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Systems-level physiological basis of selection and epistasis in adaptation

适应中选择和上位的系统级生理基础

基本信息

批准号：
8073550
负责人：
Christopher J Marx
金额：
$ 27.95万
依托单位：
HARVARD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-07-10 至 2013-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8073550
关键词：
Address Affect Alleles Biochemical Pathway Biological Biological Models Code DNA Resequencing Data Development Disabled Persons Employee Strikes Engineering Environment Enzymes Evolution Feedback Future Generations Genetic Epistasis Genetic Materials Genome Growth Horizontal Gene Transfer Individual Kinetics Malignant Neoplasms Measures Metabolic Metabolic Control Metabolic Diseases Metabolic Pathway Metabolism Methanol Methylobacterium Modeling Mutate Mutation Natural Selections Organism Pathway Analysis Pathway interactions Performance Phenotype Physiological Physiology Population Probability Process Proteins Public Health Relative (related person)Research Personnel Role Staging System Systems Biology Testing Tumor Suppressor Genes Work base cancer cell cost enzyme activity experience fitness interest mathematical model microbial novel pathogen prognostic promoter research study

项目摘要

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.

描述（由申请人提供）：是否可以预测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结合来定量地解决适应的生理基础。我们的模型系统中，甲基杆菌的核心、重要且高度互连的代谢途径已被禁用，并被一种外来的、不相关的途径所取代。该工程系统的独特优势在于，这种替代会导致健康度、生长率和代谢通量降低 3 倍，产量降低 2.5 倍，并且中央代谢中心内通量的重新分配增加 30 倍。因为这种改变直接导致次优性能，我们假设这将在实验进化过程中将选择集中在该子系统上，以便适应将主要通过替代途径和/或其生理上相互作用的途径中的突变来进行。此外，我们建议，对该代谢子系统及其与代谢网络的连接的日益扩展和验证的数学模型将使我们能够对改变单个系统组件的活性以及酶之间的上位相互作用的适应性效果做出可测试的预测。我们的初步结果支持了我们的模型的预测以及适应将影响这个中央代谢中心的断言。我们的具体目标是 1.) 探索代谢模型选择的潜力，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群体，并检查整个适应过程中的表型和遗传变化，3.) 测试上位性在观察或合成的适应性轨迹中的作用。该项目的成果将是一个新颖的模型系统和概念框架，以应用全面的系统生物学方法来理解适应中选择和上位性的生理基础。它还代表了解决通过水平基因转移引入新遗传物质后发生的适应问题的机会。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、代谢疾病的建模到对具有突变癌基因和肿瘤抑制因子的癌细胞群的“适应性”命运的预后预测。