Evol Biol (2010) 37:49–57 DOI 10.1007/s11692-009-9078-3
RESEARCH ARTICLE
Starvation Reveals Maintenance Cost of Humoral Immunity Terhi M. Valtonen • Anni Kleino • Mika Ra¨met Markus J. Rantala
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Received: 30 September 2009 / Accepted: 9 December 2009 / Published online: 23 December 2009 Ó Springer Science+Business Media, LLC 2009
Abstract Susceptibility to pathogens and genetic variation in disease resistance is assumed to persist in nature because of the high costs of immunity. Within immunity there are different kinds of costs. Costs of immunological deployment, the costs of mounting an immune response, are measured as a change in fitness following immunological challenge. Maintenance costs of immunity are associated with investments of resources into the infrastructure of an immune system and keeping the system at a given level of readiness in the absence of infection. To demonstrate the costs of immunological maintenance in the absence of infection is considered more difficult. In the present study we examined the maintenance costs of the immune system in lines of Drosophila melanogaster that differed in their antibacterial innate immune response under starved and non-starved conditions. Immunodeficient mutant flies that have to invest less in the immunological maintenance were found to live longer under starvation than wild type flies, whereas the opposite was found when food was provided ad libitum. Our study provides evidence for the physiological cost of immunological maintenance and highlights the importance of environmental variation in the study of evolutionary trade-offs.
T. M. Valtonen (&) M. J. Rantala Department of Biology, Section of Ecology, University of Turku, 20014 Turku, Finland e-mail:
[email protected] A. Kleino M. Ra¨met Institute of Medical Technology, University of Tampere, Tampere, Finland M. Ra¨met Department of Paediatrics, Tampere University Hospital, Tampere, Finland
Keywords Environmental variation Fitness Innate immunity Starvation resistance Trade-offs
Introduction Susceptibility to pathogens and genetic variation in disease resistance is assumed to persist in nature because of the high costs associated with immunity (Sheldon and Verhulst 1996; Schmid-Hempel 2003). Maintenance costs of immunity are related to investments of resources into the infrastructure of an immune system and keeping the system at a given level of readiness in the absence of infection (Schmid-Hempel 2003; Siva-Jothy et al. 2005). Deployment costs of immunity arise from a response to an immunological challenge and are measured as a change in fitness following immunological induction (SchmidHempel 2003; Siva-Jothy et al. 2005). For example, Moret and Schmid-Hempel (2000) showed a survival cost for the activation of the immune system under starvation in bumblebees and Zerofsky et al. (2005) showed a reproductive cost incurred by the activation of antimicrobial synthesis in female fruit flies. To demonstrate the costs of immunological maintenance in the absence of infection is considered more difficult (Lochmiller and Deerenberg 2000). Ra˚berg et al. (2002) investigated the question by comparing the basal metabolic rates of normal and lymphocyte deficient knockout mice (mice without adaptive, but with innate immunity) and found deficient mice having higher metabolic rates than normal mice, which indicates that an optimal combination of innate and adaptive immunity may save energy. Because invertebrates lack the adaptive defense system, the constraints set by maintenance costs are assumed to be different in invertebrates (Schmid-Hempel 2003).
