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Selective footprinting of 40S and 80S ribosome subpopulations (Sel-TCP-seq) to study translation and its control

Nature Protocols volume 17, pages 2139–2187 (2022)Cite this article

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Abstract

Multiple aspects of mRNA translation are subject to regulation. Here we present a ribosome footprinting protocol to determine the location and composition of 40S and 80S ribosome complexes on endogenous mRNAs transcriptome-wide in vivo in yeast and mammalian cells. We present an extension of the translation complex profiling (TCP-seq) protocol, originally developed in yeast, by including an immunoprecipitation step to assay the location of both 40S and 80S ribosome complexes containing proteins of interest. This yields information on where along mRNAs the ribosome-bound protein of interest joins the ribosome to act, and where it leaves again, thereby monitoring the sequential steps of translation and the roles of various translation factors therein. Rapid fixation of live cells ensures the integrity of all translation complexes bound to mRNA at native positions. Two procedures are described, differing mainly in the fixation conditions and the library preparation. Depending on the research question, either procedure offers advantages. Execution of a Sel-TCP-seq experiment takes 5–10 working days, and initial data analysis can be completed within 2 days.

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Fig. 1: Schematic experimental workflow and expected results of selective footprinting of 40S and 80S ribosome subpopulations (Sel-TCP-seq).
Fig. 2: Experimental workflow for cultured mammalian cells highlighting the main differences between the DSP and the HCHO-only procedures.
Fig. 3: Useful representation of the data.
Fig. 4: Representative gels of intermediate steps of the DSP procedure.
Fig. 5: Representative gels of intermediate steps of the HCHO-only procedure in HEK293T cells.

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Data availability

All datasets used for presentation of expected results obtained with Sel-TCP-seq are available at NCBI Geo (GSE168977 for the DSP procedure and GSE139132 for the HCHO-only procedure). These datasets were published previously14,15.

Code availability

Custom software written for the ‘DSP Procedure’ is available at https://github.com/aurelioteleman/Teleman-Lab and the Zenodo repository (https://doi.org/10.5281/zenodo.5751288)56,57. Custom software written for the ‘HCHO-only Procedure’ is available at https://github.com/Zuzalka/TCP-seq/tree/v1.0.0-alpha and the Zenodo repository (https://doi.org/10.5281/zenodo.6079350)58.

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Acknowledgements

We are grateful to members of the Preiss, Valášek and Teleman labs for insightful discussions. This work was supported by a Grant of Excellence in Basic Research (EXPRO 2019) provided by the Czech Science Foundation (19-25821X to L.S.V.), ELIXIR CZ research infrastructure project (MEYS grant no. LM2018131) including access to computing and storage facilities. Funding to T.P. was provided by an NHMRC Senior Research Fellowship (APP1135928), an Australian Research Council Discovery Project grant (DP180100111) and a Cancer Council ACT Project grant (APP1120469).

Author information

Author notes

  1. Susan Wagner

    Present address: Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG), Dresden, Germany

  2. Jonathan Bohlen

    Present address: University of Paris, Imagine Institute, Paris, France

  3. These authors contributed equally: Susan Wagner, Jonathan Bohlen, Anna Herrmannova.

Authors and Affiliations

  1. Laboratory of Regulation of Gene Expression, Institute of Microbiology CAS, Prague, Czech Republic

    Susan Wagner, Anna Herrmannova & Leoš Shivaya Valášek

  2. German Cancer Research Center (DKFZ), Heidelberg, Germany

    Jonathan Bohlen & Aurelio A. Teleman

  3. Heidelberg University, Heidelberg, Germany

    Jonathan Bohlen & Aurelio A. Teleman

  4. Laboratory of Bioinformatics, Institute of Microbiology CAS, Prague, Czech Republic

    Jan Jelínek

  5. Victor Chang Cardiac Research Institute, Darlinghurst, Australia

    Thomas Preiss

  6. Shine-Dalgarno Centre for RNA Innovation & Division of Genome Sciences and Cancer, John Curtin School of Medical Research, Australian National University, Canberra, Australia

    Thomas Preiss

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Contributions

S.W., J.B., A.H., T.P., L.S.V. and A.T. conceived and designed the project. S.W., J.B. and A.H. carried out all experimental procedures. S.W. and J.B. performed the data analysis with help from J.J. S.W., J.B. and A.H. led the preparation of the manuscript, with T.P., L.S.V. and A.T. All authors provided feedback on the manuscript and approved the final draft.

