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Distinct non-canonical translation initiation modes arise for specific host and viral mRNAs during poxvirus-induced shutoff

Nature Microbiology volume 10, pages 1535–1549 (2025)Cite this article

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Abstract

Many viruses potently inhibit host protein synthesis, termed host shutoff, while employing strategies to sustain their own translation. How and why certain host mRNAs continue to be translated at later infection stages remains unclear. Here, using RNAseq and polysome profiling, we show that during shutoff by vaccinia virus (VacV), several host mRNAs increase in polysome occupancy but only a few, primarily JUN that encodes the Jun transcription factor, result in increased protein abundance across multiple cell lines. While dispensable for Jun production, translation of viral mRNAs depended on the small ribosomal protein, Receptor for Activated C Kinase 1 (RACK1) and the eukaryotic Initiation Factor, eIF3. These differential eIF3 dependencies are associated with structurally distinct 5′ untranslated regions in viral versus JUN mRNAs. Cryo-electron microscopy structures of 40S ribosomes from mock-infected or VacV-infected cells showed that when bound to eIF3, the rotational range of the RACK1-containing 40S head domain broadens during infection. Our data reveal how eIF3-bound 40S ribosomes are remodelled late in infection and the distinct strategies of translation initiation that arise during shutoff to produce host and viral proteins required for poxvirus spread.

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Fig. 1: Host transcriptomic changes in VacV-infected HAP1 cells.
Fig. 2: Translation efficiency and predicted protein outputs for host mRNAs upregulated during infection.
Fig. 3: Translational activation of the JUN 5′ UTR at late stages of infection.
Fig. 4: Host and viral 5′ UTR’s determine distinct eIF3 dependencies at early versus late stages of infection.
Fig. 5: eIF3-bound 40S subunits exhibit broader head swivel in infected cells (state 2; most rotated).
Fig. 6: JUN expression is regulated at multiple levels and supports VacV spread.

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Data availability

The data supporting the findings of this study are available within the Article and its supplementary files. Cryo-EM maps are deposited in Electron Microscopy Data Bank (EMDB) as follows: eIF3-bound 40S, state 1, from mock-infected cells (EMD-48646); eIF3-bound 40S, state 2, from mock-infected cells (EMD-48647); free 40S, state 1, from mock-infected cells (EMD-48644), free 40S, state 2, from mock-infected cells (EMD-48645); eIF3-bound 40S consensus structure, from mock-infected cells (EMD-48642); free 40S consensus structure, from mock-infected cells (EMD-48643); eIF3-bound 40S, state 1, from VacV-infected cells (EMD-46432); eIF3-bound 40S, state 2, from VacV-infected cells (EMD-46447); free 40S, state 1, from VacV-infected cells (EMD-46449), free 40S, state 2, from VacV-infected cells (EMD-46450); eIF3-bound 40S consensus structure, from VacV-infected cells (EMD-48640); free 40S consensus structure, from VacV-infected cells (EMD-48641). Raw and processed sequencing data are deposited in NCBI Gene Expression Omnibus (GEO) under accession number GSE278320. Source data are provided with this paper.

Code availability

All code is available on CodeOcean at https://doi.org/10.24433/CO.5984508.v2 (ref. 75).

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Acknowledgements

We thank E. Bartom and C. Rosencrance (Northwestern University) for guidance on sequencing and bioinformatics; S. Rothenburg (UC Davis), M. Mendillo (Northwestern University), D. Evans (University of Alberta), P. Traktman (The Medical University of South Carolina), J. Connor (Boston University), J. Cao (The Public Health Agency of Canada) and Y. Xiang (The University of Texas Health San Antonio) for plasmids and antibodies; and C. Norbury (Penn State College of Medicine) for ECTV-infected lysates. We thank the University of Utah Beckman Center for Cryo-EM and Center for High Performance Computing for cryo-EM imaging and computational support. This work was supported by funding from the National Institutes of Health under grant numbers R35GM133772 to P.S.S., and R01AI127456 and R01AI179744 to P.S.S. and D.W. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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  1. Department of Microbiology-Immunology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA

    Chorong Park, Nathan Meade & Derek Walsh

  2. Department of Biochemistry, School of Medicine, University of Utah, Salt Lake City, UT, USA

    Aaron J. Ferrell & Peter S. Shen

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Contributions

C.P. designed the research, performed experiments and analysed data. A.J.F. performed cryo-EM imaging, processing and data analysis. N.M. assisted with experiments. P.S.S. and D.W. secured funding and oversaw the project, experimental design and data interpretation. All authors contributed to writing and approving the final version of the manuscript.

