Digi.Bio, Amsterdam, The Netherlands.
SLAS Technol. 2020 Oct;25(5):411-426. doi: 10.1177/2472630320931794. Epub 2020 Jun 25.
Digital microfluidics (DMF) is a liquid handling technique that has been demonstrated to automate biological experimentation in a low-cost, rapid, and programmable manner. This review discusses the role of DMF as a "digital bioconverter"-a tool to connect the digital aspects of the design-build-learn cycle with the physical execution of experiments. Several applications are reviewed to demonstrate the utility of DMF as a digital bioconverter, namely, genetic engineering, sample preparation for sequencing and mass spectrometry, and enzyme-, immuno-, and cell-based screening assays. These applications show that DMF has great potential in the role of a centralized execution platform in a fully integrated pipeline for the production of novel organisms and biomolecules. In this paper, we discuss how the function of a DMF device within such a pipeline is highly dependent on integration with different sensing techniques and methodologies from machine learning and big data. In addition to that, we examine how the capacity of DMF can in some cases be limited by known technical and operational challenges and how consolidated efforts in overcoming these challenges will be key to the development of DMF as a major enabling technology in the computer-aided biology framework.
数字微流控(DMF)是一种液体处理技术,已被证明能够以低成本、快速和可编程的方式实现生物实验的自动化。本文讨论了 DMF 作为“数字生物转化器”的作用,即一种将设计-构建-学习循环的数字方面与实验的物理执行联系起来的工具。本文回顾了几个应用案例,展示了 DMF 作为数字生物转化器的应用潜力,包括基因工程、测序和质谱样本制备,以及酶、免疫和基于细胞的筛选测定。这些应用表明,DMF 在新型生物和生物分子生产的全集成管道中作为集中执行平台具有巨大的潜力。在本文中,我们讨论了在这样的管道中,DMF 设备的功能高度依赖于与机器学习和大数据等不同传感技术和方法的集成。此外,我们还研究了在某些情况下,DMF 的容量可能会受到已知技术和操作挑战的限制,以及克服这些挑战的一致努力将是 DMF 作为计算机辅助生物学框架中的主要使能技术发展的关键。