Corresponding authors

Correspondence to Thomas Preiss, Leoš Shivaya Valášek or Aurelio A. Teleman.

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The authors declare no competing interests.

Peer review

Peer review information

Nature Protocols thanks Shintaro Iwasaki, Shu-Bing Qian and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Related links

Key references using this protocol

Bohlen, J. et al. Mol. Cell 79, 561–574 (2020): https://doi.org/10.1016/j.molcel.2020.06.005

Wagner, S. et al. Mol. Cell 79, 546–560 (2020): https://doi.org/10.1016/j.molcel.2020.06.004

Bohlen, J. et al. Nat. Commun. 11, 4676 (2020): https://doi.org/10.1038/s41467-020-18452-2

This protocol is an extension to: Nat. Protoc. 12, 697–713 (2017): https://doi.org/10.1038/nprot.2016.189

Extended data

Extended Data Fig. 1 Useful representation of the selected 40S and 80S libraries, complementing Fig. 5.

The datasets are available at NCBI Geo (GSE168977 and GSE139132). Similar plots, i.e., plots generated from the same datasets, were published previously1,2. a–h, Metagene plots of the distribution of the footprint length at any position around the start codon represented as a heatmap. The position of the 5′ end of the footprint is plotted. In a–d, counts are plotted in linear scale with a cap. In e–h, counts are plotted in log10 scale. The full data range is represented. a and e show eIF3B-40S footprints from the HCHO-only procedure. b and f show eIF3B-80S footprints from the HCHO-only procedure. c and g show eIF4G1-40S footprints from the DSP procedure. d and h show eIF4G1-80S footprints from the DSP procedure. Note: For this specific eIF4G1-80S library, we carried out 75 sequencing cycles, and therefore, longer footprints are also detected.

Extended Data Fig. 2 Examples of results useful for optimization experiments, complementing Box 1, and a breakdown of the remaining sequencing reads.

a, Western blots of sucrose gradient fractions of three HEK293T lysates cross-linked with increasing efficiency. Probing with antibodies against a small ribosomal protein (RPS14) and a large ribosomal protein (RPL13) reveals fractions of 40S ribosomes and the polysomal fractions. Probing with antibodies against translation initiation factors eIF3A and eIF3B shows that, with increasing cross-linking efficiency, less eIF3A and eIF3B falls off the ribosomes during the high-velocity centrifugation, and therefore, more of these factors can be found in polysomal fractions as well as on the 40S. b, Profiles from three HEK293T lysates treated with EDTA. The cells were cross-linked with different efficiencies. The blue profile displays efficient EDTA-mediated splitting of the 80S ribosome into its 40S and 60S subunits, while the green profile displays reduced splitting, indicating efficient cross-linking of the cells. The red profile shows very efficient prevention of ribosome splitting and, at the same time, low polysomes. According to our experience, it reflects over-cross-linking of cells. c, Polysome profiles of HEK293T lysates that were either treated with cycloheximide (CHX, black profile) or cross-linked with different efficiencies indicated. The red profile represents over-cross-linking, while the blue profile represents under-cross-linking (large increase in 80S ribosomes and light polysomes and decrease in heavy polysomes). Panel c reproduced with permission from ref. 14, Elsevier. d, Profiles of HEK293T lysates of cross-linked cells that were either left undigested (black profile) or digested with different RNase I concentrations. The green profile presents the most optimal digested lysate of the depicted profiles. e,f, Breakdown of the remaining fraction of sequencing reads after adapter removal (only those reads were kept that had an adapter and that were sufficiently long after adapter trimming), after rRNA removal and after mapping to a reference genome or transcriptome. e shows the breakdown for many libraries prepared according to the DSP procedure with the horizontal bar representing the average, and f for one exemplary library prepared according to the HCHO-only procedure.

Supplementary information

Supplementary Data 1

An exemplary bash script for data analysis as presented in the DSP procedure.

Supplementary Data 2

The fasta files used to deplete mouse and human rRNA sequences for data analysis as presented in the DSP procedure.

Supplementary Data 3

The fasta files used to deplete mouse and human tRNA sequences for data analysis as presented in the DSP procedure.

Supplementary Data 4

Tab-delimited text file containing feature identifiers and a position coordinate for each feature, to be used as an input file for generating metagene plots.

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Wagner, S., Bohlen, J., Herrmannova, A. et al. Selective footprinting of 40S and 80S ribosome subpopulations (Sel-TCP-seq) to study translation and its control. Nat Protoc 17, 2139–2187 (2022). https://doi.org/10.1038/s41596-022-00708-4

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