Coupling proximity biotinylation with genomic targeting to characterize locus-specific changes in chromatin environments
Bibliographic record
Abstract
Abstract Regulating gene expression involves significant and frequent changes in the chromatin environment at the locus level, especially at regulatory sequences. However, their modulation in response to pharmacological treatments or pathological conditions remain mostly undetermined. Here, we report versatile locus-specific proteomics tools to address this knowledge gap, which combine the targeting ability of the CRISPR/Cas9 system and the protein-labelling capability of the highly reactive biotin ligases TurboID (in CasTurbo) and UltraID (in CasUltra). CasTurbo and CasUltra enabled rapid chromatin protein labelling under mild conditions at repetitive sequences like centromeres and telomeres, as well as non-amplified genes. We applied CasUltra to A375 melanoma cell lines to decipher the protein environment of the MYC promoter and characterize the molecular effects of the bromodomain inhibitor JQ1, which targets bromodomain and extra-terminal (BET) proteins that regulate MYC expression. We quantified the consequences of BET protein displacement from the MYC promoter and found that it was associated with a considerable reorganisation of the chromatin composition. In addition, BET protein retention at the MYC promoter was consistent with a model of increased JQ1 resistance. Thus, through the combination of proximity biotinylation and CRISPR-Cas9-dependent genomic targeting, CasTurbo and CasUltra have successfully demonstrated their utility in profiling the proteome associated with a genomic locus in living cells. In Brief Kougnassoukou Tchara et al . report the development and application of CasTurbo and CasUltra, two locus-specific proteomics tools that fuse catalytically dead Cas9 to the engineered biotin ligases TurboID and UltraID. These tools enabled the quantitative mapping of locus-specific chromatin remodelling due to pharmacological inhibition. Highlights CasTurbo and CasUltra were developed for locus-specific label-free proteomics CasTurbo mapped the proteins localized to the centromeres and telomeres Proteins bound to the MYC promoter were quantified in melanoma cells with CasUltra CasUltra is compatible with investigating pharmacological treatment effects Graphical abstract
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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 | 0.001 | 0.001 |
| 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".