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Updated: Aug 7, 2025

LINE-1 Methylation Analysis in Mesenchymal Stem Cells Treated with Osteosarcoma-Derived Extracellular Vesicles
Published on: February 1, 2020
DNA methylation analysis identifies key transcription factors involved in mesenchymal stem cell osteogenic
Rodolfo Gómez1, Matt J Barter2, Ana Alonso-Pérez3
1Musculoskeletal Pathology Group, Institute IDIS, Santiago University Clinical Hospital, Laboratorio 18, Edificio B, Planta -2, 15706, Santiago de Compostela, Spain. rodolfo.gomez.bahamonde@sergas.es.
Background:
Knowledge about regulating transcription factors (TFs) for osteoblastogenesis from mesenchymal stem cells (MSCs) is limited. Therefore, we investigated the relationship between genomic regions subject to DNA-methylation changes during osteoblastogenesis and the TFs known to directly interact with these regulatory regions.
Results:
The genome-wide DNA-methylation signature of MSCs differentiated to osteoblasts and adipocytes was determined using the Illumina HumanMethylation450 BeadChip array. During adipogenesis no CpGs passed our test for significant methylation changes. Oppositely, during osteoblastogenesis we identified 2462 differently significantly methylated CpGs (adj. p < 0.05). These resided outside of CpGs islands and were significantly enriched in enhancer regions. We confirmed the correlation between DNA-methylation and gene expression. Accordingly, we developed a bioinformatic tool to analyse differentially methylated regions and the TFs interacting with them. By overlaying our osteoblastogenesis differentially methylated regions with ENCODE TF ChIP-seq data we obtained a set of candidate TFs associated to DNA-methylation changes. Among them, ZEB1 TF was highly related with DNA-methylation. Using RNA interference, we confirmed that ZEB1, and ZEB2, played a key role in adipogenesis and osteoblastogenesis processes. For clinical relevance, ZEB1 mRNA expression in human bone samples was evaluated. This expression positively correlated with weight, body mass index, and PPARγ expression.
Conclusions:
In this work we describe an osteoblastogenesis-associated DNA-methylation profile and, using these data, validate a novel computational tool to identify key TFs associated to age-related disease processes. By means of this tool we identified and confirmed ZEB TFs as mediators involved in the MSCs differentiation to osteoblasts and adipocytes, and obesity-related bone adiposity.
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