The Origin and Evolution of Antistasin-like Proteins in Leeches (Hirudinida, Clitellata)
Bibliographic record
Abstract
Bloodfeeding is employed by many parasitic animals and requires specific innovations for efficient feeding. Some of these innovations are molecular features that are related to the inhibition of hemostasis. For example, bloodfeeding insects, bats, and leeches release proteins with anticoagulatory activity through their salivary secretions. The antistasin-like protein family, composed of serine protease inhibitors with one or more antistasin-like domains, is tightly linked to inhibition of hemostasis in leeches. However, this protein family has been recorded also in non-bloodfeeding invertebrates, such as cnidarians, mollusks, polychaetes, and oligochaetes. The present study aims to 1) root the antistasin-like gene tree and delimit the major orthologous groups, 2) identify potential independent origins of salivary proteins secreted by leeches, and 3) identify major changes in domain and/or motif structure within each orthologous group. Five clades containing leech antistasin-like proteins are distinguishable through rigorous phylogenetic analyses based on nine new transcriptomes and a diverse set of comparative data: the trypsin + leukocyte elastase inhibitors clade, the antistasin clade, the therostasin clade, and two additional, unnamed clades. The antistasin-like gene tree supports multiple origins of leech antistasin-like proteins due to the presence of both leech and non-leech sequences in one of the unnamed clades, but a single origin of factor Xa and trypsin + leukocyte elastase inhibitors. This is further supported by three sequence motifs that are exclusive to antistasins, the trypsin + leukocyte elastase inhibitor clade, and the therostasin clade, respectively. We discuss the implications of our findings for the evolution of this diverse family of leech anticoagulants.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".