Uncovering cell factors with aggregate clearance activity by scalable induced proximity
Uncovering cell factors with aggregate clearance activity by scalable induced proximity
批准号:
10524896
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
关键词:
AddressAlzheimer&aposs DiseaseAlzheimer&aposs disease modelBindingBiochemicalBiochemistryCellsCellular biologyCodeComplementComputational TechniqueDevelopmentDiseaseDisease modelEnvironmentFoundationsFrontotemporal DementiaFunctional disorderFutureGenesGoalsHumanImageImage AnalysisIn VitroLeadLibrariesLigand BindingLigand Binding DomainLigandsMediatingMentorsMethodologyMethodsMicroscopyModelingMolecular ChaperonesNatureNerve DegenerationNeurodegenerative DisordersNeuronsOutcomePathogenicityPathologyPharmaceutical PreparationsPharmacologyPhasePopulationProcessProteinsQuality ControlRNAReagentResearchResearch PersonnelResearch TrainingSeverity of illnessSystemTDP-43 aggregationTechniquesTherapeuticTrainingTranscriptUbiquitinUntranslated RNAVisualizationWorkWritingage relatedage related neurodegenerationanalysis pipelineaptamerbasecareercomputational pipelinesdrug developmentimprovedin situ sequencinginsightloss of functionmulticatalytic endopeptidase complexmutantneuron lossneuroprotectionneurotoxicnovelpreventprotein TDP-43protein aggregationprotein degradationprotein functionproteostasisrecruitscreeningskillssmall moleculesymptom treatmenttargeted treatmenttranscriptome
中文摘要
总结
蛋白质的毒性聚集是神经退行性疾病(ND)的一种致病机制。蛋白
如额颞叶痴呆(FTD)或阿尔茨海默病(AD)中TDP-43错误折叠成聚集体,
两者都破坏内源性蛋白质功能并赋予导致神经元细胞死亡的毒性新功能。
AD或FTD没有治愈方法,但目前的研究表明,聚集体清除是一种有前途的治疗方法
战略TDP-43的聚集体受到由分子伴侣和蛋白酶组成的蛋白质稳态网络的影响。
降解机制,但哪些因素可以介导聚集体清除,以及他们如何做到这一点是未知的。
先前使用称为PROTAC的小分子配体诱导靶蛋白与组分接近的工作
泛蛋白-蛋白酶体系统的研究已被证明是清除异常蛋白质种类的一种有前途的方法。
类似地,该建议旨在系统地筛选蛋白质抑制的大的未询问部分。
网络的能力,以清除聚集的TDP-43通过配体诱导的接近。除了蛋白质,
作为降解剂或解聚剂,还将筛选RNA的聚集体清除活性。这项工作
将揭示新的质量控制因素和机制,涉及集料清除,并将提供一个
用于ND的多特异性药物的转化开发平台。
这项工作将在三个目标中完成,为我提供过渡到
独立研究。在目标1中,我将开发一个实验性的工作流程来对聚集倾向的TDP-43进行成像
在多路复用标签细胞文库中表达。我将编写计算管道来描述
聚集清除并将其与自动原位测序整合,以揭示推定的
每个细胞中的效应子。这一目标将优化试剂并开发用于诱导邻近筛选的分析方法,
训练我ND模型和合并图像分析。在目标2中,我将重点筛选蛋白质稳态网络
通过可扩展的诱导接近和验证介导神经元中聚集体清除的因素,
在体外,获得细胞生物学和生化技术的培训,以表征降解剂和解聚剂。
这项工作将揭示诱发集体清除的可重新招募因素。在目标3中,作为独立的
作为一名研究人员,我将开发转录本的汇集标签,并使用由此产生的多重细胞文库来筛选
对于具有诱导的基于邻近的聚集体清除活性的RNA。这项工作的成果将系统地
表征RNA在调节聚集中的蛋白质抑制潜力,并极大地扩展了
具有潜在治疗益处的可募集效应物。我组建的专家指导团队,以及
CHOP和宾夕法尼亚大学的优秀培训环境,将极大地促进我的研究和培训期间,
指导阶段的这一建议,并为我提供必要的技能,开始独立研究
系统地表征参与ND相关蛋白聚集的蛋白质稳态机制。
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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Uncovering cell factors with aggregate clearance activity by scalable induced proximity
-
批准号:10705215
-
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: