doi:10.1111/j.1420-9101.2010.02112.x

Do insect pests perform better on highly defended plants? Costs and benefits of induced detoxification defences in the aphid Sitobion avenae L. E. CASTAN˜ EDA, C. C. FIGUEROA & R. F. NESPOLO Instituto de Ecologı´a y Evolucio´n, Facultad de Ciencias, Universidad Austral de Chile, Valdivia, Chile

Keywords:

Abstract

detoxification enzymes; fitness cost; genetic variation; insect-plant interaction; phenotypic plasticity; plant chemical defences; standard metabolic rate; trade-offs.

Induced defences are a typical case of phenotypic plasticity, involving benefits for ‘plastic’ phenotypes under environments with variable degree of stress. Defence induction, in turn, could be energetically expensive incurring costs on growth and reproduction. In this study, we investigated the genetic variation and induction of detoxification enzymes mediated by wheat chemical defences (hydroxamic acids; Hx), and their metabolic and fitness costs using five multilocus genotypes of the grain aphid (Sitobion avenae). Cytochrome P450 monooxygenases and glutathione S-transferases activities were seen to increase with Hx levels, whereas esterases activity and standard metabolic rate increased in wheat hosts with low Hx levels. Additionally, the intrinsic rate of increase (a fitness proxy) increased in highly defended hosts. However, we did not find significant genetic variation or genotype–host interaction for any studied trait. Therefore, aphids feeding on host plants with elevated chemical defences appeared to reduce their detoxification costs and to increase their reproductive performance, which we interpret as a novel adaptation to defended plants. In brief, this study supports the notion that aphids perform better on highly defended host plants, probably related to the selective pressures during the colonization of New World agroecosystems, characterized by highly defended host plants.

Introduction The study of phenotypic plasticity and its evolutionary consequences has contributed towards shaping the ecological framework of modern evolutionary biology (Schlichting & Pigliucci, 1998; DeWitt & Scheiner, 2004). Commonly, phenotypic plasticity is defined as the change in the mean phenotype expressed by a certain genotype across a range of different environments (Bradshaw, 1965; Schlichting & Pigliucci, 1998). In a population exposed to heterogeneous environments, most organisms modify their phenotypes in order to reduce deleterious environmental effects and mortality risks (Agrawal, 2001; Hammill et al., 2008). Therefore, ‘plastic’ phenoCorrespondence: Luis E. Castan˜eda, Instituto de Ecologı´a y Evolucio´n, Facultad de Ciencias, Universidad Austral de Chile, Valdivia, 5110566, Chile. Tel.: +56 (63) 221704; fax: +56 (63) 221344; e-mail: [email protected]

types should receive a net fitness reward, although incurring significant maintenance costs compared with ‘rigid’ phenotypes (Pigliucci, 2001). Typical cases of phenotypic plasticity are induced defences, because defensive mechanisms are expressed in response to risky environmental cues (Steiner & van Buskirk, 2007). However, it is widely assumed that such defences are costly, generating an allocation trade-off between their maintenance costs and other biological functions such as growth and reproduction (Karban & Agrawal, 2002). Because of this, induced defences appear as the optimal strategy, as they are expressed only when required. On the contrary, if a given defensive phenotype does not represent costs, it should be constitutive and induced defences would not be needed (van Buskirk, 2000). The costs of induced defences are well known in plants, vertebrates, invertebrates and between animal– plant interactions (Agrawal et al., 2002; Gomez-Mestre et al., 2008; Hammill et al., 2008). An interesting model

