Constructing gene-regulatory networks in yeast for a metabolic basis of lifespan

在酵母中构建基因调控网络作为寿命的代谢基础

基本信息

批准号：
8535594
负责人：
JOHN L HARTMAN
金额：
$ 36.07万
依托单位：
UNIVERSITY OF ALABAMA AT BIRMINGHAM
依托单位国家：
美国
项目类别：
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/8535594
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

项目摘要

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）：酿酒酵母是有丝分裂后细胞衰老的有用模型。这种存活的、不分裂、静止但代谢活跃的细胞被称为按时间顺序排列的寿命（CLS）。近年来，一些基因组规模的 CLS 筛选报告了丰富的 CLS 决定基因；因此，CLS 被认为有数百个遗传决定因素。现在需要的是一种方法来了解如此多的基因如何共同发挥作用来调节衰老过程。然而，由于主要参与者缺乏共识，实现这种洞察力存在困难，因为不同的屏幕没有达到相同的结果。为什么有些基因不能产生可重复的表型仍然不清楚，而且即使在同一实验室内也经常出现这种情况。我们的研究小组汇集了互补的技能和技术，通过我们称之为构建“数据驱动网络”的方法来解决这一 CLS 困境。我们开发了一种数据驱动分析的支持技术：它被称为定量高通量细胞阵列表型分析 (Q-HTCP)，与现有技术相比，它使直接测量克隆培养物 CLS 表型的能力提高了数百倍。我们希望应用 Q-HTCP 系统地、定量地评估单倍体酵母生长中所有 6000 个非必需基因突变敲除和必需基因敲除中的 CLS，以及由更多遗传异质菌株组成的 CLS 远交模型。我们将在已知会影响 CLS 的可变环境条件下执行 CLS。这些“扰动”将包括可变的葡萄糖浓度（众所周知的 CLS 效应物），但也包括硫代谢途径 (SMP) 的输入。此外，我们发现通气会影响 CLS，并怀疑它与其他环境以及遗传因素相互作用。 SMP 是生产必需氨基酸蛋氨酸所必需的，因此饮食限制已被证明即使在没有热量限制的情况下也能延长寿命。在首次使用 Q-HTCP 进行全基因组 CLS 筛选时，我们从 4750 个基因缺失菌株中鉴定出 363 个菌株（2 个培养物中的 2 个）比参考对照菌株具有更长的存活时间。长期存活者与野生型分离的平稳趋势以及复制培养物之间 CLS 存活曲线的高度相关性使我们的结果充满信心。在我们最有信心的 363 个命中中，只有 69 个与其他三个基因组筛选中的至少一个的前 300 个重叠； 14 与三个中的两个重叠，并且没有一个与所有三个重叠。我们的结果证实了关于 CLS 决定基因缺乏共识，因为我们的筛选与所有其他三个筛选大致相同。 CLS 数据质量有力地验证了 Q-HTCP 在酵母老化研究中的实用性，因此我们组建了一个跨学科团队，包括 Q-HTCP、SMP、CLS、转录组学、代谢组学以及从大规模组学数据构建生物网络的专业知识一体化。通过跨学科合作，我们的目标是为 CLS 提供一个系统级框架，以帮助构建能够揭示细胞衰老机制的基因调控网络。