A functional genomics analysis of central carbon metabolism evolution in yeasts

描述（由申请人提供）：细胞内的代谢过程产生所有细胞功能所需的能量和小分子构建模块，而中心碳代谢-控制能量来源的关键代谢模块-是这些过程的基石。尽管这一关键作用，我们对系统尺度上的中央碳代谢的功能和演变知之甚少。例如，呼吸发酵代谢状态（对数期酿酒酵母和许多癌细胞常见）是如何进化的，它的适应性优势是什么？在这个项目中，我们提出了一个比较实验和计算研究的功能，调节和进化的中心碳代谢在十三子囊菌门真菌跨越3亿年的进化。利用先进的代谢组学方法，我们将系统地测量代谢物的浓度和通量下的各种代谢和遗传扰动在每个物种。我们将把这些代谢谱与我们实验室在相同条件下收集的表达谱（在一个平行项目中）相结合，并确定每个物种中共变代谢物和基因的功能代谢模块。我们将使用一种新的计算方法来识别跨物种的正交模块，并重建它们的进化。进化重建将预测保守的功能实体以及代谢功能和调节的主要进化变化。我们将删除模型中所有相关物种的预测关键基因，并使用相同的代谢组学方法来分析它们的反应。由此产生的轮廓将验证我们的功能预测，并完善我们的进化重建。这种创新的比较代谢组学方法将为不同代谢策略的功能和演变提供见解，并为代谢系统的研究建立一种新的系统水平方法。从我们对酵母的分析中推断出的代谢进化和调节的广泛原则可以用于理解和模拟人类代谢。在我们的研究中存在两种人类病原体意味着我们的分析将导致对致病性的演变以及代谢在毒力，感染和治疗中的作用的更深入的了解。对代谢进化的深入了解也将有助于解释糖尿病和癌症等人类疾病中代谢的病理变化。了解这些现象，包括一些酵母和许多癌细胞常见的呼吸发酵生长状态，可能最终导致更好的诊断和治疗。

DESCRIPTION (provided by applicant): Metabolic processes within a cell produce the energy and small molecule building blocks necessary for all cellular functions, and central carbon metabolism - the key metabolic module governing energy sources - is the cornerstone of these processes. Despite this key role, we understand surprisingly little about the function and evolution of central carbon metabolism on a systems scale. For example, how did the respiro- fermentative metabolic state (common to log-phase Saccharomyces cerevisiae and to many cancer cells) evolve and what are its adaptive advantages? In this project we propose a comparative experimental and computational study of the function, regulation, and evolution of central carbon metabolism in thirteen Ascomycota fungi spanning 300 million years of evolution. Using advanced metabolomics methods, we will systematically measure metabolite concentrations and fluxes under a variety of metabolic and genetic perturbations in each species. We will integrate these metabolic profiles with expression profiles collected (in a parallel project) in our lab under the same conditions and identify functional metabolic modules of co- varying metabolites and genes in each species. We will use a novel computational approach to identify orthologous modules across species and reconstruct their evolution. The evolutionary reconstruction will predict conserved functional entities as well as major evolutionary changes in metabolic function and regulation. We will delete predicted key genes in all relevant species in our model and use the same metabolomics approach to profile their responses. The resulting profiles will validate our functional predictions and refine our evolutionary reconstruction. This innovative comparative metabolomic approach will provide insights into the function and evolution of distinct metabolic strategies and establish a new systems-level approach for the study of metabolic systems. Broad principles of metabolic evolution and regulation inferred from our analysis of yeast can be brought to bear on understanding and modeling human metabolism. The presence of two human pathogens in our study means our analysis will lead to a deeper understanding of the evolution of pathogenicity and the role of metabolism in virulence, infection, and treatment. Insights into metabolic evolution will also help to explain pathological changes in metabolism in human diseases, such as diabetes and cancer. Understanding these phenomena, includingthe respiro-fermentative growth states common to some yeasts and many cancer cells, may ultimately lead to better diagnostics and therapeutics.