Abstract
A widespread strategy employed by pathogens to establish infection is to inhibit host-cell protein synthesis. Legionella pneumophila, an intracellular bacterial pathogen and the causative organism of Legionnaires’ disease, secretes a subset of protein effectors into host cells that inhibit translation elongation. Mechanistic insights into how the bacterium targets translation elongation remain poorly defined. We report here that the Legionella effector SidI functions in an unprecedented way as a transfer-RNA mimic that directly binds to and glycosylates the ribosome. The 3.1 Å cryo-electron microscopy structure of SidI reveals an N-terminal domain with an ‘inverted L’ shape and surface-charge distribution characteristic of tRNA mimicry, and a C-terminal domain that adopts a glycosyl transferase fold that licenses SidI to utilize GDP–mannose as a sugar precursor. This coupling of tRNA mimicry and enzymatic action endows SidI with the ability to block protein synthesis with a potency comparable to ricin, one of the most powerful toxins known. In Legionella-infected cells, the translational pausing activated by SidI elicits a stress response signature mimicking the ribotoxic stress response, which is activated by elongation inhibitors that induce ribosome collisions. SidI-mediated effects on the ribosome activate the stress kinases ZAKα and p38, which in turn drive an accumulation of the protein activating transcription factor 3 (ATF3). Intriguingly, ATF3 escapes the translation block imposed by SidI, translocates to the nucleus and orchestrates the transcription of stress-inducible genes that promote cell death, revealing a major role for ATF3 in the response to collided ribosome stress. Together, our findings elucidate a novel mechanism by which a pathogenic bacterium employs tRNA mimicry to hijack a ribosome-to-nuclear signalling pathway that regulates cell fate.
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Data availability
Key resource information is available in Supplementary Table 9. Further information and requests for resources and reagents will be fulfilled by Shaeri Mukherjee. The authors declare that the data supporting the findings of this study are available within the article and its Supplementary Information files. The atomic models of BshA (PDB ID: 5D00), PimB′ (PDB ID: 3OKA) and EEF2 bound to the ribosome (PDB ID: 6GZ5) were downloaded from the PDB. The atomic model of SidI has been deposited into the PDB (PDB ID: 8JHU) and the EM map has been deposited into the EMDB (EMDB ID: EMD-36294). The MS data files for Supplementary Table 1 (raw and search results) have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the dataset identifier PXD034240. The MS data files for Supplementary Table 3 (raw and search results) have been deposited to the MassIVE repository with the dataset identifier MSV000091992. The RNA-seq datasets have been deposited in the GenBank database under the accession code GSE205648. The nucleotide sequence of ATF3 mRNA was downloaded from the NCBI GenBank database (NM_001674.3). ChIP–seq data were mined from the publicly available ENCODE 3 database and the tracks were generated by the ENCODE Transcription Factor ChIP–seq Processing Pipeline using UCSC Genome Browser. Methods documentation and full metadata for each track can be found at the ENCODE project portal using the ENCODE file accessions: K562, ENCFF937OKC; A549, ENCFF851UTY; HepG2, ENCFF137OEY; and liver cells, ENCFF146URA. Source data are provided with this paper.
Code availability
The MaxQuant and Protein Prospector (v6.3.23) software required for the analysis of raw MS data are available at https://www.maxquant.org/ and https://prospector.ucsf.edu/prospector/mshome.htm, respectively. Code for the in-house PAVA software is available upon request. For cryo-EM image processing and data analysis, the micrograph frames were aligned using MotionCor2 (ref. 73; RRID: SCR_016499). The contrast transfer function (CTF) parameters were estimated using GCTF74 (RRID: SCR_016500). Particles were picked using Gautomatch (developed by K. Zhang; https://www2.mrc-lmb.cam.ac.uk/download/gautomatch-053/) without a template. Particles were extracted using a 64-pixel box size and classified in two dimensions using Relion75 (RRID: SCR_016274). Particles were imported to cryoSPARC76 (RRID: SCR_016501) for homogeneous refinement and heterogeneous refinement. Structure prediction analysis was performed using RaptorX77 (RRID: SCR_018118). Models were manually adjusted in Coot79 (RRID: SCR_014222). Model refinement was performed in Phenix80 (RRID: SCR_014224) Molecular graphics and analyses were performed with the UCSF Chimera package82 (RRID: SCR_004097). The ICE CRISPR analysis tool from Synthego was used to analyse the KO efficiency of cell lines and is available at https://www.synthego.com/products/bioinformatics/crispr-analysis.