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for the study of costs and benefits of induced defences concern the interactions between plants and insects (Karban & Agrawal, 2002; Despre´s et al., 2007). This is because plants can produce chemical defences to avoid herbivory, but at the same time, insects can themselves evolve resistance to cope with plant chemical defences. In fact, when insects are facing harmful effects of plant chemical defences, they may express several mechanisms either to detect, evade, sequestrate, excrete and ⁄ or metabolize those plant allelochemicals (Berenbaum, 2001). In the case of metabolic resistance, a high diversity of enzyme families are involved in allelochemical detoxification by insects such as cytochrome P450 monooxygenases (P450s), glutathione S-transferases (GSTs) and esterases (ESTs) (for reviews see Despre´s et al., 2007; Li et al., 2007). These three enzyme families play a critical role in degradation and neutralization of plant allelochemicals into less-toxic compounds, increasing the capacity of insects to exploit chemically defended plants (Berenbaum, 2001; Schoonhoven et al., 2005; Despre´s et al., 2007). In general, it has been found that the metabolic costs of physiological defences represent an important part of the energy budget (Angilletta, 2009). For instance, the induction of heat-shock proteins or immune-related enzymes is related with a reduction in growth, fecundity and survival in insects (Krebs & Loeschcke, 1994; Sørensen et al., 2003; Schwarzenbach & Ward, 2006). Although reductions in insect growth or fecundity occur when detoxifying enzymes are induced, which suggest significant costs of detoxification systems in these animals (Cresswell et al., 1992; Berenbaum & Zangerl, 1994; Agrawal et al., 2002), the detection of metabolic costs for induced enzymes have not been demonstrated (Neal, 1987; Appel & Martin, 1992; Castan˜eda et al., 2009). Therefore, the actual impact of induced detoxification defences on energy budget and their consequence on insect’s fitness is still an open and intriguing question. The evolutionary potential of induced defences depends on the presence of genetic variation in natural populations (Hammill et al., 2008). Substantial genetic variation for induced defences in insects has been reported for the expression of heat-shock proteins (Pauwels et al., 2005) and enzymes involved in detoxification of insecticides (Ferrari & Georghiou, 1991) and ethanol (Pecsenye et al., 2004). There is also evidence of genetic variation in enzymes involved in allelochemical detoxification, such that these mechanisms can be targets of selection, mediated by plant chemistry (Berenbaum & Zangerl, 1992; 1994). A straightforward approach to the study of genetic variation and plasticity of induced defences under heterogeneous environments is the use of organisms with clonal reproduction as models, because clonal lineages can be readily replicated in different treatments or environmental conditions (Richards et al., 2006). Fortunately, study models such as water fleas and aphids meet this experimental requirement because

parthenogenesis can be easily controlled, thus facilitating their replication and maintenance in the laboratory of isolated parthenogenetic lineages. The grain aphid, Sitobion avenae (Fabricius) (Homoptera: Aphididae), is monoecious on certain species of Poaceae, including cereals and pasture grasses (Blackman & Eastop, 2000). These host plants exhibit a broad concentration range of hydroxamic acids (Hx), which are chemical defences involved in resistance against herbivores including aphids (Corcuera et al., 1982; Niemeyer, 2009). It has been proposed that Hx modulate the genetic structuring exhibited by S. avenae (Figueroa et al., 2004, 2005), probably a consequence of heterogeneous selective environments related to host variability (Via, 1991). At the same time, the grain aphid possesses detoxification enzymes like P450s, GSTs and EST to reduce the harmful effects of Hx (Leszczynski et al., 1992; Loayza-Muro et al., 2000). Nevertheless, the response of detoxification enzymes against Hx is not clear in S. avenae. Plastic responses have been reported in aphids reared on plants containing different levels of Hx (Loayza-Muro et al., 2000), and it has also been found that aphids exposed to Hx seem not to induce detoxification enzymes, which represent just a small fraction of the energy budget of this species (Castan˜eda et al., 2009). The main goal of this study was to assess the presence of genetic variation for costs of detoxification enzymes induced by host-plant chemical defences in the grain aphid. To perform this, we measured the activity of detoxification systems (P450s, GSTs and ESTs), standard metabolic rate and life-history traits (i.e. development time, body mass at maturity) in five different multilocus genotypes of S. avenae (equated with ‘clones’ sensu lato; see Loxdale & Lushai, 2003) reared on three wheat cultivars differing in their levels of chemical defences, i.e. Hx.

Material and methods Study population and aphid maintenance During the Austral summer of 2007, 100 live aphids were sampled from ca. 10 hectares of wheat crops close to Valdivia, Chile (4006¢S–7255¢W). To reduce the chance of collecting parthenogenetic aphids from the same colony, a sampling grid in which collecting spots were separated by at least 20 m was used. To establish asexual (parthenogenetic) lineages, single adult wingless females from each sample were placed on 7-day-old barley seedlings (Hordeum vulgarae, a Hx-free host). Lineages were maintained in discrete generations at 20 ± 1º C and 16 h-light photoperiod to ensure asexuality, transferring five wingless adults on new 7-day-old barley seedlings every 10 days. These lineages were maintained for 10 generations on barley until the experiments described below were begun, and genotyped using 7 microsatellite loci (Sm10, Sm17, S3.R, S5.L, S4S, S19 and S24) as

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described by Figueroa et al. (2005). Combining the allelic size of each locus, five different multilocus genotypes (‘genotypes’ for simplicity) were characterized and redundant genotypes were discarded. Collected genotypes, their relative frequencies and allele sizes for the analysed loci are shown in Table 1.

wheat cultivar in order to take life-history measurements (see Life-history traits methodology). Meanwhile, nontransferred F3-nymphs were maintained on the same seedling, and once they had reached adulthood, they were used for standard metabolic rate and enzyme activities measurements.

