G-protein coupled receptor BAI3 promotes myoblast fusion in vertebrates
Bibliographic record
Abstract
Muscle fibers form as a result of myoblast fusion, yet the cell surface receptors regulating this process are unknown in vertebrates. In Drosophila, myoblast fusion involves the activation of the Rac pathway by the guanine nucleotide exchange factor Myoblast City and its scaffolding protein ELMO, downstream of cell-surface cell-adhesion receptors. We previously showed that the mammalian ortholog of Myoblast City, DOCK1, functions in an evolutionarily conserved manner to promote myoblast fusion in mice. In search for regulators of myoblast fusion, we identified the G-protein coupled receptor brain-specific angiogenesis inhibitor (BAI3) as a cell surface protein that interacts with ELMO. In cultured cells, BAI3 or ELMO1/2 loss of function severely impaired myoblast fusion without affecting differentiation and cannot be rescued by reexpression of BAI3 mutants deficient in ELMO binding. The related BAI protein family member, BAI1, is functionally distinct from BAI3, because it cannot rescue the myoblast fusion defects caused by the loss of BAI3 function. Finally, embryonic muscle precursor expression of a BAI3 mutant unable to bind ELMO was sufficient to block myoblast fusion in vivo. Collectively, our findings provide a role for BAI3 in the relay of extracellular fusion signals to their intracellular effectors, identifying it as an essential transmembrane protein for embryonic vertebrate myoblast fusion.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".