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Uncovering cell factors with aggregate clearance activity by scalable induced proximity

Uncovering cell factors with aggregate clearance activity by scalable induced proximity
通过可扩展的诱导接近来发现具有聚集清除活性的细胞因子
批准号:
10705215
负责人:
Yevgeniy Vladimirovich Serebrenik
金额:
$12.96万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-09-15 至 2024-08-31

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中文摘要
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英文摘要
Summary Toxic aggregation of proteins is a pathogenic mechanism in neurodegenerative disease (ND). Proteins such as TDP-43 in frontotemporal dementia (FTD) or Alzheimer’s disease (AD) misfold into aggregates, which both disrupts endogenous protein functions and confers toxic new functions that lead to neuronal cell death. There are no cures for AD or FTD, but current research suggests aggregate clearance is a promising therapeutic strategy. Aggregates of TDP-43 are influenced by the proteostasis network consisting of chaperones and degradation machinery, though which factors can mediate aggregate clearance and how they do so is not known. Prior work using small molecule ligands called PROTACs to induce proximity of target proteins to components of the ubiquitin-proteasome system has proven a promising approach for clearing aberrant protein species. Analogously, this proposal aims to systematically screen the large, uninterrogated portion of the proteostasis network for its ability to clear aggregates of TDP-43 by ligand-induced proximity. In addition to proteins that may function as degraders or disaggregases, RNAs will also be screened for aggregate clearance activity. This work will reveal new quality control factors and mechanisms involved in aggregate clearance and will provide a platform for translational development of multispecific drugs for ND. This work will be accomplished in three Aims, providing me with critical training for transition into independent research. In Aim 1, I will develop an experimental workflow to image aggregate-prone TDP-43 expressed in a multiplexed tag cell library. I will write computational pipelines to characterize mechanisms of aggregate clearance and integrate them with automated in-situ sequencing to reveal the identity of the putative effector in each cell. This aim will optimize reagents and develop analysis methods for induced proximity screens, training me in models of ND and pooled image analysis. In Aim 2, I will focus on screening proteostasis network components by scalable induced proximity and validate factors mediating aggregate clearance in neurons and in vitro, gaining training in cell biology and biochemical techniques to characterize degraders and disaggregases. This work will uncover recruitable factors inducing aggregate clearance. In Aim 3, as an independent investigator, I will develop pooled tagging of transcripts and use the resulting multiplexed cell libraries to screen for RNAs with induced proximity-based aggregate clearance activity. The outcome of this work will systematically characterize the proteostatic potential of RNAs in modulating aggregation and greatly expand the space of recruitable effectors with potential therapeutic benefit. The expert mentoring team I have assembled, as well as the excellent training environment at CHOP and Penn, will greatly facilitate my research and training during the mentored phase of this proposal and provide me with the skills necessary to begin independent research systematically characterizing proteostasis mechanisms involved in ND-associated protein aggregation.
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Uncovering cell factors with aggregate clearance activity by scalable induced proximity
  • 批准号:
    10524896
  • 项目类别:
  • 资助金额:
    $12.96万
  • 财政年份:
    2022
  • 负责人:
    Yevgeniy Vladimirovich Serebrenik
  • 依托单位:
Rapid and direct control of the proteome through a multiplexed tag system
  • 批准号:
    9899088
  • 项目类别:
  • 资助金额:
    $6.53万
  • 财政年份:
    2019
  • 负责人:
    Yevgeniy Vladimirovich Serebrenik
  • 依托单位:
Rapid and direct control of the proteome through a multiplexed tag system
  • 批准号:
    9760412
  • 项目类别:
  • 资助金额:
    $6.12万
  • 财政年份:
    2019
  • 负责人:
    Yevgeniy Vladimirovich Serebrenik
  • 依托单位: