Abstract
Viruses use internal ribosome entry sites (IRES) to hijack host ribosomes and promote cap-independent translation. Although they are well-studied in bulk, the dynamics of IRES-mediated translation remain unexplored at the single-molecule level. Here, we developed a bicistronic biosensor encoding distinct repeat epitopes in two open reading frames (ORFs), one translated from the 5′ cap, and the other from the encephalomyocarditis virus IRES. When combined with a pair of complementary probes that bind the epitopes cotranslationally, the biosensor lights up in different colors depending on which ORF is translated. Using the sensor together with single-molecule tracking and computational modeling, we measured the kinetics of cap-dependent versus IRES-mediated translation in living human cells. We show that bursts of IRES translation are shorter and rarer than bursts of cap translation, although the situation reverses upon stress. Collectively, our data support a model for translational regulation primarily driven by transitions between translationally active and inactive RNA states.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$189.00 per year
only $15.75 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
Raw images can be found at: https://doi.org/10.6084/m9.figshare.12751853.v1. Source data are provided with this paper.
Code availability
All codes and required data are available at: https://github.com/MunskyGroup/Koch_Aguilera_etal_2020.git
Change history
27 October 2020
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
References
Jackson, R. J., Hellen, C. U. T. & Pestova, T. V. The mechanism of eukaryotic translation initiation and principles of its regulation. Nat. Rev. Mol. Cell Biol. 11, 113–127 (2010).
Bornes Stéphanie et al. Translational induction of VEGF internal ribosome entry site elements during the early response to ischemic stress. Circ. Res. 100, 305–308 (2007).
Xue, S. et al. RNA regulons in Hox 5′ UTRs confer ribosome specificity to gene regulation. Nature 517, 33–38 (2015).
Stoneley, M., Paulin, F. E., Le Quesne, J. P., Chappell, S. A. & Willis, A. E. C-Myc 5′ untranslated region contains an internal ribosome entry segment. Oncogene 16, 423–428 (1998).
Ray, P. S., Grover, R. & Das, S. Two internal ribosome entry sites mediate the translation of p53 isoforms. EMBO Rep. 7, 404 (2006).
Firth, A. E. & Brierley, I. Non-canonical translation in RNA viruses. J. Gen. Virol. 93, 1385–1409 (2012).
Doudna, J. A. & Sarnow, P. Translation Initiation by Viral Internal Ribosome Entry Sites. 25 (2007).
Komar, A. A., Mazumder, B. & Merrick, W. C. A new framework for understanding IRES-mediated translation. Gene 502, 75–86 (2012).
Kieft, J. S. Viral IRES RNA structures and ribosome interactions. Trends Biochem. Sci. 33, 274–283 (2008).
Filbin, M. E. & Kieft, J. S. Toward a structural understanding of IRES RNA function. Curr. Opin. Struct. Biol. 19, 267–276 (2009).
Baird, S. D. Searching for IRES. RNA 12, 1755–1785 (2006).
Fernández-Miragall, O., de Quinto, S. L. & Martínez-Salas, E. Relevance of RNA structure for the activity of picornavirus IRES elements. Virus Res. 139, 172–182 (2009).
Gendron, K., Ferbeyre, G., Heveker, N. & Brakier-Gingras, L. The activity of the HIV-1 IRES is stimulated by oxidative stress and controlled by a negative regulatory element. Nucleic Acids Res. 39, 902–912 (2011).
Hanson, P., Yang, D., Zhang, H. & Hemida, M. in Viral Replication (ed Rosas-Acosta, G.) Ch. 5 (InTech, 2013).
Holcik, M. & Sonenberg, N. Translational control in stress and apoptosis. Nat. Rev. Mol. Cell Biol. 6, 318–327 (2005).
Hanson, P. J. et al. IRES-dependent translational control during virus-induced endoplasmic reticulum stress and apoptosis. Front. Microbiol. 3, 92 (2012).
Hetz, C. The unfolded protein response: controlling cell fate decisions under ER stress and beyond. Nat. Rev. Mol. Cell Biol. 13, 89–102 (2012).
Hooper, P. L., Hightower, L. E. & Hooper, P. L. Loss of stress response as a consequence of viral infection: implications for disease and therapy. Cell Stress Chaperones 17, 647–655 (2012).
