Programming Human Chaperone Systems Against Neurodegenerative Disease

对人类伴侣系统进行编程以对抗神经退行性疾病

基本信息

批准号：
10026294
负责人：
Edward Matthew Barbieri
金额：
$ 6.42万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-30 至 2022-09-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10026294
关键词：
Alzheimer&apos s Disease Amyotrophic Lateral Sclerosis Bar Codes Biochemical Biochemistry Biological Assay Biological Models Cell model Cell physiology Cells Cellular Stress Chaperone Gene Clustered Regularly Interspaced Short Palindromic Repeats DNA Sequence Alteration Disease Doctor of Philosophy Engineering Enzymes Exhibits Frontotemporal Dementia Gene Combinations Genes Genetic Genetic Engineering Human Human Engineering Huntington Disease In Vitro Lead Libraries Modeling Molecular Chaperones Neurodegenerative Disorders Neurons Organism Parkinson Disease Plasmids Population Process Proteins Quality Control Quantitative Microscopy Spinocerebellar Ataxias Substrate Specificity System Techniques Testing Therapeutic Toxic effect Transgenes Triplet Multiple Birth Validation Work Yeast Model System Yeasts alpha synuclein combat combinatorial cost efficient deep sequencing effective therapy exhaustion invention mutant new therapeutic target novel novel strategies professor protein TDP-43 protein aggregation protein misfolding screening therapeutic candidate tool vector yeast genetics

项目摘要

Cellular stress causes protein misfolding and aggregation, which is combatted by protein chaperone enzymes (disaggregases). In neurons, protein misfolding and aggregation can lead to neurodegenerative diseases including amyotrophic lateral sclerosis (ALS), Alzheimer's disease, frontotemporal dementia, Parkinson's disease, Huntington's disease, and spinocerebellar ataxias. The lack of viable therapeutic options reflects the dearth of our understanding regarding the cellular processes that go awry in these diseases. Since protein quality control is required for all living organisms, simple model systems such as yeast are powerful tools to study the analogous human process in a rapid and cost-efficient way. This project will leverage high-throughput genetic engineering in yeast to study and engineer human disaggregase systems to combat toxic protein aggregates that underlie Parkinson’s disease and ALS. First, I will test the hypothesis that unique combinations of human hsp110, hsp70, and hsp40 chaperones can impart disaggregase substrate specificity in a cell. I will create and test plasmid libraries for all possible triplet combinations of the known hsp110/70/40 genes in yeast models of Parkinson’s and ALS. Second, I will use eMAGE, a technique that I invented during my PhD, to engineer the previously characterized human disaggregase machinery comprised of hsp110 (Apg-2), hsp70 (Hsc70) and hsp40 (Hdj1). Lastly, I will validate the findings from yeast in human neuronal cell models of Parkinson’s disease and ALS. The experimental pipeline outlined in this proposal leverages the scale and power of yeast genetics to identify Hsp110/70/40 mutants and gene combinations that exhibit rescue of toxicity, which are then experimentally validated in a bona fide human neuron. This project will greatly enhance the current understanding of human disaggregase mechanisms by exhaustively screening the combinatorial space of three-gene chaperone interactions and it will likely identify new mechanisms for candidate therapeutics of Parkinson’s disease and ALS.

细胞应激会导致蛋白质折叠和聚集，这被蛋白链酮酶（分裂酶）抗击。在神经元中，蛋白质误后折叠和聚集会导致神经退行性疾病，包括肌萎缩性侧索硬化症（ALS），阿尔茨海默氏病，额颞痴呆，帕金森氏病，帕金森氏病，亨廷顿氏病和脊椎队的双胞质。缺乏可行的治疗选择反映了我们对这些疾病中出现问题的细胞过程的理解的死亡。由于所有生物体都需要蛋白质质量控制，因此诸如酵母等简单模型系统是以快速且具有成本效益的方式研究类似人类过程的强大工具。该项目将利用酵母中的高通量基因工程来研究和工程人类分类酶系统来对抗帕金森氏病和ALS的有毒蛋白质聚集体。首先，我将检验以下假设：人类HSP110，HSP70和HSP40伴侣的独特组合可以在细胞中赋予分解酶底物的特异性。我将在帕金森氏症和ALS的酵母模型中创建和测试质粒库的所有可能的三胞胎组合。其次，我将使用我在博士学位期间发明的技术Emage来设计先前表征的HSP110（APG-2），HSP70（HSC70）（HSC70）和HSP40（HDJ1）（HDJ1）的人类分裂酶机制。最后，我将在帕金森氏病和ALS的人类神经元细胞模型中验证酵母的发现。该提案中概述的实验管道利用了酵母遗传学的规模和力量来识别存在毒性营救的HSP110/70/40突变体和基因组合，然后在真正的人类神经元中实验验证。该项目将通过详尽筛查三基因连锁酮相互作用的组合空间来大大增强对人类分类酶机制的当前理解，并且可能会确定帕金森氏病和ALS候选疗法的新机制。