Negative regulation of activation-induced cytidine deaminase gene transcription in developing B cells by a PU.1-interacting intronic region
Bibliographic record
Abstract
Activation-induced cytidine deaminase (AID, encoded by Aicda ) plays a key role in somatic hypermutation and class switch recombination in germinal center B cells. However, off-target effects of AID are implicated in human leukemia and lymphoma. A mouse model of precursor B cell acute lymphoblastic leukemia driven by deletion of the related transcription factors PU.1 and Spi-B revealed C->T transition mutations compatible with being induced by AID. Therefore, we hypothesized that PU.1 negatively regulates Aicda during B cell development. Aicda mRNA transcript levels were increased in leukemia cells and bone marrow pre-B cells lacking PU.1 and/or Spi-B, relative to wild type cells. Using chromatin immunoprecipitation, PU.1 was found to interact with a negative regulatory region (R2–1) within the first intron of Aicda . CRISPR-Cas9-induced mutagenesis of R2–1 in cultured pre-B cells resulted in upregulation of Aicda in response to lipopolysaccharide stimulation. Mutation of the PU.1 interaction site and neighboring sequences resulted in reduced repressive ability of R2–1 in transient transfection analysis followed by luciferase assays. These results show that a PU.1-interacting intronic region negatively regulates Aicda transcription in developing B cells. • Aicda transcription is dysregulated in the absence of PU.1. • The transcription factor PU.1 interacts with the first intron of Aicda. • CRISPR-Cas9 mutation of a PU.1 site in Aicda intron 1 dysregulates transcription. • A PU.1-interacting site in intron 1 is a negative regulator of Aicda transcription.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".