Fernandez, J., Yaman, I., Sarnow, P., Snider, M. D. & Hatzoglou, M. Regulation of internal ribosomal entry site-mediated translation by phosphorylation of the translation initiation factor eIF2α. J. Biol. Chem. 277, 19198–19205 (2002).
Sonenberg, N. & Hinnebusch, A. G. Regulation of translation initiation in eukaryotes: mechanisms and biological targets. Cell 136, 731–745 (2009).
Thompson, S. R. & Sarnow, P. Regulation of host cell translation by viruses and effects on cell function. Curr. Opin. Microbiol. 3, 366–370 (2000).
Weingarten-gabbay, S. & Segal, E. Toward a systematic understanding of translational regulatory elements in human and viruses. RNA Biol. 13, 927–933 (2016).
Plank, T. D. M., Whitehurst, J. T. & Kieft, J. S. Cell type specificity and structural determinants of IRES activity from the 5’ leaders of different HIV-1 transcripts. Nucleic Acids Res. 41, 6698–6714 (2013).
Davies, M. V. & Kaufman, R. J. The sequence context of the initiation codon in the encephalomyocarditis virus leader modulates efficiency of internal translation initiation. J. Virol. 66, 9 (1992).
Gale, M., Tan, S.-L. & Katze, M. G. Translational control of viral gene expression in eukaryotes. Microbiol. Mol. Biol. Rev. 64, 239–280 (2000).
De Quinto, S. L., Lafuente, E. & Martínez-Salas, E. IRES interaction with translation initiation factors: Functional characterization of novel RNA contacts with eIF3, eIF4B, and eIF4GII. RNA 7, 1213–1226 (2001).
Morisaki, T. et al. Real-time quantification of single RNA translation dynamics in living cells. Science 352, 1425–1429 (2016).
Viswanathan, S. et al. High-performance probes for light and electron microscopy. Nat. Methods 12, 568–576 (2015).
Yan, X., Hoek, T. A., Vale, R. D. & Tanenbaum, M. E. Dynamics of translation of single mRNA molecules in vivo. Cell 165, 976–989 (2016).
Carocci, M. & Bakkali-Kassimi, L. The encephalomyocarditis virus. Virulence 3, 351–367 (2012).
Chamond, N., Deforges, J., Ulryck, N. & Sargueil, B. 40S recruitment in the absence of eIF4G/4A by EMCV IRES refines the model for translation initiation on the archetype of type II IRESs. Nucleic Acids Res. 42, 10373–10384 (2014).
Bochkov, Y. A. & Palmenberg, A. C. Translational efficiency of EMCV IRES in bicistronic vectors is dependent upon IRES sequence and gene location. BioTechniques 41, 283–292 (2006).
McNeil, P. L. & Warder, E. Glass beads load macromolecules into living cells. J. Cell Sci. 88, 669–678 (1987).
Azzam, M. E. & Algranati, I. D. Mechanism of puromycin action: fate of ribosomes after release of nascent protein chains from polysomes. Proc. Natl Acad. Sci. USA 70, 3866–3869 (1973).
Tokunaga, M., Imamoto, N. & Sakata-Sogawa, K. Highly inclined thin illumination enables clear single-molecule imaging in cells. Nat. Methods 5, 159–161 (2008).
Cattoglio, C. et al. Determining cellular CTCF and cohesin abundances to constrain 3D genome models. eLife 8, e40164 (2019).
Adivarahan, S. et al. Spatial organization of single mRNPs at different stages of the gene expression pathway. Mol. Cell 72, 727–738 (2018).
Khong, A. & Parker, R. mRNP architecture in translating and stress conditions reveals an ordered pathway of mRNP compaction. J. Cell Biol. 217, 4124–4140 (2018).
Svitkin, Y. V. et al. General RNA-binding proteins have a function in poly(A)-binding protein-dependent translation. EMBO J. 28, 58–68 (2009).
Sharma, A. K. et al. A chemical kinetic basis for measuring translation initiation and elongation rates from ribosome profiling data. PLoS Comput. Biol. 15, e1007070 (2019).
Morisaki, T. & Stasevich, T. J. Quantifying single mRNA translation kinetics in living cells. Cold Spring Harb. Perspect. Biol. 10, a032078 (2018).