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In invertebrates evolutionary costs of immunological maintenance have been studied especially in the fruit fly Drosophila melanogaster. For example, artificial selection for improved resistance against parasitoid wasps, Asobara tabida and Leptopilina boulardi, was shown to correlate with reduced larval competitive ability in unparasitized D. melanogaster (Kraaijeveld and Godfray 1997; Fellowes et al. 1998). Ye et al. (2009) selected flies for improved defense against the bacterium Pseudomonas aeruginosa and showed the evolved capacity for defense to be costly as evidenced by reduced longevity, larval viability and a rapid loss of the trait in the absence of selection. In another study on D. melanogaster by Hoang (2001) survivors of A. tabida parasitism were shown to have reduced desiccation and starvation resistance compared to their unparasitized relatives. In this study it is, however, not possible to distinguish between immunological costs and costs associated with parasitism. McKean et al. (2008) looked at the genetic correlations between fecundity in the absence of infection and resistance to bacterial infection under both food-limited and food-unlimited environments in female D. melanogaster. A negative genetic correlation between fecundity and resistance was only found in the food-limited environment. The significant genotype-by-environment interaction for the maintenance costs in this study emphasized the importance of examining cost and genetic correlations between different fitness traits in both stressed and nonstressed environments. Environmental variation is believed to affect the magnitude and sign of phenotypic correlations (Roff 2002). Environment can also affect the way in which genes are expressed so that genes that influence a trait in one environment may not be important in a different one (Sgro` and Hoffmann 2004). Hence the sign of a phenotypic correlation changing can also reflect changes in genetic correlations (Via and Lande 1985). Earlier studies have shown that phenotypic plasticity is likely to be a very important feature of immune response (Siva-Jothy et al. 2005). Insects rely solely on innate immune reactions for protection against infection. Innate immunity is divided into cellular and humoral immune defense—the latter being characterized by the production of antimicrobial peptides (AMPs) (Leclerc and Reichhart 2004; Royet et al. 2005). The AMP response is critical for protection against microbial pathogens. In Drosophila two signaling pathways, Toll and Imd, regulate the production of these peptides (Lemaitre et al. 1995). Both signaling cascades lead to nuclear localization of an NF-jB family transcription factor Dif/Dorsal or Relish, respectively, consequently leading to the expression of AMP genes (Leclerc and Reichhart 2004; Royet et al. 2005). The Imd pathway branches into two distinct sub pathways of which one leads to transcription of AMP genes via Relish while the other, JNK
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signaling, is not required for AMP gene expression, but rather has a role in cellular immune responses and in the stress response (Park et al. 2004; Royet et al. 2005). Relish protein has recently been shown to play a crucial role in limiting the duration of JNK activity (Park et al. 2004). Immune response to Gram-negative bacteria is primarily mediated via the Imd pathway, whereas the Toll pathway reacts to fungi and Gram-positive bacteria (Leclerc and Reichhart 2004; Royet et al. 2005). Relish mutant flies do not produce AMPs in response to Gram-negative bacteria, which makes them more sensitive to bacterial infections than wild type flies (wt). Resistance against fungi is also lowered in the mutant flies whereas cellular immune reactions are unaffected (Hedengren et al. 1999). In spite of the profound effects on the immune response, homozygous Relish mutants are fertile and give rise to normal offspring (see Hedengren et al. 1999 for complete description of the Relish E20-mutant). Resource availability can play an important role in determining the strength and direction of trade-offs between immunity and other life history components in insects (McKean et al. 2008). Costs of immunity may often be detected first when conditions deteriorate, because organisms can compensate extra demands by increasing the intake of resources (Moret and Schmid-Hempel 2000; Hoang 2001; Schmid-Hempel 2003; McKean et al. 2008). In the present study we examined the costs of immunological maintenance using lines of D. melanogaster that differed in the functioning of the humoral Imd signaling pathway due to differences in the functional transcription factor Relish. The aim of the present study was to look whether there are costs associated with maintaining a normally functioning immune system in the absence of infection and whether or not these costs are different under two different food regimes. For this, we measured the longevity of D. melanogaster wt and Relish mutant flies under starved and non-starved conditions. We found the mutant flies outliving the wt flies under starving conditions, whereas the opposite was found when food was provided ad libitum. It seems that the longer starvation tolerance of the mutant flies can at least in part be explained by reduced investment in immunological maintenance.
