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性和工业蛋白质，如单抗、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。了解这些机制将使设计蛋白质分泌和提高高价值蛋白质生产的策略成为可能。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专注于生物大数据分析的暑期项目中接受培训。该项目将建立一种新的方法来识别和量化直接调节蛋白质分泌的宿主细胞分泌途径机制。主要焦点将放在对生物治疗行业至关重要的单抗(MAbbs)和相关的Fc融合分子上。蛋白质-蛋白质相互作用(PPI)将在mAbs/相关蛋白质和细胞分泌途径机制之间进行原位测量。这将使用我们的FC介导的抗体识别生物素化(FcBAR)方法进行邻近生物素化。这个项目将(1)建立一种测量分泌蛋白质的基本PPI的方法，并确定与分泌速度相关的PPI。这种方法将应用于生产利妥昔单抗的CHO(中国仓鼠卵巢)细胞。(2)将应用一种新的系统生物学分析方法来揭示PPI强度的变化如何影响分泌。这一计算框架将有助于确定相互作用蛋白质的作用，并为进一步研究确定PPI的优先顺序。(3)调节这些相互作用因子的表达，以验证它们在mAb分泌中的作用。(4)最后，通过对额外的Fc融合蛋白的PPI进行量化，并比较不同分泌蛋白对分泌途径的需求差异，将确定用于蛋白质分泌的特定产品PPI与更一般的PPI。该项目开发的工具将指导宿主细胞工程以制造不同的蛋白质，并将提供对哺乳动物分泌途径功能的深入见解。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.