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An open-source FACS automation system for high-throughput cell biology.
Wiener, Diane M; Huynh, Emily; Jeyakumar, Ilakkiyan; Bax, Sophie; Sama, Samia; Cabrera, Joana P; Todorova, Verina; Vangipuram, Madhuri; Vaid, Shivanshi; Otsuka, Fumitaka; Sakai, Yoshitsugu; Leonetti, Manuel D; Gómez-Sjöberg, Rafael.
Affiliation
  • Wiener DM; Chan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
  • Huynh E; Chan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
  • Jeyakumar I; Chan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
  • Bax S; Chan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
  • Sama S; Chan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
  • Cabrera JP; Chan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
  • Todorova V; Chan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
  • Vangipuram M; Chan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
  • Vaid S; Chan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
  • Otsuka F; Medical Business Group, Sony Corporation, San Jose, California, United States of America.
  • Sakai Y; Medical Business Group, Sony Corporation, San Jose, California, United States of America.
  • Leonetti MD; Chan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
  • Gómez-Sjöberg R; Chan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
PLoS One ; 19(3): e0299402, 2024.
Article in En | MEDLINE | ID: mdl-38512845
ABSTRACT
Recent advances in gene editing are enabling the engineering of cells with an unprecedented level of scale. To capitalize on this opportunity, new methods are needed to accelerate the different steps required to manufacture and handle engineered cells. Here, we describe the development of an integrated software and hardware platform to automate Fluorescence-Activated Cell Sorting (FACS), a central step for the selection of cells displaying desired molecular attributes. Sorting large numbers of samples is laborious, and, to date, no automated system exists to sequentially manage FACS samples, likely owing to the need to tailor sorting conditions ("gating") to each individual sample. Our platform is built around a commercial instrument and integrates the handling and transfer of samples to and from the instrument, autonomous control of the instrument's software, and the algorithmic generation of sorting gates, resulting in walkaway functionality. Automation eliminates operator errors, standardizes gating conditions by eliminating operator-to-operator variations, and reduces hands-on labor by 93%. Moreover, our strategy for automating the operation of a commercial instrument control software in the absence of an Application Program Interface (API) exemplifies a universal solution for other instruments that lack an API. Our software and hardware designs are fully open-source and include step-by-step build documentation to contribute to a growing open ecosystem of tools for high-throughput cell biology.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2024 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2024 Document type: Article Affiliation country: