Symbionts of the ciliate <i>Euplotes</i> : diversity, patterns and potential as models for bacteria–eukaryote endosymbioses
Bibliographic record
Abstract
Endosymbioses between bacteria and eukaryotes are enormously important in ecology and evolution, and as such are intensely studied. Despite this, the range of investigated hosts is narrow in the context of the whole eukaryotic tree of life: most of the information pertains to animal hosts, while most of the diversity is found in unicellular protists. A prominent case study is the ciliate Euplotes, which has repeatedly taken up the bacterium Polynucleobacter from the environment, triggering its transformation into obligate endosymbiont. This multiple origin makes the relationship an excellent model to understand recent symbioses, but Euplotes may host bacteria other than Polynucleobacter, and a more detailed knowledge of these additional interactions is needed in order to correctly interpret the system. Here, we present the first systematic survey of Euplotes endosymbionts, adopting a classical as well as a metagenomic approach, and review the state of knowledge. The emerging picture is indeed quite complex, with some Euplotes harbouring rich, stable prokaryotic communities not unlike those of multicellular animals. We provide insights into the distribution, evolution and diversity of these symbionts (including the establishment of six novel bacterial taxa), and outline differences and similarities with the most well-understood group of eukaryotic hosts: insects.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".