Epigenetic reprogramming enhances the therapeutic efficacy of osteoblast‐derived extracellular vesicles to promote human bone marrow stem cell osteogenic differentiation
Bibliographic record
Abstract
Abstract Extracellular vesicles (EVs) are emerging in tissue engineering as promising acellular tools, circumventing many of the limitations associated with cell‐based therapies. Epigenetic regulation through histone deacetylase (HDAC) inhibition has been shown to increase differentiation capacity. Therefore, this study aimed to investigate the potential of augmenting osteoblast epigenetic functionality using the HDAC inhibitor Trichostatin A (TSA) to enhance the therapeutic efficacy of osteoblast‐derived EVs for bone regeneration. TSA was found to substantially alter osteoblast epigenetic function through reduced HDAC activity and increased histone acetylation. Treatment with TSA also significantly enhanced osteoblast alkaline phosphatase activity (1.35‐fold), collagen production (2.8‐fold) and calcium deposition (1.55‐fold) during osteogenic culture ( P ≤ 0.001). EVs derived from TSA‐treated osteoblasts (TSA‐EVs) exhibited reduced particle size (1‐05‐fold) ( P > 0.05), concentration (1.4‐fold) ( P > 0.05) and protein content (1.16‐fold) ( P ≤ 0.001) when compared to untreated EVs. TSA‐EVs significantly enhanced the proliferation (1.13‐fold) and migration (1.3‐fold) of human bone marrow stem cells (hBMSCs) when compared to untreated EVs ( P ≤ 0.05). Moreover, TSA‐EVs upregulated hBMSCs osteoblast‐related gene and protein expression (ALP, Col1a, BSP1 and OCN) when compared to cells cultured with untreated EVs. Importantly, TSA‐EVs elicited a time‐dose dependent increase in hBMSCs extracellular matrix mineralisation. MicroRNA profiling revealed a set of differentially expressed microRNAs from TSA‐EVs, which were osteogenic‐related. Target prediction demonstrated these microRNAs were involved in regulating pathways such as ‘endocytosis’ and ‘Wnt signalling pathway’. Moreover, proteomics analysis identified the enrichment of proteins involved in transcriptional regulation within TSA‐EVs. Taken together, our findings suggest that altering osteoblasts’ epigenome accelerates their mineralisation and promotes the osteoinductive potency of secreted EVs partly due to the delivery of pro‐osteogenic microRNAs and transcriptional regulating proteins. As such, for the first time we demonstrate the potential to harness epigenetic regulation as a novel engineering approach to enhance EVs therapeutic efficacy for bone repair.
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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".