Materials and Methods Flies To create lines of flies that differed in their humoral immunity due to differences in the expression of the Relish gene, we crossed immunocompromised Relish E20 Drosophila mutant flies with wt Oregon R flies. The outcrossing was necessary because Relish mutants may
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Fig. 1 Schematic illustration of the crossing scheme used to create the experimental lines (one of the 12 ancestral pairs is given as an example). Wild type line with normal immunity (white colored text) was chosen a closely related pair with impaired immunity (bold text). Both lines descended from the same ancestral breeding pair (ancestral pair 1). See text for more details
differ not only in the function of their humoral immunity but also in other life history traits compared to normal flies and thus, normal flies from these outcrosses provide a better control group for our experiment. The use of flies with a common background would have been ideal for this purpose. Unfortunately, they are not available and hence, the background of the flies created for the present experiment is not tightly controlled (see ‘‘Discussion’’ section for more details). We established the lines by placing 12 pairs consisting of a wt Oregon R and a Relish E20 mutant flies of opposite sexes in separate 30 ml yeast supplemented vials (these 12 pairs are later referred to as ancestral pairs). To produce flies that were homozygous for the Relish locus (either the Oregon R wt allele or the Relish E20 deletion mutation) we disposed the parental pair before the next generation flies emerged and maintained the lines as inbred lines by full sib mating. In the first generation we tripled the amount of lines by setting up three brother–sister pairs per line and in the following two generations we doubled the amount lines each generation in the same manner (see Fig. 1). After the fifteenth generation we allowed four sisters and three of their brothers to continue a line to reduce the probability of an accidental loss of a line. The immune deficit of Relish E20 mutants is revealed after exposure to high amounts of pathogenic microbes or after bacteria has been injected directly into the hemocoel (Hedengren et al. 1999; Matova and Anderson 2006). After the first few generations of brother–sister mating, we tested 5–10 adult flies from each line for their resistance to infection by the bacterium Enterobacter cloacae. According to Hedengren et al. (1999) Relish mutants die within 17 h when infected with approximately 2 9 105 of E. cloacae bacteria, whereas wt flies generally survive this treatment. We pierced the thoraces of individual flies at 7 days after eclosion with a 0.1 mm pin that we had dipped in a suspension of an overnight culture of the bacteria on LB-agar plates. Control flies were only pricked with a pin. We used CO2 to anesthetize the flies. After infection we
placed the flies on fresh food. We regarded flies that were alive 24 h after the infection as representing lines with normal immunity; the ones dead as representing lines with impaired immunity. For the experiment we chose eight pairs of lines. Each pair consisted of a mutant and a wt line that descended from the same ancestral breeding pair—one of the 12 pairs that we established the lines with. For certainty, we conducted the infection assay again at the end of the experiment with flies from lines that we had chosen for the experiment. This time ten males and ten females from each line were tested. Because one of the immunocompromised lines survived the treatment we decided to exclude it from the experiment. Hence, the final analyses included descendant lines of five ancestral pairs, eight lines with normal immunity and seven lines with impaired immunity (one wt and one mutant line from ancestor 1, three wt and three mutant lines from ancestor 2, two wt and one mutant lines from ancestor 3, one wt and one mutant line from ancestor 4 and one wt and one mutant line from ancestor 5; see Fig. 1).
Fly Rearing and Maintenance We reared the flies on agar/cornmeal/yeast/syrup diet at 22°C in a 12L:12D light regime throughout the study. In the experiment we used two larval growth densities. Half of the study was conducted on progeny of a pair of flies that was allowed to reproduce for 24 h in a 30 ml container with ad libitum access to dietary yeast for the adult flies and 10 ml of artificial diet for the larvae. The other half of the study was conducted with flies that were reared in identical containers but at a density of 30 eggs. The eggs were collected from a pair of flies that was allowed to interact for 24 h. In both cases we collected the experimental flies as virgins upon eclosion and kept them in fresh food vials for 2 days until used in the assay.
