Abstract
In this study we present an approach for optimizing protein crystallization trials at the multi-microliter scale utilizing the Opentrons-2 liquid handling robot. Our research demonstrates the robot's capability to automate 24-well sitting drop protein crystallization trials. Using Python scripts for precise control, the study explores the robot's application in mixing and setting up crystallization plates with a model protein (hen egg white lysozyme) and a periplasmic protein from Campylobacter jejuni, a crystal utilized in the Snow lab as a biomaterial for nanotechnology that requires large, consistent batches. In a head-to-head comparison with manual 24-well plate setup, crystal growth statistics indicate our approach can reduce manual labor and increase reliability in protein crystallization, and may also reduce variability, offering an economical and versatile tool for laboratories. This study shows facile adaption of the Opentrons interface and hardware for growth of two different crystal types. All developed liquid handling routines and relevant data files, in addition to demonstration videos are available at https://github.com/jbderoo/Opentrons2-Protein-Crystallization.