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Fisher's geometrical model and the mutational patterns of antibiotic resistance across dose gradients

机译:费舍尔的几何模型和剂量梯度抗生素抗性的突变模式

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Fisher's geometrical model (FGM) has been widely used to depict the fitness effects of mutations. It is a general model with few underlying assumptions that gives a large and comprehensive view of adaptive processes. It is thus attractive in several situations, for example adaptation to antibiotics, but comes with limitations, so that more mechanistic approaches are often preferred to interpret experimental data. It might be possible however to extend FGM assumptions to better account for mutational data. This is theoretically challenging in the context of antibiotic resistance because resistance mutations are assumed to be rare. In this article, we show with Escherichia coli how the fitness effects of resistance mutations screened at different doses of nalidixic acid vary across a dose-gradient. We found experimental patterns qualitatively consistent with the basic FGM (rate of resistance across doses, gamma distributed costs) but also unexpected patterns such as a decreasing mean cost of resistance with increasing screen dose. We show how different extensions involving mutational modules and variations in trait covariance across environments, can be discriminated based on these data. Overall, simple extensions of the FGM accounted well for complex mutational effects of resistance mutations across antibiotic doses.
机译:Fisher的几何模型(FGM)已被广泛用于描绘突变的健身效果。这是一种普遍模型,具有很少的潜在假设,它给出了对自适应过程的大而全面的观点。因此,在若干情况下具有吸引力,例如适应抗生素,但是充满了限制,从而通常优选更具机制方法来解释实验数据。然而,也可以扩展FGM假设以更好地解释突变数据。这在理论上是在抗生素抗性的背景下具有挑战性的,因为抗性突变被认为是罕见的。在本文中,我们展示了大肠杆菌,如何在不同剂量的水中筛选的抗性突变的健身效应在剂量梯度上变化。我们发现了与基本FGM定性一致的实验模式(剂量抗性率,伽马分布成本),但也是由于筛选剂量增加,诸如降低平均抗性成本的意外模式。我们展示了涉及突变模块的不同扩展和环境的特征协方差的变化,可以根据这些数据进行区分。总体而言,FGM的简单扩展占抗生素剂量的抗性突变的复杂突变效应。

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