Zonadhesin Is Essential for Species Specificity of Sperm Adhesion to the Egg Zona Pellucida
Bibliographic record
Abstract
Interaction of rapidly evolving molecules imparts species specificity to sperm-egg recognition in marine invertebrates, but it is unclear whether comparable interactions occur during fertilization in any vertebrate species. In mammals, the sperm acrosomal protein zonadhesin is a rapidly evolving molecule with species-specific binding activity for the egg zona pellucida (ZP). Here we show using null mice produced by targeted disruption of Zan that zonadhesin confers species specificity to sperm-ZP adhesion. Sperm capacitation selectively exposed a partial von Willebrand D domain of mouse zonadhesin on the surface of living, motile cells. Antibodies to the exposed domain inhibited adhesion of wild-type spermatozoa to the mouse ZP but did not inhibit adhesion of spermatozoa lacking zonadhesin. Zan(-/-) males were fertile, and their spermatozoa readily fertilized mouse eggs in vitro. Remarkably, however, loss of zonadhesin increased adhesion of mouse spermatozoa to pig, cow, and rabbit ZP but not mouse ZP. We conclude that zonadhesin mediates species-specific ZP adhesion, and Zan(-/-) males are fertile because their spermatozoa retain adhesion capability that is not species-specific. Mammalian sperm-ZP adhesion is therefore molecularly robust, and species-specific egg recognition by a protein in the sperm acrosome is conserved between invertebrates and vertebrates, even though the adhesion molecules themselves are unrelated.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".