Genome replication in asynchronously growing microbial populations

Florian Pflug, Deepak Bhat, Simone Pigolotti
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Abstract

Biological cells adopt specific programs to replicate their genomes. Information about the replication program of an organism can be obtained by sequencing an exponentially growing cell culture and studying the frequency of DNA fragments as a function of genomic position. However, a quantitative interpretation of this data has been challenging for asynchronously growing cultures. In this paper, we introduce a general theory to predict the abundance of DNA fragments in asynchronously growing cultures from any given stochastic model of the DNA replication program. As key examples, we present stochastic models of DNA replication in Escherichia coli and in budding yeast. In both cases, our approach leads to analytical predictions that are in excellent agreement with experimental data and permit to infer biophysically relevant parameters. In particular, our method is able to infer the locations of known replication origins in budding yeast with high accuracy. These examples demonstrate that our method can provide insight into a broad range of organisms, from bacteria to eukaryotes.
非同步生长微生物群体的基因组复制
生物细胞采用特定的程序来复制它们的基因组。通过对呈指数增长的细胞培养物进行测序,并研究dna片段的频率与基因组位置的关系,可以获得有关生物体复制程序的信息。然而,对这些数据的定量解释对于异步生长的文化具有挑战性。在本文中,我们介绍了一个一般理论,以预测DNA复制程序的任意给定的随机模型中异步生长培养的DNA片段的丰度。作为关键的例子,我们提出了大肠杆菌和芽殖酵母DNA复制的随机模型。在这两种情况下,我们的方法导致与实验数据非常一致的分析预测,并允许推断生物物理相关参数。特别是,我们的方法能够以很高的准确性推断出出芽酵母中已知复制起源的位置。这些例子表明,我们的方法可以深入了解从细菌到真核生物的广泛生物。
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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