Constructing gene-regulatory networks to reveal the metabolic basis of lifespan i

构建基因调控网络揭示寿命的代谢基础

• 批准号: 8721828
• 负责人: JOHN L HARTMAN
• 金额: $ 37.64万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2017-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8721828
• 关键词: Accounting; Address; Affect; Age Factors; Aging; Aging-Related Process; Alleles; Amino Acids; Biochemical; Biological; Biological Assay; Biology of Aging; Caloric Restriction; Cell Aging; Cells; Collection; Computing Methodologies; Consensus; DNA Sequence; Data; Data Analyses; Data Quality; Environmental Risk Factor; Essential Amino Acids; Essential Genes; Etiology; Future; Gene Deletion; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genes; Genetic; Genetic Determinism; Genetic Variation; Genome; Genomics; Genotype; Glucose; Haploidy; Health; Hydrogen Sulfide; Individual; Knock-out; Laboratories; Laboratory Research; Libraries; Longevity; Mass Spectrum Analysis; Measurement; Measures; Messenger RNA; Metabolic; Metabolic Pathway; Metabolism; Methionine; Methods; Mitotic; Modeling; Monitor; Pathway Analysis; Pathway interactions; Phase; Phenotype; Production; Proteomics; Regulation; Regulator Genes; Reporting; Research; Research Infrastructure; Resources; Robotics; Saccharomyces cerevisiae; Saccharomycetales; Sulfur; Sulfur Metabolism Pathway; Survivors; System; Systems Biology; Techniques; Technology; Testing; Variant; Yeasts; aging gene; base; cell type; data integration; dietary restriction; environmental intervention; gene environment interaction; gene function; genome-wide; genome-wide analysis; high throughput technology; insight; interdisciplinary collaboration; longevity gene; metabolomics; mutant; novel; phenomics; programs; reconstruction; response; skills; theories; trait; transcriptomics; trend; yeast genetics

DESCRIPTION (provided by applicant): S. cerevisiae has been a useful model of aging for post-mitotic cells. This survival non-dividing, quiescent but metabolically active cells, is termed chronological lifespan (CLS). Several genome-scale CLS screens have reported abundant CLS-determining genes in recent years; thus, there are thought to be hundreds of genetic determinants of CLS. What is needed now is a way to understand how so many genes function together to regulate the aging process. However, there are difficulties in achieving such insight due to lack of consensus about the primary players, since different screens have not reached the same results. It remains obscure why some genes do not give reproducible phenotypes, and often this can be the case even within the same laboratory. Our research group assembles complementary skills and technologies to address this CLS quandary by an approach we call constructing "data-driven networks". We have developed an enabling technology for data driven analysis: it is called quantitative high throughput cell array phenotyping (Q-HTCP), and it increases the capacity to directly measure CLS phenotypes of clonal cultures by several hundred fold over existing technologies. We wish to apply Q-HTCP to systematically and quantitatively assess CLS in all 6000 mutant knockouts of non-essential genes and knockdowns of essential genes in haploid yeast growing, as well as in an outbred model for CLS, consisting of much more genetically heterogeneous strains. We will perform CLS under variable environmental conditions know to influence CLS. These 'perturbations' will include variable glucose concentration, a well-known effecter of CLS, but also inputs to the sulfur metabolic pathways (SMP). Additionally, we have found aeration to influence CLS and suspect that it interacts with other environmental, as well as genetic factors. SMP are required for production of the essential amino acid methionine, for which dietary restriction has been shown to extend life span even in the absence of caloric restriction. In the first use of Q-HTCP for a genome-wide CLS screen, we identified 363 out of 4750 gene deletion strains to reproducibly (2 of 2 cultures) have longer survival than the reference control strain. Lending confidence to our result were the smooth trends of separation of long survivors from the wild type, and the high correlation in CLS survival curves between replicate cultures. Among our most confident 363 hits, only 69 overlapped with the top 300 of at least one of three other genome screens; 14 overlapped with two of the three, and none overlapped with all three. Our result confirms a lack of consensus about CLS determining genes, since our screen was in accord about equally with all of the other three screens. The CLS data quality strongly validated the utility of Q-HTCP for yeast aging research, and so we have assembled an interdisciplinary team including expertise in Q-HTCP, SMP, CLS, transcriptomics, metabolimics and construction of biological networks from large-scale omic data integration. Through interdisciplinary collaboration, we aim to deliver a systems level framework for CLS to help construct gene regulatory networks that can reveal mechanisms of cellular aging.

描述（由申请人提供）：酿酒酵母已成为有丝分裂后细胞衰老的有用模型。这种生存非分裂的，静止但代谢活性细胞被称为 年代寿命（CLS）。近年来，几个基因组尺度的CLS筛选报告了CLS确定的基因丰富。因此，人们认为CLS的遗传决定因素数百个。现在需要的是一种理解这么多基因如何共同起作用以调节衰老过程的方法。但是，由于对主要参与者的共识缺乏共识，因此很难获得这种见解，因为不同的屏幕没有达到相同的结果。为什么某些基因不给出可重复的表型，这仍然是晦涩的，即使在同一实验室中，通常也是如此。我们的研究小组组装了互补的技能和技术，通过我们称为构建“数据驱动网络”的方法来解决这一问题。我们已经开发了一种用于数据驱动分析的能力技术：它称为定量高吞吐量细胞阵列表型（Q-HTCP），它增加了直接测量克隆培养物的CLS表型的能力，而不是现有技术的数百倍。我们希望将Q-HTCP应用于所有6000个非必需基因的突变敲除中的CLS，并在单倍体酵母生长中的基本基因的敲除以及CLS的杂种模型中，由遗传性异构菌株组成。我们将在可变的环境条件下执行CLS，以影响CLS。这些“扰动”将包括可变的葡萄糖浓度，这是CLS的众所周知效应剂，也包括对硫代谢途径（SMP）的输入。此外，我们发现曝气会影响CLS，并怀疑它与其他环境和遗传因素相互作用。 SMP是生产必需氨基酸蛋氨酸所必需的，即使在没有热量限制的情况下，饮食限制也可以延长寿命。在首次将Q-HTCP用于全基因组CLS筛选中，我们发现4750个基因缺失菌株中有363个可重复地（2种培养物中的2种）比参考控制菌株更长。对我们结果的贷款是长期存活者与野生型分离的平稳趋势，以及在复制培养物之间的CLS存活曲线中的高相关性。在我们最自信的363次命中中，只有69个与其他三个基因组屏幕中的至少一个中的前300个重叠； 14与三个中的两个重叠，没有三个重叠。我们的结果证实了关于CLS确定基因的共识，因为我们的屏幕与其他所有三个屏幕都相同。 CLS数据质量强烈验证了Q-HTCP对酵母老化研究的实用性，因此我们组装了一个跨学科团队，其中包括Q-HTCP，SMP，CLS，CLS，转录组学，代谢和从大型OMIC数据集成的生物网络构建的专业知识。通过跨学科的合作，我们旨在为CL提供一个系统级框架，以帮助构建可以揭示细胞衰老机制的基因调节网络。