Quantitative network signal combinations downstream of TCR activation can predict IL-2 production response
Quantitative network signal combinations downstream of TCR activation can predict IL-2 production response
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DOI：
10.4049/jimmunol.178.8.4984
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发表时间：
2007-04-15
影响因子：
4.4
通讯作者：
Lauffenburger, Douglas A.
中科院分区：
文献类型：
--
作者：
Kemp, Melissa L.;Wille, Lucia;Lauffenburger, Douglas A.
由tcr -肽/MHC （TCR-pMHC）结合激活的近端信号事件一直是当前研究的焦点，但了解随后的下游信号网络如何整合以控制最终的亲和力适当的TCRpNlHC T细胞反应仍然是下一个关键的挑战。我们假设，跨多种途径的关键下游网络信号的定量组合必须编码由TCR激活产生的信息，为能够解释和预测T细胞功能反应的定量模型提供基础。为此，我们在一组三种髓磷脂蛋白脂蛋白139-151改变的肽配体刺激的1B6 T细胞杂交瘤中，沿着10分钟至4小时的5个时间点，测量了6条下游通路上的11个蛋白质节点。根据该数据汇编生成的多元回归模型成功地理解了各种IL-2产生反应，并且成功地预测了对额外肽处理的先验反应，表明TCR结合信息在下游网络中被定量编码。单独的节点和/或时间点测量不能有效地解释IL-2反应，这表明信号必须跨多个途径动态集成，以充分表示编码的TCR信号信息。更重要的是，该模型还成功预测了MEK/ERK和PI3K/Akt通路的单独和联合抑制剂对T细胞反应的影响的先验直接实验测试。总之，我们的研究结果显示了TCR激活下游的多通路网络信号如何定量整合，将pMHC刺激转化为功能性细胞反应。
Proximal signaling events activated by TCR-peptide/MHC (TCR-pMHC) binding have been the focus of intense ongoing study, but understanding how the consequent downstream signaling networks integrate to govern ultimate avidity-appropriate TCRpNlHC T cell responses remains a crucial next challenge. We hypothesized that a quantitative combination of key downstream network signals across multiple pathways must encode the information generated by TCR activation, providing the basis for a quantitative model capable of interpreting and predicting T cell functional responses. To this end, we measured 11 protein nodes across six downstream pathways, along five time points from 10 min to 4 h, in a 1B6 T cell hybridoma stimulated by a set of three myelin proteolipid protein 139-151 altered peptide ligands. A multivariate regression model generated from this data compendium successfully comprehends the various IL-2 production responses and moreover successfully predicts a priori the response to an additional peptide treatment, demonstrating that TCR binding information is quantitatively encoded in the downstream network. Individual node and/or time point measurements less effectively accounted for the IL-2 responses, indicating that signals must be integrated dynamically across multiple pathways to adequately represent the encoded TCR signaling information. Of further importance, the model also successfully predicted a priori direct experimental tests of the effects of individual and combined inhibitors of the MEK/ERK and PI3K/Akt pathways on this T cell response. Together, our findings show how multipathway network signals downstream of TCR activation quantitatively integrate to translate pMHC stimuli into functional cell responses.