Experimental design

Standard metabolic rate

To evaluate the effects of plant chemical defences on enzyme activities, standard metabolic rate and life-history traits of the aphids, three wheat cultivars (cv.) (Triticum aestivum) with different concentrations of Hx (mean ± standard error, n = 6) were used as experimental hosts: (i) wheat cv. Huayu´n (low Hx: 0.26 ± 0.08 mmol per kg. fresh mass); (ii) wheat cv. Ciko (intermediate Hx: 2.09 ± 0.6 mmol per kg. fresh mass); and (iii) wheat cv. Quele´n (high Hx: 5.91 ± 1.18 mmol per kg. fresh mass). A nested design was employed to detect any variation within and between genotypes on a certain wheat host as follows (see Lynch & Walsh, 1998, p. 593). Because of logistic constrains related to metabolic measurements, as detailed in the following paragraphs, we performed the experiments on each wheat host separately in time. Parental generation: five adult wingless females of each genotype were transferred from barley seedlings to a 7 day-old wheat seedling of one of the experimental hosts (e.g. low, intermediate or high Hx). After 3 days of asexual reproduction, parental aphids were removed from seedlings. First generation (F1): seven days after removing parental aphids, 10 wingless F1-adults from each genotype were split into two sublines, placed in two different seedlings and removed after 3 days of nymph production. Splitting of each genotype in two sublines allowed the evaluation and statistical control of variations within genotypes and experimental hosts (Castan˜eda et al., 2009). Second generation (F2): seven days after removing F1-adults, 18 wingless F2-adults from each subline were divided into six groups and transferred to new individual seedlings. F2-adults were removed after 1 day of asexual reproduction, and nymphs were maintained on wheat seedlings. Third (focal) generation (F3): after 4 days following F2-adults removal, one of the F3-nymphs was transferred to a new seedling of the same

For each wheat seedling per respective wheat host, nine wingless adult aphids (from the third generation) were collected. These aphids were cooled on ice and weighed to the nearest microgram on a microbalance (Sartorius, Goettingen, Germany) before measuring their standard metabolic rate (SMR). SMR was measured as the volume of CO2 produced by each aphid replicate using stop-flow system as previously described by Castan˜eda et al. (2009; 2010a).

Table 1 Relative frequency (Rf) and allele combination of the five multilocus genotypes of Sitobion avenae identified in this study, using seven microsatellite loci.

Detoxification enzymes Immediately following metabolic rate measurements were performed, each replicate was separated into three groups of three aphids each, whereupon each group was used to determine the specific activity of one detoxification enzyme family ⁄ system: P450s, GSTs, or ESTs. P450s activity was determined by the fluorescent method following Castan˜eda et al. (2009; 2010a), although the temperature at which reactions were incubated was modified from 37 to 30 C by 4 h in a Problot 12S hybridization chamber (Labnet, Woodbridge, NJ). GSTs and ESTs activities were determined by fluorescence and absorbance methods as described by Castan˜eda et al. (2009), respectively. Determinations of GSTs and ESTs activities were performed in two samples per replicate; high correlations were found between them (GSTs: r = 0.95, t130 = 34.99, P < 0.001; and ESTs: r = 0.93, t130 = 29.67, P < 0.001). Hence, we used the average of both measurements as raw data. P450s determination was performed once only. Fluorescence (P450s and GSTs) and absorbance (ESTs) measurements were performed in a Wallac 1420 Victor3 microplate reader (Perkin-Elmer, Waltham, MA, USA). Net fluorescence (for P450s and GSTs) or absorbance (for

Locus Genotype

Rf

Sm10*

Sm17*

S3.R 

S5.L 

S4S*

S19 

S24 

Alpha Beta Gamma Delta Epsilon

0.22 0.28 0.30 0.14 0.06

164 164 154 164 164

178 178 178 178 178

337 337 361 345 361

225 223 217 225 223

170 170 164 164 164

124 138 158 138 138

165 165 165 165 165

166 164 164 164 164

178 178 181 178 178

337 337 361 361 361

227 227 227 227 227

170 174 176 170 170

124 140 174 140 140

182 178 165 165 178

Microsatellite primers developed by Simon et al. (1999) and Wilson et al. (2004) are indicated by * and  , respectively.

