Mechanisms of PTPσ-Mediated Presynaptic Differentiation
Bibliographic record
Abstract
Formation of synapses between neurons depends in part on binding between axonal and dendritic cell surface synaptic organizing proteins, which recruit components of the developing presynaptic and postsynaptic specializations. One of these presynaptic organizing molecules is protein tyrosine phosphatase σ (PTPσ). Although the protein domains involved in adhesion between PTPσ and its postsynaptic binding partners are known, the mechanisms by which it signals into the presynaptic neuron to recruit synaptic vesicles and other necessary components for regulated transmitter release are not well understood. One attractive candidate to mediate this function is liprin-α, a scaffolding protein with well-established roles at the synapse. We systematically mutated residues of the PTPσ intracellular region (ICR) and used the yeast dihydrofolate reductase (DHFR) protein complementation assay to screen for disrupted interactions between these mutant forms of PTPσ and its various binding partners. Using a molecular replacement strategy, we show that disrupting the interaction between PTPσ and liprin-α, but not between PTPσ and itself or another binding partner, caskin, abolishes presynaptic differentiation. Furthermore, phosphatase activity of PTPσ and binding to extracellular heparan sulfate (HS) proteoglycans are dispensable for presynaptic induction. Previous reports have suggested that binding between PTPσ and liprin-α is mediated by the PTPσ membrane-distal phosphatase-like domain. However, we provide evidence here that both of the PTPσ phosphatase-like domains mediate binding to liprin-α and are required for PTPσ-mediated presynaptic differentiation. These findings further our understanding of the mechanistic basis by which PTPσ acts as a presynaptic organizer.
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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".