Functional Analysis of a Dominant Negative Mutation of Interferon Regulatory Factor 5
Bibliographic record
Abstract
BACKGROUND: Interferon regulatory factor (IRF) family members have been implicated as critical transcription factors that function in immune response, hematopoietic differentiation and cell growth regulation. Activation of IRF-5 results in the production of pro-inflammatory cytokines such as TNFalpha, IL6 and IL12p40, as well as type I interferons. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we identify a G202C (position relative to translation start codon) missense-mutation transcript of IRF-5 in transformed B and T cell lines, which were either infected or non-infected by viruses, and peripheral blood from ATL or CLL patients. The mutated transcript encodes a novel protein in which the sixty-eighth amino acid, Alanine, is substituted by Proline (IRF-5P68) in the DNA binding domain of IRF-5. IRF-5P68 phenotype results in a complete loss of its DNA-binding activity and functions as a dominant negative molecule through interacting with wild type IRF-5. Co-expression of IRF-5P68 inhibits MyD88-mediated IRF-5 transactivation. Moreover, Toll-like receptor (TLR)-dependent IL6 and IL12P40 production induced by lipopolysaccharide (LPS), R837 or CpG ODN 1826 was reduced in IRF-5 (P68) expressing cells as compared to the control cells. CONCLUSION: IRF-5P68 acts as a dominant negative regulator that interferes with IRF-5-mediated production of pro-inflammatory cytokines. The functional characterization of the novel IRF-5 mutant in transformed B and T cell lines and in ATL and CLL patients may lead to a better understanding of the role of these transcriptional regulators in hematopoietic malignancies.
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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) | 0.001 | 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 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".