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ESTs) corresponded to the difference between the sample and the blanks (i.e. wells containing only reaction buffer). Enzyme activities and aphid body mass (i.e. covariate) were used for statistical analyses, whereas mass-specific enzyme activities (i.e. SMR adjusted by aphid body mass) were used to construct the graphs. Aphid body mass was only used as a covariate when it was significantly correlated with enzyme activities (see Statistical analyses section). Life-history traits Life-history measurements were performed on transferred nymphs of the third generation (see Experimental design section), which were individually caged in clipcages (i.e. a 35 mm diam. plastic Petri dish, foam ring and metallic clip), and placed on leaves of wheat seedlings. Nymphs were checked every 24 h in order to record the first reproduction event (development time: Td). When a wingless F3-female reached reproductive maturity (i.e. asexual production of its first nymph), it was weighted on a microbalance (Sartorius, Goettingen, Germany) to measure body mass at maturity. Only wingless aphids were used as focal individuals, and winged ones were excluded from the experiment. Newborn nymphs produced by each aphid were counted (Md) and removed daily from the clip-cage for a period equal to Td (Hale et al., 2003; Figueroa et al., 2004; Castan˜eda et al., 2010b). Furthermore, we estimated the intrinsic rate of increase (rm) for each aphid, which relates the individual aphid fecundity to development time (Wyatt & White, 1977). It was estimated using the following equation: rm = 0.738 * (lnMd) ⁄ Td, where lnMd is the natural logarithm of Md and 0.738 is a correction factor extracted from the regression slope between intrinsic rate obtained from life-table and Wyatt and White’s methods (1977). This simplified method has been shown to behave in a remarkably similar way to the classical estimator of Birch (1948), which would require a complete life-table and more time-consuming calculations (Castan˜eda et al., 2010a,b). Statistical analyses Statistical analyses were performed using Statistica 6.0 software (Statsoft, Inc, 2004). Assumptions of normality and homoscedasticity were checked for each dependent variable. GSTs activity and body mass at maturity were log10-transformed to fulfil these parametric assumptions. GSTs activity and life-history traits were analysed using a nested mixed-model A N O V A , to test effects of wheat hosts (‘host’ for simplicity), genotypes, interaction between genotype and host, and sublines nested within genotype– host interaction. P450s, ESTs and SMR were analysed using the same effects in a nested mixed-model A N C O V A with body mass as covariate, which was significantly correlated with P450s activity (r = 0.32, t144 = 4.07,

P < 0.001), ESTs activity (r = 0.70, t137 = 11.63, P < 0.001), and SMR (r = 0.79, t139 = 15.31, P < 0.001). For all analyses, host and subline nested within genotype–host were considered as fixed effects, and genotype and genotype–host interaction as random effects. Unequal N HSD tests were performed to evaluate a posteriori differences when effects were significant. Lastly, to evaluate the relationship between fitness and metabolic costs, a linear correlation between rm and mass-residuals of SMR was performed. Residual values were extracted from a significant linear regression between SMR and body mass (F1,139 = 82.46, P < 0.001). Furthermore, an A N C O V A analysis was performed to test differences among genotypes (categorical variable) in the relationship between rm (response variable) and mass-residuals of SMR (predictor variable).