Aguilera, L. U. et al. Computational design and interpretation of single-RNA translation experiments. PLoS Comput. Biol. 15, e1007425 (2019).
Munsky, B., Neuert, G. & van Oudenaarden, A. Using gene expression noise to understand gene regulation. Science 336, 183–187 (2012).
Ingolia, N. T., Hussmann, J. A. & Weissman, J. S. Ribosome profiling: Global views of translation. Cold Spring Harb. Perspect. Biol. 11, a032698 (2019)
Ruiz-Ramos, R., Lopez-Carrillo, L., Rios-Perez, A. D., De Vizcaya-Ruíz, A. & Cebrian, M. E. Sodium arsenite induces ROS generation, DNA oxidative damage, HO-1 and c-Myc proteins, NF-κB activation and cell proliferation in human breast cancer MCF-7 cells. Mutat. Res. Toxicol. Environ. Mutagen 674, 109–115 (2009).
Wang, C., Han, B., Zhou, R. & Zhuang, X. Real-time imaging of translation on single mRNA transcripts in live cells. Cell 165, 990–1001 (2016).
Pelletier, J. & Sonenberg, N. Internal initiation of translation of eukaryotic mRNA directed by a sequence derived from poliovirus RNA. Nature 334, 320–325 (1988).
Marshall, R. A., Aitken, C. E., Dorywalska, M. & Puglisi, J. D. Translation at the single-molecule level. Annu. Rev. Biochem. 77, 177–203 (2008).
Wu, B., Eliscovich, C., Yoon, Y. J. & Singer, R. H. Translation dynamics of single mRNAs in live cells and neurons. Science 352, 1430–1435 (2016).
Kanamori, Y. & Nakashima, N. A tertiary structure model of the internal ribosome entry site (IRES) for methionine-independent initiation of translation. RNA 7, 266–274 (2001).
Edelstein, A. D. et al. Advanced methods of microscope control using μManager software. J. Biol. Methods 1, e10 (2014).
Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).
Acknowledgements
We thank L. Lavis for kindly providing JF646 labeled HaloTag ligand and H. Scherman for purifying Halo-MCP and GFP-scFv (anti-SunTag). We thank L. Whitehead and collaborators for the Imagej Zoom plugin. We thank all members of the Stasevich and Munsky labs for their support and helpful discussions. B.M. and L.A. were supported by a grant from the W.M. Keck Foundation and by the NIH (grant no. 5R35GM124747). T.J.S., A.K. and T.M. were supported by the National Institutes of Health (grant no. R35GM119728).
Author information
Authors and Affiliations
Contributions
A.K. and T.J.S. designed and planned all experiments. A.K. cloned all plasmids and performed all experiments. T.M. assisted A.K. with microscopy and particle tracking. B.M. and L.A. performed all modeling and fitting. T.J.S. and A.K. wrote the main manuscript, with assistance from T.M. for experimental methods related to microscopy and particle tracking and from B.M. and L.A. for computational sections. B.M. and L.A. wrote the computational details in Supplementary Note 1. A.K., L.A., T.M., B.M. and T.J.S. edited the manuscript. B.M. and T.J.S. acquired funding and designed the computational and experimental studies.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Peer review information Peer reviewer reports are available. Anke Sparmann was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Controls for bleedthrough and active translation.
a-b, Five frame average of a Cap Only and IRES Only translation spots. mRNA marker dye, JF646, was not added to these cells. Cells were imaged for 3-minutes with a 6-second interval between each capture. c, Top graphs show normalized total intensity over time for Cap-dependent (left) and IRES-mediated translation spots (right), after addition of puromycin. Gray lines indicate individual cells. Thick dark line indicates the average total intensity of all cells. Red dashed lines indicate time at which puromycin was added. Cap-dependent: n = 5 cells. IRES-mediated: n = 5 cells. Bottom graphs show normalized total intensity of Cap-dependent (left) and IRES-mediated (right) translation spots without the addition of puromycin. Cap-dependent: n = 6 cells. IRES-mediated: n = 5 cells. All cells (control and drug treated) were imaged for 10-minutes with a 1-minute interval. Error bars represent S.E.M.
