Stochastic tuning: a novel regulatory mechanism for cellular adaptation

随机调谐：一种新的细胞适应调节机制

• 批准号: 10256756
• 负责人: Saeed F Tavazoie
• 金额: $ 40.24万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-09 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10256756
• 关键词: Affect; Aging; Behavior; Binding; Biology; Blood Vessels; CRISPR interference; Cell model; Cells; Chemicals; Chromatin; DNA; DNA Sequence; Data; Dependence; Development; Disease; Environment; Epigenetic Process; Etiology; Eukaryota; Eukaryotic Cell; Event; Foundations; Functional disorder; Future; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Gene Expression Regulation; Genetic; Genetic Screening; Genetic Transcription; Genome; Goals; Health; High-Throughput Nucleotide Sequencing; Human Cell Line; Image; Individual; Libraries; Malignant Neoplasms; Mammalian Cell; Medicine; Messenger RNA; Modification; Molecular; Monitor; Noise; Nucleosomes; Organ; Output; Pathway interactions; Phase; Physiological; Physiology; Play; Population; Process; Publishing; Regulator Genes; Reporter; Research; Resistance; Resolution; Role; Saccharomyces cerevisiae; Saccharomycetales; Signal Transduction; Sorting - Cell Movement; System; Time; Validation; Yeasts; biological systems; developmental disease; genome wide screen; genomic locus; improved; knowledge of results; non-genetic; novel; optogenetics; programs; promoter; temporal measurement

Abstract Regulation of gene expression is the fundamental mechanism by which cells adapt to changes in the external environment. As such, dedicated pathways have evolved to sense environmental signals and to convey this information to specific signaling and regulatory circuits in order to execute pre-programmed changes in gene expression. This has been our conventional understanding of gene regulation and cellular adaptation for over sixty years. We have recently discovered that eukaryotic cells employ an entirely distinct strategy to achieve adaptive gene expression states independent of these conventional hard-wired pathways. In this process that we call stochastic tuning, cells utilize the inherent noise in mRNA transcription to randomly increase or decrease expression of genes and to actively reinforce only those changes that improve the overall health of the cell. This real-time empirical optimization strategy enables cells to adapt to extreme/unfamiliar environments by establishing arbitrary patterns of gene expression that are beyond the capacity of their hard- wired regulatory programs. We have extensive published and preliminary data that stochastic tuning operates in both budding yeast S. cerevisiae and human cell-lines. We are compelled by the possibility that stochastic tuning may be a widespread mechanism of adaptation in eukaryotes. In particular, it may be the basis for ‘non- genetic’ phenomena of disease relevance including epigenetic chemotherapeutic resistance. We have recently identified candidate genetic loci and chemical perturbations that substantially affect stochastic tuning behavior in yeast. We propose to substantially scale these efforts to comprehensively identify the underlying cis and trans molecular effectors using unbiased systems biological approaches. These include: (1) utilization of our recently developed full yeast CRISPR-interference library to quantitatively determine the role of all essential and non-essential genes in stochastic tuning; (2) Comprehensive profiling of all core yeast promoters for tuning efficacy using FACS-sorting of fluorescent reporter libraries and high-throughput sequencing; (3) de novo computational inference and experimental validation of critical DNA sequence features; (4) high-resolution profiling of mRNA and chromatin dynamics along a tuning trajectory; (5) precise induction and monitoring of tuning events using optogenetic perturbations and high-temporal resolution monitoring of gene expression in single cells; and (6) determining the functional roles of discovered effectors in the distinct phases of tuning using a closed-loop system that enables precise control and monitoring of tuning trajectories. These efforts represent the very first systematic genetic interrogation of stochastic tuning. We expect these studies to generate a parts-list of key effectors in stochastic tuning and to delineate their roles in the various phases of the process, monitored and perturbed in single cells. This is a critical first step in the determining the detailed molecular mechanism of stochastic tuning and in revealing the full implications of this gene-regulatory phenomenon in physiology, development, and disease.

摘要 基因表达调控是细胞适应外部环境变化的基本机制 环境。因此，专门的路径已经进化来感知环境信号并传达这一信息 将信息传递给特定的信号和调节电路，以执行基因的预编程变化 表情。多年来，这一直是我们对基因调控和细胞适应的传统理解。 六十年了。我们最近发现，真核细胞采用一种完全不同的策略来实现 适应性基因表达状态不依赖于这些传统的硬连接通路。在这个过程中， 我们称之为随机调节，细胞利用信使核糖核酸转录中固有的噪声随机增加或 减少基因的表达，并积极加强那些改善整体健康的变化 牢房。这种实时经验优化策略使细胞能够适应极端/陌生的环境 通过建立超出其硬能力的基因表达的任意模式来保护环境 有线监管计划。我们有大量已公布的和随机调整操作的初步数据 在萌芽中的酵母S.cerevisiae和人类细胞系中。我们被随机性的可能性所驱使 在真核生物中，调谐可能是一种广泛的适应机制。尤其是，这可能是“非-- 与疾病相关的遗传现象，包括表观遗传化疗耐药。我们最近做了 确定了显著影响随机调谐行为的候选遗传基因座和化学扰动 放在酵母里。我们建议大幅扩大这些工作的规模，以全面识别基本的身份证明文件和 使用无偏系统生物学方法的跨分子效应器。这些措施包括：(1)利用我们的 最近开发的全酵母CRISPR干扰文库可以定量确定所有必需的作用 以及随机调整中的非必需基因；(2)所有核心酵母启动子的综合图谱以供调整 使用FACS的有效性--荧光报告文库的分类和高通量测序；(3)从头开始 关键DNA序列特征的计算推断和实验验证；(4)高分辨率 沿调节轨迹的信使核糖核酸和染色质动力学的图谱；(5)精确的诱导和监测 利用光遗传扰动和高时间分辨率监测基因表达来调节事件 单细胞；以及(6)确定所发现的效应器在调谐的不同阶段中的功能角色 使用能够精确控制和监控调谐轨迹的闭环系统。这些努力 代表了随机调谐的第一次系统的遗传询问。我们预计这些研究将 生成随机调优中关键效应器的部件列表，并描述它们在不同阶段的角色 这一过程在单个细胞中受到监测和干扰。这是确定详细信息的关键第一步 随机调谐的分子机制以及揭示这种基因调控的全部含义 生理、发育和疾病方面的现象。