Department of Medicine and Nephrology, University of California, San Diego, La Jolla, California, USA.
J Surg Res. 2012 Jul;176(1):e41-6. doi: 10.1016/j.jss.2011.12.002. Epub 2011 Dec 22.
Systems biology is gaining importance in studying complex systems such as the functional interconnections of human genes [1]. To investigate the molecular interactions involved in T cell immune responses, we used databases of physical gene-gene interactions to constructed molecular interaction networks (interconnections) with R language algorithms. This helped to identify highly interconnected "hub" genes AT(1)P5C1, IL6ST, PRKCZ, MYC, FOS, JUN, and MAPK1. We hypothesized that suppression of these hub genes in the gene network would result in significant phenotypic effects on T cells and examined this in vitro. The molecular interaction networks were then analyzed and visualized with Cytoscape.
Jurkat and HeLa cells were transfected with siRNA for the selected hub genes. Cell proliferation was measured using ATP luminescence and BrdU labeling, which were measured 36, 72, and 96 h after activation.
Following T cell stimulation, we found a significant decrease in ATP production (P < 0.05) when the hub genes ATP5C1 and PRKCZ were knocked down using siRNA transfection, whereas no difference in ATP production was observed in siRNA transfected HeLa cells. However, HeLa cells showed a significant (P < 0.05) decrease in cell proliferation when the genes MAPK1, IL6ST, ATP5C1, JUN, and FOS were knocked down.
In both Jurkat and HeLa cells, targeted gene knockdown using siRNA showed decreased cell proliferation and ATP production in both Jurkat and HeLa cells. However, Jurkat T cells and HELA cells use different hub genes to regulate activation responses. This experiment provides proof of principle of applying siRNA knockdown of T cell hub genes to evaluate their proliferative capacity and ATP production. This novel concept outlines a systems biology approach to identify hub genes for targeted therapeutics.
系统生物学在研究复杂系统（如人类基因的功能相互关系）方面的重要性日益增加。为了研究 T 细胞免疫反应中的分子相互作用，我们使用物理基因-基因相互作用数据库，使用 R 语言算法构建分子相互作用网络（连接）。这有助于识别高度相互连接的“枢纽”基因 AT(1)P5C1、IL6ST、PRKCZ、MYC、FOS、JUN 和 MAPK1。我们假设抑制基因网络中的这些枢纽基因将对 T 细胞产生显著的表型影响，并在体外进行了研究。然后使用 Cytoscape 分析和可视化分子相互作用网络。
用选定的枢纽基因的 siRNA 转染 Jurkat 和 HeLa 细胞。在激活后 36、72 和 96 小时，通过 ATP 发光和 BrdU 标记测量细胞增殖。
在 T 细胞刺激后，当使用 siRNA 转染敲低枢纽基因 ATP5C1 和 PRKCZ 时，我们发现 ATP 产生显着减少（P <0.05），而在用 siRNA 转染的 HeLa 细胞中未观察到 ATP 产生的差异。然而，当基因 MAPK1、IL6ST、ATP5C1、JUN 和 FOS 被敲低时，HeLa 细胞的细胞增殖显着减少（P <0.05）。
在 Jurkat 和 HeLa 细胞中，使用 siRNA 进行靶向基因敲低均显示 Jurkat 和 HeLa 细胞中的细胞增殖和 ATP 产生减少。然而，Jurkat T 细胞和 HELA 细胞使用不同的枢纽基因来调节激活反应。该实验提供了使用 siRNA 敲低 T 细胞枢纽基因来评估其增殖能力和 ATP 产生的原理证明。这一新颖的概念概述了一种系统生物学方法，用于鉴定用于靶向治疗的枢纽基因。
