Stochastic tuning: a novel regulatory mechanism for cellular adaptation

随机调谐：细胞适应的新型调节机制

• 批准号: 10668425
• 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/10668425
• 关键词: Affect; Aging; Behavior; Binding; Biology; Blood Vessels; CRISPR interference; Cell model; Cells; Chemicals; Chromatin; DNA; DNA Sequence; Data; Dedications; 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; Genes; 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; Resolution; Role; Saccharomyces cerevisiae; Saccharomycetales; Signal Transduction; Sorting; System; Time; Validation; Yeasts; biological systems; candidate identification; genome wide screen; genomic locus; improved; knowledge of results; non-genetic; novel; optogenetics; programs; promoter; temporal measurement; therapy resistant

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界环境变化的基本机制。 环境因此，专门的通路已经发展到感知环境信号并传达这种信号。 信息传递到特定的信号和调节电路，以执行基因的预编程变化。 表情这是我们对基因调控和细胞适应的传统理解， 六十年。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独立于这些传统的硬连线途径。在这个过程中， 我们称之为随机调谐，细胞利用mRNA转录中的固有噪声随机增加或 减少基因的表达，并积极加强只有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/不熟悉的环境。 环境通过建立任意的基因表达模式，超出了他们的硬， 有线监管程序。我们有广泛的出版和初步的数据，随机调谐操作 在两种芽殖酵母S.酿酒酵母和人细胞系。我们不得不考虑随机的 调谐可能是真核生物中广泛存在的适应机制。特别是，它可能是"非- 疾病相关性的“遗传”现象，包括表观遗传化疗耐药性。我们最近 识别出的候选遗传基因座和化学扰动显著影响随机调谐行为 在酵母中。我们建议大幅度扩大这些努力，以全面确定基本的独联体， 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 最近开发了完整的酵母CRISPR干扰文库，以定量确定所有必需的CRISPR的作用。 和非必需基因的随机调整;（2）全面剖析所有核心酵母启动子的调整 使用荧光报告文库的FACS分选和高通量测序的功效;（3）从头 关键DNA序列特征的计算推理和实验验证;（4）高分辨率 mRNA和染色质动力学沿调谐轨迹沿着的谱分析;（5）精确诱导和监测 使用光遗传学扰动和高时间分辨率监测基因表达来调节事件， 单个细胞;和（6）确定所发现的效应物在不同的调谐阶段中的功能作用 使用闭环系统，能够精确控制和监测调谐轨迹。这些努力 代表了第一个系统的随机调谐的遗传询问。我们希望这些研究能够 生成随机调整中的关键效应器的部分列表，并描述它们在各个阶段的作用， 在单个细胞中监测和干扰该过程。这是确定详细的 随机调谐的分子机制，并揭示这种基因调控的全部含义， 生理、发育和疾病中的现象。