years, and only after treating them with the SA-analogue BTH. Furthermore, the fruits we harvested carried no seeds (FIGURE S2.3). This suggests that SA-mutants in general may be severely compromised in their physiology. Insect herbivores employ different strategies to circumvent host defenses (reviewed by Alba et al., 2011). Suppression of JA defenses may occur via the induction of SA-related defenses, as observed for the fungus Botrytis cinerea (El Oirdi et al., 2011), for lepidopteran caterpillars (Weech et al., 2008; Bruessow et al., 2010) and whiteflies (Zarate et al., 2007; Zhang et al., 2013). Other herbivores accomplish suppression independent from SA (Musser et al., 2002, 2005; Soler et al., 2012; Wu et al., 2012) or even independent from both the JA- and SA-pathway (Consales et al., 2012). Zhang et al. (2009) showed that additional infestation of whiteflies on spider- mite infested lima bean plans lead to a reduction in the levels of not only JA but also SA. This suggests that whitefly-mediated interference with spider mite-induced plant responses is not due to negative cross-talk with SA. In contrast, in our system we found that SA is involved in the suppression of JA-responses induced by spider mites on co-infested plants. However, as our results also suggest, the primary suppression of JA-defenses by russet mites is independent from SA and, hence, other factors must be involved as well. This is also indicated by the fact that induction of JA-related phytohormones was not increased in russet mite-infested SA-deficient plants compared to WT plants infested with russet mites. Therefore we conclude that, unlike whiteflies on Arabidopsis (Zhang et al., 2013), russet mites suppress JA defenses in an SA-independent manner. In FIGURE 2.7, a schematic overview is provided of the JA and SA responses induced by russet and spider mites and how we think these interact in plants infested with both mite species. It is tempting to speculate that the presence of russet mites on a spider mite- infested plant may have affected the performance of these spider mites not only via the plant but also as a result of direct competition between the two herbivores. If

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such interactions would occur it could, in theory, cause a decrease in spider mite feeding intensity, which, in turn, could (partly) explain the reduced JA-defenses we observe in the presence of russet mites. However, there are several data that contra-

FIGURE 2.7 Schematic overview of the JA and SA responses induced by spider mites (A), russet mites (B) and the two species together (C) on tomato. AU=Artificial Unit; WT = wild-type.

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dict this direct interference hypothesis. First, we observed that spider mites laid more eggs on WT tomato plants that had been pre-infested with russet mites as compared to uninfested plants (CHAPTER 3), suggesting they eat equally much or more, not less, in their presence. Second, expression of PR-P6 was doubled in WT plants co-infested with both species compared to plants infested with either of the species alone, suggesting that the feeding damage is equal or more in the presence of both species. Third, for three of the four JA-marker genes significant suppression was not observed in co-infested nahG plants, which implies that spider mites keep on eating and damaging these plants, also in the presence of russet mites. Finally, we have no indications of direct interactions between russet mites and spider mites suggesting that other, plant-mediated, factors must have been responsible for the observed effects. Russet mites often prefer to colonize the stems of tomatoes before the population expands to the leaves. Remarkably, in stems infested with russet mites, levels of JA were reduced twofold as compared to the levels measured in uninfested control stems (FIGURE 2.6A). Before jumping to conclusions, it is important to keep in mind here that russet mite infestation leads to a rapid degradation of trichomes on toma- to stems (CHAPTER 5) and that trichomes from tomato stem tissue have been reported to contain significant amounts of JA (Peiffer et al., 2009). Hence, it is possible that the reduction in JA-content in russet mite-infested stems is (partly) due to the loss of trichomes on this tissue, rather than to a suppression of endogenous JA biosynthesis. To investigate if this induced morphological alteration stands at the basis of the JA-suppressed phenotype in stems, it would be relevant to measure phytohormone levels in trichome mutants as well. For instance, the odorless-2 mutant could be a good candidate for this since it has less type VI trichomes than WT plants, while it is unaffected in its JA-regulated defenses in the leaves (Kang et al., 2010). In general, JA-Ile amounts (per g fresh weight) in tomato stems were very low as compared to the levels in leaves. In tomato, JA is produced primarily in the companion cells of the phloem (Hause et al., 2003; Stenzel et al., 2003) while biosynthesis of JA-Ile has been reported to occur in leaves, in a conjugation reaction carried out by the enzyme Jasmonate Resistant 1 (JAR1) (Suza et al., 2010). Matsuura et al. (2011) confirmed that biosynthesis of JA-Ile from JA and Ile occurs in wounded tomato leaves. Furthermore they found, by applying radiolabeled JA-Ile in relatively high amounts to the wounded tissue, that JA-Ile was transported throughout the plant via the stems and, hence, that it could be a mobile signal. It is unknown at present if JAR1 expression is restricted to particular tissues, such as the phloem where JA is produced, or to the mesophyll where JA-Ile binds to the SCFCOI1 complex (Wasternack et al., 2006). Possibly, conjugation of JA and Ile occurs predominantly in non-stem tissue, which could explain the low JA-Ile amounts in the stem.

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Alternatively, there could also be a trivial explanation for the observed difference, i.e., tomato stems may contain relatively more water than leaves and, hence, comparing phytohormones on the basis of tissue fresh weight may be inappropriate. However, the amounts of SA in uninfested stems were in the same range as those observed in leaves, when calculated per g tissue fresh-weight, suggesting the comparison may actually hold. Unexpectedly, SA levels did not increase in russet mite-infested stems (FIGURE 2.6C), as they did in russet mite-infested leaflets (FIGURE 2.5C). This suggests that suppression of JA accumulation in stems is independent from a concomitant increase in SA. Taken together, induced phytohormone accumulation in stems may differ from that in the leaves and a more detailed analysis of defense gene expression in these tissues is necessary to determine if the same applied for induced defenses. Since the stems are the primary habitat of tomato russet mites, these data could provide important additional insights in how russet mites deal with host plant defenses. On the possible mechanisms along which russet mites interfere with the plant defense response we can only speculate. Yet, concerning this, first it is important to note that the saliva of some gall-inducing eriophyoids may contain phytohormonal substances, which, upon feeding, can be secreted into epidermal cells where they initiate development of (abnormal) plant tissues. For instance, eriophyoid galls were found to contain more indole acetic acid (IAA) than non-attacked leaf tissue (Balasubramanian & Purshothaman, 1972; in: Krantz & Lindquist, 1979). De Lillo & Monfreda (2004) suggested that saliva of Aceria caulobia contains IAA and cytokinin- like compounds, which probably is related to the ability of this mite species to induce galls on its host plant, Suaeda fruticosa. To the best of our knowledge, nobody ever reported on substances present in the saliva of vagrant eriophyoid species, such as russet mites. Yet, technically it is possible to collect ‘salivary secretions’ from this species (De Lillo & Monfreda, 2004; FIGURE 2.8), which opens up exciting new possibilities to analyze the content of these fluids and their (potential) impact on host plant defenses. Second, increasing evidence suggests that herbivores produce so-called effectors, i.e., proteins that are secreted in the saliva to suppress plant defenses, reminiscent of bacterial and fungal pathogens (Nomura et al., 2005). The first effector protein characterized from a herbivore was Glucose oxidase (GOX), which is widely present in the saliva of caterpillars, like Helicoverpa zea (Musser et al., 2002) and, as was discovered later, also in the saliva of some phloem feeding insects such as aphids (Harmel et al., 2008). The presence of GOX in caterpillar saliva was found to suppress wound-induced accumulation of nicotine in tobacco (Nicotiana tabacum) plants (Musser et al., 2002, 2005). Furthermore, it was found that also H. zea saliva contains ATP hydrolyzing enzymes (i.e., an apyrase, ATP synthase and ATPase

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FIGURE 2.8 Light micrograph of an Aculops lycopersici specimen and its ‘salivary secretion’ at the basis of the mouthparts (see arrow). Mites were collected by spinning an infested tomato leaflet in an Eppendorf tube. Subsequently, they were mounted in a droplet of microscope immersion oil on a slide and observed under a light microscope (magnification of 400×) (following the method of De Lillo & Monfreda, 2004).

13A1), which could suppress JA- and ET-regulated defense genes in tomatoes (Wu et al., 2012). As in caterpillars (Musser et al., 2002, 2005; Schmelz et al., 2012) and aphids (Bos et al., 2010), it is tempting to consider the possibility that russet mites produce and secrete effectors in their saliva, targeting specific components in defense signaling pathways. Later on in this thesis (CHAPTER 6) I will go in more detail into this. At this point, it suffices to mention that we have obtained a complete genome and transcriptome of russet mites and, from the transcriptome data, we have identified several candidate effector proteins (CHAPTER 6), which we are planning to test for their effect on host plant defenses. In conclusion, we have shown that russet mites suppress JA-responses, since they induce accumulation of SA and JA-related phytohormones, while only the downstream SA-response, and not the JA-response, is up-regulated by russet mites. Furthermore, since russet mites also did not induce JA-responses on SA-deficient nahG plants, we could show that russet mites suppress JA-defenses independent from SA. However, since the JA-response was restored on co-infested nahG plants, we conclude that induction of SA by russet mites does antagonize the JA-response induced by spider mites, when sharing the same leaflet. The fact that suppression of defenses affects responses induced by competing species prompts the question if such indirect interactions can modify a herbivore’s community structure. Cultivated tomato can be attacked by as many as 100-200 dif-

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ferent arthropod herbivores (Lange & Bronson, 1981), and russet mites are a worldwide pest of tomatoes (Perring, 1996). Hence, it is likely that in nature as well as in greenhouses russet mites often co-occur on plants with other pest species. Probably because infestations are often recognized too late, russet mites densities in greenhouses have been reported to be much higher than those used in the present study (Kawai & Haque, 2004). Therefore it is possible that, under these (semi-natural) conditions, the effect of russet mite-induced responses on spider mite-induced defense responses may be much more pronounced as the effects observed in the present study, i.e., the intermediate responses we have observed during co-infestation may escalate to full suppression. The consequences of russet mite-induced (SA) and - suppressed (JA) defenses for natural competitors of russet mites are described in CHAPTER 3.

Acknowledgements The ICS RNAi construct was produced during a 6-months transformation training that was offered to IBED staff in 2010. We thank dr. Rosanna Mirabella (Plant Physiology, University of Amsterdam) for excellent teaching and assistance with the cloning and stable transformations and dr. Frank Takken (Phytopathology, University of Amsterdam) for providing the pGollum vector. Also, we thank Arjen van Doorn, Michel de Vries for assistance with the LC-MS measurements, Jan van Arkel for pho- tographing the mites, Cor Rijkers (Syngenta, Bergen op Zoom) for providing BTH and Harold Lemereis, Ludek Tikovsky and Thijs Hendrix for taking care of our tomato plants.

References Abramovitch, R.B., Anderson, J.C. & Martin, G.B. (2006) Bacterial elicitation and evasion of plant innate immunity. Nature Rev. Mol. Cell Biol. 7, 601-611. Adie, B., Chico, J.M., Rubio-Somoza, I. & Solano, R. (2007) Modulation of plant defenses by ethylene. J. Plant Growth Regul. 26, 160-177. Alba, J.M., Glas, J.J., Schimmel, B.C.J. & Kant, M.R. (2011) Avoidance and suppression of plant defenses by herbivores and pathogens. J. Plant Int. 6, 221-227. Alba, J.M., Schimmel, B.C.J., Glas, J.J., Pappas, M.L., Schuurink, R.C., Sabelis, M.W. & Kant, M.R. (2013) Spider mites suppress both jasmonate and salicylate defenses to their benefit but this may backfire when living in communities. Submitted. Ament, K., Kant, M.R., Sabelis, M.W., Haring, M.A. & Schuurink, R.C. (2004) Jasmonic acid is a key regulator of spider mite-induced volatile terpenoid and methyl salicylate emission in tomato. Plant Physiol. 135, 2025-2037. Bleeker, P.M., Diergaarde, P.J., Ament, K., Schütz, S., Johne, B., Dijkink, J., Hiemstra, H., de Gelder, R., de Both, M.T.J., Sabelis, M.W., Haring, M.A. & Schuurink, R.C. (2011) Tomato-produced 7-epizingiberene and R-curcumene act as repellents to whiteflies. Phytochem. 72, 68-73. Bos, J.I.B., Prince, D., Pitino, M., Maffei, M.E., Win, J. & Hogenhout, S.A. (2010) A functional genomics approach identifies candidate effectors from the aphid species Myzus persicae (green peach aphid). PLoS Genet. 6 (11), e1001216.

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SUPPLEMENTAL MATERIAL AND METHODS

Creating the ICS RNAi construct To investigate the role of SA in the plant-mediated interactions between russet mites, spider mites and the phytopathogen Pst DC3000, we have made use of transgenic nahG plants. However, since these plants may give rise to unwanted side-effects due to the accumulation of catechol (Van Wees & Glazebrook, 2003), we also took a different approach by attempting to create transgenic lines in which expression of Isochorismate Synthase (ICS) was knocked down using RNA-interference (RNAi). ICS encodes an enzyme involved in SA biosynthesis in tomato plants (Uppalapati et al., 2007). A gene construct was designed to simultaneously silence ICS and the β-glu- curonidase (GUS) reporter gene, via the production of short interfering hairpin RNAs (hpRNA). The reason to include GUS is that it can be transiently expressed in leaves of stably transformed plants using ATTAs, thereby making it easier to screen for plants that show strong silencing (Ament et al., 2010). This method was successfully applied before for the silencing of SAMT and two interactors of a NBS-LRR-encoding resistance protein in tomato (Ament et al., 2010, and Lukasik-Shreepathy et al., 2012, respectively), as well for the silencing of NBS-LRR-encoding genes in lettuce (Wroblewski et al., 2007). The construct was made as follows: a 352-bp fragment of the 3’ part of the mRNA (Solyc06g071030; 1497-1850 bp downstream from the ATG codon) (FIGURE S2.1) was amplified with primers on which SfiI cleavage restriction sites had been introduced: F-Sfi-ICS = ATGGCCATGTAGGCC-GAAGAGAGTGAATTTGCGGTTG and R-Sfi-ICS = ATGGCCAGAGAGGCC-AAATTGCATATGACAGGTTGATG (15 bp-adapters containing the Sfi restriction sites are indicated in bold), using a proofreading polymerase (Phire Hot Start, Thermo Scientific, Landsmeer, The Netherlands). After sequencing the fragment, it was digested with restriction enzyme SfiI and ligated in the pre-made binary vector pGollum, which contained already a 344-bp part of the GUS gene (U12639, bases 3514-3858) fused to an intron (~700 bp) of the pyruvate orthophosphate dikinase (pdk) gene from Flaveria trinervia, which separated the two arms of the inverted repeat (FIGURE S2.2). The complete ICS fragment was sequenced in this construct, including its borders, using the Sfi-ICS primers, the pGreenF2 primer (ACTATCCTTCGCAAGACCC), annealing to the 35S promoter, a primer for the GUS fragment (CCAACTCCTACCGTAC) and the OSCtermRev primer (TCATGCGATCATAGGCGTCT), annealing to the OCS termina- tor. SfiI was purchased from New England Biolabs (Ipswich, UK) and T4 DNA ligase was obtained from Fermentas (St. Leon-Rot, Germany).

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Stable plant transformations For tomato-stable transformation, the construct was introduced into Agrobacterium tumefaciens strain LBA4404 (Hoekema et al., 1983), using electroporation. Transgenic plants were produced using explants derived from cotyledons of sterile seedings of S. lycopersicum (cultivar CM), as previously reported (Cortina & Culiáñez-Macià, 2004).

Analysis of transgenic plants Genomic DNA was isolated from leaves of the different T0 lines and PCR was used to determine whether plants had been transformed, using primers on the 35S pro-

atatttcaagagagattacgagcagagcacgagtcgtttagggctgttttcgagtccttcagaactggttctgacaagaggcg gccgcggatatctgggcttaatgctgaagatgaatagtgcatctgtagataggggtttaaaattgcatatttgctattttatg ttttgctaatcctttgccatagaggatgactgcccagtgtcttacgctgggggagggtttagccatttctattgtaatatagt gtaattcgtgtagcaaaataggtagttgatggccttgactggagggctatatgctatgggtccattgcctctgtactactgga aattttggtaatgaaggttttcaatgatagaagtggttcattaagcaataaatggatgtatggaagacaaatatcttgtaatc attggcttggctcatgaaaacaattttgattcgggatgtttaagagcccgtttggactagcttaaaagttggtcaaagttact tttaattttgtttttatttctggaagtgttcggtaaatatgaaacataatttaaagaagtgtttgacaaagtaaaaaatgact taaaataattcagaaatcaaagtaggtctcctgttacttcttttttgatctaaaagttatttcagtttaacttttttattttt tatcttaaaagcaatttttttaaagtcaattcaaacgggcgctttttttatttgtctatgtttgactttatacatgtcttgag aaagtaactaattaaaattttaagtttactataacactgttggaatatattaaattctatacgtgtcttgagaaagtaactaa ttaaaattttaagttttcactcatgtcattaaatatggatggagaacgtattaagtagaggaagagatgagatggcacacaag gacaatagagttttcactcctcccatctatttgtggtcttggaattcaactttatagcggctaagatgtgtaatggtggccca tttcttacatcatctatggcaaataataaacttctgcgtatataaagtaaagaccatacttgtttattgggtttaattttggg tgtacaaattggttacattcaaattaaaaacaatatcgattcccaaacttccatcttaATGGCTGTAGGTGTAAGGCACTGCA CCATAAGGTTCATGGAACTTGAATCATCATCACTAATGAAATGTTTGCTCTTGTCTTCACCTCTATATAGAAAGCAATCAGTT CACTTCTCCAACTCTTCTACTCAAAGATATAATCAATGTTGTTCATTGTCGATGAATGGATGCCAAGGCGATTCAAGAGCTCC TATTGGAATCGTTGAAACTCGAACTTTGCCTGCAGTTTCTAGCCCTGCATTGGCCATGGAACGTCTCAATTCTGCCATCTCCG ATATGATTAAGTCCGATCCTCCGCCTTACGATTCCGGCATTATTCGCCTTGAGGTGCCAATTGAAGAGCAGATTGAATCACTT GAGTGGCTTCATGCCCAGAACCATCTCCTCCTCCCTCGCTGCTTCTTCTCCGGTCGAAGAGTTGCTTCTGAAATGTGCATCAA TGGAGCTTCTTCTCATTCTAAATTGGTCAGTGTAGCTGGTGTCGGTTCAGCTGTCTTCTTTACTCATTTACGTCCCTTCTCAT TAGACGATTGGCGTGCTATAAGAAGGTTCCTCTCCAAGAAATGTCCACTAATTCGTGCTTATGGGGCAATCCGATTTGATGCA ACAGCCAATATAGCTTCTGAATGGAGTGCTTTTGGCTCATTTTATTTCATGGTTCCTCAGGTTGAGTTTGATGAGCTTGAAGG AAGTTCAATTATTGCTGCAACTATTGCATGGGACAATGCTGCCTCATGGACATACCAGAGGGCAATAGATGCACTTCAGGCCA CAATATGGCAGCTTTCCTCCGTTCTTATAACAGTGCAGAAGAAAAATCCCCATTCGCATATACTTGCCAATACACATGTGCCG GGTAAAGCGTCTTGGGACCATGCGGTTAACCGTGCTTTGCAAATAATAAGCAGAAATGACCCTGTACTGATCAAGGTGGTACT TGCTCGTAGCACCAGAGTTGTGACAGCTGCAGATATTGATCCACTAACATGGCTGGCTTGCTTAAAGGTTGAAGGAGAAAATG CATATCAGTTCTGTTTGCAACCTCCCCATTCGCCGGCATTCATTGGAAACACTCCAGAGCAGCTATTTCATCGGGACCGCCTC AGCATTTGTAGTGAGGCTTTAGCTGGAACACGGGCTAGGGGTGGATCAGAGCTTCTGGATCTTAATATAGAACAGGATTTACT ATCCAGCGCTAAGGACCATAATGAGTTTGCTATAGTACGGGAGTGCATAAGAAGAAGATTGGAGGCTGTGTGTTCAAGCGTTA TAATTGAACCAAAGAAAGCAATAAGAAAATTTACAAGAGTTCAACATCTTTACGCTCGATTGAGGGGGAGACTCCAGGCTGAA GATGATGAGTTTAAGATATTGTCATCCGTGCACCCTACTCCAGCAGTTTGTGGGTATCCTACAGAAGATGCACGGGCTTTTAT TTCAGAAACTGAAATGTTTGACCGAGGAATGTATGCTGGTCCTGTTGGTTGGTTTGGAGGGGAAGAGAGTGAATTTGCGGTTG GAATAAGGTCGGCTTTGGTTGAAAAGGGTCTTGGCGCACTAATTTATGCGGGAACTGGGATAGTGGAAGGAAGTGATTCATCT CTAGAATGGGAAGAGCTAGAGCTAAAGACTTCACAGTTCACCAAATTGATGAAACTTGAGGCACCTCTTTTGACTAGAGGACA AAGTAGGATTATCAATCAGAATCAGAAAGGTTTGTCATGCCTGCCGCATCGTATTTAGtagacatttgtgaaaaggagagggg gggagagagagagagaaaattatactgccatcttttcatattctttgtatgcaaatatcatcaacctgtcatatgcaattttg gggatgcaaaactaatctaatgatagatagctacttatcttggttgagagatt

FIGURE S2.1 Sequence of the 3041bp SlICS mRNA. Coding sequence is indicated in uppercase; 5’and 3’UTR are indicated in lowercase; start codon in bold. Primer sequences used to generate the RNAi construct are underlined.

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moter sequence (35s_F: TTCAAAGCAAGTGGATTGATGTG and 35s_R2: GCTCTTAT- ACTCGAGC GTGTCC). The plasmid was included as a positive control. Three independent lines were obtained. Transformed plants were severely affected in their morphology, as they grew in a ‘bush-like’ structure, evidenced by the production of many

(A) MAS3’ = vector sequence 35S = promoter sequence ICS = target gene sequence GUS = GUS reporter gene Intron = intron from pyruvate orthophosphate dikinase (pdk) gene from Flaveria trinervia to obtain hairpin

GTTTCCTAAAGTGCGTGGCATTTTCTGCTTTGTATTGTTTCTCAATTCTG TAACGTTTGCTTTTCTTATGAATTTTCAAATAAATTATCAGATCTCTCTG CCGACAGTGGTCCCAAAGATGGACCCCCACCCACGAGGAGCATCGTGGAAAAAGAAGACGTTCCAACCACGTC (MAS3’) TTCAAAGCAAGTGGATTGATGTGACATCTCCACTGACGTAAGGGATGACG CACAATCCCACTATCCTTCGCAAGACCCTTCCTCTATATAAGGAAGTTCA TTTCATTTGGAGAGGACACGCTCGAGTATAAGAGCTCTATTTTTACAACA ATTACCAACAACAACAAACAACAAACAACATTACAATTACATTTACAATT ACC (35S) ATGGCCATGTAGGCCGAAGAGAGTGAATTTGCGGTTGGAATAAGGTCGGCTTTGGTTGAAAAGGGTCTTGGCGCA CTAATTTATGCGGGAACTGGGATAGTGGAAGGAAGTGATTCATCTCTAGAATGGGAAGAGCTAGAGCTAAAGACT TCACAGTTCACCAAATTGATGAAACTTGAGGCACCTCTTTTGACTAGAGGACAAAGTAGGATTATCAATCAGAAT CAGAAAGGTTTGTCATGCCTGCCGCATCGTATTTAGTAGACATTTGTGAAAAGGAGAGGGGGGGAGAGAGAGAGA GAAAATTATACTGCCATCTTTTCATATTCTTTGTATGCAAATATCATCAACCTGTCATATGCAATTTGGCCTCTC TGGCCAT(ICS) GGGCCAACTCCTACCGTACCTCGCATTACCCTTACGCTGA AGAGATGCTCGACTGGGCAGATGAACATGGCATCGTGGTGATTGATGAAA CTGCTGCTGTCGGCTTTAACCTCTCTTTAGGCATTGGTTTCGAAGCGGGC AACAAGCCGAAAGAACTGTACAGCGAAGAGGCAGTCAACGGGGAAACTCAGCAAGCGCACTTACAGGCGATTAAA GAGCTGATAGCGCGTGACAAAAACCACCCAAGCGTGGTGATGTGGAGTATTGCCAACGAACCGGATACCCGTCCG CAAGGTGCACGGGAATATTTCGCGCCACTGGCGGAAGCAACGCGTAAACTCGAC(GUS) GGCCACTCGTGTCCCTTGTGAAAGAAATAATTATGTTCTATCAATGATTTAACATAGACAAGATCAATGATGTTA CTTAGTATAATCATGATAAACTAATTGTTTAATTGTGAAAAAATCCATTTATAAATTTATTGCTCCATATTATTA TTTATATGTAAAAAGTATGACATTGATAGTTAATACCATATAAAATTGATATATTTTGCACTTTTATTATATTAT CTTTATTTATCGAACGTGTATATGATTACTGATTCTATTAGTTTGATACCATTCTGGAACTTCATTTCTGTCTGG TTTTATTGAA (part of the intron)

(B) ttcaaagcaagtggattgatgtgacatctccactgacgtaagggatgacgcacaatcccactatccttcgcaaga cccttcctctatataaggaagttcatttcatttggagaggacacgctcgagtataagagctctatttttacaaca attaccaacaacaacaaacaacaaacaacattacaattacatttacaattaccATGGCCATGTAGGCCGAAGAGA GTGAATTTGCGGTTGGAATAAGGTCGGCTTTGGTTGAAAAGGGTCTTGGCGCACTAATTTATGCGGGAACTGGGA TAGTGGAAGGAAGTGATTCATCTCTAGAATGGGAAGAGCTAGAGCTAAAGACTTCACAGTTCACCAAATTGATGA AACTTGAGGCACCTCTTTTGACTAGAGGACAAAGTAGGATTATCAATCAGAATCAGAAAGGTTTGTCATGCCTGC CGCATCGTATTTAGTAGACATTTGTGAAAAGGAGAGGGGGGGAGAGAGAGAGAGAAAATTATACTGCCATCTTTT CATATTCTTTGTATGCAAATATCATCAACCTGTCATATGCAATTTGGCCTCTCTGGCCATgggccaactcctacc gtacctcgcattacccttacgctgaagagatgctcgactgggcagatgaacatggcatcgtggtgattgatgaaa ctgctgctgtcggctttaacctctctttaggcattggtttcgaagcgggcaacaagccgaaagaactgtacagcg aagaggcagtcaacggggaaactcagcaagcgcacttacaggcgattaaagagctgatagcgcgtgacaaaaacc acccaagcgtggtgatgtggagtattgccaacgaaccggatacccgtccgcaaggtgcacgggaatatttcgcgc cactggcggaagcaacgcgtaaactcgacGGCCACTCGTGTCCCTTGTGAAAGAAATAATTATGTTCTATCAATG ATTTAACATAGACAAGATCAATGATGTTACTTAGTATAATCATGATAAACTAATTGTTTAATTGTGAAAAAATCC ATTTATAAATTTATTGCTCCATATTATTATTTATATGTAAAAAGTATGACATTGATAGTTAATACCATATAAAAT TGATATATTTTGCACTTTTATTATATTATCTTTATTTATCGAACGTGTATATGATTACTGATTCTATTAGTTTGA TACCATTCTGGAACTTCATTTCTGTCTGGTTTTATTGAA…gtcgagtttacgcgttgcttccgccagtggcgcga aatattcccgtgcaccttgcggacgggtatccggttcgttggcaatactccacatcaccacgcttgggtggtttt tgtcacgcgctatcagctctttaatcgcctgtaagtgcgcttgctgagtttccccgttgactgcctcttcgctgt acagttctttcggcttgttgcccgcttcgaaaccaatgcctaaagagaggttaaagccgacagcagcagtttcat caatcaccacgatgccatgttcatctgcccagtcgagcatctcttcagcgtaagggtaatgcgaggtacggtagg agttggcccATGGCCAGAGAGGCCAAATTGCATATGACAGGTTGATGATATTTGCATACAAAGAATATGAAAAGA TGGCAGTATAATTTTCTCTCTCTCTCTCCCCCCCTCTCCTTTTCACAAATGTCTACTAAATACGATGCGGCAGGC ATGACAAACCTTTCTGATTCTGATTGATAATCCTACTTTGTCCTCTAGTCAAAAGAGGTGCCTCAAGTTTCATCA ATTTGGTGAACTGTGAAGTCTTTAGCTCTAGCTCTTCCCATTCTAGAGATGAATCACTTCCTTCCACTATCCCAG TTCCCGCATAAATTAGTGCGCCAAGACCCTTTTCAACCAAAGCCGACCTTATTCCAACCGCAAATTCACTCTCTT CGGCCTACATGGCCAT

FIGURE S2.2 Sequence of the 35S::irGUS-irICS construct. (A) Different parts of the sequence are indicated by different colours (35S promoter=green; ICS fragment=red; GUS fragment=blue; intron=black) Primers used for sequencing are underlined. (B) the same sequence but with the inverted repeat (as expressed in the plant).

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side-branches and stunted growth (FIGURE S2.3). One year after transfer to the soil, the plants still had not produced a single flower. Hence, we started to spray them with the SA-analogue BTH (Syngenta, Basel, Switzerland) in a concentration of 0.2 g/l to rescue possible defects caused by SA-deficiency. Plants were sprayed every 2 days. This approach seemed successful, because the plants started to produce flow- ers and fruits, 8 weeks after the BTH treatment was started. Unfortunately, however, the fruits harvested did not contain any seeds (FIGURE S2.3). In a second rescue attempt, plants were grafted on rootstocks of WT plants (cv. CM) but unfortunately

FIGURE S2.3 ICS plants are severely affected in their growth. Nine-week-old representative plants, showing that, compared to untransformed plants (A), irICS plants display stunted growth (B) and produce many side-branches (C). Spraying with BTH induced flowering in irICS plants, but the fruits did not contain seeds (D).

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also this approach did not result in the production of seed-containing tomatoes. To test whether the silencing of ICS had an effect on SA levels, phytohormones were measured in the (un-induced) T0 plants. Phytohormone measurements were performed as described in the Material and methods section. Most transformed plants displayed 2-fold reduced SA-levels compared to the untransformed control plant. In contrast, JA-Ile levels were higher in transformed plants compared to the untransformed control plant, which might be due to the JA/SA-antagonism (FIGURE S2.4).

FIGURE S2.4 Phytohormone levels in irICS plants. Amounts of endogenous JA (A), JA-Ile (B) and SA (C) in a untransformed (Untransf.) as well as in several transformed plants that were either cut or grafted.

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References Ament, K., Krasikov, V., Allmann, S., Rep, M., Takken, F.L.W. & Schuurink, R.C. (2010) Methyl salicylate production in tomato affects biotic interactions. Plant J. 62, 124-134. Cortina, C. & Culiáñez-Macià, F.A. (2004) Tomato transformation and transgenic plant production. Plant Cell. Tiss. Org. 76, 269-275. Hoekema, A., Hirsch, P.R., Hooykaas, P.J.J. & Schilperoort, R.A. (1983) A binary plant vector strategy based on separation of vir- and T-region of the Agrobacterium tumefaciens Ti-plasmid. Nature, 303, 179-180. Lukasik-Shreepaathy, E., Vossen, J.H., Tameling, W.I.L., Vroomen, M.J. De, Cornelissen, B.J.C. & Takken, F.L.W. (2012) Protein-protein interactions as a proxy to monitor conformational changes and activation states of the tomato resistance protein I-2. J. Exp. Bot. 63, 3047-3060. Uppalapati, S.R., Ishiga, Y., Wangdi, T., Kunkel, B.N., Anand, A., Mysore, K.S. & Bender, C.L. (2007) The phytotoxin coronatine contributes to pathogen fitness and is required for suppression of salicylic acid accumulation in tomato inoculated with Pseudomonas syringae pv. tomato DC3000. Mol. Plant Microbe Interact. 20, 955-965. Van Wees, S.C.M. & Glazebrook, J. (2003) Loss of non-host resistance of Arabidopsis nahG to Pseudomonas syringae pv. phaseolicola is due to degradation products of salicylic acid. Plant J. 33, 733-742. Wroblewski, T., Piskurewicz, U., Tomczak, A., Ochoa, O. & Michelmore, R.W. (2007) Silencing of the major family of NBS-LRR-encoding genes in lettuce results in the loss of multiple resistance specificities. Plant J. 51, 803-818.

65 JorisGlas-chap2_Gerben-chap2.qxd 26/05/2014 00:18 Page 66 JorisGlas-chap3_Gerben-chap2.qxd 26/05/2014 00:22 Page 67 3 Russet mite-induced plant defenses increase tomato resistance to a phytopathogen but facilitate a competing herbivore

J.J. Glas, M. Stoops, C.A. Villarroel, A. Ooms, S. Simoni, M.W. Sabelis & M.R. Kant

Plant parasites have to cope with their host’s defences and with each other, as competitors. Competition between individuals may be direct, but can also occur indirectly via induced changes in plant quality. Some parasites are able to manipulate their host plant to their own benefit but how this affects parasite natural communities remains a poorly understood question. Here, we show that plant parasites interact via the plant defenses they induce and that these indirect interactions can determine the performance of individual community members. As described in CHAPTER 2, we found that tomato russet mites (Aculops lycopersici) suppress jasmonic acid (JA)-related defenses, whereas they induce those that depend on salicylic acid (SA), and this can augment SA-defenses induced by competing herbivores, resulting in suppression of the JA-response via JA/SA-cross-talk. In this chapter, we show that absence of JA-defenses increases russet mite population growth, and thus, that by suppressing the JA pathway russet mites manipulate the plant defensive system. However, this metabolic hijack affects also the reproductive performance of other community members: while inhibiting the SA-sensitive bacterial leaf pathogen Pseudomonas syringae, it facilitates the spider mite Tetranychus urticae, a JA-sensitive food competitor of russet mites in the field. Furthermore, we found that while facilitating spider mites, russet mites experience reduced population growth. Thus, we conclude that whether or not host-defense manipulation improves a parasite’s fitness depends on interactions with other parasites via the sum of community-induced defenses, implicating bidirectional cau- sation of community structure of parasites sharing a plant.

n nature as well as agriculture, plants suffer from a diverse community of parasites, Iinvolving herbivores as well as pathogens. Upon attack by parasites, plants under- go rapid physiological changes (Howe & Jander, 2008) which take place not only at the site of attack, but also in the undamaged parts of attacked leaves and in distal undamaged (systemic) leaves, thereby increasing resistance plant-wide (Wu & Baldwin, 2010). Two hormone signaling pathways play a major role in the regulation of these defense responses: the JA pathway, which is induced by herbivores and necrotrophic pathogens (Howe & Jander, 2008), and the SA pathway, which orches- trates defenses against biotrophic pathogens (Glazebrook, 2005) and some phloem-

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feeding herbivores (Kaloshian & Walling, 2005). Herbivores and pathogen-induced plant responses can alter the plant in such a way that not only the initial attacker but also subsequent attackers are affected (e.g., De Vos et al. 2006; Stout et al., 2006; Long et al., 2007; Spoel et al., 2007; Thaler et al., 2010; Tack & Dicke, 2013). This implies that, apart from directly competing for the same resource, also referred to as ‘exploitation competition’, herbivores may also indirectly compete with each other via induced changes in the quality of the plant, i.e., via ‘plant-mediated indirect interactions’ (Ohgushi, 2005). Here, we study how plant attackers influence each other’s performance by inducing and suppressing defense responses in a shared host plant. Our model system includes the tomato russet mite (Aculops lycopersici), a tiny eriophyoid mite species and specialist pest species on tomato (Solanum lycopersicum) (Gerson & Weintraub, 2012), and two of its natural competitors, i.e., the two-spotted spider mite (Tetranychus urticae) and the plant pathogenic bacterium Pseudomonas syringae pv. tomato DC3000 (Pst DC3000). All three species are pests of tomato in countries where this crop is grown (FIGURE 3.1; Jones et al., 1991). We have observed that on field-grown tomato plants in Italy russet mite infestations were often followed by T.

FIGURE 3.1 Pest distribution data for tomato russet mites (Aculops lycopersici), spider mites (Tetranychus urticae) and the bacterial pathogen Pseudomonas syringae pv. tomato (source: www.plantwise.org, accessed on 22/01/2013).

