Systems Analysis of the Unfolded Protein response in Saccharomyces cerevisiae

未折叠蛋白反应(UPR)是一种大规模的、协调的反应，以纠正错误折叠的蛋白质在 真核生物。单元格并行协调的不同操作集(约酵母中的380个基因)来缓解 在蛋白质合成、折叠、糖基化和转位过程中可能出现的各种问题 膜结合和分泌蛋白对治疗性蛋白的产生和分泌有很大影响 聚集性蛋白相关疾病。拟议的工作将绘制生物信息流通过 许多基因参与了反应，以实现对UPR的理解并确定靶点 改变回应。将从现有资源中构建普遍定期审议的生物互动网络 酵母的生物相互作用数据。转录、蛋白质组、代谢组和代谢流量数据将 收集的重组酵母通过调节UPR诱导产生前胰岛素和TNFa。UPR关联 从X组学数据中检测到的生物分子水平的变化将叠加到 相互作用网络，揭示了生物信息流在UPR中的流动。这一组合 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 分泌蛋白质的生产。特别是，代谢物测量可以指出在 糖基化途径、氨基酸供应、能量、氧化还原平衡或脂质合成。文字记录和 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。由此 可以针对信息、重要的生物分子和相互作用来提高蛋白质产量 并且，在人类身上，确定预防/治疗聚集蛋白相关疾病的目标。调查结果： 建议的工作将非常有助于理解分子及其相互联系涉及的 压力反应。这一策略代表了一种多方面的方法来理解复杂的生物学 响应，并与NIH构建块、生物路径和网络路线图一致 主动权。酵母是一种有吸引力的治疗性蛋白质的商业生产者，但它的局限性是低 可以通过这项工作改进的产品产量或质量较差。全面了解普遍定期审议 可能对已知与聚合相关的疾病的预防和治疗产生影响 蛋白质，如阿尔茨海默氏症，2型糖尿病，以及抗凋亡的，不受控制的蛋白质产生 某些癌症。

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.