Extended Data Fig. 2 IRES and cap translation site localization and mobility.
a, Quantification of translating and non-translating mRNA distances in micrometers (µm) to nearest-neighbor translation spot within single cells. Each point represents the average distance per cell. n = 39 cells. b, Quantification of distance in µm from the nucleus of translating and non-translating mRNA. Each point represents the average distance from the edge of the nucleus per cell. n = 39 cells. c, Representative cell out of n = 11 cells imaged with fast imaging conditions. An example mRNA is highlighted with a white circle and a track through time of that mRNA is graphed below. d, Cumulative distribution function plot of non-translating mRNA (red), IRES Only (purple), Cap Only (yellow), and Cap+IRES (gray) species based on their diffusion coefficients (µm2 /sec). Inset shows the Mean Square Displacements (MSD) of the different species over time in seconds. n = 3771 total tracked mRNA (translating and non-translating), n = 11 cells. e, Schematic showing how the jump angles are measured. Error bars represent the standard error of the mean (S.E.M). f, Circular plots of the jump angle distributions for non-translating mRNA, Cap Only, IRES Only and Cap+IRES translation sites. For the box and whisker plots, the thick black lines indicate the medians, the boxes indicate the 25%-75% range, and the whiskers indicate the 5%-95% range. The p-values are based on a two-tailed Mann-Whitney test: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.
Extended Data Fig. 3 Measuring distances between Cap and IRES nascent chains in Cap+ IRES translation spots.
a, Representative data set of measured distances of Cap (light green) and IRES (blue) nascent chains to 3′UTR through time in single Cap+IRES translation tracks. b, Median distances of Cap and IRES nascent chains to 3′UTR of each Cap+IRES track. Distances are measured in nanometers (nm). 3′ UTR coordinates were fixed at (0,0) for all analyses. n = 296 translation spots.
Extended Data Fig. 4 Ribosomal run-off curves from single cells after addition of Harringtonine.
a, Harringtonine-induced ribosomal run-off curves from single cells. Each curve shows the decay in nascent chain signal intensity from all Cap-dependent and (b) IRES-mediated translation sites within a single cell post-Harringtonine. Run-off curves were phenomenologically fit to a Tanh function to align curves in time for averaging in Fig. 3. The slope of fitted curves at a normalized intensity value of 0.5 was used to estimate the elongation rate. c, Cap-dependent (n = 7 cells) and (d) IRES-mediated (n = 5 cells) translation controls in which no drugs were added. Each gray line shows the total nascent chain signal intensity from all translation sites in an individual cell. The thick black line is a representative cell. Intensity in arbitrary units (a.u.). All cells were imaged for 45 minutes with a 1-minute interval between each capture.
Extended Data Fig. 5 Original Tag comparison to Switch Tag, single mRNA selection, and polysome intensity calibrations.
a, Quantification of the percentages of each type of translation sites for the Original Tag (left, n = 39 cells) and the Switch Tag (right, n = 37 cells). Each point represents a single-cell measurement. b, Probability histograms showing distributions of mRNA intensities of non-translating mRNA (Red), Cap Only (Yellow), IRES Only (Purple), and Cap+IRES (Gray) translation sites for the Original Tag and the Switch Tag. The gray boxes represent the mRNA intensity threshold used to eliminate multiple mRNAs. Intensities in arbitrary units (a.u.). c, Translation site calibration measurements. The intensities of Cap in Cap Only translation sites (n = 20spots) in the Original Tag were compared to a 10xFlag calibration system (n = 47spots) with a known number of ribosomes. These comparisons lead to a calculated number of 14.6 ribosomes in Cap Only translation sites using the Original Tag. For the box and whisker plots, the thick black lines indicate the medians (A and C), and the dashed red line indicate the weighted means (A) the boxes indicate the 25%-75% range, and the whiskers indicate the 5%-95% range. The p-values are based on a two-tailed Mann-Whitney test: *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.