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Survival Analysis: Analyzing the Cost of Immunological Maintenance To detect differences in the allocation of resources into immunological maintenance in the absence of infection we followed the survival of 2-day old virgin wt and Relish mutant flies under starved and non-starved conditions. We determined survival as the time from the placement of a fly in a 30 ml assay vial to its death. In starved conditions we provided each fly with a vial containing no food but an access to water by placing a 1 cm thick moist cotton ball in the vial. The non-starved vials contained 10 ml of standard media and dry yeast for food. We capped the vials with cotton plugs so that the flies had enough space to move freely. For each line we set 17–25 no-food and 9–17 ad libitum food vials per sex. Altogether we set 729 (Mutant: 157# ? 169$ = 326; WT: 200# ? 203$ = 403) no-food and 324 (Mutant: 74# ? 72$ = 146; WT: 87# ? 91$ = 178) ad libitum food vials. At the beginning we scored the survival of the flies in starving conditions every 6 h, but as soon as the flies started dying we started observing them every 2 h. The survival of the flies in nonstarved conditions was checked once a day and every 2 weeks these flies were moved over to fresh food vials. Thorax length, as an estimate of body size, was measured after the experiment under a light microscope using an ocular micrometer. Statistics To seek for significant differences between the survival of flies that were of the same sex and Relish genotype (Oregon R wt or Relish E20 deletion mutation) but that had grown at different larval densities, and to find out whether or not we could pool these groups together, we used the Kruskal–Wallis test and, for the multiple comparisons, the Mann–Whitney test. These analyses revealed that one pair, Relish mutant females on the non-starved treatment, differed statistically significantly from each other (data not shown). We conducted all further analyses on data that was pooled over different larval growth densities. The fact that one of the groups did not meet the criteria was taken into account in the interpretation of the results (see ‘‘Survival Under Non-Starved Conditions’’ section). We used Cox regression survival analysis (Cox proportional hazards regression) to examine survival differences among Relish mutant and wt flies. In the models, we presented food treatment, Relish genotype (wt versus Relish mutant), genotype (ancestral pair that the line was established with) and sex as categorical covariates, size as a continuous covariate and survival time as the dependent variable. We initiated model fitting with a model that included all main effects and the two- and three-way
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interaction terms that best addresses the subject of interest (see ‘‘Results’’). The best model was searched using backward stepwise method (Backward LR). All statistical analyses were conducted using SPSS 16.0 for Windows.
Results Environment-Dependent Survival In order to analyze the effect of environment on survival we initiated model fitting with a model that included all main effects, all two-way interactions with environment and a three-way interaction Relish genotype 9 sex 9 environment. The final model contained environment (OR = 0.0004, Wald = 65.613, df = 1, P \ 0.001), size (OR = 1.076, Wald = 48.724, df = 1, P \ 0.001), Relish genotype (OR = 1.481, Wald = 23.538, df = 1, P \ 0.001), genotype (Wald = 155.184, df = 4, P \ 0.001), genotype 9 environment (Wald = 74.948, df = 4, P \ 0.001), and Relish genotype 9 environment (OR = 0.416, Wald = 38.601, df = 1, P \ 0.001) as the best predictors of survival. The starving environment was clearly the more stressful food treatment of the two environments. Significant interaction between genotype and environment indicated that genotype-specific survival was different under starved and non-starved environments. The most interesting result, in the context of our study, was the significant Relish genotype by environment interaction that indicated that the survival of immunocompromised Relish mutants and wt flies differed by environment. According to the results, increase in size was associated with reduced survival. In addition, males and females seemed to respond similarly to the treatments as sex was not included in the final model. Survival Under Starved and Non-Starved Environments To further analyze the Relish genotype by environment interaction found in the Cox survival analysis conducted for the pooled data we applied the analysis again separately for each sex and for both environments. We initiated model fitting with a model that included size, Relish genotype, genotype and the two-way interaction Relish genotype 9 size as covariates. Survival Under Starved Conditions The best model predicting survival of females in starving conditions contained size (OR = 0.752, Wald = 33.763, df = 1, P \ 0.001), Relish genotype (OR = 0.000001, Wald = 34.241, df = 1, P \ 0.001), genotype (Wald = 83.383, df = 4, P \ 0.001) and the interaction term Relish
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Fig. 2 Cumulative survival of immunodeficient Relish mutant and wt flies under a starved and b non-starved environment. Curves represent the survival functions calculated by the Cox regression survival analysis. Relish mutant flies are shorterlived when food is provided ad libitum, but longer-lived under starvation compared to wt flies. See text for statistical analyses
genotype 9 size (OR = 1.449, Wald = 35.398, df = 1, P \ 0.001). For males Relish genotype (OR = 0.002, Wald = 20.732, df = 1, P \ 0.001), genotype (Wald = 80.398, df = 4, P \ 0.001) and the interaction term Relish genotype 9 size (OR = 1.291, Wald = 23.910, df = 1, P \ 0.001) were included in the final model. Relish mutants, males and females, survived longer under starving conditions than wt flies (Fig. 2a). However, the effect of Relish genotype on survival depended on size. For females the interaction was due to the fact that whereas among Relish mutants increase in size was associated with longer survival, the opposite was true among wt females. Among males larger size was associated with decreased lifespan, but the effect was more pronounced among wt flies than Relish mutant flies. The fact that all flies in the non-starved treatment survived the experimental period of the starved flies indicates that the starvation data is not biased by deaths of flies by other mortality factors.
