Systems Analysis of the Unfolded Protein response in Saccharomyces cerevisiae

酿酒酵母中未折叠蛋白反应的系统分析

• 批准号: 7408407
• 负责人: Keith Edward Jaggard Tyo
• 金额: $ 3.76万
• 依托单位: CHALMERS UNIVERSITY OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-30 至 2010-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7408407
• 关键词: Accounting; Affinity; Alzheimer' s Disease; Amino Acids; Apoptosis; Appearance; Binding; Biological; Biological Process; Cells; Classification; Codon Nucleotides; Collaborations; Complex; Computer software; Consensus; Coupled; DNA-Protein Interaction; Data; Disease; Endoplasmic Reticulum; Enzymes; Equilibrium; Eukaryota; Eukaryotic Cell; Facility Construction Funding Category; Gene Dosage; Gene Proteins; Genes; Genetic; Genome; Graph; Human; Hybrids; Knowledge; Laboratories; Lead; Lipids; Literature; Malignant Neoplasms; Maps; Mass Spectrum Analysis; Measurement; Membrane; Metabolic; Microarray Analysis; Modeling; Modification; Network-based; Non-Insulin-Dependent Diabetes Mellitus; Oxidation-Reduction; Pathway Analysis; Pathway interactions; Phosphorylation; Prevention; Production; Productivity; Protein Biosynthesis; Protein Secretion; Proteins; Proteomics; Recombinant Proteins; Recombinants; Resistance; Resources; Saccharomyces cerevisiae; Score; Systems Analysis; Transcript; United States National Institutes of Health; Work; Yeasts; analytical method; base; biological adaptation to stress; chromatin immunoprecipitation; follow-up; glycosylation; improved; intracellular protein transport; metabolomics; prevent; promoter; protein aggregate; protein expression; protein folding; protein metabolite; protein misfolding; protein protein interaction; protein transport; research study; response; scaffold; size; therapeutic protein

DESCRIPTION (provided by applicant): The unfolded protein response (UPR) is a large-scale, coordinated response to correct misfolded proteins in eukaryotes. The diverse set of actions a cell coordinates in parallel (approx. 380 genes in yeast) to alleviate the various problems that can occur in protein synthesis, folding, glycosylation, and translocation of membrane-bound and secreted proteins has a large impact on therapeutic protein production and aggregated protein-related disease. The proposed work will map the biological information flow through the many genes involved in the response to achieve an understanding of the UPR and identify targets for altering the response. A biological interaction network of the UPR will be constructed from available biological interaction data for yeast. Transcriptional, proteomic, metabolomic, and metabolic flux data will be collected for recombinant yeast producing preinsulin and TNFa with modulated UPR induction. UPR- associated changes in biological molecule levels detected from the X-omics data will be superimposed onto the interaction network, revealing the flow of biological information in the UPR. This combination of information from biological interaction networks and X-omics-scale data will lead to a better understanding of secreted protein production. In particular, metabolite measurements can indicate possible limitations in glycosylation pathways, amino acid supply, energetics, redox balance, or lipid synthesis. Transcript and protein levels may reveal pathways that benefit or detract from high level secretion of protein. From this information, important biological molecules and interactions can be targeted to improve protein production and, in humans, identify targets to prevent/treat aggregated-protein related disease. The findings of the proposed work will be very helpful in understanding the molecules and their interconnections involved in stress response. This strategy represents a multifaceted approach to understanding a complex biological response and is consistent with the NIH Building Blocks, Biological Pathways, and Networks roadmap initiative. Yeast is an attractive commercial producer of therapeutic proteins, but can be limited by low product yields or poor quality that could be improved by this work. A thorough understanding of the UPR could have consequences for prevention and treatment of disease known to be related to aggregated protein, such as Alzheimer's, Type 2 diabetes, and apoptosis-resistant, uncontrolled protein production in certain cancers.

描述（由申请人提供）：未折叠蛋白反应（UPR）是真核生物中纠正错误折叠蛋白的大规模协调反应。单元格中不同的操作集以并行（大约）的方式协调。（酵母中有380个基因）来缓解在蛋白质合成、折叠、糖基化和膜结合蛋白和分泌蛋白易位中可能发生的各种问题，对治疗性蛋白质产生和聚集蛋白相关疾病有很大影响。拟议的工作将绘制生物信息流，通过参与反应的许多基因，以实现对普遍定期审议的理解，并确定改变反应的目标。利用现有的酵母生物相互作用数据，构建普遍定期审议生物相互作用网络。转录、蛋白质组学、代谢组学和代谢通量数据将收集重组酵母在调节UPR诱导下产生胰岛素前期和TNFa。从x组学数据中检测到的与UPR相关的生物分子水平变化将叠加到相互作用网络中，揭示UPR中的生物信息流。这种结合生物相互作用网络和x组学规模数据的信息将有助于更好地理解分泌蛋白的产生。特别是，代谢物测量可以指示糖基化途径、氨基酸供应、能量学、氧化还原平衡或脂质合成的可能限制。转录物和蛋白质水平可以揭示高水平蛋白质分泌的有利或不利途径。根据这些信息，重要的生物分子和相互作用可以作为改善蛋白质生产的靶标，并在人类中确定预防/治疗聚集蛋白相关疾病的靶标。本文的研究结果将有助于理解应激反应中的分子及其相互关系。该策略代表了一种理解复杂生物反应的多方面方法，与NIH构建模块、生物途径和网络路线图倡议一致。酵母是一种有吸引力的治疗性蛋白质的商业生产者，但可能受到产品产量低或质量差的限制，这些可以通过这项工作得到改善。全面了解普遍定期审议可能对预防和治疗已知与聚集蛋白有关的疾病产生影响，如阿尔茨海默氏症、2型糖尿病，以及某些癌症中抗凋亡、不受控制的蛋白质产生。