Genomic determinants implicated in the glucocorticoid-mediated induction of KLF9 in pulmonary epithelial cells
Bibliographic record
Abstract
Ligand-activated glucocorticoid receptor (GR) elicits variable glucocorticoid-modulated transcriptomes in different cell types. However, some genes, including Krüppel-like factor 9 (KLF9), a putative transcriptional repressor, demonstrate conserved responses. We show that glucocorticoids induce KLF9 expression in the human airways in vivo and in differentiated human bronchial epithelial (HBE) cells grown at air-liquid interface (ALI). In A549 and BEAS-2B pulmonary epithelial cells, glucocorticoids induce KLF9 expression with similar kinetics to primary HBE cells in submersion culture. A549 and BEAS-2B ChIP-seq data reveal four common glucocorticoid-induced GR binding sites (GBSs). Two GBSs mapped to the 5'-proximal region relative to KLF9 transcription start site (TSS) and two occurred at distal sites. These were all confirmed in primary HBE cells. Global run-on (GRO) sequencing indicated robust enhancer RNA (eRNA) production from three of these GBSs in BEAS-2B cells. This was confirmed in A549 cells, plus submersion, and ALI culture of HBE cells. Cloning each GBS into luciferase reporters revealed glucocorticoid-induced activity requiring a glucocorticoid response element (GRE) within each distal GBS. While the proximal GBSs drove modest reporter induction by glucocorticoids, this region exhibited basal eRNA production, RNA polymerase II enrichment, and looping to the TSS, plausibly underlying constitutive KLF9 expression. Post glucocorticoid treatment, interactions between distal and proximal GBSs and the TSS correlated with KLF9 induction. CBP/P300 silencing reduced proximal GBS activity, but negligibly affected KLF9 expression. Overall, a model for glucocorticoid-mediated regulation of KLF9 involving multiple GBSs is depicted. This work unequivocally demonstrates that mechanistic insights gained from cell lines can translate to physiologically relevant systems.
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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 | 0.000 |
| 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".