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Correspondence to Derek Walsh.

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Extended data

Extended Data Fig. 1 GO Term analysis of transcriptomic changes during VacV infection.

GO Term analysis of differentially expressed genes that were upregulated (left) or downregulated (right) in total, 80S or polysome samples detailed in Fig. 1. DESeq2 uses Wald tests to evaluate the significance of differential expression and applies Benjamini-Hochberg (BH) correction to control the false discovery rate (FDR). Adjusted p-values (padj) identify significantly differentially expressed genes after multiple testing correction.

Extended Data Fig. 2 Translational downregulation of 5’TOP mRNAs during infection.

a. In uninfected cells, specific genes highly enriched in association with the 80 s ribosome were identified. A heatmap of differential gene expression between total and 80 s or total and polysome samples is annotated above with 5’TOP genes in red. Beneath: 20 nucleotide sequence motifs of 82 known or potential 5’TOP genes were generated using weblogo.berkely.edu. b. Log2FC changes in 5’TOP mRNAs contained in 80S or polysome fractions from mock infected or infected samples from Fig. 1. Red and blue bars indicate increases and decreases in Log2FC enrichment over total RNA, respectively. c. Log2FC comparison of total mock versus infected or 80S mock versus infected samples. While also downregulated at the transcript level, more robust loss from 80S samples was detected in infected samples. DESeq2 uses Wald tests to evaluate the significance of differential expression and applies Benjamini-Hochberg (BH) correction to control the false discovery rate (FDR). Adjusted p-values (padj) identify significantly differentially expressed genes after multiple testing correction. The adjusted p-value cutoff was set above 0.01 and the Log2FC threshold was set to 1.1. For a–c, data is derived from 3 biologically independent experiments.

Extended Data Fig. 3 Induction of JUN expression in orthopoxvirus-infected cells.

a. PCR analysis of RNA levels of JUN and DNAJB1, together with GAPDH and late viral RNA (A14) in HAP1 cells infected with VacV at MOI 10 for the indicated times in hours post-infection (h.p.i.). b. qPCR analysis of JUN (left) and DNAJB1 (right) expression in samples as described in A, normalized to β-actin. The body of the box plot represents the minima and maxima of the distribution and the median line. The whiskers extend from the minimum and maximum values of the data points no outliers shown n = 4 per group, one-way ANOVA with two-sided, Tukey’s multiple comparison test. Data are presented as mean values +/− SEM. n.s. = no significance, ****padjust ≤0.0001. Statistical values are shown for JUN expression at 1 h.p.i., illustrating that although not significant statistically using multiple sample comparisons, there is a statistically significant increase over uninfected samples using paired t-tests. c. PCR analysis of RNA levels for representative host genes induced during infection, together with GAPDH isolated from mock or VacV-infected (MOI 10) total lysate, 80S or polysome (poly) fractions of HAP1 cells at 24 h.p.i. qPCR analysis associated with this panel is shown in Fig. 2b of the main manuscript. d. MRC5 or 293 A cells were mock infected or infected with VacV at MOI 10 for 24 h. Whole cell lysates were analyzed by WB using the indicated antibodies. e. Differentiated THP1 cells (macrophages) were infected with VacV at MOI 20 or 40 for 1 or 2 days, as indicated. Whole cell lysates were analyzed by WB using the indicated antibodies. Data in D-E is representative of 3 independent experiments. f. Murine B6/WT19 fibroblasts or human HeLa cells were infected with Ectromelia Virus (ECTV) at MOI 10 for 24 h. Whole cell lysates were analyzed by WB using the indicated antibodies. Note that HSP70 is not detectable in mouse cells, due either to low protein abundance or species specificity of the antibody used. Data in F is representative of 2 independent experiments per cell type. Source data are provided as a Source Data file.

Source data

Extended Data Fig. 4 Comparisons of predicted gene expression changes with published proteomic resources.

