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Post-Translational Regulations of Transcriptional Activity of RUNX2.

ABSTRACT: Runt-related transcription factor 2 (RUNX2) is a key transcription factor for bone formation and osteoblast differentiation. Various signaling pathways and mechanisms that regulate the expression and transcriptional activity of RUNX2 have been thoroughly investigated since the involvement of RUNX2 was first reported in bone formation. As the regulation of Runx2 expression by extracellular signals has recently been reviewed, this review focuses on the regulation of post-translational RUNX2 activity. Transcriptional activity of RUNX2 is regulated at the post-translational level by various enzymes including kinases, acetyl transferases, deacetylases, ubiquitin E3 ligases, and prolyl isomerases. We describe a sequential and linear causality between post-translational modifications of RUNX2 by these enzymes. RUNX2 is one of the most important osteogenic transcription factors; however, it is not a suitable drug target. Here, we suggest enzymes that directly regulate the stability and/or transcriptional activity of RUNX2 at a post-translational level as effective drug targets for treating bone diseases.

SUBMITTER: Kim HJ

PROVIDER: S-EPMC7057842 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Post-Translational Regulations of Transcriptional Activity of RUNX2.

Kim Hyun-Jung HJ Kim Woo-Jin WJ Ryoo Hyun-Mo HM

Molecules and cells 20200201 2

Runt-related transcription factor 2 (RUNX2) is a key transcription factor for bone formation and osteoblast differentiation. Various signaling pathways and mechanisms that regulate the expression and transcriptional activity of RUNX2 have been thoroughly investigated since the involvement of RUNX2 was first reported in bone formation. As the regulation of Runx2 expression by extracellular signals has recently been reviewed, this review focuses on the regulation of post-translational RUNX2 activi ...[more]

PMID: 31878768

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Project description:Respiratory epithelial cells are the primary target of influenza virus infection in human. However, the molecular mechanisms of airway epithelial cell responses to viral infection are not fully understood. Revealing genome-wide transcriptional and post-transcriptional regulatory relationships can further advance our understanding of this problem, which motivates the development of novel and more efficient computational methods to simultaneously infer the transcriptional and post-transcriptional regulatory networks.Here we propose a novel framework named SITPR to investigate the interactions among transcription factors (TFs), microRNAs (miRNAs) and target genes. Briefly, a background regulatory network on a genome-wide scale (~23,000 nodes and ~370,000 potential interactions) is constructed from curated knowledge and algorithm predictions, to which the identification of transcriptional and post-transcriptional regulatory relationships is anchored. To reduce the dimension of the associated computing problem down to an affordable size, several topological and data-based approaches are used. Furthermore, we propose the constrained LASSO formulation and combine it with the dynamic Bayesian network (DBN) model to identify the activated regulatory relationships from time-course expression data. Our simulation studies on networks of different sizes suggest that the proposed framework can effectively determine the genuine regulations among TFs, miRNAs and target genes; also, we compare SITPR with several selected state-of-the-art algorithms to further evaluate its performance. By applying the SITPR framework to mRNA and miRNA expression data generated from human lung epithelial A549 cells in response to A/Mexico/InDRE4487/2009 (H1N1) virus infection, we are able to detect the activated transcriptional and post-transcriptional regulatory relationships as well as the significant regulatory motifs.Compared with other representative state-of-the-art algorithms, the proposed SITPR framework can more effectively identify the activated transcriptional and post-transcriptional regulations simultaneously from a given background network. The idea of SITPR is generally applicable to the analysis of gene regulatory networks in human cells. The results obtained for human respiratory epithelial cells suggest the importance of the transcriptional, post-transcriptional regulations as well as their synergies in the innate immune responses against IAV infection.

Dataset Information

Post-Translational Regulations of Transcriptional Activity of RUNX2.

Publications

Post-Translational Regulations of Transcriptional Activity of RUNX2.

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