survival of flies grown at different densities and it is not shown in the figure. The reason why a difference in survival between the two groups was found only among Relish mutant females on the non-starved treatment is not clear to us. In the Cox regression survival analysis the interaction term Relish genotype 9 size (OR = 0.987, Wald = 9.793, df = 1, P = 0.002) was the only term included in the final model for females in the starved environment, whereas for males the final model included Relish genotype (OR = 0.791, Wald = 2.096, df = 1, P = 0.148) as the only predictor of survival. According to the results female wt flies were longer-lived than mutant females when food was provided ad libitum. For males of different Relish genotype the difference in survival was not statistically significant (Fig. 2b). For females the effect of Relish genotype on survival was size dependent, mainly due to decreased survival in larger size Relish mutant females grown at a density of 30 eggs.
Survival Under Non-Starved Conditions There was a statistically significant difference in the survival of Relish mutant females grown at different larval densities—flies grown in vials of 30 eggs were outlived by flies grown in vials in which a female was allowed to lay eggs for 24 h (Fig. 2b). Since this was the only pair among which a significant difference in the survival between the two growth density groups was found, we analyzed the groups pooled together, and the results of the Cox regression survival analysis thus describe the pooled data. Figure 2b depicts the survival functions calculated by the Cox regression survival analysis, the survival curves for both growth density groups are shown for the Relish females. The results reported in the text, however, describe the survival of pooled wt and pooled Relish mutant lines. For the Relish mutant females the survival curve for the pooled data runs between the curves representing the
Discussion In the present study we examined the maintenance costs of a normally functioning immune system in the absence of infection under two food regimes. Using flies that differed in their antibacterial innate immune response we showed that under starving environment the survival of the immunodeficient flies was greater than that of the wt flies, whereas the opposite was found when food was provided ad libitum. Starvation resistance has been shown to be a complex trait affected by a number of genes (e.g. Harbison et al. 2004). Hence it is not surprising that genetic background was one of the predictors of survival in the final Cox regression models for both males and females in the starving environment. Because of the inbreeding procedure
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used to create the experimental flies, both wt and Relish mutant lines have reduced genetic variation, but are likely to have different alleles fixed at various loci. To minimize the differences in genetic variation between the groups of immunocompromised and wt flies, we picked the experimental lines among those ancestral pairs that had both immunocompromised and wt lines among them. Considering the present experimental setting we consider having done the best we could to make the variation similar in the groups that we are comparing—immunocompromised versus wt flies. However, in order to be more certain that the effect that we see is due to Relish and not some gene(s) segregating in the background we included descendent lines of five ancestral pairs to both groups. Unquestionably, the best way to control for the background would have been to backcross the mutant strain to a common background. According to Hedengren et al. (1999) the creation of Relish E20 strain involved recombining a number of different strains. In the process only those flies with particular characteristics were selected and further bred. Hence, to recreate the desired common background for the mutant strain 10 years after the creation of the strain is practically impossible. Definitively showing that the observed difference in starvation resistance between the immunodeficient and wt flies arises from differential investment in immunological maintenance is not easy, because of the difficulty in excluding alternative explanations like pleiotropy and linkage disequilibrium. These issues are a common problem with studies that make use of selection lines, thus, making our study no exception (see e.g. Fellowes et al. 1998; Kraaijeveld et al. 2001; Luong and Polak 2007). If there is a linkage between Relish and genes that influence survival and if the genes at the linked loci differ between the original Relish E20 and Oregon R strains, any detected difference between wt and mutant lines may incorrectly be ascribed to immunity. Costs due to genetic pleiotropy arise if Relish influences other fitness traits besides immune defense. Linkage disequilibrium is more likely than pleiotropy to be a factor here, because according to our understanding, the knowledge of the role of Relish in the fly physiology is that it is not involved in other nonimmunological processes and it thus provides an effective tool for the study of life-history trade-offs. Considering the present experimental setting, we did our best to reduce the probability that either one of the groups would have been genetically better suited for surviving famine conditions. However, due to the problems related to linkage disequilibrium we have to conclude that the results presented here are merely suggestive rather than conclusive. In order to more convincingly demonstrate the maintenance cost of immunity, mutations in multiple genes that disrupt the immune system in various ways would be desirable.
