Enabling high‐throughput biology with flexible open‐source automation

Autor: Emma J. Chory, Kevin M. Esvelt, Erika A. DeBenedictis, Dana W Gretton
Rok vydání: 2021
Předmět:
Medicine (General)
QH301-705.5
Systems biology
bioautomation
Methods & Resources
Biology
Article
General Biochemistry
Genetics and Molecular Biology
Automation
03 medical and health sciences
R5-920
0302 clinical medicine
Software
liquid‐handling
Metabolomics
Biomanufacturing
Biology (General)
Throughput (business)
High throughput biology
030304 developmental biology
computer.programming_language
robotics
0303 health sciences
General Immunology and Microbiology
business.industry
Applied Mathematics
systems biology
Articles
high‐throughput biology
Python (programming language)
Living systems
Computational Theory and Mathematics
Embedded system
Metabolome
Synthetic Biology & Biotechnology
General Agricultural and Biological Sciences
business
computer
030217 neurology & neurosurgery
Information Systems
Zdroj: Molecular Systems Biology
Molecular Systems Biology, Vol 17, Iss 3, Pp n/a-n/a (2021)
ISSN: 1744-4292
Popis: Our understanding of complex living systems is limited by our capacity to perform experiments in high throughput. While robotic systems have automated many traditional hand‐pipetting protocols, software limitations have precluded more advanced maneuvers required to manipulate, maintain, and monitor hundreds of experiments in parallel. Here, we present Pyhamilton, an open‐source Python platform that can execute complex pipetting patterns required for custom high‐throughput experiments such as the simulation of metapopulation dynamics. With an integrated plate reader, we maintain nearly 500 remotely monitored bacterial cultures in log‐phase growth for days without user intervention by taking regular density measurements to adjust the robotic method in real‐time. Using these capabilities, we systematically optimize bioreactor protein production by monitoring the fluorescent protein expression and growth rates of a hundred different continuous culture conditions in triplicate to comprehensively sample the carbon, nitrogen, and phosphorus fitness landscape. Our results demonstrate that flexible software can empower existing hardware to enable new types and scales of experiments, empowering areas from biomanufacturing to fundamental biology.
An open‐source Python platform enables advanced liquid handling robots to perform a variety of complex high‐throughput experiments that could never be performed manually.
Databáze: OpenAIRE
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