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Acknowledgements
We thank all of the members of the S.M. and P.W. laboratories for their critical evaluation and discussions of the data. We thank Z.-Q. Luo for his gift of isogenic ΔsidI and SidI-complemented L. pneumophila strains. We thank S. Venkatraman and L. Calviello from the Floor laboratory for helpful discussions. We thank B. Al-Sady and E. Simental from the Al-Sady laboratory for help with radioactivity experiments. We thank J. Yee from the Spitzer laboratory for help with flow cytometry experiments. We thank J. Noack, C. J. Sarabia and B. Wang for technical assistance with the project. L.W. acknowledges a fellowship from the Damon Runyon Cancer Research Foundation (DRG-2312-17). S.S. is supported by a Helen Hay Whitney Postdoc fellowship and K99 grant (grant no. 1K99GM143527-01A1) from NIGMS. N.J.K. acknowledges financial support from the National Institutes of Health (grant no. U19 AI135990). A.L.B. acknowledges financial support from the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation. S.N.F. is a Pew Scholar in the Biomedical Sciences, supported by The Pew Charitable Trusts and acknowledges financial support from the National Institutes of Health (grant no. DP2GM132932). A. Sil acknowledges financial support from the National Institutes of Health (grant no. R01AI136735) and a gift fund from the Chan Zuckerberg Biohub. P.W. acknowledges financial support from the National Institutes of Health (grant no. R01GM032384) and the Howard Hughes Medical Institute. S.M. acknowledges financial support from the National Institutes of Health (grant nos R01GM140440 and R01GM144378), the Pew Charitable Trust (grant no. A129837), a Bowes Biomedical Investigator award and a gift fund from the Chan–Zuckerberg Biohub. We thank the Vincent J. Coates Genomics Sequencing Laboratory at the California Institute for Quantitative Biosciences (QB3) for help with the RNA-seq experiments. We also thank the QB3 shared cluster for computational support.
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Conceptualization: A. Subramanian and S.M. Methodology: A. Subramanian, L.W., T.M., M.V., S.S., D.L.S., R.J.C., N.J.K., S.N.F., A. Sil, P.W. and S.M. Investigation: A. Subramanian, L.W., T.M., M.V., E.S., E.H.P., S.K., D.L.S., R.J.C. and K.H.L. Formal analysis: A. Subramanian, L.W., M.V., D.L.S. and R.J.C. Writing (original draft): A. Subramanian, L.W. and S.M. Writing (review and editing): A. Subramanian, L.W., M.V., A. Sil, P.W. and S.M. Visualization: A. Subramanian, L.W. and S.M. Funding acquisition: P.W. and S.M. Resources: S.S., A.L.B. and S.N.F. Supervision: A. Subramanian, D.L.S., N.J.K., A. Sil, P.W. and S.M.
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P.W. is an inventor on US Patent 9708247 held by the Regents of the University of California that describes ISRIB and its analogues. Rights to the invention have been licensed by UCSF to Calico. The N.J.K. laboratory has received research support from Vir Biotechnology, F. Hoffmann-La Roche and Rezo Therapeutics. N.J.K. has financially compensated consulting agreements with the Icahn School of Medicine at Mount Sinai, New York, Maze Therapeutics, Interline Therapeutics, Rezo Therapeutics, GEn1E Lifesciences, Inc, and Twist Bioscience Corp. N.J.K. is on the Board of Directors of Rezo Therapeutics and is a shareholder in Tenaya Therapeutics, Maze Therapeutics, Rezo Therapeutics and Interline Therapeutics. D.L.S. has a consulting agreement with Maze Therapeutics and Rezo Therapeutics. All other authors declare no competing interests.
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Extended data
Extended Data Fig. 1 Analysis of protein synthesis rates in cells after heterologous expression of L. pneumophila EITs and MS analyses of SidI-interacting partners.
a–b, Analysis of protein synthesis rates in cells after heterologous expression of L. pneumophila EITs. a, Cells expressing epitope-tagged L. pneumophila EITs were subjected to puromycin pulse–chase analyses. Immunoblotting of lysates was performed using antibodies to puromycin and tubulin. Data are representative of two independent experiments. The values beneath the immunoblots represent densitometric quantification of puromycylated peptides normalized to the amount of tubulin in cells. b, The expression levels of L. pneumophila toxins were determined by qRT-PCR. Data represent the mean ± s.e.m. n, independent replicates; GFP (n = 25); lgt1, lgt2, lgt3, legK4 and ravX (n = 4); sidI and sidL (n = 6). Data were normalized to the average Ct values of the reference gene RPS29. c,d, MS analyses of SidI-interacting partners highlights the translation machinery as targets of SidI. c, Venn diagram depicting the common interacting partners enriched in GST–SidI-pulldown eluates from HEK293T cell lysates (n = 2) and RRLs (n = 1). n, independent replicates. d, List of translation-machinery components selectively enriched by GST–SidI. GST–SidI enrichment is calculated as a ratio of the peptide intensities observed in GST–SidI-pulldown eluates over GST-pulldown eluates or marked as peptide intensities uniquely measured only in GST–SidI-pulldown eluates. n.d., not detected.
