Neuronal Phenotype in the Mature Nervous System Is Maintained by Persistent Retrograde Bone Morphogenetic Protein Signaling
Bibliographic record
Abstract
The terminal differentiation of many developing neurons occurs after they innervate their target cells and is triggered by secreted target-derived signals that are transduced by presynaptic cognate receptors. Such retrograde signaling induces the expression of genes that are often distinctive markers of neuronal phenotype and function. However, whether long-term maintenance of neuronal phenotype requires persistent retrograde signaling remains poorly understood. Previously, we demonstrated that retrograde bone morphogenetic protein (BMP) signaling induces expression of a phenotypic marker of Drosophila Tv neurons, the neuropeptide FMRFamide (FMRFa). Here, we used a genetic technique that spatiotemporally targets transgene expression in Drosophila to test the role of persistent BMP signaling in the maintenance of Tv phenotype. We show that expression of dominant blockers of BMP signaling selectively in adult Tv neurons dramatically downregulated FMRFa expression. Moreover, adult-onset expression of mutant Glued, which blocks dynein/dynactin-mediated retrograde axonal transport, eliminated retrograde BMP signaling and dramatically downregulated FMRFa expression. Finally, we found that BMP deprivation did not affect Tv neuron survival and that FMRFa expression fully recovered to control levels after the termination of BMP blockade or Glued expression. Our results show that persistent retrograde BMP signaling is required to induce and to subsequently maintain the expression of a stably expressed phenotypic marker in a subset of mature Drosophila neurons. We postulate that retrograde maintenance of neuronal phenotype is conserved in vertebrates, and as a consequence, neuronal phenotype is likely vulnerable to neurodegenerative disease pathologies that disrupt neuronal connectivity or axonal transport.
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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) | 0.000 | 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".