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urticae infestations on the same plants. This prompted us to hypothesize that russet mite infestations may alter the interactions between spider mites and their host, thereby influencing the reproductive performance of spider mites. Hence, we quantified defense responses in tomato plants infested with spider mites, russet mites, or the combination of spider mites and russet mites and found that russet mites suppressed spider mite-induced JA-dependent defense responses (CHAPTER 2). Here, we ask the question whether russet mite-induced responses in tomato change the ecological interactions occurring within their natural communities. First, we test the hypothesis that russet mites, by suppressing JA-defenses, benefit spider mites. Second, we assess the impact of russet mite-induced SA-defenses on Pst growth. Third, we investigate the role of JA-defenses in natural resistance of tomato against russet mites by measuring russet mite population growth on the def-1 mutant, which is defective in JA-dependent defense signaling (Howe et al., 1996). Finally, we investigate if, and if yes how, these host plant-mediated changes in the russet mite’s community feed back onto the russet mite itself.

MATERIAL AND METHODS Plants, mites and bacteria Tomato seeds (Solanum lycopersicum cv. Castlemart (CM), defenseless-1 (def-1), and a transgenic line 35S::prosystemin (prosys+), both in the genetic background of CM) and S. lycopersicum cv. Moneymaker (MM) as well as the transgenic line nahG, in the genetic background MM were germinated in soil and grown in a greenhouse compartment at a temperature of 25ºC and a 15/9 h light/dark regime. One week prior to each experiment, plants were transferred to a climate room with day/night temperatures of 27ºC/25ºC, a 16/8 h light/dark regime and 60% RH. All experiments were performed on 21-day-old plants. The def-1 plants are deficient in wound- and systemin-induced JA accumulation and in the expression of downstream defense genes (Howe et al., 1996). Prosys+ plants overexpress the prosystemin gene, resulting in a constitutively activated JA-signaling pathway (Chen et al., 2006). The nahG plants are transformed with the bacterial gene nahG encoding salicylate hydroxylase which removes endogenous SA by converting it into catechol (Brading et al., 2000). Both the prosys+ and the nahG gene are under the control of the constitutively expressed CaMV 35S promoter. Experiments with wild-type (WT) and mutant/transgenic lines were always carried out in parallel. Tomato russet mites (Aculops lycopersici, also referred to as russet mites or abbreviated as RM) were obtained from Koppert Biological Systems (Berkel en Rodenrijs, The Netherlands), who, in turn, had obtained them in the summer of 2008 from naturally infested plants in a greenhouse in the Westland area (The Netherlands), and was since reared in insect cages (BugDorm-44590DH, Bug Dorm

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Store, MegaView Science, Taichung, Taiwan) in a climate room on tomato plants (cv. CM) that were between 3 and 5 weeks old. Two-spotted spider mites (T. urticae, also called spider mites or abbreviated as SM) were originally obtained in 2001 from a single European spindle tree (Euonymus europaeus), in the dunes near Santpoort (The Netherlands) (GPS coordinates: 52 26.503 N, 4 36.315 E). The strain we used has been described as a JA-inducing mite genotype and as susceptible to these defenses (Kant et al., 2008). Since its collection from the field, the strain has been propagated on detached bean (Phaseolus vulgaris) (cv. 746 Speedy) leaves that were placed with the abaxial surface on wet cotton wool and maintained in a climate room (temperature of 25ºC, a 16/8 h light/dark regime and 60% RH). Pst DC3000 bacteria were grown on King’s Broth (KB) medium (King et al., 1954) agar plates, containing rifampicin (50 μg/ml), and grown at 28ºC for 2-3 days. Subsequently, single colonies were picked and bacterial cultures were grown overnight at 28ºC in liquid KB medium with rifampicin (50 μg/ml). Bacterial cells were collected

by centrifugation (3000 rpm for 10 min), resuspended in 10 mM MgSO4 and adjusted to the required optical density (OD) (see sections Pst DC3000 growth assays and Russet mite population growth experiments) before pressure infiltration into the leaflets.

Samplings in tomato fields Tomatoes growing in the field were sampled to determine the co-occurrence of plant- eating mites. Samplings were performed in several areas of Italy that are well-known for their tomato production (FIGURE 3.2). On each location at least two samples were taken, the first one in July and the second one in September. Samplings were done at 93 different sites in total, in the summer of 1997 and 1998. For each sample, 80- 100 leaves (i.e., compound leaves) were randomly collected. Subsequently, these leaves were examined under a stereomicroscope and on each leaflet the presence/absence of spider mites as well as that of russet mites was recorded.

Spider mite reproductive performance assays To obtain RM-infested leaflets before the start of the SM-performance experiments, 21- day-old tomato plants were infested by transferring small (ca. 0.5 cm²) pieces of leaflets with RM to the leaflets of the clean plants. These pieces had been cut from leaflets picked from a well-infested tomato plant and each piece contained ca. 250 mobile stages of RM. In total, three leaflets per plant were infested, i.e., one leaflet of the second true compound leaf (counted from the bottom to the top of the plant), one from the third true compound leaf and the terminal leaflet of the fourth true compound leaf. To prevent mites from dispersing, a thin barrier of lanolin was applied on the petioles of leaflets that were chosen for infestation. Uninfested control plants received lanolin, but no mites.

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FIGURE 3.2 Map of Italy with the regions indicated where russet mites and spider mites were found together. The colour of the symbols indicates the order in which infestations occurred.

Subsequently, four young adult female SM were placed on the adaxial surface of the RM-infested leaflets and on leaflets of the same age and position of non-infested control plants, using a soft bristle paintbrush. At this point in time, the plants had been infested with RM for 7 days. After 4 days (i.e., 11 days after the start of the experiment), infested leaflets were detached and SM adults and their eggs were

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counted using a stereomicroscope. The experiment was performed on WT, def-1 and prosys+ plants. The results presented in FIGURE 3.3 represent the mean number of eggs per mite per day of 24 leaflets that were obtained from 8 plants. The experiment was carried out twice, at different time-points, with similar results. In order to obtain SM of the same age, egg waves were generated in a climate room (temperature of 25ºC, a 16/8 h light/dark regime and 60% RH), as previously described (Kant et al., 2004). In short, 20-30 random adult female spider mites were selected from a rearing colony and allowed to produce eggs for a period of 48 hours on detached bean leaflets on wet cotton wool. After this period, the adults were removed but the eggs were maintained. After 14 days, the 2±2 days young adult females were collected and these were used for the oviposition assays.

Pst DC3000 growth assays At the start of the assays, 21-day-old plants were infested with RM as described in the section Spider mite reproductive performance assays). Experiments were performed on WT (cv. MM) and SA-deficient nahG plants. After 7 days of infestation with RM, the left halves (bordering the midrib) of RM-infested leaflets and similar leaflets from non-infest-

ed control plants were pressure infiltrated with Pst DC3000 (OD600=0.001) in 10 mM MgSO4 using blunt 1-ml syringes (BD Plastipak, Franklin Lakes, USA). Three days after infection with Pst, leaflets were detached and two 1 cm2 circular leaf discs were

punched out from the infiltrated leaflet halves and ground in 500 μl 10 mM MgSO4. Serial dilutions were prepared by taking 20 μl of the leaf disc solution and diluting it in

180 μl 10 mM MgSO4. Twenty μl of each serial dilution was plated on KB medium + Rifampicin (50 μg/ml) plates. The number of Colony Forming Units (CFU) was counted 2 days after incubation at room temperature. Leaflets from the third and fourth compound leaf (counted from the bottom of the plant) were infected. Bacterial growth in both leaves was very similar. In FIGURE 3.5, data for leaf 3 are presented. In total, 7 plants were infected per genotype and per treatment and the experiment was repeated a second time with a similar result.

Russet mite population growth experiments For the RM population growth experiments, 21-day-old tomato plants were infested by transferring 20 RM to each of three leaflets per plant. Thus, in total plants were infested with 60 RM each. To prevent mites from dispersing we applied a thin barrier of lanolin on the petioles of leaflets that were chosen for infestation. Uninfested control plants received lanolin, but no mites. We always picked the same leaflets for infestation, i.e., one leaflet of the second true compound leaf (counted from the bottom to the top of the plant), one from the third true compound leaf and the terminal leaflet of the fourth true compound leaf. Leaflets with the same position were used

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for the gene expression and phytohormone measurements. To assess RM performance, infested leaflets were detached and mites (all stages) were washed off by rins- ing the leaflets one by one for 20 s in 25 ml 100% ethanol. Infested leaflets that came from the same plant were washed in the same solution. RM were counted by running 2 ml of the leaf washes through a particle counting system (PAMAS SVSS, PAMAS, Rutesheim, Germany). Leaf washes were counted 20 s after mixing them, to avoid that air bubbles enter the system. Adult RM are around 120-150 μm in size while their eggs are around 20 μm. Therefore, the number of particles measured in the range of 50-200 μm was used to quantify the number of adult mites. The number of mites per plant was calculated by multiplying the mean number of particles per ml with the total volume of 25 ml. This counting method was validated by means of a dose- response experiment. In this experiment, we infested leaflets on intact plants with 2, 4, 8, 16, 32 and 64 mites and after 14 days the mites were washed off, as described earlier. The numbers counted implied exponential population growth, corresponding to the starting conditions (data not shown). Only low numbers of particles (33±8) were counted in samples that came from clean uninfested leaflets. For the RM-SM co-infestation experiment (FIGURE 3.6), plants were infested by transferring 20 RM to each of the three leaflets per plant. After 7 days of RM infestation, half of the plants were co-infested with five adult SM on the RM-infested leaflets. Thus, dual-infested plants were infested with in total 15 SM per plant. The population growth of RM was assessed after 14 days of infestation with RM (and hence after 7 days of infestation with SM) by counting the number of RM as described above. The values presented in FIGURE 3.6 represent the mean of 13-15 plants, obtained in two independent experiments. For the RM-Pst co-infestation experiment (FIGURE 3.7), plants were infested by transferring 20 RM to each of three leaflets per plant. After 7 days of RM infestation, three

leaflets of half of the RM-infested plants were infiltrated with Pst in 10 mM MgSO4 and three leaflets of the other half of the RM-infested plants were infiltrated with mock 10

mM MgSO4. The same three leaflets were chosen for infiltration from each plant. Since older leaflets are more susceptible to Pst compared to the younger leaflets (personal observation), the leaflets from the third and fourth compound leaf were infiltrated with a

bacterial suspension which had an OD600 of 0.0001, whereas the oldest leaflet (i.e., the leaflet on the second fully expanded leaf) was infiltrated with a lower OD600 of 0.00005. Of each leaflet, approximately ¼ of the leaf area was infiltrated with bacteria. The population growth of RM was assessed after 14 days of infestation with RM (and hence after 7 days of infestation with Pst) by counting the number of RM as described above. The values presented in FIGURE 3.7 represent the mean of 15 plants, obtained from two independent experiments. Symptoms of Pst infection were visible at the time of sampling, with sometimes (minor) parts of the leaflet being senesced and/or necrotic.

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For assessing RM performance on WT and def-1 plants (FIGURE 3.8), plants were infested by transferring 20 RM to each of the three leaflets per plant. RM population growth was assessed after 8, 12 and 16 days by counting the number of RM as described above. The values presented in FIGURE 3.8 represent the means of 5-10 plants per time-point, obtained from two independent experiments. In a third replicate of the experiment, using 10 plants per treatment, we sampled only at 16 days after infestation. This experiment gave a similar result (data not shown).

Statistical analysis Spider mite oviposition data (FIGURES 3.3 and 3.4) were analyzed with ANOVA using ‘Treatment’ as fixed factor and including ‘Plant replicate’ as random factor. Means of each group were compared using Fisher’s LSD post hoc test and homogeneity of variances was assessed by means of the Levene’s test. Pst performance data were analyzed with the Student t-test (FIGURE 3.5). Russet mite population growth data were log-transformed before statistical analysis (FIGURES 3.6, 3.7 and 3.8). Values presented in the graphs represent untransformed data. Student t-tests were performed in Excel (Microsoft, Redmond, WA, USA) and ANOVA followed by Fisher’s LSD tests in SPSS 20.0 (SPSS, Chicago, IL, USA).

RESULTS Russet mite infestations precede spider mite outbreaks in the field Tomatoes growing in the field and in the greenhouse were sampled to determine the occurrence of plant-eating mites. Spider mites or russet mites were found at 77 sampling sites and in 33 cases the two species were found together on the same plant. Because we sampled repeatedly, we noticed that in 21 of those cases russet mite infestations had preceded spider mite infestations (X2=9.85, d.f.=1, P=0.0017) (TABLE 3.1, FIGURE 3.2), whereas in only 5 of the cases spider mites were observed first. In seven cases the order of infestation was unknown (TABLE 3.1).

Russet mites increase reproductive performance of spider mites on WT tomato plants To test the hypothesis that spider mites benefit from russet mite infestations, we co- infested plants with russet and spider mites and measured spider mite reproductive performance by counting the number of spider mite eggs produced on plants that had been pre-infested with russet mites and plants that had been infested with spider mites only. We found that spider mites produced significantly more eggs on def- 1 than on WT plants (P=0.002; FIGURE 3.3), confirming that they are susceptible to JA- dependent defenses (Li et al., 2002; Kant et al., 2008). Strikingly, on WT plants that had been pre-infested with russet mites, spider mites produced significantly more

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TABLE 3.1 Russet mite infestations precede spider mite infestations significantly more often than the other way round. Location Russet mites Spider mites Order of infestation observed first observed first unknown 1 San Bonico, PC * 2 Torre Mar., Montalto di Castro, VT * 3 Valentini, S. Giorgio Piac., PC * 4 Rurimoni, Montalto di Castro, VT * 5 Saliceto di Cadeo, PC * 6 Veneziani, S. Giorgio Piac., PC * 7 Saliceto di Cadeo, PC * 8 Monticello, Caorso, PC * 9 Bondiocca di Caorso, PC * 10 Casalfoschino di Sissa, PR * 11 Trecasali, PR * 12 Bianconese di Fontevivo, PR * 13 Prati B. Calabrina, Cesena, FC * 14 Capannaguzzo, Cesena, FC * 15 Milano, Montalto di Castro, VT * 16 Arsia, Cesa, AR * 17 Meini, Poggetti, GR * 18 Arsia, Rispescia, GR * 19 Dragoni, Poggio al Pino, GR * 20 Marioni, Poggio al Pino, GR * 21 Bondiocca di Caorso, PC * 22 Campo 4, Caorso, PC * 23 Oliva, Aversana, Battipaglia, SA * 24 Galassi R, Cannara, PG * 25 Dragoni, Sterpeto, GR * 26 Arsia, Rispescia, GR * 27 Meini, Vareop., GR * 28 Vallepega, Comacchio, FE * 29 Dragoni, Favacchio, GR * 30 Gianandrea, Rosignano, LI * 31 Di Francesco, La California, Bibbona, LI * 32 Frolani, Bolgheri, LI * 33 Di Nola, Lucera, FG * List of samples documenting the (co-)occurrence of russet mites and spider mites on field-grown tomatoes in Italy. Spider mites or russet mites were found on tomato on 77 field sites. In the 33 cases shown in this table they co- occurred on the same host plant. In seven cases the order of infestation was unknown. In 21 out of the remaining 26 field observations, russet mite infestations preceded spider mite infestations (X2=9.85, d.f.=1, P=0.0017). Locations are indicated by the name of the farm (if applicable), followed by the name of the town and region (SA=Salerno, PG=Perugia, FG=Foggia, LI=Livorno, GR=Grosseto, AR=Arezzo, VT=Viterbo, FE=Ferrara, PC=Piacenza, PR=Parma, FC=Forlì-Cesena).

eggs as compared to plants infested with spider mites only (P=0.027). In contrast, russet mites did not affect spider mite oviposition rate on def-1 plants (‘SM’ on def- 1 vs. ‘Both mites’ on def-1; P=0.21). Furthermore, the number of eggs produced by spider mites on co-infested WT plants was similar to the number of eggs produced

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FIGURE 3.3 Spider mites (SM) benefit from suppression of JA-defenses by russet mites (RM) in wild-type (WT) tomato plants to the same extent as they benefit from the def-1 mutation. Average (+SEM) number of eggs produced by SM on WT (cv. CM) and JA-deficient mutant def-1 plants that were pre-infested with RM (‘Both mites’) or not (‘SM’). Values in the bars indicate mean oviposition rates and different letters above bars denote significant differences (ANOVA followed by Fisher’s LSD test: P<0.05). Three leaflets per plant were analyzed. In total, eight plants per genotype and per treatment were analyzed.

on def-1 plants infested with spider mites only (P=0.28). Finally, the number of eggs produced on co-infested def-1 plants was marginally significantly different from the number of eggs produced on WT plants infested with spider mites only (‘SM’ on WT vs. ‘Both mites’ on def-1; P=0.053) and not different from the number of eggs produced on WT plants infested with both mite species (‘Both mites’ on WT vs. ‘Both mites’ on def-1; P=0.83).

Spider mite performance is not affected by russet mite feeding on prosys+ plants Subsequently, we performed the same experiment as described in b) but this time using prosys+ plants, which display constitutively activated JA-defenses (Chen et al., 2006; Kandoth et al., 2007). As in the previous experiment, spider mites produced significantly more eggs on WT plants that had been previously infested with russet mites than on clean plants (P=0.011; FIGURE 3.4). In contrast, the presence of russet mites did not affect the number of eggs produced by spider mites on prosys+ plants (P=0.48). Spider mites produced significantly fewer eggs on prosys+ plants compared to WT plants (‘SM’ on WT vs. ‘SM’ on prosys+; P=0.025) confirming that they suffer from the strong JA-defense responses in these plants. Also, the number of eggs pro-

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FIGURE 3.4 Spider mite (SM) performance is not affected by the presence of RM (Both mites) on transgenic 35S::prosystemin tomatoes which have a constitutively activated JA-response. Average (+SEM) number of eggs produced by SM on wild-type (cv. CM) and transgenic 35S::prosystemin plants (prosys+) that were pre- infested with RM (‘Both mites’) or not (‘SM’). Values in the bars represent means and different letters above bars indicate significant differences in SM oviposition rate (ANOVA followed by Fisher’s LSD test: P<0.05). Three leaflets per plant were analyzed. In total, 10 plants per genotype and per treatment were analyzed.

duced on co-infested prosys+ plants was significantly lower compared to the number of eggs produced on WT plants infested with spider mites only (P=0.006) or with the two species simultaneously (P<0.001).

Russet mite-induced SA inhibits growth of Pst DC3000 in tomato leaflets Russet mites induce a significant accumulation of SA in tomato leaflets (FIGURE 2.5C). To investigate the consequence of russet mite-induced SA for growth of the bacterial pathogen Pst DC3000, we infiltrated uninfested control and russet mite-infested leaflets with Pst and determined growth of the bacterium 3 days after the start of the infection. In leaflets that had been pre-infested with russet mites, bacterial growth was significantly reduced compared to uninfested control leaflets (P<0.001). In contrast, on nahG plants the presence of russet mites did not have an effect on Pst bacterial growth (P=0.15) (FIGURE 3.5). Furthermore, bacterial growth was significantly higher on nahG as compared to WT plants (P<0.001; FIGURE 3.5), although in a second replicate of the experiment we did not observe a significant difference in bacterial growth between WT and nahG plants.

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FIGURE 3.5 Russet mite-induced SA inhibits growth of Pst DC3000 on tomato. Pst population growth, quantified as the mean (+SEM) number of colony forming units (CFU/cm2), in wild-type (WT) (cv. MM) and nahG plants that were either without RM (‘Pst’) or had been pre-infested with RM (‘Pst + RM’) for 7 days. In total, seven plants were used per genotype and per treatment. The asterisks indicate a statistically significant difference (Student t- test: P<0.001).

Spider mites inhibit population growth of russet mites Spider mites display an increased reproductive performance on tomato WT leaflets previously infested with russet mites (FIGURE 3.3). To determine whether increased spider mite performance would have an effect on russet mite performance, we co- infested russet mite-infested plants with spider mites and measured russet mite population growth 14 days after infesting them with russet mites. Introducing spider mites on russet mite-infested WT leaflets had a significantly negative effect on russet mite population size (Student t-test; P=0.033; FIGURE 3.6). The same effect was found on def-1 plants, where it turned out to be even more pronounced (Student t- test; P=0.004; FIGURE 3.6). The same trend was found in a pilot experiment, in which we sampled leaflets 12 days after infesting them with russet mites (5 days after infesting with spider mites) (data not shown).

Pst infections do not interfere with russet mite population growth We found that russet mite feeding strongly inhibited growth of Pst on WT tomatoes. The fact that this effect was absent on SA-deficient nahG plants (FIGURE 3.5) shows that the negative effect on Pst is due to SA-defenses induced by russet mites. To determine whether reduced bacterial performance would affect russet mite perform-

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FIGURE 3.6 Spider mites inhibit russet mite (RM) population growth. Shown is the mean (+SEM) RM population size (number of mites/plant) on wild-type (WT) (cv. CM) and def-1 plants infested with RM alone (‘RM’) or co- infested with SM (‘RM+SM’) 14 days after infestation with RM. Plants had been infested with RM for 7 days when SM was introduced. Values represent the mean of 13-15 plants. Asterisks represent significant differences as determined by Student t-test (*, P<0.05; **, P<0.01).

ance, we co-infiltrated russet mite-infested WT plants with Pst and measured russet mite population growth 14 days after infesting them with russet mites. Since on nahG plants russet mite infestations did not interfere with Pst growth (FIGURE 3.5), the same procedure was carried out on nahG plants as a control treatment. The results showed that russet mite performance was not significantly different between WT and nahG plants, suggesting that russet mites do not suffer from SA-mediated defenses. Second, it appeared that Pst infections did not change russet mite population growth, neither on WT nor on nahG plants (ANOVA: P=0.83; FIGURE 3.7). The same result was found in a pilot experiment, in which leaflets were sampled 12 days after infesting them with russet mites (and 5 days after infiltrating them with Pst) (data not shown).

Russet mites display a higher growth rate on def-1 plants To assess if defense suppression is costly for russet mites, we measured russet mite population growth rates on WT and mutant def-1 plants at different time-points after infestation. Def-1 plants are deficient in the induced expression of proteinase inhibitors (Ament et al., 2004) and therefore highly vulnerable to spider mite attack (Li et al., 2002). At day 8 and 12 after infestation, russet mite population sizes were not

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FIGURE 3.7 Pst DC3000 infections do not interfere with russet mite (RM) population growth. Shown is the mean (+SEM) RM population size (number of mites/plant) on wild-type (WT) and nahG plants infested with RM alone (‘RM’) or co-infected with Pst (‘RM + Pst’) 14 days after infestation with RM. Plants were infiltrated with Pst 7 days after infestation with RM. Values represent the mean of 15 plants. Letters above bars indicate results according to ANOVA (P=0.83).

significantly different between WT and mutant plants (Student t-test P=0.27 and P=0.31, respectively; FIGURE 3.8). However, at day 16 after infestation, the mean population size of russet mites was significantly higher on def-1 mutant plants as compared to WT plants (P=0.036).

DISCUSSION By making use of tomato mutants in the JA- and SA-pathway, we have investigated the consequences of russet mite-induced defenses for the interactions with two naturally co-occurring species, i.e., the two-spotted spider mite and the bacterial phytopathogen Pst DC3000. Russet mites often co-occur together with spider mites, and, strikingly, infestations of the latter often ‘follow’ the first (TABLE 3.1; cf. also Castagnoli et al., 1998). To explain this observation, we hypothesized that russet mites change the interaction between spider mites and their tomato host, in such a way that spider mites benefit. We found that the oviposition rate of spider mites feeding from WT plants that had been pre- infested with russet mites was increased by ca. 30% as compared to the same rate on clean WT plants (FIGURES 3.3 and 3.4). Furthermore, we found that spider mites produced significantly more eggs on def-1 compared to WT plants, whereas oviposition

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FIGURE 3.8 Suppression is costly because the population of russet mites (RM) grows faster on the JA-deficient mutant def-1 than it does on wild-type (WT) plants. Values represent the mean (±SEM) number of RM per plant, obtained from 5-10 plants in two independent experiments. The asterisk indicates a significant difference after 16 days (Student t-test on log transformed data: P=0.036).

rates on transgenic prosys+ plants were reduced. This confirms that the spider mite strain we used is sensitive to JA-defenses (Kant et al., 2008). Notably, the positive effect of the def-1 mutation on spider mite oviposition was similar to that of russet mite infestation (FIGURE 3.4), suggesting that russet mites, by suppressing JA-responses, ‘change’ WT plants in such a way that they are experienced by spider mites as if it were def-1 plants. On prosys+ plants, russet mite-infestation did not affect spider mite oviposition, which, in theory, could be due to (1) reduced performance of russet mites on prosys+, or (2) the inability of russet mites to suppress JA-defenses in prosys+ plants. The first explanation is not likely, since in preliminary experiments we did not find that russet mite performance was lower on prosys+ plants compared to WT plants. The second hypothesis could indeed explain why spider mites do not profit from russet mite infestations on prosys+ plants. Yet, given that russet mites seem to suppress JA-defenses downstream of JA-accumulation (CHAPTER 2), this explanation is perhaps not the most likely as they would then theoretically also be able to turn prosys+ plants into a better host for spider mites. To answer this question, a detailed investigation of the defensive status of prosys+ plants infested with spider mites, russet mites and the combination of russet mites and spider mites should be carried out, by measuring phytohormones and defense gene expression. It should be noted that we are not the first to observe a positive effect of feeding by an eriophyoid mite on spider mite fecundity. Westphal et al. (1992) reported that

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Aceria cladophthirus induced a hypersensitive reaction which lead to an increase in spider mite fecundity of about 40% when these fed on (detached) Solanum dulcamara leaves previously infested with the eriophyoid. Also in other systems evidence has been found that different species may positively affect each other via induced plant responses. For instance, Zhang et al. (2009) found that whiteflies suppress JA- defenses in Lima bean and this resulted in a better performance of spider mites on leaf discs that had been taken from whitefly-infested plants than on leaf discs from clean plants. Because the leaf disc assay is less laborious than whole plant assays, we also tried the leaf disc setup described by Zhang et al. (2009). However, on leaf discs we did not find that russet mites facilitate spider mites, in contrast to what we observed in the whole plant assays (data not shown). At present, we do not have a good explanation for why our results obtained in the whole plant assay differ from those obtained in the leaf disc assay. However, in general leaf discs are perhaps not the best to use for these induced defense experiments, since wounding, which occurs during preparation of the leaf discs, typically induces strong JA-dependent responses (Howe & Jander, 2008), which are likely to overrule herbivore-induced responses. Hence, in future work, it is recommended to assess spider mite fecundity using intact leaflets or on intact plants (as for instance in Li et al., 2004). In CHAPTER 2, we showed that russet mites suppress spider mite-induced JA- responses on WT plants, but that this suppression is no longer significant on nahG plants (FIGURE 2.4). To study the potential consequences of this, we also performed an oviposition experiment on nahG plants with the expectation to find no, or even a negative, effect of russet mite pre-infestation on spider mite oviposition on these plants as compared to WT plants. Unexpectedly however, on the WT control plants (cv. MM, the genetic background of nahG) russet mite pre-infestations did not increase spider mite oviposition rates, in contrast to what we observed on the cv. CM. We observed that spider mites produced more eggs on MM than on CM plants (8.7 vs. 7.0 eggs/mite/day, and this difference was marginally significant: P=0.054) (data not shown). Hence, it could be that MM plants are so much reduced in resistance to spider mites that the positive effect of russet mite infestation is no longer relevant. MM plants have a reduced number of type VI trichomes compared to CM plants (ca. 600 vs. ca. 1200 cm-2; Peiffer et al., 2009; Bleeker et al., 2012) and because trichomes are important in resistance of tomato to spider mites (Alba et al., 2009), it is likely that this plays a role in the reduced resistance of MM plants. In any case, since we did not find a difference in spider mite performance on the control WT plants, it is difficult to draw conclusions from this experiment. Subsequently, we tested whether the presence of spider mites affected russet mite growth. We found that the russet mite population growth was significantly reduced on WT plants that had been co-infested with spider mites, and a similar

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effect was found on def-1 plants (FIGURE 3.6), indicating that spider mite decrease russet mite growth. To which extent this effect is due to plant-mediated facilitation of spider mites by russet mites remains to be investigated. This could be done, for instance, by measuring russet mite performance on nahG plants with and without spider mites, as on these plant suppression of spider mite-induced JA-responses is disabled (FIGURE 2.4). In the case that competition of spider mites on russet mites is mediated via an effect on the JA-pathway, russet mite growth is unlikely to be affected by spider mite feeding on nahG, whereas russet mite growth is expected to be negatively affected in the case that the effect is due to direct competition. To assess the consequence of russet mite-mediated SA-induction, additional experiments were performed with Pst DC3000, which is a virulent bacterial strain reported to elicit both JA-defenses as well as SA accumulation in tomato (Stout et al., 1999; Fidantsef et al., 1999; Thaler et al., 2010). Pst activates the JA-pathway via the phytotoxin coronatine (Zhao et al., 2003), which enhances bacterial virulence by attenuating the accumulation of SA (Uppalapati et al., 2007) and downstream SA- dependent defense responses (Zhao et al., 2003; Uppalapati et al., 2007). In line with this, a JA-insensitive mutant (jai1) of tomato is resistant to Pst DC3000 (Zhao et al., 2003). Both JA as well as SA-defense responses have been reported to negatively affect Pst growth (Thaler et al., 1999, 2004). Yet, the role of SA in the interaction between tomato and Pst has not been completely resolved, as Li et al. (2002) did not find convincing evidence that Pst growth was enhanced on tomato nahG plants, aligning with our observation that Pst growth was not always improved on nahG plants. Similarly, O’Donnell et al. (2001) did not find a difference in Xanthomonas campestris pv. vesicatoria growth rates between WT and nahG plants. Thus, tomato appears to differ in this respect from Arabidopsis and tobacco, where nahG consis- tently allows for increased bacterial growth as compared to WT plants (e.g., Delaney et al., 1994; Block et al., 2005). We found that Pst growth rates were greatly reduced in russet mite-infested WT plants compared to uninfested WT plants. In contrast, this negative effect was not observed on nahG plants, which suggests that russet mite-induced SA can inhibit Pst growth rates. Since we did not see an effect of russet mite infestation on nahG plants, we can exclude the possibility that russet mites directly interfere with Pst. We also investigated the reciprocal interaction by investigating the effect of Pst on russet mite population growth and found that the latter was not negatively affected by Pst on WT plants, nor on nahG plants (FIGURE 3.8). This means we can exclude that the effect of russet mite infestation on Pst growth is caused by differences in mite density. Obviously, using a higher bacterial concentration or infecting a greater proportion of the leaflet may have resulted in a different outcome. Yet, since we were primarily interested in plant-mediated indirect effects we deliberately chose to work under these experimental conditions.

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Finally, we tested the hypothesis that there are costs associated with the suppression of JA-defenses by russet mites. This was done by allowing them to build up a population on tomato def-1 in comparison to WT plants. These experiments revealed significant costs since after 16 days of infestation, equivalent to two generation cycles, russet mite populations had grown larger on def-1 than on WT tomatoes (FIGURE 3.8). An alternative explanation for this finding could be that defenses are effectively not suppressed fully down to levels in def-1 by russet mites. Indeed, in WT plants, expression levels of the JA-marker genes were up-regulated slightly above control levels (FIGURE 2.2), suggesting that defense suppression by russet mites is not absolute. Russet mite population growth did not differ between WT and nahG plants indicating that they are not affected by SA-dependent defense responses (FIGURE 3.7). Since russet mites suppress JA-defenses independent from JA/SA-cross-talk (CHAPTER 2), this finding was in line with our expectation. Yet, it would be good to confirm this result in an independent tomato SA-mutant as catechol production in nahG plants may result in inadvertent effects (Van Wees & Glazebrook, 2003). The importance of competition as a factor in shaping insect communities sharing a plant has been strongly debated (reviewed by Denno et al., 1995; Kaplan & Denno, 2007). Initially, following the (at that time) prevailing view in ecology, competition was considered to be a central factor shaping the distribution and diversity of insect herbivore communities. At the most extreme side, Janzen (1973) argued that essential- ly all insects feeding from a common host plant are in competition with one another, since they will have to share resources. Later, this view was severely critized, for instance by Lawton & Strong (1981) who argued that factors like climatic conditions, host plant phenology and the distribution of host plants should be considered much more important when one aims to explain the structure of insect communities. Consequently, in the early 1980s competition for resources among herbivores was considered to be the exception rather than the rule. Yet, from the 1980s onwards, many experimental studies have appeared suggesting that negative, but also positive, interactions may frequently occur between plant parasites, even when their densities are relatively low, when they feed from different plant tissues and at different times, or when belonging to different feeding guilds (e.g., Faeth, 1986; Karban, 1986, 1989; Harrison & Karban, 1986; Stout et al., 2006; Tack & Dicke, 2013). Hence, the result of these studies was that competition regained its central status in insect community ecology. Yet, relatively few studies have investigated the specific roles of the different defense pathways (JA, SA, ET) in these ecological interactions. Studies in which plants were sprayed with JA and/or with the commercial SA analogue benzo(1,2,3)thiadiazole-7-carbothioic acid S-methyl ester (BTH) have shown that artificial induction of defense responses can influence the structure of natural communities of herbivores and pathogens associated with plants in the field (Inbar et al.,

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1998; Thaler et al., 2001). Also, it has been shown that responses induced by one particular species can result in resistance to another (e.g., Long et al., 2007; Poelman et al., 2008; Mouttet et al., 2013) and the order of herbivore arrival on the plant can influence the performance and number of herbivore species occurring later in the season (Van Zandt & Agrawal, 2004; Viswanathan et al., 2005; Erb et al., 2011). In addition to these field studies, laboratory experiments have been performed with model organisms, usually with the aim to reveal the effectiveness of SA- and JA- regulated defenses against attackers with different feeding styles. De Vos et al. (2006), making use of mutants impaired in the JA, ET or SA-pathway, reported that feeding by the JA-inducing caterpillar Pieris rapae did not, as was expected, induce resistance against the necrotrophic fungus Alternaria brassicicola. In contrast, feeding by the caterpillar reduced disease symptoms caused by Pst, but this effect was independent from JA, ET and SA. Thaler et al. (2010) showed that Pst induces JA, SA and activity of proteinase inhibitors in tomato plants, which reduces the growth of Spodoptera exigua caterpillars. Tobacco mosaic virus infections induced SA, but not JA or proteinase inhibitor activity, and this caused induced susceptibility to S. exigua caterpillars but induced resistance to aphids (Myzus persicae). Summarizing, induction of the JA and/or SA pathway may decrease (De Vos et al., 2006; Thaler et al., 2010) or increase (Thaler et al., 2010; Sarmento et al., 2011) the performance of competing organisms on the same host. Only a few studies, on spider mites, whiteflies and aphids, have examined the effects of defense suppression on other species. Kant et al. (2008) showed that JA- defense suppressing spider mites had a small, but significant, positive effect on the performance of ‘inducer’ mites (i.e., mite genotypes that normally induce the JA- and SA-pathway) when sharing the feeding site with ‘suppressor’ mites. Subsequently, Sarmento et al. (2011) showed that T. urticae had an higher oviposition rate on leaf discs on which T. evansi had fed previously, whereas induction of defenses by T. urticae resulted in decreased oviposition by T. evansi. Zhang et al. (2009) showed that JA-defense suppressing whiteflies improved the performance of spider mites on Lima bean and Soler et al. (2012) found that the cabbage aphid (Brevicoryne brassicae) inhibits the production of JA in cabbage (Brassica oleracea) plants, and this cor- related with increased growth and development of caterpillars of the large cabbage white butterfly (Pieris brassicae). Notably, in the whitefly-spider mite, as well as in the aphid-caterpillar example, suppression of JA-defenses was shown to be independent from SA, although the latter was induced by whiteflies. As shown here, russet mites, by inducing SA, may increase the plant’s resistance to bacterial phytopathogens. Yet, at the same time, russet mites increase the reproductive performance of spider mites when these invade their feeding sites, and this, in turn, slows down growth of the russet mites. Hence, the russet mite-induced

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changes that feed back into its community are due to a shift in the relative resistance or susceptibility of the shared host plants and this means our data confirm previous predictions that interactions among different phytophagous organisms can indeed be indirectly mediated by plants (Ohgushi, 2005). The results of our study also show that, unlike in the two above examples, crosstalk between the SA and JA pathway is likely to play a role in the spider mite-russet mite interaction. Furthermore, it shows that the fitness benefits of defense suppression by russet mites depend on the community structure and that such suppression may backfire when competitors take advantage of it as well. Finally, these interactions can be bidirectional since one parasite population may respond to plant defenses induced or suppressed by another and, subsequently, also vice versa. Taken together, we show that parasite-plant-parasite interactions are subject to bidirectional causality in that plant parasites induce plant responses that may positively or negatively impact on them and their competitors implicating that ultimately a parasite’s fitness depends on how they themselves alter the community context. Hence, these findings have major implications for understanding under which conditions induction and suppression of host plant defenses can be adaptive.

