Collective gradient sensing with limited positional information
Collective gradient sensing with limited positional information
复制标题
具有有限位置信息的集体梯度感知
DOI：
10.1103/physreve.105.044410
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发表时间：
2022
影响因子：
2.4
通讯作者：
Camley, Brian A.
中科院分区：
文献类型：
--
作者：
Ipiña, Emiliano Perez;Camley, Brian A.
真核细胞通过感知化学梯度来决定何时何地移动。细胞簇可以通过整合跨簇进行的浓度测量来比单个细胞更准确地感测梯度。当小区对它们在集群内的位置具有有限的知识时，即，位置信息有限？我们采用最大似然估计研究梯度传感精度的一群细胞与有限的位置信息。如果细胞必须估计它们在集群内的位置，这会降低集体梯度感测的准确性。我们将我们的结果与拔河模型进行了比较，在拔河模型中，细胞通过极化远离它们的邻居而不依赖于它们的位置信息来响应梯度。随着细胞位置不确定性的增加，存在一种权衡，其中拔河模型更准确地响应化学梯度。然而，对于足够大的细胞簇或足够浅的化学梯度，即使位置不确定性很高，拔河模型也总是低于整合所有细胞信息的模型。
Eukaryotic cells sense chemical gradients to decide where and when to move. Clusters of cells can sense gradients more accurately than individual cells by integrating measurements of the concentration made across the cluster. Is this gradient-sensing accuracy impeded when cells have limited knowledge of their position within the cluster, i.e., limited positional information? We apply maximum likelihood estimation to study gradient-sensing accuracy of a cluster of cells with finite positional information. If cells must estimate their location within the cluster, this lowers the accuracy of collective gradient sensing. We compare our results with a tug-of-war model where cells respond to the gradient by polarizing away from their neighbors without relying on their positional information. As the cell positional uncertainty increases, there is a trade-off where the tug-of-war model responds more accurately to the chemical gradient. However, for sufficiently large cell clusters or sufficiently shallow chemical gradients, the tug-of-war model will always be suboptimal to one that integrates information from all cells, even if positional uncertainty is high.