The Human Tau Interactome: Binding to the Ribonucleoproteome, and Impaired Binding of the Proline-to-Leucine Mutant at Position 301 (P301L) to Chaperones and the Proteasome
Bibliographic record
Abstract
The tau protein is central to the etiology of several neurodegenerative diseases, including Alzheimer's disease, a subset of frontotemporal dementias, progressive supranuclear palsy and dementia following traumatic brain injury, yet the proteins it interacts with have not been studied using a systematic discovery approach. Here we employed mild in vivo crosslinking, isobaric labeling, and tandem mass spectrometry to characterize molecular interactions of human tau in a neuroblastoma cell model. The study revealed a robust association of tau with the ribonucleoproteome, including major protein complexes involved in RNA processing and translation, and documented binding of tau to several heat shock proteins, the proteasome and microtubule-associated proteins. Follow-up experiments determined the relative contribution of cellular RNA to the tau interactome and mapped interactions to N- or C-terminal tau domains. We further document that expression of P301L mutant tau disrupts interactions of the C-terminal half of tau with heat shock proteins and the proteasome. The data are consistent with a model whereby a higher propensity of P301L mutant tau to aggregate may reflect a perturbation of its chaperone-assisted stabilization and proteasome-dependent degradation. Finally, using a global proteomics approach, we show that heterologous expression of a tau construct that lacks the C-terminal domain, including the microtubule binding domain, does not cause a discernible shift of the proteome except for a significant direct correlation of steady-state levels of tau and cystatin B.
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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".