Extended Data Fig. 6 Model of the bicistronic gene construct.
a, The most complete mathematical model considers four mutually exclusive RNA states: non-translating (SOFF), Cap-dependent (SCAP-ON), IRES-mediated (SIRES-ON), and both Cap and IRES (SCAP+IRES-ON). All transition rate values between RNA states are free-independent parameters. A cross-over mechanism (CO symbol in the figure), by which a ribosome that completes the translation of the Cap-dependent protein could immediately reinitiate translation of the IRES-mediated protein, is represented by the reaction parameter kCO. b, Comparison of 14 different sub-models. The sub-models test different hypotheses, including variations of the number of mRNA states (3 or 4 states), dependency on Cap and IRES switching states, and/or the existence of the cross-over mechanism. A complete description is given in the Supplementary Information (S.I.). c, Cross-validation is used to compare two possible mechanisms of translation inhibition under NaAs stress. The first mechanism mimics the inhibition of the Cap activation rates at the mRNA level (LNaAs-k-ON-C; that is, block of kON-C and k’ON-C). The second mechanism considers blocking ribosomal initiation for Cap (LNaAs-k-INIT-C; that is, block of kINIT-C). d, Optimization process and cross-validation for the DTT stress. The same inhibitory mechanisms described in c are tested for DTT stress. Relative Log-likelihood values for the optimization process are calculated according to (S.I.) Eq. 23 and Eq. 26 for the NaAs and DTT cross-validation experiments, respectively. A selection threshold (dashed red line) was defined by a log-likelihood of 100 worse than the most complex and best fitting model. Models above the selection threshold were discarded (gray background), and their cross-validation log-likelihood values are not shown. The best model shown (green background) was chosen as the model with fewest free parameters below the selection threshold. A complete description is given in the Statistics and Reproducibility section. e, Model simulations for the best-fit model 4SIm2 under NaAs and DTT stresses. The figure shows the effect of blocking ribosomal initiation and activation for Cap.
Supplementary information
Supplementary Information
Supplementary Note 1.
Supplementary Video 1
Visualizing cap-dependent and IRES-mediated translation at the single-molecule level of the bicistronic biosensor (smF-KDM5B-IRES-ST-Kif18b); related to Fig. 1. A U2OS cell was beadloaded with scFv-GFP (shown in blue), Cy3-FLAG Fab (shown in green), Halo-MCP (shown in red), and the biosensor. The entire cell volume was acquired every 6 s (movie duration is 3 min) on a home-built HILO microscope. The Zoom FIJI plugin was used to show all the different modes of translation as well as non-translating mRNA within the cell. Image is 66.56 × 66.56 μm.
Supplementary Video 2
Tracking fast-moving mRNA and translation sites on the bicistronic biosensor (smF-KDM5B-IRES-ST-Kif18b); related to Fig. 2. A U2OS cell was beadloaded with scFv-GFP (shown in blue), Cy3-FLAG Fab (shown in green), Halo-MCP (shown in red), and the biosensor. A single plane of the cell was imaged at an imaging rate of 77 msec. Image is 52.39 × 42.64 μm.
Source data
Source Data Fig. 1
Percentages of modes of translation for original tag for Fig. 1d
Source Data Fig. 2
Raw intensity and xy coordinates data used to generate Fig. 2 c,d
Source Data Fig. 3
Raw intensity data before and after addition of harringtonine
Source Data Fig. 4
Intensity data for cap, IRES and cap + IRES translation spots in the original tag and switch tag
Source Data Fig. 5
Experimental and simulation data used to generate all of Fig. 5
Source Data Extended Data Fig. 6
Statistical source data
Rights and permissions
About this article
Cite this article
Koch, A., Aguilera, L., Morisaki, T. et al. Quantifying the dynamics of IRES and cap translation with single-molecule resolution in live cells. Nat Struct Mol Biol 27, 1095–1104 (2020). https://doi.org/10.1038/s41594-020-0504-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41594-020-0504-7
This article is cited by
-
Engineering a synthetic gene circuit for high-performance inducible expression in mammalian systems
Nature Communications (2024)
-
Branched chemically modified poly(A) tails enhance the translation capacity of mRNA
Nature Biotechnology (2024)
-
Single-molecule visualization of mRNA circularization during translation
Experimental & Molecular Medicine (2023)
-
Integrative solution structure of PTBP1-IRES complex reveals strong compaction and ordering with residual conformational flexibility
Nature Communications (2023)
-
Imaging translational control by Argonaute with single-molecule resolution in live cells
Nature Communications (2022)