The Co-Chaperone HspBP1 Is a Novel Component of Stress Granules that Regulates Their Formation
Bibliographic record
Abstract
The co-chaperone HspBP1 interacts with members of the hsp70 family, but also provides chaperone-independent functions. We report here novel biological properties of HspBP1 that are relevant to the formation of cytoplasmic stress granules (SGs). SG assembly is a conserved reaction to environmental or pathological insults and part of the cellular stress response. Our study reveals that HspBP1 (1) is an integral SG constituent, and (2) a regulator of SG assembly. Oxidative stress relocates HspBP1 to SGs, where it co-localizes with granule marker proteins and polyA-RNA. Mass spectrometry and co-immunoprecipitation identified novel HspBP1-binding partners that are critical for SG biology. Specifically, HspBP1 associates with the SG proteins G3BP1, HuR and TIA-1/TIAR. HspBP1 also interacts with polyA-RNA in vivo and binds directly RNA homopolymers in vitro. Multiple lines of evidence and single-granule analyses demonstrate that HspBP1 is crucial for SG biogenesis. Thus, HspBP1 knockdown interferes with stress-induced SG assembly. By contrast, HspBP1 overexpression promotes SG formation in the absence of stress. Notably, the hsp70-binding domains of HspBP1 regulate SG production in unstressed cells. Taken together, we identified novel HspBP1 activities that control SG formation. These features expand HspBP1's role in the cellular stress response and provide new mechanistic insights into SG biogenesis.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".