The interactive ‘Plotter’ worksheet from proteomic studies by Soday et al., 2019 was used to compare changes in the levels of proteins in our predicted protein output analysis and in prior ribosome profiling studies. Blue lines show protein levels in uninfected samples. Red line show protein levels in VacV-infected samples. a. Expression levels of proteins at the top of our finalized ‘protein output’ predictions. b. Expression levels of proteins that top our list of largest increase in TE without filtering out low read counts. In line with these being too low to be accurate or reliable predictors, none of these mRNAs are associated with proteins that increase in abundance during infection. c. Expression levels of proteins that our analysis suggests are encoded by mRNAs whose TE increase the most but whose total mRNA levels decline so much that they would not be expected to increase protein production. d. Expression levels of proteins predicted to be translationally increased by Dhungel et al., 2017. Note that increases are small and transient but align with the early-to-mid stage phase of infection in their study. For information on replicates and statistical analyses, please refer to the relevant cited publication in each panel.

Extended Data Fig. 5 Effects of eIF3 depletion on JUN versus late viral proteins in primary NHDFs infected with VacV.

HAP1 cells were treated with control non-targeting siRNAs (con) or one of two independent siRNAs targeting eIF3d or eIF3a, followed by infection with VacV at MOI 10 for 24 h. Samples were analyzed by WB for the indicated proteins. Blots are representative of 3 independent experiments. Source data are provided as a Source Data file.

Source data

Extended Data Fig. 6 Transcriptomic and translational analysis of host genes during VacV infection of HAP1 cells lacking RACK1.

RACK1 knockout HAP1 cells (shown in Fig. 3g) were infected with VacV at MOI 25 for 24 h. Cell lysates were prepared and fractionated. PolyA-mRNA was isolated from total, 80S and polysome (pols) fractions and sequenced on a Novaseq S4. Differential gene expression between mock infected WT HAP1 cells and VacV-infected RACK1 knockout cells using DEseq comparisons of total, 80S and polysome samples. DESeq2 uses Wald tests to evaluate the significance of differential expression and applies Benjamini-Hochberg (BH) correction to control the false discovery rate (FDR). Adjusted p-values (padj) identify significantly differentially expressed genes after multiple testing correction. p-adjusted cutoff was set to above 0.01 and Log2FC to 1.1. Results show that host genes are increased or decreased to the same extent even in the absence of RACK1, demonstrating that RACK1 and its phosphorylation are not essential for host transcript and translational reprogramming during infection. Data is derived from 3 biologically independent experiments.

Extended Data Fig. 7 Consensus structures of eIF3-bound and free 40S particles from mock-infected and VacV-infected cells.

a. mock-infected samples. b. VacV-infected samples. Resolution of each structure is indicated.

Extended Data Fig. 8 Cryo-EM data processing workflow and classification of 40S head classes by 3DVA for mock-infected and VacV-infected samples.

a. Representative cryo-EM micrographs of purified ribosomes from mock-infected (left, out of 18,975 curated micrographs) and VacV-infected (right, out of 10,764 curated micrographs) cells. b. Reference-free 2D class averages of extracted particles. c. Data processing workflow. 40S particles were used for downstream 3DVA processing. d. CryoSPARC 3DVA workflow. The mask used in focused classification is shown in purple. Maps that displayed the greatest degree of 40S head rotation swiveling are indicated by red boxes. e. Gold standard FSC curves for eIF3-bound 40S particles, state 1 (least rotated), state 2 (most rotated) and of free 40S, state 1 (least rotated), state 2 (most rotated).

Extended Data Fig. 9 Extent of 40S head swivel on eIF3-bound 40S subunits is greater in ribosomes from infected cells (state 1; least rotated).

