REAL-TIME QUANTITATIVE IMAGING OF INTRACELLULAR BIOTHIOL DYNAMICS

细胞内生物硫醇动力学的实时定量成像

基本信息

  • 批准号:
    9753260
  • 负责人:
  • 金额:
    $ 30.62万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-09-22 至 2021-07-31
  • 项目状态:
    已结题

项目摘要

 DESCRIPTION (provided by applicant): The objective of this proposal is to develop a series of specific biothiol probes that will exhibit different ratiometric spectroscopic properties after undergoing reversible reactions, and thus quantitatively monitor the dynamics of biothiols through real-time imaging with subcellular resolution. Despite the existence of myriad small molecule fluorescent probes developed for biological imaging, very few can provide meaningful quantitative results, especially when tasked to detect redox signaling molecules, like glutathione (GSH) and H2S. Our recent work demonstrated that reversibility of sensing reactions is key to quantitatively monitoring the dynamics of small molecules in cells. Ratiometric probes are preferred for live cell imaging because they allow quantitative measurements of analyte concentrations independent of probe concentration. Taking advantage of reversible Michael additions, we developed CouBro, the first fluorescent probe for quantitative imaging of GSH in live cells. Due to the reversible nature of the reaction between the probe and GSH, we are able to quantify mM concentrations of GSH with as little as 50 nM CouBro. Furthermore, the GSH concentrations in several cell lines, measured using CouBro, are well correlated with those values obtained from lysates. In addition, we showed that this live imaging method has excellent reproducibility and is able to detect GSH fluctuations in cells upon external stimulation. In the preliminary study, we developed a computational chemistry approach to predict the thermodynamics and kinetics of reactions between biothiols and their probes, which will guide our design of biothiol probes. We also developed organelle specific H2S probes by applying genetically encoded protein technology to reaction-based small molecule fluorescent probes. This universal targeting strategy enables us to infer the signaling molecule concentration in the micro-environment around a protein of interest. In Aim 1, we will develop a series of GSH probes with fast kinetics and organelle specificity to monitor intracellular GSH dynamics. The probe design process will be facilitated by computational chemistry. In Aim 2, we will develop new reversible chemistry for H2S specific reactions. Due to inconsistently reported H2S levels, ranging from nM to µM, H2S probes with a range of dissociation constants will be developed. We will also monitor H2S signaling dynamics by labeling key enzymes responsible for H2S production and proteins specific to certain organelles. In Aim 3, we will apply these newly developed biothiol probes to investigate Grx3 mediated GSH metabolism and its interplay with H2S signaling in cancer cells, particularly during tumorigenesis in vivo. Successful completion of this project will provide a comprehensive toolbox for quantitative imaging of GSH and H2S dynamics and further elucidate their roles in redox-related cancer signaling and development.
 描述(申请人提供):本方案的目标是开发一系列特定的生物硫醇探针,这些探针在经历可逆反应后将显示不同的比率光谱性质,从而通过亚细胞分辨率的实时成像定量监测生物硫醇的动力学。尽管存在着无数用于生物成像的小分子荧光探针,但很少有能够提供有意义的定量结果的,特别是当任务是检测氧化还原信号分子时,如谷胱甘肽(GSH)和硫化氢。我们最近的工作表明,传感反应的可逆性是定量监测细胞内小分子动力学的关键。比率探针是活体细胞成像的首选,因为它们允许不依赖于探针浓度的分析物浓度的定量测量。利用可逆的Michael加成,我们开发了第一个荧光探针CouBro,用于活细胞中GSH的定量成像。由于探针和GSH之间反应的可逆性,我们能够用短短50 NM的CouBro来定量GSH的毫米级浓度。此外,用CouBro测量的几种细胞系中的GSH浓度与从裂解物中获得的值有很好的相关性。此外,我们还表明,这种实时成像方法具有良好的重复性,能够检测细胞在外部刺激下的GSH波动。在初步研究中,我们开发了一种计算化学方法来预测生物硫醇与其探针之间的反应的热力学和动力学,这将指导我们的生物硫醇探针的设计。我们还将基因编码的蛋白质技术应用到基于反应的小分子荧光探针中,开发了细胞器特异性的硫化氢探针。这种通用的靶向策略使我们能够推断出目标蛋白质周围微环境中的信号分子浓度。在目标1中,我们将开发一系列具有快速动力学和细胞器特异性的GSH探针来监测细胞内GSH动态。探针的设计过程将由计算化学来促进。在目标2中,我们将为特定的硫化氢反应开发新的可逆化学。由于报告的硫化氢水平不一致,范围从纳米到微米,将开发具有一定解离常数范围的硫化氢探测器。我们还将通过标记负责产生硫化氢的关键酶和某些细胞器特有的蛋白质来监测硫化氢信号的动态。在目标3中,我们将应用这些新开发的生物硫醇探针来研究Grx3介导的GSH代谢及其与癌细胞中H2S信号的相互作用,特别是在体内肿瘤形成过程中。该项目的成功完成将为GSH和H2S动力学的定量成像提供一个全面的工具箱,并进一步阐明它们在氧化还原相关癌症信号和发展中的作用。

