Automation of protein crystallization scaleup via Opentrons-2 liquid handling

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 script...

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Main Authors: Jacob B. DeRoo, Alec A. Jones, Caroline K. Slaughter, Tim W. Ahr, Sam M. Stroup, Grace B. Thompson, Christopher D. Snow
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:SLAS Technology
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Online Access:http://www.sciencedirect.com/science/article/pii/S2472630325000263
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author Jacob B. DeRoo
Alec A. Jones
Caroline K. Slaughter
Tim W. Ahr
Sam M. Stroup
Grace B. Thompson
Christopher D. Snow
author_facet Jacob B. DeRoo
Alec A. Jones
Caroline K. Slaughter
Tim W. Ahr
Sam M. Stroup
Grace B. Thompson
Christopher D. Snow
author_sort Jacob B. DeRoo
collection DOAJ
description 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
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institution Kabale University
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publishDate 2025-06-01
publisher Elsevier
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series SLAS Technology
spelling doaj-art-de00d45ef6cb4701a60ef1dea25938df2025-08-20T03:39:57ZengElsevierSLAS Technology2472-63032025-06-013210026810.1016/j.slast.2025.100268Automation of protein crystallization scaleup via Opentrons-2 liquid handlingJacob B. DeRoo0Alec A. Jones1Caroline K. Slaughter2Tim W. Ahr3Sam M. Stroup4Grace B. Thompson5Christopher D. Snow6School of Biomedical Engineering, Colorado State University, United States of AmericaSchool of Biomedical Engineering, Colorado State University, United States of AmericaDepartment of Cellular and Molecular Biology, Colorado State University, United States of AmericaDepartment of Chemical Engineering, Colorado State University, United States of AmericaDepartment of Chemistry, Colorado State University, United States of AmericaSchool of Biomedical Engineering, Colorado State University, United States of America; Department of Electrical Engineering, Colorado State University, United States of AmericaSchool of Biomedical Engineering, Colorado State University, United States of America; Department of Cellular and Molecular Biology, Colorado State University, United States of America; Department of Chemical Engineering, Colorado State University, United States of America; Department of Chemistry, Colorado State University, United States of America; Corresponding author.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-Crystallizationhttp://www.sciencedirect.com/science/article/pii/S2472630325000263Liquid handlingProtein crystallizationCrystallographySitting drop crystallization
spellingShingle Jacob B. DeRoo
Alec A. Jones
Caroline K. Slaughter
Tim W. Ahr
Sam M. Stroup
Grace B. Thompson
Christopher D. Snow
Automation of protein crystallization scaleup via Opentrons-2 liquid handling
SLAS Technology
Liquid handling
Protein crystallization
Crystallography
Sitting drop crystallization
title Automation of protein crystallization scaleup via Opentrons-2 liquid handling
title_full Automation of protein crystallization scaleup via Opentrons-2 liquid handling
title_fullStr Automation of protein crystallization scaleup via Opentrons-2 liquid handling
title_full_unstemmed Automation of protein crystallization scaleup via Opentrons-2 liquid handling
title_short Automation of protein crystallization scaleup via Opentrons-2 liquid handling
title_sort automation of protein crystallization scaleup via opentrons 2 liquid handling
topic Liquid handling
Protein crystallization
Crystallography
Sitting drop crystallization
url http://www.sciencedirect.com/science/article/pii/S2472630325000263
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