Extended Data Fig. 2 Cryo-EM workflow and characterization of SidI structure.
a, Representative micrograph (from n = 5,620 micrograph images) showing the quality of data used for the final reconstruction of the SidI structure. Scale bar, 200 Å. b, Data processing scheme of the SidI structure. c, Fourier shell correlation (FSC) plots of the 3D reconstructions of SidI unmasked (grey) and masked (orange). d, Orientation angle distribution of the SidI reconstruction. e, EM maps of different regions of the SidI structure showing the quality of the data and the fit of the model. f, Local resolution map of the SidI structure.
Extended Data Fig. 3 Biochemical and biophysical characterization of SidI.
a–c, GDP hydrolysis assay with 1 µM GST, GST–SidI and GST–Lgt2. Nucleotide sugars (50 µM) were provided as precursors. Graphs depict amount of nucleotide release. Data represent the mean ± s.e.m.; n = 3 independent replicates per treatment condition. d, Overlay of SidI (gold) and GDP–PimB′ (light grey) showing the structural similarity between the enzymatic pockets and the conserved amino acids. e, Different views of the SidI structure showing the three distinct kinks. f, Surface-charge distribution on the tRNA-mimicry domains of SidI, eEF2, EF-G, eRF1 and EF-P. The boxes highlight the regions in eEF2, EF-G, eRF1 and EF-P that contact the ribosome. g, Melting curve analyses of GST–SidI and GST–SidI mutants (n = 2 independent replicates).
Extended Data Fig. 4 Comparative structural and functional enzymatic analyses of SidI reveals a potential mode of ribosome binding.
a, Overlay of eEF2 and SidI structures showing their similarity in size and shape. The positively charged loops are boxed in black boxes. b, Structure of SidI overlayed on the structure of eEF2 in the eEF2-bound ribosome structure (PDB ID: 6GZ5). c, Zoomed-in view of the eEF2–ribosome complex showing the positively charged regions on eEF2 making contacts with: (1) eS31, (2) 18S rRNA and (3) tRNA at the P-site. d,e, MS analyses of Con-A-enriched proteins after in vitro mannosylation reactions with 1 µM GST–SidI or GST–SidI R453P co-incubated with ribosomes (240 nM) and GDP–mannose (50 µM). Graphs depict the average peptide counts of ribosomal proteins and SidI (n = 2 independent replicates). f,g, Con-A-enriched ribosomal proteins at/near the A-site/P-site and peptide exit tunnel of the ribosome (PDB ID: 6GZ5) are highlighted in green and blue, respectively.
Extended Data Fig. 5 SidI mutants precipitate eEF1A and tRNA ligases from HEK293T lysates.
a,b, Enrichment of interaction partners from HEK293T lysates with GST, GST–SidI and GST–SidI K-rich loop mutant (a) or GST–SidI R453P pulldowns (b). Immunoblotting was performed using antibodies to RTCB, VARS, CARS, eEF1A and GST. Data are representative of two independent experiments.
Extended Data Fig. 6 Analyses of RNA-seq datasets reveal a dynamic induction of stress transcripts during L. pneumophila infection in an effector-dependent manner.
a, Principal component analyses on all differentially expressed genes in HEK293-FcγR cells infected with WT and ΔdotA L. pneumophila for 1, 2, 4 or 8 h, and in HEK293T cells treated with ANS (0.1 µM) and DD-B (0.1 µM) for 4 h. Coloured circles depict replicates. b, Fold induction of upregulated and downregulated transcripts in common with transcripts induced by ribosome-stalling insults. Expression levels of transcripts are after WT and ΔdotA L. pneumophila infections normalized to uninfected controls; n = 2 independent replicates per time point.
