Evolutionary trade-offs occur if selection on one trait reduces the value of another (Stearns 1992). Such a cost of adaptation can lead to negative genetic correlations between fitness components, thereby maintaining genetic diversity and preventing the evolution of omnipotent generalists (Kassen 2002). This universal principle of adaptation costs may also play an important role in coevolutionary interactions between hosts and parasites. Parasites are generally expected to select for higher resistance in the host. However, an increase in resistance can be accompanied by a reduction in fitness-relevant life-history traits, such as competitive ability, fecundity, seed production, etc. Costs of resistance are then defined (and measured) as a reduction of fitness in the absence of parasites (Simms and Rausher 1987; Kraaijeveld et al. 2002; Strauss et al. 2002). Associated costs are predicted to select for optimal levels of resistance balanced against other important fitness related life-history traits. Theoretical models show that trade-offs between resistance and other fitness components can help maintain resistance polymorphism within populations (e.g., Gillespie 1975; Parker 1992; Antonovics and Thrall 1994; Bowers et al. 1994; Agrawal and Lively 2002), but also promote genetic divergence between populations that vary in their exposure to parasite-mediated selection (Elmqvist et al. 1993; Hasu et al. 2009) or that live in environments where costs of resistance are expressed differently (Jessup and Bohannan 2008).
Generally, costs of resistance are thought to arise from a conflict between allocation of limited resources to the defense machinery and to other fitness-relevant functions (Simms and Rausher 1987; Coustau et al. 2000; Labbé et al. 2010). In various plant, invertebrate, or microbial systems, costs of resistance have been demonstrated among naturally occurring genotypes (Biere and Antonovics 1996; Strauss et al. 2002; Tian et al. 2003; Carton et al. 2005; Gwynn et al. 2005; Jessup and Bohannan 2008); over the past few years, an increasing number of studies has also addressed this issue in laboratory selection experiments (Table 1). It is commonly assumed that these trade-offs result from antagonistic pleiotropy of genes conferring resistance, but impairing other fitness functions (Lenski 1988; Tian et al. 2003). The underlying functional basis may vary from system to system. Overproduction of defense structures or molecules may have energetic costs, interfere with other biochemical pathways, or even be immunopathogenic (Coustau et al. 2000; Kraaijeveld et al. 2001; Brown 2003).
|(A) Studies testing effects of parasite-mediated selection|
|Reference||Host||Type of experiment1||Selection for resistanceagainst||Cost (bold type = significant fitnesscost identified)||Environment costs tested||Additional observations||Subsequent relaxed selection2|
|(Hurd et al. 2005)||Anopheles gambiae||Artificial selection||Plasmodium yoelii nigeriensis||Hatch rate (–18%); Longevity, mating success, size, bloodmeal size, egg production||Temperature stress, starvation, flight activity||Parallel selection for susceptibility|
|(Fuxa and Richter 1998)||Anticarsia gemmatalis||Artificial selection||Nucleopolyhedro-virus||Fertility (–39% viable offspring), pupal weight (–10%), neonate survival (–7%); Longevity||Standard laboratory conditions||Resistant insects lived longer||Repeated (3x) loss of resistance within 3 generations|
|(Kraaijeveld and Godfray 1997)||Drosophila melanogaster||Artificial selection||Endoparasitoid Asobara tabida||Competitive ability (–50%, low food); Larval and pupal survival/development, adult longevity/size, early fecundity, fluctuating asymmetry||Different food levels|
|(Fellowes et al. 1998)||Drosophila melanogaster||Artificial selection||Endoparasitoid Leptopilina boulardi||Competitive ability (–45%, low food); Fecundity, egg viability, starvation tolerance, size and development rate||Different food levels|
|(Kolss et al. 2006)||Drosophila melanogaster||Experimental evolution||Endoparasitoid Asobara tabida||Learning ability to avert shock||Standard laboratory conditions||No loss of resistance after 50 generations|
|(Vijendravarma et al. 2009)||Drosophila melanogaster||Artificial selection||Microsporidian Tubulinosema kingi||Fecundity (–38%), Competitive ability (–78%, low food); Survival||High and low food|
