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: 7650722
• 负责人: Keith Edward Jaggard Tyo
• 金额: $ 0.79万
• 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/7650722
• 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; 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

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. UPRassociated 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.

未折叠蛋白反应（UPR）是一种大规模的协调反应，以纠正错误折叠的蛋白质， 真核生物一个细胞并行协调的不同动作集（大约）。酵母中的380个基因）来缓解 在蛋白质合成、折叠、糖基化和转运中可能发生的各种问题， 膜结合和分泌的蛋白质对治疗性蛋白质的产生具有很大的影响， 聚集蛋白相关疾病。拟议的工作将绘制生物信息流通过 许多基因参与的反应，以实现对普遍定期审议的理解，并确定目标， 改变反应。普遍定期审议的生物相互作用网络将利用现有的 酵母的生物相互作用数据。转录、蛋白质组学、代谢组学和代谢通量数据将在 收集产生具有调节的UPR诱导的前胰岛素和TNF α的重组酵母。UPR相关 从X-omics数据检测到的生物分子水平的变化将叠加到 互动网络，揭示普遍定期审议中生物信息的流动。的这种组合 来自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 分泌蛋白质生产。特别是，代谢物测量可以表明代谢物可能存在的限制。 糖基化途径、氨基酸供应、能量学、氧化还原平衡或脂质合成。转录物和 蛋白质水平可以揭示有益于或有损于蛋白质高水平分泌的途径。从这个 信息，重要的生物分子和相互作用可以被靶向以提高蛋白质生产 并在人类中鉴定预防/治疗聚集蛋白相关疾病的靶点。的调查结果 所提出的工作将非常有助于理解分子及其相互联系， 应激反应这一策略代表了一种多方面的方法来理解一个复杂的生物学过程。 响应，并与NIH构建模块，生物途径和网络路线图一致 倡议酵母是治疗性蛋白质的有吸引力的商业生产者，但可能受到低浓度的限制。 产品产量或质量差，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性 蛋白质，如阿尔茨海默氏症，2型糖尿病，和抗糖尿病，不受控制的蛋白质生产， 某些癌症。