The role of defensive symbionts in host–parasite coevolution
Bibliographic record
Abstract
Understanding the coevolution of hosts and parasites is a long-standing goal of evolutionary biology. There is a well-developed theoretical framework to describe the evolution of host-parasite interactions under the assumption of direct, two-species interactions, which can result in arms race dynamics or sustained genotype fluctuations driven by negative frequency dependence (Red Queen dynamics). However, many hosts rely on symbionts for defence against parasites. Whilst the ubiquity of defensive symbionts and their potential importance for disease control are increasingly recognized, there is still a gap in our understanding of how symbionts mediate or possibly take part in host-parasite coevolution. Herein we address this question by synthesizing information already available from theoretical and empirical studies. First, we briefly introduce current hypotheses on how defensive mutualisms evolved from more parasitic relationships and highlight exciting new experimental evidence showing that this can occur very rapidly. We go on to show that defensive symbionts influence virtually all important determinants of coevolutionary dynamics, namely the variation in host resistance available to selection by parasites, the specificity of host resistance, and the trade-off structure between host resistance and other components of fitness. In light of these findings, we turn to the limited theory and experiments available for such three-species interactions to assess the role of defensive symbionts in host-parasite coevolution. Specifically, we discuss under which conditions the defensive symbiont may take over from the host the reciprocal adaptation with parasites and undergo its own selection dynamics, thereby altering or relaxing selection on the hosts' own immune defences. Finally, we address potential effects of defensive symbionts on the evolution of parasite virulence. This is an important problem for which there is no single, clear-cut prediction. The selection on parasite virulence resulting from the presence of defensive symbionts in their hosts will depend on the underlying mechanism of defence. We identify the evolutionary predictions for different functional categories of symbiont-conferred resistance and we evaluate the empirical literature for supporting evidence. We end this review with outstanding questions and promising avenues for future research to improve our understanding of symbiont-mediated coevolution between hosts and parasites.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".