Aminopeptidase N is a receptor for hedgehog merbecoviruses
Bibliographic record
Abstract
ABSTRACT Merbecoviruses, closely related to the highly pathogenetic Middle East Respiratory Syndrome Coronavirus (MERS-CoV), circulate in hedgehogs throughout Europe and Asia, raising concerns about zoonotic transmission to humans and domestic animals. Unfortunately, how these viruses enter host cells remains unknown, hindering experimental studies. Here, we tested known coronavirus receptor orthologues from European hedgehogs ( Erinaceus europaeus ) and identified Aminopeptidase N (APN) as an entry receptor for hedgehog merbecoviruses. We confirm this result with single-cycle pseudotype and replication-competent virus experiments as well as protein binding assays. A screen of 30 mammalian APN orthologues reveals restricted cross-species receptor use. Cryo-electron microscopy analysis of the viral glycoprotein–receptor complex shows a unique interface distinct from known coronavirus spike:APN interactions, providing a molecular basis for species barriers. These findings expand the known range of receptor use not only within merbecoviruses but also betacoronaviruses, improving our understanding of betacoronavirus receptors, and informing risk assessments for viral emergence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".