TCDD alters essential transcriptional regulators of osteogenic differentiation in multipotent mesenchymal stem cells
Bibliographic record
Abstract
Differentiation of multipotent mesenchymal stem cells (MSCs) into bone-forming osteoblasts requires strict coordination of transcriptional pathways. Aryl hydrocarbon receptor ligands, such as 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), have been shown to alter osteoblast differentiation in vitro and bone formation in multiple developmental in vivo models. The goal of the present study was to establish a global transcriptomic landscape during early, intermediate, and apical stages of osteogenic differentiation in vitro in response to TCDD exposure. Human bone-derived mesenchymal stem cells (hBMSCs) were cultured in growth media (GM), osteogenic differentiation media (ODM), or ODM containing 10 nM TCDD (ODM + TCDD), thus enabling a comparison of the transcriptomic profiles of undifferentiated, differentiated, and differentiated-TCDD-exposed hBMSCs, respectively. In this test system, exposure to TCDD attenuated the differentiation of hBMSCs into osteoblasts as evidenced by reduced alkaline phosphatase activity and mineralization. At various timepoints, we observed altered expression of genes that play a role in the Wnt, fibroblast growth factor, bone morphogenetic protein/transforming growth factor beta developmental pathways, as well as pathways related to extracellular matrix organization and deposition. Reconstruction of gene regulatory networks with the interactive dynamic regulatory event miner (iDREM) analysis revealed modulation of transcription factors (TFs) including POLR3G, NR4A1, RDBP, GTF2B, POU2F2, and ZEB1, which may putatively influence osteoblast differentiation and the requisite deposition and mineralization of bone extracellular matrix. We demonstrate that the combination of RNA-Seq data in conjunction with the iDREM regulatory model captures the transcriptional dynamics underlying MSC differentiation under different conditions in vitro. Model predictions are consistent with existing knowledge and provide a new tool to identify novel pathways and TFs that may facilitate a better understanding of the osteoblast differentiation process, perturbation by exogenous agents, and potential intervention strategies targeting those specific pathways.
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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) | 0.001 | 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 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".