IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v7y2016i1d10.1038_ncomms10256.html
   My bibliography  Save this article

Label-free cell cycle analysis for high-throughput imaging flow cytometry

Author

Listed:
  • Thomas Blasi

    (Imaging Platform at the Broad Institute of Harvard and MIT
    Helmholtz Zentrum München—German Research Center for Environmental Health, Institute of Computational Biology
    Technische Universität München)

  • Holger Hennig

    (Imaging Platform at the Broad Institute of Harvard and MIT)

  • Huw D. Summers

    (College of Engineering, Swansea University)

  • Fabian J. Theis

    (Helmholtz Zentrum München—German Research Center for Environmental Health, Institute of Computational Biology
    Technische Universität München)

  • Joana Cerveira

    (Flow Cytometry Facility, The Francis Crick Institute, Lincoln's Inn Fields Laboratory)

  • James O. Patterson

    (Cell Cycle Laboratory, The Francis Crick Institute)

  • Derek Davies

    (Flow Cytometry Facility, The Francis Crick Institute, Lincoln's Inn Fields Laboratory)

  • Andrew Filby

    (Newcastle Upon Tyne University, Faculty of Medical Sciences, Bioscience Centre, International Centre for life)

  • Anne E. Carpenter

    (Imaging Platform at the Broad Institute of Harvard and MIT)

  • Paul Rees

    (Imaging Platform at the Broad Institute of Harvard and MIT
    College of Engineering, Swansea University)

Abstract

Imaging flow cytometry combines the high-throughput capabilities of conventional flow cytometry with single-cell imaging. Here we demonstrate label-free prediction of DNA content and quantification of the mitotic cell cycle phases by applying supervised machine learning to morphological features extracted from brightfield and the typically ignored darkfield images of cells from an imaging flow cytometer. This method facilitates non-destructive monitoring of cells avoiding potentially confounding effects of fluorescent stains while maximizing available fluorescence channels. The method is effective in cell cycle analysis for mammalian cells, both fixed and live, and accurately assesses the impact of a cell cycle mitotic phase blocking agent. As the same method is effective in predicting the DNA content of fission yeast, it is likely to have a broad application to other cell types.

Suggested Citation

  • Thomas Blasi & Holger Hennig & Huw D. Summers & Fabian J. Theis & Joana Cerveira & James O. Patterson & Derek Davies & Andrew Filby & Anne E. Carpenter & Paul Rees, 2016. "Label-free cell cycle analysis for high-throughput imaging flow cytometry," Nature Communications, Nature, vol. 7(1), pages 1-9, April.
    • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms10256
    DOI: 10.1038/ncomms10256
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms10256
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/ncomms10256?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guocheng Fang & Zhen Qiao & Luqi Huang & Hui Zhu & Jun Xie & Tian Zhou & Zhongshu Xiong & I-Hsin Su & Dayong Jin & Yu-Cheng Chen, 2024. "Single-cell laser emitting cytometry for label-free nucleolus fingerprinting," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Dennis Pischel & Jörn H Buchbinder & Kai Sundmacher & Inna N Lavrik & Robert J Flassig, 2018. "A guide to automated apoptosis detection: How to make sense of imaging flow cytometry data," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-17, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms10256. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.