Extended Data Fig. 7 Characterization of stress-transcript induction and ATF3 accumulation by L. pneumophila and inhibitors of ribosome function.
a, Heat map of absolute stress-transcript abundances (RPKM values) from L. pneumophila-infected macrophages extracted from RNA-seq datasets previously published by Lipo and colleagues34. b, Immunoblotting of ATF3 in lysates of Casp1/Casp11−/− primary BMDM cells infected with WT or ΔdotA L. pneumophila (MOI = 10), or treated with ANS (0.01 µM, 0.1 µM, 1 µM or 10 µM). The samples were derived from parallel experiments and the gels were processed in parallel. Data are representative of two independent experiments. c, Immunoblotting of ATF3 in the lysates of HEK293-FcγR cells infected with the indicated L. pneumophila strains. The values beneath the immunoblots depict densitometric quantification of ATF3 band intensities normalized to controls. Data are representative of two independent experiments. d–h, Fold induction of ATF3, TNFRSF12A, HSPB8, PPP1R15A and GADD45A mRNA, measured by qRT-PCR, in HEK293T cells treated with vehicle control (n = 6), ANS 0.1 µM (n = 4), DD-B 0.1 µM (n = 4), DON 1 µM (n = 4), CHX 0.1 µM (n = 4) or HTN 0.1 µM (n = 4) for 4 h, or expressing FLAG–SidI (n = 6) or FLAG–SidI R453P (n = 3). Data represent the mean ± s.e.m. for n independent replicates. Transcript expression values were normalized internally to the reference gene RPS29 and expressed as the log2-transformed fold change over the levels in controls. i, Immunoblotting of ATF3 in the lysates of HEK293T cells treated with ANS (0.01 µM, 0.1 µM, 1 µM and 10 µM); DD-B (0.001 µM, 0.01 µM, 0.1 µM and 1 µM); CHX (0.01 µM, 0.1 µM, 1 µM and 10 µM); DON (0.01 µM, 0.1 µM, 1 µM and 10 µM) and HTN (0.01 µM, 0.1 µM, 1 µM and 10 µM) for 4 h. Data are representative of three independent experiments. Samples from the same experiment were processed in parallel on different gels. j, Heat map of the ATF3 band intensities measured by densitometric analyses of the blots in i. k, Indirect immunofluorescence of ATF3 in HeLa cells treated with ANS, DD-B, CHX, DON or HTN at the indicated concentrations. Scale bar, 10 µM. Data are representative of two independent experiments. The nuclear region is marked by arrows.
Extended Data Fig. 8 Characterization of translation rates, stress signalling and cell viability during L. pneumophila infections.
a, Immunoblotting of the lysates of cells infected with WT, ΔdotA and Δ5 L. pneumophila was performed using antibodies to puromycin. Ponceau S staining of membranes serves as a loading control. Data are representative of two independent experiments. b, Immunoblotting of lysates of cells treated with ANS (0.01 µM, 0.1 µM, 1 µM and 10 µM), DD-B (0.001 µM, 0.01 µM, 0.1 µM and 1 µM), CHX (0.01 µM, 0.1 µM, 1 µM and 10 µM), DON (0.01 µM, 0.1 µM, 1 µM and 10 µM) or HTN (0.01 µM, 0.1 µM, 1 µM and 10 µM) for 4 h was performed using antibodies to puromycin. Ponceau S staining of membranes serves as a loading control. Gels were processed in parallel. Data are representative of two independent experiments. c, Immunoblotting of ATF3, ATF4, phospho-eIF2 and GAPDH in the lysates of WT and eIF2 S51A+/+ MEF cells treated with ANS (0.01 µM, 0.1 µM, 1 µM and 10 µM) or thapsigargin (Tg; 1 µM) for 4 h. Data are representative of two independent experiments. d,e, Immunoblotting of ATF3 in the lysates of WT and eIF2 S51A+/+ MEF cells treated with DD-B (0.001 µM, 0.01 µM, 0.1 µM and 1 µM) for 4 h (d); and HEK293T cells treated with ANS (0.1 µM) or transfected with FLAG–SidI in the absence or presence of ISRIB (200 nM; e). Data are representative of two independent experiments. f, Immunoblotting of p-p38 and total p38 in lysates of HEK293T cells treated with ANS (0.01 µM, 0.1 µM, 1 µM and 10 µM), DD-B (0.001 µM, 0.01 µM, 0.1 µM and 1 µM), CHX (0.01 µM, 0.1 µM, 1 µM and 10 µM), DON (0.01 µM, 0.1 µM, 1 µM and 10 µM) or HTN (0.01 µM, 0.1 µM, 1 µM and 10 µM) for 4 h. Data are representative of two independent experiments. Samples from the same experiment were processed in parallel on different gels. g, Heat map of the p-p38 band intensities, measured by densitometric analyses, of the blots in f. h, Phosphoproteomics pipeline and inferred kinase activation in WT L. pneumophila-infected cells (MOI = 100) based on the analyses of phosphorylation sites on proteins. Kinases of the mitogen and stress activated protein kinase pathways are positively regulated and highlighted in green. i, Immunoblotting of p-p38 and total p38 in the lysates of HEK293-FcγR cells infected with WT, Δ5 or Δ5+sidI L. pneumophila strains (MOI = 50). The values beneath the immunoblots represent densitometric quantification of p-p38 levels normalized to the total p38 levels. Data are representative of two independent experiments. j, Cell viability measurements of HEK293-FcγR cells infected with WT L. pneumophila (MOI = 50; U.I., 8 h and 10 h samples (n = 4); 1 h, 2 h and 4 h samples (n = 2); n, independent replicates per time point. For samples with n ≥ 3, data represent the mean ± s.e.m. P values were calculated using a Student’s t-test.