Results Detoxification enzyme activities and SMR Detoxification enzymes varied significantly among wheat hosts, although not all enzymes responded similarly (Fig. 1 and Table 2a–c). The P450s activity exhibited significant effects of wheat hosts (Table 2a), showing an increased activity in hosts with high Hx levels (Fig. 1a). Aphids reared on high Hx host exhibited a higher P450s activity than those on intermediate (P = 0.008) and low Hx wheat hosts (Unequal N HSD tests: P < 0.001). In contrast, aphids on intermediate Hx hosts showed a higher P450s activity than those on low Hx hosts (Unequal N HSD tests: P = 0.008). The GSTs activity varied significant among wheat hosts (Table 2b), highest activity was found on hosts with intermediate Hx levels and then decreased towards hosts with high Hx levels (Fig. 1b). Specifically, aphids reared on low-Hx hosts exhibited a lower GSTs activity than aphids on intermediate (Unequal N HSD tests: P < 0.001) and high-Hx wheat hosts (Unequal N HSD tests: P = 0.004), whereas aphids reared on high-Hx hosts showed a lower activity than on intermediate-Hx hosts (Unequal N HSD tests: P < 0.001). ESTs activity also exhibited a significant effect of wheat hosts (Table 2c), although in this case, the activity decreased in hosts with high Hx levels (Fig. 1c). Aphids reared on high-Hx host exhibited a lower ESTs activity than those reared on intermediate-Hx host (Unequal N HSD tests: P = 0.002) and low-Hx host (Unequal N HSD tests: P < 0.001), whereas ESTs activity of aphids reared on intermediate–Hx host and low-Hx host did not differ significantly (Unequal N HSD tests: P = 0.07). Furthermore, significant differences between wheat hosts were found for SMR (Table 2d), which also decreased in hosts with high Hx levels (Fig. 2a). Aphids reared on high-Hx host exhibited a lower SMR than on intermediate (Unequal N HSD tests: P = 0.01) and lowHx wheat hosts (Unequal N HSD tests: P = 0.002), whereas the SMR of aphids reared on intermediate and

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Mass-specific P450s activity (U replicate–1 mg–1)

Alpha

Beta

Gamma

Deltha

Epsilon

(a) 250

a

b

c

200

150

50

0

3000

(b) a

c

b

GSTs activity (U replicate–1)

2500

2000

1500

1000

500

0

0.08

Mass-specific ESTs activity (U replicate–1 mg–1)

Table 2 Mixed-model nested A N ( C ) O V A testing for genotype (random factor), host (fixed factor), genotype · host (genotype–host interaction; random factor) and subline nested in genotype–host interaction (fixed factor) effects on (a) cytochrome P450 monooxygenases (P450s), glutathione S-transferases (GSTs) and esterases (ESTs) activities, and (d) standard metabolic rate (SMR). Mass was added to A N C O V A when it was significantly correlated with the dependent variable. Effects were considered significant at P < 0.05. Effect

100

(c) a

a

b

5

(a) P450s activity Genotype Host Genotype · host Subline (genotype · Mass Error (b) log10 GSTs activity Genotype Host Genotype · host Subline (genotype · Error (c) ESTs activity Genotype Host Genotype · host Subline (genotype · Mass Error (d) SMR Genotype Host Genotype · host Subline (genotype · Mass Error

host)

host)

host)

host)

d.f.

MS

F

P

4 2 8 15 1 115

683 28123 5286 3405 9480 3166

0.13 5.32 1.55 1.08 2.99

0.967 0.034 0.220 0.387 0.086

4 2 8 15 102

0.008 0.345 0.012 0.012 0.011

0.69 28.26 1.01 1.14

0.621 0.0002 0.465 0.328

4 2 8 15 1 108

0.00002 0.00087 0.00003 0.00004 0.00711 0.00006

0.64 25.80 0.83 0.70 122.84

0.647 0.0003 0.589 0.776 <0.0001

4 2 8 15 1 110

0.253 2.533 0.156 0.174 34.597 0.214

1.63 16.26 0.90 0.81 161.55

0.258 0.002 0.543 0.663 <0.0001

0.06

0.04

0.02

0.00 Low

Intermediate

High

Hx-levels in wheat hosts

Fig. 1 Enzyme activities of (a) cytochrome P450 monooxygenases adjusted by body mass (mass-specific P450s), (b) glutathione S-transferases (GSTs) and (c) esterases adjusted by body mass (massspecific ESTs) in five multilocus genotypes of the aphid S. avenae across three wheat hosts differing in levels of hydroxamic acids (Hx; wheat chemical defences). Nonsignificant differences between genotypes were found. Bars represent mean (±SE) of each genotype, black lines show overall mean in each wheat host and letters indicate significant differences between wheat hosts at P < 0.05.

