Systems-level physiological basis of selection and epistasis in adaptation

描述（由申请人提供）：是否有可能预测整个生物网络中选择和上位相互作用的潜力？在这里，我们建议通过实验和计算方法的整合，定量地解决适应的生理基础。我们的模型系统是其中甲基杆菌的中心的、必需的和高度相互关联的代谢途径已经被禁用并且被外来的、不相关的途径取代的系统。这种工程系统的独特优势在于，这种替换特别导致适应性、生长速率和代谢通量降低3倍，以及产量降低2.5倍和中央代谢中心内通量重新分布30倍。由于这种改变直接导致次优性能，我们假设这将集中在这个子系统在实验进化过程中的选择，使适应将在很大程度上通过突变的替代途径和/或那些它的生理相互作用。此外，我们建议，越来越多的扩展和验证的数学模型，这个代谢子系统及其连接的代谢网络将使我们能够测试的健身效果的预测，改变个别系统组件的活动，以及酶之间的上位相互作用。我们的初步结果支持我们的模型的预测和断言，适应将打击这个中央代谢枢纽。我们的具体目标是1）。探索利用代谢模型进行选择的潜力，并通过调节酶的表达水平直接测试预测，2.）进化祖先菌株的复制种群，并检查整个适应过程中的表型和遗传变化;测试上位性在观察或合成的自适应轨迹中的作用。该项目的结果将是一个新的模型系统和概念框架，应用全面的系统生物学方法来理解适应中的选择和上位性的生理基础。这也是通过水平基因转移引入新的遗传物质后解决适应问题的机会。我们预计，将选择和上位性纳入定量框架将对公共卫生产生影响，从病原体的适应，代谢疾病的建模，到具有突变癌基因和肿瘤抑制因子的癌细胞群体的“适应性”命运的预后预测。

DESCRIPTION (provided by applicant): Is it possible to predict both the potential for selection and epistatic interactions across a biological network? Here we propose to quantitatively address the physiological basis of adaptation through the integration of experimental and computational approaches. Our model system is one in which the central, essential and highly interconnected metabolic pathway of Methylobacterium has been disabled and replaced with a foreign, unrelated pathway. The unique advantage of this engineered system is that this replacement specifically results in a 3-fold reduction in fitness, growth rate and metabolic flux, as well as 2.5-fold lower yield and a 30-fold redistribution of flux within the central metabolic hub. Because this alteration directly causes sub-optimal performance, we hypothesize that this will focus selection upon this subsystem during experimental evolution such that adaptation will largely proceed through mutations in the substituted pathway and/or those that it physiologically interacts with. Furthermore, we suggest that increasingly extended and verified mathematical models of this metabolic subsystem and its connections to the metabolic network will allow us to make testable predictions of the fitness effects of altering the activity of individual system components, as well as epistatic interactions between enzymes. Our preliminary results support both our model's predictions and the assertion that adaptation will strike this central metabolic hub. Our specific aims are to 1.) explore the potential for selection with metabolic models and directly test predictions by modulating expression levels of enzymes, 2.) evolve replicate populations of the ancestral strain and examine phenotypic and genetic changes throughout the course of adaptation and 3.) test the role of epistasis in the adaptive trajectories observed or synthesized. The result of this project will be a novel model system and conceptual framework to apply a comprehensive, systems biology approach to understanding the physiological basis of selection and epistasis in adaptation. It also represents the opportunity to address adaptation occurring after introduction of new genetic material via horizontal gene transfer. We anticipate that placing selection and epistasis into a quantitative framework will have public health impacts ranging from the adaptation of pathogens, the modeling of metabolic diseases, to prognostic predictions of the 'adaptive' fate of a population of cancer cells with mutated oncogenes and tumor suppressors.