Cai Jingyi, Li Chaoyuan, Li Shun, Yi Jianru, Wang Jun, Yao Ke, Gan Xinyan, Shen Yu, Yang Pu, Jing Dian, Zhao Zhihe
State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Department of Oral Implantology, Shanghai Engineering Research Center of Tooth Restoration and Regeneration, School and Hospital of Stomatology, Tongji University, Shanghai, China.
Front Bioeng Biotechnol. 2022 Mar 9;10:780211. doi: 10.3389/fbioe.2022.780211. eCollection 2022.
Mechanical force, being so ubiquitous that it is often taken for granted and overlooked, is now gaining the spotlight for reams of evidence corroborating their crucial roles in the living body. The bone, particularly, experiences manifold extraneous force like strain and compression, as well as intrinsic cues like fluid shear stress and physical properties of the microenvironment. Though sparkled in diversified background, long noncoding RNAs (lncRNAs) concerning the mechanotransduction process that bone undergoes are not yet detailed in a systematic way. Our principal goal in this research is to highlight the potential lncRNA-focused mechanical signaling systems which may be adapted by bone-related cells for biophysical environment response. Based on credible lists of force-sensitive mRNAs and miRNAs, we constructed a force-responsive competing endogenous RNA network for lncRNA identification. To elucidate the underlying mechanism, we then illustrated the possible crosstalk between lncRNAs and mRNAs as well as transcriptional factors and mapped lncRNAs to known signaling pathways involved in bone remodeling and mechanotransduction. Last, we developed combinative analysis between predicted and established lncRNAs, constructing a pathway-lncRNA network which suggests interactive relationships and new roles of known factors such as H19. In conclusion, our work provided a systematic quartet network analysis, uncovered candidate force-related lncRNAs, and highlighted both the upstream and downstream processes that are possibly involved. A new mode of bioinformatic analysis integrating sequencing data, literature retrieval, and computational algorithm was also introduced. Hopefully, our work would provide a moment of clarity against the multiplicity and complexity of the lncRNA world confronting mechanical input.
机械力无处不在，常常被人们视为理所当然而被忽视，但现在，大量证据证实了它们在生物体内的关键作用，这使得机械力备受关注。特别是骨骼，它会受到多种外力作用，如应变和压缩，以及一些内在因素，如流体剪切应力和微环境的物理特性。尽管在多样化的背景下受到关注，但关于骨骼所经历的机械转导过程的长链非编码RNA（lncRNA）尚未得到系统的详细阐述。我们这项研究的主要目标是突出潜在的以lncRNA为重点的机械信号系统，骨骼相关细胞可能会利用这些系统来响应生物物理环境。基于可靠的力敏感mRNA和miRNA列表，我们构建了一个用于lncRNA识别的力响应竞争性内源性RNA网络。为了阐明潜在机制，我们随后阐述了lncRNA与mRNA以及转录因子之间可能的相互作用，并将lncRNA映射到参与骨重塑和机械转导的已知信号通路。最后，我们对预测的lncRNA和已确定的lncRNA进行了联合分析，构建了一个通路 - lncRNA网络，该网络揭示了诸如H19等已知因子的相互作用关系和新作用。总之，我们的工作提供了一个系统的四重网络分析，发现了与力相关的候选lncRNA，并突出了可能涉及的上游和下游过程。我们还引入了一种整合测序数据、文献检索和计算算法的生物信息学分析新模式。希望我们的工作能为应对机械输入时lncRNA世界的多样性和复杂性带来一丝清晰。
