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复杂条件下细菌启动子活性动力学的线性叠加与预测

Linear superposition and prediction of bacterial promoter activity dynamics in complex conditions.

作者信息

Rothschild Daphna, Dekel Erez, Hausser Jean, Bren Anat, Aidelberg Guy, Szekely Pablo, Alon Uri

机构信息

Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel.

出版信息

PLoS Comput Biol. 2014 May 8;10(5):e1003602. doi: 10.1371/journal.pcbi.1003602. eCollection 2014 May.

Abstract

Bacteria often face complex environments. We asked how gene expression in complex conditions relates to expression in simpler conditions. To address this, we obtained accurate promoter activity dynamical measurements on 94 genes in E. coli in environments made up of all possible combinations of four nutrients and stresses. We find that the dynamics across conditions is well described by two principal component curves specific to each promoter. As a result, the promoter activity dynamics in a combination of conditions is a weighted average of the dynamics in each condition alone. The weights tend to sum up to approximately one. This weighted-average property, called linear superposition, allows predicting the promoter activity dynamics in a combination of conditions based on measurements of pairs of conditions. If these findings apply more generally, they can vastly reduce the number of experiments needed to understand how E. coli responds to the combinatorially huge space of possible environments.

摘要

细菌常常面临复杂的环境。我们探究了复杂条件下的基因表达与较简单条件下的基因表达之间的关系。为解决这个问题,我们在由四种营养物质和压力的所有可能组合构成的环境中,对大肠杆菌中的94个基因进行了准确的启动子活性动态测量。我们发现,不同条件下的动态变化可以由每个启动子特有的两条主成分曲线很好地描述。因此,多种条件组合下的启动子活性动态是每种单独条件下动态的加权平均值。这些权重往往总和约为1。这种称为线性叠加的加权平均特性,使得基于成对条件的测量能够预测多种条件组合下的启动子活性动态。如果这些发现更具普遍性,那么它们可以大幅减少为了解大肠杆菌如何应对组合数量巨大的可能环境所需进行的实验数量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c7b/4014397/7784108b00d8/pcbi.1003602.g001.jpg

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