Acknowledgements We thank Harold Lemereis, Ludek Tikovsky and Thijs Hendrix for taking care of our tomato plants and Alessandra Scala (Plant Physiology, UvA) for providing P. syringae. Also, we would like to thank all members of the Population Biology group as well as the Plant Physiology group for many useful comments, suggestions and stimulating discussions.

REFERENCES Alba, J.M., Montserrat, M. & Fernández-Muñoz, R. (2009) Resistance to the two-spotted spider mite (Tetranychus urticae) by acylsucroses of wild tomato (Solanum pimpinellifolium) trichomes studied in a recombinant inbred line population. Exp. Appl. Acarol. 47, 35-47. Ament, K., Kant, M.R., Sabelis, M.W., Haring, M.A. & Schuurink, R.C. (2004) Jasmonic acid is a key regulator of spider mite-induced volatile terpenoid and methyl salicylate emission in tomato. Plant Physiol. 135, 2025-2037. Bleeker, P.M., Mirabella, R., Diergaarde, P.J., van Doorn, A., Tissier, A., Kant, M.R., Prins, M., De Vos, M., Haring, M.A. & Schuurink, R.C. (2012) Improved herbivore resistance in cultivated tomato with the sesquiterpene biosynthetic pathway from a wild relative. Proc. Natl. Acad. Sci. USA 109, 20124-20129. Block, A., Schmelz, E., Jones, J.B. & Klee, H.J. (2005) Coronatine and salicylic acid: the battle between Arabidopsis and Pseudomonas for phytohormone control. Mol. Plant Pathol. 6, 79-83. Brading, P.A., Hammond-Kosack, K.E., Parr, A. & Jones, J.D.G. (2000). Salicylic acid is not required for Cf-2 and Cf-9-dependent resistance of tomato to Cladosporium fulvum. Plant J. 23, 305-318. Castagnoli, M., Liguori, M., Nannelli, R. & Simoni, S. (1998) Preliminary survey on mite fauna of tomato in Italy. Redia 81, 45-54 (in Italian with English abstract). Chen, H., Jones, A.D. & Howe, G.A. (2006) Constitutive activation of the jasmonate signaling pathway enhances the production of secondary metabolites in tomato. FEBS Lett. 580, 2540-2546.

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Li, C., Williams, M.M., Loh, Y.T., Lee, G.I. & Howe, G.A. (2002) Resistance of cultivated tomato to cell content-feeding herbivores is regulated by the octadecanoid-signaling pathway. Plant Physiol. 130, 494-503. Li, J., Shan, L., Zhou, J.M. & Tang, X. (2002) Overexpression of Pto induces a salicylate-independent cell death but inhibits necrotic lesions caused by salicylate-deficiency in tomato plants. Mol. Plant Microbe In. 15, 654-661. Li, L., Zhao, Y., McCaig, B.C, Wingerd, B.A., Wang, J., Whalon, M.E., Pichersky, E. & Howe, G.A. (2004) The tomato homolog of CORONATINE-INSENSITIVE1 is required for the maternal control of seed maturation, jasmonate-signaled defense responses, and glandular trichome development. Plant Cell 16, 126-143. Long, J.D., Hamilton, R.S. & Mitchell, J.L. (2007) Asymmetric competition via induced resistance: specialist herbivores indirectly suppress generalist preference and populations. Ecol. 88, 1232-1240. Mouttet, R., Kaplan, I., Bearez, P., Amiens-Desneux, E & Desneux, N. (2013) Spatiotemporal patterns of induced resistance and susceptibility linking diverse plant parasites. Oecol. (DOI 10.1007/s00442-013- 2716-6) Ohgushi, T. (2005) Indirect interaction webs: herbivore-induced indirect effects through trait change in plants. Annu. Rev. Ecol. Evol. Syst. 36, 81–105. O’Donnell, P.J., Jones, J.B., Antoine, F.R., Ciardi, J. & Klee, H.J. (2001) Ethylene-dependent salicylic acid regulates an expanded cell death response to a plant pathogen. Plant J. 25, 315-323. Peiffer, M., Tooker, J.F., Luthe, D.S., Felton & G.W. (2009) Plants on early alert: glandular trichomes as sensors for insect herbivores. New Phytol. 184, 644-656. Poelman, E.H., Broekgaarden, C., Van Loon, J.J.A. & Dicke, M. (2008) Early season herbivore differentially affects plant defence responses to subsequently colonizing herbivores and their abundance in the field. Mol. Ecol. 17, 3352-3365. Sarmento, R.A., Lemos, F., Dias, C.R., Kikuchi, W.T., Rodrigues, J.C.P., Pallini, A., Sabelis, M.W. & Janssen, A. (2011) A herbivorous mite down-regulates plant defence and produces web to exclude competitors. PLoS ONE 6, e23757. Soler, R., Badenes-Pérez, F.R., Broekgaarden, C., Zheng, S.-J., David, A., Boland, W. & Dicke, M. (2012) Plant-mediated facilitation between a leaf-feeding and a phloem-feeding insect in a brassicaceous plant: from insect performance to gene transcription. Func. Ecol. 26, 156-166. Spoel, S.H., Johnson, J.S. & Dong, X. (2007) Regulation of tradeoffs between plant defenses against pathogens with different lifestyles. Proc. Natl. Acad. Sci. USA 104, 18842-18847. Stout, M.J., Fidantsef, A.L., Duffey, S.S. & Bostock, R.M. (1999) Signal interactions in pathogen and insect attack: systemic plant-mediated interactions between pathogens and herbivores of the tomato, Lycopersicon esculentum. Physiol. Mol. Plant Pathol. 54, 115-130. Stout M.J., Thaler J.S. & Thomma, B. (2006) Plant-mediated interactions between pathogenic microorganisms and herbivorous arthropods. Annu. Rev. Entomol. 51, 663-89. Tack, A.J.M. & Dicke, M. (2013) Plant pathogens structure arthropod communities across multiple spatial and temporal scales. Funct. Ecol. 27, 633-645. Thaler, J.S., Fidantsef, A.L., Duffey, S.S. & Bostock, R.M. (1999) Trade-offs in plant defense against pathogens and herbivores: a field demonstration of chemical elicitors of induced resistance. J. Chem. Ecol. 25, 1597-1609. Thaler, J.S., Stout, M.J., Karban, R. & Duffey, S.S. (2001) Jasmonate-mediated induced plant resistance affects a community of herbivores. Ecol. Entomol. 26, 312-324. Thaler, J.S., Owen, B. & Higgins, V.J. (2004) The role of the jasmonate response in plant susceptibility to diverse pathogens with a range of lifestyles. Plant Physiol. 135, 530-538. Thaler J.S., Agrawal A.A. & Halitschke, R. (2010) Salicylate-mediated interactions between pathogens and herbivores. Ecol. 91, 1075-1082. Uppalapati, S.R., Ishiga, Y., Wangdi, T., Kunkel, B.N., Anand, A., Mysore, K.S. & Bender, C.L. (2007) The phytotoxin coronatine contributes to pathogen fitness and is required for suppression of salicylic acid accumulation in tomato inoculated with Pseudomonas syringae pv. tomato DC3000. Mol. Plant Microbe In. 20, 955-965.

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Viswanathan, D.V., Narwani, A.J.T. & Thaler, J.S. (2005) Specificity in induced plant responses shapes patterns of herbivore occurrence on Solanum dulcamara. Ecol. 86, 886-896. Van Wees, S.C.M. & Glazebrook, J. (2003) Loss of non-host resistance of Arabidopsis nahG to Pseudomonas syringae pv. phaseolicola is due to degradation products of salicylic acid. Plant J. 33, 733-742. Westphal, E., Perrot-Minnot, M.J., Kreiter, S. & Gutierrez, J. (1992) Hypersensitive reaction of Solanum dulcamara to the gall mite Aceria cladophthirus causes an increased susceptibility to T. urticae. Exp. Appl. Acarol. 15, 15-26. Wu, J. & Baldwin, I.T. (2010) New insights into plants responses to the attack from insect herbivores. Annu. Rev. Genet. 44, 1-24. Van Zandt, P.A. & Agrawal, A.A. (2004) Community-wide impacts of herbivore-induced plant responses in milkweed (Asclepias syriaca). Ecol. 85, 2616-2629. Zhang, P.J., Zheng, S.J., Van Loon, J.J.A., Boland, W., David, A., Mumm, R. & Dicke, M. (2009) Whiteflies interfere with indirect plant defense against spider mites in Lima bean. Proc. Natl. Acad. Sci. USA 106, 21202-21207. Zhao, Y., Thilmony, R., Bender, C.L., Schaller, A., He, S.Y. & Howe, G.A. (2003) Virulence systems of Pseudomonas syringae pv. tomato promote bacterial speck disease in tomato by targeting the jasmonate signaling pathway. Plant J. 36, 485-499.

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J.J. Glas, J.M. Alba, R.C. Schuurink, M.W. Sabelis & M.R. Kant

Tomatoes are commonly attacked by different herbivores. Among these are phytophagous mites, including the generalist Tetranychus urticae and the specialists Tetranychus evansi and Aculops lycopersici. Tomato defense responses to spider mites have been relatively well characterized: whereas the common genotypes of T. urticae activate the jasmonic acid (JA)- and salicylic acid (SA)-dependent pathways, T. evansi was found to suppress both these defense pathways. In contrast, A. lycopersici up-regulates SA-mediated defenses but down-regulates JA- dependent defenses. In order to get a broader overview of these differences, we compared phytohormone- and transcriptome-wide responses in leaflets after attack by T. urticae, T. evansi, A. lycopersici or the combination of T. urticae and A. lycopersici using LC-MS and microarray analysis, respectively. Tetranychus urticae and A. lycopersici altered the expression of a comparable number of genes (ca. 15%) compared to uninfested control plants of which approximately 50% was regulated similarly by both mite species. In contrast, T. evansi influenced the expression of only 2% of the plant genes in comparison to uninfested plants. Moreover, the absolute magnitude of up- or down-regulation of tomato genes was much smaller in the case of T. evansi. In particular genes annotated as having a role in photosynthesis, cell wall modification, hormone metabolism and stress responses (e.g., PR-proteins; glutathione S-transferases; cytochrome P450s; peroxidases; WRKY transcription factors) were affected by T. urticae as well as by A. lycopersici. Both defense-inducing and defense-suppressing mites caused a down-regulation of photosynthesis-related genes with the largest number of genes being affected in leaflets infested with both species simultaneously. In addition, uniquely- regulated genes were identified as well, for instance a xylanase inhibitor up-regulated only by A. lycopersici and possibly important in mediating plant defense responses. Finally, several hypothesizes are discussed that may explain our observations in the context of recent work on the relation between defenses and resource allocation.

n nature plants are regularly confronted with biotic attackers against which they Ihave to defend themselves. Induced defense responses, which, together with con-

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stitutive defenses, determine the capability of a plant to withstand these attackers, depend mainly on the action of the phytohormones jasmonic acid (JA) and salicylic acid (SA). These two phytohormones, together with several others (Erb et al., 2012), regulate anti-herbivore and pathogen defenses, which includes the synthesis of toxins and inhibitors of food digestion (Howe & Jander, 2008) and re-allocation of resources (Gómez et al., 2012). Tomato (Solanum lycopersicum) has become a well-established model organism to elucidate wound- and herbivore-induced defense mechanisms in plants (e.g., Ryan, 2000; Li et al., 2004; Scranton et al., 2013). Only a limited number of microarray studies have been undertaken to identify tomato transcriptional responses to herbivory, for instance to the two-spotted spider mite Tetranychus urticae (Ament et al., 2004; Kant et al., 2004; Li et al., 2004), caterpillars of the beet armyworm (Spodoptera exigua) (Rodriguez-Saona et al., 2010) and aphids (Macrosiphum euphorbiae) (Rodriguez-Saona et al., 2010). Spider mites (Tetranychus spp.) use their paired stylets to feed from parenchyma cells leading to chlorotic lesions were cells have been emptied and it has been estimated that approximately 1 mm2 of leaf area is damaged per day per adult spider mite on tomato (Kant et al., 2004). The two-spotted spider mite T. urticae, which is highly polyphagous (Dermauw et al., 2012), induces both JA- and SA-regulated genes, among which are JA-dependent wound-induced proteinase inhibitors (PINs), SA-responsive pathogenesis-related proteins (PR-proteins), and genes depending on both JA and SA signaling, such as Geranylgeranyl Pyrophosphate Synthase1 (GGPS1), which is involved in production of plant volatiles (Kant et al., 2004; Ament et al., 2006). Closely related to T. urticae is the red tomato spider mite T. evansi which has specialized to feed on solanaceous plants in Brazil and Africa and has recently made its entry into Europe (Boubou et al., 2012). Just like some rare T. urticae genotypes (Kant et al., 2008), T. evansi was found to suppress the plant’s defense responses (Sarmento et al., 2011). The mechanism by which this suppression occurs is not known, but appears to be independent from the JA/SA-antagonism, since both defense pathways are suppressed by T. evansi (Alba et al., submitted). Adult females of both spider mite species produce, depending on the temperature, around 5-12 eggs per day on tomato (Sarmento et al., 2011), which develop in reproducing adults themselves within 2 weeks, resulting in exponential population growth. A third phytophagous mite pest of tomato is the specialist tomato russet mite Aculops lycopersici, which, like T. evansi, has specialized to use solanaceous plants as host. However, since adult russet mites have much shorter stylets (ca. 10 μm) compared to adult spider mites (ca. 150 μm) (Park & Lee, 2002), they do not reach the mesophyll layer but instead feed only on epidermal cells of leaves and stems of tomato. Russet mites do not only target very different tomato tissues compared to

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spider mites, but also have a different effect on induced responses as they were found to induce SA-mediated defenses but suppress JA-dependent defenses (CHAPTER 2). Hence, the A. lycopersici-induced response is distinct from T. urticae, which induces both the JA- and SA-pathway, as well as that from T. evansi, which suppresses both defense pathways. To enhance our understanding of the differences between defense suppression and induction by these three mite species, we compared transcriptional changes in leaflets that had been infested with T. urticae, T. evansi, A. lycopersici or with the combination of T. urticae and A. lycopersici using a 60-mer oligonucleotide microarray (Agilent/Nimblegen) carrying 44195 probes designed on public tomato EST libraries. In addition, we measured phytohormone levels in the same tissues used for the transcriptome analysis to compare transcriptional responses with the accumulation of the phytohormones 12-oxo-phytodienoic acid (OPDA), JA, jasmonic acid- isoleucine (JA-Ile), SA and abscisic acid (ABA).

Material and methods Plants and mites Tomato seeds [S. lycopersicum cv. Castlemart (CM)] were germinated in soil and grown in a greenhouse compartment at a temperature of 25ºC and a 15/9 h light/dark regime. One week prior to the start of the experiment, plants were transferred to a climate room at 25ºC and a 16/8 h light/dark regime with 300 μE m-2 s-1 and 60% RH. Plants were infested when they were 21 days old and samples when 28 days old. The tomato russet mite (A. lycopersici) was obtained from Koppert Biological Systems (Berkel en Rodenrijs, The Netherlands) who in turn had collected them in 2008 from a tomato greenhouse in the Westland area (The Netherlands). Russet mites were reared in insect cages (BugDorm-44590DH, Bug Dorm Store, MegaView Science, Taichung, Taiwan) in a climate room (day/night temperature of 27ºC/25ºC, a 16/8 h light/dark regime and 60% RH) on tomato plants (cv. CM) that were between 3 and 5 weeks old. The two-spotted spider mite (T. urticae) strain we used was originally obtained in 2001 from a single European spindle tree (Euonymus europaeus) in the dunes near Santpoort (The Netherlands) (GPS coordinates: 52 26.503 N 4 36.315 E), and has been described as T. urticae Santpoort-2 (Alba et al., submitted). In a previous study, where it was referred to as ‘KMB’, T. urticae Santpoort-2 was characterized as an ‘inducer’ of JA-defenses and as susceptible to these defenses (Kant et al., 2008). Since its collection from the field, the strain has been propagated on detached bean (Phaseolus vulgaris) leaves that were placed with the abaxial surface on wet cotton wool and maintained in a climate room (temperature of 25ºC, a 16/8 h light/dark and 60% RH).

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The tomato red spider mite (T. evansi) was collected in a tomato greenhouse on the campus of the University of Viçosa (Brazil) (GPS coordinates: 20 45.473 S 42 52.163 W) where it was maintained on S. lycopersicum (cv. Santa Clara) as described previously (Sarmento et al., 2011). In 2009, 10 heavily infested leaves from this population were transferred to Amsterdam where it was subsequently propagated on detached leaves of S. lycopersicum (cv. CM) in a climate room (temperature of 25ºC, a 16/8 h light/dark and 60% RH). The species identity of A. lycopersici was confirmed on the basis of the morphology of the prodorsal shield (F. Faraji, personal observation). The species identity of T. urticae and T. evansi was confirmed on the basis of the morphology of the male reproductive organ (the aedeagus) and on the basis of a phylogenetic construction using the mitochondrial cytochrome oxidase subunit 1 (CO1) sequences (cf. Alba et al., submitted). The CO1-sequences and sequencing primers can be found in GenBank under the following IDs: T. urticae: KF447571 and T. evansi: KF447575.

Infestation and sampling of plants At the start of the experiments, 21-day-old tomato plants were infested simultaneously with T. evansi, T. urticae, A. lycopersici or with T. urticae and A. lycopersici together. Spider mite infestations were performed by individually transferring adult females, randomly collected from the rearing colony, with a fine brush to each of three leaflets per plant. Each leaflet received 15 spider mites so that in total each plant was infested with 45 spider mites. Russet mite infestations were performed by transferring mites on small pieces of leaflets (ca. 0.5 cm²) to the leaflets of uninfested plants. These leaflet pieces had been cut from leaves picked from a well-infested tomato plant and each piece contained ca. 250 mobile stages of RM as determined with a stereomicroscope. To prevent mites from dispersing we applied a thin barrier of lanolin (Sigma-Aldrich Chemie, Zwijndrecht, The Netherlands) on the petioles of leaflets that were chosen for infestation. Uninfested control plants received the lanolin barrier, but no mites. Within an experiment, each plant was taken as one replicate (i.e., three leaflets per plant were later on pooled together for RNA extraction). In total six plants were infested per treatment. Sampled leaflets were flash-frozen in liquid nitrogen and stored at -80°C until total RNA was extracted. Care was taken to always pick leaflets with the same position for infestation, i.e., one leaflet of the second compound leaf, one from the third compound leaf and the terminal leaflet of the fourth compound leaf (counted from the bottom to the top of the plant). Samplings were performed at the same time of the day on day 7 after infestation. The experiment was repeated 4× during four consecutive weeks in March 2012. Hence, in total there were 120 samples (6 samples × 5 treatments × 4 replicate trials).

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RNA isolation Leaflets were ground in liquid nitrogen, and total RNA was extracted using a phenol- LiCl-based method as described by Verdonk et al. (2003). The integrity of RNA was checked on 1% agarose gels. Total RNA was subsequently quantified using a NanoDrop 100 spectrophotometer (Fisher Scientific, Loughborough, UK).

Microarray hybridizations For the microarray hybridizations, equal amounts of RNA were pooled per treatment (i.e., the six RNA samples obtained from the same trail week and the same treatment type were pooled). Per pooled treatment one array was hybridized so that in total 20 arrays were used (5 treatments × 4 replicate trials weeks). The probe sequences (60- mer oligos) were identical to those from the tomato Agilent 44k array (Agilent, Santa Clara, CA, USA) and included ~600 custom sequences. The probes were synthesized in spots on the 135k Nimblegen array format (Nimblegen, Madison, WI, USA) having each probe represented by three spots on each array. Preparation, labeling, purification and hybridizations were carried out according to protocols provided by the manufacturer (Nimblegen). Samples were cy3 labeled and these were normalized across arrays via a common reference design using a cy5 labeled pool of all the samples as the reference on each array.

Microarray analysis First, all signal intensities were normalized within each array using Lowess. Subsequently, all triplicate probe-sets were averaged. These averages were then normalized across arrays by means of the averaged common reference signals. These relative intensities are equivalent to the relative expression levels of the genes represented by each probe. For data analysis we selected only those probes that gave a good hit on the predicted genome CDSs available at the SGN database (Bombarely et al., 2011), i.e., those that had a match smaller or equal to 1E-20 (corresponding to maximally three mismatches between the 60-mer probe and the target sequence). Applying this cri- terion resulted in a list of 28077 probes suitable for the analysis (64% of the total of 44195 that were spotted on the array). Since many of these probes were duplicated on the array (i.e., different probes corresponding to the same gene) we subsequently filtered the array to select for the unique genes. This yielded a total number of 15504 genes that were represented on the array (~50% of the total number of 31760 tomato genes). In the case of duplicated probes the values for the individual probes were averaged. Significant differences in gene expression between control and treat-

ment samples were identified using a nested ANOVA on the log2-transformed relative expression values. P-values were adjusted according to Benjamini & Hochberg’s

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step-up procedure for controlling the False Discovery Rate (FDR) (Benjamini & Hochberg, 1995). The P-values of the arrays on which <5% of all genes were significantly regulated before P-value correction (which was the case for the T. evansi samples) were adjusted via Simes’ step up FDR procedure (Simes, 1986) which behaves a little less stringent at small fractions of regulated genes (Bretz et al., 2005). Differentially expressed genes were identified based on an adjusted P-value <0.05. Differences in gene expression between treatments were visualized using MapMan. In MapMan, large data sets can be projected onto metabolic pathways or assigned to functional categories (called ‘BINs’, ‘subBINs’) thereby allowing for detection of trends that might be less apparent when looking at individual genes (Thimm et al., 2004). In MapMan, we performed a so-called over/under-representation or enrichment analysis (FIGURE 4.2). Here, the experiment is divided into up- and down-regulated genes. In both cases, if a category has more genes than expected exceeding the threshold it is colored in green, if it has less than colored in red. Over- or under- representation was tested by applying Fisher’s test for over representation analysis (ORA) with the threshold set to 1. Since the Benjamini & Hochberg multiple testing correction is known as a conservative approach, which can sometimes be too stringent (Huang et al., 2009) we performed the same analysis with and without the Benjamini & Hochberg correction. Classes in FIGURE 4.2 that were found to be significantly different also after the Benjamini & Hochberg correction are indicated by an asterisk. For the ORA only those genes where selected where at least one of the treatments was significantly different from the control (adjusted P-value <0.05).

Phytohormone analysis Phytohormones were extracted and quantified by means of LC-MS as described in CHAPTER 2. Phytohormone data were log-transformed and analyzed using ANOVA, with ‘Treatment’ (with the levels: ‘Control’, ‘T. urticae’, ‘T. evansi’, ‘A. lycopersici’ and ‘T. urticae + A. lycopersici’) as fixed factor and ‘Experimental Replicate’ (with levels 1-4) included as random factor in the model. The means of each group were compared using Fisher’s least significant difference (LSD) post hoc test.

Results and Discussion Phytohormone analysis Since transcriptional responses are tightly regulated by phytohormones, we first measured phytohormone accumulation in the same samples as used for the transcriptome analysis. Tetranychus urticae induced a significant increase in levels of the JA-precursor OPDA, JA and JA-Isoleucine (JA-Ile), the bio-active form of JA, as well as SA and ABA, when compared to uninfested control plants (FIGURE 4.1). In contrast, T. evansi did not induce the accumulation of OPDA, JA and ABA, whereas levels of

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FIGURE 4.1 Phytohormone levels in leaflets infested with different mite species. The figure shows the mean (+SEM) amounts (ng/g fresh weight; n=21-24 from four replicate experiments) of endogenous OPDA (A), JA (B), JA-Ile (C), SA (D) and ABA (E) in uninfested and mite-infested wild-type (cv. CM) leaflets after 7 days of infestation. C = Uninfested control plants, U = Tetranychus urticae. E = T. evansi, A = Aculops lycopersici. Different letters capping the bars indicate significant differences (ANOVA followed by Fisher’s LSD test: P<0.05). The same samples were used for the transcriptome analysis.

JA-Ile and SA were slightly higher in T. evansi-infested leaflets in comparison to con- trols, but ca. 6- and 3-fold lower when compared to T. urticae-infested leaflets. Similar to T. urticae, also A. lycopersici induced a significant increase in levels of OPDA, JA and JA-Ile and SA although the levels were lower in comparison to leaflets infested with T. urticae. Aculops lycopersici also induced a significant accumulation

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of ABA, up to levels that were similar to those measured in leaflets infested with T. urticae. In leaflets co-infested with T. urticae and A. lycopersici simultaneously, levels of JA-Ile were significantly increased in comparison to leaflets that had been infested with T. urticae only or A. lycopersici only, whereas levels of SA and ABA in these leaflets were similar to those in leaflets infested with T. urticae only (FIGURE 4.1).

Overview of transcriptional changes Tetranychus evansi regulated 2% of the total number of the 15504 unique genes on the array (98 up and 176 down compared to control plants), T. urticae 13% (1004 up and 1010 down compared to control plants), A. lycopersici 14% (1239 up and 980 down compared to control plants) and the combination of T. urticae and A. lycopersici 16% (1232 up and 1287 down compared to control plants) (TABLE 4.1). One hundred eighteen genes were specifically regulated by T. evansi alone (1%) (22 up and 96 down), 531 genes specifically by T. urticae alone (3%) (200 up and 331 down), 634 genes specifically by A. lycopersici alone (5%) (329 up and 305 down) and 795 specifically by the combination of T. urticae and A. lycopersici (6%) (289 up and 506 down). Seventy-four genes were similarly regulated in all four treatments (0.5%) (56 up and 18 down). Six hundred sixty-nine genes were up-regulated by T. urticae and A. lycopersici (67% of the total number of T. urticae-induced genes; 54% of the total number of A. lycopersici-induced genes), whereas 443 genes were down-regulated by both mite species (44% of the total number of genes down-regulated by T. urticae; 34% of the total number of genes down-regulated by A. lycopersici). Three genes, among which two GDSL esterases, were induced by A. lycopersici, yet down-regulated by T. urticae, whereas no genes were found that followed the reverse pattern, i.e., induced by T. urticae but down-regulated by A. lycopersici. A total of 69 genes were induced by A. lycopersici and T. evansi (70% of the total number of T. evansi-induced genes; 21% of the total number of A. lycopersici-induced genes), whereas 38 genes were down-regulated by both T. evansi and A. lycopersici (22% of the total number of genes down-regulated by T. evansi; 12% of the total number of genes down-regulated by A. lycopersici). Two genes, i.e., a vesicle-associated membrane protein and a small nucleolar ribonucleoprotein, were up-regulated by A. lycopersici, yet down- regulated by T. evansi. No genes were found that were up-regulated by T. evansi and down-regulated by A. lycopersici. Generally, T. evansi had a much weaker effect on the magnitude of tomato’s transcriptional up- and down regulation than the other two mite species as indicated by the fact that not only the number of regulated genes was smaller in the case of T. evansi (TABLE 4.1), but also the fold-regulations were smaller when compared to the

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TABLE 4.1 Tomato genes differentially expressed in response to mite feeding. Treatment Up-regulated No. genes down-regulated Total Tetranychus evansi 98 176 274 T. urticae 1004 1010 2014 Aculops lycopersici 1239 980 2219 T. urticae and A. lycopersici 1232 1287 2519

other two species. For instance, of the genes that were significantly up-regulated, A. lycopersici and T. urticae regulated, respectively, 583 (47% of the total number of A. lycopersici-induced genes) and 494 (49% of the total number of T. urticae-induced genes) genes more than 2-fold up, whereas T. evansi regulated only 24 genes (22% of the total number of T. evansi-induced genes) more than 2-fold up. Similarly, of the genes that were significantly down-regulated, A. lycopersici and T. urticae regulated, respectively, 165 (17% of the total number of genes down-regulated by A. lycopersici) and 96 genes (10% of the total number of genes down-regulated by T. urticae) more than 2-fold, whereas T. evansi did not regulate any gene (0%) more than 2-fold down.

MapMan functional categories enriched in differentially regulated genes In FIGURE 4.2 the result of a so-called PageMan analysis (Usadel et al., 2006) is shown for which the experiment is divided in up- and down-regulated genes. The colors green and red indicate whether genes from a particular category are over- or underrepresented, respectively, in the total group of genes that are up- or down-regulated by a particular treatment. The PageMan analysis confirms that the effect of T. evansi on the tomato transcriptome is much more subtle than the effect of the other two mite species: whereas T. urticae and A. lycopersici had a significant effect on 18 functional categories, only six of those [i.e., photosynthesis (‘PS’); ‘TCA/organic acid transformation’; ‘N-metabolism’; ‘hormone metabolism’; ‘miscellaneous’; ‘protein’] were significantly affected by T. evansi as well. Genes in the category ‘PS’, including those related to photosystem I and II, were significantly overrepresented in the group of down-regulated genes, whereas they were underrepresented in the group of up-regulated genes and this was the case for all treatments. This suggests that also T. evansi affected photosynthesis, in a similar way as T. urticae and A. lycopersici, although the effect was weaker as indicated by the fact that only three photosynthesis subcategories were significantly affected by T. evansi, whereas 11 and six categories were affected by A. lycopersici and T. urticae, respectively (FIGURE 4.2). Furthermore, in plants simultaneously infested with T. urticae and A. lycopersici, 16 photosynthesis subcategories were significantly influenced indicating that the effect on photosynthesis was more extensive in these plants compared to plants that had been infested with either of the two mite species alone.

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FIGURE 4.2 Pageman functional categories enriched in the genes that are differentially regulated by mites. The degree of enrichment among the up- and down-regulated genes is indicated by the different shades of green and red, respectively (green=overrepresented; red=underrepresented). Differentially regulated genes were identified as those with adjusted P<0.05. E = Tetranychus evansi, A = Aculops lycopersici, U = T. urticae. Functional categories that tested significantly different also after the Benjamini & Hochberg correction are indicated by an asterisk.

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Genes involved in ‘minor carbohydrate (CHO) metabolism’ (i.e., the hexose monophosphate pathway and uronic acid pathway) and ‘glycolysis’ were overrepresented among the down-regulated genes in T. urticae- and A. lycopersici-infested leaflets, whereas genes related to the ‘TCA (tricarboxylic acid) cycle’ were generally overrepresented among the genes up-regulated by T. urticae and A. lycopersici, although not always (cf., e.g., the ‘carbonic anhydrases’ which were more often found among the genes down-regulated by A. lycopersici). Down-regulation of CHO metabolism genes has been observed before in plant- pathogen interactions, for instance in hot pepper (Capsicum annuum) plants that had been infected with the pathogen Xanthomonas axonopodis (Lee et al., 2004). As suggested by Lee et al. (2004), this could indicate that attacked plants switch their carbon flow from the primary metabolic pathway to secondary metabolism, for instance to activate defenses. Expression levels of cell wall-associated genes were affected by both T. urticae and A. lycopersici when compared to uninfested control plants. For instance, genes in the subcategory ‘cell-wall proteins’, including the arabinogalactan proteins (AGPs), were overrepresented among the genes down-regulated by A. lycopersici and T. urticae. AGPs have been found on the plasma membrane and in the cell wall of plants but their function has remained elusive (Ellis et al., 2010). Genes in the category ‘cell wall modification’ were overrepresented among the up-regulated genes in tomatoes infested with either T. urticae or A. lycopersici. However, after applying the Benjamini & Hochberg correction, cell wall modification-related genes were still overrepresented among the A. lycopersici-induced genes, but not among those up-regulated by T. urticae, suggesting that the effect of A. lycopersici on cell wall modification is more pronounced compared to T. urticae. Genes of the ‘aspartate family pathway’ involved in amino acid metabolism were enriched in the A. lycopersici down-regulated gene-pool but not in the T. urticae down-regulated gene pool. The aspartate family pathway is involved in the synthesis of essential amino acids, including lysine, threonine, methionine and isoleucine (Kirma et al., 2012). In contrast, for both T. urticae and A. lycopersici, genes involved in the biosynthesis of the aromatic amino acids were more often found among the up-regulated genes. Furthermore, also genes of the phenylpropanoid pathway were overrepresented among the genes induced by A. lycopersici alone as well as among those induced by A. lycopersici and T. urticae together. Notably, genes in the category ‘terpenoids’ were specifically overrepresented among the T. urticae-induced genes. In addition, genes that have a role in lignin biosynthesis were overrepresented among the up-regulated genes in the samples infested with both mite species and genes of the subcategory ‘flavonoid chalcones’ were specifically overrepresented among the genes down-regulated by A. lycopersici (FIGURE 4.2).

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Phytohormone-related genes were affected by all three mite species, although not in the same way. The total pool of T. urticae-induced genes was enriched in JA- metabolism-related genes, whereas this was not the case for A. lycopersici. Remarkably, among the genes up-regulated by T. evansi there was a significant enrichment in transcripts encoding for the JA biosynthesis enzyme allene oxide synthase (AOS). Also, the pool of T. evansi-induced genes appeared to be enriched in SA- metabolism related genes. Genes related to auxin, cytokinin and ethylene signaling were significantly more often found among the up-regulated genes in plants co-infested with T. urticae and A. lycopersici. Strikingly, the group of A. lycopersici-induced genes was specifically enriched in gibberellin-related genes, whereas these were also overrepresented among the genes down-regulated by T. urticae. Genes involved in ‘tetrapyrrole synthesis’ were overrepresented among the genes down-regulated by A. lycopersici, but not by T. urticae, although the reverse was true for the tetrapyrrole subcategory ‘uroporphyrinogen carboxylase’. Tetrapyrroles, like chlorophyll, play important roles in photosynthesis and respiration in plants (Tanaka & Tanaka, 2007). Then, a number of gene groups annotated as ‘stress proteins’, including PR-proteins, glutathione S transferases, peroxidases and WRKY transcription factors were overrepresented among the genes up-regulated by T. urticae and A. lycopersici, whereas auxin-related transcription factors were also overrepresented among the genes down-regulated by T. urticae and by A. lycopersici. Genes involved in the category ‘signalling’ were significantly more often found in the pool of genes up-regulated by A. lycopersici and T. urticae. Genes in the signaling subcategory ‘sugar and nutrient physiology’ were specifically overrepresented in the gene pool induced by both mite species. Finally, among the A. lycopersici up-regulated genes the ‘leucine rich repeat XI receptor kinases’ were found to be overrepresented and this was the case only in the A. lycopersici-infested samples, whereas genes in the other two signaling subcategories (‘receptor kinases’ and ‘receptor kinases DUF26’) were overrepresented in the pool of T. urticae-induced genes as well.

Transcriptional regulation of defense pathways by the different mite species JA and SA are known as the major plant hormones responsible for defenses against herbivores and pathogens, respectively. Hence, in the following text we discuss the effect of the mites on these specific defense pathways in more detail.

