Phosphorylation‐dependent control of Activity‐regulated cytoskeleton‐associated protein (Arc) protein by TNIK
Bibliographic record
Abstract
Activity-regulated cytoskeleton-associated protein (Arc) is an immediate early gene product that support neuroplastic changes important for cognitive function and memory formation. As a protein with homology to the retroviral Gag protein, a particular characteristic of Arc is its capacity to self-assemble into virus-like capsids that can package mRNAs and transfer those transcripts to other cells. Although a lot has been uncovered about the contributions of Arc to neuron biology and behavior, very little is known about how different functions of Arc are coordinately regulated both temporally and spatially in neurons. The answer to this question we hypothesized must involve the occurrence of different protein post-translational modifications acting to confer specificity. In this study, we used mass spectrometry and sequence prediction strategies to map novel Arc phosphorylation sites. Our approach led us to recognize serine 67 (S67) and threonine 278 (T278) as residues that can be modified by TNIK, which is a kinase abundantly expressed in neurons that shares many functional overlaps with Arc and has, along with its interacting proteins such as the NMDA receptor, and been implicated as a risk factor for psychiatric disorders. Furthermore, characterization of each residue using site-directed mutagenesis to create S67 and T278 mutant variants revealed that TNIK action at those amino acids can strongly influence Arc's subcellular distribution and self-assembly as capsids. Together, our findings reveal an unsuspected connection between Arc and TNIK. Better understanding of the interplay between these two proteins in neuronal cells could lead to new insights about apparition and progression of psychiatric disorders. Cover Image for this issue: https://doi.org/10.1111/jnc.15077.
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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".