Systems Analysis of the Unfolded Protein response in Saccharomyces cerevisiae

描述(申请人提供)：未折叠蛋白反应(UPR)是对真核生物中错误折叠的蛋白质的大规模、协调反应。单元格并行协调的不同操作集(约为了缓解蛋白质合成、折叠、糖基化以及膜结合和分泌蛋白质的移位中可能出现的各种问题(酵母中的380个基因)，对治疗性蛋白质生产和聚集性蛋白质相关疾病有很大影响。拟议的工作将绘制通过参与反应的许多基因的生物信息流，以实现对普遍定期审议的理解，并确定改变反应的目标。根据现有的酵母生物相互作用数据，将构建UPR的生物相互作用网络。将收集转录、蛋白质组、代谢组和代谢通量数据，用于生产胰岛素原和TnFa的重组酵母，并调节UPR诱导。从X-组学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的信息和X-组学规模的数据的结合将导致对分泌蛋白生产的更好理解。特别是，代谢物测量可以指出糖基化途径、氨基酸供应、能量、氧化还原平衡或脂质合成方面的可能限制。转录本和蛋白质水平可能揭示有利于或削弱蛋白质高水平分泌的途径。根据这些信息，可以针对重要的生物分子和相互作用来提高蛋白质产量，并在人类中确定预防/治疗聚集蛋白相关疾病的目标。这项拟议工作的发现将非常有助于理解与应激反应有关的分子及其相互联系。这一战略代表了一种多方面的方法来理解复杂的生物反应，并与NIH积木、生物路径和网络路线图倡议一致。酵母是一种很有吸引力的治疗性蛋白质的商业生产商，但可能会受到产品产量低或质量差的限制，这些都可以通过这项工作来改进。对UPR的透彻理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，如阿尔茨海默氏症、2型糖尿病，以及某些癌症中抗凋亡、不受控制的蛋白生产。

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.