Marine Leech Anticoagulant Diversity and Evolution
Bibliographic record
Abstract
Leeches (Annelida: Hirudinea) possess powerful salivary anticoagulants and, accordingly, are frequently employed in modern, authoritative medicine. Members of the almost exclusively marine family Piscicolidae account for 20% of leech species diversity, and they feed on host groups (e.g., sharks) not encountered by their freshwater and terrestrial counterparts. Moreover, some species of Ozobranchidae feed on endangered marine turtles and have been implicated as potential vectors for the tumor-associated turtle herpesvirus. In spite of their ecological importance and unique host associations, there is a distinct paucity of data regarding the salivary transcriptomes of either of these families. Using next-generation sequencing, we profiled transcribed, putative anticoagulants and other salivary bioactive compounds that have previously been linked to blood feeding from 7 piscicolid species (3 elasmobranch feeders; 4 non-cartilaginous fish feeders) and 1 ozobranchid species (2 samples). In total, 149 putative anticoagulants and bioactive loci were discovered in varying constellations throughout the different samples. The putative anticoagulants showed a broad spectrum of described antagonistic pathways, such as inhibition of factor Xa and platelet aggregation, which likely have similar bioactive roles in marine fish and turtles. A transcript with homology to ohanin, originally isolated from king cobras, was found in Cystobranchus vividus but is otherwise unknown from leeches. Estimation of selection pressures for the putative anticoagulants recovered evidence for both positive and purifying selection along several isolated branches in the gene trees, and positive selection was also estimated for a few select codons in a variety of marine species. Similarly, phylogenetic analyses of the amino acid sequences for several anticoagulants indicated divergent evolution.
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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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".