Extended Data Fig. 9 ATF3 binds to genomic regions of stress-inducible transcripts.
Mapping and enrichment of ATF3-binding zones on the ATF3, TNFRSF12A, HSPB8, PPP1R15A and GADD45A genes across four cell types. H3K27Ac tracks mark acetylation of lysine 27 of the H3 histone protein across 7 cell types (GM12878, H1-hESC, HSMM, HSMM, K562, NHEK and NHLF cells). Tracks of each cell type are marked with a different colour and displayed as a transparent overlay. The enrichment scores for ATF3 peaks were extracted from the ENCODE project datasets and visualized using the UCSC genome browser (human hg38 assembly). The display for this track shows the site location with the point-source of the peak marked with a coloured vertical bar and the level of enrichment at the site indicated by the darkness of the item. The enrichment values were computed based on signal values assigned by the ENCODE pipeline. The input signal values were multiplied by a normalization factor calculated as the ratio of the maximum score value (1,000) to the signal value at 1 s.d. from the mean, with values exceeding 1,000 capped at 1,000.
Extended Data Fig. 10 ATF3 depletion attenuates stress-transcript induction.
a–d, Fold-change induction of TNFRSF12A, HSPB8, PPP1R15A and GADD45A mRNA in parent and ATF3-KO HEK293T cells expressing GFP, FLAG–SidI or FLAG–SidI R453P, or treated with ANS (0.1 µM) measured by qRT-PCR (n = 2 independent replicates). Transcript expression values were normalized internally to the reference gene RPS29 and expressed as fold change over the levels in GFP-expressing cells.
Supplementary information
Supplementary Table 1
MS analyses of SidI-interacting partners in HEK293T lysates and RRLs.
Supplementary Tables 2, 7, 8 and 9
Supplementary Table 2. Cryo-EM data collection, reconstruction and model refinement statistics. Supplementary Table 7. List of siRNAs and oligonucleotides. Supplementary Table 8. Amino-acid sequences of Legionella effector proteins used in this study. Supplementary Table 9. Key resources used in this study.
Supplementary Table 3
MS analyses of Con-A pulldowns after in vitro mannosylation reactions with SidI and ribosomes.
Supplementary Table 4
Fold changes in transcript expression levels in cells infected with L. pneumophila or treated with the ribosome-stalling inducers ANS and DD-B. Differentially expressed genes were identified by comparing replicate means for contrasts of interest using LIMMA version 3.30.8. Genes were considered significantly differentially expressed if they were statistically significant (at 5% FDR) with an effect size of at least 2× (absolute log2(fold change) ≥ 1) for a given contrast. LIMMA implements a two-sided moderated t-test with empirical Bayesian shrinkage.
Supplementary Table 5
Gene-set-enrichment analyses on the ranked list of genes from the RNA-seq datasets.
Supplementary Table 6
Inferred kinase-activity scores for cells infected with L. pneumophila for 1 h by reanalysis of phosphoproteomics datasets in the study by Noack and colleagues43.
Source data
Source Data Figs. 1–7 and Extended Data Figs. 1,5,7,8.
Unprocessed western blots and/or gels.
Source Data Figs. 1–7 and Extended Data Figs. 1,3,4,6–8,10.
Statistical source data for graphs.
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Subramanian, A., Wang, L., Moss, T. et al. A Legionella toxin exhibits tRNA mimicry and glycosyl transferase activity to target the translation machinery and trigger a ribotoxic stress response. Nat Cell Biol 25, 1600–1615 (2023). https://doi.org/10.1038/s41556-023-01248-z
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DOI: https://doi.org/10.1038/s41556-023-01248-z
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