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Production of antibody therapeutic fragments by reduced genome E. coli in continuous culture

Production of antibody therapeutic fragments by reduced genome E. coli in continuous culture
在连续培养中通过减少基因组大肠杆菌生产抗体治疗片段
批准号:
10215525
负责人:
FREDERICK R BLATTNER
金额:
$94.45万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-07-13 至 2023-06-30

项目摘要

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中文摘要
翻译
Scarab Genomics的C-Flow™技术是一种高效的连续培养系统, 在短短几周内就能生产出10公斤的蛋白质。该项目将决定C-Flow是否可以 进一步发展为生产单链抗体治疗剂的有效系统。 抗体片段,特别是单链变体,对于诊断和治疗越来越重要。 应用如毒素和病毒中和,在E.大肠杆菌,尽管效率很低, 在当前的技术中。它们作为疾病爆发和生物威胁的疗法具有巨大的潜在意义, 在西非抗击埃博拉病毒取得显著成功。其他抗体对于例如以下疾病的治疗是非常成功的: 癌症和自身免疫性疾病。这些分子具有多种结构和适应症, 制造业的问题。由于缺乏糖基化,抗体片段在体内的寿命很短,需要多次糖基化。 高剂量,导致昂贵的药物。因此,快速、有效且 低成本是迫切需要的。该项目将优化三种结构不同的单一C-Flow生产 链片段抗体,以评估该方法的普遍适用性。目标是高表达 通过小型设备,实现了前所未有的高水平和可持续生产。 抗体片段的正确折叠对于功能至关重要。E.大肠杆菌的表达和传递机制, 蛋白质折叠发生的周质包括分子伴侣、信号序列和密码子使用, 分布这些机制将针对所有三种抗体片段进行优化。计算机预测 揭示折叠缺陷的能力,这些缺陷可以通过基因工程来纠正,以取代残基或区域 折叠不好的。通过测试不强烈表达的示例性免疫毒素,可以确定使用 将探索用于提高可制造性的合理抗体设计的软件预测。工程化 将实施和评估计算机预测所建议的变化。这样一个完整的系统, 软件和生产技术可以对生物紧急情况作出快速反应,从爆发到 几周后就可以进行临床试验了具体目标是: 1.优化结构简单的抗体片段scFv-SG 1的生产,在1升和10升C-Flow中进行 规模,后者延长到至少30天,以评估连续的抗体生产。 2.根据目标1优化结构更复杂的抗体片段scFabYMF 10的生产,纯化 抗体,并通过评估scFabYMF 10与其靶抗原的结合来测试其功能。 3.增强抗体-毒素缀合物B3 Fv-PE 40(在E.大肠杆菌), 生理和基因工程方法。确定是否需要预先的软件辅助设计 该蛋白质可用于预测改进的可制造性。
英文摘要
Scarab Genomics’ C-Flow™ technology is a highly efficient continuous culture system that can produce kilograms of protein in a few weeks at a mere 10-liter scale. This project will determine whether C-Flow can be further developed as an efficient system for production of single-chain antibody therapeutics. Antibody fragments, especially single-chain variants, are increasingly important for diagnostic and therapeutic use such as toxin and virus neutralization, being relatively easy to manufacture in E. coli, albeit very inefficiently in current techniques. They are of great potential significance as therapies for outbreaks and biothreats, with notable success against Ebola in West Africa. Other antibodies are remarkably successful for e.g. treatment of cancer and autoimmune diseases. These molecules have a variety of structures and indications but severe problems in manufacturing. Lacking glycosylation, antibody fragments are short-lived in vivo, requiring multiple high doses, leading to prohibitively expensive drugs. Therefore, a method of production that is fast, efficient, and low in cost is critically needed. This project will optimize C-Flow production of three structurally distinct single chain fragment antibodies, to evaluate the general applicability of the approach. The goal is high expression levels and sustained production on an unprecedented scale with small-footprint equipment. Correct folding of antibody fragments is critical for function. E. coli mechanisms for expression and delivery into the periplasm, where protein folding occurs, include chaperones, signal sequences, and codon usage and distribution. These mechanisms will be optimized for all three antibody fragments. Computer predictions have the power to reveal folding defects that could be corrected by genetic engineering to replace residues or regions that do not fold well. By testing an example immunotoxin that does not express strongly, the possibility of using software predictions for rational antibody design for increased manufacturability will be explored. Engineered changes suggested by computer predictions will be implemented and evaluated. Such an integrated system of software and production technology could provide a rapid response to a bio-emergency, going from outbreak to therapeutic ready for clinical testing in weeks. The Specific Aims are: 1. Optimize production of a structurally simple antibody fragment, scFv-SG1, at 1-liter then 10-liter C-Flow scales, extending the latter to at least 30 days to evaluate continuous antibody production. 2. Optimize production of a more structurally complex antibody fragment, scFabYMF10 as per Aim 1, purify the antibody and test its function by evaluating scFabYMF10 binding to its target antigen. 3. Enhance expression of the antibody-toxin conjugate B3Fv-PE40 (poorly expressed in E. coli) using physiological and genetic engineering approaches. Determine whether up-front software-assisted design of the protein can be used to predict improved manufacturability.
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Software for the complete characterization of antibody repertoires: from germline and mRNA sequence assembly to deep learning predictions of their protein structures and targets
  • 批准号:
    10699546
  • 项目类别:
  • 资助金额:
    $64.88万
  • 财政年份:
    2023
  • 负责人:
    FREDERICK R BLATTNER
  • 依托单位:
Production of antibody therapeutic fragments by reduced genome E. coli in continuous culture
  • 批准号:
    10081714
  • 项目类别:
  • 资助金额:
    $100.0万
  • 财政年份:
    2020
  • 负责人:
    FREDERICK R BLATTNER
  • 依托单位:
Rapid structure-based software to enhance antibody affinity and developability for high-throughput screening: Aiming toward total in silico design of antibodies
  • 批准号:
    10603473
  • 项目类别:
  • 资助金额:
    $100.0万
  • 财政年份:
    2020
  • 负责人:
    FREDERICK R BLATTNER
  • 依托单位:
Rapid structure-based software to enhance antibody affinity and developability for high-throughput screening
  • 批准号:
    10385733
  • 项目类别:
  • 资助金额:
    $99.87万
  • 财政年份:
    2020
  • 负责人:
    FREDERICK R BLATTNER
  • 依托单位:
海外基金