Combinatorial regulation by ERK1/2 and CK1δ protein kinases leads to HIF-1α association with microtubules and facilitates its symmetrical distribution during mitosis
Bibliographic record
Abstract
Abstract Hypoxia-inducible factor-1 (HIF-1) is the key transcriptional mediator of the cellular response to hypoxia and is also involved in cancer progression. Regulation of its oxygen-sensitive HIF-1α subunit involves post-translational modifications that control its stability, subcellular localization, and activity. We have previously reported that phosphorylation of the HIF-1α C-terminal domain by ERK1/2 promotes HIF-1α nuclear accumulation and stimulates HIF-1 activity while lack of this modification triggers HIF-1α nuclear export and its association with mitochondria. On the other hand, modification of the N-terminal domain of HIF-1α by CK1δ impairs HIF-1 activity by obstructing the formation of a HIF-1α/ARNT heterodimer. Investigation of these two antagonistic events by expressing double phospho-site mutants in HIF1A −/− cells under hypoxia revealed independent and additive phosphorylation effects that can create a gradient of HIF-1α subcellular localization and transcriptional activity. Furthermore, modification by CK1δ caused mitochondrial release of the non-nuclear HIF-1α form and binding to microtubules via its N-terminal domain. In agreement, endogenous HIF-1α could be shown to co-localize with mitotic spindle microtubules and interact with tubulin, both of which were inhibited by CK1δ silencing or inhibition. Moreover, CK1δ expression was necessary for equal partitioning of mother cell-produced HIF-1α to the daughter cell nuclei at the end of mitosis. Overall, our results suggest that phosphorylation by CK1δ stimulates the association of non-nuclear HIF-1α with microtubules, which may serve as a means to establish a symmetric distribution of HIF-1α during cell division under low oxygen conditions.
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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".