The octadecanoid pathway Induced defense responses against herbivores in tomato depend on the signaling peptide systemin, which itself is derived from a larger protein, prosystemin, the levels of which are known to increase in response to wounding in tomato (Ryan, 2000). Systemin is perceived by the membrane-bound receptor SR160 resulting in the acti-

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vation of the octadecanoid pathway, as indicated by the activation of mitogen-activated protein kinases (MAPKs) (MPK1, 2 and 3), synthesis of JA and expression of downstream defense genes (Kandoth et al., 2007). Even though prosystemin levels are known to increase in response to wounding, on our array none of the mite-infestations changed the expression of this gene (FIGURE 4.3). JA synthesis takes place partly in the chloroplast and partly in the peroxisome. First, the fatty acid substrate linolenic acid (LA) is released from membrane lipids by the action of phospholipases and converted via the action of several enzymes into JA. In tomato it was shown that wounding results in an increase in the levels of the early second messenger phosphatidic acid (PA) (Munnik, 2001) as well as lysophospholipids, suggesting increased activity of the phospholipases PLA, PLD and/or PLC (Lee et al., 1997). Indeed, Narváez-Vásquez et al. (1999) showed that wounding as well as treatments with sys-

temin increased activity of a phospholipase2 (PLA2) and this increased the concentrations of lysophosphatidylcholine in tomato leaves. It is important to note that, although it is known that phospholipases hydrolyze phospholipids thereby releasing lysophosphatidylcholine and LA, there is much controversy about exactly which lipases are responsible for the generation of the JA substrate. Candidates that have been proposed to be involved in JA biosynthesis in Arabidopsis include the phos-

pholipases1 (PLA1) DEFECTIVE IN ANTHER DEHISCENSE 1 (DAD1), DONGLE (DGL) γ and PLA1 1 (Wasternack & Hause, 2013). However, in tomato no lipases involved in JA biosynthesis have been characterized yet.

In our experiment, PLA2 expression appeared to be down-regulated by T. urticae as well as by A. lycopersici, but it did not change in response to T. evansi (not shown in FIGURE 4.2). Arabidopsis plants that were silenced for expression of PLDβ1 contained lower levels of PA and JA as well as JA-related defense gene expression, which consequently made them more susceptible to B. cinerea (Zhao et al., 2013), showing that PLDβ1 is necessary for the formation JA in Arabidopsis. On our toma- to array, expression of PLDβ1 was induced by T. urticae as well as by A. lycopersici, but not by T. evansi, which correlates well with the JA levels induced by these mites (FIGURE 4.1). Apart from PLAs and PLDs, also PLCs are known to play a role in the formation of PA and in tomato responses to pathogen attack (Munnik, 2001; Vossen et al., 2010). The PLCs on the array showed distinct expression patterns in response to infestation with mites. Expression of PLC1 was suppressed by JA-inducing mites, but not by T. evansi, whereas for PLC2 the opposite pattern was observed, i.e., induction by A. lycopersici, yet not by T. evansi. Tetranychus urticae also induced expression of PLC2, albeit not significantly. For PLC4 and PLC6 the expression levels did not change in response to mite infestations. The first committed step in the octadecanoid pathway is carried out by the enzyme lipoxygenase (LOX), which catalyzes the insertion of molecular oxygen into

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FIGURE 4.3 The JA-pathway is differentially regulated by the three mite species. Shown is an overview of the most important genes that have been connected to the JA-defense signaling pathway. Bars represent the relative average (+SEM) expression values of each gene. All values were divided by the lowest average value (such that the lowest average is always 1). C = Uninfested control plants, U = Tetranychus urticae. E = T. evansi, A = Aculops lycopersici. Asterisks indicate significant differences with uninfested control plants. Expression values are given for Prosystemin (Prosys; Solyc05g051750.2); Phospholipase Dβ1 (PLDβ1; Solyc08g080130.2); Lipoxygenase C (LOX-C; Solyc01g006540.2); Lipoxygenase D (LOX-D; Solyc03g122340.2); Allene Oxide Synthase (AOS; Solyc04g079730.1); Allene Oxide Cyclase (AOC; Solyc02g085730.2); Jasmonate Zim-domain Protein 1 (JAZ1; Solyc12g009220.1); Jasmonate Zim-domain Protein 2 (JAZ2; Solyc03g122190.2); Jasmonate Zim-domain Protein 3 (JAZ3; Solyc01g005440.2); Jasmonate Zim-domain Protein 8 (JAZ8; Solyc08g036660.2); Polyphenol Oxidase D (PPO-D; Solyc08g074680.2); Polyphenol Oxidase E/F (PPO-E/F; Solyc08g074630.1); Proteinase Inhibitor I (PI-I; Solyc09g084470.2); Proteinase Inhibitor II (PI-IIf; Solyc03g020080.2); Proteinase Inhibitor II (PI-IIc; Solyc03g020050.2); Kunitz-type Proteinase Inhibitor (KPI; Solyc03g098790.1) which is similar to Cathepsin D inhibitor (CDI; AJ295638.1); Threonine Deaminase (TD; Solyc09g008670.2); Leucine Aminopeptidase (LAP; Solyc12g010020.1); and Salicylic Acid Carboxyl Methyltransferase (SAMT; Solyc09g091550.2).

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position 13 of LA, resulting in hydroperoxy-linolenic acid, which is then further converted by the enzymes AOS and allene oxide cyclase (AOC) into the JA-intermediate OPDA (Turner et al., 2002; Wasternack et al., 2006). Subsequently, OPDA is exported from the chloroplast and imported into the peroxisomes where it is converted by the OPDA reductase (OPR3) into cyclopentane-1-octanoic acid, followed by three cycles of β-oxidation to yield the final product JA (Wasternack et al., 2006). In a next step, JA is then conjugated to isoleucine (Ile) by the enzyme jasmonate resistant 1 (JAR1) (Suza et al., 2010), leading to the formation of JA-Ile, which is the bioactive form of JA (Fonseca et al., 2009). Clearly, the enzymes involved in JA-biosynthesis were differentially regulated by the mites. Tomato possesses at least six lipoxygenases (LOXs) of which TomloxA, TomloxB and TomloxE are expressed in fruits during ripening, whereas TomloxC and TomloxD are expressed in leaves as well (Chen et al., 2004; Hu et al., 2013). TomloxC expression levels did not change in response to mite infestations. In contrast, TomloxD was significantly up-regulated by T. urticae as well as by A. lycopersici, but not by T. evansi. TomloxD is known to be expressed in leaves and is induced by wounding and treatment with systemin or methyl jasmonate (Heitz et al., 1997). Similar to TomloxD, also AOS and AOC were up-regulated by T. urticae and A. lycopersici feeding. Despite the fact that feeding by T. evansi did not induce JA accumulation (FIGURE 4.1), it did up-regulate expression of AOS, to a similar extent as feeding by T. urticae did. Expression of AOC followed a similar trend, although T. evansi did not induce this gene significantly. Taken together, these data show that both T. urticae and A. lycopersici activate the octadecanoid pathway. In contrast, T. evansi may suppress TomloxD and thereby the flux through the pathway, thus preventing JA to accumulate. Alternatively, low expression of TomloxD may be due to indirect feedback regulation by down-stream signaling components. The induction of AOS in T. evansi-infested plants may indicate an attempt of the plant to compensate for the low JA levels, but this remains to be tested. Activation of JA-regulated responses depends on the binding of JA-Ile to the SCFCOI1 (Skip/Cullin/F-box) receptor complex. In an un-induced situation, transcription is not activated due to the binding of the Jasmonate ZIM domain (JAZ) repressor proteins to downstream transcription factors, like MYC2, which themselves are bound to JA-responsive elements present in the promoters of JA-responsive genes (Wasternack & Hause, 2013). JAZ proteins are known as suppressors of the JA-response since newly synthesized JAZ proteins, of which the expression is induced in response to JA, can establish negative feedback loops by binding MYC2, thereby blocking expression of downstream JA-responsive genes (Chini et al., 2007). JAZ8 is also known as a suppressor of the JA-response, but appears to execute this function independent from

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the SCFCOI1 complex (Shyu et al., 2012). Upon stimulation of the JA-pathway, the JAZ proteins are ubiquitinated by the F-box protein CORONATINE INSENSITIVE1 (COI1) complex and subsequently degraded, thereby un-repressing transcription factors such as MYC and thereby releasing the transcription of defense-related genes. Examples of such defense-related genes in tomato include Wound-Induced Proteinase Inhibitor I and II (WIPI-I and II) (Graham et al., 1985a,b), Jasmonic Inducible Protein-21 (JIP-21) (Lisón et al., 2006), Polyphenol Oxidase-F (PPO-F) (Newman et al., 1993), Threonine Deaminase (TD) (Gonzales-Vigil et al., 2011) and Leucine Aminopeptidase (LAP) (Fowler et al., 2009). However, whether (all of) these are under control of the JAZ proteins is as yet not clear. Both T. urticae and A. lycopersici up-regulated expression of JAZ1 as well as JAZ8, and this response was enhanced in plants infested with both species simultaneously. Tetranychus evansi also induced expression of JAZ1 and JAZ8 although to a much lesser extent than T. urticae or A. lycopersici. In contrast, the expression of JAZ2 and JAZ3 did not change significantly in response to mite feeding (FIGURE 4.3). Importantly, the effect of JAZ proteins on the JA-response is regulated on the protein level since induction of JA-accumulation not only induces their expression, but also their binding to the SCFCOI1 complex and, thus, their degradation. Hence, this implies that it is difficult to draw conclusions solely based on the expression patterns of these genes. Even though T. urticae and A. lycopersici induced JAZ expression to a similar extent, the defense genes responded very differently. Whereas T. urticae feeding caused a significant up-regulation of JA-dependent defense genes, including PI-I, PI-IIc, PI-IIf and LAP, none of these were induced by A. lycopersici. Note that PI-IIf is also known as WIPI-II (Alba et al., submitted). Furthermore, the expression pattern for KPI (also known as JIP-21 or Cathepsin D inhibitor (CDI) (Lisón et al., 2006), PPO- E/F and TD showed a very similar trend, although for these genes there was too much variation to detect statistically significant differences (FIGURE 4.3). Notably, in co-infested plants, the expression levels of PI-I, PI-IIf, KPI, PPO-E/F, TD and LAP, but not PI-IIc, were reduced to half the levels induced in plants infested with T. urticae only (FIGURE 4.3). Hence, these results confirm previous findings that in plants co-infested with A. lycopersici, T. urticae-induced JA-defense responses are suppressed, rather than not-induced. Moreover, this suppression occurs downstream of JA-biosynthesis since in co-infested leaflets levels of JA remained up-regulated, for JA-Ile even to additive levels (FIGURE 4.1). With the exception of LAP, T. evansi did not cause a significant up-regulation of JA-dependent defense genes, thereby confirming previous findings that T. evansi suppresses plant defenses (Sarmento et al., 2011). Strikingly, expression of PI-IIc and PPO-D was not suppressed by A. lycopersici in co-infested plants. Expression of Salicylic Acid carboxyl Methyl Transferase (SAMT) was induced by all three mite species, and, like PPO-D and PI-IIc, also this

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gene was not suppressed in co-infested plants. SAMT, which depends on JA-signaling, is known to be involved in the biosynthesis of the volatile methyl salicylate (MeSA) (Ament et al., 2004, 2010). Also Geranylgeranyl Pyrophosphate Synthase (GGPS1), which is involved in the biosynthesis of the volatile 4,8,12-trimethyltrideca- 1,3,7,11-tetraene (TMTT) and depends on both the JA- and SA-signaling pathway (Ament et al., 2006), was induced by T. urticae as well as by A. lycopersici, and levels in plants co-infested with both mite species were similar to those induced by T. urticae alone (not shown in FIGURE 4.3 as this gene depends on both JA and SA). Hence, these results suggest that A. lycopersici does not suppress all JA-dependent genes. Possibly, suppression targets only a subset of genes, for instance because there is differential regulation of genes downstream of JA, as, for example, in Arabidopsis where there are two branches downstream of JA, i.e., the ERF and the MYC branch (Pieterse et al., 2012). Alternatively, it could be that some of these genes are regulated by other signals, additional to JA. Future experiments should reveal the effect of A. lycopersici on the volatile profile emitted by tomato plants, as well as the consequences for the third trophic level, i.e., attraction of natural enemies.

The phenylpropanoid pathway In CHAPTER 2, we found that both T. urticae and A. lycopersici induce accumulation of SA as well as accumulation of transcripts of the SA-marker gene PRP6. SA can be synthesized in plants from chorismic acid via two distinct branches. However, note that several details of these pathways are unknown and can be different across plant species. The first branch runs via isochorismate synthase (ICS), which in Arabidopsis and tomato is up-regulated upon pathogen infections and produces the SA precursor isochorismic acid (Wildermuth et al., 2001; Uppalapati et al., 2007). In the second branch, chorismic acid-derived cinnamic acid, which is produced from phenylalanine via the enzyme phenylalanine ammonia lyase (PAL), is converted into SA via either benzoate intermediates or coumaric acid (Boatwright et al., 2013). However, note that the steps of the second branch have not been experimentally confirmed in tomato (Blanco-Ulate et al., 2013). Remarkably, even though T. urticae, as well as A. lycopersici, induced accumulation of SA (FIGURE 4.1), expression of ICS (Solyc06g071030 is tomato’s only ICS gene) did not change in response to any of the mite treatments (not shown in FIGURE 4.4). In contrast, expression of PAL was up-regulated by T. urticae as well as by A. lycopersici, but not by T. evansi, suggesting that the up-regulation of SA in our tomato-mite system is constrained by the activity of PAL, rather than that of ICS. However, it must be noted that tomato possesses at least 17 loci annotated as PAL in the Heinz genome and nine additional putative PAL loci organized in multiple clusters and hence there may be a high level of functional redundancy (Chang et al., 2008). Downstream of SA, the

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expression of Pathogenesis-related Proteins (PRs) was up-regulated by both T. urticae and A. lycopersici, including PR1, PR1b, PR4, β-glucanase (member of the PR-2 family), endochitinase (PR-3) and a thaumatin-like protein (PR-5). Co-infested plants appeared to display additive responses of PR1 and PR1b compared to plants infested with T. urticae alone, in accordance with previous results where we found a stronger response of PR-P6 in plants co-infested with T. urticae and A. lycopersici compared to plants infested with either T. urticae or A. lycopersici alone (CHAPTER 2). PR-proteins are often used as markers for SA-defenses and are associated with resistance responses of plants to pathogens. For instance, β-1,3-glucanase and chitinase hydrolyze β-1,3-glucan and chitin, respectively, which are major components of fungal and bacterial cell walls, and this is thought to inhibit pathogen growth (Van Loon et al., 2006). Also the peritrophic membrane of many arthropods contains chitin but per- foration of it due to induced plant chitinases, as can be obtained using insect chitinases (Kramer & Muthukrishnan, 1997) has not been demonstrated convincingly (Kitajima et al., 2010). The osmotin precursor protein (NP24), a thaumatin-like protein, was also up-regulated by both T. urticae and A. lycopersici (not shown in FIGURE 4.4). NP24, which was previously found to be induced in tomato plants infected with Citrus Exocortis Viroid (Bellés et al., 1999), inhibits fungal growth on tomatoes (Pressey, 1997) and is possibly under control of ERF transcription factors (Hongxing et al., 2005). Furthermore, at least eight peroxidases were induced by both T. urticae and A. lycopersici. Peroxidases have diverse functions: they produce reactive oxygen species, which are toxic to microorganisms, and they also play a role in the polymerization of cell wall compounds, like lignin and suberin (Passardi et al., 2005). Shown in FIGURE 4.4 is the Ep5C gene, which codes

for a secreted cationic peroxidase, and is induced by H2O2 during the oxidative burst following Pseudomonas syringae infections (Coego et al., 2005). Ep5C is known as a susceptibility factor since plants with a functional Ep5C were more susceptible to P. syringae than tomatoes in which Ep5C was silenced (Coego et al., 2005). Hence, it would be interesting to test the resistance of these tomatoes to A. lycopersici since they induced the highest expression of this gene and may take advantage of it. Taken together, the results so far confirm that tomatoes respond to T. urticae with a mixture of JA- and SA-dependent responses, whereas attack by A. lycopersici only up-regulates SA- mediated defenses. In contrast to the other two species, T. evansi did not, or only marginally, induce JA- or SA-dependent defense responses. The shikimate pathway, which precedes the phenylpropanoid pathway, does not only generate SA but is also responsible for lignin, and flavonoid/benzonoid formation. The first is a structural component of cell walls and the second constitutes a large group of secondary metabolites predominantly associated with stress. Chorismate, the endproduct of the shikimate pathway, is produced from phospho- enolpyruvate and erythrose-4-phosphate and functions as the precursor for many

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compounds produced in the phenylpropanoid pathway (Weaver & Herrmann, 1997). In this pathway, chorismate is converted via the sequential actions of chorismate mutase (CMU), PAL, cinnamate 4-hydroxylase (C4H) and 4-coumarate:coenzyme A ligase (4CL) into 4-coumaroyl-CoA, which can then be further converted in separate sub-branches to produce either lignins, flavonoids or anthocyanins (FIGURE 4.3). One out of the five 4CL genes on the array was induced in response to A. lycopersici, whereas the others did not change in any of the treatments. There were three genes encoding Cinnamoyl-CoA-reductase (CCR), the first dedicated step in the lignin biosynthesis branch, of which one was significantly up-regulated by T. urticae (FIGURE 4.4). In contrast, the expression of genes coding for the second dedicated enzyme cinnamyl alcohol dehydrogenase (CAD), did not change. Six genes on the array, of the in total 25 putative loci present in the genome, were annotated as caffeoyl-CoA O-methyltransferase (CCoAOMT) and all of these were up-regulated by A. lycopersici and, except for one, also by T. urticae, whereas T. evansi induced only one of them (i.e., the one shown in FIGURE 4.4). CCoAOMT is associated with lignification in tomato (Ye et al., 1997) and, because its activity is induced by fungal elicitors, it has been proposed to play a role in defense by catalyzing the synthesis of polymers to reinforce the cell wall (Pakusch et al., 1989). Hence, this result suggests that plants lignify their cell walls to protect themselves against mite attack, a phenomenon which actually has been described indeed for eriophyoid mites (Petanovic & Kielkiewicz, 2010). Apart from lignins, 4-coumaroyl-CoA can also branch off to the flavonoids/benzenoids. In that case it is converted via the sequential actions of chalcone synthase (CHS) and chalcone isomerase (CHI) into flavonoids, such as the flavanone naringenin (Petrussa et al., 2013). Naringenin can be further converted by flavanone 3-hydroxylase (F3H) to yield dihydrokaempferol which subsequently is hydroxylated by flavonoid 3'-hydroxylase (F3'H) and flavonoid 3',5'-hydroxylase (F3'5'H) to produce, respectively, the flavonoids dihydroquercetin and dihy- dromyricetin (Petrussa et al., 2013). Dihydroquercetin can then be further converted by flavonol synthase (FLS) into quercetin (Olsen et al., 2010). Tomato possesses two genes annotated as CHS (CHS1: Solyc09g091510 and CHS2: Solyc05g053550) of which the expression levels were lower in response to T. urticae and A. lycopersici compared to T. evansi. Significant down-regulation was observed for CHS1 in response to A. lycopersici, whereas CHS2 was significantly down-regulated in response to infestation with both T. urticae and A. lycopersici simultaneously (FIGURE 4.4). Three genes were annotated as CHI, which showed vari- able expression patterns in response to mite feeding. One of them, Solyc02g067870 was slightly but significantly down-regulated by T. urticae (FIGURE 4.4). A second CHI (Solyc08g061480.2) was up-regulated by A. lycopersici, but not affected by T. urticae or T. evansi (not shown in FIGURE 4.3).

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The tomato genome harbors eight F3H-like expressed genes, two of which were on the array and of those one was up-regulated by A. lycopersici and T. urticae, but not by T. evansi. The expression of flavonol synthase (FLS), of which tomato has five homologs, did not change much in response to any of the mites (FIGURE 4.4).

FIGURE 4.4 Regulation of the phenylpropanoid pathway by the three mite species. Shown is an overview of the most important genes of the phenylpropanoid pathway. Bars represent the relative average (+SEM) expression values of each gene. All values were divided by the lowest average value (such that the lowest average is always 1). C = Uninfested control plants, U = Tetranychus urticae. E = T. evansi, A = Aculops lycopersici. Asterisks indicate significant differences with uninfested control plants. Expression values are given for Phenylalanine ammonia lyase (PAL; Solyc09g007900.2); Pathogenesis-related protein 1 (PR-1; Solyc00g174330.2); Pathogenesis-related protein 1b (PR-1b; Solyc00g174340.1); Pathogenesis-related protein-like protein (PR like; Solyc04g064880.2); Pathogenesis-related protein 4b (PR-4b; Solyc01g097240.2); Beta-glucanase (Solyc01g060020.2); Endochitinase (Solyc02g082920.2); Thaumatin-like protein (Solyc12g056360.1); Osmotin-like protein (Solyc08g080640.1); 4-coumarate CoA ligase (4CL; Solyc03g117870.2); Chalcone synthase 1 (CHS1; Solyc09g091510.2); Chalcone synthase 2 (CHS2; Solyc05g053550.2); Chalcone isomerase (CHI; Solyc02g067870.2); Cinnamoyl-CoA reductase (CCR; Solyc03g116910.2); Cinnamyl alcohol dehydrogenase (CAD; Solyc01g107590.2); Caffeoyl-CoA O-methyltransferase (CCoAOMT; Solyc02g093250.2); Flavanone 3- hydroxylase-like protein (F3H; Solyc03g080190.2); Flavonol synthase (FLS; Solyc06g083910.2); Dihydroflavonol 4-reductase (DFR; Solyc02g085020.2); Anthocyanidin synthase (ANS; Solyc10g076660.1); and UDP flavonoid 3- O-glucosyltransferase (UFGT; Solyc10g083440.1).

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Finally, dihydroflavonols can be converted to anthocyanins, in a series of reactions catalyzed by dihydroflavonol reductase (DFR), anthocyanidin synthase (ANS) and UDP-glucose:flavonoid 3-O-glucosyl transferase (UFGT) (Petrussa et al., 2013). Expression levels of DFR and UFGT were significantly down-regulated in plants infested with T. urticae and A. lycopersici simultaneously. The tomato genome possesses eight genes encoding ANS, of which four were on the array. Out of these four, one was induced by T. urticae (shown in FIGURE 4.4), two did not change in response to any of the mites, and one was down-regulated by T. urticae as well as by A. lycopersici. Taken together, both A. lycopersici and T. urticae affect genes involved in flavonoid as well as anthocyanin biosynthesis, whereas expression levels did not change in response to T. evansi. However, the consequences of these effects remain inconclusive since for many of these homologs it is unknown if they are tissue-specific and which encode for the rate-limiting enzymes. Future work should include (1) a (targeted) metabolomics approach to reveal the consequences of these transcriptional changes for flavonoid/anthocyanin levels, and also (2) the possible effects on mite performance.

Genes differentially regulated in Aculops lycopersici-infested plants in comparison to uninfested plants Genes of which the expression was affected most strongly by A. lycopersici are divided below in several categories i.e., coding for: (1) defense proteins, (2) proteins involved in cell wall modification, (3) R-gene proteins and (4) other proteins. Furthermore, genes down-regulated by A. lycopersici are discussed (5). The complete list of the top-50 most strongly up- and down-regulated genes is shown in TABLE S4.1A and B, respectively.

Defense proteins Genes from several of the major PR-gene families were among the top-50 most highly up-regulated genes, including members of the family PR-1 (PR-1b; #31 in TABLE S4.1A), PR-2 (β-1,3-glucanase; #10) and PR-3 (chitinase; #16), (acidic chitinase; #39), (endochitinase; #49). Three peroxidases were highly up-regulated as well (#3, #6, #25). The closest homolog in Arabidopsis (score: 398; E-value: 1e-111) of the highest A. lycopersici-induced peroxidase (#3) is a cell-wall bound peroxidase, named AtPRX71, which plays a role in the lignification of cell walls (Shigeto et al., 2013). Furthermore, also a thaumatin-like protein (#43) as well as a gene annotated as Major allergen Mal d 1 (#32) were highly up-regulated by A. lycopersici. The Major allergen Mal d 1 is similar to a NCBI sequence annotated as Tomato Stress Induced-1 (TSI- 1) (GB: Y15846.1), which is highly homologous to the potato (Solanum tuberosum) STH-2 gene (Matton et al., 1993) and inducible by SA and Fusarium oxysporum infections (Sree Vidya et al., 1999).

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Cell wall modification Plants possess a large array of enzymes involved in cell wall formation and modification but which can also affect disease susceptibility, for instance because they inhibit the activity of phytopathogen-secreted cell-wall degrading enzymes (CWDEs). Examples of CWDEs that can be inhibited by plant proteins are polygalacturonases, pectinesterases, pectin lyases, pectate lyases, xylanases and endoglucanases (Juge, 2006; Cantu et al., 2008; Wolf et al., 2012). Aculops lycopersici caused a significant 6-fold increase in the expression of a gene annotated as xylanase inhibitor (Solyc01g079940.2), and, notably, this response was triggered by A. lycopersici only and not at all by T. urticae or T. evansi (note that this gene is not listed in TABLE S4.1B as it represented number 63 and was therefore not in the top-50). Unfortunately, xylanase inhibitors have not been characterized yet in tomato, and there are at least 18 loci annotated as xylanase inhibitor. It is likely that many of these genes serve primarily to regulate non-pathogenesis related develop- mental processes, which may involve cell wall modifications. Nevertheless, there are indications that xylanase inhibitors can also enhance the resistance to cell-wall degrading pathogens (Moscetti et al., 2013). Hence, given that xylans are a major component of plant cell walls, it could be that xylanases are important in pathogenicity, as shown for example for Botrytis cinerea (Brito et al., 2006). However, no genes annotated as xylanase were found in the A. lycopersici genome. A gene that is related to the xylanase inhibitor is the xyloglucan-specific endoglucanase inhibitor protein (XEGIP; GB: DQ056434), which was found to inhibit the activity of the fungal xyloglucan-specific endoglucanase (XEG) (Qin et al., 2003). Although the levels were not significantly different from those in control plants, XEGIP was most strongly induced by A. lycopersici when compared to the induction by other mite species. Also two other CWDE inhibitors, i.e., an inhibitor of polygalacturonase (Solyc07g065090.1) and an inhibitor of pectinesterase (Solyc11g005820.1), were not regulated by A. lycopersici, nor by T. urticae or T. evansi. Several concanavalin A-like lectin/glucanases have been found in the genome of A. lycopersici, as well as in the genome of T. urticae, and some of these carry a signal peptide, which suggests that in theory these mites could be secreting glucanases when piercing the plant cell to feed (see CHAPTER 6, General discussion). Taken together, it could be that A. lycopersici secretes proteins that degrade polysaccha- rides in the plant cell wall to make penetration of it easier, analogous to what has been described for pathogens and nematodes (Mitreva-Dautova et al., 2006). Several cell-wall-modification-associated genes, including an unknown protein with an extensin-like region (#7) and a pectate lyase (#24) were strongly up-regulated by A. lycopersici (TABLE S4.1B). Extensins are hydroxyproline-rich glycoproteins that form cross linked networks in the plant cell walls thereby strengthening it, which

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may well be part of a plant’s defense response (Showalter, 1993). The unknown protein with an extensin-like region (#7) corresponds to an NCBI sequence called LEMMI8 (GB: Z46674.1), which was found to be induced upon giant cell formation during root-knot nematode (Meloidogyne) infections (Van der Eycken et al., 1996). LEMMI8 was also up-regulated by T. urticae, although only 4-fold in comparison to control plants, but not by T. evansi. Hence, this suggests that A. lycopersici and gall- inducing nematodes, which both induce SA (Uehara et al., 2010), may have similar effects on cell wall metabolism. The pectate lyase (#24) was also up-regulated by T. urticae (7-fold compared to control plants), as well as by T. evansi, although less strongly by the latter (3-fold). Pectate lyases are involved in the degradation of the structural cell wall polysaccha- ride pectin. In addition, they cause the release of oligogalacturonides from the plant cell wall, which are perceived as elicitors by some plants leading to the activation of induced plant defenses (De Lorenzo et al., 1991; Doares et al., 1995). Pectate lyases can also be produced and secreted by plant pathogens, thereby softening the leaf tissue and facilitating pathogen growth (Marín-Rodríguez et al., 2002). Taken together, whereas both A. lycopersici and T. urticae have a relatively strong effect on genes involved in cell wall modification, this response is much less apparent in the case of T. evansi. Also, it remains to be investigated to what extent these changes are a response of the plant, for instance to repair damaged plant tissue, or whether these changes are caused by the attacker to facilitate the infestation. The xylanase inhibitor was the only CWDE inhibitor specifically induced by A. lycopersici. Whether CWDEs cause pathogenicity of mites could be investigated by silencing their expression and assessing the consequences for mite performance and/or damage symptoms on tomato.

R-genes Among the most strongly induced genes by A. lycopersici were several Resistance- genes (R-genes). R-proteins are sensors that recognize pathogen secreted proteins and are hard-wired to defenses, like the hypersensitive response, to limit the spread of the disease (Bent & Mackey, 2007). Genes that share structural homology with R-genes that were induced included a disease resistance response protein (TABLE S4.1A; #1), a NBS- LRR class disease resistance protein (#36), and an EIX (Ethylene Inducing Xylanase 2) receptor (#11) (Ron & Avni, 2004). EIX receptor genes are homologous to the Ve and Cf resistance genes of tomato (Ron & Avni, 2004) and bind EIX, which is a fungal xylanase elicitor (Bailey et al., 1990). It has been shown that EIX2, but not EIX1, is essential for mediating defense responses in tobacco (N. tabacum) plants (Ron & Avni, 2004). Tetranychus urticae also induced the EIX2 gene, but not the xylanase inhibitor.

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Other genes Other interesting candidates on the top 50 list of up-regulated genes included three WRKY transcription factors (TABLE S4.1A; #9; #15; #38), which play major roles in regulating plant responses to pathogens (Pieterse et al., 2012), members of the 1- aminocyclopropane-1-carboxylate (ACC) oxidase gene family (#22; #23; #30), involved in ethylene biosynthesis (Barry et al., 1996), and SAMT (#35), which converts SA into methyl salicylate (Ament et al., 2010). Also a syntaxin (#20) was up-regulated by A. lycopersici, as well as by T. urticae. BlastP analysis against the TAIR database, using the protein sequence obtained from the DNA sequence of this gene (Solyc01g006950.2) revealed that this gene has the highest sequence homology with AtSYP121 (score: 411; E-value: e-115). Plants in which this gene was mutated allowed for a higher number of penetrations by barley powdery mildew (Blumeria graminis sp. hordei) (Collins et al., 2003), indicating that SYP121 plays a role in resistance at the plant cell wall.

Tomato genes down-regulated by Aculops lycopersici About 10% of the top-50 of genes most strongly down-regulated by A. lycopersici encoded proteins for chlorophyll metabolism, photosynthesis and/or carbon fixation including a protochlorophyllide reductase (TABLE S4.1B; #14), proteins related to photosystem II (#45; #50) and light harvesting complexes (chlorophyll a-b binding protein; #26; #31). Although not in the top-50, the expression of three Ribulose-1 5-bis- phosphate carboxylase (RuBisCO) genes was also significantly down-regulated by A. lycopersici. Down-regulation of photosynthesis is commonly observed in plants subjected to biotic attack and this can be part of the plant’s JA-dependent defense response (Creelman & Mullet, 1997; Bilgin et al., 2010). However, the same phenomenon can also be due to the blockage of resource allocation leading to sucrose accumulation which is hard-wired to photosynthesis and down-regulates it, as observed for some pathogens (Kocal et al., 2008) and nematodes (Cabello et al., 2014). Some pathogens hijack the plants sugar metabolism via secreted cytokinins (Walters & McRoberts, 2006), also typically produced by gall-inducing arthropods (Yamaguchi et al., 2012). Although A. lycopersici does not produce galls, it may secrete cytokinins like other eriophyoids have been suggested to do (De Lillo & Monfreda, 2004).

Comparison between transcriptional responses induced by Tetranychus urticae and Aculops lycopersici Subsequently, we compared transcriptional responses induced by T. urticae and A. lycopersici by selecting the top-15 genes that were (a) most strongly up-regulated relative to the control by T. urticae but not regulated by A. lycopersici, (b) most strongly up-regulated relative to the control by A. lycopersici, but not regulated by T.

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urticae, (c) most strongly up-regulated relative to the control by T. urticae and also significantly up-regulated by A. lycopersici, or (d) most strongly down-regulated relative to the control by T. urticae and also significantly down-regulated by A. lycopersici (TABLE S4.2A-D). Among the genes specifically up-regulated by T. urticae were four proteinase inhibitors (TABLE S4.2A; #2; #3; #7; #9), as well as a polyphenol oxidase (#10). In contrast, genes induced by A. lycopersici, but not by T. urticae, included the xylanase inhibitor described in the previous section (#2), an expansin (#3) and two GDSL esterases (#4; #6) (‘GDSL’ refers to a conserved protein motif). GDSL esterases/ lipases are extracellular glycoproteins with multiple functions predominantly associated with lipid metabolism (Chepyshko et al., 2012). To date, only a few members have been characterized which play roles in plant development (Ling et al., 2006) and in plant immunity (Hong et al., 2008; Kim et al., 2013). In the tomato genome over a 100 GDSL esterases/lipases are annotated, but the family is largely uncharacterized. Out of the 54 GDSL esterases/lipases on the array, eight were up-regulated by A. lycopersici, whereas six were down-regulated. Five of the A. lycopersici-down-regulated GDSL esterases were also suppressed by T. urticae, whereas four were induced by both species. Only one GDSL esterase was regulated by T. evansi. Without individual characterization of these genes it is hard to speculate on their role in mite- induced plant responses. A possibly relevant gene specifically up-regulated by A. lycopersici (3-fold) was a gibberellin-regulated protein 2 (Solyc02g083880.2) (#20 and thus not listed in TABLE S4.2B). Notably, two other gibberellin-regulated proteins were up-regulated by both T. urticae and A. lycopersici, yet not by T. evansi, and the same was true for a gene annotated as gibberellin receptor GID1L2 (Solyc10g050880.1). Three gibberellin-regulated proteins were down-regulated by T. urticae, yet not by A. lycopersici nor by T. evansi. Since gibberellin and JA are known to antagonize each other’s action (Hou et al., 2013), it could be that gibberellin plays a role in the A. lycopersici-mediated inhibition of the JA-response, analogous to the scenario suggested for the necrotrophic fungus Fusarium moniliforme which produces gibberellin, possibly to disable JA-mediated defenses (Navarro et al., 2008; cf. also FIGURE 4.2). Supporting this hypothesis, a putative ent-kaurene oxidase (Solyc04g083160.1), which in Arabidopsis is known to be involved in biosynthesis of gibberellin (GA) (Helliwell et al., 1999), was 2-fold up-regulated by A. lycopersici. However, other genes involved in GA biosynthesis, for instance the GA 20-oxidases (SlGA20ox1, -2, and -4), were not significantly regulated by A. lycopersici indicating that more research, such as a direct determination of GA levels, is required to make conclude on the effect of A. lycopersici on GA signaling. Yet, since GA also has been implicated in trichome branching and development

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(An et al., 2012) and considering the strong effect russet mites have on trichomes (Van Houten et al., 2013) it seems worthwhile to investigate this lead on the role of GA in the tomato-russet mite interaction in more detail. Among the genes most strongly up-regulated by T. urticae, but also by A. lycopersici, were SA-responsive genes, including PR1b and β-glucanase (#13; #6; respectively). Other genes that were up-regulated by both species included SAMT (#7) and an ACC-oxidase (#10) (TABLE S4.2C). Genes that were most strongly down-regulated by T. urticae but also by A. lycopersici included photosynthesis-related genes (i.e., photosystem I reaction center subunit VI; #13), genes related to cell-wall modification (2 XET/XTHs; #1; #5) and lignin biosynthesis (CCoAOMT; #12) as well as auxin signaling (indole-3-acetic acid-amido synthetase GH3.8 and auxin response factor 9; #2; #7). In rice, indole-3-acetic acid–amido synthetase was shown to prevent the accumulation of auxin and this consequently suppressed expression of expansins and enhanced plant resistance (Ding et al., 2008). Thus, down-regulation of indole-3- acetic acid-amido synthetase may have as a consequence that suppression of expansins is prevented and plant resistance is decreased. Of the 21 expansins on the array, four were induced and one was down-regulated by A. lycopersici. The most strongly A. lycopersici-induced expansin (TABLE S4.2B; #3) is highly homologous to the expansin A8 gene, encoding an enzyme involved in cell wall extension which, in Brassica oleracea, has been connected to auxin-dependent growth responses in plants (Esmon et al., 2006). Possibly, up-regulation of this gene is related to a typical growth-related symptom of russet mite infestation, namely the russet mite-induced ‘curling’ of the leaves (FIGURE 1.5).