项目成果

期刊论文数量(0)
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Jin Wang其他文献

Jin Wang的其他文献

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{{ truncateString('Jin Wang', 18)}}的其他基金

Mathematical Modeling and Scientific Computing for Infectious Disease Research
传染病研究的数学建模和科学计算
  • 批准号:
    10793008
  • 财政年份:
    2023
  • 资助金额:
    $ 30.62万
  • 项目类别:
Development of First-in-Class RIPK1 Degraders to Improve Cancer Immunotherapies
开发一流的 RIPK1 降解剂以改善癌症免疫疗法
  • 批准号:
    10390589
  • 财政年份:
    2022
  • 资助金额:
    $ 30.62万
  • 项目类别:
Development of First-in-Class RIPK1 Degraders to Improve Cancer Immunotherapies
开发一流的 RIPK1 降解剂以改善癌症免疫疗法
  • 批准号:
    10661495
  • 财政年份:
    2022
  • 资助金额:
    $ 30.62万
  • 项目类别:
Development of First-in-Class RIPK1 Degraders to Improve Cancer Immunotherapies
开发一流的 RIPK1 降解剂以改善癌症免疫疗法
  • 批准号:
    10746264
  • 财政年份:
    2022
  • 资助金额:
    $ 30.62万
  • 项目类别:
Developing Novel Soluble Epoxide Hydrolase Inhibitors for the Treatment of Alzheimer's Disease
开发用于治疗阿尔茨海默病的新型可溶性环氧化物水解酶抑制剂
  • 批准号:
    10503835
  • 财政年份:
    2020
  • 资助金额:
    $ 30.62万
  • 项目类别:
Developing Novel Soluble Epoxide Hydrolase Inhibitors for the Treatment of Alzheimer's Disease
开发用于治疗阿尔茨海默病的新型可溶性环氧化物水解酶抑制剂
  • 批准号:
    10802956
  • 财政年份:
    2020
  • 资助金额:
    $ 30.62万
  • 项目类别:
Reversible Covalent BTK Degraders as the Next Generation Targeted Therapy to Treat B-cell Malignancies
可逆共价 BTK 降解剂作为治疗 B 细胞恶性肿瘤的下一代靶向疗法
  • 批准号:
    10737768
  • 财政年份:
    2020
  • 资助金额:
    $ 30.62万
  • 项目类别:
Developing Novel Soluble Epoxide Hydrolase Inhibitors for the Treatment of Alzheimer's Disease
开发用于治疗阿尔茨海默病的新型可溶性环氧化物水解酶抑制剂
  • 批准号:
    10412114
  • 财政年份:
    2020
  • 资助金额:
    $ 30.62万
  • 项目类别:
Developing Novel Soluble Epoxide Hydrolase Inhibitors for the Treatment of Alzheimer's Disease
开发用于治疗阿尔茨海默病的新型可溶性环氧化物水解酶抑制剂
  • 批准号:
    10663178
  • 财政年份:
    2020
  • 资助金额:
    $ 30.62万
  • 项目类别:
Developing Novel Soluble Epoxide Hydrolase Inhibitors for the Treatment of Alzheimer's Disease
开发用于治疗阿尔茨海默病的新型可溶性环氧化物水解酶抑制剂
  • 批准号:
    10261446
  • 财政年份:
    2020
  • 资助金额:
    $ 30.62万
  • 项目类别:

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口服抗肿瘤药物的获取延迟
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