The impacts of host association and perturbation on symbiont fitness
Bibliographic record
Abstract
Symbiosis can benefit hosts in numerous ways, but less is known about whether interactions with hosts benefit symbionts-the smaller species in the relationship. To determine the fitness impact of host association on symbionts in likely mutualisms, we conducted a meta-analysis across 91 unique host-symbiont pairings under a range of spatial and temporal contexts. Specifically, we assess the consequences to symbiont fitness when in and out of symbiosis, as well as when the symbiosis is under suboptimal or varying environments and biological conditions (e.g., host age). We find that some intracellular symbionts associated with protists tend to have greater fitness when the symbiosis is under stressful conditions. Symbionts of plants and animals did not exhibit this trend, suggesting that symbionts of multicellular hosts are more robust to perturbations. Symbiont fitness also generally increased with host age. Lastly, we show that symbionts able to proliferate in- and outside host cells exhibit greater fitness than those found exclusively inside or outside cells. The ability to grow in multiple locations may thus help symbionts thrive. We discuss these fitness patterns in light of host-driven factors, whereby hosts exert influence over symbionts to suit their own needs. Supplementary Information: The online version contains supplementary material available at 10.1007/s13199-024-00984-6.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".