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Autonomy and integration in complex parasite life cycles

Published online by Cambridge University Press:  29 September 2016

DANIEL P. BENESH*
Affiliation:
Marine Science Institute, University of California, Santa Barbara, CA 93106-6150, USA
*
*Corresponding author: Marine Science Institute, University of California, Santa Barbara, CA 93106-6150, USA. E-mail: daniel.benesh@lifesci.ucsb.edu

Summary

Complex life cycles are common in free-living and parasitic organisms alike. The adaptive decoupling hypothesis postulates that separate life cycle stages have a degree of developmental and genetic autonomy, allowing them to be independently optimized for dissimilar, competing tasks. That is, complex life cycles evolved to facilitate functional specialization. Here, I review the connections between the different stages in parasite life cycles. I first examine evolutionary connections between life stages, such as the genetic coupling of parasite performance in consecutive hosts, the interspecific correlations between traits expressed in different hosts, and the developmental and functional obstacles to stage loss. Then, I evaluate how environmental factors link life stages through carryover effects, where stressful larval conditions impact parasites even after transmission to a new host. There is evidence for both autonomy and integration across stages, so the relevant question becomes how integrated are parasite life cycles and through what mechanisms? By highlighting how genetics, development, selection and the environment can lead to interdependencies among successive life stages, I wish to promote a holistic approach to studying complex life cycle parasites and emphasize that what happens in one stage is potentially highly relevant for later stages.

Information

Type
Review Article
Copyright
Copyright © Cambridge University Press 2016 
Figure 0

Fig. 1. The adaptive decoupling hypothesis. The relative fitness of different phenotypes is plotted over time. In (A), there are two phenotypes with simple life cycles; they grow in size over time, but there is no major restructuring of the phenotype. The ‘triangle’ phenotype performs better as a small juvenile but is then outperformed by the ‘circle’ phenotype later in life. The fitness of a given phenotype can vary over time for many reasons, such as a change in foraging ecology (e.g. the optimal prey differs for small juveniles and larger adults), in predator risk or type (e.g. large sizes may provide a ‘size refuge’), or in required tasks (e.g. reproduction later in life or dispersal at the end of a season). This tradeoff between the phenotypes optimal for juveniles and those optimal for adults favours a complex life cycle. In (B), there is metamorphosis from the ‘triangle’ to the ‘circle’ phenotype, which maximizes lifetime fitness (inset). In order to produce distinct phenotypes in succession, the genetic and ontogentic covariance between life phases is broken apart, thereby allowing different stages to respond independently to unique selective pressures, i.e. they are adaptively decoupled.

Figure 1

Fig. 2. The effect of genetic covariance on the phenotypic response to selection. Symbols represent different genetic groups (e.g. clones, full-sibs, maternal half-sibs, etc.; the exact genetic relationships are important for calculating and interpreting genetic correlations, but not for demonstrating the concept). A parasite trait expressed in the first host is negatively genetically correlated with a trait measured in the second host. In (A), selection (red vector, open arrow) favours high values of both traits, such as if the traits were the infection rate in each of the two hosts. As selection is orthogonal to the genetic covariance, there will be a slow and limited response to selection (blue vector, closed arrow). In (B), there is only selection on the trait in the first host, but because of the genetic correlation, there will be an indirect, correlated response to selection in the trait in the second host.

Figure 2

Fig. 3. Genetic correlations across hosts in the tapeworm Schistocephalus solidus. Each point is the mean for a family of full siblings. Fourteen families were in the parental generation (P), and they were used to infect copepods, the first intermediate host, and then sticklebacks, the second intermediate host. These 14 families were then crossed in vitro to produce another seven families that constituted the F1 generation. There were no significant family-level correlations between (A) infection rates in copepods and fish (Pearson correlations, P generation: r = −0·22, P = 0·44, F1 generation: r = −0·13, P = 0·79) or (B) between growth in copepods and infectivity to fish (P generation: r = 0·09, P = 0·77, F1 generation: r = −0·22, P = 0·64). This can be attributed to the low heritability of infection rates (broad-sense H2 = 0·01 to 0·03 for copepod and <0·01 for fish infection rates). The average sample sizes for calculating family means were 195 for copepod infection rate, 24 for size in copepods, and 25 for fish infection rate. Data from Benesh et al. (2014b).

Figure 3

Fig. 4. The body length (in mm on a log10 scale) of 65 tapeworm species in their copepod first host and their vertebrate second host. Species are grouped according to whether they have a two-host life cycle (second host is definitive host) or a longer life cycle (second host is an intermediate host). In (A), the sizes of individual species are connected by lines. Note how the size variation in copepods is restricted compared with that in the next host. In (B), the relationship between worm size in the copepod host and in the second host is plotted. It was not significant (non-phylogenetic Pearson correlations, two hosts: r = 0·13, P = 0·58, more than two hosts: r = 0·10, P = 0·52). (D. P. Benesh, unpublished observation)

Figure 4

Table 1. Studies on how transmission with or without an intermediate host (IH) affects establishment probability and development

Figure 5

Fig. 5. (A) Hypothetical growth trajectories of a parasite in its intermediate host. Growth is slower and the development of infectivity (where the curves transition from solid to dotted) is delayed under stressful conditions. This is a common response to nutritional stress, such as a crowded infection or a starved host, but numerous other factors could stress larval parasites, including e.g. thermal stress, pollutants or host immunity, and these stressors need not affect growth and development in the same way. (B) The negative effects of being in a poor quality intermediate host can persist into the next host, i.e. there are carryover effects. It is also possible that once parasites are in a new host, they compensate for a stressful larval period, particularly if the trait of interest is measured long after transmission.