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。 信息到特定的信号电路以执行基因的编程更改 表达。 六十年。我们最近发现真核细胞采用完全不同的策略 自适应基因表达在这些过程中独立于这些传统的硬连线途径。 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 降低基因表达并积极加强这些改变这些的总体健康 单元。实时的经验优化策略使细胞适应极端 通过建立基因表达的任意模式来超出其硬性能力的环境 有线监管计划。 在出现的S.酿酒酵母和人类细胞线中，我们被随机性的可能性所强迫 调整可能是真核生物中适应的广泛机制。 遗传学的疾病现象，包括表观遗传化学治疗性 鉴定出候选遗传基因座和墓地扰动，这些基因座严重影响随机调整行为 在年度中 使用无偏系统生物学方法的反式分子效应子包括：（1）我们的利用 最近开发了完整的酵母CRIS-iispr-IISPR介入库，以定量确定所有必需品的作用 随机调整中的必需基因； 使用FACS进行荧光文库和高通量测序的功效； 临界DNA序列（4）高分辨率的计算推断和实验验证 沿调谐轨迹的mRNA和染色质动力学的分析； 使用光遗传学扰动和基因表达的高暂时分辨率调整事件 单细胞和（6）确定发现效应子的功能作用 使用闭环系统，可以精确控制和监视这些轨迹 代表了随机调整的第一个系统遗传询问。 在随机调整中生成零件列表，并描述的各个阶段 该过程在单个单元格中受到监测和扰动。 随机调整的分子机制，并陶醉于该基因屈光度的全部含义 生理，发育和疾病的现象。