ENGINEERING ORGANELLE FUNCTION TO REWIRE CANCER CELL METABOLISM

改造细胞器功能以重新连接癌细胞代谢

基本信息

  • 批准号:
    8756590
  • 负责人:
  • 金额:
    $ 235.38万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2014
  • 资助国家:
    美国
  • 起止时间:
    2014-09-30 至 2019-06-30
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): A cell executes well over 10E8 simultaneous biochemical reactions at hundreds of different locations during every second of its lifetime. Coordinating these innumerable processes is a formidable task that is essential to the correct functioning of each tissue and the entire organism. In response to ever changing internal and external cues, cells have evolved mechanisms that can sense nutrient and energy status and, in response, prompt fine-tuned changes in metabolic activity that buffer these variations. Our recent work has highlighted the role of one organelle, the lysosome, as a gate-keeper of metabolic homeostasis. The lysosome can sense and relay variations in cellular nutrient levels to the master growth regulatory protein kinase mTORC1. In turn, mTORC1 governs catabolic reactions within the lysosome that supply the cell with metabolic building blocks and help maintain global nutrient supply. Importantly, dysregulated lysosomal function is the cause of hereditary metabolic disorders, and is emerging as a contributing factor to the progression of some aggressive cancers. Current technologies that employ mass spectrometers or fluorescent biosensors in whole cells or cell populations cannot reach inside the lysosome to identify and measure the hundreds of metabolites that are generated inside it over time. In order to build a comprehensive, systems-level model of how the lysosome regulates cellular metabolism, a reductionist approach that captures essential spatial and temporal features of lysosomal function in a simplified context is needed. Our goal is to develop a novel in vitro system that wil enable the study of metabolism at the single organelle level. In the current proposal, our system will reconstitute the fusion of lysosomes with organelles known as autophagosomes in test tubes or on the surface of coverslips. Imaging at high spatial and temporal resolution, we will dissect the participation of the lysosome in autophagy, a cellular 'self-eat' process that is essential to the homeostasis of both normal and cancer cells. By scaling up this preparation, and coupling it to high throughput metabolite profiling, we will generate a spatial and temporal 'metabolic map' that profiles hundreds of nutrients generated within the lysosome, describes the time course of their buildup and export, and identifies the transport mechanisms that release these nutrients to the cell. Leveraging the spatial and temporal resolution of our system, we will address a major challenge in present-day cancer research- how highly lethal pancreatic ductal adenocarcinoma (PDAC) exploits autophagy to gain a growth and survival advantage in nutrient-poor microenvironments. Using our 'inside knowledge' of the lysosomal metabolome, we will test the hypothesis that autophagy may allow PDAC cells to maintain homeostasis by tapping into large intracellular reservoirs of nutrients, and we will devise novel strategies to deplete these internal nutrient stores. This project will generate novel tools to illuminate the subcellular organization of metabolism, and lay the foundations for innovative ways to rewire cancer cell metabolism.
描述(由申请人提供):细胞在其生命周期的每一秒钟内在数百个不同的位置同时进行超过10 E8个生化反应。协调这些无数的过程是一项艰巨的任务,对于每个组织和整个有机体的正确功能至关重要。为了应对不断变化的内部和外部线索,细胞进化出了能够感知营养和能量状态的机制,并作为回应,促使代谢活动发生微调变化,以缓冲这些变化。我们最近的工作强调了一个细胞器,溶酶体,作为代谢稳态的守门人的作用。溶酶体可以感知细胞营养水平的变化,并将其传递给主生长调节蛋白激酶mTORC 1。反过来,mTORC 1控制溶酶体内的分解代谢反应,为细胞提供代谢构建模块,并帮助维持全球营养供应。重要的是,溶酶体功能失调是遗传性代谢紊乱的原因,并且正在成为一些侵袭性癌症进展的促成因素。目前在整个细胞或细胞群中使用质谱仪或荧光生物传感器的技术无法到达溶酶体内部,以识别和测量随着时间的推移在其内部产生的数百种代谢物。为了建立一个全面的,系统水平的模型,溶酶体如何调节细胞代谢,还原论的方法,捕捉基本的空间和时间特征的溶酶体功能在一个简化的情况下是必要的。我们的目标是开发一种新的体外系统,使代谢的研究在单个细胞器的水平。在目前的提议中,我们的系统将在试管中或盖玻片表面上重建溶酶体与称为自噬体的细胞器的融合。在高空间和时间分辨率的成像,我们将剖析溶酶体参与自噬,细胞的“自食”过程,是必不可少的正常和癌细胞的稳态。通过放大这种制备,并将其与高通量代谢物分析相结合,我们将生成一个空间和时间的“代谢图”,该图描述了溶酶体内产生的数百种营养物质,描述了它们的积累和输出的时间过程,并确定了将这些营养物质释放到细胞的运输机制。利用我们系统的空间和时间分辨率,我们将解决当今癌症研究中的一个主要挑战-高度致命的胰腺导管腺癌(PDAC)如何利用自噬在营养不良的微环境中获得生长和生存优势。利用我们对溶酶体代谢组的“内部知识”,我们将测试自噬可能允许PDAC细胞通过利用大的细胞内营养库来维持稳态的假设,并且我们将设计新的策略来耗尽这些内部营养库。该项目将产生新的工具来阐明代谢的亚细胞组织,并为重塑癌细胞代谢的创新方法奠定基础。

