Reconstruction of cellular variability from spatiotemporal patterns of Dictyostelium discoideum.

Christiane Hilgardt, Stefan C Müller, Marc-Thorsten Hütt
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Abstract

Variability in cell properties can be an important driving mechanism behind spatiotemporal patterns in biological systems, as the degree of cell-to-cell differences determines the capacity of cells to locally synchronize and, consequently, form patterns on a larger spatial scale. In principle, certain features of spatial patterns emerging with time may be regulated by variability or, more specifically, by certain constellations of cell-to-cell differences. Similarly, measuring variability in a system (i.e. the spatial distribution of cell-cell differences) may help predict properties of later-stage patterns.Here we apply and compare different statistical methods of extracting such systematic cell-to-cell differences in the case of patterns generated with a simple model system of an excitable medium and of experimental data by the slime mold Dictyostelium discoideum. We demonstrate with the help of a correlation analysis that these methods produce systematic (i.e. stationary) results for cell properties. Furthermore, we discuss possible applications of our method, in particular how these cell properties may serve as predictors of certain later-stage patterns.

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根据盘基竹荪的时空模式重建细胞变异性。
细胞特性的变异性可能是生物系统时空模式背后的一个重要驱动机制,因为细胞间差异的程度决定了细胞局部同步的能力,从而在更大的空间尺度上形成模式。原则上,随着时间推移而出现的空间模式的某些特征可能受到变异性的调节,或者更具体地说,受到细胞间差异的某些组合的调节。同样,测量一个系统中的变异性(即细胞间差异的空间分布)可能有助于预测后期模式的特性。在此,我们应用并比较了不同的统计方法,以提取这种系统性细胞间差异,并以可激发介质的简单模型系统和盘状粘菌的实验数据所产生的模式为例。我们通过相关性分析证明,这些方法能产生细胞特性的系统性(即静态)结果。此外,我们还讨论了我们的方法可能的应用,特别是这些细胞特性如何作为某些后期模式的预测因子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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