Coinfection of slime feather duster worms (Annelida, <i>Myxicola</i>) by different gregarine apicomplexans (<i>Selenidium</i>) and astome ciliates reflects spatial niche partitioning and host specificity
Bibliographic record
Abstract
Abstract Individual organisms can host multiple species of parasites (or symbionts), and one species of parasite can infect different host species, creating complex interactions among multiple hosts and parasites. When multiple parasite species coexist in a host, they may compete or use strategies, such as spatial niche partitioning, to reduce competition. Here, we present a host–symbiont system with two species of Selenidium (Apicomplexa, Gregarinida) and one species of astome ciliate co-infecting two different species of slime feather duster worms (Annelida, Sabellidae, Myxicola) living in neighbouring habitats. We examined the morphology of the endosymbionts with light and scanning electron microscopy (SEM) and inferred their phylogenetic interrelationships using small subunit (SSU) rDNA sequences. In the host ‘Myxicola sp. Quadra’, we found two distinct species of Selenidium; S. cf. mesnili exclusively inhabited the foregut, and S. elongatum n. sp. inhabited the mid to hindgut, reflecting spatial niche partitioning. Selenidium elongatum n. sp. was also present in the host M. aesthetica, which harboured the astome ciliate Pennarella elegantia n. gen. et sp. Selenidium cf. mesnili and P. elegantia n. gen. et sp. were absent in the other host species, indicating host specificity. This system offers an intriguing opportunity to explore diverse aspects of host–endosymbiont interactions and competition among endosymbionts.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".