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Unfortunately, because of the integrated and organizational characteristics of the immune system with other physiological systems most mutants may not be suitable for this kind of experiments (Lochmiller and Deerenberg 2000). The entire Relish transcription unit is situated inside an intron of the Nmdmc gene, which encodes a bifunctional enzyme that is involved in tetrahydrofolate metabolism (Price and Laughon 1993; Hedengren et al. 1999). The Nmdmc gene has two alternative splice forms, of which both span over the Relish region. Relish E20-mutants show normal expression of Nmdmc transcript A, whereas the transcript B is absent in the mutant flies. Under standard laboratory conditions even the complete loss of Nmdmc expression has not been observed seriously affecting the viability of the flies and it is assumed that the products of this enzyme can be obtained in sufficient quantities from the food or from a homolog of this enzyme (Hedengren et al. 1999). The Relish gene unit is known to have four transcripts, of which the maternal 2.7 kb transcript is expressed in females and in early embryos, the 3.1 kb transcript is strongly induced in infected flies, and the 3.5 kb transcript is constitutively present, whereas the 3.5 kb is found occasionally in low abundances (Dushay et al. 1996; Hedengren et al. 1999). The lack of Relish developmental effects is somewhat surprising, considering that one of the Relish transcripts is expressed in early embryos, probably as a maternally contributed transcript (Hedengren et al. 1999). This conclusion is supported by the observation that Relish is expressed in nurse cells in the ovary (Hedengren et al. 1999). The function of Relish in embryogenesis, if any, is considered redundant or that it is involved in a more subtle process that is not required for survival (Hedengren et al. 1999). It is generally recognized that immunity is costly, but less is known about how these costs are distributed among different compartments of the immune system. It seems likely that Relish mutants have to invest less in immunity than wt flies, but that the amount of resources invested in the products encoded by the Relish gene unit are likely to vary in time. The costs of maintaining the different compartments of the immune system could be put into perspective if we knew more about their contribution to body mass and about their re-newel dynamics. This would enable more reliable predictions of the costs associated with immunological maintenance. It is appreciated that the insect host defense system shares many of the basic characteristics of the mammalian acute phase response (Hoffmann 1995). Simple model organisms can be used to elucidate the genetic architecture of complex traits and thereby enhance our understanding of these traits in general. Drosophila mutants provide an effective tool for the study of the immune system especially in areas where more traditional methods are inappropriate.
