Department of Hand Surgery, Affiliated Hospital of Nantong University, Nantong, Jiangsu, China.
Department of Anatomy, Medical School, Nantong University, Nantong, Jiangsu, China.
Biosci Rep. 2020 Jun 26;40(6). doi: 10.1042/BSR20191547.
Modulation of tendon healing remains a challenge because of our limited understanding of the tendon repair process. Therefore, we performed the present study to provide a global perspective of the gene expression profiles of tendons after injury and identify the molecular signals driving the tendon repair process.
The gene expression profiles of flexor digitorum profundus tendons in a chicken model were assayed on day 3, weeks 1, 2, 4, and 6 after injury using the Affymetrix microarray system. Principal component analysis (PCA) and hierarchical cluster analysis of the differentially expressed genes showed three distinct clusters corresponding to different phases of the tendon healing period. Gene ontology (GO) analysis identified regulation of cell proliferation and cell adhesion as the most enriched biological processes. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis revealed that the cytokine-cytokine receptor interaction and extracellular matrix (ECM)-receptor interaction pathways were the most impacted. Weighted gene co-expression network analysis (WGCNA) demonstrated four distinct patterns of gene expressions during tendon healing. Cell adhesion and ECM activities were mainly associated with genes with drastic increase in expression 6 weeks after injury. The protein-protein interaction (PPI) networks were constructed to identify the key signaling pathways and hub genes involved.
The comprehensive analysis of the biological functions and interactions of the genes differentially expressed during tendon healing provides a valuable resource to understand the molecular mechanisms underlying tendon healing and to predict regulatory targets for the genetic engineering of tendon repair. Tendon healing, Adhesion, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Weighted Gene Co-expression Network Analysis, Protein-protein Interaction.
由于我们对肌腱修复过程的了解有限，因此肌腱愈合的调节仍然是一个挑战。因此，我们进行了本研究，以提供肌腱损伤后基因表达谱的全局视角，并确定驱动肌腱修复过程的分子信号。
使用 Affymetrix 微阵列系统检测鸡模型屈肌腱在损伤后第 3 天、第 1、2、4 和 6 周的基因表达谱。差异表达基因的主成分分析（PCA）和层次聚类分析显示，三个不同的聚类对应于肌腱愈合期的不同阶段。基因本体论（GO）分析确定了细胞增殖和细胞黏附的调节作为最丰富的生物学过程。京都基因与基因组百科全书（KEGG）通路分析显示细胞因子-细胞因子受体相互作用和细胞外基质（ECM）-受体相互作用途径受影响最大。加权基因共表达网络分析（WGCNA）显示肌腱愈合过程中存在四种不同的基因表达模式。细胞黏附和 ECM 活性主要与 6 周后表达急剧增加的基因相关。构建蛋白质-蛋白质相互作用（PPI）网络以鉴定涉及的关键信号通路和枢纽基因。
对肌腱愈合过程中差异表达基因的生物学功能和相互作用的综合分析为理解肌腱愈合的分子机制以及预测肌腱修复的遗传工程调控靶点提供了有价值的资源。
肌腱愈合；黏附；基因本体论；京都基因与基因组百科全书；加权基因共表达网络分析；蛋白质-蛋白质相互作用。
