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Evolution of a Genome-Encoded Bias in Amino Acid Biosynthetic Pathways Is a Potential Indicator of Amino Acid Dynamics in the Environment

机译:氨基酸生物合成途径中基因组编码偏倚的进化是环境中氨基酸动力学的潜在指标

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Overcoming the stress of starvation is one of an organism’s most challenging phenotypic responses. Those organisms that frequently survive the challenge, by virtue of their fitness, will have evolved genomes that are shaped by their specific environments. Understanding this genotype–environment–phenotype relationship at a deep level will require quantitative predictive models of the complex molecular systems that link these aspects of an organism’s existence. Here, we treat one of the most fundamental molecular systems, protein synthesis, and the amino acid biosynthetic pathways involved in the stringent response to starvation. These systems face an inherent logical dilemma: Building an amino acid biosynthetic pathway to synthesize its product—the cognate amino acid of the pathway—may require that very amino acid when it is no longer available. To study this potential “catch-22,” we have created a generic model of amino acid biosynthesis in response to sudden starvation. Our mathematical analysis and computational results indicate that there are two distinctly different outcomes: Partial recovery to a new steady state, or full system failure. Moreover, the cell’s fate is dictated by the cognate bias, the number of cognate amino acids in the corresponding biosynthetic pathway relative to the average number of that amino acid in the proteome. We test these implications by analyzing the proteomes of over 1,800 sequenced microbes, which reveals statistically significant evidence of low cognate bias, a genetic trait that would avoid the biosynthetic quandary. Furthermore, these results suggest that the pattern of cognate bias, which is readily derived by genome sequencing, may provide evolutionary clues to an organism’s natural environment.
机译:克服饥饿的压力是生物体最具挑战性的表型反应之一。那些经常在挑战中幸存下来的生物,凭借其适应性,将进化出由其特定环境塑造的基因组。要想在深层次上理解这种基因型-环境-表型关系,就需要对连接生物体存在的这些方面的复杂分子系统进行定量预测模型。在这里,我们处理了最基本的分子系统之一,蛋白质合成,以及参与对饥饿的严格反应的氨基酸生物合成途径。这些系统面临着一个固有的逻辑困境:建立一个氨基酸生物合成途径来合成其产物——该途径的同源氨基酸——当它不再可用时,可能需要该氨基酸。为了研究这种潜在的“第22条军规”,我们创建了一个氨基酸生物合成的通用模型,以应对突然的饥饿。我们的数学分析和计算结果表明,存在两种截然不同的结果:部分恢复到新的稳定状态,或完全系统故障。此外,细胞的命运是由同源偏差决定的,即相应生物合成途径中同源氨基酸的数量相对于蛋白质组中该氨基酸的平均数量。我们通过分析超过1,800种测序微生物的蛋白质组来测试这些影响,这揭示了低同源偏倚的统计学显着证据,这是一种可以避免生物合成困境的遗传特征。此外,这些结果表明,通过基因组测序很容易得出的同源偏差模式可能为生物体的自然环境提供进化线索。

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