Oligomerization of Transcriptional Intermediary Factor 1 Regulators and Interaction with ZNF74 Nuclear Matrix Protein Revealed by Bioluminescence Resonance Energy Transfer in Living Cells
Bibliographic record
Abstract
Transcriptional intermediary factor 1 (TIF1) alpha and KAP-1/TIF1beta, two members of the TIF1 family of nuclear cofactors, are ubiquitous co-regulators of nuclear receptors and KRAB motif-containing zinc finger transcription factors, respectively. Despite the functional evidence suggesting a role for TIF1 proteins as modulators of transcription, the study of their interactions with transcriptional machineries in physiologically relevant systems has been difficult. Here, we have developed a bioluminescence resonance energy transfer (BRET) biophysical approach to study protein-protein interactions in the nuclear compartment of living mammalian cells. We report that TIF1alpha and KAP-1 form homo- and hetero-oligomers in intact mammalian cells. BRET titration experiments indicate that both homo- and hetero-oligomers occur with relatively high affinity suggesting that they could co-exist in cells. Furthermore, we demonstrate that KAP-1 but not TIF1alpha interacts with the KRAB multifinger ZNF74 in the nuclear matrix. Splice variants and point mutants of ZNF74 that lack transcriptional activity were found not to interact with KAP-1 confirming the physiological importance of this interaction in living cells. The interaction of ZNF74 with KAP-1 did not prevent KAP-1 homomerization indicating that the oligomers most likely represent the transcriptionally active species. Furthermore, the detection of ternary ZNF74.KAP-1.TIF1alpha complexes suggests the existence of cross-talk between KAP-1-interacting KRAB proteins and TIF1alpha-interacting nuclear receptors. In addition to providing new insights into the molecular interactions involved in the transcriptional activities of these proteins, this study shows that BRET can be advantageously used as a non-transcription-based oligomerization detection system to study the interaction of transcriptionally active proteins, including nuclear matrix proteins, in living 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 | 0.001 |
| 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".