Control of gene expression by dynamic metabolic oscillations

通过动态代谢振荡控制基因表达

• 批准号: 10668353
• 负责人: John G. Albeck
• 金额: $ 37.72万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-04 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10668353
• 关键词: Aging; Autophagocytosis; Biological Assay; Cells; Chronic Disease; Diabetes Mellitus; Disease; FOXO3A gene; Gene Expression; Genes; Genetic Transcription; Human body; Inflammation; Kinetics; Lysosomes; Malignant Neoplasms; Measures; Metabolic; Metabolic stress; Metabolism; Metformin; Methods; Modeling; Play; Process; Reporter; Role; Stress; Systems Biology; Testing; Translations; Work; cell growth; cell growth regulation; drug sensitivity; inducible gene expression; inhibitor; mathematical model; novel strategies; pharmacologic; programs; response; senescence; transcription factor; transcriptome

Summary Emerging evidence shows that changes in cellular metabolism can induce broad shifts in gene expression, but the mechanisms underlying this connection are not fully understood. Previous work has not examined the impact of temporal dynamics on metabolism-induced gene expression. Recent work in systems biology has shown that oscillations in upstream inputs can be filtered by gene expression machinery to modulate gene expression, through a process termed dynamic filtering. Additionally, we have recently shown that cellular metabolic status fluctuates rapidly in response to various forms of metabolic stress. These cycles drive asynchronous oscillating activity of transcription factors including FOXO3, a key regulator of stress genes that plays a role in aging, and TFEB, a central regulator of lysosome and autophagy genes. We therefore hypothesize that oscillations in metabolic state drive gene expression programs that are distinct from those under static unstressed conditions. We propose that dynamics-sensitive gene expression programs can influence cell fate decisions such as differentiation, cell growth, senescence, inflammation, and drug sensitivity. In this project, we will investigate how metabolic oscillations control the expression of TFEB and FOXO3 target genes. We will use live-cell reporters, inducible expression constructs, and other methods to measure key kinetic parameters in the transcription and translation of target genes. To identify broader gene expression programs modulated by metabolic dynamics, we will use mathematical modeling in combination with transcriptome-level profiling. Functional assays will be used to test how dynamically sensitive gene expression programs alter cell fates. We expect our study to establish an important unexplored mechanism that explains how short-term regulation of cellular metabolic status influences chronic diseases including cancer, diabetes, and aging. Our results will address the outstanding question of how pharmacological metabolic inhibitors such as metformin provide benefits in cancer and aging. The models generated will establish a new approach to evaluate candidate pharmacological compounds.

概括 新的证据表明细胞代谢的变化可以引起基因的广泛变化 表达，但这种联系背后的机制尚未完全了解。以前的 工作尚未检查时间动态对代谢诱导基因的影响 表达。系统生物学的最新研究表明，上游输入的振荡可以 被基因表达机器过滤以调节基因表达，通过一个过程 称为动态过滤。此外，我们最近发现细胞代谢状态 响应各种形式的代谢应激而快速波动。这些循环驱动 转录因子的异步振荡活动，包括 FOXO3（FOXO3 的关键调节因子） 应激基因在衰老中发挥作用，以及 TFEB（溶酶体的中央调节因子） 自噬基因。因此，我们假设代谢状态的振荡驱动基因 表达程序与静态无应激条件下的表达程序不同。我们 提出动态敏感的基因表达程序可以影响细胞命运的决定 例如分化、细胞生长、衰老、炎症和药物敏感性。在这个 项目中，我们将研究代谢振荡如何控制 TFEB 的表达和 FOXO3 靶基因。我们将使用活细胞报告基因、诱导表达构建体和其他 测量靶基因转录和翻译中关键动力学参数的方法。 为了确定代谢动力学调节的更广泛的基因表达程序，我们将使用 数学建模与转录组水平分析相结合。功能测定将 用于测试动态敏感基因表达程序如何改变细胞命运。我们期望 我们的研究旨在建立一个重要的未探索的机制来解释短期如何 细胞代谢状态的调节影响慢性疾病，包括癌症、糖尿病、 和老化。我们的研究结果将解决药理学代谢如何这一突出问题 二甲双胍等抑制剂对癌症和衰老有好处。生成的模型将 建立评估候选药理学化合物的新方法。

项目成果

Deciphering the History of ERK Activity from Fixed-Cell Immunofluorescence Measurements.

从固定细胞免疫荧光测量中解读 ERK 活性的历史。

• 发表时间: 2024-02-17
• 作者: Ram, Abhineet;Pargett, Michael;Choi, Yongin;Murphy, Devan;Cabel, Markhus;Kosaisawe, Nont;Quon, Gerald;Albeck, John
• 通讯作者: Albeck, John

A guide to ERK dynamics, part 2: downstream decoding.

ERK 动态指南，第 2 部分：下游解码。

• 发表时间: 2023-12-13
• 作者: Ram, Abhineet;Murphy, Devan;DeCuzzi, Nicholaus;Patankar, Madhura;Hu, Jason;Pargett, Michael;Albeck, John G
• 通讯作者: Albeck, John G

A guide to ERK dynamics, part 1: mechanisms and models.

ERK 动力学指南，第 1 部分：机制和模型。

• 发表时间: 2023-12-13
• 作者: Ram, Abhineet;Murphy, Devan;DeCuzzi, Nicholaus;Patankar, Madhura;Hu, Jason;Pargett, Michael;Albeck, John G
• 通讯作者: Albeck, John G