BIOS: The bio-intelligent DBTL cycle, a key enabler catalysing the industrial transformation towards sustainable biomanufacturing

BIOS：生物智能 DBTL 循环，是催化工业向可持续生物制造转型的关键推动者

• 批准号: 10041365
• 金额: $ 65.06万
• 依托单位: INGENZA LIMITED
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10041365
• 关键词: BIOS; bio; intelligent; DBTL; cycle

The usage of fossil resources leading to increasing atmospheric CO2 levels and global climate change should be rapidly replaced by implementing a circular economy. Circular bioeconomy converting sustainable substrates in moderately operating bioprocesses offers a plenitude of solutions. While synthetic biology provides a multitude of tools for strain engineering, their rapid use in hosts for optimal performance under industrial conditions is still challenging. Promising innovations are often trapped in the ‘valley-of-death’ as strain engineering faces a too complex space of putative manipulations. Novel approaches are needed to increase speed and success rate of strain and bioprocess engineering. The bio-intelligent approach, rigorously applied in BIOS, aims to accelerate and improve the conventional ‘design-build-test-learn’ (DBTL) cycle for strain and bioprocess engineering. Interdisciplinary collaboration will bridge microbiology, molecular biology, biochemical engineering with informatics, automation engineering, and mechanical engineering. Novel innovative metrics, biosensors, and bioactuators are developed for bi-directionally communication at biological-technical interfaces. Digital twins are created mimicking cellular and process levels. Integrating AI not only improves prediction quality but also enables hybrid learning, the key reason to increase speed and success rate in the novel bio-intelligent DBTL cycle (biDBTL). The power of biDBTL will be showcased by creating P. putida producer strains for terpenes, polyolefines, and methylacrylate. All are highly attractive products with a high potential for reducing anthropogenic greenhouse footprint. BIOS will open the door to a de-centralized, networked collaboration for strain and process engineering that efficiently links individual expertise for the sake of a symbiotic and rapid progress. BIOS also paves the way to de-centralized bio-manufacturing by implementing autonomous, self-controlled bioprocesses.

化石资源的使用导致大气中二氧化碳含量增加和全球气候变化，应通过实施循环经济来迅速取代，在适度运行的生物过程中转化可持续基质提供了多种解决方案，而合成生物学则提供了多种应变工具。工程方面，它们在工业条件下的最佳性能宿主中的快速使用仍然具有挑战性，因为应变工程面临着过于复杂的假定操作空间，因此有前途的创新常常陷入“死亡之谷”。提高菌株和生物过程工程的速度和成功率。BIOS 中严格应用的生物智能方法旨在加速和改进菌株和生物过程工程的传统“设计-构建-测试-学习”(DBTL) 周期。合作将微生物学、分子生物学、生物化学工程与信息学、自动化工程和机械工程联系起来，开发新的创新指标、生物传感器和生物执行器，用于生物技术接口的双向通信。数字孪生是模仿细胞和过程水平而创建的，集成人工智能不仅可以提高预测质量，还可以实现混合学习，这是提高新型生物智能 DBTL 循环 (biDBTL) 速度和成功率的关键原因。通过创建萜烯、聚烯烃和丙烯酸甲酯生产菌株来展示所有这些都是极具吸引力的产品，具有减少人为温室足迹的巨大潜力。 BIOS 还通过实现自主、自我控制的生物过程，为分散的生物制造铺平了道路。