Selective DNA Binding and Association with the CREB Binding Protein Coactivator Contribute to Differential Activation of Alpha/Beta Interferon Genes by Interferon Regulatory Factors 3 and 7
Bibliographic record
Abstract
Recent studies implicate the interferon (IFN) regulatory factors (IRF) IRF-3 and IRF-7 as key activators of the alpha/beta IFN (IFN-alpha/beta) genes as well as the RANTES chemokine gene. Using coexpression analysis, the human IFNB, IFNA1, and RANTES promoters were stimulated by IRF-3 coexpression, whereas the IFNA4, IFNA7, and IFNA14 promoters were preferentially induced by IRF-7 only. Chimeric proteins containing combinations of different IRF-7 and IRF-3 domains were also tested, and the results provided evidence of distinct DNA binding properties of IRF-3 and IRF-7, as well as a preferential association of IRF-3 with the CREB binding protein (CBP) coactivator. Interestingly, some of these fusion proteins led to supraphysiological levels of IFN promoter activation. DNA binding site selection studies demonstrated that IRF-3 and IRF-7 bound to the 5'-GAAANNGAAANN-3' consensus motif found in many virus-inducible genes; however, a single nucleotide substitution in either of the GAAA half-site motifs eliminated IRF-3 binding and transactivation activity but did not affect IRF-7 interaction or transactivation activity. These studies demonstrate that IRF-3 possesses a restricted DNA binding site specificity and interacts with CBP, whereas IRF-7 has a broader DNA binding specificity that contributes to its capacity to stimulate delayed-type IFN gene expression. These results provide an explanation for the differential regulation of IFN-alpha/beta gene expression by IRF-3 and IRF-7 and suggest that these factors have complementary rather than redundant roles in the activation of the IFN-alpha/beta genes.
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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 | 0.001 |
| 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".