15 NSFBIO: Rewritable biocomputers in mammalian cells

15 NSFBIO：哺乳动物细胞中的可重写生物计算机

• 批准号: BB/P011926/1
• 负责人: Declan Bates
• 金额: $ 37.96万
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FP011926%2F1
• 关键词: 15; NSFBIO; Rewritable; biocomputers; mammalian

A major objective in synthetic biology is to achieve the ability to predictably design and construct genetic circuits to control cellular functions. Although recent years have seen numerous advances towards this goal, the sophistication, performance and scale of mammalian genetic circuits trail their microbial counterparts. The overarching goal of this proposal is to develop a suite of versatile gene expression tools and to use these tools to construct a genetic biocomputation platform with rewritable memory capability in mammalian cells. The memory feature is crucial to allow for permanent responses to transient or conditional signals, and has direct applications in protein production and tissue-specific gene expression. Moreover, genetic circuits with memory capabilities allow recordings of past events in complex environments where continuous monitoring is not feasible. For instance, E. coli engineered with a memory circuit have been placed inside a mouse gut to sense and remember drug exposure.

合成生物学的一个主要目标是实现可预测地设计和构建遗传回路来控制细胞功能的能力。尽管近年来在实现这一目标方面取得了许多进展，但哺乳动物遗传回路的复杂性、性能和规模都落后于它们的微生物同类。本课题的总体目标是开发一套通用的基因表达工具，并利用这些工具在哺乳动物细胞中构建具有可重写记忆能力的遗传生物计算平台。记忆特征对于瞬时或条件信号的永久反应至关重要，并且在蛋白质生产和组织特异性基因表达中有直接应用。此外，具有记忆能力的基因回路允许在复杂环境中记录过去的事件，而连续监测是不可行的。例如，将带有记忆回路的大肠杆菌放置在老鼠的肠道内，以感知和记忆药物暴露。

项目成果

Mechanistic modelling of tyrosine recombination reveals key parameters determining the performance of a CAR T cell switching circuit.

• DOI: 10.1049/enb.2019.0020
• 发表时间: 2020-03
• 期刊: Engineering biology

A mechanistic model of the BLADE platform predicts performance characteristics of 256 different synthetic DNA recombination circuits.

• DOI: 10.1371/journal.pcbi.1007849
• 发表时间: 2020-12
• 期刊: PLoS computational biology
• 影响因子: 4.3
• 作者: Bowyer JE;Ding C;Weinberg BH;Wong WW;Bates DG
• 通讯作者: Bates DG