Comparison between transcriptional responses induced by Tetranychus urticae and T. evansi Finally, we compared the tomato transcriptional responses to feeding by the two suppressor species T. evansi and A. lycopersici by selecting the top-15 genes that were (a) most strongly up-regulated compared to the control by T. evansi but not regulated by A. lycopersici, (b) most strongly up-regulated compared to the control by A. lycopersici but not regulated by T. evansi, (c) most strongly up-regulated compared to the control by T. evansi and also significantly up-regulated by A. lycopersici, or (d) strongest down-regulated compared to the control by T. evansi and also significantly down-regulated by A. lycopersici (TABLE S4.3A-D). Strikingly, the magnitude of up- and down-regulation for most genes was much larger for A. lycopersici than for T. evansi (TABLE S4.3A-D). This can reflect a funda- mental difference between these two mites, but may also have been caused by differences in their densities (i.e., maybe at lower A. lycopersici densities the two

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responses would have been more similar). Among the genes specifically up-regulated by T. evansi was a MYB transcription factor (TABLE S4.3A; #3), called Abscisic acid induced MYB1 (AIM1: an R2R3MYB protein) (AbuQamar et al., 2009). AIM1 is homologous to the Arabidopsis MYB78 (At5G49620) (score: 654; E-value: 3.5e-65) and MYB108/BOS1 (At3G06490) (score: 639; E-value: 2.2e-67) and mediates ABA responses to Botrytis cinerea as well abiotic stresses such as salinity and oxidative stress in tomato (AbuQamar et al., 2009). Among the genes up-regulated most strongly up-regulated by A. lycopersici, but not by T. evansi, were several genes associated with SA-defenses, such as a WRKY transcription factor (TABLE S4.3B; #6), a β-glucanase (#4), two peroxidases (#2; #13) and an unknown protein with an extensin-like region (#3), which is again the LEMMI8 discussed previously (in the section Genes differentially regulated in A. lycopersici- infested plants in comparison to uninfested plants). Among the genes most strongly up-regulated by T. evansi and also by A. lycopersici was a Ribonuclease T2 (TABLE S4.3C; #2). Ribonuclease T2, which is also up-regulated by T. urticae, is associated with phosphate starvation, ethylene responses, and programmed cell death. Silencing Ribonuclease T2 delays leaf senescence and abscission (Lers et al., 2006). Also two cell-wall related genes, i.e., a pectinesterase (#4) and a pectate lyase (#9), as well as SAMT (#8) were up-regulated by T. evansi and A. lycopersici, albeit all of these to higher levels by A. lycopersici than by T. evansi. The JA-biosynthesis enzyme AOS (#6), of which tomato has only a single copy in its genome, was induced up to similar levels by the three mite species. SAMT levels induced by T. urticae were approximately 2-fold higher compared to those induced by A. lycopersici and approximately 5-fold higher compared to those induced by T. evansi, indicating that both ‘suppressor’ mites may partially down-regulate it’s expression coinciding with lower levels of JA (FIGURE 4.1). In contrast, the Ribonuclease T2 was induced almost 2-fold higher by T. urticae than by T. evansi but 2-fold lower than by A. lycopersici. Furthermore, the expression patterns of the pectinesterase and the pectate lyase were induced to comparable levels by A. lycopersici and T. urticae, whereas their expression levels were 2- to 3-fold lower in response to T. evansi. Hence, the expression of these genes parallels the accumulation of both JA and SA, and may be (partly) dependent on JA-accumulation, as JA was found to mediate modifications of the cell-wall pectin matrix, thereby increasing its defensive properties (Taurino et al., 2014). Finally, genes that were down-regulated by both mite species included a cell-wall located arabinogalactan protein (TABLE S4.3D; #8), as well as the auxin response factor 9 (ARF9) (#1). ARF9 was found to be a repressor of auxin signaling (Zouine et al., 2014). Interestingly, it appeared that two of the four Auxin F-box 5 proteins (AFB5) on the array (Solyc02g079190.2 and Solyc06g008780.1), both close homologs of the

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Arabidopsis auxin receptor TIR1 (At3G62980; score: 642; E-value: 0.0 and score: 1290; E-value: 1.4e-139, respectively), were down-regulated by A. lycopersici but not by T. evansi, nor by T. urticae. AFB5 was discovered to function as part of an auxin co-receptor (Villalobos et al., 2012) and down-regulation of auxin signaling can be mediated by SA and is associated with anti-pathogen defenses (Wang et al., 2007; Kazan & Manners, 2009). Hence, it could be that in A. lycopersici-infested plants auxin signaling is antagonized by SA. However, the relationship between auxin and anti-herbivore defenses still remains to be elucidated (Meldau et al., 2012).

Conclusions To obtain a broader overview of responses induced by mites we have compared the transcriptional responses and phytohormonal rearrangements induced during feeding by three different mites species on tomato. Tetranychus urticae feeding caused a 2- to 3-fold increase in the accumulation of JA, JA-Ile and SA, which was accompanied by the induction of well-known JA- and SA-dependent defense genes, including wound-induced proteinase inhibitors and PR-proteins, in line with previous results (Kant et al., 2004, 2008; Alba et al., submitted). In total, T. urticae regulated 2014 genes (TABLE 4.1). The phytohormonal and transcriptional profile in T. evansi-infested leaflets differed markedly from that in leaflets fed upon by T. urticae, even though the two species are closely related. Tetranychus evansi did not induce the accumulation of JA, nor that of ABA, whereas levels of JA-Ile and SA were only slightly increased in comparison to control plants. Most strikingly, T. evansi regulated only 274 genes (TABLE 4.1), which is ca. 8× less than the number regulated by T. urticae and A. lycopersici. Furthermore, the magnitude of up and down-regulation in response to T. evansi was much lower than for the genes that respond to T. urticae and A. lycopersici feeding, which is remarkable given that T. evansi is known to cause ca. 2-fold more tissue damage on tomato compared to T. urticae after 7 days of infestation (Alba et al., submitted). Related to this, despite the fact that T. evansi causes more visual feeding damage to the leaf blade, the undamaged tissues of T. evansi-infested leaflets stay longer green and ‘healthy’ compared to those infested with T. urticae which senesce almost twice as fast during the course of the infestation. Tetranychus urticae and T. evansi also differ in the kind of visual feeding-damage symptoms they cause: whereas T. evansi feeding results in the formation of small, white-coloured chlorotic lesions, these lesions get surrounded by small areas of brownish and senesced tissue and sometimes micro-oedema in the case of T. urticae, reminiscent of hypersensitive-like responses (Alba et al., submitted). Aculops lycopersici belongs to the eriophyoid mites, which feed on epidermal cells. Interestingly, eriophyoid mites are thought to have evolved their stylet structure

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and support to feed on plants completely independent from the Tetranychidae (Lindquist et al., 1996). Aculops lycopersici induced the accumulation of JA-related phytohormones as well as that of SA and regulated a total of 2219 genes (TABLE 4.1) of which 50% was also regulated by T. urticae. Hence, the total number of genes regulated by T. urticae and A. lycopersici was comparable, and even showed considerable overlap, even though the effect on the JA-pathway was markedly different (FIGURE 4.3). Yet, there also appeared to be specificity in the response: for instance a xylanase inhibitor was specifically induced by A. lycopersici and also some GA-related genes appeared to be specifically affected by A. lycopersici (FIGURE 4.2), possibly indicating differential effects of these mites on tissue growth/cell proliferation. Experiments with plants in which the expression of A. lycopersici-induced genes are silenced (e.g., the xylanase inhibitor) would be necessary to test to which extent these genes affect the susceptibility of tomato to A. lycopersici and to which extent these are related to the growth distortions that occur on tomato plants with high population densities of A. lycopersici. In summary, our visual observations underscore the transcriptome results that T. evansi and T. urticae have very different effects on their host plant: whereas T. evansi has adapted in such a way that it is not, or hardly, recognized by the plant at all, T. urticae, as well as A. lycopersici, elicit strong responses in tomato, although they are not the same. The question that remains is how T. evansi manages to suppress host defense responses. Suppression of host plant responses has been described for species with life styles different from that of spider mites, for instance galling insects, like the tephri- tid fly Eurosta solidaginis and the gelechiid moth Gnorimoschema gallaesolidaginis which did not induce the accumulation of JA and SA in stems of Solidago altissima plants (Tooker et al., 2008; Tooker & De Moraes, 2009). Similarly, also phloem-feeding aphids have been reported to elicit only weak responses in Nicotiana attenuata (Voelckel et al., 2004). It could be that, like gall-inducing pathogens (Deeken et al., 2006) and gall-inducing insects (Tooker et al., 2008; Compson et al., 2011), T. evansi is somehow able to interfere with the plant’s source-sink relationships and maybe can block induced senescence thereby explaining why T. evansi attacked leaflets remain relatively ‘healthy and green’ as compared to leaflets that are attacked by the ‘inducer’ species T. urticae. It has been suggested that plants respond to herbivory by down-regulating the expression of photosynthesis-related genes (Creelman & Mullet, 1997) and re-allocating resources, i.e., transporting resources away from the herbivore-damaged tissues to unattacked parts of the plants, like for instance the roots (Schwachtje et al., 2006). As shown in tomato, this process can be stimulated by JA (Gómez et al., 2010), but does not necessarily depend on it, as was shown in a study using N. attenuata

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(Schwachtje et al., 2006). However, according to an alternative second hypothesis, JA and herbivory may also cause an increased flow of resources from unattacked parts of a plant to the attacked parts to support or increase the production of defenses there (Schultz et al., 2013; Ferrieri et al., 2013). Because these defenses are costly to produce this may lead to a reduction of resources in the unattacked parts of the plant, as shown by Machado et al. (2013). Possibly T. urticae and A. lycopersici, which both induce strong accumulation of JA, stimulate re-allocation of resources, i.e., away from the attacked tissues, whereas in T. evansi-infested leaflets this process is blocked or even reversed if such leaves become sinks. Hence, this could imply that the suppression of JA and SA-related defenses is actually a side-product of a more general mechanism by which T. evansi interferes with the source-sink physiology of its host. Yet, following the second hypothesis of increased resource flow to the attacked tissues, it could also be that T. evansi suppresses defenses just to prevent the (local) depletion of resources from which not only the plant but also the mite ultimately would suffer. Induction of defenses in response to T. urticae and A. lycopersici would, according to this theory, increase resource flow but also cause the (local) depletion of resources, as they are used for the activation of defenses. Hence, this scenario argues against the T. evansi ‘sink hypothesis’. To speculate a bit further on this, it could also be that T. evansi somehow has evolved a way to optimize the balance between defense and availability of resources: i.e., it may increase (JA-dependent) sink strength, while at the same time suppressing JA-dependent downstream responses. Whether induction of JA can lead to an increase in sink strength could be tested by making use of def-1 plants, which are deficient in the induced expression of JA-dependent defense genes.

Acknowledgements We thank Harold Lemereis, Ludek Tikovsky and Thijs Hendrix for growing the toma- to plants and Michel de Vries for assistance with the LC-MS measurements.

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127 JorisGlas-chap4_Gerben-chap2.qxd 26/05/201400:25Page128 128 C TABLE S4.1A List of top 50 genes up-regulated by Aculops lycopersici (A) as compared to control (C). HAPTER # Primary accession Locus identifier No. matching Annotation** Average relative expression (cv. Heinz genome) probes* (C) ± SE (A) ± SE P *** 1 BF097728 Solyc01g021600.2 1 Disease resistance response protein 1.0±0.1 31.0±4.6 <0.001 4 2 X79337 Solyc05g007950.2 1 Ribonuclease T2 1.0±0.2 20.2±2.5 0.001 |

3 AK325152 Solyc01g105070.2 2 Peroxidase 1.0±0.1 17.6±4.8 0.005 M 4 TA53900_4081 Solyc02g062890.1 1 Myo-inositol transporter 2 1.10.2 17.7±6.2 0.003 ITE -

5 BW692867 Solyc05g014590.2 1 Transcription Factor 1.0±0.2 14.3±1.2 0.001 TRANSCRIPTOME INDUCED 6 TA38392_4081 Solyc03g006700.2 2 Peroxidase 1.0±0.2 14.2±5.4 0.013 7 BI203929 Solyc04g071070.2 2 Unknown Protein (Extensin-like region) 1.0±0.2 13.4±6.8 0.015 8 AI779401 Solyc06g034370.1 1 Pectinesterase 1.0±0.2 12.8±3.3 0.004 9 TA55334_4081 Solyc02g071130.2 1 WRKY transcription factor 29 1.0±0.1 12.3±1.9 0.001 10 M80608 Solyc01g060020.2 13 Beta-glucanase 1.0±0.2 11.9±4.9 0.011 11 TA56617_4081 Solyc07g008600.1 2 LRR receptor-like serine (EIX Receptor 2) 1.0±0.1 11.8±2.2 0.001 12 BI421164 Solyc03g098740.1 1 Kunitz trypsin inhibitor 1.0±0.0 10.7±6.1 0.047 13 AK326143 Solyc06g075690.2 2 Auxin-regulated protein 1.0±0.1 10.5±2.6 0.001 14 BI421969 Solyc01g080570.2 1 Inosine-uridine preferring nucleoside hydrolase family protein 1.0±0.2 10.4±2.0 0.008 -

15 AK325041 Solyc08g067340.2 3 WRKY transcription factor 1.0±0.3 10.1±4.2 0.004 TOMATO IN CHANGES WIDE 16 CK468696 Solyc04g072000.2 1 Chitinase 1.0±0.1 9.9±2.7 0.006 17 DB687120 Solyc02g036480.1 1 Harpin-induced protein-like 1.0±0.1 9.6±1.3 0.002 18 AK320983 Solyc10g078230.1 1 Cytochrome P450 1.10.1 10.0±1.9 0.006 19 AK328976 Solyc01g073820.2 1 CHP-rich zinc finger protein-like 1.0±0.1 9.4±1.6 0.002 20 AK327896 Solyc01g006950.2 1 Syntaxin 1.0±0.2 9.3±2.2 0.004 21 AI781281 Solyc09g072810.2 1 Receptor like kinase 1.0±0.1 9.2±1.4 0.002 22 AK320817 Solyc09g010000.2 2 1-aminocyclopropane-1-carboxylate oxidase-like protein 1.0±0.2 8.9±2.1 0.002 23 BE451616 Solyc11g007890.1 1 1-aminocyclopropane-1-carboxylate oxidase 4 1.0±0.1 8.6±1.9 0.006 24 X55193 Solyc02g093580.2 3 Pectate lyase 1.0±0.2 8.6±2.0 0.003 25 AK320453 Solyc05g052280.2 1 Peroxidase 1.0±0.1 8.4±2.7 0.006 26 AK321158 Solyc08g068680.2 3 Decarboxylase family protein 1.0±0.2 8.4±1.3 0.007 27 TA36742_4081 Solyc09g090980.2 1 Major allergen Mal d 1 1.0±0.1 8.3±1.5 0.004 28 AW039918 Solyc01g080800.2 1 PBSP domain-containing protein 1.10.1 8.7±1.6 0.002 29 BI205317 Solyc12g049030.1 1 Fatty acid desaturase 1.0±0.3 8.0±1.9 0.001 30 X04792 Solyc07g049530.2 3 1-aminocyclopropane-1-carboxylate oxidase 1.0±0.2 7.6±2.0 0.002 31 Y08804 Solyc00g174340.1 4 Pathogenesis-related protein 1b 1.0±0.2 7.5±1.4 0.005 JorisGlas-chap4_Gerben-chap2.qxd 26/05/201400:25Page129

32 AK247106 Solyc09g090990.2 1 Major allergen Mal d 1 1.30.4 9.9±1.8 0.014 33 AK322567 Solyc04g040130.1 1 Omega-6 fatty acid desaturase 1.0±0.1 7.4±1.2 0.005 34 AI487343 Solyc10g005320.2 1 Tryptophan synthase beta chain 1 1.0±0.1 7.4±3.7 0.036 35 BI204548 Solyc09g091550.2 2 Salicylic acid carboxyl methyltransferase 1.0±0.3 7.3±1.2 0.013 M

36 AK247049 Solyc07g056200.2 1 NBS-LRR class disease resistance protein 1.0±0.1 7.2±1.1 0.002 ITE 37 AJ010942 Solyc09g075820.2 1 Solute carrier family facilitated glucose transporter member 3 1.0±0.1 7.1±1.0 0.001 - 38 AK328588 Solyc04g072070.2 1 WRKY transcription factor 16 1.0±0.1 7.1±0.9 0.003 TRANSCRIPTOME INDUCED 39 TA38585_4081 Solyc05g050130.2 2 Acidic chitinase 1.0±0.2 7.0±1.1 0.005 40 AK323831 Solyc08g006750.2 1 Decarboxylase family protein 1.0±0.1 6.9±2.2 0.011 41 AK328694 Solyc12g045030.1 1 Short-chain dehydrogenase 1.0±0.2 6.8±1.7 <0.001 42 AK323116 Solyc04g054950.2 2 Tropinone reductase I 1.0±0.1 6.8±2.1 0.005 43 BI422997 Solyc12g056360.1 1 Thaumatin-like protein 1.0±0.1 6.8±0.8 0.002 44 AK325161 Solyc07g053420.2 2 Ring H2 finger protein 1.0±0.1 6.7±1.1 0.007 45 TA38703_4081 Solyc04g048900.2 2 Calreticulin 2 calcium-binding protein 1.0±0.1 6.5±0.6 0.001 46 TA36557_4081 Solyc02g093250.2 1 Caffeoyl-CoA O-methyltransferase 1.0±0.1 6.5±1.0 0.004 47 AK324373 Solyc01g105630.2 1 Calmodulin 1.0±0.1 6.5±0.7 <0.001 48 CK468710 Solyc09g011590.2 3 Glutathione S-transferase-like protein 1.0±0.1 6.5±0.9 0.003 - 49 AK322555 Solyc02g082920.2 3 Endochitinase (Chitinase) 1.0±0.2 6.5±1.4 0.001 TOMATO IN CHANGES WIDE 50 TA56994_4081 Solyc03g093890.2 1 Myb-related transcription factor 1.0±0.1 6.4±0.8 0.005 * E-value: match smaller or equal to 1E-20 (corresponding to maximally three mismatches with target sequence) ** Sequences without annotation (‘unknown proteins’) were excluded *** Filter: genes significantly up-regulated (P<0.05, after P-value adjustment); expression levels of A relative to the control (A/C) were sorted from high to low | C HAPTER 129 4 JorisGlas-chap4_Gerben-chap2.qxd 26/05/201400:25Page130 130 C TABLE S4.1B List of top 50 genes down-regulated by Aculops lycopersici (A) as compared to control (C). HAPTER # Primary accession Locus identifier No. matching Annotation** Average relative expression (cv. Heinz genome) probes* (C) ± SE (A) ± SE P *** 1 AK324667 Solyc11g056680.1 1 LRR receptor-like serine 7.0±0.4 1.3±0.2 0.002 4 2 AK319624 Solyc06g072710.2 2 RNA polymerase sigma factor 4.7±2.7 1.1±0.2 0.020 |

3 TA41641_4081 Solyc07g007260.2 1 Metallocarboxypeptidase inhibitor 3.9±0.5 1.0±0.2 0.012 M 4 ES894162 Solyc08g005680.2 6 Undecaprenyl pyrophosphate synthase 5.3±1.2 1.4±0.3 0.006 ITE -

5 AK321585 Solyc10g008720.2 1 GDSL esterase 5.7±1.1 1.5±0.4 0.042 TRANSCRIPTOME INDUCED 6 AF022022 Solyc03g120380.2 1 Auxin response factor 9 4.0±0.8 1.1±0.3 0.015 7 AK323165 Solyc09g082660.2 1 Caffeoyl-CoA O-methyltransferase 7.3±0.6 2.2±0.4 0.016 8 AK320870 Solyc07g018240.1 1 Elongation of very long chain fatty acids protein 4 5.3±0.6 1.6±0.3 0.019 9 AK324470 Solyc04g050730.2 3 GDSL esterase 4.5±0.8 1.4±0.3 0.014 10 GO375339 Solyc08g068480.1 1 Indole-3-acetic acid-amido synthetase GH3.8 5.5±1.2 1.7±0.2 0.002 11 AK326126 Solyc09g059170.1 1 Anthocyanidin 3-O-glucosyltransferase 5.2±0.9 1.7±0.4 0.032 12 AK319952 Solyc03g116730.2 5 Stearoyl-CoA 9-desaturase 3.6±0.6 1.2±0.3 0.014 13 AK322811 Solyc01g110570.2 1 Auxin-induced SAUR-like protein 5.7±1.7 2.0±0.5 0.001 14 AK319568 Solyc10g006900.2 2 Protochlorophyllide reductase 4.1±0.9 1.4±0.4 0.010 -

15 AK323749 Solyc10g083300.1 1 Beta-fructofuranosidase insoluble isoenzyme 2 4.3±0.8 1.5±0.4 0.010 TOMATO IN CHANGES WIDE 16 AI899566 Solyc01g090970.2 1 Cortical cell-delineating protein 5.1±1.0 1.8±0.9 0.047 17 BP904709 Solyc02g080210.2 3 Pectinesterase 3.4±0.7 1.2±0.4 0.014 18 BI931968 Solyc05g009270.2 2 Fatty acid elongase 3-ketoacyl-CoA synthase 3.2±0.4 1.2±0.2 0.018 19 AK320997 Solyc02g080230.2 1 Rop-interactive crib motif-containing protein 1 4.4±0.5 1.6±0.3 0.013 20 AI771973 Solyc12g055970.1 1 Endoglucanase 1 2.8±0.5 1.0±0.2 0.006 21 TA35934_4081 Solyc02g087400.1 1 Ankyrin repeat domain containing protein 3.4±0.6 1.3±0.3 0.008 22 AK325510 Solyc05g010320.2 2 Chalcone--flavonone isomerase 4.2±0.2 1.6±0.3 0.044 23 AK323669 Solyc08g076820.2 2 BHLH transcription factor 3.6±0.3 1.3±0.3 0.020 24 BI928480 Solyc01g110340.2 2 Endoglucanase 1 3.3±0.7 1.2±0.2 0.037 25 TA38829_4081 Solyc01g006330.2 2 PAP fibrillin family protein 3.7±0.9 1.4±0.2 0.022 26 AK322006 Solyc12g011280.1 1 Chlorophyll a-b binding protein 3.3±0.9 1.3±0.3 0.011 27 AW624057 Solyc04g078900.2 1 Cytochrome P450 3.9±0.8 1.5±0.3 0.011 28 DB718513 Solyc12g094640.1 1 Glyceraldehyde-3-phospha te dehydrogenase B 3.3±0.3 1.3±0.2 0.016 29 BP896662 Solyc02g086180.2 1 Sterol C-5 desaturase 3.8±0.7 1.5±0.2 <0.001 30 TA55690_4081 Solyc05g053400.1 1 Glucosyltransferase 3.3±0.3 1.3±0.2 0.006 31 AK246535 Solyc12g006140.1 1 Chlorophyll a-b binding protein 3.2±1.1 1.2±0.4 0.008 JorisGlas-chap4_Gerben-chap2.qxd 26/05/201400:25Page131

32 AK327204 Solyc09g091510.2 2 Chalcone synthase 4.9±0.7 1.9±0.4 0.043 33 AK247438 Solyc10g018300.1 1 Transketolase 1 3.2±0.7 1.3±0.3 0.016 34 AK320997 Solyc04g081300.2 2 Endoglucanase 1 3.2±0.2 1.3±0.2 0.015 35 DB695486 Solyc03g025190.2 1 Multidrug resistance protein mdtK 5.0±0.5 2.0±0.4 0.029 M

36 AK325110 Solyc04g071340.2 2 Fructose-1 6-bisphosphatase class 1 2.5±0.8 1.0±0.2 0.026 ITE 37 TA36896_4081 Solyc04g054740.2 7 Inositol-3-phosphate synthase 3.4±0.5 1.3±0.2 0.004 - 38 AW625752 Solyc03g083100.2 1 Calmodulin-binding protein family-like 3.7±0.6 1.5±0.1 0.004 TRANSCRIPTOME INDUCED 39 TA36417_4081 Solyc08g067320.1 1 Chlorophyll a 3.4±0.4 1.3±0.3 0.005 40 AK326720 Solyc03g019790.2 2 Alpha-galactosidase 3.2±0.4 1.3±0.3 0.021 41 AK247484 Solyc01g091320.2 1 Sterol 4-alpha-methyl-oxidase 2 2.5±0.2 1.0±0.2 0.024 42 K03290 Solyc08g069010.2 2 Pentatricopeptide repeat-containing protein 3.2±0.5 1.3±0.2 0.008 43 DB707884 Solyc09g065780.2 1 Fatty acid elongase 3-ketoacyl-CoA synthase 2.5±0.8 1.0±0.1 0.025 44 AW039265 Solyc01g108630.2 2 Nitrite reductase 2.5±0.6 1.0±0.2 0.005 45 AI779861 Solyc12g099650.1 1 Photosystem II 5 kDa protein 3.3±0.8 1.4±0.4 0.036 46 AK325398 Solyc05g005080.2 5 Endo-1 4-beta-glucanase 2.4±0.3 1.0±0.2 0.012 47 AI482604 Solyc03g116280.2 2 1-aminocyclopropane-1-carboxylate oxidase 2.8±0.3 1.2±0.1 0.003 48 BT013770 Solyc04g008040.2 2 microtubule associated protein Type 1 3.1±0.5 1.3±0.3 0.011 - 49 TA39716_4081 Solyc06g064550.2 5 Aspartokinase-homoserine dehydrogenase 2.9±0.6 1.2±0.3 0.015 TOMATO IN CHANGES WIDE 50 AK325903 Solyc06g060340.2 5 Chloroplast photosystem II-associated protein 3.4±0.4 1.4±0.2 0.011 * Sequences without annotation (‘unknown proteins’) were excluded ** E-value: match smaller or equal to 1E-20 (corresponding to maximally three mismatches with target sequence) *** Filter: genes significantly down-regulated (P<0.05, after P-value adjustment); expression levels of A relative to the control (A/C) were sorted from low to high | C HAPTER 131 4 JorisGlas-chap4_Gerben-chap2.qxd 26/05/201400:25Page132 132 C TABLE S4.2A List of top 15 genes up-regulated by Tetranychus urticae (U) but not by Aculops lycopersici (A) as compared to control (C). HAPTER # Primary accession Locus identifier No. Annotation** Average relative expression (cv. Heinz genome) matching probes* (C) ± SE (U) ± SE P *** (A) ± SE P (U+A) ± SE P 4 1 BI422799 Solyc10g083690.2 1 Cytochrome P450 1.0±0.2 22.4±7.9 0.009 14.0±7.0 0.072 54.4±27.6 0.003 |

2 AW738222 Solyc03g098720.2 1 Kunitz trypsin inhibitor 1.0±0.2 17.0±5.8 0.015 2.3±0.6 0.053 3.4±1.1 0.13 M 3 TA36831_4081 Solyc03g020080.2 1 Proteinase inhibitor II 1.0±0.2 15.0±5.8 0.004 2.8±1.4 0.19 4.6±1.2 0.012 ITE -

4 AK329507 Solyc04g064880.2 1 Pathogenesis-related protein-like protein 1.0±0.2 14.7±3.4 0.002 8.9±5.4 0.080 52.7±40.2 0.025 TRANSCRIPTOME INDUCED 5 TA53149_4081 Solyc01g106600.2 2 Pathogenesis-related protein 1 1.1±0.1 9.8±1.9 <0.001 1.3±0.3 0.58 7.6±1.3 0.005 6 AI483484 Solyc01g095960.2 2 Diacylglycerol O-acyltransferase 1.0±0.1 7.5±0.9 0.003 1.4±0.3 0.083 2.5±0.5 0.12 7 AK247244 Solyc03g020060.2 1 Proteinase inhibitor II 1.0±0.2 7.5±1.9 0.006 1.3±0.5 0.89 2.6±0.9 0.023 8 TA36864_4081 Solyc10g083700.2 1 Cytochrome P450 1.0±0.1 7.2±2.8 0.024 4.2±1.6 0.073 18.0±9.5 0.013 9 X94946 Solyc03g020050.2 2 Proteinase inhibitor II (CEV157) 1.0±0.1 6.7±2.7 0.023 1.6±0.5 0.27 6.4±3.2 0.065 10 TA39970_4081 Solyc08g074680.2 2 Polyphenol oxidase 1.0±0.1 6.6±1.0 0.012 1.5±0.4 0.15 6.7±1.1 0.008 11 AK320874 Solyc12g045020.1 1 Cytochrome P450 1.2±0.3 7.1±0.9 0.010 4.6±1.2 0.076 9.6±0.5 0.004 12 AK325284 Solyc02g087070.2 1 Peroxidase family protein 1.0±0.1 5.3±0.6 0.003 2.0±0.3 0.066 5.2±1.1 0.008 13 AF092655 Solyc06g074990.1 1 Nitrate transporter 1.0±0.1 5.2±0.9 0.006 3.1±0.8 0.074 8.0±2.2 0.007 -

14 AK320468 Solyc03g097500.2 2 Hydroxycinnamoyl CoA shikimate 1.0±0.1 4.6±0.5 0.004 3.5±1.6 0.078 7.8±1.9 0.009 TOMATO IN CHANGES WIDE 15 TA47283_4081 Solyc10g076680.1 1 1-aminocyclopropane-1-carboxylate oxidase 1.0±0.1 4.5±1.4 0.012 1.4±0.4 0.39 5.0±2.5 0.075 * Sequences without annotation (‘unknown proteins’) were excluded ** E-value: match smaller or equal to 1E-20 (corresponding to maximally three mismatches with target sequence) *** Filter: genes significantly induced by U (P<0.05, after P-value adjustment) and not regulated by A; expression levels of U relative to the control (U/C) were sorted from high to low JorisGlas-chap4_Gerben-chap2.qxd 26/05/201400:25Page133

TABLE S4.2B List of top 15 genes up-regulated by Aculops lycopersici (A) but not by Tetranychus urticae (U) as compared to control (C). # Primary accession Locus identifier No. Annotation** Average relative expression (cv. Heinz genome) matching probes* (C) ± SE (U) ± SE P *** (A) ± SE P (U+A) ± SE P M

1 BG127002 Solyc08g078870.1 3 Proline-rich protein 1.0±0.2 2.7±0.6 0.10 6.3±1.4 0.014 6.9±1.6 0.022 ITE 2 AK323935 Solyc01g079940.2 3 Xylanase inhibitor 1.0±0.2 1.6±0.3 0.17 6.0±2.1 0.010 4.8±0.4 0.007 - 3 ES896026 Solyc09g018020.2 2 Expansin 1.1±0.1 1.0±0.1 0.70 6.4±1.7 0.015 5.6±1.7 0.028 TRANSCRIPTOME INDUCED 4 BW691510 Solyc09g063060.2 1 GDSL esterase 1.0±0.1 1.1±0.1 0.53 5.8±2.1 0.048 3.3±0.6 0.016 5 TA54590_4081 Solyc06g061280.2 1 Cinnamoyl-CoA reductase-like protein 1.0±0.1 1.4±0.2 0.13 5.2±1.5 0.021 5.2±1.0 0.007 6 BT014283 Solyc02g071620.2 1 GDSL esterase 1.0±0.1 1.4±0.2 0.20 5.1±0.8 0.001 5.2±1.4 0.011 7 AK321780 Solyc08g068770.1 1 N-acetyltransferase 1.0±0.2 3.6±1.2 0.063 4.9±0.8 0.024 7.1±1.9 0.009 8 AW223874 Solyc12g070080.1 1 N-acylethanolamine amidohydrolase 1.0±0.2 2.8±0.8 0.053 4.2±1.4 0.011 5.7±1.9 0.043 9 AW649410 Solyc11g067190.1 1 Fatty acyl coA reductase 1.0±0.1 1.8±0.4 0.12 3.9±0.9 0.005 11.8±8.9 0.089 10 AK247396 Solyc08g067390.2 1 Blight-associated protein P12 1.1±0.2 1.7±0.3 0.15 4.0±0.9 0.021 3.2±0.4 0.017 11 BT012962 Solyc05g009430.2 1 Endonuclease 1.0±0.2 1.5±0.3 0.25 3.6±0.5 0.019 3.7±0.7 0.016 12 BI208939 Solyc05g007300.2 2 Receptor expression-enhancing protein 5 1.0±0.1 1.5±0.1 0.10 3.1±0.6 0.019 2.1±0.2 0.019 13 AK321018 Solyc09g082570.2 1 Neurogenic locus notch protein-like 1.0±0.1 1.5±0.1 0.079 3.1±0.4 0.009 2.7±0.3 0.007 - 14 AF514775 Solyc11g065760.1 1 Thymidine kinase 1.0±0.2 1.7±0.5 0.083 3.1±1.1 0.030 2.1±0.2 0.12 TOMATO IN CHANGES WIDE 15 AK322107 Solyc06g072550.2 1 UPF0497 membrane protein 8 1.0±0.3 1.7±0.1 0.076 3.0±0.4 0.007 3.0±0.2 0.012 * Sequences without annotation (‘unknown proteins’) were excluded ** E-value: match smaller or equal to 1E-20 (corresponding to maximally three mismatches with target sequence) *** Filter: genes significantly induced by A (P<0.05, after P-value adjustment) and not regulated by U; expression levels of A relative to the control (A/C) were sorted from high to low | C HAPTER 133 4 JorisGlas-chap4_Gerben-chap2.qxd 26/05/201400:25Page134 134 C TABLE S4.2C List of top 15 genes up-regulated by both Aculops lycopersici (A) and Tetranychus urticae (U) as compared to control (C). HAPTER # Primary accession Locus identifier No. Annotation** Average relative expression (cv. Heinz genome) matching probes* (C) ± SE (U) ± SE P *** (A) ± SE P (U+A) ± SE P 4 1 BE354788 Solyc03g098760.1 1 Kunitz-type protease inhibitor-like protein 1.0±0.3 26.3±6.9 0.001 4.4±1.2 0.017 9.9±2.6 0.002 |

2 AI487343 Solyc10g005320.2 1 Tryptophan synthase beta chain 1 1.0±0.1 22.3±0.8 <0.001 7.4±3.7 0.036 26.9±12.3 0.006 M 3 BI421969 Solyc01g080570.2 1 Inosine-uridine preferring nucleoside ITE -

hydrolase family protein 1.0±0.2 19.6±0.9 <0.001 10.4±2.0 0.008 23.9±5.1 <0.001 TRANSCRIPTOME INDUCED 4 BW692867 Solyc05g014590.2 1 Transcription Factor 1.0±0.2 15.4±2.3 0.002 14.3±1.2 0.001 22.9±3.9 <0.001 5 BI929069 Solyc01g105450.2 1 ABC transporter G family member 11 1.0±0.2 14.8±3.4 0.003 5.0±0.7 0.003 9.9±1.9 0.001 6 M80608 Solyc01g060020.2 13 Beta-glucanase 1.0±0.2 14.8±5.7 0.004 11.9±4.9 0.011 18.3±2.4 0.002 7 BI204548 Solyc09g091550.2 2 Salicylic acid carboxyl methyltransferase 1.0±0.3 13.3±2.5 0.001 7.3±1.2 0.013 13.6±1.6 0.002 8 X79337 Solyc05g007950.2 1 Ribonuclease T2 1.0±0.2 11.3±1.4 0.001 20.2±2.5 0.001 19.7±3.0 0.001 9 AM949788 Solyc02g067750.2 1 Carbonic anhydrase 1.0±0.2 10.9±5.1 0.012 3.3±0.5 0.000 9.2±3.3 0.025 10 X04792 Solyc07g049530.2 3 1-aminocyclopropane-1-carboxylate oxidase 1.0±0.2 10.7±1.8 0.002 7.6±2.0 0.002 16.1±3.7 0.004 11 TA53412_4081 Solyc02g092120.2 1 Phytosulfokines 3 1.0±0.1 10.2±0.7 <0.001 6.4±1.0 0.004 15.9±6.3 0.007 12 BI205317 Solyc12g049030.1 1 Fatty acid desaturase 1.0±0.3 9.8±0.5 0.002 8.0±1.9 0.001 13.6±1.8 0.001 -

