Enabling high‐throughput biology with flexible open‐source automation
Name
msb.20209942.pdf
Description
Published version
Size
3.68 MB
Format
Adobe PDF
Checksum (MD5)
4227ffbc92fac1916ef8232df4e92614
Author(s)
Chory, Emma J
Gretton, Dana W
DeBenedictis, Erika A
Esvelt, Kevin M
Date Issued
2021
Journal
Molecular Systems Biology
Publisher
EMBO
Version
Final published version
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Massachusetts Institute of Technology. Department of Biological Engineering
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
10.15252/msb.20209942
https://doi.org/10.15252/msb.20209942
