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Systems Analysis of the Unfolded Protein response in Saccharomyces cerevisiae

酿酒酵母未折叠蛋白反应的系统分析

基本信息

批准号：
7923466
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
项目类别：
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/7923466
关键词：
Accounting Affinity Alzheimer&apos 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 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 Suppressor Genes Systems Analysis Transcript United States National Institutes of Health Work Yeasts analytical method base biological adaptation to stress chromatin immunoprecipitation follow-up glycosylation improved metabolomics prevent promoter protein aggregate protein expression protein folding protein metabolite protein misfolding protein protein interaction protein transport research study response scaffold therapeutic protein

项目摘要

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。一个细胞并行协调的不同动作集（大约）。酵母中的380个基因），以减轻在膜结合和分泌蛋白的蛋白质合成、折叠、糖基化和易位中可能发生的各种问题，对治疗性蛋白质生产和聚集蛋白相关疾病具有很大影响。拟议的工作将通过参与反应的许多基因绘制生物信息流，以了解普遍定期审议并确定改变反应的目标。一个生物相互作用网络的普遍定期审议将构建从现有的酵母生物相互作用的数据。将收集产生前胰岛素和TNF α的重组酵母的转录、蛋白质组学、代谢组学和代谢通量数据，并调节UPR诱导。从X-omics数据中检测到的生物分子水平的UPR相关变化将叠加到相互作用网络上，揭示UPR中的生物信息流。这种来自生物相互作用网络和X组学规模数据的信息的组合将导致更好地理解分泌蛋白质的产生。特别地，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中的可能限制。转录和蛋白质水平可以揭示有益于或减损高水平蛋白质分泌的途径。从这些信息中，可以靶向重要的生物分子和相互作用，以改善蛋白质的产生，并在人类中，确定预防/治疗聚集蛋白相关疾病的靶点。这些发现将有助于理解应激反应中的分子及其相互联系。该策略代表了理解复杂生物反应的多方面方法，并与NIH构建模块，生物途径和网络路线图倡议一致。酵母是治疗性蛋白质的有吸引力的商业生产者，但可能受到产品产量低或质量差的限制，这可以通过这项工作来改善。对普遍定期审议的全面了解可能会对预防和治疗已知与聚集蛋白有关的疾病产生影响，例如阿尔茨海默氏症、2型糖尿病和某些癌症中的抗阿尔茨海默病、不受控制的蛋白质产生。