|(Ye et al. 2009)||Drosophila melanogaster||Artificial selection||Bacterium Pseudomonas aeruginosa||Longevity (–11%, females only), Egg viability (–30%); Development time, body mass, attractiveness, offspring produced||Standard laboratory conditions||∼6% faster development time for resistance selected lines||Resistance lost within 5 generations|
|(Luong and Polak 2007)||Drosophila nigrospiracula||Experimental evolution||Ectoparasitic mite Macrocheles subbadius||Fecundity (–30%); Longevity||Low and high temperature||Reduced resistance within 5 generations, maintained further 20 generations (Polak 2003)|
|(Boots and Begon 1993)||Plodia interpunctella||Experimental evolution||Granulosis virus||Development time (24% slower), Egg hatch (–3%); Egg production, pupal weight||Standard laboratory conditions||Resistant moths 5% larger||After 2 generations reduction in fitness 8%|
|(Milks et al. 2002)||Trichoplusia ni||Artificial selection||Nucleopolyhedro-virus||Pupal weight, development time, survival, fecundity||Standard laboratory conditions||Parasite allowed to coevolve;Resistant selected pupae heavier and develop faster||Resistance retained after seven generations of relaxed selection|
|(Webster and Woolhouse 1999)||Biomphalaria glabrata||Artificial selection||Schistosoma mansoni||Fertility (–75% egg production); Longevity||Standard laboratory conditions||Parallel selection for higher susceptibility|
|(Zbinden et al. 2008)||Daphnia magna||Experimental evolution||Microsporidian Octosporea bayeri||Clonal growth rate (–40%); Competitive ability, survival||High and low food, low density||Resistant selected Daphnia superior competitors|
|(Chao et al. 1977)||Escherichia coli||Experimental evolution||Phage T7||Competitive ability (–20%)||Standard laboratory conditions||2 outcomes, with different coexisting mutants|
|(Lenski and Levin 1985)||Escherichia coli||Experimental evolution||Phage T2, T4, T5, T7 (all separately)||Competitive ability (–50% T4)||Standard laboratory conditions||No costs of resistance against T5|
|(Brockhurst et al. 2004)||Pseudomonas fluorescens||Experimental evolution||Phage SBW25Φ2||Competitive ability (–19%)||Standard laboratory conditions|
|(Buckling et al. 2006)||Pseudomonas fluorescens||Experimental evolution||Phage SBW25Φ2 for lines with high and low mutation loads||Competitive ability (–5%, high mutation load only)||Standard laboratory conditions|
|(Lopez-Pascua and Buckling 2008)||Pseudomonas fluorescens||Experimental evolution||Phage SBW25Φ2||Competitive ability (–5% in rich, –25% in poor environment)||High and low resources|
|(Morgan et al. 2009)||Pseudomonas fluorescens||Experimental evolution||Phage SBW25Φ2||Growth||Standard laboratory conditions|
|(Gallet et al. 2009)||Pseudomonas fluorescens||Experimental evolution||Predatory bacterium Bdellovibrio bacteriovorus||Carrying capacity (–75%, for FM morph at end of experiment);Growth||Standard laboratory conditions|
|(Lohse et al. 2006)||Paramecium caudatum||Experimental evolution||Bacterium Holospora undulata||Clonal growth (–25%)||Standard laboratory conditions|
|(Schulte et al. 2010)||Caenorhabditis elegans||Artificial selection||Bacterium Bacillus thuringiensis||Adult size, Population growth||Standard laboratory conditions|
|(B) Studies specifically testing effects of relaxed parasite-mediated selection|
|Reference||System||Type of experiment||Relaxed selection for resistance against||Cost (bold type = trait for which fitness cost was still identified)||Environment costs tested||Additional observations||Number of generations selection relaxed|
|(Lenski 1988)||Escherichia coli||Experimental evolution||Phage T4||Competitive ability (Compensatory mutation reduced fitness cost from 43% to 22%)||Standard laboratory conditions||No loss of resistance||400 generations|
|(Meyer et al. 2010)||Escherichia coli||Experimental evolution||Phage T6||Competitive ability||Standard laboratory conditions||No loss of resistance; No cost of resistance for ancestral lines; correlated responses to other phages||∼44 500 generations|
The form of the relationship between parasite resistance and other fitness traits is important for the evolution of resistance characteristics in host populations. In particular the shape of the relationship is important regarding whether parasite-mediated selection will maintain resistance polymorphism or not. An increasingly costly, or convex, relationship between parasite resistance and other fitness traits may select for one evolutionary stable, generalist strategy in a host population. Conversely, for a decreasingly costly relationship, coexistence of highly resistant and highly susceptible types is possible (Boots and Haraguchi 1999).