low-Hx hosts did not differ significantly (Unequal N HSD tests: P = 0.73). On the other hand, neither genotype, genotype–host interaction (i.e. GxE) nor subline nested within genotype–host interaction had significant effects on P450s, GSTs and ESTs activities and SMR (Table 2). These results suggest (i) the absence of genetic variation for enzyme activities and energy metabolism in the aphid lineages tested; (ii) that the ranking of genotypes is maintained across different wheat hosts (e.g. absence of genotypeby-environment interaction); and (iii) absence of subline effects for any genotype tested reared on any wheat host. Life-history traits Development time and body mass at maturity exhibited nonsignificant effects owing to host, genotypes, genotype–host interaction and subline nested within genotype–host interaction (Table 3a,b). However, rm was significantly different between wheat hosts and genotypes (Table 3c), increasing towards highly defended

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Mass-specific SMR (μl h–1 mg–1)

1.0

Alpha

Beta

Gamma

Epsilon

Delta

(a) a

a

b

0.8

0.6

Effect

0.4

0.2

0.0

Intrinsic rate of increase (day–1)

0.4

Table 3 Mixed-model nested A N O V A testing for genotype (random factor), host (fixed factor), genotype · host (genotype–host interaction; random factor) and subline nested in genotype–host interaction (fixed factor) effects on (a) development time, (b) body size at maturity, and (c) intrinsic rate of increase. Effects were considered significant at P < 0.05.

(b) a

b

b

0.3

0.2

(a) Development time Genotype Host Genotype · host Subline (genotype · host) Error (b) Body size at maturity Genotype Host Genotype · host Subline (genotype · host) Error (c) Intrinsic rate of increase Genotype Host Genotype · host Subline (genotype · host) Error

d.f.

MS

F

P

4 2 8 13 91

0.045 0.104 0.039 0.050 0.037

1.14 2.63 0.80 1.33

0.405 0.133 0.617 0.208

4 2 8 12 73

0.030 0.016 0.020 0.016 0.019

1.48 0.79 1.32 0.80

0.295 0.485 0.322 0.651

4 2 8 11 66

0.0021 0.0104 0.0004 0.0009 0.0014

4.98 24.22 0.50 0.63

0.0260 0.0004 0.8307 0.8003

0.1

0.40 0.0 Low

Intermediate

High

Hx-levels in wheat hosts Fig. 2 Standard metabolic rate (a) adjusted by body mass (massspecific SMR), and (b) intrinsic rate of increase in five multilocus genotypes of the aphid S. avenae across three wheat hosts differing in levels of hydroxamic acids (Hx; wheat chemical defences). Bars represent means (±SE) of each genotype, black lines show overall mean in each wheat host, and letters indicate significant differences between wheat hosts at P < 0.05.

hosts (Fig. 2b). Aphids reared on low-Hx host exhibited a lower reproductive performance than on intermediate (Unequal N HSD tests: P = 0.049) and high-Hx hosts (Unequal N HSD tests: P < 0.001). In contrast, rm of aphids reared on intermediate and high-Hx hosts did not differ significantly (P = 0.06). We found significant genetic variation for rm (Table 3c), although following the Unequal N HSD test, we did not find differences between genotypes. Additionally, rm exhibited nonsignificant effects of genotype–host interaction and subline nested within genotype–host interaction (Table 3c). A significant trade-off was found between rm and SMR because they were negatively correlated, suggesting that aphids with low maintenance costs allocated more energy in reproduction (r = )0.23, t86 = 2.13, P = 0.036; Fig. 3). Using an A N C O V A analysis, no significant difference between genotypes was detected in the relationship rm vs. mass-residuals of SMR (F4,80 = 1.35, P = 0.26). This in turn suggests that genetic variation is

Intrinsic rate of increase (day–1)

6

r = –0.23, P = 0.036 0.35 0.30 0.25 0.20 0.15

Low Hx wheat host Intermediate Hx wheat host High Hx wheat host

–0.2

–0.1

0.0

0.1

0.2

Mass-residuals of SMR Fig. 3 Relationship between intrinsic rate of increase and standard metabolic rate (mass-residuals SMR; it was expressed as ll CO2 h)1 aphid)1) in aphids reared on three wheat hosts differing in levels of hydroxamic acids (Hx; wheat chemical defences): low (black circles), intermediate (grey circles), and high (grey triangles) Hx levels. Black line shows the overall trend between both variables.

irrelevant in terms of the relationship between metabolic and fitness costs.

