An Open-Source Framework for Automated High-Throughput Cell Biology Experiments - Katunin, Pavel; Zhou, Jianbo; Shehata, Ola M.; Peden, Andrew A.; Cadby, Ashley; Nikolaev, Anton (Frontiers in Cell and Developmental Biology, 2021)
Modern data analysis methods such as optimisation algorithms or deep learning have been successfully applied to a number of biotechnological and medical questions. For these methods to be efficient, a large number of high quality and reproducible experiments needs to be conducted requiring a high degree of automation. Here we present an open-source hardware and low-cost framework that allows for automatic high-throughput generation of large amounts of cell biology data. Our design consists of an epifluorescent microscope with automated XY-stage for moving a multiwell plate containing cells and a perfusion manifold allowing programmed application of up to 8 different solutions. Our system is very flexible and can be adapted easily for individual experimental needs. To demonstrate the utility of the system we have used it to perform high-throughput Ca2+ imaging and large-scale fluorescent labelling experiments.