IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v597y2021i7877d10.1038_s41586-021-03887-4.html
   My bibliography  Save this article

Single-cell Ribo-seq reveals cell cycle-dependent translational pausing

Author

Listed:
  • Michael VanInsberghe

    (Oncode Institute, Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht)

  • Jeroen Berg

    (Oncode Institute, Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht)

  • Amanda Andersson-Rolf

    (Oncode Institute, Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht)

  • Hans Clevers

    (Oncode Institute, Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht)

  • Alexander Oudenaarden

    (Oncode Institute, Hubrecht Institute-KNAW (Royal Netherlands Academy of Arts and Sciences) and University Medical Center Utrecht)

Abstract

Single-cell sequencing methods have enabled in-depth analysis of the diversity of cell types and cell states in a wide range of organisms. These tools focus predominantly on sequencing the genomes1, epigenomes2 and transcriptomes3 of single cells. However, despite recent progress in detecting proteins by mass spectrometry with single-cell resolution4, it remains a major challenge to measure translation in individual cells. Here, building on existing protocols5–7, we have substantially increased the sensitivity of these assays to enable ribosome profiling in single cells. Integrated with a machine learning approach, this technology achieves single-codon resolution. We validate this method by demonstrating that limitation for a particular amino acid causes ribosome pausing at a subset of the codons encoding the amino acid. Of note, this pausing is only observed in a sub-population of cells correlating to its cell cycle state. We further expand on this phenomenon in non-limiting conditions and detect pronounced GAA pausing during mitosis. Finally, we demonstrate the applicability of this technique to rare primary enteroendocrine cells. This technology provides a first step towards determining the contribution of the translational process to the remarkable diversity between seemingly identical cells.

Suggested Citation

  • Michael VanInsberghe & Jeroen Berg & Amanda Andersson-Rolf & Hans Clevers & Alexander Oudenaarden, 2021. "Single-cell Ribo-seq reveals cell cycle-dependent translational pausing," Nature, Nature, vol. 597(7877), pages 561-565, September.
  • Handle: RePEc:nat:nature:v:597:y:2021:i:7877:d:10.1038_s41586-021-03887-4
    DOI: 10.1038/s41586-021-03887-4
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41586-021-03887-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/s41586-021-03887-4?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Wenqi Hu & Haitao Zeng & Yanan Shi & Chuanchuan Zhou & Jiana Huang & Lei Jia & Siqi Xu & Xiaoyu Feng & Yanyan Zeng & Tuanlin Xiong & Wenze Huang & Peng Sun & Yajie Chang & Tingting Li & Cong Fang & Ke, 2022. "Single-cell transcriptome and translatome dual-omics reveals potential mechanisms of human oocyte maturation," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    2. T.V., Binil Shyam & Sharma, Rati, 2024. "mRNA translation from a unidirectional traffic perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    3. Azelle Hawdon & Niall D. Geoghegan & Monika Mohenska & Anja Elsenhans & Charles Ferguson & Jose M. Polo & Robert G. Parton & Jennifer Zenker, 2023. "Apicobasal RNA asymmetries regulate cell fate in the early mouse embryo," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    4. Bin Shao & Jiawei Yan & Jing Zhang & Lili Liu & Ye Chen & Allen R. Buskirk, 2024. "Riboformer: a deep learning framework for predicting context-dependent translation dynamics," Nature Communications, Nature, vol. 15(1), pages 1-10, December.

    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:nature:v:597:y:2021:i:7877:d:10.1038_s41586-021-03887-4. 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.