Chronic Knockout of the ETS Transcription Factor ERG Promotes Loss of Endothelial Cell Identity and Endothelial Cell Dysfunction in an Aortic Endothelial Cell Model Relevant For Atherosclerosis
Bibliographic record
Abstract
Background: The ETS transcription factor ERG is a key endothelial cell (EC) transcription factor.ERG represses vascular inflammation and is downregulated in chronic inflammatory diseases (eg, liver fibrogenesis, atherosclerosis).Previously, transient ERG knock-down has been associated with endothelial-mesenchymal transition (EndMT) and EC dysfunction; however, the mechanisms underlying EndMT and the EC dysfunction associated with chronic ERG loss have not been elucidated in an atherosclerosis-relevant model.We hypothesize that chronic ERG knockout (KO) in telomerase-immortalized human aortic ECs (telo-HAECs) induces EndMT and contributes to EC dysfunction underlying vascular dysregulation in atherosclerosis.Methods: TeloHAECs with CRIPSR/Cas9-mediated deletion of ERG were used.Chromatin accessibility and gene expression in ERG KO and wildtype (WT) teloHAECs were assessed using ATAC-seq (n ¼ 2) and RNA-seq (n ¼ 5-6).TOBIAS and diffTF were used to identify enriched motifs by footprinting (P < .05)and to profile TF activity (FDR < 0.05), respectively.ERG-mediated EC dysfunction was investigated using immunofluorescence (IF; n ¼ 3), Western blot (WB; n ¼ 3), and a timelapse migration assay (n ¼ 3).Results: There were w 21,000 differentially accessible chromatin peaks between ERG KO and WT ECs.Integrated analysis of chromatin accessibility and gene expression demonstrated increased activity of TGFb-SMAD and IL-1b signaling constituents and classical EndMT transcription factors.Loss of ERG downregulated EC genes (eg, CLDN5, TIE1) and protein expression (eg, CDH5, vWF) and upregulated mesenchymal genes (eg, ACTA2, FSP1) and protein distribution (eg, FN1, COL1A1).Investigation of EC-dysfunction phenotypes revealed increased migration and proliferation in ERG KO teloHAEC -with the percentage of Ki67 positive ECs increasing from 14% to 49% (P < .05;n ¼ 3).Conclusion: ERG KO in cultured aortic ECs markedly impacts chromatin accessibility and gene expression and induces EC identity loss, migration, and proliferation, providing mechanistic insight into the role of ERG in vascular dysfunction in atherosclerosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".