BACKGROUND: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSION: 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. Published by Elsevier Inc.
BACKGROUND: 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. MATERIALS AND METHODS: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. RESULTS: 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. CONCLUSION: 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. Published by Elsevier Inc.
Authors: Michael T McManus; Brian B Haines; Christopher P Dillon; Charles E Whitehurst; Luk van Parijs; Jianzhu Chen; Phillip A Sharp Journal: J Immunol Date: 2002-11-15 Impact factor: 5.422
Authors: He Li; Xin Li; Stanley E Smerin; Lei Zhang; Min Jia; Guoqiang Xing; Yan A Su; Jillian Wen; David Benedek; Robert Ursano Journal: Front Neurol Date: 2014-09-23 Impact factor: 4.003