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In the present study smaller size (measured as thorax length) was in most cases associated with longer survival. Only among starved Relish mutant females larger size was associated with longer life span. We compared the average sizes of mutant and wt flies and found the mutant flies somewhat smaller than the wt flies (data not shown). Selection experiments for increased starvation resistance have shown that an increase in the lipid and glycogen content of adult D. melanogaster underlies the increased resistance to starvation (Hoffmann and Harshman 1999), and it has been suggested that smaller flies could be at a disadvantage when starved because they store less energetic reserves than larger flies (Hoang 2001). Studies on wild populations of several strain of Drosophila have not always been consistent with this suggestion (e.g. Parkash and Munjal 1999; Hoffmann et al. 2001) nor has selection for increased starvation resistance always led to increased accumulation of energetic reserves (Hoffmann and Parsons 1993). Reduced metabolic rate has been hypothesized as a general explanation for stress resistance (Hoffmann and Parsons 1989) and larger size could thus be of advantage, because, in general, bigger individuals have slower rates of metabolism than their smaller conspecifics (Speakman 2005). The difference in energy metabolism has also been used to explain why larger individuals in general live longer (Speakman 2005). Again, however, there are several studies conducted on different strains of Drosophila that found no relationship between energy expenditure and lifespan (see Speakman 2005 and the references therein). Moreover, Hoffmann and Parsons (1989) demonstrated a decrease in metabolic rate independent of body size in lines of D. melanogaster selected for desiccasion resistance. In general, starvation and desiccasion resistance are considered to correlate with each other (Hoffmann and Harshman 1999). In the present study system, smaller size was found, in most cases, to correlate with longer survival together with Relish genotype. Hence it seems that the longer survival of the mutant flies compared to wt flies under starving conditions could at least in part be explained by reduced investments in immunological maintenance. Under starved conditions flies were much shorter-lived than under non-starved conditions. The possibility for an individual to get infected with a pathogen in a non-sterile laboratory environment in which the flies were kept is likely to increase with increasing lifespan, and it could explain why under the non-starved environment wt flies were longer-lived than mutant flies with impaired immunity. Environmental variation is believed to affect the sign of phenotypic correlations (Roff 2002). A study by McKean et al. (2008) demonstrates the cost of immunological maintenance as evidenced by a negative genetic correlation between female D. melanogaster fecundity and resistance to bacterial infection in a food-limited
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environment. The absence of such a correlation in the nonstarved environment made the authors conclude that costs of maintaining immunity are easy to overlook in an environment in which resources are not limiting and moreover, requires that different genotypes would have to respond differently to the unlimited food environment. Fellowes et al. (1998) found improved resistance against parasitoid wasp to correlate with reduced larval competitive ability in D. melanogaster, whereas no other correlated responses, e.g. to adult starvation tolerance, were found. Also Luong and Polak (2007) demonstrated a negative genetic correlation between ectoparasite avoidance (behavioral defense) and reproduction in D. nigrospiracula being more prevalent under thermal stress. In the study by Luong and Polak (2007) no correlated response for longevity was detected. Different forms of defense are thus likely to bear different costs, be context dependent and involve damage to different fitness-related traits. The cellular immune response has recently been suggested to be the more effective arm of the innate immunity in clearing bacterial infections than the humoral arm. In the mealwormbeetle, Tenebrio molitor, it was showed that cellular responses were responsible for the elimination of most of the infecting bacteria, whereas the induced antimicrobial compounds functioned only secondarily to eliminate those bacteria that had survived the constitutive immune response (Haine et al. 2008). It thus seems reasonable to assume that the two arms of the innate immune system bear different costs. Selection lines for improved resistance have been used widely in studies investigating costs of immunological defense (e.g. Kraaijeveld and Godfray 1997; Fellowes et al. 1998; Luong and Polak 2007; Ye et al. 2009). However, it appears that in most cases it is not possible to differentiate the costs of antibacterial defense from those of cellular defense. For example, in the study by Ye et al. (2009) investment in both aspects of immunity was shown to underline the improved defense against the bacteria P. aeruginosa. In the study by McKean et al. (2008) it is also not possible to differentiate between the costs of cellular and humoral immunity. Using genetically modified D. melanogaster Libert et al. (2006) demonstrated by overexpressing the putative pathogen receptor molecule PGRP-LE that chronic activation of innate immunity pathways reduces lifespan in D. melanogaster. The reduced longevity was shown to be due to continued activation of the NF-jB factor Relish suggesting the presence of a physiological cost for enhanced immunity and a trade-off between resistance and longevity mediated by chronic NF-jB signaling. Relish is a key factor in the induction of an entire set of antibacterial as well as antifungal peptides with no known effects on cellular immune reactions (Hedengren et al. 1999). Our work is the first attempt to demonstrate the
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costs associated with the maintenance of the antimicrobial defense system in the absence of infection. Acknowledgements This study was funded by the Academy of Finland to M.J.R., the Finnish Cultural Foundation’s Varsinais-Suomi Regional Fund to T.M.V., Competitive Research Funding of the Pirkanmaa Hospital District to A.K. and by grants from the Academy of Finland, the Foundation for Pediatric Research, Sigrid Juselius Foundation, Emil Aaltonen Foundation and Competitive Research Funding of the Pirkanmaa Hospital District to M.R.
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