Elucidating essential factors for production of recombinant secreted proteins through proteomics

哺乳动物细胞被用来生产有价值的治疗和工业蛋白质，如单克隆抗体、酶、细胞因子和疫苗。许多重要的蛋白质很难产生，因为它们不容易从细胞中分泌出来。该项目将破译控制蛋白质分泌的分子机制。了解这些机制将有助于制定蛋白质分泌工程和提高高价值蛋白质生产的策略。还将开发先进的机器学习方法来指导细胞工程。作为该项目的一部分，当地高中生将在一个以生物大数据分析为重点的暑期项目中接受培训。本项目将建立一种新的方法来鉴定和量化直接调节蛋白质分泌的宿主细胞分泌通路机制。主要重点将是单克隆抗体（mab）和相关的fc融合分子，对生物治疗行业至关重要。蛋白-蛋白相互作用（PPIs）将在单克隆抗体/相关蛋白和细胞分泌途径机制之间原位测量。这将使用接近生物素化和我们的fc介导的生物素化抗体识别（FcBAR）方法来完成。本项目将(1)建立一种测量分泌蛋白必需ppi的方法，并确定与分泌速率相关的ppi。该方法将应用于产生利妥昔单抗的CHO（中国仓鼠卵巢）细胞。(2)一种新的系统生物学分析方法将被应用于揭示PPI强度的变化如何影响分泌。这个计算框架将有助于确定相互作用蛋白质的作用，并优先考虑ppi的进一步研究。(3)这些相互作用因子的表达将被调节，以验证它们在mAb分泌中的作用。(4)最后，用于蛋白质分泌的产品特异性ppi与更一般的ppi将通过定量其他fc融合蛋白的ppi来确定，并比较不同分泌蛋白的分泌途径需要有多大差异。该项目开发的工具将指导宿主细胞工程用于多种蛋白质的生物制造，并将为哺乳动物分泌途径的功能提供深入的见解。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Mammalian cells are used to produce valuable therapeutic and industrial proteins, such as monoclonal antibodies, enzymes, cytokines and vaccines. Many important proteins are difficult to produce because they are not easily secreted from cells. This project will decipher the molecular mechanisms controlling protein secretion. Understanding these mechanisms will enable strategies for engineering protein secretion and improving production of high-value proteins. Advanced machine learning approaches will also be developed to guide cell engineering. As part of this project, local high school students will be trained in a summer program focused on biological big data analytics. This project will establish a novel method to identify and quantify the host cell secretory pathway machinery that directly regulates protein secretion. The primary focus will be on monoclonal antibodies (mAbs) and related Fc-fusion molecules of primary importance to the biotherapeutic industry. Protein-protein interactions (PPIs) will be measured in situ between the mAbs/related proteins and the cellular secretory pathway machinery. This will be done using proximity biotinylation with our Fc-mediated biotinylation by antibody recognition (FcBAR) method. This project will (1) establish a method for measuring essential PPIs for a secreted protein and identify PPIs correlating with secretion rate. This method will be applied to Rituximab-producing CHO (Chinese hamster ovary) cells. (2) A novel systems biology analysis approach will be applied to unravel how changes in PPI strength impact secretion. This computational framework will help define roles of interacting proteins and prioritize PPIs for further study. (3) Expression of these interaction factors will be modulated to validate their role in mAb secretion. (4) Finally, product-specific vs. more general PPIs used for protein secretion will be identified by quantifying PPIs for additional Fc-fusion proteins and comparing how much the secretory pathway needs differ across secreted proteins. The tools developed by this project will guide host cell engineering for biomanufacturing of diverse proteins and will provide deep insights into the functions of the mammalian secretory pathways.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.