Dynamic protein interaction networks to map molecular origins of envronmental and genomic variations.

动态蛋白质相互作用网络可绘制环境和基因组变异的分子起源。

• 批准号: RGPIN-2021-03216
• 负责人: Michnick, Stephen
• 金额: $ 4.23万
• 依托单位: Université de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=742439
• 关键词: Dynamic; protein; interaction; networks; map

Problem and Hypotheses: The fate of an organisms is governed by its genome and the environment and the interactions of both with the biochemical networks that make up living cells. A surrogate measurement for the contributions of all biomolecules to cell fate can be found in the spatiotemporal dynamics of protein-protein interaction networks (PINS). We have developed methods to address the dynamics of PINS on a whole proteome scale in the budding yeast Saccharomyces cerevisiae by means of a Protein-fragment Complementation Assay (PCA) using a methotrexate-resistant the enzyme Dihydrofolate Reductase (DHFR) as reporter (Tarassov, et al. Science, 2008; Stynen, Abd Rabbo, et al., Cell, 2018). Surprisingly, we also observed a remarkable overlap between the proteins that respond to drug treatments and human homologues that have been found in genome-wide association studies (GWAS) associated with human disease, suggesting that PCA can link environmental and genomic variation effects to mechanistic consequences. Our central hypothesis is that the dynamics of PINS will accurately capture the biochemical-mechanistic effects of environmental stimuli and genetic variation. At what scale i.e. how many PCA reporters are needed to make accurate predictions of environmental or single nucleotide polymorphisms (SNP) on biochemical mechanisms? To address this question, we will perform two studies: in the short term we will cross PCA containing strains with existing outbred laboratory strains (Sen & Jarosz, Cell, 2018) to establish a benchmark for SNP resolution at which we can predict mechanistic effects from PINs. Second, in the medium term we will implement a new strategy to perform whole protein interactomes in a single test. This massive simplification of DHFR PCA screening will permit us to perform interactomes on large numbers of outbred strains and under a variety of different environmental conditions and to address a variety of fundamental questions in molecular genetics. Objectives: We will ask the following questions: 1 - How is genetic variation reflected in changes in PINs? 2 - How do genetic variation and environmental stress synergize on the structure of the PIN? 3 - At what SNP resolution do PINs resolve genomic effects on biochemical processes? 4-How much are variations in genes or environment reflected in the organization of the PINs, including among orthologs, at hubs and clusters within the network? 5-Can we predict genomic variation associated with human diseases from yeast PIN variation caused by gene and environment effects? These studies will contribute to advancement of knowledge by: 1- Providing a new strategy to directly probe the dynamics of an entire protein interactome. 2 - Revealing principles and mechanisms of dynamic biochemical network organization. 3 - Providing new insight into the principles of evolution of the cellular machinery. 4 - Providing insight into genome-environment interactions with molecular networks.

问题和假设：生物体的命运由其基因组和环境以及两者与构成活细胞的生化网络的相互作用决定。所有生物分子对细胞命运的贡献的替代测量可以在蛋白质-蛋白质相互作用网络 (PINS) 的时空动力学中找到。我们开发了方法，通过使用甲氨蝶呤抗性酶二氢叶酸还原酶 (DHFR) 作为报告基因（Tarassov，等人，《科学》，2008 年；Stynen、Abd Rabbo 等人，《细胞》，2018 年）。令人惊讶的是，我们还观察到对药物治疗有反应的蛋白质与在与人类疾病相关的全基因组关联研究（GWAS）中发现的人类同源物之间存在显着的重叠，这表明 PCA 可以将环境和基因组变异效应与机械后果联系起来。我们的中心假设是 PINS 的动力学将准确捕捉环境刺激和遗传变异的生化机械效应。需要多大的规模，即需要多少个 PCA 报告基因才能准确预测环境或多态性 (SNP) 对生化机制的影响？为了解决这个问题，我们将进行两项研究：短期内，我们将含有 PCA 的菌株与现有的远交实验室菌株进行杂交 (Sen & Jarosz, Cell, 2018)，以建立 SNP 分辨率的基准，在该基准上我们可以预测机械效应PIN 码。其次，从中期来看，我们将实施一种新策略，在一次测试中进行整个蛋白质相互作用组分析。 DHFR PCA 筛选的这种大规模简化将使我们能够在各种不同的环境条件下对大量远交菌株进行相互作用组分析，并解决分子遗传学中的各种基本问题。目标：我们将提出以下问题： 1 - PIN 的变化如何反映遗传变异？ 2 - 遗传变异和环境压力如何协同作用于 PIN 结构？ 3 - PIN 在什么 SNP 分辨率下可以解决基因组对生化过程的影响？ 4-PIN 的组织（包括直系同源之间、网络内的枢纽和集群）反映了多少基因或环境的变化？ 5-我们能否通过基因和环境影响引起的酵母PIN变异来预测与人类疾病相关的基因组变异？这些研究将通过以下方式促进知识的进步： 1-提供直接探测整个蛋白质相互作用组动态的新策略。 2 - 揭示动态生化网络组织的原理和机制。 3 - 提供对细胞机制进化原理的新见解。 4 - 提供对基因组-环境与分子网络相互作用的洞察。