Discussion Plasticity of detoxification defences We found that the activity of detoxification enzymes of the grain aphid exhibited phenotypic plasticity in relation

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to wheat host. One of the main chemical defences in wheat plants are the hydroxamic acids (Osbourn et al., 2003), which play a key role in resistance against a wide range of insects, including aphids (Sicker & Schulz, 2002). Aphids reared on wheat plants with high Hx levels exhibited higher enzyme activities of P450s and GSTs compared to those with low Hx levels. Therefore, induction of these enzymes is most probably related to the chemical defences produced by these plants. Several previous studies in insect herbivorous species have found evidence for an induction of detoxification enzymes by plant chemical defences (see reviews by Agrawal, 2001; Despre´s et al., 2007; Li et al., 2007), including aphids (Leszczynski et al., 1992; Loayza-Muro et al., 2000; Francis et al., 2005). In contrast, aphids reared on plants with high Hx levels displayed a comparatively lower ESTs enzyme activity. Such decrease indicates a response mediated by Hx, an effect reported previously in aphids for enzyme activities of NADPH cytochrome c reductase, GSTs and ESTs (Loayza-Muro et al., 2000; Mukanganyama et al., 2003). Classical explanations for this phenomenon have invoked feeding deterrence (i.e. insects stop feeding) as the proximal cause for reduced enzyme activity when insects feed on plants containing toxic compounds such as alkaloids, glucosinolates, amongst others (Berenbaum, 2001). However, our findings show that aphid body sizes did not change across wheat plants and P450s and GSTs activities increased with Hx levels, so that feeding deterrence is not involved in the reduced activity of ESTs. Hence, other mechanisms must be involved in the ESTs response, such as inhibition mediated by interaction with final products of other enzyme reactions occurring at the same time or energy cost of enzyme production. Evidence of genetic variation for allelochemical detoxification in insects is scarce. Even so, Berenbaum & Zangerl (1992) reported significant heritability of furanocoumarin metabolism in the Parsnip webworm moth, Despressaria pastinacella (Duponchel) (Lepidoptera: Oecophoridae). Our results indicated rather that detoxification enzymes in the grain aphid exhibit nonsignificant variation among multilocus genotypes. Perhaps, a higher number of aphid genotypes than used in the current study would increase the statistical power of detecting significant genetic variation in S. avenae. Nevertheless, Chilean populations of this species are characterized by a very low genetic diversity (ca. 4%) compared to European source populations (Figueroa et al., 2005). Hence, the probability to collecting a higher number of genotypes in a more intense field sampling is unlikely. In other words, the reduced genetic variation that we found in detoxification mechanisms would be a feature of the studied population. Costs of detoxification defences Our results show that induction of P450s and GSTs activity did not increase simultaneously with SMR,

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supporting the view that metabolic costs of detoxification defences decrease in wheat hosts with high levels of chemical defences. At the same time, rm correlated with Hx levels, indicating that aphids have a better reproductive performance on highly defended host plants. Even so, such host plant chemistry had no effects on other traits like development time and body size at maturity, which means that Hx detoxification is related to costs on reproductive performance but not on development time or body size at maturity. We did not find detectable costs for induced responses of P450s and GSTs activities, whereas ESTs activity was associated with an increase in SMR and fitness costs towards low-Hx wheat hosts. Most probably, costs of ESTs production explain the metabolic costs and decreased reproduction on low defended hosts. Nevertheless, using our current approach, we cannot explain why increased ESTs activity (and not P450s and GSTs activities) is related to metabolic costs, and further studies are clearly required to investigate the dual relationship between enzyme activities and metabolism. Costs of detoxification enzymes have been found for several insect species (Cresswell et al., 1992; Agrawal et al., 2002), although an absence of evidence for costs has also been reported (Neal, 1987; Appel & Martin, 1992). In fact, in two previous studies performed on S. avenae, we found that the increased activity of detoxification enzymes was not accompanied by an increase in metabolic rate. Whereas the first study was performed in a multiclonal colony reared on Hx-containing wheats, in which we reported low correlations between detoxification enzyme activities and SMR (Castan˜eda et al., 2009), In the second study, we found that ‘superclones’ (i.e. the most common and time-persistent genotypes in aphid populations reproducing primarily by obligate parthenogenesis) do not need to modify their detoxifying capacity because the cost is similar across defended wheat plants (Castan˜eda et al., 2010a). Paradoxically, this study suggests that detoxification systems incur fitness and metabolic costs, but not when aphids are feeding highly defended hosts, which was our main expectation. Rather, we found that those costs were highest when aphids were feeding on poorly defended plants. Metabolic and fitness trade-off Trade-offs are expected to constrain the simultaneous maximization of negatively correlated traits (Roff, 1992). Apparently, this is the case for the relationship between metabolic and fitness costs of detoxification enzymes. We found that as levels of chemical defences on host plants rise, aphids tend to reduce metabolic costs and to maximize reproductive performance. Nevertheless, the fact that they perform better on defended plants is an interesting and unexpected result. An explanation is that the appropriate resolution to detect such costs was not yet achieved. Yet, we were able to detect metabolic and

