Structural and Functional Insights into TAZ2‐mediated CBP/p300 Recruitment by the Melanogenic Transcription Factor MITF
Bibliographic record
Abstract
The microphthalmia‐associated transcription factor (MITF) is a master regulator of development and differentiation within the melanocyte lineage. However, aberrant MITF activity can lead to multiple malignancies such as skin cancer, where it plays a key role in modulating the proliferation and invasiveness of melanoma. MITF is a basic helix‐loop‐helix leucine zipper transcription factor that binds to specific gene promoters via a central DNA‐binding domain. MITF also recruits transcriptional co‐activators, such as the histone acetyltransferase CREB‐binding protein and its homologue p300 (CBP/p300) through an N‐terminal acidic transactivation domain (TAD), however the details of these interactions are not yet fully understood. In order to gain insight into the mechanisms of gene regulation by MITF, we investigated the structure and functional interaction between MITF‐TAD and the transcription adapter putative zinc finger (TAZ2) domain of CBP/p300. In mammalian‐one‐hybrid assays MITF transcriptional activity was enhanced in the presence of co‐transfected CBP/p300 and abolished upon deletion of residues within the MITF‐TAD. Peptide microarrays indicated that no one residue of MITF is essential for TAZ2 binding, however, deletion of multiple residues in MITF‐TAD ablated its ability to bind TAZ2. NMR‐based chemical shift mapping experiments determined that MITF‐TAD interacts with the same surface of TAZ2 as the adenoviral protein E1A, which has been shown to inhibit MITF function. We determined that E1A and MITF‐TAD directly compete for CBP/p300 through the TAZ2 domain using NMR‐based titrations, pulldown, and mammalian‐hybrid assays. Furthermore, we used qPCR to measure the effect of disrupting these interactions on the transcription of MITF‐specific target genes in melanoma‐derived cell lines. Understanding mechanistic details regarding the interaction between MITF and its co‐activators is fundamental to our understanding of gene regulation by MITF and may outline a potential new strategy to inhibit MITF function. Support or Funding Information This research was funded by the Beatrice Hunter Cancer Research Institute, Nova Scotia Heath Research Foundation Scotia Scholars Award, a Canadian Institutes of Health Research studentship, Dalhousie Nova Scotia Graduate Scholarship, and Izaak Walton Killam Predoctoral Scholarship.
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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) | 0.002 | 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".