RNA-binding proteins with basic-acidic dipeptide (BAD) domains self-assemble and aggregate in Alzheimer's disease
Bibliographic record
Abstract
The U1 small nuclear ribonucleoprotein 70 kDa (U1-70K) and other RNA-binding proteins (RBPs) are mislocalized to cytoplasmic neurofibrillary Tau aggregates in Alzheimer's disease (AD), yet the co-aggregation mechanisms are incompletely understood. U1-70K harbors two disordered low-complexity domains (LC1 and LC2) that are necessary for aggregation in AD brain extracts. The LC1 domain contains highly repetitive basic (Arg/Lys) and acidic (Asp/Glu) residues, referred to as a basic-acidic dipeptide (BAD) domain. We report here that this domain shares many of the properties of the Gln/Asn-rich LC domains in RBPs that also aggregate in neurodegenerative disease. These properties included self-assembly into oligomers and localization to nuclear granules. Co-immunoprecipitations of recombinant U1-70K and deletions lacking the LC domain(s) followed by quantitative proteomic analyses were used to resolve functional classes of U1-70K-interacting proteins that depend on the BAD domain for their interaction. Within this interaction network, we identified a class of RBPs with BAD domains nearly identical to that found in U1-70K. Two members of this class, LUC7L3 and RBM25, required their respective BAD domains for reciprocal interactions with U1-70K and nuclear granule localization. Strikingly, a significant proportion of RBPs with BAD domains had elevated insolubility in the AD brain proteome. Furthermore, we show that the BAD domain of U1-70K can interact with Tau from AD brains but not from other tauopathies. These findings highlight a mechanistic role for BAD domains in stabilizing RBP interactions and in potentially mediating co-aggregation with the pathological AD-specific Tau isoforms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".