Systems Biology of Protein and Phenotypic Evolution

项目总结/摘要 进化系统生物学中一个重要且目前尚未解决的挑战是 描述生物组织的不同层次之间的机制和相互作用 塑造蛋白质、细胞网络和表型的进化。我们的实验室已经 对理解进化与系统和细胞生物学之间的相互关系感兴趣 十几年来我们以前进行了计算和实验分析 探索多层次组织的演变过程。在本提案中，我们将 整合蛋白质、网络、细胞和表型尺度上的约束和影响， 建立一个描述蛋白质进化的综合定量框架。我们将使用一个 结合计算和实验的方法来追求这些基本的科学问题 全球蛋白质适应度景观如何影响蛋白质的短期和长期模式 进化？细胞网络的结构和功能如何影响蛋白质的进化 变更？细胞类型和组织特异性限制对蛋白质进化的作用是什么？如何 蛋白质组库的进化是否会影响所观察到的表型突变的模式和速率？ 进化？因为生物系统不仅限制，而且本身也是 探索上述主题也将使我们能够解决重要的生物学问题。 问题.例如，如何以及在何种程度上蛋白质表达水平和效率， 蛋白质功能在进化中得到优化，以及细胞网络的变化如何推动 微生物表型进化除了了解基本的生物学问题， 提案结果将对生物医学产生重要影响。具体而言，他们将允许 更好地理解和预测基因突变对蛋白质功能的定量影响， 细胞网络，不同的细胞类型和发育阶段，并最终对物种的 表型

Project Summary/Abstract An important and currently unsolved challenge in evolutionary systems biology is to describe how the mechanisms and interactions between different levels of biological organization shape the evolution of proteins, cellular networks, and phenotypes. Our laboratory has been interested in understanding the inter-relationships between evolution and systems and cell biology for more than a decade. We have previously carried out computational and experimental analyses exploring evolutionary processes at multiple levels of organization. In this proposal we will integrate constraints and effects at the protein, network, cellular, and phenotypic scales, towards developing an integrated and quantitative framework describing protein evolution. We will use a combined computational-experimental approach to pursue such fundamental scientific questions as: How do global protein fitness landscapes affect short- and long-term patterns of protein evolution? How do the structure and function of cellular networks affect protein evolutionary changes? What is the role of cell type- and tissue-specific constraints on protein evolution? How does the evolution of protein repertoires influence the observed patterns and rates of phenotypic evolution? Because biological systems not only constrain, but are also themselves the products of evolution, exploring the aforementioned topics will also allow us to address important biological questions. For example, how and to what extent protein expression levels and the efficiency of protein function are optimized in evolution, and how changes in cellular networks may drive microbial phenotypic evolution. In addition to understanding fundamental biological questions, proposal results will have important implications for biomedicine. Specifically, they will allow to better understand and predict the quantitative effects of genetic mutations on protein function, cellular networks, diverse cell types and developmental stages, and ultimately on species’ phenotypes.