13 Y08804 Solyc00g174340.1 4 Pathogenesis-related protein 1b 1.0±0.2 9.8±2.3 0.004 7.5±1.4 0.005 16.3±2.7 0.001 TOMATO IN CHANGES WIDE 14 AK320983 Solyc10g078230.1 1 Cytochrome P450 1.1±0.1 10.0±1.4 0.004 10.0±1.9 0.006 24.6±8.5 0.002 15 TA38392_4081 Solyc03g006700.2 2 Peroxidase 1.0±0.2 9.1±2.0 0.003 14.2±5.4 0.013 25.0±5.2 0.003 * Sequences without annotation (‘unknown proteins’) were excluded ** E-value: match smaller or equal to 1E-20 (corresponding to maximally three mismatches with target sequence) *** Filter: genes significantly induced by U as well as by A (P<0.05, after P-value adjustment); expression levels of U relative to the control (U/C) were sorted from high to low JorisGlas-chap4_Gerben-chap2.qxd 26/05/201400:25Page135

TABLE S4.2D List of top 15 genes down-regulated by both Aculops lycopersici (A) and Tetranychus urticae (U) as compared to control (C). # Primary accession Locus identifier No. Annotation** Average relative expression (cv. Heinz genome) matching probes* (C) ± SE (U) ± SE P *** (A) ± SE P (U+A) ± SE P M

1 AK323038 Solyc09g008320.2 2 Xyloglucan endotransglucosylase 4.8±1.0 1.4±0.3 0.004 2.0±0.5 0.006 1.0±0.3 0.005 ITE 2 GO375339 Solyc08g068480.1 1 Indole-3-acetic acid-amido synthetase 5.5±1.2 1.7±0.4 0.003 1.7±0.2 0.002 1.0±0.3 0.044 - 3 AK319674 Solyc08g063090.2 1 Delta-6-desaturase 4.6±0.9 1.5±0.4 0.018 2.3±0.5 0.041 1.0±0.3 0.008 TRANSCRIPTOME INDUCED 4 AK324667 Solyc11g056680.1 1 LRR receptor-like serine 7.0±0.4 2.3±0.6 0.021 1.3±0.2 0.002 1.0±0.4 0.011 5 AK319483 Solyc07g052980.2 4 Xyloglucan endotransglucosylase 4.0±0.6 1.4±0.3 0.030 1.8±0.3 0.000 1.0±0.4 0.027 6 AK322123 Solyc01g089850.2 1 Cyclin-dependent protein kinase regulator 4.0±0.4 1.5±0.4 0.010 2.1±0.2 0.009 1.0±0.2 0.019 7 AF022022 Solyc03g120380.2 1 Auxin response factor 9 4.0±0.8 1.5±0.0 0.018 1.1±0.3 0.015 1.0±0.2 0.001 8 AK323669 Solyc08g076820.2 2 BHLH transcription factor 3.6±0.3 1.4±0.3 0.016 1.3±0.3 0.020 1.0±0.1 0.000 9 AK322811 Solyc01g110570.2 1 Auxin-induced SAUR-like protein 5.7±1.7 2.3±0.9 0.026 2.0±0.5 0.001 1.0±0.2 0.008 10 AK320904 Solyc02g091690.2 3 BHLH transcription factor 3.3±0.6 1.4±0.2 0.041 1.5±0.2 0.022 1.0±0.1 0.005 11 AI899566 Solyc01g090970.2 1 Cortical cell-delineating protein 5.1±1.0 2.1±0.5 0.001 1.8±0.9 0.047 1.0±0.3 0.036 12 AK323165 Solyc09g082660.2 1 Caffeoyl-CoA O-methyltransferase 7.3±0.6 3.0±0.6 0.029 2.2±0.4 0.016 1.0±0.3 0.016 13 DB690187 Solyc06g066640.2 1 Photosystem I reaction center subunit VI 3.0±0.5 1.2±0.2 0.001 1.4±0.3 0.002 1.0±0.1 0.005 - 14 AK319584 Solyc04g074640.2 3 L-ascorbate peroxidase 3.6±0.6 1.5±0.3 0.005 1.5±0.5 0.029 1.0±0.2 0.015 TOMATO IN CHANGES WIDE 15 AK320997 Solyc02g080230.2 1 Rop-interactive crib motif-containing protein 1 4.4±0.5 1.9±0.3 0.031 1.6±0.3 0.013 1.0±0.2 0.006 * Sequences without annotation (‘unknown proteins’) were excluded ** E-value: match smaller or equal to 1E-20 (corresponding to maximally three mismatches with target sequence) *** Filter: genes significantly down-regulated by U as well as by A (P<0.05, after P-value adjustment); expression levels of U relative to the control (U/C) were sorted from low to high | C HAPTER 135 4 JorisGlas-chap4_Gerben-chap2.qxd 26/05/201400:25Page136 136 C TABLE S4.3A List of top 15 genes up-regulated by Tetranychus evansi (E) but not by Aculops lycopersici (A) as compared to control (C). Tetranychus urticae (U) is shown HAPTER as the benchmark. # Primary accession Locus identifier No. Annotation** Average relative expression (cv. Heinz genome) matching 4 probes* (C) ± SE (E) ± SE P *** (A) ± SE P (U) ± SE P (U+A) ± SE P |

1 AW738222 Solyc03g098720.2 1 Kunitz trypsin inhibitor 1.0±0.2 4.5±1.2 0.010 2.3±0.6 0.053 17.0±5.8 0.015 3.4±1.1 0.13 M 2 U50152 Solyc12g010020.1 2 Leucyl aminopeptidase 1.0±0.2 2.6±1.1 0.032 1.6±0.7 0.78 3.7±1.2 0.048 1.9±0.7 0.27 ITE -

3 EU934734 Solyc12g099120.1 1 MYB transcription factor 1.0±0.1 1.4±0.1 0.025 1.1±0.2 1.0 1.2±0.2 0.74 1.2±0.4 0.95 TRANSCRIPTOME INDUCED 4 BE459432 Solyc07g008210.2 1 TPR domain protein 3.5±0.7 4.8±0.9 0.047 2.5±0.8 0.32 2.0±0.2 0.13 1.0±0.2 0.042 5 BI933877 Solyc12g005310.1 1 Auxin-responsive GH3-like 1.2±0.1 1.6±0.2 0.006 1.2±0.1 0.96 1.0±0.1 0.32 1.1±0.1 0.96 6 BF096497 Solyc09g091950.1 1 Ethylene-responsive transcription factor 1 1.1±0.1 1.5±0.1 0.003 1.0±0.2 0.78 1.3±0.2 0.41 1.0±0.1 0.62 7 BP884866 Solyc10g007680.2 1 Regulator of chromosome condensation RCC1 1.1±0.0 1.5±0.0 0.005 1.0±0.0 0.16 1.0±0.1 0.35 1.1±0.1 0.98 8 BM410063 Solyc05g008040.2 1 ATP-dependent DNA helicase RECG-like 1.0±0.1 1.3±0.1 0.018 1.4±0.1 0.064 1.4±0.0 0.072 1.2±0.1 0.27 9 TC209857 Solyc03g098010.2 1 Acid phosphatase 1.5±0.3 1.9±0.5 0.008 1.0±0.2 0.23 1.2±0.2 0.52 1.1±0.2 0.66 -

10 AK324639 Solyc01g006390.2 1 Cysteine-rich extensin-like TOMATO IN CHANGES WIDE protein-4 1.1±0.1 1.3±0.2 0.018 1.0±0.0 0.82 2.4±0.3 0.003 1.4±0.3 0.42 11 DB685772 Solyc05g014380.2 1 Multidrug resistance protein ABC transporter family 1.0±0.1 1.2±0.0 0.032 1.1±0.1 0.40 1.2±0.1 0.18 1.3±0.2 0.13 12 AI898932 Solyc04g080790.2 2 BEL1-like homeodomain protein 3 1.0±0.1 1.2±0.1 0.027 1.3±0.2 0.20 1.2±0.1 0.34 1.3±0.2 0.26 13 TA56362_4081 Solyc01g098690.2 2 LRR receptor-like serine 1.0±0.1 1.2±0.1 0.013 1.5±0.2 0.053 1.4±0.2 0.092 1.5±0.1 0.011 14 AK321241 Solyc07g045160.2 2 Phosphofructokinase family protein 1.0±0.3 1.2±0.3 0.019 1.3±0.1 0.23 1.3±0.2 0.12 1.3±0.2 0.22 15 TA41814_4081 Solyc09g042750.2 1 Acyl-CoA thioesterase 9 1.0±0.1 1.2±0.1 0.034 1.3±0.1 0.31 1.3±0.1 0.30 1.2±0.1 0.42 * Sequences without annotation (‘unknown proteins’) were excluded ** E-value: match smaller or equal to 1E-20 (corresponding to maximally three mismatches with target sequence) *** Filter: genes significantly induced by E (P<0.05, after P-value adjustment) and not by A; expression levels of E relative to the control (E/C) were sorted from high to low JorisGlas-chap4_Gerben-chap2.qxd 26/05/201400:25Page137

TABLE S4.3B List of top 15 genes up-regulated by Aculops lycopersici (A) but not by Tetranychus evansi (E) as compared to control (C). Tetranychus urticae (U) is shown as the benchmark. # Primary accession Locus identifier No. Annotation** Average relative expression (cv. Heinz genome) matching M P P P P

probes* (C) ± SE (E) ± SE *** (A) ± SE (U) ± SE (U+A) ± SE ITE 1 TA53900_4081 Solyc02g062890.1 1 Myo-inositol transporter 2 1.1±0.2 1.0±0.1 1.0 17.7±6.2 0.003 7.3±1.4 0.003 16.9±2.2 0.001 - 2 TA38392_4081 Solyc03g006700.2 2 Peroxidase 1.0±0.2 1.3±0.2 0.24 14.2±5.4 0.013 9.1±2.0 0.003 25.0±5.2 0.003 TRANSCRIPTOME INDUCED 3 BI203929 Solyc04g071070.2 2 Unknown Protein (Extensin-like region) 1.0±0.2 2.1±0.6 0.12 13.4±6.8 0.015 3.5±0.7 0.003 12.8±4.2 0.005 4 M80608 Solyc01g060020.2 13 Beta-glucanase 1.0±0.2 1.2±0.2 0.60 11.9±4.9 0.011 14.8±5.7 0.004 18.3±2.4 0.002 5 BI421164 Solyc03g098740.1 1 Kunitz trypsin inhibitor 1.0±0.0 1.1±0.1 0.62 10.7±6.1 0.047 8.7±2.7 0.007 45.5±35.8 0.023 6 AK325041 Solyc08g067340.2 3 WRKY transcription factor 1.0±0.3 1.4±0.2 0.20 10.1±4.2 0.004 6.5±1.5 0.002 9.2±2.2 0.013 7 DB687120 Solyc02g036480.1 1 Harpin-induced protein-like 1.0±0.1 1.9±0.4 0.061 9.6±1.3 0.002 7.6±0.5 0.001 13.1±3.3 0.003 8 AK320983 Solyc10g078230.1 1 Cytochrome P450 1.1±0.1 1.0±0.2 1.0 10.0±1.9 0.006 10.0±1.4 0.004 24.6±8.5 0.002 9 AK327896 Solyc01g006950.2 1 Syntaxin 1.0±0.2 1.8±0.6 0.21 9.3±2.2 0.004 6.8±1.2 <0.001 13.4±3.8 0.009 10 AI781281 Solyc09g072810.2 1 Receptor like kinase 1.0±0.1 1.4±0.4 0.52 9.2±1.4 0.002 5.4±0.3 <0.001 10.1±1.5 0.001 11 AK320817 Solyc09g010000.2 2 1-aminocyclopropane- - 1-carboxylate oxidase-like protein 1.0±0.2 1.5±0.2 0.17 8.9±2.1 0.002 4.7±0.9 0.003 10.5±2.2 0.003 TOMATO IN CHANGES WIDE 12 BE451616 Solyc11g007890.1 1 1-aminocyclopropane-1- carboxylate oxidase 4 1.0±0.1 1.2±0.1 0.29 8.6±1.9 0.006 3.1±0.3 0.002 7.2±0.6 <0.001 13 AK320453 Solyc05g052280.2 1 Peroxidase 1.0±0.1 1.2±0.2 0.17 8.4±2.7 0.006 3.9±0.9 0.002 8.9±0.8 <0.001 14 TA36742_4081 Solyc09g090980.2 1 Major allergen Mal d 1 1.0±0.1 1.2±0.3 0.85 8.3±1.5 0.004 6.0±1.0 0.007 11.9±2.8 0.004 15 AW039918 Solyc01g080800.2 1 PBSP domain-containing protein 1.1±0.1 1.0±0.2 0.84 8.7±1.6 0.002 7.6±1.4 0.004 17.0±7.5 0.008 * Sequences without annotation (‘unknown proteins’) were excluded ** E-value: match smaller or equal to 1E-20 (corresponding to maximally three mismatches with target sequence) *** Filter: genes significantly induced by A (P<0.05, after P-value adjustment) and not by E; expression levels of A relative to the control (A/C) were sorted from high to low | C HAPTER 137 4 JorisGlas-chap4_Gerben-chap2.qxd 26/05/201400:25Page138 138 C TABLE S4.3C List of top 15 genes up-regulated by both Aculops lycopersici (A) and Tetranychus evansi (E) as compared to control (C). Tetranychus urticae (U) is shown HAPTER as the benchmark. # Primary accession Locus identifier No. Annotation** Average relative expression (cv. Heinz genome) matching 4 probes* (C) ± SE (E) ± SE P *** (A) ± SE P (U) ± SE P (U+A) ± SE P |

1 BE354788 Solyc03g098760.1 1 Kunitz-type protease inhibitor- M like protein 1.0±0.3 6.3±1.3 0.001 4.4±1.2 0.017 26.3±6.9 0.001 9.9±2.6 0.002 ITE -

2 X79337 Solyc05g007950.2 1 Ribonuclease T2 1.0±0.2 6.1±1.9 0.002 20.2±2.5 0.001 11.3±1.4 0.001 19.7±3.0 0.001 TRANSCRIPTOME INDUCED 3 BW692867 Solyc05g014590.2 1 Transcription Factor 1.0±0.2 4.4±1.0 0.002 14.3±1.2 0.001 15.4±2.3 0.002 22.9±3.9 <0.001 4 AI779401 Solyc06g034370.1 1 Pectinesterase 1.0±0.2 3.8±0.8 0.002 12.8±3.3 0.004 8.1±0.2 0.001 15.3±0.4 <0.001 5 AI487343 Solyc10g005320.2 1 Tryptophan synthase beta chain 1 1.0±0.1 3.4±0.2 0.002 7.4±3.7 0.036 22.3±0.8 <0.001 26.9±12.3 0.006 6 AJ271093 Solyc04g079730.1 2 cytochrome P450 (AOS) 1.0±0.1 3.3±0.7 0.001 4.0±0.4 0.007 4.2±0.7 0.014 4.4±0.7 0.006 7 BI929069 Solyc01g105450.2 1 ABC transporter G family member 11 1.0±0.2 3.0±0.8 0.006 5.0±0.7 0.003 14.8±3.4 0.003 9.9±1.9 0.001 8 BI204548 Solyc09g091550.2 2 Salicylic acid carboxyl methyltransferase 1.0±0.3 2.8±0.6 0.017 7.3±1.2 0.013 13.3±2.5 0.001 13.6±1.6 0.002 9 BI208459 Solyc02g093580.2 3 Pectate lyase 1.0±0.2 2.8±0.6 0.001 8.6±2.0 0.003 7.1±0.8 0.001 11.4±1.9 0.001 -

10 BF097728 Solyc01g021600.2 1 Disease resistance response TOMATO IN CHANGES WIDE protein 1.0±0.1 2.6±0.3 0.001 31.0±4.6 <0.001 7.8±0.4 <0.001 29.4±3.4 <0.001 11 AK326143 Solyc06g075690.2 2 Auxin-regulated protein 1.0±0.1 2.4±0.5 0.024 10.5±2.6 0.001 5.5±0.9 0.001 13.6±3.8 <0.001 12 AK325249 Solyc03g013160.2 1 Amino acid transporter family protein 1.0±0.1 2.3±0.6 0.011 3.1±0.3 0.009 4.5±0.4 <0.001 4.1±0.7 0.004 13 AK327264 Solyc01g109710.2 4 Universal stress protein 1.0±0.2 2.3±0.3 0.026 4.2±0.9 0.013 4.1±0.4 0.004 7.1±2.0 <0.001 14 EG553551 Solyc08g036660.2 1 Protein TIFY 5A 1.0±0.1 2.3±0.2 0.012 6.0±1.0 0.003 7.2±1.2 0.002 11.0±2.0 0.001 15 AK327684 Solyc01g107390.2 1 Auxin-responsive GH3 product 1.0±0.1 2.3±0.4 0.038 3.8±0.7 0.008 7.7±0.8 <0.001 12.0±5.5 0.019 * Sequences without annotation (‘unknown proteins’) were excluded ** E-value: match smaller or equal to 1E-20 (corresponding to maximally three mismatches with target sequence) *** Filter: genes significantly induced by A as well as by E (P<0.05, after P-value adjustment); expression levels of E relative to the control (E/C) were sorted from high to low JorisGlas-chap4_Gerben-chap2.qxd 26/05/201400:25Page139

TABLE S4.3D List of top 15 genes down-regulated by both Aculops lycopersici (A) and Tetranychus evansi (E) as compared to control (C). Tetranychus urticae (U) is shown as the benchmark. # Primary accession Locus identifier No. Annotation** Average relative expression (cv. Heinz genome) matching M P P P P

probes* (C) ± SE (E) ± SE *** (A) ± SE (U) ± SE (U+A) ± SE ITE 1 AF022022 Solyc03g120380.2 1 Auxin response factor 9 4.0±0.8 2.1±0.4 0.007 1.1±0.3 0.015 1.5±0.0 0.018 1.0±0.2 0.001 - 2 AK320214 Solyc03g123410.1 1 Oxalate oxidase-like germin 171 3.5±0.8 2.0±0.6 0.004 2.0±0.8 0.047 1.5±0.6 0.043 1.0±0.1 0.004 TRANSCRIPTOME INDUCED 3 TC213326 Solyc01g088250.2 2 IQ-domain 11 2.5±0.4 1.8±0.2 0.019 1.2±0.1 0.003 1.1±0.0 0.009 1.0±0.2 0.002 4 AK320870 Solyc07g018240.1 1 Elongation of very long chain fatty acids protein 4 5.3±0.6 3.8±0.4 0.018 1.6±0.3 0.019 2.5±0.8 0.015 1.0±0.2 0.028 5 AK320174 Solyc06g061070.2 5 Glycine cleavage system H protein 12.6±0.3 1.9±0.2 0.047 1.4±0.2 0.013 1.5±0.3 0.031 1.0±0.3 0.041 6 TA40164_4081 Solyc02g084610.1 1 LRR receptor-like serine 3.4±0.2 2.4±0.2 0.031 1.6±0.2 0.002 1.6±0.2 0.002 1.0±0.3 0.018 7 AK321042 Solyc04g082710.2 1 Cathepsin B-like cysteine proteinase 3 1.8±0.1 1.3±0.1 0.009 1.1±0.0 0.003 1.1±0.2 0.097 1.0±0.1 0.003 8 GO376269 Solyc01g091530.2 1 Fasciclin-like arabinogalactan protein 13 3.0±0.2 2.2±0.2 <0.001 1.3±0.2 0.013 1.6±0.1 0.003 1.0±0.2 0.014 9 BT012874 Solyc05g043330.2 1 GDSL esterase 3.1±0.7 2.3±0.5 0.015 1.5±0.3 0.012 1.8±0.5 0.043 1.0±0.3 0.007 - 10 AI896455 Solyc07g047620.1 1 Pentatricopeptide repeat- TOMATO IN CHANGES WIDE containing protein 1.4±0.1 1.0±0.1 0.038 1.0±0.1 0.015 1.1±0.0 0.076 1.0±0.1 0.070 11 AK324715 Solyc04g077780.2 4 LIM domain protein 2.6±0.2 2.0±0.3 0.044 1.5±0.2 0.018 1.6±0.3 0.026 1.0±0.1 0.014 12 AK319509 Solyc04g015040.2 2 Peptidyl-prolyl cis-trans isomerase 2.7±0.4 2.1±0.2 0.045 1.4±0.3 0.032 1.6±0.3 0.030 1.0±0.2 0.020 13 BG129133 Solyc08g005440.2 2 Cc-nbs-lrr resistance protein 1.3±0.1 1.0±0.1 0.007 1.0±0.1 0.030 1.0±0.1 0.034 1.1±0.1 0.19 14 AK322096 Solyc05g005540.2 1 BURP domain-containing protein 2.0±0.3 1.5±0.3 0.048 1.0±0.1 0.015 1.1±0.2 0.019 1.2±0.3 0.12 15 AK321515 Solyc07g054210.2 1 Protochlorophyllide reductase - ike protein 3.3±0.3 2.5±0.2 0.019 1.5±0.3 0.015 1.7±0.2 0.034 1.0±0.3 0.011 * Sequences without annotation (‘unknown proteins’) were excluded ** E-value: match smaller or equal to 1E-20 (corresponding to maximally three mismatches with target sequence) *** Filter: genes significantly down-regulated by A as well as by E (P<0.05, after P-value adjustment); expression levels of E relative to the control (E/C) were sorted from low to high | C HAPTER 139 4 JorisGlas-chap4_Gerben-chap2.qxd 26/05/2014 00:25 Page 140 JorisGlas-chap5_Gerben-chap2.qxd 26/05/2014 00:30 Page 141 5 Herbivory-associated degradation of tomato trichomes and its impact on biological control of Aculops lycopersici

Y.M. van Houten, J.J. Glas, H. Hoogerbrugge, J. Rothe, K.J.F. Bolckmans, S. Simoni, J. van Arkel, J.M. Alba, M.R. Kant & M.W. Sabelis

Tomato plants have their leaves, petioles and stems covered with glandular trichomes that protect the plant against two-spotted spider mites and many other herbivorous arthropods, but also hinder searching by phytoseiid mites and other natural enemies of these herbivores. This trichome cover creates competitor-free and enemy-free space for the tomato russet mite (TRM) Aculops lycopersici (Acari: Eriophyidae), being so minute that it can seek refuge and feed inbetween the glandular trichomes on tomato cultivars currently used in practice. Indeed, several species of predatory mites tested for biological control of TRM have been reported to feed and reproduce when offered TRM as prey in laboratory experiments, yet in practice these predator species appeared to be unable to prevent TRM outbreaks. Using the phytoseiid mite, Amblydromalus limonicus, we found exactly the same, but also obtained evidence for successful establishment of a population of this predatory mite on whole plants that had been previously infested with TRM. This successful establishment may be explained by our observation that the defensive barrier of glandular plant trichomes is literally dropped some time after TRM infestation of the tomato plants: the glandular trichome heads first rapidly develop a brownish discoloration after which they dry out and fall over onto the plant surface. Wherever TRM triggered this response, predatory mites were able to successfully establish a population. Nevertheless, biological control was still unsuccessful because trichome deterioration in TRM-infested areas takes a couple of days to take effect and because it is not a systemic response in the plant, thereby enabling TRM to seek temporary refuge from predation in pest-free trichome- dense areas which continue to be formed while the plant grows. We formulate a hypothesis unifying these observations into one framework with an explicit set of assumptions and predictions to be tested in future experiments.

Experimental and Applied Acarology (2013) 60: 127-138

riophyoid mites are among the smallest arthropods on Earth (Lindquist et al., E1996). Their worm-like body has a cross-section diameter of ca. 50 μm, at least 5× smaller than that of phytoseiid mites, several species of which are their most significant predators (Sabelis, 1996). The minute size of the eriophyoid mite is the key to their ecological success, enabling them to reach places small enough to be free

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of predators and still suitable to get access to food resources in the plant (Sabelis & Bruin, 1996). Moreover, it allows many of them to develop a plant-parasitic life-style (Lindquist et al., 1996). Many eriophyoids live in plant galls they induce, and others have a vagrant life-style, frequently changing feeding sites that vary in the degree of protection against predators (Sabelis & Bruin, 1996; Conijn et al., 1996; Lesna et al., 2005). In agricultural crops, such mites may easily reach pest status when predators are lacking. Chemical control is often ineffective because the eriophyoids may feed under protective structures of the plant (Lindquist et al., 1996). Although such structures can also hamper predators, biological control with predatory mites appeared a promising solution (e.g., Lesna et al., 2005). Dense covers of (glandular) hairs are known to protect vital plant parts against many herbivorous arthropods (Wagner et al., 2004; Peiffer et al., 2009; Kang et al., 2009). On tomato, glandular trichomes on leaves and stems protect the plant constitutively against two-spotted spider mites (Chatzivasileiadis et al., 1997, 1998, 1999, 2001; Alba et al., 2009), but they may also hinder predatory mites (Van Haren et al., 1987) and other natural enemies (Simmons & Gurr, 2005). In theory, this would create competitor-free and enemy-free space for eriophyoid mites being so minute that they can seek refuge and feed between the glandular hairs. A pest outbreak of such mites would then be inevitable unless tomato plants can readjust their constitutive defenses to prevent them from backfiring (Eisner et al., 1998). The tomato russet mite Aculops lycopersici (Tryon) represents such a case. On tomato, this mite uses its ca. 10 μm long stylets to feed on epidermal cells between the glandular trichomes that are present on leaves, but even more so on those of the petioles and stems of tomato. In absence of control measures, this eriophyoid mite becomes a pest (Perring, 1996). Efforts to find natural enemies for control of tomato russet mites have resulted in a long list of candidate predators, especially among the Phytoseiidae (e.g., Park et al., 2010). Several species of these predatory mites were found in natural association with tomato russet mites and all of them showed a capacity to feed and reproduce on a diet of tomato russet mites alone. The latter tests were carried out on small tomato leaf discs under laboratory conditions. However, the candidate predators tested for their control capacity on whole plants failed to suppress the pest (Trottin-Caudel et al., 2003; Fischer et al., 2005; Van Houten et al., 2011) or required more generations to adapt to tomato as a host plant (Van Haren et al., 1987) and have an impact on the pest (Castagnoli et al., 2003). In this article we present similar bioassays for another predatory mite, Amblydromalus limonicus (Garman and McGregor), but go further in assessing the underlying causes for success or failure (1) to feed on tomato russet mites, (2) to establish a population on a whole plant infested with tomato russet mites and (3) to control TRM on whole plants. Finally (4), we present data showing how TRM modi-

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fies plant morphology (in particular that of tomato trichomes) and formulate a testable hypothesis to explain the results on (1) to (3).

Material and methods Origin of the predator strain and tomato plants The strain of A. limonicus used in our experiments was collected in New Zealand by Peter Workman (Crop and Food Research, Auckland) on beans and tomatoes in 2007. After collection, he predatory mites were reared on a diet of Typha latifolia pollen for 1.5 years. The mites for the oviposition test were taken directly from this culture; the mites for the establishment test were reared on tomato plants heavily infested with TRM for 10 weeks before the start of the experiment. The A. limonicus used for the population test (FIGURE 5.1) were reared on astigmatid mites for at least 3 months.All experiments were carried out on tomato (Solanum lycopersicum) cv. Elanto, with the exception of the direct (microscopical) observations on changes in trichome morphology which were done on tomato (S. lycopersicum) cv. Castlemart.

Oviposition test To assess the ability of A. limonicus to reproduce on TRM, we introduced a young gravid female on a tomato leaf disc (7 cm2) with >300 TRM (mixed stages). Over a period of 4 days the predatory mites were transferred each day to fresh leaf disks with TRM, thereby ensuring an ample supply of prey and enabling assessment of the number of predatory mite eggs produced per day. The leaf disc was placed upside down on a layer of agar at the bottom of a small plastic cup. The cup was closed by a lid with a gauze-covered hole to allow air exchange and it was placed in a climate room at 25ºC and 75% RH under a 16/8 h light/dark regime. To avoid effects of the rearing diet to which the predatory mites had been exposed prior to the experiment, egg production during the first day was excluded from analysis and that during the other 3 days was taken into account. We also repeated exactly the same test with young (<1 day old) whitefly eggs [Trialeurodes vaporariorum (Westwood)] as prey because predatory mites produce the same amount of offspring eating these eggs as when eating TRM (see Results section, Oviposition test). This allowed us to uncouple the indirect effect of TRM on the predatory mite via alterations in the host plant and the direct effect of TRM on the predatory mite, being its prey. The data of both experiments were statistically analyzed by a Student t-test to compare two means from unequal samples and with homogeneous variance.

Establishment tests on TRM-infested tomato plants To test predatory mite establishment on whole plants infested with TRM, preliminary experiments were carried out in a greenhouse (mean temperature 21ºC, range 16-

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35ºC; mean relative humidity 60%, range 24-85%) in spring 2009. A cucumber leaf disc (4.5 cm2) with 10 young females of A. limonicus was introduced on the bottom (= oldest) leaf from each of six young (4-leaf stage) tomato plants, each of which had been infested 4 days earlier by placing five leaf discs, each with ca. 300 TRM (mixed stages), randomly on the four leaves of the plant. The plants were together in a screen cage (3 × 1 × 2 m) to reduce the risk of pest infestation from elsewhere. During the subsequent experimental period plants were allowed to develop from four to nine leaves, but thereafter the plant apices were removed thereby maintaining a constant plant size. After 4 weeks one leaflet was taken randomly per compound leaf of each plant. The leaflets collected from each plant were put together in a plastic box and next they were inspected one by one under a binocular microscope to count the total number of predators. The same experiment was carried out with tomato plants of the same age infested by greenhouse whiteflies (T. vaporariorum) in order to compare the ability of A. limonicus to establish itself on plants infested with russet mites with that on plants infested with an unrelated but also suitable herbivore as prey. To establish the whitefly infestation, 90 adult whiteflies were released in a screen cage with 6 tomato plants (thus ca. 15 whiteflies per plant), 2 days prior to the introduction of the predatory mites at the bottom leaves. To ensure favourable food conditions for the predators at the moment of their introduction, these tomato plants were also ‘dusted’ with cattail pollen (Typha latifolia), a suitable alternative food source for many phytoseiid mites, including A. limonicus. Data were statistically analysed by a Games-Howell test to compare means derived from groups with unequal sample sizes and with unequal variances. Based on the information obtained from the first preliminary trial, we repeated the experiment with TRM and A. limonicus early in the summer of 2009 (mean temperature 23ºC, range 19-34ºC; mean relative humidity 60%, range 25-99%), but now the leaflets sampled from three strata (three leaves at the bottom, three at the middle and three at the top) of each plant were stored in separate boxes. Moreover, not only predatory mites were counted, but also TRM. Finally, the experiments differed in having a larger TRM inoculum (ca. 2500 instead of ca. 1500), a larger number of tomato plants (10 instead of six) and two sample dates (3 and 4 weeks after predator introduction) instead of only one. To correct for the effect of differences in absolute densities across replications (see large standard errors in the Results section, Establishment tests on TRM-infested plants), we expressed the population sizes in each stratum as a proportion of the total population found in all samples from a given plant (at the same sampling date) (TABLE 5.1).

Small-scale biocontrol tests To test for the impact of A. limonicus on biological control of TRM, we carried out experiments in six screen cages (12 m2 ground surface), each with 10 tomato plants, in an experimental greenhouse during the summer of 2009 (mean temperature 23ºC,

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range 19-35ºC; mean relative humidity 70%, range 24-99%). At the start of the experiments the tomato plants, each with 10 fully expanded leaves, received a leaf disc with TRM on the third to the seventh leaf from the oldest one (bottom leaf). These discs had been cut from leaflets picked from a well-infested tomato plant and, based on a sample of 30 leaf discs taken at random, we estimated that each disc harboured on average ca. 280 mobile stages of TRM. Each plant received five of these leaf discs (and thus a total of 1400 TRM). Six days after the introduction of the TRM-discs, ca. 140 predators (all mobile stages of A. limonicus) per tomato plant were introduced onto leaves 3-7 in three randomly selected cages. During the subsequent experimental period plants were allowed to grow until they had 16 leaves, but thereafter plant apices and side-shoots were removed, thereby maintaining a constant plant size and leaf area. To monitor the temporal population dynamics of TRM and of A. limonicus in three strata of the plant, three leaflets were taken from each plant (30 leaflets/cage), once a week from day 8 (since TRM introduction) onwards: one leaflet from the lower part (stratum 1: leaf 2-6), one from the middle (stratum 2: leaf 7-11) and one from the top of the plant (stratum 3: leaf 12-16). The leaflets on which the predatory mites and the TRM had been released were excluded from sampling since we wanted to assess arthropod mobility across strata during the course of the experiment. First, only the predatory mites on each leaflet sampled per stratum were counted under a stereomicroscope, because they are relatively agile. Next, the number of TRM was assessed by counting their mobile stages in a representative subsample, i.e., small leaf discs (3.5 cm2), each cut from an additional leaflet obtained from the same strata from which we had assessed the predatory mite densities.

Assessments of tomato trichome deterioration in response to TRM infestation Using a stereomicroscope equipped with a photo camera, we inspected (at 30-40× magnification) trichomes of the glandular (Type I and VI) and non-glandular (Type III and V) type on leaves and stems of TRM-infested tomato plants as well as TRM-free plants (Luckwill, 1943). Visible changes in external appearance of the trichomes and the whole plant were recorded on photograph at least once every 3-4 days. The results of these observations are summarized in a video providing a slideshow of the morphological and other changes in trichomes of TRM-infested tomato leaves, petioles and stems (supplementary material). To quantify the process of trichome deterioration trichomes were counted on three plants (3 weeks old) infested with russet mites (ca. 1500 mixed stages) and on three uninfested control plants at the basis of the main stem. Three stem/petiole sections (6 mm long) were studied in detail, one in the middle of the main stem, one on the petiole

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of the first true leaf (FIGURE 5.2, petiole 1) and one on the petiole of the second leaf (FIGURE 5.2, petiole 2) (leaves are numbered from the bottom of the plant). Photographs (taken against a contrasting background) were taken of these sections and then used to count intact (=unaffected) and amber-coloured Type VI trichomes (Luckwill, 1943) (to facilitate counting this was done in each of three consecutive subsections of 2 mm long). This procedure was carried out on days 0, 4, 7, 11, 14 and 18 after TRM infestation.

Results Oviposition test The oviposition rate of young A. limonicus females fed on a diet of (amply supplied) TRM (all stages) did not significantly differ from that on a diet of (amply supplied) greenhouse whitefly eggs. Young adult females of the predatory mite A. limonicus produced on tomato leaf discs with fresh whitefly eggs as food (n=13) on average 3.0±0.1 eggs and on discs with tomato russet mites (all stages; n=8) as food on average 3.6±0.2 eggs. These mean oviposition rates are not significantly different according to a t-test with unequal sample sizes, assuming homogeneous variances (t = 1.095; P>0.2). Thus, if these two prey-diets, i.e., their quality and/or quantity, were the only determinants of predator establishment, we would expect equal establishment success of A. limonicus on tomato plants infested by TRM and those infested by greenhouse whiteflies.

