Development of a robotic directed evolution approach to whole cell biosensor production

全细胞生物传感器是经过重新设计的单细胞生物体，可以检测和响应环境中的元素。全细胞生物传感器可以通过以可检测的方式进行响应来测量各种分子的存在，例如通过产生荧光或有色色素。精确测量分子靶标的能力在医疗诊断和环境监测等领域中被广泛要求。与现有的检测方法相比，全细胞生物传感器具有成本低、可自我复制和可生物降解等优点。这些特性将使全细胞生物传感器适合于现场测试和护理点诊断，包括在资源有限的地方。本研究的目的是创建一种基于微流体的平台，与工程生物传感器支架相结合，可以应用于工程和生产适应不同目标的全细胞生物传感器。这将通过三个跨学科和互补的研究目标来实现。我们的第一个目标是将合成生物工程应用于细菌，以创造一种模块化设计的生物传感器，在这种传感器中，传感元件可以针对新的目标进行“切割和改变”，而不需要重新设计整个系统。这将利用过去模块化生物传感器的工程，这表明以模块化方式重新利用纳米物体作为传感元件是可能的。我们的工作将同样利用物理和计算管道来设计和修改纳米实体的目标，这些目标已经建立得很好，使纳米实体成为创建可重新定位的感应域的一个特别有希望的起点。我们的第二个目标将采用设计的纳米实体生物传感器，并应用最先进的定向进化技术来优化它们作为生物传感器的功能，以及在需要时将它们重新定向到替代目标。我们的方法将结合机器人显微镜和微流控技术，这使得有可能在单个细胞水平上观察整个细胞生物传感器的更长时间段，包括它们对时变刺激的反应。通过这种方法，还可以向单个细胞传递光信号，以便从大型工程变种库中选择表现最好的例子。反复向细胞传递“存活”或“死亡”信号的过程将被用来驱动大型文库实现预期的性能：在这种情况下，对重要的生物目标进行敏感和特定的检测。最后，第三个目标将是应用模块化纳米体设计和基于显微镜的工程平台来构建新型的全细胞生物传感器，特别关注开发高度特异和可靠的生物传感器作为低成本和可访问的诊断平台。该项目属于EPSRC的医疗保健技术和工程研究领域。该项目直接解决围绕疾病预测、诊断和干预的优化的挑战是四大挑战之一。在工程学领域，该项目的跨学科重点位于EPSRC研究领域“合成生物学”和“机器人学”的交汇点。

Whole cell biosensors are single-celled organisms that have been re-engineered to detect and respond to elements of their environment. Whole cell biosensors can be used to measure the presence of various molecules by responding in a detectable way, for instance by production of fluorescence or a colored pigment. The ability to accurately measure molecular targets is required broadly in fields including medical diagnostics and environmental monitoring. When compared to existing detection methods, whole cell biosensors are advantageous in that they are low-cost, self-replicating and bio-degradable. These properties would make whole cell biosensors suitable for field-testing and point-of-care diagnostics, including in resource limited locations.The aim of this research is to create a microfluidics-based platform, coupled to engineered biological biosensor scaffolds, that can be applied for engineering and producing whole cell biosensors that are adaptable to different targets. This will be achieved via three interdisciplinary and complementary research objectives. Our first objective will apply synthetic biological engineering in bacteria to create a modularly designed biosensor in which the sensing element can be 'chopped and changed' for new targets without re-engineering the entire system. This will leverage past engineering of modular biosensors, which demonstrate it is possible to re-purpose nanobodies as sensing elements in a modular fashion. Our work will similarly leverage physical and computational pipelines for designing and modifying the targets of nanobodies, which are well-established, making nanobodies a particularly promising starting point for creating for re-targetable sensing domains.Our second objective will take designed nanobody biosensors and apply state-of-the-art directed evolution technology to optimise their functionality as biosensors, as well as to re-direct them to alternative targets when desired. Our approach will combine a robotic microscope and microfluidics, which make it possible to observe whole cell biosensors for extended periods of time at the level of individual cells, including their response to time varying stimuli. Via such an approach it is also possible to deliver light signals to individual cells to select the best performing examples out of large libraries of engineered variants. The process of iteratively delivering 'survive' or 'die' signals to cells will be used to drive large libraries toward desired performance: in this case sensitive and specific detection of important biological targets.Finally, the third objective will be to apply the modular nanobody designs and microscope based engineering platform to build novel whole cell biosensors, with a particular focus on developing highly specific and reliable biosensors as a low-cost and accessible diagnostics platform.This project falls within the EPSRC 'Healthcare Technologies' and 'Engineering' research areas.Within Healthcare it directly addresses challenges surrounding optimisation of disease prediction, diagnosis and intervention is one of the four grand challenges. Within Engineering the project's interdisciplinary focus lies at the intersection of the EPSRC Research Areas "Synthetic Biology" and "Robotics"