Journal article Open Access

An Open-Source Modular Framework for Automated Pipetting and Imaging Applications

Wei Ouyang; Richard Bowman; Haoran Wang; Kaspar Bumke; Joel Collins; Ola Spjuth; Jordi Carreras-Puigvert; Benedict Diederich


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    <subfield code="a">&lt;p&gt;The number of samples in biological experiments are continuously increasing, but complex protocols and human experimentation in many cases lead to suboptimal data quality and hence difficulties in reproducing scientific findings. Laboratory automation can alleviate many of these problems by precisely reproducing machine-readable protocols. Fully automated lab setups with multiple instruments generally require high up-front investments and due to proprietary systems and lack of open APIs they are notoriously difficult for scientists to customize and control outside of the vendor-supplied software. Here, we demonstrate automated, high-throughput experiments for interdisciplinary research in life science that can be replicated on a modest budget, using open tools to ensure reproducibility. We have combined the open-source projects Openflexure, Opentrons, ImJoy and UC2. Our fully automated sample preparation and imaging pipeline can easily be replicated and established in many laboratories as well as in educational contexts through easy-to-understand algorithms and easy-to-build microscopes. In addition, the creation of feedback loops, with later pipetting or imaging steps depending on analysis of previously acquired images, enables the realization of smart microscopy experiments, featuring completely autonomously performed experiments. We provide all building instructions, software, and protocols in publicly available repositories (&lt;a href="https://beniroquai.github.io/Hi2)"&gt;https://beniroquai.github.io/Hi2)&lt;/a&gt; to prove the concept of smart lab automation using inexpensive, open tools. We believe this democratizes access to the power and repeatability of automated experiments.&lt;/p&gt;</subfield>
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