Evidence map›Paper›PMID 38512845›Full record

ArticlePloS one2024

An open-source FACS automation system for high-throughput cell biology.

Diane M Wiener, Emily Huynh, Ilakkiyan Jeyakumar, Sophie Bax, Samia Sama, Joana P Cabrera, Verina Todorova, Madhuri Vangipuram, Shivanshi Vaid, Fumitaka Otsuka and 3 more

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Diane M WienerChan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.ORCID 0000-0002-4063-1865
Emily HuynhChan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.ORCID 0009-0007-6620-0530
Ilakkiyan JeyakumarChan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.ORCID 0000-0002-6973-9167
Sophie BaxChan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
Samia SamaChan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
Joana P CabreraChan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
Verina TodorovaChan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.ORCID 0000-0002-3776-4253
Madhuri VangipuramChan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.ORCID 0000-0001-7271-2689
Shivanshi VaidChan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
Fumitaka OtsukaMedical Business Group, Sony Corporation, San Jose, California, United States of America.
Yoshitsugu SakaiMedical Business Group, Sony Corporation, San Jose, California, United States of America.
Manuel D LeonettiChan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.
Rafael Gómez-SjöbergChan Zuckerberg Biohub-San Francisco, San Francisco, California, United States of America.ORCID 0000-0001-8017-9669

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

SoftwareAutomationFlow Cytometry

Identifiers

PMID38512845
PMCPMC10956866

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.