Feedback regulation of proliferation vs. differentiation rates explains the dependence of CD4 T-cell expansion on precursor number
Feedback regulation of proliferation vs. differentiation rates explains the dependence of CD4 T-cell expansion on precursor number
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DOI：
10.1073/pnas.1019706108
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发表时间：
2011-02-22
影响因子：
11.1
通讯作者：
Grossman, Zvi
中科院分区：
文献类型：
--
作者：
Bocharov, Gennady;Quiel, Juan;Grossman, Zvi
调节免疫应答中T细胞克隆扩增和收缩的机制仍有待确定。最近的一项研究确定，在CD 4 T细胞前体数量（PN）和扩增因子（FE）之间存在对数线性关系，在每只小鼠3- 30，000个前体的范围内，斜率接近-0.5。结果表明，抑制前体扩增的竞争，为特定的抗原呈递细胞或其他抗原特异性细胞在相同的微环境中的行动，作为最可能的解释。几种分子机制可能占这种抑制进行了检查和拒绝。在这里，我们采用了以前提出的概念，“反馈调节生长和分化的平衡”，并表明它可以解释所观察到的结果。我们假设，最分化的效应细胞（或记忆细胞）限制生长分化程度较低的效应细胞，局部，通过增加后者的细胞的分化率在剂量依赖性的方式。因此，在依赖于初始PN的延迟之后，扩展被阻止和逆转，这说明了响应的峰值对该数字的依赖性。我们提出了一个简约的数学模型，能够再现免疫反应动力学。模型定义部分是通过要求与可用的BrdU标记和羧基荧光素二乙酸琥珀酰亚胺酯（CFSE）稀释数据的一致性来实现的。校准模型正确预测FE作为PN的函数。我们的结论是，反馈调节平衡的生长和分化，虽然等待明确的实验表征的假设细胞和分子参与调控，可以解释的动力学的CD 4 T细胞抗原刺激的反应。
The mechanisms regulating clonal expansion and contraction of T cells in response to immunization remain to be identified. A recent study established that there was a log-linear relation between CD4 T-cell precursor number (PN) and factor of expansion (FE), with a slope of similar to-0.5 over a range of 3-30,000 precursors per mouse. The results suggested inhibition of precursor expansion either by competition for specific antigen-presenting cells or by the action of other antigen-specific cells in the same microenvironment as the most likely explanation. Several molecular mechanisms potentially accounting for such inhibition were examined and rejected. Here we adopt a previously proposed concept, "feedback-regulated balance of growth and differentiation," and show that it can explain the observed findings. We assume that the most differentiated effectors (or memory cells) limit the growth of less differentiated effectors, locally, by increasing the rate of differentiation of the latter cells in a dose-dependent manner. Consequently, expansion is blocked and reversed after a delay that depends on initial PN, accounting for the dependence of the peak of the response on that number. We present a parsimonious mathematical model capable of reproducing immunization response kinetics. Model definition is achieved in part by requiring consistency with available BrdU-labeling and carboxyfluorescein diacetate succinimidyl ester (CFSE)-dilution data. The calibrated model correctly predicts FE as a function of PN. We conclude that feedback-regulated balance of growth and differentiation, although awaiting definite experimental characterization of the hypothetical cells and molecules involved in regulation, can explain the kinetics of CD4 T-cell responses to antigenic stimulation.