TY - JOUR
T1 - Single-cell Ribo-seq reveals cell cycle-dependent translational pausing
AU - VanInsberghe, Michael
AU - van den Berg, Jeroen
AU - Andersson-Rolf, Amanda
AU - Clevers, Hans
AU - van Oudenaarden, Alexander
N1 - © 2021. The Author(s), under exclusive licence to Springer Nature Limited.
PY - 2021/9
Y1 - 2021/9
N2 - 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.
AB - 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.
U2 - 10.1038/s41586-021-03887-4
DO - 10.1038/s41586-021-03887-4
M3 - Article
C2 - 34497418
SN - 0028-0836
VL - 597
SP - 561
EP - 565
JO - Nature
JF - Nature
IS - 7877
ER -