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.

抽象的 基因表达的调节是细胞适应外部变化的基本机制 环境。因此，专门的途径已经发展为感知环境信号并传达这一点 信息到特定的信号传导和调节电路，以执行基因的预编程变化 表达。这是我们对基因调节和细胞适应过度的常规理解 六十年。我们最近发现，真核细胞的员工是实现的完全不同的策略 自适应基因表达与这些常规硬连线途径无关。在这个过程中 我们称为随机调整，细胞利用mRNA转录中的固有噪声来随机增加或 减少基因表达，并积极加强那些改善总体健康的变化 细胞。这种实时的经验优化策略使细胞能够适应极端/不熟悉 通过建立任意基因表达模式的环境，这些模式超出了其硬性的能力 有线监管计划。我们拥有广泛的发布和初步数据，可随机调整操作 在发芽的酵母菌中，酿酒酵母和人类细胞线。我们被随机性的可能性所强迫 调整可能是真核生物适应的宽度机制。特别是，它可能是“非 - 遗传的疾病相关现象，包括表观遗传化疗抗性。我们最近有 鉴定出候选遗传局部和化学扰动，这些局部和化学扰动基本影响随机调节行为 在酵母中。我们建议实质上扩展这些努力，以全面识别基本的CI和 使用无偏系统生物学方法的反式分子效应。这些包括：（1）我们的利用 最近开发了完整的酵母CRISPR干预库，以定量确定所有必需品的作用 和随机调整中的非必需基因； （2）对所有核心酵母启动子进行调整的全面分析 使用荧光报告库和高通量测序的FACS分类的功效； （3）从头开始 临界DNA序列特征的计算推断和实验验证； （4）高分辨率 沿调谐轨迹的mRNA和染色质动力学分析； （5）精确诱导和监测 使用光遗传学扰动和对基因表达的高暂时分辨率监测中的调整事件 单细胞； （6）确定在调谐的不同阶段发现效应的功能作用 使用闭环系统，该系统可以精确控制和监视调谐轨迹。这些努力 代表了随机调整的第一个系统遗传询问。我们希望这些研究能够 在随机调整中产生关键效果的零件列表，并在各个阶段描述其角色 该过程在单个细胞中受到监测和干扰。这是确定细节的关键第一步 随机调整的分子机制，并揭示了该基因调节的全部含义 生理，发育和疾病的现象。