Establishment tests on TRM-infested plants In contrast to the above expectation, the first series of preliminary experiments on establishment after 4 weeks showed a significantly higher number of predators on TRM-infested plants than on whitefly-infested plants On plants with whiteflies + Typha pollen numbers of predatory mites reached up to 75.7±32.1 adult mites per plant while on plants with TRM it reached levels up to 1274.0±108.2 adult mites per plant within a time span of 2 weeks. Mean numbers of predators per plant were significantly different according to a Games-Howell test with unequal sample sizes and hetero- geneous variances (since the minimum significant difference MSD at the 5% level equals 47.38 which is much less than the difference between means). Although prey densities had not been precisely quantified in the latter experiments, they can be considered ample prey supply to achieve maximum reproduction. Thus, we had no reason to assume that the observed difference in establishment success was due to the amount of prey (and pollen as alternative food) on these plants. We also carried out a second series of experiments on predatory mite establishment, differing from the first in that samples of predatory mites, as well as TRMs, were taken from different strata in the plant. The results, given as mean and SEM of the percentages per plant (TABLE 5.1), did not require statistical treatment because the variables of interest, i.e., the proportions of the (TRM and predator) population we

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TABLE 5.1 Mean (+SEM) percentage of total population of predatory mites (all stages of Amblydromalus limonicus) per tomato plant in one of three strata (top, middle, bottom), 3 and 4 weeks since 10 females were released on the leaves at the bottom of a tomato plant that received ca. 2500 tomato russet mites, 4 days before predator introduction. Number of plants is 10 (= replicates). Data are not statistically analyzed because the differences between mean % TRM and mean % predators in the top stratum (after 3 and 4 weeks) are much larger than 3× their SEM. Establishment success (%) Period Stratum Tomato russet mites Predatory mites 3 weeks Top 13.3±2.5 0.0±0.0 Middle 53.8±3.5 14.8±9.1 Bottom 32.9±4.8 85.2±9.1 4 weeks Top 58.4±5.1 11.5±2.8 Middle 35.3±4.6 43.6±7.3 Bottom 6.2±1.6 44.8±8.2

recorded in the top stratum, differed more than 3× their SEM and suggesting that the TRM populations spread much faster from the lowest stratum (where they were introduced on the plant) to the top stratum, than do the predatory mites (also released at the bottom of the plant). Direct observations on the tomato plants showed that progress of the predatory mites to upper parts in the plant was strongly synchronized with the change in trichome density due to their collapse.

Small-scale biocontrol test As a final test, replicated experiments on biocontrol of TRM with the predatory mite A. limonicus and on TRM dynamics without predators showed that the bottom stratum of the plant harbours very few TRM and that the predator population stabilizes rapidly, but is much smaller than originally released (ca. 2%) (FIGURE 5.1; lower panel). The middle stratum shows an initial increase of the TRM population during the last week and this is slightly stronger in absence than in presence of the predators (FIGURE 5.1; middle panel). The predators were hardly found in the middle stratum until in the last week of the experiment. In the top stratum the TRM population increased strongly during the last 3 weeks and this was clearly strongest in absence of the predators (FIGURE 5.1; top panel). Predators were rarely ever found in the top stratum and only very few individuals appeared in the last week of the experiment. We conclude that, even though there was little or no prey at the bottom of the plant, we had not recorded any predators that had moved up to the higher strata until the last week of the experiment, whereas the TRM population readily spread to the top of the plant where their populations build up starting from 3 weeks before the end of the experiment. Overall, there is reason to think that the predator population had some suppressive effect on the growth rate of the TRM population, but biocontrol was clearly ineffective. Differences in TRM population at the last sampling date between plants with and without predators were not significant [two- sample-test: P=0.38 (top), P=0.26 (middle), P=0.12 (bottom), P=0.27 (overall)].

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Assessments of trichome deterioration in response to TRM infestation A possible explanation for the differential establishment success emerged from direct observations on the plants in this experiment. We noticed a striking response of toma- to plants to TRM but not to whiteflies: during TRM-infestation first the colour in the glandular heads changed from oblique to amber-coloured, followed by drying out of the stalk and finally rapid deterioration of both glandular and non-glandular trichomes altogether. Massive trichome collapse could be observed wherever TRM numbers increased beyond a threshold of ca. 50 mobiles per cm2 which is a density easily reached within days after a moderate starting infection. Trichome collapse, especially that of the glan-

FIGURE 5.1 Population dynamics of tomato russet mites (diamonds) and predatory mites (Amblydromalus limonicus; squares) and tomato russet mites (Aculops lycopersici; triangles) in absence of predators in three different strata (top, middle, bottom) of tomato plants over a period of 7 weeks (mean ± SEM number of mites per leaflet or leaf disc). Five leaf discs, each with 280 tomato russet mites, were placed on leaf 3-7 on day 0. Six days later, 140 predatory mites (all mobile stages) were randomly distributed over leaf 3-7. Each of the two treatments was replicated three times. The vertical arrows indicate the approximate time period in which glandular hair fall-over takes place on the stems. Differences in TRM population at the last sampling date between plants with and without predators did not test significantly different using the two-sample-test (see Results section).

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dular trichomes, may remove a barrier critical to the establishment of predatory mites. Detailed observations on changes in the trichomes (see supplementary material with video providing slideshow) showed that (1) trichome collapse only occurs on plant parts with TRM but not systemically, that (2) non-glandular trichomes deteriorate within 3 days, that (3) glandular trichomes turn amber-coloured after 3 days and that (4) they collapse within a week, depending on the density of TRM. Thus, the sampling time inter- vals selected in the experiments to follow (3 to 4 weeks in the establishment test; 7 weeks in the biocontrol test) are long enough to get severe trichome deterioration. Quantitative assessments of Type VI trichomes on stems and petioles of TRM- infested tomato plants showed a gradual decline in intact trichomes and a gradual increase in amber-coloured trichomes over a period of 18 days (FIGURE 5.2). Since tri-

FIGURE 5.2 Changes in the mean (±SEM) number of intact type VI trichomes (left panels) and amber-coloured type VI trichomes (right panels) per section (6 mm long) per plant over a period of 18 days. Upper panels relate to main stem sections, middle panels to petiole 1 sections and lower panels to petiole 2 sections. For the number of intact type VI trichomes on stems the lines start to separate significantly at day 4; on petiole 1 on day 11 and on petiole 2 on day 11. Moreover, trichome ambering became apparent on the stems on day 7; on petiole 1 on day 7 and on petiole 2 on day 10 (t-test at α = 0.05).

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chome collapse is a progressive phenotype and the time points are dependent data we only determined the time point at which the control and treatment line (FIGURE 5.2) numerically start separating using a t-test on the individual time points at α = 0.05. For the number of intact type VI trichomes on stems the lines start to separate significantly at day 4; on petiole 1 on day 11 and on petiole 2 on day 11. Moreover, trichome ambering became apparent on the stems on day 7; on petiole 1 on day 7 and on petiole 2 on day 10. However, uninfested plants (with or without apex/leaf removal) do not show trichome deterioration at all. This confirms the visual observations in the experiments on predator establishment and TRM biocontrol.

Discussion As reported for several other phytoseiid mites (see introduction), the generalist predatory mite, A. limonicus, can feed and reproduce on a diet of TRM alone when offered on tomato leaves with low trichome densities. This explains why our preliminary trials indicated that the predatory mite was able to establish and rapidly build up a population on whole tomato plants heavily infested with TRM. However, despite successful establishment this predator was not able to control TRM on whole plants inoculated with TRM. Possibly releasing more predatory mites, or more frequently, could improve their capacity to control TRM. Nevertheless, in the presence of an initially high and expanding population of predatory mites, the TRM population continued to increase, albeit at a slower pace (probably due to predation). In the course of the biocontrol experiment we observed that over time there was a gradual decrease in active glandular trichomes on leaves, petioles and stems because they dried out and collapsed. This process required days rather than hours and became apparent only after TRM had developed a population for several days up to a week. We hypothesize that the ineffective control by the predatory mites arises because the TRM populations escaped predator control by moving up in the plant at a rate faster than their predators. The relatively slow upward movement of the predators in the plant cannot be due to arrestment of the predators in the lowest strata because here the leaves had very low TRM densities (and no other prey/food) during the last weeks of the experiment. Hence, there must be another factor impeding their spread over the plant. Although in general the reasons for residing in a particular stratum of the plant can be many and varied (e.g., abiotic conditions in the mid-stratum as argued by Shipp et al. (2003) or in the apex as argued by Onzo et al., 2010), our experience with A. limonicus (and other phytoseiids) on trichome-free plants is that they stay, or now and then move to, wherever the prey is positioned on the plant (e.g., see also Weintraub et al., 2007; Onzo et al., 2009). Hence we hypothesize that this delay in predator response to TRM movement in the tomato plant arises from the time required for TRM to reach densities sufficiently high to give rise to the collapse of tomato trichomes.

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The collapse of glandular and non-glandular trichomes could either be the result of mites directly feeding on the trichomes or from mite-induced physiological changes in the plant. Preliminary data suggest that russet mites suppress JA defences in tomato (J.J. Glas & M.R. Kant, unpublished data) reminiscent of some spider mite genotypes (Kant et al., 2008; Sarmento et al., 2011). It is well known that a plant’s jasmonate metabolism can have a profound impact on trichomes (Pauwels & Goossens, 2011), i.e., on their development (Traw & Bergelson, 2003), density (Boughton et al., 2005) and chemistry (Li et al., 2004). The amber discoloration of the glandular trichome heads that precedes their massive collapse (this paper) was also observed during trichome hyperplasia in Quercus ilex trichomes upon attack by Aceria ilicis mites. Here, the discoloration was paralleled by an increased accumulation of simple phenolics and flavonoids within these trichomes (Karioti et al., 2011). Hence, possibly the amber discoloration is due to accumulation of (oxidized) proan- thocyanidins and/or their polymers (Zhao et al., 2010). However, if such changes can be the cause of both glandular and non-glandular trichome deterioration or whether these are only symptomatic of it, remains a question to be elucidated. Trichome collapse, especially that of the glandular trichomes, may remove a barrier critical to the establishment of predatory mites. This may take effect especially when they have to move from leaf to leaf because tomato cultivars commonly used in practice exhibit the highest densities of glandular trichomes on the stems (Van Haren et al., 1987; Sato et al., 2011). However, TRM is too small to be hindered by tomato trichomes and whitefly nymphs hardly move over the plant surface, whereas their adults can fly. Most notably, trichome collapse did not occur all over the surface of the plant, but only where TRM reached sufficiently high densities. Thus, these pest arthropods are not hindered by the glandular trichome ‘forests’ on stems of tomato plants. Moreover, the predatory mites under study established best and built up a (6× larger) population where the surface of the tomato plants was cleared from glandular trichomes. Taken together this may explain why A. limonicus is able to establish on TRM-infested tomato plants but not on whitefly infested plants and/or plants supplied with pollen. Based on the experimental results and direct observations we formulate a hypothesis in an attempt to explain them by one unifying principle. We propose that (1) forests of glandular trichomes, i.e., where they occur at high densities on the plant surface, provide a refuge to TRM by protecting them against predatory mites, that (2) TRM feeding induces the plant to deteriorate trichomes (or alternatively, TRM directly causes trichomes to fall-over), that (3) this allows predatory mites to move on the plant surface unhindered by glandular trichomes, thereby enabling them to find and con- sume TRM, and that (4) the process of trichome fall-over is local and proceeds slow enough to provide TRM with enemy-free space elsewhere on the plant, thereby making biocontrol with predatory mites unsuccessful. The first conjecture is supported by

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the observation that the per capita rate of predation on TRM on a plant surface devoid of glandular trichomes is much higher than that on a plant surface with these trichomes, and that TRM tends to seek refuge in the trichome forest especially when there are predatory mites around (Simoni & Sabelis, 2010). Note, however, that the very high densities of glandular trichomes found on wild type tomato can provide resistance against TRM (Leite et al., 1999), which could explain why natural selection did not favour TRM genotypes that keep trichomes intact. The second conjecture requires in-depth plant physiological research. From a functional point of view (sensu Tinbergen, 1963), the plant benefits from trichome deterioration because TRM becomes more exposed to predation provided these predators are around (whereas it would otherwise be destroyed by TRM). Moreover, TRM may also experience direct negative effects from glandular secretions (see, e.g., Wagner et al., 2004; Shepherd et al., 2005) or from contact with glandular trichome heads (Peiffer et al., 2009). If so, TRM may attempt to reduce this by disturbing trichome functioning and integrity, but we have no observations so far to substantiate this. The third conjecture is actually the one most strongly supported. Establishment of phytoseiid mites on TRM-infested tomato has been observed not only in the experiments with A. limonicus presented in this article, but also in experiments with Amblyseius swirskii (Athias-Henriot) (Van Houten et al., 2012) and with Typhlodromips montdorensis (Schicha) (Van Houten, pers obs.). The fourth conjecture requires experiments to assess the rate of trichome collapse during the ontogeny of a tomato plant in response to TRM feeding initiated on leaves of different age. Also, it would be of interest to find tomato genotypes that exhibit systemic induction of trichome deterioration in response to TRM attack. We emphasize that our hypothesis requires extensive and detailed experiments before it can be accepted or rejected. Our motivation to formulate this hypothesis is that – by making it explicit – it may stimulate critical tests and thereby advance our insight into the underlying mechanisms determining biocontrol successes or failures on plants with glandular trichomes, such as tomato.

References Alba JM, Montserrat M, Fernandez-Munoz R (2009) Resistance to the two-spotted spider mite (Tetranychus urticae) by acylsucroses of wild tomato (Solanum pimpinellifolium) trichomes studied in a recombinant inbred line population. Experimental and Applied Acarology 47: 35-47 Boughton AJ, Hoover K, Felton GW (2005) Methyl jasmonate application induces increased densities of glandular trichomes on tomato (Lycopersicon esculentum). Journal of Chemical Ecology 31:2211–2216 Castagnoli M, Simoni S, Liguori M (2003) Evaluation of Neoseiulus californicus (McGregor) (Acari: Phytoseiidae) as a candidate for the control of Aculops lycopersici (Tyron) (Acari Eriophyoidea): a preliminary study. Redia, 86:97-100 Chatzivasileiadis EA, Boon JJ, Sabelis MW (1999) Accumulation and turnover of 2-tridecanone in Tetranychus urticae Koch and its consequences for resistance of wild and cultivated tomatoes. Experimental and Applied Acarology 23:1011–1021

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Chatzivasileiadis EA, Egas M, Sabelis MW (2001) Resistance to 2-tridecanone in Tetranychus urticae Koch: effects of induced resistance, cross-resistance and heritability. Experimental and Applied Acarology 25:717–730 Chatzivasileiadis EA, Sabelis MW (1997) Toxicity of methyl ketones from tomato trichomes to Tetranychus urticae Koch. Experimental and Applied Acarology 21:473–484 Chatzivasileiadis EA, Sabelis MW (1998) Variability in susceptibility among cucumber and tomato strains of Tetranychus urticae Koch to 2-tridecanone from tomato trichomes: Effects of host plant shift. Experimental and Applied Acarology 22:455–466 Conijn CGM, van Aartrijk J, Lesna I (1996) Flower bulbs. – In: E.E. Lindquist, M.W. Sabelis, J. Bruin (eds.), Eriophyoid Mites – Their Biology, Natural Enemies and Control. Elsevier Science Publishers, Amsterdam, pp. 651–658 Eisner T, Eisner M, Hoebeke RE (1998) When defense backfires: Detrimental effect of a plant’s protective trichomes on an insect beneficial to the plant. Proceedings of the National Academy of Sciences USA 95:4410–4414 Fischer S, Klötzli F, Falquet L, Celle O (2005) An investigation on biological control of the tomato russet mite Aculops lycopersici (Massee) with Amblyseius andersoni (Chant). IOBC/WPRS Bulletin 28:99–102 Kang J-H, Shi F, Jones AD, Marks MD, Howe GA (2010) Distortion of trichome morphology by the hairless mutation of tomato affects leaf surface chemistry. Journal of Experimental Botany 61:1053–1064 Kant MR, Sabelis MW, Haring MA, Schuurink RC (2008) Intraspecific variation in a generalist herbivore accounts for induction and impact of host-plant defenses. Proceedings of the Royal Society B: Biological Sciences 275: 443–452 Karioti A, Tooulakou G, Bilia AR, Psaras GK, Karabourniotis G, Skalts H (2011) Erinea formation on Quercus ilex leaves: Anatomical, physiological and chemical responses of leaf trichomes against mite attack. Phytochemistry 72:230-237 Leite GLD, Picanco M, Guedes RNC, Zanuncio JC (1999) Influence of canopy height and fertilization levels on the resistance of Lycopersicon hirsutum to Aculops lycopersici (Acari: Eriophyidae). Experimental and Applied Acarology 23:633–642 Lesna I, Conijn CGM, Sabelis MW (2005) From Biological Control to Biological Insight: Rust-mite induced change in bulb morphology, a new mode of indirect plant defence? In: G. Weigmann, G. Alberti, A. Wohltmann and S. Ragusa (eds), Acarine Biodiversity in the Natural and Human Sphere. Phytophaga (Palermo) 14:285–291 Li L, Zhao Y, McCaig BC, Wingerd BA, Wang J, Whalon ME, Pichersky E, Howe GA (2004) The tomato homolog of CORONATINE-INSENSITIVE1 is required for the maternal control of seed maturation, jasmonate-signaled defense responses, and glandular trichome development. Plant Cell 16:126–143 Lindquist EE, Sabelis MW, Bruin J (eds.) (1996) Eriophyoid mites – Their biology, natural enemies and control. World Crop Pests Vol. 6. Elsevier, Amsterdam, The Netherlands. Luckwill, LC. 1943. The Genus Lycopersicon: Historical, Biological, and Taxonomic Survey of the Wild and Cultivated Tomatoes. Aberdeen University Press, Aberdeen. Onzo A, Sabelis MW., Hanna R. 2010. Effects of Ultraviolet Radiation on Predatory Mites and the Role of Refuges in Plant Structures. Physiological Entomology 39:695-701. Onzo A, Sabelis MW., Hanna R. 2009. Within-Plant Migration of the Predatory Mite Typhlodromalus aripo from the Apex to the Leaves of Cassava: Response to Day–Night Cycle, Prey Location and Prey Density. Journal of Insect Behavior 22:186-195. Park H-H, Shipp L, Buitenhuis R (2010) Predation, development, and oviposition by the predatory mite Amblyseius swirskii (Acari: Phytoseiidae) on tomato russet mite (Acari: Eriophyidae). Journal of Economic Entomology 103:563–569 Pauwels L, Goossens A (2011) The JAZ proteins: A crucial interface in the jasmonate signaling cascade. The Plant Cell 23:3089–3100 Peiffer M, Tooker JF, Luthe DS, Felton GW (2009) Plants on early alert: glandular trichomes as sensors for insect herbivores. New Phytologist 184:644–656

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Perring TM (1996) Vegetables. In: E.E. Lindquist, M.W. Sabelis and J. Bruin (eds.). Eriophyoid Mites – Their Biology, Natural Enemies and Control. World Crop Pests Vol. 6. Elsevier, Amsterdam, The Netherlands, pp. 593-610 Sabelis MW (1996) Phytoseiidae. In: E.E. Lindquist, M.W. Sabelis and J. Bruin (eds.). Eriophyoid Mites – Their Biology, Natural Enemies and Control. World Crop Pests Vol. 6. Elsevier, Amsterdam, The Netherlands, pp. 427–456 Sabelis MW, Bruin J (1996) Evolutionary ecology: life history patterns, food plant choice and dispersal. In: E.E. Lindquist, M.W. Sabelis and J. Bruin (eds.). Eriophyoid Mites – Their Biology, Natural Enemies and Control. World Crop Pests Vol. 6. Elsevier, Amsterdam, The Netherlands, pp. 329–366 Sabelis MW, Lesna I, Aratchige NS (2007) A tritrophic perspective to the biological control of eriophyoid mites. IOBC/WPRS Bulletin 30(5): 91-93 Sarmento RA, Lemos F, Bleeker PM, Schuurink RC, Pallini A, Oliveira MGA, Lima E, Kant M, Sabelis MW, Janssen A (2011) A herbivore that manipulates plant defence. Ecology Letters 14: 229–236 Sato, MM, de Moraes GJ, Haddad ML, Wekesa, VW (2011) Effect of trichomes on the predation of Tetranychus urticae (Acari: Tetranychidae) by Phytoseiulus macropilis (Acari: Phytoseiidae) on tomato, and the interference of webbing. Experimental and Applied Acarology 54:21–32 Shepherd RW, WT Bass, Houtz RL, Wagner GJ (2005) Phylloplanins of tobacco are defensive proteins deployed on aerial surfaces by short glandular trichomes. The Plant Cell 17:1851–1861 Shipp JL, Wang K (2003) Evaluation of Amblyseius cucumeris (Acari: Phytoseiidae) and Orius insidiosus (Hemiptera: Anthocoridae) for control of Frankliniella occidentalis (Thysanoptera: Thripidae) on greenhouse tomatoes. Biological Control 28:271-281 Simoni S, Sabelis MW (2010) Glandular trichome ‘forests’ on tomato leaves act as a predation refuge for tomato russet mites. Abstracts XII International Congress of Acarology, Recife. Simmons AT, Gurr GM (2005) Trichomes of Lycopersicon species and their hybrids: effects on pests and natural enemies. Agricultural and Forest Entomology 7:265-276 Tinbergen N (1963) On the aims and methods of ethology. Zeitschrift für Tierpsychologie 20:410-433 Traw MB, Bergelson J (2003) Interactive effects of jasmonic acid, salicylic acid, and gibberellin on induction of trichomes in Arabidopsis. Plant Physiol. 133: 1367-137 Trottin-Caudal Y, Fournier C, Leyre J-M (2003) Biological control of Aculops lycopersici (Massee) using the predatory mites Neoseiulus californicus McGregor and Neoseiulus cucumeris (Oudemans) on tomato greenhouse crops. In: Proceedings, International Symposium on Greenhouse Tomato: Integrated Crop Protection and Organic Production, 17-19 September 2003, Avignon, France: 153–157 Van Haren RJF, Steenhuis MM, Sabelis MW, de Ponti OMB (1987) Tomato stem trichomes and dispersal success of Phytoseiulus persimilis relative to its prey Tetranychus urticae. Experimental and Applied Acarology 3:115–121 Van Houten YM, Knapp M, Hoogerbrugge H, Bolckmans, KJ (2012) The potential of Amblyseius swirskii as biocontrol agent for Aculops lycopersici on tomatoes. IOBC Bulletin (in press) Wagner GJ, Wang E, Shepherd RW (2004) New approaches for studying and exploiting an old protuberance, the plant trichome. Annals of Botany 93:3–11 Weintraub PG, Kleitman S, Alchanatis V, Palevsky E (2007) Factors affecting the distribution of a predatory mite on greenhouse sweet pepper. Experimental and Applied Acarology 42:23-35 Zhao J, Pang Y, Dixon RA. (2010) The mysteries of proanthocyanidin transport and polymerization. Plant Physiology 153:437-443

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SUPPLEMENTARY MATERIAL Detailed observations on changes in the trichomes (video slideshow: http://link.springer.com/content/esm/art:10.1007/s10493-012-9638-6/file/MediaObjects/10493_2012_9638_ MOESM1_ESM.mp4). Three stills from the video sequence:

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lants mediate interactions between different plant feeders, but the underlying Pmechanisms remain often unknown (Stout et al., 2006; Mouttet et al., 2013; Soler et al., 2013). Hence, as argued by Soler et al. (2013), there is a need to integrate insights from molecular studies on plant defense mechanisms, which usually deal with the interaction between a plant and a single herbivore, with insights from ecological studies, that are often performed at the community level and without taking plant physiological mechanisms into account. In this thesis, I have combined these two approaches by investigating both molecular and ecological aspects of interactions occurring in a natural community of plant parasites on tomato. So, the question that now may be asked is: what can be learned from the results of this study?

Ecological consequences of induced defenses One of the most striking ecological observations presented in this thesis is that on field-grown tomatoes in Italy russet mite infestations tend to be followed by spider mite infestations. As shown in CHAPTERS 2 & 3, this observation may be explained by the finding that russet mites promote the performance of spider mites because they suppress JA defenses. Against this background, several new questions emerge. For example, one may ask whether spider mites show a preference for russet mite-infested plants when given the choice between clean and russet mite-infested plants, like they seem to do in the field, and, if so, how this preference is established. Since spider mites are known to respond to plant odours (Pallini et al., 1996), it may well be that plant volatiles mediate attraction of spider mites to russet mite-infested plants. My experiments showed that russet mite populations grow faster in the complete absence of JA-defenses, suggesting that defense suppression is adaptive for russet mites. Yet, in the presence of spider mites, russet mite growth was strongly reduced. To what extent the negative effect of spider mites on russet mites is due to russet mite-induced plant-mediated facilitation of spider mites remains to be determined. This could be done by using a tomato genotype on which russet mites are unable to suppress, but we did not identify such mutants yet. Whatever the reasons, the important point emerging is that fitness consequences of defense suppression can be strongly context-dependent, i.e., depending on which other attackers are present. Although not yet tested, I expect that the time point, the sequence of arrival as well as infestation density of these other attackers play a major role as well.

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So far, only few studies have assessed the consequence of defense suppression on the performance of other attackers (Zhang et al., 2009; Sarmento et al., 2011; Soler et al., 2012), but how host-plant mediated changes in a herbivore’s community feedback onto the suppressing herbivore itself was never investigated. As my results show, the outcome of these interactions can be unpredictable and counter- intuitive since they depend on simultaneous reciprocal changes between individual community members. Most importantly, defense suppression can backfire in natural communities. The observation that spider mites benefit from russet mites, who thereby are clearly disadvantaging themselves, begs the question if russet mites somehow have evolved a strategy to prevent competitors from taking advantage from down-regulated plant defenses, as suggested for T. evansi which produces a dense silken web presumably to prevent competitors from benefiting from down-regulated plant defenses (Sarmento et al., 2011). Russet mites however do not produce a profuse web, but it could be that they disperse to the trichome-dense parts of plants – like the stems or younger leaflets – following local invasions of herbivores and/or predators (CHAPTER 5). Because trichome-dense areas are in general hard to access for arthropods, russet mites may, in doing so, avoid the negative effects of competition and predation. Hence, from the russet mite-point of view, degradation of the trichomes seems disadvantageous, whereas plants may potentially profit as the russet mites become more exposed and therefore vulnerable to predation (CHAPTER 5). To obtain further insight in the mechanism and functional significance of trichome degradation it would be worthwhile to search for tomato genotypes that show trichome browning and degradation in the absence of russet mites or, alternatively, genotypes that fail to display trichome degradation in the presence of russet mites. Moreover, it may actually pay off to generate trichome-less tomato varieties for the commercial tomato production in greenhouses to aid biological control.

Limitations of the nahG mutant and marker genes It is well known that JA defenses in plants can be suppressed by up-regulating SA defenses and that some parasites abuse this phenomenon to their own benefit. To assess whether the antagonistic interaction between SA and JA plays a role in plants infested with russet mites, we used the SA-deficient tomato-mutant nahG. This approach appeared to very instrumental, as it allowed us to disentangle the ‘primary’ suppression of JA defenses by russet mites from the antagonistic ‘secondary’ suppression caused by SA in plants infested with both spider mites and russet mites (CHAPTER 2). However, there are drawbacks to the use of this mutant as well. For instance, Van Wees & Glazebrook (2003) reported that susceptibility of nahG plants to P. syringae pv. phaseolicola was due to the production of catechol and hydrogen

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peroxide, rather than to the absence of SA. Furthermore, a later study showed that nahG may act on substrates other than SA which may result in pleiotropic changes in the metabolism of nahG plants (Heck et al., 2003). Hence, there is a need for an independent SA-mutant in tomato, but, unfortunately, an attempt to create an RNAi line by silencing the enzyme isochorismate synthase was unsuccessful (discussed in CHAPTER 2). An alternative way to assess the role of SA in the tomato-mite interactions could be to make use of chemical SA inhibitors, which reduce enzyme activity, but these compounds may cause pleiotropic effects thereby hampering interpretation of the results. For example, paclobutrazol (PBZ) is known to inhibit not only the activity of benzoic acid 2-hydroxylase, a key enzyme in SA biosynthesis, but also gibberellin biosynthesis (Hayat et al., 2013). In experiments I did together with a Master student, Marije Stoops, the amounts of SA decreased 3-fold after treatment with PBZ but when these plants were infested with russet mites amounts did not significantly differ from the water control (data not shown). Hence, we did not continue into this direction. Unexpectedly, we discovered another problem in nahG plants. Via qRT-PCR measurements we observed that both PR-P6 and PR-P1a were up-regulated by spider mites not only in wild-type but also in nahG plants, despite the absence of SA. Hence, this suggests that nahG plants actually do display (part of) the downstream SA-response. Possibly, residual SA accumulation in nahG plants (see CHAPTER 2, FIGURE 2.5) is sufficient to induce the expression of PR-genes. A second explanation for this observation could be that expression of PR-genes is regulated by signals additional to SA. For example, it has been reported that ethylene precursors may induce expression of PR-P6 in tomato as well (Tornero et al., 1997, where PR-P6 is referred to as PR1b1). To investigate the role of ethylene of PR-gene expression, one could, for instance, treat nahG plants with ethylene and see whether this correlates with PR-gene expression levels. Other additional signals have been reported to induce expression of PR-genes in tomato as well, for instance gentisic acid (GA) which is derived from SA and accumulates in response to tomato mosaic virus infections (Bellés et al., 1999). Whether GA regulates PR-proteins, including PR-P6, could be tested in a similar way, by measuring expression of PR-genes after treating nahG tomatoes with GA or by determining GA levels directly in mite-infested nahG tomatoes. Nevertheless, the existence of additional hormonal signals which possibly partly compensate for the SA-deficiency in the downstream nahG defense response does not alter the main conclusion that the primary suppression by russet mites is independent from SA while the secondary suppression of the spider mite-induced response is not.

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Do russet mite endosymbionts play a role in defense suppression? A major question that needs to be addressed in follow-up research is by means of which mechanism russet mites suppress JA-defenses. Not much is known about the mechanisms by which other herbivores suppress defenses, but, as summarized in CHAPTER 1, the scarcely available evidence suggests that they, similar to plant pathogens and nematodes, produce and secrete effector molecules (mostly proteins) which interfere with the establishment of plant defense responses during feeding. In addition, it has been reported that herbivores may vector pathogens that suppress plant defenses, thereby increasing the quality of the plant host to the herbivore, as a form of micro ecosystem engineering. Examples of defense-suppressing pathogens vectored by herbivores include bacteria (Chung et al., 2013), viruses (Belliure et al., 2005) and phytoplasmas (Sugio et al., 2011). Hence, it could be that russet mites vector a pathogen, or, alternatively, russet mites could carry spores of fungi resulting in secondary infections, as reported for some eriophyoid mite species (Gamliel- Atinsky et al., 2009). In order to exclude this possibility as much as possible, russet mite-infested leaf material was screened for some of the most commonly occurring pathogens in the commercial production of tomatoes. In these screenings, which were carried out at NAK Tuinbouw (Roelofarendsveen, The Netherlands) and Scientia Terrae (St.- Katelijne-Waver, Belgium), leaf material was tested for 50 plant pathogenic fungi, 11 bacteria and 12 viruses (TABLE S6.1). However, the results of all these screenings turned out negative. In addition, shortly before finishing this thesis, a bulk sequence analysis was performed via Illumina MiSeq of a PCR-fragment of russet mite-derived 16S ribosomal DNA revealing that bacteria are associated with russet mites. This analysis yielded three alpha-proteobacterial clusters: 6.6% of the 128.000 read-pairs could be attributed to the order of the Rickettsiales, 25.4% to the genus Sphingomonas and 62.3% to the family of the Bradyrhizobiaceae (H. Staudacher & B. Schimmel, unpublished data; Supplemental methods). A well-known member of the Rickettsiales that has been associated with defense suppression by insects is Wolbachia. Barr et al. (2010) reported that Wolbachia plays a role in defense suppression by western corn rootworm beetles (Diabrotica virgifera virgifera) in maize. However, in a later study, using the same experimental system, no effect of Wolbachia was found (Robert et al., 2013). The largest number of reads from the Illumina run on russet mites matched to the genus Bradyrhizobium. Bradyrhizobium bacteria are normally found in the plant rhizosphere where they are involved in nitrogen fixation (Ehinger et al., 2014), and have, like bacteria of the genus

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Sphingomonas, not been associated with defense suppression. Moreover, it is unclear from literature if Bradyrhizobium bacteria can be also free-living, i.e., independent from rhizobia. It must be noted that in the same Illumina run 50 spider mite strains were tested, many of which reared under the same conditions as russet mites, and none of these carried Bradyrhizobium. Bacteria from the family of the Enterobacteriaceae and the Pseudomonadaceae, of which members have been shown to be involved in defense suppression (Chung et al., 2013), were represented by <0.2% of the total pool (Supplemental methods). However, these families are large and constitute of many different species. Taken together, although we cannot exclude mite-surface or plant-surface contamination of the samples, this result suggests that we may have overlooked some microorganisms associated with russet mites previously. However, since russet mites do not suppress JA via induction of SA, as reported for oral bacteria from the genus Pseudomonas and Enterobacter of the Colorado beetle (Chung et al., 2013), I still favor the hypothesis that the suppression is due to mite-borne secretions, rather than to microbes in, and/or vectored by, the mite.

Searching for russet mite effectors My current hypothesis is that russet mites produce effector(s) that suppress JA- defenses. Effectors are intensely investigated in the field of plant pathology and have been broadly defined as ‘microbial and pest secreted molecules that alter host-cell processes or structure generally promoting the microbe lifestyle’ (Win et al., 2012). It must be noted that different definitions are used by different authors, i.e., sometimes restricting it to secreted proteins or to secreted proteins that interact with host proteins. Examples of secreted protein effectors include members of the transcription activator-like (TAL) effector family, which are secreted by Xanthomonas bacteria and which function as transcription factors by directly binding specific host-DNA sequences and activating transcription of specific genes in the nucleus of the plant cell to their own benefit (Boch et al., 2009). Other effectors, like AvrPtoB from Pseudomonas syringae, mimick the activity of plant E3 ubiquitin ligases, thereby inhibiting programmed cell death and increasing virulence (Janjusevic et al., 2006). Yet others again function as hormone mimics, for instance the phytotoxin coronatine, which is a mimic of jasmonic acid isoleucine (JA-Ile) that is produced by some plant pathogenic bacteria and fungi (e.g., P. syringae and Fusarium oxysporum) to activate the JA-pathway and thereby suppressing SA-dependent defenses (Brooks et al., 2005; Cole et al., 2014). Finally, effectors may also interfere with plant development as reported for SAP11 of phytoplasma bacteria, which binds to TCP transcription factors, thereby altering plant development and suppressing JA-biosynthesis (Sugio et al., 2011).

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In order to reveal the mechanism underlying defense suppression, we sequenced the genome and transcriptome of russet mites and mined it for putative effectors (the procedure is described in the Supplemental methods). Using a series of annotation- independent filtering steps (described in the Supplemental methods), candidates were selected to work on in the near future: on top of this list are six proteins that were annotated as ‘secreted salivary gland peptides’ and one as ‘Cathepsin S’ (belonging to a large family of 19 papain-like genes). Other proteins that ranked high on the list may be false positives, since three are annotated as ‘cuticular proteins’ and one as a ‘midgut chitinase’. Additional salivary proteomics and in situ verifica- tion of candidates will be required to get a better view on putative false positives and false negatives and to fine-tune the selection criteria of our candidates. Applying hard in silico criteria for preparing a short list of proteins, such as salivary secreted proteins, has the obvious drawback that not only false positives will be selected (which will be recognized sooner or later during the downstream characterization process) but also that potentially interesting candidates will be overlooked altogether. For example, by manually blasting cDNAs, we found homologs of effectors from other organisms such as the nematode Globodera rostochiensis effector protein VAP1 (venom allergen-like effector protein) (E-value: 3E-30). VAP1 perturbs the active site of the papain-like cysteine protease Rcr3pim of the red currant toma- to (Solanum pimpenellifolium), thereby increasing the susceptibility of these plants to nematodes (Lozano-Torres et al., 2012). Most importantly, susceptibility depends on the Cf-2 protein and in the presence of this protein S. pimpenellifolium plants are protected not only against the leaf mold fungus Cladosporium fulvum but also against G. rostochiensis, thus showing that single plant immune receptors can mediate multiple disease resistances (Lozano-Torres et al., 2012). An easy and informative assay to test the functional role of the VAP1-like homologs in russet mites would be to test susceptibility of Cf-2 tomatoes to russet mites. Now that russet mite sequencing data are available, we can clone candidate effectors and test their function by expressing them in planta (such as in Arabidopsis, tobacco or tomato) via stable or transient Agrobacterium-mediated transformation to determine whether they induce a phenotype, for example a hypersensitive response or suppressed defenses, and influence russet mite performance. Future studies should focus as well on the in planta targets of these putative effectors, thereby giving insight in the molecular mechanism underlying defense suppression. In addition, it may be feasible to knock down (effector) genes in the mite itself by expressing double stranded RNA’s of russet mite genes in plants to obtain silencing via RNA interference (RNAi), as demonstrated for insects and nematodes (e.g., Baum et al., 2007; Sindhu et al., 2009). To conclude, several directions for future research can be identified at this point. First, to advance our understanding of factors that contribute to russet mite resist-

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ance, it would be helpful to assess mite performance not only on cultivated tomatoes, which have lost much of their resistance during cultivation, but also on wild solanaceous plants. Second, the consequence of russet mite-associated trichome degradation for attraction and establishment of natural enemies should be tested further as this may lead to a better understanding of the mechanisms determining the efficacy of biological control of russet mites on tomato. Ideally, these tests should include not only cultivated but also wild solanaceous host plants to assess if trichome degradation occurs on these species, and they should also include a predator that is naturally associated with russet mites on (wild) solanaceous plants in the field (as yet unknown). Finally, effort should be put in characterizing russet mite elicitors and effectors which are likely to play a role in induction and suppression of defenses and trichome degradation.

