异质性胸腺输出和稳态增殖如何塑造幼稚T细胞受体克隆丰度分布
How heterogeneous thymic output and homeostatic proliferation shape naive T cell receptor clone abundance distributions
摘要：
表达相同T细胞受体（TCR）序列的T细胞组代表T细胞克隆。生物体中不同初始T细胞克隆的数量反映了胸腺中T细胞发育期间由V（D）J基因区段重组产生的不同T细胞受体（TCR）的数量。TCR多样性，更具体地说，克隆丰度分布是免疫功能的重要因素。特异性重组模式比其他重组模式更频繁地发生，而已知TCR与自身抗原之间的后续相互作用会触发增殖并维持初始T细胞存活。这些过程是TCR依赖性的，导致克隆依赖性胸腺输出和幼稚T细胞增殖率。使用平均场近似的解决方案的一个受管制的出生-死亡-移民模型和修改所产生的采样，我们系统地量化如何TCR依赖的异质性移民和增殖率影响的形状的克隆丰度分布（不同的克隆的数量，由一个特定数量的细胞，或“克隆计数”）。通过比较来自我们的异质性出生-死亡-移民模型的预测克隆计数与实验采样的克隆丰度，我们表明，虽然移民率的异质性导致预测克隆计数的变化很小，显着的异质性增殖率是必要的，以产生观察到的丰度与合理的生理参数值。我们的分析提供了生理参数之间的约束，这些参数是产生定性匹配数据的预测所必需的。模型的假设和潜在的其他重要的机械因素进行了讨论。
英文摘要：
The set of T cells that express the same T cell receptor (TCR) sequence represents a T cell clone. The number of different naive T cell clones in an organism reflects the number of different T cell receptors (TCRs) arising from recombination of the V(D)J gene segments during T cell development in the thymus. TCR diversity and more specifically, the clone abundance distribution is an important factor in immune function. Specific recombination patterns occur more frequently than others while subsequent interactions between TCRs and self-antigens are known to trigger proliferation and sustain naive T cell survival. These processes are TCR-dependent, leading to clone-dependent thymic export and naive T cell proliferation rates. Using a mean-field approximation to the solution of a regulated birth-death-immigration model and a modification arising from sampling, we systematically quantify how TCR-dependent heterogeneities in immigration and proliferation rates affect the shape of clone abundance distributions (the number of different clones that are represented by a specific number of cells, or "clone counts"). By comparing predicted clone counts derived from our heterogeneous birth-death-immigration model with experimentally sampled clone abundances, we show that although heterogeneity in immigration rates causes very little change to predicted clone-counts, significant heterogeneity in proliferation rates is necessary to generate the observed abundances with reasonable physiological parameter values. Our analysis provides constraints among physiological parameters that are necessary to yield predictions that qualitatively match the data. Assumptions of the model and potentially other important mechanistic factors are discussed.
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