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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

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中文摘要
翻译
圣甲虫基因组公司的C-Flow™技术是一种高效的连续培养系统,可以生产 在仅仅10升的规模下,在几个星期内就可以获得1000公斤的蛋白质。这个项目将决定C-Flow是否可以 进一步发展成为生产单链抗体治疗药物的有效系统。 抗体片段,特别是单链变异体,在诊断和治疗中越来越重要 使用,如毒素和病毒中和,相对容易在大肠杆菌中生产,尽管效率很低 在目前的技术中。它们作为暴发和生物疗法的治疗方法具有巨大的潜在意义, 西非抗击埃博拉取得显著成功。其他抗体非常成功地用于治疗,例如 癌症和自身免疫性疾病。这些分子具有各种结构和适应症,但严重 制造方面的问题。缺乏糖基化,抗体片段在体内生存时间很短,需要多次 高剂量,导致令人望而却步的昂贵药物。因此,一种快速、高效和 低成本是迫切需要的。该项目将优化C-Flow生产三个结构不同的单 链片段抗体,以评价该方法的普遍适用性。目标是高表达 利用占地面积小的设备,以史无前例的规模持续生产。 抗体片段的正确折叠对功能至关重要。大肠埃希氏菌的表达和传递机制 发生蛋白质折叠的周质包括伴侣、信号序列和密码子使用以及 分发。这些机制将针对所有三个抗体片段进行优化。计算机的预测已经 揭示折叠缺陷的能力,这些缺陷可以通过基因工程来取代残基或区域来纠正 折得不好的东西。通过测试一种不强烈表达的示例免疫毒素,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。经过精心设计 将实施和评估计算机预测所建议的变化。这样一个集成的系统 软件和生产技术可以提供对生物紧急情况的快速反应,从爆发到 治疗准备好在几周内进行临床测试。具体目标是: 1.优化1升后10升C-Flow生产结构简单的抗体片段ScFv-SG1 将后者延长到至少30天,以评估持续产生抗体的情况。 2.优化生产更复杂的抗体片段scFabYMF10,如目标1所示,纯化 并通过检测ScFabYMF10与其靶抗原的结合来检测其功能。 3.提高抗体-毒素结合物B3Fv-PE40(在大肠杆菌中弱表达)的表达 生理学和基因工程方法。确定前期软件辅助设计是否 这种蛋白质可以用来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