Acknowledgements I thank Carlos Villarroel and Merijn Kant for performing bioinformatics on the russet mite genome and transcriptome sequencing data and Merijn Kant for writing the Supplemental methods section. I thank Heike Staudacher for including russet mites in her Illumina MiSeq run.

References Barr, K., Hearne, L.B., Briesacher, S., Clark, T.L. & David, G.E. (2010) Microbial symbionts in insects influence downregulation of defense genes in maize. PLoS ONE 5, e11339. Baum, J.A., Bogaert, T., Clinton, W., Heck, G.R., Feldmann, P., Ilagan, O., Johnson, S., Plaetinck, G., Munyikwa, T., Pleau, M., Vaughn, T. & Roberts, J. (2007) Control of coleopteran insect pests through RNA interference. Nat. Biotechnol. 25, 1322-1326. Bellés, J.M., Garro, R., Fayos, J., Navarro, P., Primo, J. & Conejero, V. (1999) Gentisic acid as a pathogen- inducible signal, additional to salicylic acid for activation of plant defenses in tomato. Mol. Plant Microbe In. 12, 227-235. Belliure, B., Janssen, A., Maris, P.C., Peters, D. & Sabelis, M.W. (2005) Herbivore arthropods benefit from vec- toring plant viruses. Ecol. Lett. 8, 70-79. Boch, J., Scholze, H., Schornack, S., Landgraf, A., Hahn, S., Kay, S., Lahaye, T., Nickstadt, A. & Bonas, U. (2009) Breaking the code of DNA binding specificity of TAL-type III effectors. Science 326, 1509-1512. Brooks, D.M., Bender, C.L. & Kunkel, B.N. (2005) The Pseudomonas syringae phytotoxin coronatine promotes virulence by overcoming salicylic acid-dependent defences in Arabidopsis thaliana. Mol. Plant Pathol. 6, 629-639. Chung, S.H., Rosa, C., Scully, E.D., Peiffer, M., Tooker, J.F., Hoover, K., Luthe, D.S. & Felton, G.W. (2013) Herbivore exploits orally secreted bacteria to suppress plant defenses. Proc. Natl. Acad. Sci. USA 110, 15728-15733. Cole, S.J., Yoon, A.J., Faull, K.F. & Diener, A.C. (2014) Host perception of jasmonates promotes infection by Fusarium oxysporum formae speciales that produce isoleucine- and leucine-conjugated jasmonates. Mol. Plant Pathol. (DOI: 10.1111/mpp.12117). Ehinger, M., Mohr, T.J., Starcevich, J.B., Sachs, J.L., Porter, S.S. & Simms, E.L. (2014) Specialization-gener- alization trade-off in a Bradyrhizobium symbiosis with wild legume hosts. BMC Ecol. 14, 8. Gamliel-Atinsky, E., Freeman, S., Sztejnberg, A., Maymon, M., Ochoa, R., Belausov, E. & Palevsky, E. (2009) Interaction of the mite Aceria mangiferae with Fusarium mangiferae, the causal agent of mango malfor- mation disease. Phytopathol. 99, 152-159.

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Hayat, S., Ahmad, A., Alyemeni, M.N. (eds.) (2013) Salicylic acid: plant growth and development. Springer, Dordrecht. Heck, S., Grau, T., Buchala, A., Métraux, J.P. & Nawrath, C. (2003) Genetic evidence that expression of NahG modifies defence pathways independent of salicylic acid biosynthesis in the Arabidopsis-Pseudomonas syringae pv. tomato interaction. Plant J. 36, 342-352. Janjusevic, R., Abramovitch, R.B., Martin, G.B. & Stebbins, C.E. (2006) A bacterial inhibitor of host programmed cell death defenses is an E3 ubiquitin ligase. Science 311, 222-226. Lozano-Torres, J.L., Wilbers, R.H.P., Gawronski, P., Boshoven, J.C., Finkers-Tomczak, A., Cordewener, J.H.G., America, A.H.P., Overmars, H.A., Van ‘t Klooster, J.W., Baranowski, L., Sobczak, M., Ilyas, M., Van der Hoorn, R.A.L., Schots, A., De Wit, P.J.G.M., Bakker, J., Goverse, A. & Smant, G. (2012) Dual disease resistance mediated by the immune receptor Cf-2 in tomato requires a common virulence target of a fungus and a nematode. Proc. Natl. Acad. Sci. USA. 109, 10119-10124. Mouttet, R., Kaplan, I., Bearez, P., Amiens-Desneux, E. & Desneux, N. (2013) Spatiotemporal patterns of induced resistance and susceptibility linking diverse plant parasites. Oecol. 173, 1379-1386. Pallini, A., Janssen, A. & Sabelis, M.W. (1997) Odour-mediated responses of phytophagous mites to conspe- cific and heterospecific competitors. Oecol. 110, 179-185. Robert, C.A.M., Frank, D.L., Leach, K.A., Turlings, T.C.J., Hibbard, B.E. & Erb, M. (2013) Direct and indirect plant defenses are not suppressed by endosymbionts of a specialist root herbivore. J. Chem. Ecol. 39, 507-515. Sarmento, R.A., Lemos, F., Dias, C.R., Kikuchi, W.T., Rodrigues, J.C.P., Pallini, A., Sabelis, M.W. & Janssen, A. (2011) A herbivorous mite down-regulates plant defence and produces web to exclude competitors. PLoS ONE 6, e23757. Sindhu, A.S., Maier, T.R., Mitchum, M.G., Hussey, R.S., Davis, E.L. & Baum, T.J. (2009) Effective and specific in planta RNAi in cyst nematodes: expression interference of four parasitism genes reduces parasitic success. J. Exp. Bot. 60, 315-324. Soler, R., Badenes-Pérez, F.R., Broekgaarden, C., Zheng, S.-J., David, A., Boland, W. & Dicke, M. (2012) Plant-mediated facilitation between a leaf-feeding and a phloem-feeding insect in a brassicaceous plant: from insect performance to gene transcription. Func. Ecol. 26, 156-166. Soler, R., Erb, M. & Kaplan, I. (2013) Long distance root–shoot signalling in plant–insect community interactions. Trends Plant Sci. 18, 149-156. Stout M.J., Thaler J.S. & Thomma, B. (2006) Plant-mediated interactions between pathogenic microorganisms and herbivorous arthropods. Annu. Rev. Entomol. 51, 663-89. Sugio, A., Kingdom, H.N., MacLean, A.M., Grieve, V.M. & Hogenhout, S.A. (2011) Phytoplasma protein effector SAP11 enhances insect vector reproduction by manipulating plant development and defense hormone biosynthesis. Proc. Natl. Acad. Sci. USA 108, E1254-E1263. Tornero, P., Gadea, J., Conejero, V. & Vera, P. (1997) Two PR-1 genes from tomato are differentially regulated and reveal a novel mode of expression for a pathogenesis-related gene during the hypersensitive response and development. Mol. Plant Microbe Int. 10, 624-634. Win, J., Chaparro-Garcia, A., Belhaj, K., Saunders, D.G.O., Yoshida, K., Dong, S., Schornack, S., Zipfel, C., Robatzek, S., Hogenhout, S.A. & Kamoun, S. (2012) Effector biology of plant-associated organisms: con- cepts and perspectives. Cold Spring Harb. Symp. Quant. Biol. 77, 235-247. Zhang, P.J., Zheng, S.J., Van Loon, J.J.A., Boland, W., David, A., Mumm, R. & Dicke, M. (2009) Whiteflies interfere with indirect plant defense against spider mites in Lima bean. Proc. Natl. Acad. Sci. USA 106, 21202-21207.

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TABLE S6.1 List of the fungi (A), bacteria (B) and viruses (C) that were tested in russet mite-infested leaf material. None of these were detected.

Plant pathogenic fungi Plant pathogenic bacteria Viruses Alternaria sp. Erwinia amylovora Komkommermozaïekvirus Athelia (Sclerotium) rolfsi Erwinia carotovora stam Alstroemeria (CMV-A) Botrytis sp. Erwinia chrysanthemi Impatiëns-vlekkenvirus (INSV) Botrytis cinerea Pseudomonas chicorii Pepinomozaïekvirus (PepMV) Botrytis porri Pseudomonas fluorescens Tabaksmozaïekvirus WU1 Botrytis tulipae Pseudomonas marginalis Tomatemozaïekvirus stam D 03 Colletotrichum sp. Pseudomonas syringae Tomatenbronsvlekkenvirus (TSWV) Colletotrichum acutatum Pseudomonas viridiflava Colletotrichum coccodes Ralstonia solanacearum Coniothyrium fuckelii Rhizobiuim radiobacter Cylindrocladium sp. Xanthomonas fragariae Cylindrocarpon destructans Didymella sp. Fusarium sp. Fusarium culmorum Fusarium oxysporum Fusarium sacchari Fusarium solani Geotrichum candidum Myrothecium roridum Phoma destructiva Phomopsis scleriotioides Plectosphaerella cucumerina Pyrenochaeta lycopersici Rhizoctonia solani Sclerotinia sp. Sclerotinia minor Sclerotinia sclerotiorum Sclerotinia trifoliorum Thielaviopsis basicola Verticillium sp. Verticillium albo-atrum Verticillium dahliae Pythium sp. Pythium aphanidermatum Pythium dissotocum Pythium irregulare Pythium polymastum Pythium sylvaticum Pythium ultimum Phytophthora sp. Phytophthora cactorum Phytophthora capsici Phytophthora cinamomi Phytophthora citricola Phytophthora cryptogea Phytophthora drechsleri Phytophthora infestans Phytophthora nicotianae Phytophthora ramorum

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Supplemental methods

Mite material Tomato russet mites (A. lycopersici) were reared in insect cages (BugDorm-44590DH, Bug Dorm Store, MegaView Science, Taichung, Taiwan) in a climate room on toma- to (S. lycopersicum) plants (cv. Castlemart) that were between 3 and 6 weeks old. The climate room was set to day/night temperatures of 27ºC/25ºC, a 16/8 h light/dark regime and 60% RH. Harvesting of russet mites was performed regularly by detaching highly infested leaflets and placing them in 1.5-ml Eppendorf tubes.

Eppendorf tubes were filled with H2O and mites (all stages) were washed off by rins- ing and briefly vortexing the tubes. Then, tubes were centrifuged (13.000 rpm for 3 min) after which the tomato tissue was removed. Tubes were centrifuged again

(13.000 rpm for 2 min) after which the H2O was carefully pipetted out. The resulting ‘pellet’ of russet mites was frozen in liquid nitrogen and stored at -80°C until RNA or DNA was extracted.

Aculops lycopersici cDNA RNA was extracted from russet mites using the RNeasy Mini Kit (Qiagen, Valencia, USA), according to the manufacturers instructions. Forty-five μg of russet mite total RNA was submitted to poly(A)+ selection of mRNA. First strand cDNA synthesis was primed with a N6 randomized primer. Then, two adapters required for 454 sequencing, called A and B, were ligated to the 5' and 3' ends of the cDNA. The cDNA was finally amplified with 17 PCR cycles using a proof reading enzyme. Subsequently, the cDNA was normalized by one cycle of denaturation and reassociation of the cDNA. Reassociated ds-cDNA was separated from the remaining ss-cDNA (normalized cDNA) by passing the mixture over a hydroxylapatite column. After hydroxylapatite chromatography, the ss-cDNA was PCR amplified for seven cycles. For 454- Titanium+ sequencing, the cDNA in the size range of 500-800 bp was eluted from a preparative agarose gel delivering 20 μl of 29 ng/μl cDNA. An aliquot of the size frac- tionated cDNA was analyzed by capillary electrophoresis. Using MIRA software, 1.271.693 of the 1.370.005 raw sequencing reads were assembled in a strand-specific manner into 17064 contigs with an average coverage of 30 (courtesy Carlos Villarroel). Contigs were blastx annotated using Blast2Go using default parameter settings. Contamination with tomato cDNA was estimated to be in the range of 4%.

Aculops lycopersici gDNA DNA was extracted using a slighly modified version of the CTAB method (Doyle & Doyle, 1987). Sixty μg DNA dissolved in TE buffer was used for the preparation of three 454-Titanium+ sequencing libraries at Eurofins (Germany): (1) a shotgun library

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obtained via random priming; (2) a 8 Kb long-paired end library and (3) a 20 Kb long- paired end library. The shotgun library delivered 1.854.028 reads with a mean length of 503 nts; the 8 kb library 561.338 paired reads with a mean length of 366 nts (170 nts per read) and the 20 kb library 671.995 paired reads with a mean length of 359 nts (169 per read). Using MIRA and Newbler software, these were assembled into 22 scaffolds with 32-fold coverage. Five of these scaffolds comprised the complete 32.4 Mb A. lycopersici genome which has two holokinetic chromosomes. Although the connections are weak, probably scaffold 1 connects to scaffold 3 into a 16.1 Mb superscaffold while scaffold 5 connects via scaffold 2 to scaffold 4 into a 16.4 Mb superscaffold. The assembly harbors only 392 gaps longer than 50 nts. The GC content of the genome is 45.8. The mitochondrion assembled into a single 13.5 Mb scaffold. The remaining scaffolds (in total 2.4 Mb) were from non A. lycopersici DNA: six of these could be mapped to the tomato genome and the remaining 11 fragments are most probably of prokaryotic origin. The 17064 cDNA-derived contigs were blasted to the genome via blastn and this resulted in 12.427 putative loci: 2685 of these were overlapping on opposite strands of the gDNA (i.e., cis-natural antisense RNAs). Subsequently, the raw sequencing reads were used for extrapolating a gene model (VIB Ghent: Stephane Rombauts and Yves Van De Peer) from the five genome scaffolds and this resulted into 12.779 predicted proteins (for comparison: there are 18.316 in the 90Mb large T. urticae genome) which are 266 amino acids long on average (for comparison: these are 359 amino acids long on average for T. urticae). 4206 of these could not be blastx annotated (using Blast2GO on the non-redundant protein database of NCBI) whith an E- value cut off of < 1E-10 while 7714 had their highest hit within the T. urticae data base. The splice sites in the A. lycopersici genome appeared highly conserved with on average only 1.5 exons per gene (for comparison: 3.8 exons per gene for T. urticae) and an average intron length of 500 nts (for comparison: 407 nts for T. urticae). Interestingly, A. lycopersici proteins are very rich in low-complexity regions outside of functional domains, a property predicted for compact genomes (Gunasekaran et al., 2003). However, we did not perform a quantitative analysis of this phenomenon yet.

Selection of effector candidates Candidates were selected from the predicted proteome (12779 proteins) on the basis of arbitrary hierarchical filters: (1) the presence of a signal peptide using Phobius and SignalP (2118 proteins left which cluster into 1749 families using MLC) then (2) the absence of trans-membrane domains using TMHelix (1327 proteins left) followed by (3) target side prediction using WOLFP Sort and we continued with the 517 proteins that had no organelle prediction (note that 194 had a nuclear prediction). We used a

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cut off of a maximum of 500 amino acids long (still relatively long since the average eukaryotic protein is 350 amino acids long) and at least eight cysteins. Using these criteria, 59 proteins were left of which 32 could not be annotated. Of the remaining proteins, six were annotated as ‘secreted salivary gland peptides’, three as ‘cuticular proteins’ and one as a ‘midgut chitinase’ and another one as ‘Cathepsin S’ (belonging to a large family of 19 papain-like genes).

Illumina MiSeq Universal 16S primers (Primer_FW: TCCTACGGGNGGCWGCAG; Primer_RV: TGAC- TACHVGGGTATCTAAKCC) were used on russet mite DNA to amplify a 444 bp large region by PCR. The product was purified and barcoded and a 2 × 250 bp paired-end read library was constructed which was subsequently sequenced using Ilumina MiSeq at LGC genomics (Berlin, Germany). This delivered 255.194 reads (127.597 pairs) which were assembled using Qiime software after chloroplast sequences had been removed. Operational Taxonomic Units were derived via a blast on GreenGenes (http://greengenes.lbl.gov/cgi-bin/nph-index.cgi) and those comprising <0.1% of the sample were removed (courtesy Heike Staudacher). Bacteria represented by <0.2% of the total pool were an alpha-proteobacterium (genus Wolbachia), two gamma-proteobacteria (family of the Enterobacteriaceae and the Pseudomonadaceae) and one beta-proteobacterium (family of the Comamonadaceae). The remaining bacterial groups were all alpha-proteobacteria: i.e., 6.6% beloning to the order of the Rickettsiales; 25.4% belonging to the genus Sphingomonas and 62.3% to the family of the Bradyrhizobiaceae.

References Doyle, J.J. & Doyle, J.L. (1987) A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem. Bull. 19, 11-15. Gunasekaran, K., Tsai, C.J., Kumar, S., Zanuy, D. & Nussinov, R. (2003) Extended disordered proteins: targeting function with less scaffold. Trends Biochem. Sci. 28, 81-85.

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Summary

lants are members of complex ecological communities, often consisting of Pspecies from different trophic levels, including herbivorous arthropods, plant pathogenic micro-organisms, predators, parasitoids and pollinators. Attack by herbivores and pathogens leads to the rapid adjustment of a plant’s metabolism, which may affect interactions in the entire plant-associated community. The molecular mechanisms of plant defense responses, as well as how these responses mediate interactions with the various plant community members, are currently topics of major interest in the field of plant-herbivore interactions. In the research described in this thesis, I have investigated ecological interactions occurring between members of a simple community on the cultivated tomato (Solanum lycopersicum). For my experiments, I used three herbivore species as well as a microbial pathogen: (1) the specialist tomato russet mite (Aculops lycopersici); (2) the generalist two-spotted spider mite (Tetranychus urticae); (3) the specialist tomato red spider mite (Tetranychus evansi) and 4) the plant pathogen Pseudomonas syringae pv. tomato (Pst). In the first part of this thesis, the consequences of russet mite herbivory for tomato plant defenses are described. Tomato defenses are regulated by two main phytohormones: jasmonic and salicylic acid, and these two are well-known to antagonize each other’s actions. As reported in CHAPTERS 2 and 4, I found that russet mites caused an accumulation of the plant hormone jasmonic acid (JA), just like spider mites did. However, defense responses downstream of JA-accumulation were not, or only marginally, induced by russet mites whereas they were strongly induced by spider mites. From this result, I conclude that russet mites suppress JA-defenses and this suppression occurs downstream of JA-biosynthesis. Additional infestation of spider mite-infested plants with russet mites resulted in a significant downregulation of the spider mite-induced JA-response. In contrast, both russet mites and spider mites induced a strong salicylic acid (SA)-dependent defense response, and, accordingly, this response was doubled in the presence of both mite species. Furthermore, a significant suppression of spider mite-induced JA-defense marker genes by russet mites was not observed in SA-deficient nahG tomatoes, indicating that in the presence of both species spider mite-induced JA-responses are antagonized by SA. However, in contrast to spider mites alone, russet mites alone still did not induce JA-responses in nahG plants. This suggests that russet mites suppress JA-defenses independ-

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SUMMARY

ent from SA, even though accumulation of the latter might well reinforce this suppression. In the second part of this thesis, the ecological consequences of russet mite- induced responses were investigated using two natural competitors of russet mites: the spider mite T. urticae and the bacterial leaf pathogen Pst. As described in CHAPTER 3, I found that spider mites had a higher reproductive performance on wild- type tomato plants that had been pre-infested with russet mites compared to clean plants, which may explain why in the field russet mite infestations are often followed by spider mite infestations. Increased performance of spider mites on russet mite- infested plants was not observed on JA-deficient def-1 plants, nor on prosys+ plants, which display constitutively activated JA-responses, suggesting that the positive effect of russet mites on spider mites is due to suppression of JA-defenses by russet mites. Spider mites, in turn, inhibited russet mite growth and this happened on both wild-type and def-1 plants, suggesting that it is due to direct competition of spider mites on russet mites. In additional experiments, I found that russet mites suppressed growth of the bacterial pathogen P. syringae on wild-type, but not on nahG tomatoes, indicating that Pst suffers from SA induced by russet mites. In CHAPTER 4, the analysis of transcriptional changes of single genes was extended by performing a transcriptome-wide analysis in mite-infested tomatoes using microar- rays, with the specific aim to compare transcriptional changes induced by the two ‘suppressor’ species T. evansi and A. lycopersici. In terms of number of genes regulated, the russet mite-induced transcriptional profile appeared to be similar to that induced by T. urticae whereas the effect caused by T. evansi was much more subtle compared to T. urticae and A. lycopersici (ca. 8× fewer genes regulated). The mechanisms underlying this differential impact on the tomato transcriptome remain to be elucidated. In the third part of the thesis, the implications of russet mite attack for biological control were investigated. As reported in CHAPTER 5, russet mite herbivory causes a distinct and dramatic effect on the tomato glandular trichomes, i.e. the heads of glandular trichome rapidly turn brown, after which they dry out and collapse onto the plant surface, as do the non-glandular trichomes. As a consequence of the clearing of the trichomes, predatory mites were better able to establish themselves on russet mite-infested plants, even though biological control on these plants appeared to be still insufficient. This is likely due to the fact that too many russet mites still receive protection from predation from trichomes that have not yet degraded. The functional significance of the ‘trichome degradation’ phenotype as well as the mechanism underlying this phenomenon remains to be determined. Finally, as discussed in CHAPTER 6, we sequenced the russet mite genome allowing us to identify some candidate effector proteins, which might be involved in russet mite-induced defense suppression as well as trichome degradation.

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Samenvatting

lanten vormen de basis van complexe ecologische levensgemeenschappen, be- Pstaan de uit soorten van diverse trofische niveaus zoals plantenetende insecten en mijten, plant pathogene micro-organismen, bestuivers, parasitoïden en preda- toren. Insectenvraat en ziektes veroorzaakt door plant pathogenen leiden tot ingrij- pende veranderingen in het metabolisme van een plant, met mogelijke gevolgen voor de hele levensgemeenschap rondom de plant. De moleculaire mechanismen van plant-afweerreacties alsmede de consequenties van deze reacties voor interacties met andere organismen zijn onderwerpen die tegenwoordig volop in de belang- stelling staat binnen het onderzoeksveld van plant-herbivoor relaties. In het onderzoek beschreven in dit proefschrift heb ik me gericht op ecologische relaties zoals die voorkomen binnen een simpele levensgemeenschap van plant parasieten op de gecultiveerde tomaat (Solanum lycopersicum). Voor mijn experimenten heb ik gebruik gemaakt van drie soorten herbivoren en een pathogeen: (1) de specialistische tomatenroestmijt (Aculops lycopersici); (2) the generalistische bonenspintmijt (Tetranychus urticae); (3) de specialistische invasieve spintmijt (Tetranychus evansi) en (4) de plant pathogeen Pseudomonas syringae pv. tomato (Pst). In het eerste deel van dit proefschrift heb ik onderzocht hoe tomatenplanten rea- geren op herbivorie door roestmijten. In verdediging van tomaat tegen plagen en ziekten spelen twee hormonen een belangrijke rol: jasmonzuur en salicylzuur en het is bekend dat deze twee hormonen een negatief effect op elkaar hebben. Net als bonenspintmijten bleken roestmijten de productie van jasmonzuur te stimuleren. Echter, in tegenstelling tot bonenspintmijten die ook de bijbehorende jasmonzuur- gereguleerde verdedigingsrespons induceerden, deden roestmijten dit niet. Uit dit resultaat concluderen we dat roestmijten de jasmonzuurrespons van tomaat kunnen onderdrukken, en het is aannemelijk om te denken dat deze onderdrukking plaats- vindt downstream van de productie van jasmonzuur. Verder bleek dat zowel roest- als spintmijten een sterke salicylzuur-afhankelijke respons induceerden, en deze respons bleek dubbel zo sterk in de aanwezigheid van beide soorten mijten, terwijl de spintmijt-geïnduceerde jasmonzuurrespons juist onderdrukt werd in planten met beide soorten mijten. Ook zagen we dat in salicylzuur-deficiënte nahG tomaten suppressie van de spintmijt-geïnduceerde jasmonzuurrespons vaak niet meer significant was terwijl roestmijten alleen, in tegenstelling tot spintmijten alleen, ook in nahG tomaten geen jasmonzuurrespons induceerden. Uit deze resultaten concluderen we dat roestmijten de jasmonzuurrespons van

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SAMENVATTING

tomaat onderdrukken, onafhankelijk van salicylzuur, terwijl in bladeren geïnfesteerd met beide soorten mijten de gecombineerde salicylzuurrespons de reden is voor de onderdrukking van de jasmonzuurrespons. In het tweede deel van dit proefschrift heb ik me gericht op de gevolgen van roestmijt-geïnduceerde veranderingen in de plant voor twee natuurlijke concurrenten van de roestmijt: de bonenspintmijt T. urticae en de plant pathogeen Pst. Spintmijten bleken meer eitjes te leggen op tomaten die in aanwezigheid van roestmijten, maar dit effect werd niet gevonden op de jasmonzuur-deficiënte tomaten mutant def-1 en ook niet op planten van het transgene genotype prosys+, die een sterkere jasmonzuurrespons vertonen in reactie op herbivorie. Uit deze resultaten concluderen we dat spintmijten profiteren van de aanwezigheid van roestmijten vanwege het onderdrukken van jasmonzuur verdediging door laatstgenoemde. Dit resultaat zou kunnen verklaren waarom op tomatenplanten in het veld aantastingen met roestmijten vaak worden gevolgd door infecties met spintmijt. Spintmijten bleken op hun beurt de groei van roestmijten te remmen, en omdat dit gebeurde op zowel wild-type als verdedigingloze def-1 planten denken we dat dit effect veroorzaakt wordt directe competitie van spintmijten op roestmijten. Uit aan- vullende experimenten bleek dat roestmijten de groei van de bacterie Pst remmen in wild-type, maar niet in nahG tomaten. Dit resultaat laat zien dat Pst last heeft van sali cylzuur geïnduceerd door roestmijten. HOOFDSTUK 4 beschrijft resultaten van tomaten microarray-experimenten, die zijn uitgevoerd om transcriptionele veranderingen na vraat door de twee verdediging- onderdrukkende soorten T. evansi en A. lycopersici met elkaar te kunnen vergelijken. Het bleek dat T. urticae en A. lycopersici een vergelijkbaar aantal genen reguleerden, terwijl T. evansi veel (ca. 8×) minder genen reguleerde. De mechanismen die verant- woordelijk zijn voor dit verschil moeten in vervolgonderzoek worden opgehelderd. Een opvallend verschijnsel dat optreedt na herbivorie door roestmijten is het omvallen van de trichomen. In het derde deel van dit proefschrift hebben we de consequenties van dit verschijnsel voor biologische bestrijding onderzocht. Ondanks dat roofmijten zich beter konden vestigen op planten waar roestmijten opzaten, waarschijnlijk doordat ze minder gehinderd werden door de trichomen, bleek biologische bestrijding niet goed te werken. We denken dat dit komt omdat teveel roestmijten nog bescherming zoeken tussen de trichomen die nog niet zijn omgevallen. Waarom roestmijten de trichomen laten omvallen en hoe dit precies werkt is nog onduidelijk en vereist meer onderzoek. Tenslotte, zoals beschreven in HOOFDSTUK 6, is het genoom van de roestmijten in kaart gebracht. Dit is een eerste stap naar het identificeren van kandidaat effector eiwitten die mogelijk een rol spelen in het onderdrukken van de tomaten verdediging door roestmijten en het omvallen van de trichomen.

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Biography

oris Glas was born on February 28, 1983, in JAmsterdam, The Netherlands. After spending his childhood in Nkandla (South Africa), he returned to The Netherlands at the age of 11 where he obtained his secondary school certificate (VWO, Greijdanus College, Zwolle) in 2001. Subsequently, he studied Biology at Wageningen University where he graduated in 2007. The research for his Master’s thesis was carried out in Potchefstroom (South Africa) under supervision of prof. Johnnie van den Berg (North- West University) and prof. Marcel Dicke (Wageningen University). Also as part of his Master’s, he spent 5 months in the lab of prof. May R. Berenbaum (University of Illinois, USA) for an internship. He then, in 2007, moved to Amsterdam and complet- ed a 1-year Master’s program in Philosophy at the Free University. On February 1, 2009, Joris started his PhD-project in the group of dr. Merijn Kant (Molecular and Chemical Ecology) and prof. Maus W. Sabelis (Population Biology) at the Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam. From January 1, 2014, Joris is employed as a postdoctoral researcher in the same group.

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Dankwoord / Acknowledgements

et het schrijven van dit dankwoord is een eind gekomen aan een periode van Mruim 5 jaar onderzoek doen. Vijf jaar waarin veel mensen een belangrijke rol hebben gespeeld en van wie de hulp en steun onmisbaar is geweest. In de eerste plaats wil ik jou bedanken, Maus, voor het warme welkom in de groep en je vertrouwen. Het blijft grappig dat ik via Matthijs, mijn toenmalige huisgenoot, in contact met je kwam, af en toe meeging naar seminars, en uiteindelijk zelfs bij je ben gaan promoveren. En wat een uitstekend idee om met Aculops te gaan werken! Je enthousiasme voor het onderzoek is aanstekelijk en het is dankzij jouw inspanningen dat we zo’n diverse, leuke en levendige groep hebben, met collega’s afkomstig uit de hele wereld. Dank voor de vele avondjes uit eten, meestal op donderdag na een sem- inar, en die superleuke zeildag in Friesland. Het bericht over jouw ziekte was een slag voor iedereen, en het maakt me stil als ik jou zie vechten voor je gezondheid. Merijn, daar is ‘ie dan, het proefschrift van je eerste aio. Ik realiseer me dat je met het aannemen van mij een risico nam aangezien ik in eerste instantie niet veel erva- ring had met labwerk. En dat was wel wat er (ook) moest gebeuren. Dank voor je vertrouwen, je inspanningen om mij wegwijs te maken in de wereld van de moleculaire biologie, je goede ideeën, je snelle commentaren, en je geduld. Ik heb er erg veel van geleerd, en ik heb zin om nu echt verder met het nieuwe project aan de slag te gaan. En natuurlijk gefeliciteerd met je VIDI, wat een topresultaat! Uiteraard veel dank ook voor alle aio’s en postdocs, collega’s die meer dan eens vrienden zijn geworden. Juan, we have worked together from the beginning and there were months that I saw you more than any other person. Your persistence and enthu- siasm for science are admirable and an example for many of us. Thanks for your sin- cere interest in what I was doing and all the support and help. Bart, dank voor de gezelligheid tijdens al die keren samen eten. Dankzij jou zijn een aantal dingen op het lab nu een stuk beter georganiseerd dan voorheen. Succes met al die transformaties, en leuk dat we nog een tijd directe collega’s zijn! Carlos, that day we went cycling to the beach was great, thanks. Good luck with your mite effectors, nice work! Fernando & Heike, thanks for your friendship, for the daily talks, for the jokes, for being the people who you are. It was great fun to work together, and I will especially never forget those days we had in Mariazell, that was great! Next time you run the Silvesterlauf as well, I hope ☺. Dear Karen, thanks for your friendship, for the talks and walks, and for your support at difficult moments, it was very important for me.

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DANKWOORD

Marije en Astra, het was superleuk om jullie te begeleiden tijdens jullie stages, dank voor jullie bijdragen! Dit project was niet mogelijk geweest zonder de samenwerking met de Plant Fysiologen. Rob en Michel, dank voor jullie frisse blik, enthousiasme en constructieve feedback tijdens de wekelijkse Plantenfysiologiemeetings. Rossana, thanks for teaching us the basics of cloning and plant transformations, it was very useful and a great experience. The other Plant Physiologists, Alessandra, Arjen, Eleni, Michel de V, Petra, Piet, Silke, thanks for all those times you guys helped me out by answering a question or borrowing something. Ook het team van het IBED moleculaire lab, Betsie, Lin en Peter, het blijft een uitdaging, DNA isoleren van Aculops, en je hebt er VEEL voor nodig. Bedankt voor jullie hulp! Then all the other people I had the privilege to work with, have coffee with, or share a room with during the past years: Alexandra, Anieke, Arne, Bram, Chris, Dan, Felipe, Firdevs, Floor, George, Isa, Jie, Josinaldo, Livia, Maria, Martijn, Michiel, Nazer, Nicola, Nicky, Nina, Paul, Paulien, Rocio, Roos, Sauro, Thomas, Wagner, Yukie. Thanks for being such nice colleagues! De collega’s van Koppert, Yvonne, Hans, Markus, ik vond het leuk dat jullie betrokken waren bij dit project en ik vind het interessant om van dichtbij de vertaling van wetenschappelijke resultaten naar de praktijk te zien. Ik zie er naar uit om ook de komende jaren met jullie samen te werken. Jan van Arkel, de foto’s zijn fantastisch, dank voor de prettige samenwerking. Jan Bruin, ik denk nog vaak met plezier terug aan die week in Ceský Krumlov! Leuk dat jij uiteindelijk ook m’n proefschrift in elkaar hebt gezet, dank. Harold, Ludek en Thijs, bedankt voor alle afgeleverde tomaten, jullie zijn een superteam en het was altijd gezellig om even langs te komen voor planten en een praatje. Lieve familie en vrienden, jullie herinnerden mij er steeds weer aan dat de wereld toch echt groter is dan het sciencepark. Dank daarvoor, het was af en toe nodig, geloof ik. De ‘Wageningers’ Johan, Bob & Christine, Rudolf, Charlotte, Gerd, Gert, Richard & Mariëlle, Jacob & Willemien, Melle & Alida, Michel & Janne, Marnix & Marian, Jan Ubbo & Aukje, dank voor jullie vriendschap. Huisgenoten, Matthijs, Arjen, Geert Jan, dank voor al die keren dat er een biertje was, een gesprek, begrip en soms ook relativering. Allen die ik in de Tituskapel leerde kennen, dank voor ont- moeting en gesprek, het is erg belangrijk geweest. Lieve papa en mama, Arie & Lisanne, Janske, Boudewijn & Livia, Wypkjen & Teun-Pieter, Wolter & Fennelien en Victorine. Het was altijd fijn om met enige regelmaat een weekend in Beerzerveld te zijn en weer even te proeven van het buitenleven, en niet te vergeten de ‘GB’ op zondagavond. Dank voor wie jullie zijn, voor alle begrip, steun en liefde, ik voel me een bevoorrecht mens. In het bijzonder ook bedankt, Wyp en TP, voor al die keren dat ik bij jullie aan de Wibautstraat terecht kon voor een bord met eten na een lange dag werken. Dat was goed.

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ACKNOWLEDGEMENTS

Lieve Elsa, je hebt veel meegekregen van mijn promotieperikelen, eerst van een afstand, later van dichtbij. Dank voor wie je bent, je meeleven en steun, je vult me aan op een manier die ik niet van tevoren had kunnen bedenken. Ik voel me geze- gend met jou. Soli Deo gloria

Joris Glas, 20 mei 2014

176 Consequences of russet mite-induced tomato defenses for community interactions mite-induced tomato defenses for community interactions Consequences of russet Uitnodiging Consequences of russet mite-induced Tot het bijwonen van de openbare tomato defenses for community verdediging van het proefschrift interactions Consequences of russet mite-induced tomato defenses for community interactions

door Joris Glas

Woensdag 02 juli 2014 om 12:00 uur in de Agnietenkapel Oudezijds Voorburgwal 231 te Amsterdam

Receptie na afloop van de verdediging

Joris Glas [email protected] 06-30238878

Paranimfen: Joris Glas 2014

Arie Glas [email protected] 06-13560469

Johan Bondt Joris Glas [email protected] 06-52463089