Rapid and direct control of the proteome through a multiplexed tag system

通过多重标签系统快速直接控制蛋白质组

基本信息

项目摘要

Project Summary Understanding and regulating the functions of the proteome is a primary goal in the biomedical sciences. Cancer biology, in a particular, is a field that is currently greatly benefiting from high-throughput functional analysis of genes and proteins. The selective reliance of cancer cells on common cell pathways, a phenomenon known as non-oncogene addiction, is often studied via high-throughput screening approaches, thus uncovering new potential therapies. Unfortunately, modern functional screens based on CRISPR and RNA interference, although informative, cannot affect the proteome acutely and are thus not only technically limiting, but also especially susceptible to compensation mechanisms that obscure protein roles. Additionally, in the time it takes to establish genetic knockdown, many proteins essential for viability are lost and cannot be tested for interesting phenotypes in non-viability screen formats. To facilitate a broader and more comprehensive study of the proteome, I propose to develop a new screening paradigm based on rapid and direct modulation of proteins at a genome-wide scale. This screening platform will initially be developed to uncover many new insights on non- oncogenic addiction in cancer cells. The technology is based on a multiplexed cell library where each gene is tagged with a ligand-binding, bioorthogonal protein, one cell at a time. Small-molecule ligands will bidirectionally regulate the stability of tagged proteins. In the first aim, I will determine the rules required for efficient large-scale protein tagging. Subsequently, in the second aim, I will construct a genome-wide multiplexed tag library in cancer cells and perform a protein essentiality screen by rapid degradation, demonstrating the ability of the platform to uncover novel hits. Essentiality screens performed with traditional genetic perturbation tools, like CRISPR and RNA interference, are predicted to be much more susceptible to cell compensation mechanisms, and so I will directly compare the results obtained from this screen to results obtained from other, comparable essentiality screens. In the third aim, I will utilize the developed platform to comprehensively explore the role of proteostasis in non-oncogene addiction. Specifically, I will uncover a subcellular map of acute responses to proteotoxic stress in both cancerous and healthy cells. This will be achieved by using a subset of the multiplexed tag cell library to induce compartment-specific protein destabilization, which will be analyzed by single-cell RNA sequencing. In summary, I will develop a strategy to rapidly and directly modulate the proteome in a high-throughput manner, facilitating studies that will greatly contribute to our understanding of non-oncogenic addiction in cancer cells and leading to the development of novel cancer therapies. The success of this project will be greatly facilitated by its environment, which provides access to facilities and insight from experts from both the Children’s Hospital of Philadelphia and the University of Pennsylvania. Exciting, nearby collaborations can be easily established once this platform is developed, immediately putting its potential to use where it will be most beneficial.
项目总结

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Yevgeniy Vladimirovich Serebrenik其他文献

Yevgeniy Vladimirovich Serebrenik的其他文献

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{{ truncateString('Yevgeniy Vladimirovich Serebrenik', 18)}}的其他基金

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:
    10524896
  • 财政年份:
    2022
  • 资助金额:
    $ 6.53万
  • 项目类别:
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
  • 财政年份:
    2022
  • 资助金额:
    $ 6.53万
  • 项目类别:
Rapid and direct control of the proteome through a multiplexed tag system
通过多重标签系统快速直接控制蛋白质组
  • 批准号:
    9760412
  • 财政年份:
    2019
  • 资助金额:
    $ 6.53万
  • 项目类别:

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