Examining the Role of Ataxin-2 Protein and its Domains in Cellular Function, Translational Control and Neurodegeneration
Bibliographic record
Abstract
Ataxin-2 (ATXN2) is a gene implicated in spinocerebellar ataxia type II (SCA2), amyotrophic lateral sclerosis (ALS) and Parkinsonism. The encoded protein is a therapeutic target for ALS and related conditions. ATXN2 (or Atx2 in insects) can function in translational activation, translational repression, mRNA stability and in the assembly of mRNP-granules, a process mediated by intrinsically disordered regions (IDRs). Our work has shown that the C-terminal IDR of Atx2 is essential for both long-term habituation and degeneration model progression in flies. On the other hand, we subsequently show the structured LSm domain, which can help stimulate mRNA translation, antagonizes mRNP-granule assembly. We built on previous research through a series of experiments on Drosophila and human Ataxin-2 proteins to highlight a poly-A tail ? polyA-binding protein (PABP) ? Atx2 interaction driven localisation mechanism for the protein. Results of Targets of RNA-Binding Proteins Identified by Editing (TRIBE), co-localization and immunoprecipitation experiments indicate that the PABP interacting, PAM2 motif of Ataxin-2 may be a major determinant of the mRNA and protein content of Ataxin-2 mRNP granules. Transgenic experiments in Drosophila indicate that while the Atx2-LSm domain may protect against neurodegeneration, structured PAM2- and unstructured IDR- interactions both, through distinct modes of action, support Atx2-induced cytotoxicity. Examining radically truncated Atx2 constructs in cells and transgenic flies allowed to separate and independently assay the effects of structured and unstructured domains and their respective interactions. Taken together, the data lead to a proposal for how Ataxin-2 interactions are remodeled during translational control and how structured and non-structured interactions contribute differently to the specificity and efficiency of RNP granule condensation as well as to neurodegeneration, with powerful implications for future therapeutic approaches.
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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".