Elucidating essential factors for production of recombinant secreted proteins through proteomics

通过蛋白质组学阐明生产重组分泌蛋白的重要因素

• 批准号: 2030039
• 负责人: Nathan Lewis
• 金额: $ 67万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2030039&HistoricalAwards=false
• 关键词: Elucidating; essential; factors; production; recombinant

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.

哺乳动物细胞用于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生产，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。了解这些机制将使工程蛋白质分泌和提高高价值蛋白质的生产策略成为可能。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，当地高中生将参加一个专注于生物大数据分析的暑期课程。本项目将建立一种新的方法来鉴定和定量直接调节蛋白质分泌的宿主细胞分泌途径机制。主要重点将放在单克隆抗体（mAb）和相关的Fc融合分子的生物制药行业的首要重要性。将原位测量mAb/相关蛋白与细胞分泌途径机制之间的蛋白质-蛋白质相互作用（PPI）。这将使用邻近生物素化与我们的Fc介导的抗体识别生物素化（FcBAR）方法来完成。本项目将（1）建立分泌蛋白的必需PPI的测定方法，并鉴定与分泌率相关的PPI。该方法将应用于生产利妥昔单抗的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解开PPI强度的变化如何影响分泌。这种计算框架将有助于定义相互作用蛋白质的作用，并优先考虑PPI的进一步研究。(3)将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，将通过定量其他Fc融合蛋白的PPI并比较不同分泌蛋白的分泌途径需求差异来鉴定用于蛋白分泌的产品特异性PPI与更通用PPI。该项目开发的工具将指导多种蛋白质生物制造的宿主细胞工程，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NSF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。