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细胞分裂时分子的随机分配。

Random partitioning of molecules at cell division.

机构信息

Department of Systems Biology, Harvard University, Boston, MA 02115, USA.

出版信息

Proc Natl Acad Sci U S A. 2011 Sep 6;108(36):15004-9. doi: 10.1073/pnas.1013171108. Epub 2011 Aug 22.

Abstract

Many RNAs, proteins, and organelles are present in such low numbers per cell that random segregation of individual copies causes large "partitioning errors" at cell division. Even symmetrically dividing cells can then by chance produce daughters with very different composition. The size of the errors depends on the segregation mechanism: Control systems can reduce low-abundance errors, but the segregation process can also be subject to upstream sources of randomness or spatial heterogeneities that create large errors despite high abundances. Here we mathematically demonstrate how partitioning errors arise for different types of segregation mechanisms and how errors can be greatly increased by upstream heterogeneity but remarkably hard to avoid through controlled partitioning. We also show that seemingly straightforward experiments cannot be straightforwardly interpreted because very different mechanisms produce identical fits and present an approach to deal with this problem by adding binomial counting noise and testing for convexity or concavity in the partitioning error as a function of the binomial thinning parameter. The results lay a conceptual groundwork for more effective studies of heterogeneity among growing and dividing cells, whether in microbes or in differentiating tissues.

摘要

许多 RNA、蛋白质和细胞器在细胞中的数量非常少,以至于单个拷贝的随机分配会在细胞分裂时导致较大的“分配错误”。即使是对称分裂的细胞也可能偶然产生组成非常不同的子细胞。错误的大小取决于分配机制:控制系统可以减少低丰度的错误,但分配过程也可能受到上游随机性或空间异质性的影响,尽管丰度很高,但仍会产生较大的错误。在这里,我们从数学上演示了不同类型的分配机制如何产生分配错误,以及上游异质性如何极大地增加错误,但通过受控分配却很难避免错误。我们还表明,看似简单的实验不能简单地解释,因为非常不同的机制会产生相同的拟合,并且提出了一种通过添加二项式计数噪声并测试分配错误作为二项式变薄参数的函数的凸性或凹性来处理此问题的方法。这些结果为更有效地研究生长和分裂细胞中的异质性奠定了概念基础,无论是在微生物还是分化组织中。

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