Individual cells in a solution display variable uptake of nanomaterials, peptides, and nutrients. Such variability reflects their heterogeneity in endocytic capacity. In a recent work, we have shown that the endocytic capacity of a cell depends on its size and surface density of endocytic components (transporters). We also demonstrated that in MDA-MB-231 breast cancer cells, the cell-surface transporter density (n) may decay with cell radius (r) following the power rule n ∼ rα, where α ≈ -1. In this work, we investigate how n and r may independently contribute to the endocytic heterogeneity of a cell population. Our analysis indicates that the smaller cells display more heterogeneity because of the higher stochastic variations in n. By contrast, the larger cells display a more uniform uptake, reflecting less-stochastic variations in n. We provide analyses of these dependencies by establishing a stochastic model. Our analysis reveals that the exponent α in the above relationship is not a constant; rather, it is a random variable whose distribution depends on cell size r. Using Bayesian analysis, we characterize the cell-size-dependent distributions of α that accurately capture the particle uptake heterogeneity of MDA-MB-231 cells.

中文翻译：

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使用贝叶斯分析剖析细胞群中的粒子摄取异质性

溶液中的单个细胞显示出对纳米材料、肽和营养物质的不同吸收。这种可变性反映了它们内吞能力的异质性。在最近的一项工作中，我们已经表明细胞的内吞能力取决于其内吞成分（转运蛋白）的大小和表面密度。我们还证明，在 MDA-MB-231 乳腺癌细胞中，细胞表面转运蛋白密度 (n) 可能会按照幂律 n ∼ rα 随细胞半径 (r) 衰减，其中 α ≈ -1。在这项工作中，我们研究了 n 和 r 如何独立地影响细胞群的内吞异质性。我们的分析表明，由于 n 的随机变化较高，较小的细胞显示出更多的异质性。相比之下，较大的细胞显示出更均匀的吸收，反映了 n 的随机变化较小。我们通过建立随机模型来分析这些依赖关系。我们的分析表明，上述关系中的指数 α 不是常数；相反，它是一个随机变量，其分布取决于像元大小 r。使用贝叶斯分析，我们表征了 α 的细胞大小依赖性分布，该分布可准确捕获 MDA-MB-231 细胞的颗粒摄取异质性。