<i>Saccharomyces cerevisiae</i> Hsp104 Enhances the Chaperone Capacity of Human Cells and Inhibits Heat Stress-Induced Proapoptotic Signaling
Bibliographic record
Abstract
Hsp104, the most potent thermotolerance factor in Saccharomyces cerevisiae, is an unusual molecular chaperone that is associated with the dispersal of aggregated, non-native proteins in vivo and in vitro. The close cooperation between Hsp100 oligomeric disaggregases and specific Hsp70 chaperone/cochaperone systems to refold and reactivate heat-damaged proteins has been dubbed a "bichaperone network". Interestingly, animal genomes do not encode a Hsp104 ortholog. To investigate the biochemical and biological consequences of introducing into human cells a stress tolerance factor that has protein refolding capabilities distinct from those already present, Hsp104 was expressed as a transgene in a human leukemic T-cell line (PEER). Hsp104 inhibited heat-shock-induced loss of viability in PEER cells, and this action correlated with reduced procaspase-3 cleavage but not with reduced c-Jun N-terminal kinase phosphorylation. Hsp104 cooperated with endogenous human Hsp70 and Hsc70 molecular chaperones and their J-domain-containing cochaperones Hdj1 and Hdj2 to produce a functional hybrid bichaperone network capable of refolding aggregated luciferase. We also established that Hsp104 shuttles across the nuclear envelope and enhances the chaperoning capacity of both the cytoplasm and nucleoplasm of intact cells. Our results establish the fundamental properties of protein disaggregase function in human cells with implications for the use of Hsp104 or related proteins as therapeutic agents in diseases associated with protein aggregation.
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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".