Genotypic context modulates fitness landscapes: Effects on the speed and direction of evolution for antimicrobial resistance
Genotypic context modulates fitness landscapes: Effects on the speed and direction of evolution for antimicrobial resistance
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基因型环境调节适应性景观：对抗菌素耐药性进化速度和方向的影响
DOI：
10.1101/427328
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Eppstein, Margaret J.
中科院分区：
文献类型：
--
作者：
Ogbunugafor, Brandon C.;Guerrero, Rafael F.;Eppstein, Margaret J.
了解驱动适应性进化动态的力量是进化生物学中许多子领域的目标。适应度景观类比已成为解决许多系统中这些主题的有用抽象，最近的治疗揭示了不同的环境如何通过改变适应度景观的地形来构建适应性进化的细节。在这项研究中，我们研究了所建模的适应度景观所嵌入的更大的环境基因型背景如何影响适应度景观地形和随后的进化。通过对经验适应度景观的模拟，我们发现基因型环境（由所研究基因座之外的区域的遗传变异性定义）（在本例中是抗生素的重要细菌酶靶标），以几种令人惊讶的方式影响进化的速度和方向。这些发现对于我们如何研究自然界中耐药性的进化以及关于转基因生物体中如何发生生物进化的假设具有重要意义。更一般地说，这些发现涉及适应性进化中“差异如何产生差异”的理论：生物体之间微小的遗传差异可以极大地改变进化发生方式的细节，这甚至可以迅速推动即使是稍微不同的种群进一步疏远。作者摘要技术进步使科学家能够越来越轻松地在生物体基因组内的特定位点设计个体突变。这些突破为科学家提供了研究不同工程突变如何影响给定基因或蛋白质功能的工具，从而对基因型-表型作图和进化产生有用的见解。在这项研究中，我们使用工程细菌菌株来展示酶中耐药性进化的动态（速度和方向）如何取决于该细菌酶的物种类型，以及细菌基因组中其他基因是否存在突变。这些发现对公共卫生、基因工程和物种形成理论具有广泛的影响。在公共卫生和生物医学的背景下，我们的结果表明，未来管理抗菌药物耐药性的努力必须在预测耐药性如何发生之前考虑不同病原体种群的基因组成，而不是假设相同的耐药途径将出现在不同的病原体种群中。关于更广泛的进化生物学理论，我们的结果表明，即使生物体之间很小的遗传差异也可能改变未来进化的发生方式，可能导致密切相关的种群迅速分化。
Understanding the forces that drive the dynamics of adaptive evolution is a goal of many subfields within evolutionary biology. The fitness landscape analogy has served as a useful abstraction for addressing these topics across many systems, and recent treatments have revealed how different environments can frame the particulars of adaptive evolution by changing the topography of fitness landscapes. In this study, we examine how the larger, ambient genotypic context in which the fitness landscape being modeled is embedded affects fitness landscape topography and subsequent evolution. Using simulations on empirical fitness landscapes, we discover that genotypic context, defined by genetic variability in regions outside of the locus under study (in this case, an essential bacterial enzyme target of antibiotics), influences the speed and direction of evolution in several surprising ways. These findings have implications for how we study the evolution of drug resistance in nature, and for presumptions about how biological evolution might be expected to occur in genetically-modified organisms. More generally, the findings speak to theory surrounding how “difference can beget difference” in adaptive evolution: that small genetic differences between organisms can greatly alter the specifics of how evolution occurs, which can rapidly drive even slightly diverged populations further apart.Author summaryTechnological advances enable scientists to engineer individual mutations at specific sites within an organism’s genome with increasing ease. These breakthroughs have provided scientists with tools to study how different engineered mutations affect the function of a given gene or protein, yielding useful insight into genotype-phenotype mapping and evolution. In this study, we use engineered strains of bacteria to show how the dynamics (speed and direction) of evolution of drug resistance in an enzyme depends on the species-type of that bacterial enzyme, and on the presence/absence of mutations in other genes in the bacterial genome. These findings have broad implications for public health, genetic engineering, and theories of speciation. In the context of public health and biomedicine, our results suggest that future efforts in managing antimicrobial resistance must consider genetic makeup of different pathogen populations before predicting how resistance will occur, rather than assuming that the same resistance pathways will appear in different pathogen populations. With regard to broader theory in evolutionary biology, our results show how even small genetic differences between organisms can alter how future evolution occurs, potentially causing closely-related populations to quickly diverge.
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影响因子：
4.3
作者：
Nichol D;Jeavons P;Fletcher AG;Bonomo RA;Maini PK;Paul JL;Gatenby RA;Anderson AR;Scott JG
通讯作者：
Scott JG
影响因子：
1.6
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影响因子：
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适应度景观之间隐藏的随机性限制了逆向进化。
影响因子：
8.6
作者：
Tan,Longzhi;Serene,Stephen;Chao,HuiXiao;Gore,Jeff
通讯作者：
Gore,Jeff
影响因子：
4.5
作者：
Flynn KM;Cooper TF;Moore FB;Cooper VS
通讯作者：
Cooper VS