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fitness costs on poorly defended host wheats in this as in previous studies (Castan˜eda et al., 2009; 2010a). A second explanation is that the highest defended hosts were not used (and hence, the insects did not develop the highest possible counter-defensive responses), although the wheat variety here used has the highest known Hx level (cv. Quele´n) in Chilean agro-ecosystems. In fact, several lines of evidence suggest that aphids rarely use – or are exposed to – wheat plants with higher Hx levels than those present in the cv. Quele´n (Figueroa et al., 2002; 2004; 2005). That the low-Hx treatment included some unknown effects that increased costs and reduced fitness, compared with the high-Hx host may also be posited. Yet, it is well established that wheat plants only produce Hx as secondary metabolites with antiherbivory effects (Osbourn et al., 2003; Niemeyer, 2009). Lastly, the use of artificial diets is an alternative to avoid such unmeasured effects. But this procedure has other disadvantages such as high aphid mortality and lack of continuous reproduction, which severely constraint long-term experimental settings as here studied (Caillaud & Rahbe, 1999). Our results are best explained by the fact that the genotypes tested were ‘adapted’ to highly defended wheats, increasing fitness and reducing metabolic costs on this class of host plants. The invasion processes of S. avenae in Chile supports this explanation. The species was introduced during the middle 1970s (Apablaza, 1974) and probably involved just a few individuals from Europe, the most likely source (Figueroa et al., 2005). During the initial colonization, aphids were under strong selective pressures, especially mediated by Hx in host plants (Figueroa et al., 2005). This view is supported by the fact that at the time of introduction, the preferred wheat cultivars cultivated in Chile were those exhibiting higher Hx levels in comparison with European cultivars (Copaja et al., 1991; Nicol et al., 1992; Figueroa et al., 2004). It is likely that Hx-tolerant aphids have been directly selected and have evolved thus in an environment of highly defended hosts. Evidence of genetic variation suggests detoxification enzymes could facilitate insect adaptations to changes in host plant chemistry (Berenbaum & Zangerl, 1992). Direct support of the selective process mediated by wheat chemistry needs to be tested comparing European (ancestral) and Chilean (descendant) populations. Such an analysis would give insights into the evolutionary changes in detoxification systems, energy metabolism and reproductive performance that have seemingly occurred during the introduction and colonization phase of this aphid in Chile. Such an approach was successfully performed by Lee et al. (2003), who detected evolutionary shifts in salinity tolerance from a saline ancestral to freshwater descendant populations of the invasive copepod, Eurytemora affinis (Poppe) (Copepoda: Calanoida). In conclusion, we have shown that energy costs in S. avenae involve induced responses of detoxification

systems and reduction of these costs favours a higher reproductive performance of the insects on chemically stressful environments. We hope that these findings may help to understand how induced defences evolve and what the roles of physiological mechanisms are which govern invasive processes. Furthermore, several questions remain open inviting to future research about the genetic variation and trade-offs associated with detoxification enzyme systems, or the physiological and ⁄ or reproductive differences between original and new populations caused by selection events during biological invasions.

Acknowledgments This study was funded by CONICYT doctoral grant AT-2406132 to L.E. Castan˜eda and by CONICYT-PBCT Anillos ACT-38 grant to C. C. Figueroa and R. F. Nespolo. L. E. Castan˜eda was supported by FONDECYT grant 3090056. We thank Marcela Filu´n for the aphid maintenance and reproductive measurements, Pablo Corte´s for his help with the metabolic measurements, Sebastian Fuentes for his work on aphid genotyping, and Hermann Niemeyer for determining Hx levels in experimental wheat hosts. We also thank Leonardo Bacigalupe, Hugh Loxdale and one anonymous reviewer for their valuable comments on the manuscript.

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