项目成果

期刊论文数量(5)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(1)
The lysosome as a command-and-control center for cellular metabolism.
  • DOI:
    10.1083/jcb.201607005
  • 发表时间:
    2016-09-12
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Lim CY;Zoncu R
  • 通讯作者:
    Zoncu R
The Lysosome as a Regulatory Hub.
Hybrid Structure of the RagA/C-Ragulator mTORC1 Activation Complex.
  • DOI:
    10.1016/j.molcel.2017.10.016
  • 发表时间:
    2017-12-07
  • 期刊:
  • 影响因子:
    16
  • 作者:
    Su MY;Morris KL;Kim DJ;Fu Y;Lawrence R;Stjepanovic G;Zoncu R;Hurley JH
  • 通讯作者:
    Hurley JH
A nutrient-induced affinity switch controls mTORC1 activation by its Rag GTPase-Ragulator lysosomal scaffold.
  • DOI:
    10.1038/s41556-018-0148-6
  • 发表时间:
    2018-09
  • 期刊:
  • 影响因子:
    21.3
  • 作者:
    Lawrence RE;Cho KF;Rappold R;Thrun A;Tofaute M;Kim DJ;Moldavski O;Hurley JH;Zoncu R
  • 通讯作者:
    Zoncu R
Emerging Roles for the Lysosome in Lipid Metabolism.
  • DOI:
    10.1016/j.tcb.2017.07.006
  • 发表时间:
    2017-11
  • 期刊:
  • 影响因子:
    19
  • 作者:
    Thelen AM;Zoncu R
  • 通讯作者:
    Zoncu R
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Roberto Zoncu其他文献

Roberto Zoncu的其他文献

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{{ truncateString('Roberto Zoncu', 18)}}的其他基金

Molecular Mechanisms of Organelle-based Metabolic Signaling
基于细胞器的代谢信号传导的分子机制
  • 批准号:
    10623647
  • 财政年份:
    2023
  • 资助金额:
    $ 235.38万
  • 项目类别:
Spatio-temporal regulation of mTORC1 signaling in normal and disease states
正常和疾病状态下 mTORC1 信号传导的时空调节
  • 批准号:
    10408711
  • 财政年份:
    2019
  • 资助金额:
    $ 235.38万
  • 项目类别:
Molecular mechanisms for lipid sensing by mTORC1
mTORC1 脂质传感的分子机制
  • 批准号:
    10393506
  • 财政年份:
    2019
  • 资助金额:
    $ 235.38万
  • 项目类别:
Spatio-temporal regulation of mTORC1 signaling in normal and disease states
正常和疾病状态下 mTORC1 信号传导的时空调节
  • 批准号:
    10174962
  • 财政年份:
    2019
  • 资助金额:
    $ 235.38万
  • 项目类别:

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