The stress-induced nucleolar accumulation of hsc70 is mediated by specific signals, nucleolar chaperone networks and RNA
Bibliographic record
Abstract
Heat shock cognate 70 kDa protein (hsc70) is a well conserved molecular chaperone involved in many physiological functions such as the stress response, protein folding, and protein transport. Moreover, hsc70 plays roles in human disease, such as cancer, neurodegenerative disease, heart and brain ischemia, and it also takes part in the aging process. With the help of co-chaperones and ATP hydrolysis, hsc70 can restore proper protein folding by binding to normally inaccessible hydrophobic residues on its target. Following heat shock, hsc70 traffics from the cytoplasm to the nucleoplasm. Hsc70 further accumulates in nucleoli during heat stress recovery. Using GFP-tagged portions of hsc70, I identified the nucleolar localization sequence (NoLS) of hsc70. Following quantification of the fluorescence signal, I showed that the nucleolar accumulation of different constructs varied. This allowed me to identify a heat inducible segment on hsc70, residues 225 to 297, which is sufficient for nucleolar accumulation during recovery from stress. The analysis of deletion mutants generated for segment 225-297 revealed that some constructs accumulated in the nucleolus constitutively, while others did not target GFP to nucleoli. Using pharmacological inhibitors, I also showed that PI3-kinase, MEK (MAP kinase kinase) and tyrosine dephosphorylation are involved in the hsc70 nucleolar accumulation process. The nucleolus is a well defined compartment in the nucleus that is dynamic and characterized by multiple functions. Nucleoli are currently at the center of important discoveries as they play a role in diseases such as cancer. The nucleolus participates in the control of cell cycle progression and viral infections, but its fundamental function is the assembly of ribosomes. Several thousand proteins have been identified in the nucleolus; however, as the nucleolus is dynamic, this composition depends on physiological and environmental conditions. My work focused on reviewing our knowledge of the possible chaperone networks present in the nucleolus. A new set of proteins, the nucleolar multitasking proteins (NoMPs), has been identified as chaperones that are necessary for the specific function of the nucleolus. These multitasking proteins include B23 and nucleolin. This work provided the basis for us to predict interactions between chaperones in the nucleolus.Many proteins of the nucleolus are dynamic: they can traffic to other cellular compartments when environmental conditions change. To define the mechanisms of hsc70 nucleolar accumulation during stress recovery, my work aimed at identifying the nucleolar binding partners of hsc70. I provided evidence that RNA plays a role for hsc70 nucleolar accumulation by treating heat shocked cells with detergent and RNase. Furthermore, inhibition of RNA polymerase I increased the retention time of endogenous hsc70 in the nucleolus. In further studies I examined the GFP-tagged hsc70 NoLS in transfected cells. This reporter displayed increased nucleolar accumulation and delayed release from the nucleolus during the recovery from heat shock when cells were treated with actinomycin D. On the other hand, RNA polymerase I inhibition was not sufficient to accumulate hsc70 or the GFP-tagged NoLS in nucleoli under normal growth conditions. In addition to the links between nucleolar RNA and hsc70, my research demonstrated that hsc70 and its NoLS bind to polyA+ RNA under normal growth conditions.Taken together, my studies advance our current understanding of the nucleolar accumulation of hsc70 during heat stress recovery. I identified important sequence elements, pathways and possible nucleolar anchors that contribute to hsc70 nucleolar accumulation. My work congregates important concepts that will likely be beneficial to human health.
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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".