Department of Mathematics, University of Utah, Salt Lake City, Utah 84112, USA.
Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, South Bend, Indiana 46556, USA.
Phys Rev Lett. 2020 Jul 3;125(1):018102. doi: 10.1103/PhysRevLett.125.018102.
Many types of cells require the ability to pinpoint the location of an external stimulus from the arrival of diffusing signaling molecules at cell-surface receptors. How does the organization (number and spatial configuration) of these receptors shape the limit of a cell's ability to infer the source location? In the idealized scenario of a spherical cell, we apply asymptotic analysis to compute splitting probabilities between individual receptors and formulate an information-theoretic framework to quantify the role of receptor organization. Clustered configurations of receptors provide an advantage in detecting sources aligned with the clusters, suggesting a possible multiscale mechanism for single-cell source inference.
许多类型的细胞需要能够从扩散信号分子到达细胞表面受体的位置来精确定位外部刺激。这些受体的组织（数量和空间配置）如何影响细胞推断源位置的能力极限？在球形细胞的理想化情况下，我们应用渐近分析来计算单个受体之间的分裂概率，并制定信息论框架来量化受体组织的作用。受体的聚类配置为检测与聚类对齐的源提供了优势，这表明单细胞源推断可能存在一种多尺度机制。
