Inositol polyphosphate multikinase physically binds to the SWI/SNF complex and modulates BRG1 occupancy in mouse embryonic stem cells
Bibliographic record
Abstract
Inositol polyphosphate multikinase (IPMK), a key enzyme in inositol polyphosphate (IP) metabolism, is a pleiotropic signaling factor involved in major biological events, including transcriptional control. In the yeast, IPMK and its IP products promote the activity of the chromatin remodeling complex SWI/SNF, which plays a critical role in gene expression by regulating chromatin accessibility. However, the direct link between IPMK and chromatin remodelers remains unclear, raising the question of how IPMK contributes to transcriptional regulation in mammals. By employing unbiased screening approaches and in vivo/in vitro immunoprecipitation, here we demonstrate that mammalian IPMK physically interacts with the SWI/SNF complex by directly binding to SMARCB1, BRG1, and SMARCC1. Furthermore, we identified the specific domains required for IPMK-SMARCB1 binding. Notably, using CUT&RUN and ATAC-seq assays, we discovered that IPMK co-localizes with BRG1 and regulates BRG1 localization as well as BRG1-mediated chromatin accessibility in a genome-wide manner in mouse embryonic stem cells. Together, these findings show that IPMK regulates the promoter targeting of the SWI/SNF complex, thereby contributing to SWI/SNF-meditated chromatin accessibility, transcription, and differentiation in mouse embryonic stem cells.
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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 | 0.001 |
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".