a–c. 40S head swivel on eIF3-bound 40S particles from mock-infected cells. a. Fitting of the eIF3-bound 40S state (PDB 6ZVJ) into cryo-EM reconstruction of eIF3-bound 40S ribosomal subunit (state 1) isolated from mock-infected cells. Insets show focused views of good fits of the 40S body (RPS7, RPS13), but the model is slightly displaced in the 40S head (RPS25, RPS18, RPS5, RPS16). b. Focused views of RPS5 and RPS25 before (eIF3-bound 40S, PDB 6ZVJ) and after (best fit) separate rigid-body fitting of the 40S head into the cryo-EM density. Right, overlay of the before-and-after fitting reveals the trajectory of motion (tan, before; green, after). c. Separate rigid-body fitting of the 40S head into cryo-EM reconstruction of ribosomes from mock-infected cells reveals a 1.4° rotation of the head (green ribbon). Tan ribbon, standard fit from PDB 6ZVJ based on 40S body components. Rotation axis depicted as gray rod. d-f. 40S head swivel on eIF3-bound 40S particles from VacV-infected cells. d. Fitting of the eIF3-bound 40S state (PDB 6ZVJ) into cryo-EM reconstruction of eIF3-bound 40S ribosomal subunit (state 1) isolated from VacV-infected cells. Insets show focused views of good fits of the 40S body (RPS8), but the model is slightly displaced in the 40S head (RPS18, RPS12, RPS27a). e. Focused views of RPS18 before (eIF3-bound 40S, PDB 6ZVJ) and after (best fit) separate rigid-body fitting of the 40S head into the cryo-EM density. Right, overlay of the before-and-after fitting reveals the trajectory of motion (tan, before; green, after). f. Separate rigid-body fitting of the 40S head into cryo-EM reconstruction of virus-modified ribosomes reveals a 3.8° rotation of the head (green ribbon). Tan ribbon, standard fit from PDB 6ZVJ based on 40S body components. Rotation axis depicted as gray rod. g. Comparison of extent of 40S head swivel between mock-infected and VacV-infected cells. Structures of the 40S head in the least rotated state (state 1) after rigid body fitting (mock infected: teal, VacV infected: pink) overlayed against a previously published structure of eIF3-bound 40S particles (PDB 6ZVJ, tan), highlighting the increase in movement from VacV infected samples. Rotation axes of movement indicated by black rods.

Extended Data Fig. 10 Effects of JUN depletion or HSP70 inhibition on VacV Replication.

a. HAP1 cells were treated with control non-targeting siRNAs or one of two independent siRNAs targeting JUN (to deplete the Jun protein) followed by infection with VacV at MOI 10 for 24 h. Representative WB’s are shown demonstrating the relative efficacy of each JUN-targeting siRNA and the lack of effects of viral protein accumulation at high MOI. b. Measurement of viral titers from HAP1 cells treated and infected as described in A. n = 3, no statistical significance was found for any sample. c. Measurement of viral titers from NHDF cells treated with the HSP70 inhibitors, PES-CI (2.5 mM) or VER155008 (20 mM) followed by infection with VacV at MOI 0.01 for 72 h. n = 9 independent samples from 3 biologically independent experiments, one-way ANOVA, two-sided Tukey’s multiple comparison test. Data are presented as mean values +/− SEM. n.s. = no significance, *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, ****p ≤ 0.0001. Source data are provided as a Source Data file.

Source data

Supplementary information

Reporting Summary

Peer Review File

Supplementary Tables 1–5

1. Datasets for genes enriched in 80S polysomes. 2. Datasets for TE calculations for uninfected cells from 3 biological replicate experiments. 3. Datasets for TE calculations for infected cells from 3 biological replicate experiments. 4. Datasets for relative TE, relative total RNA abundance and predicted protein output calculations for uninfected versus infected cells using base means from 3 biological replicate experiments shown in Supplementary Tables 2 and 3. Tab 1 provides finalized datasets wherein genes with low read counts and artificially polyA-enriched histone mRNAs were removed as they produce unreliable TE calculations. Tab 2 provides raw unfiltered datasets. 5. Details of primers used for PCR and cloning in this study.

Supplementary Video 1

Maps were generated in cryoSPARC 3DVA ‘simple’ mode. The first component (component 0) is shown. Compare 40S head motion with Video 2.

Supplementary Video 2

Maps were generated in cryoSPARC 3DVA ‘simple’ mode. The first component (component 0) is shown. Compare 40S head motion with Video 1.

Source data

Source Data Fig. 2

Statistical source data.

Source Data Fig. 2

Unprocessed western blots.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 3

Unprocessed PCR gels and western blots.

Source Data Fig. 4

Statistical source data.

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Unprocessed western blots.

Source Data Fig. 6

Statistical source data.

Source Data Fig. 6

Unprocessed western blots.

Source Data Extended Data Fig. 3

Statistical source data.

Source Data Extended Data Fig. 3

Unprocessed PCR gels and western blots.

Source Data Extended Data Fig. 5

Unprocessed western blots.

Source Data Extended Data Fig. 10

Statistical source data.

Source Data Extended Data Fig. 10

Unprocessed western blots.

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Park, C., Ferrell, A.J., Meade, N. et al. Distinct non-canonical translation initiation modes arise for specific host and viral mRNAs during poxvirus-induced shutoff. Nat Microbiol 10, 1535–1549 (2025). https://doi.org/10.1038/s41564-025-02009-4

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