Precursor of Brain-derived Neurotrophic Factor (proBDNF) Forms a Complex with Huntingtin-associated Protein-1 (HAP1) and Sortilin That Modulates proBDNF Trafficking, Degradation, and Processing
Bibliographic record
Abstract
proBDNF, a precursor of brain-derived neurotrophic factor (BDNF), is anterogradely transported and released from nerve terminals, but the mechanism underlying this process remains unclear. In this study, we report that proBDNF forms a complex with Huntingtin associated protein-1 (HAP1) and sortilin, which plays an important role in proBDNF intracellular trafficking and stabilization. The interaction of proBDNF with both HAP1A and sortilin in co-transfected HEK293 cells is confirmed by both fluorescence resonance energy transfer and co-immunoprecipitation. The frequent co-localization (>90%) of endogenous HAP1, sortilin, and proBDNF is also found in cultured cortical neurons. Mapping studies using GST pulldown and competition assays has defined the interacting region of HAP1 with proBDNF within amino acids 371-445 and the binding sequences of proBDNF to HAP1 between amino acids 65 and 90. Fluorescence recovery after photobleaching confirms the defective movement of proBDNF-containing vesicles in neurites of HAP1(-/-) neurons, which can be partially restored by reintroducing HAP1 cDNA into the neurons. However, the effect is significantly increased by simultaneously reintroducing both HAP1 and sortilin. proBDNF and HAP1 are highly co-localized with organelle markers for the Golgi network, microtubules, molecular motor, or endosomes in normal neurons, but this co-localization is reduced in HAP1(-/-) neurons. Co-immunoprecipitation and Western blot showed that sortilin stabilizes the proBDNF·HAP1 complex in co-transfected HEK293 cells, helping to prevent proBDNF degradation. Furthermore, the complex facilitates furin cleavage to release mature BDNF.
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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) | 0.001 | 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".