Given the above genetic and functional constraints, we can establish two main predictions about the evolution of costs of resistance. First, parasite-mediated selection for increased resistance should lead to a correlated decrease in fitness in the absence of the parasite. This can be tested by artificial selection or experimental evolution, comparing the direct response to selection for resistance and the correlated response for fitness (Table 1A). These types of experiments can reveal very strong evolutionary trade-offs between resistance and fitness; often, however, these costs are only detectable for certain fitness components and under certain environmental conditions (mostly stressful). In a few cases, resistance benefits were detected for certain traits (Table 1A).
The second prediction holds that costly resistance should be selected against in the absence of parasites. That is, relaxing parasite-mediated selection should re-establish fitness and lead to a correlated decrease in resistance. Only very few studies have properly tested this second prediction. A number of studies that initially set out to test the first prediction tentatively explored the consequence of subsequent relaxed parasite-mediated selection for a relatively limited number of selection lines and generations (Table 1A). Among these studies, one identified an increase in fitness after two to four generations of relaxed parasite-mediated selection in one population (Boots and Begon 1993), and three studies a reduction in resistance (Fuxa and Richter 1998; Luong and Polak 2007; Ye et al. 2009), but they do not report the corresponding changes in resistance or fitness, respectively. Other studies relaxed parasite-mediated selection for cost-free resistance and, not surprisingly, no change in resistance was later observed (Milks et al. 2002; Kolss et al. 2006; Meyer et al. 2010). To our knowledge only one study has explored the effect of long-term relaxed parasite-mediated selection for populations where costs of resistance were identified. In Escherichia coli populations, the cost of resistance against a bacteriophage declined by 50% over 400 generations in the absence of phage, and this without loss of resistance (Lenski 1988). This was explained by the action of compensatory mutations restoring fitness functions, without compromising resistance. Similarly, when retracting the bacterial biopesticide Bacillus thuringiensis, resistant diamondback moth populations showed reversal toward susceptibility and an increase in fitness within several generations, although not necessarily to ancestral levels (Tabashnik et al. 1994). Thus relaxed selection does not necessarily lead to the evolutionary return to the ancestral state, raising the general question of the reversibility of evolutionary trajectories (Teotonio and Rose 2000).
We investigated reverse evolution of costs of resistance in experimental long-term populations of the protozoan Paramecium caudatum and the bacterial parasite Holospora undulata. For these populations, a previous study had indicated parasite-mediated selection and costs of resistance: paramecia from populations coevolving with the parasite had higher levels of resistance, but lower growth rates than paramecia from naive populations, never exposed to the parasite (Lohse et al. 2006). The present study was motivated by the occurrence of a third population type: Over the course of the long-term experiment, some initially infected populations lost infection and became disease-free. We compared resistance and fitness (reproductive rate) of these “recovered” populations with still “infected” populations, and “naive” populations that had never been exposed to the parasite. We predicted selection for increased fitness and a concomitant decrease in resistance in the “recovered” populations, after extinction of the parasite. If selection occurs along a trade-off function, we expected fitness and resistance of the “recovered” populations to be identical to that of naive populations (full reversal) or intermediate between those of still “infected” and naive populations (partial reversal). The position of the recovered populations along this trade-off function would then depend on time required for acquisition of compensatory or back mutations. Our experimental design also allowed us to investigate the shape of the trade-off function, between resistance and fitness in the absence of the parasite, using multiple genotypes and populations.