Abstract
In order to survive, bacteria continually sense, and respond to, environmental fluctuations. Stringent control represents a key bacterial stress response to nutrient starvation1,2 that leads to rapid and comprehensive reprogramming of metabolic and transcriptional patterns3. In general, transcription of genes for growth and proliferation is downregulated, while those important for survival and virulence are upregulated4. Amino acid starvation is sensed by depletion of the aminoacylated tRNA pools5, and this results in accumulation of ribosomes stalled with non-aminoacylated (uncharged) tRNA in the ribosomal A site6,7. RelA is recruited to stalled ribosomes and activated to synthesize a hyperphosphorylated guanosine analogue, (p)ppGpp8, which acts as a pleiotropic secondary messenger. However, structural information about how RelA recognizes stalled ribosomes and discriminates against aminoacylated tRNAs is missing. Here we present the cryo-electron microscopy structure of RelA bound to the bacterial ribosome stalled with uncharged tRNA. The structure reveals that RelA utilizes a distinct binding site compared to the translational factors, with a multi-domain architecture that wraps around a highly distorted A-site tRNA. The TGS (ThrRS, GTPase and SpoT) domain of RelA binds the CCA tail to orient the free 3′ hydroxyl group of the terminal adenosine towards a β-strand, such that an aminoacylated tRNA at this position would be sterically precluded. The structure supports a model in which association of RelA with the ribosome suppresses auto-inhibition to activate synthesis of (p)ppGpp and initiate the stringent response. Since stringent control is responsible for the survival of pathogenic bacteria under stress conditions, and contributes to chronic infections and antibiotic tolerance, RelA represents a good target for the development of novel antibacterial therapeutics.
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Acknowledgements
We thank A. Kelley for providing tRNAs, A. Xu and J. Murray for their contributions to the early stages of this project, C. G. Savva for help with data collection, J. Grimmett and T. Darling for computing support, and X. Bai, G. Murshudov, S. H. W. Scheres, and S. Tan for discussions. This work was supported by grants to V.R. from the UK Medical Research Council (MC_U105184332), the Wellcome Trust (WT096570), the Agouron Institute, and the Louis-Jeantet Foundation.
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A.B., I.S.F., and V.R. designed the study. Y.G. purified ribosomes. I.S.F. prepared samples, optimized conditions and collected data. A.B. processed data and interpreted the cryo-electron microscopy reconstructions. A.B., I.S.F., and V.R. wrote the manuscript. All authors discussed and commented on the final manuscript.
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Extended data figures and tables
Extended Data Figure 1 In silico 3D classification scheme.
a, All particles were subjected to 2D classification, from which non-ribosomal particles were discarded, before 3D refinement. To isolate particles containing A-site tRNA and RelA, 3D classification focused on occupancy of the ribosomal A site was performed. Refinement of these 183,615 particles resulted in a reconstruction with a nominal resolution of 2.9 Å. A second round of 3D classification isolated 164,353 well-aligned particles. Conformational heterogeneity of the ribosome was resolved by 3D classification without alignment, which identified two dominant classes in which the body of the small subunit occupies different positions (indicated with an arrow). Class 1 was used as the reference for model building, refinement, and interpretation. To resolve additional conformational heterogeneity of RelA, focused classification with signal subtraction (FCwSS) was performed on each domain, with the hydrolase (HYD) and synthetase (SYN) domains treated as a single unit. For the RRM, zinc-finger and TGS domains a single class was isolated in which the density was better resolved than in the reference class. The overall resolution of the reconstructions are reported according to the Fourier shell correlation (FSC) = 0.143 criterion. Multiple conformations of the HYD and SYN domains were identified, with the four best-resolved classes shown. Together these account for 42% of the particles. b, The two main classes for the TGS domain provide an example of the small conformational differences that were isolated using FCwSS.
Extended Data Figure 2 Quality of maps and models.
a, FSC curve for the EM map. b, The unfiltered and unsharpened density map, in both surface and slice view, coloured by local resolution. c, Fit of models to maps. FSC curves calculated between the refined model and the final map (black), with the self- and cross-validated correlations in blue and magenta, respectively. Information beyond 3.0 Å was not used during refinement and preserved for validation. d, e, Examples of high-resolution features of the map. d, Density for selected rRNA modifications and paromomycin. e, Density for the codon–anticodon interaction in the A site. e, Unfiltered and unsharpened map of RelA bound to the bacterial ribosome, showing the ribosome-binding RelA domains coloured by local resolution according to the FCwSS maps (see Extended Data Fig. 1). The regions amplified in panels f and g are highlighted. f, The RelA ZFD and RRM coloured by local resolution. g, The TGS domain coloured by local resolution.
Extended Data Figure 3 Examples of RelA density.
a, Density for the interaction between the 3′ CCA of the A/T-tRNA and the TGS domain. b, A modelled tRNAAla demonstrates that even the smallest aminoacyl groups would clash with RelA. The sphere size of the atoms of the aminoacyl group corresponds to their van der Waals radii. c, C74 stacks with His432 and C75 can potentially interact with Arg438 of the TGS domain. d, Density for helix α4 of the TGS domain. e, Density for TGS α3. f, Density for the interaction between the ZFD and uS19, showing distinctive density for two consecutive histidine residues. g, Example of side chain density used for the de novo building of the ZFD.
Extended Data Figure 4 RelA domains are connected by flexible linkers.
Two related views showing the density that connects the RelA HYD, SYN and TGS domains with the ZFD/RRM. The linker runs between the A/T-tRNA and the ribosome, but remains flexible as suggested by the weak and broken density. The figure shows the unfiltered, unsharpened density map for the ribosomal small subunit (SSU) of class 4 (Extended Data Fig. 1) with the large subunit removed for clarity.
Extended Data Figure 5 The conformation of uncharged A-site tRNA in the presence of RelA is distinct from aminoacylated A/T-tRNA in the presence of EF-Tu.
a, The ASLs of A-site tRNA (purple) and A/T-tRNA (grey) superpose until base-pair 27:43. At this point, the A-site tRNA is distorted so that the tRNA elbow regions are separated by a 6° rotation. b, A second 11° rotation occurs at base-pair 7:66 of the acceptor stem so that the A-site tRNA in the presence of RelA is closer to the ribosomal SRL.
Extended Data Figure 6 RelA topology diagram.
Secondary structure elements for RelA residues 404–740 are numbered separately for each domain. Unbuilt sections are shown as dashed lines. Topologies were extracted using Pro-origami50.
Extended Data Figure 7 RelA binds RNA through electropositive surfaces.
a, The ZFD and RRM of RelA act together to recognize the ASF of the LSU rRNA. b, As in a, but with the ZFD and RRM shown in surface representation coloured by electrostatic potential. c, The RelA TGS domain binds the acceptor arm of the A/T-tRNA. d, As in c, but with the TGS domain in surface representation coloured by electrostatic potential. Electrostatic potentials were calculated using APBS51, where k is Boltzmann’s constant, T is the temperature of the calculation (310 K) and ec is the charge of an electron.
Extended Data Figure 8 RelA contains an RNA recognition motif (RRM).
a, The RRM from RelA binds the ASF (nucleotides 894–899 shown) through the face of the β-sheet. b, RRMs recognize a wide variety of RNA molecules, but share a common fold and a similar protein–RNA interface, for example in the interaction between PRP24 and U6 small nuclear RNA (PDB accession code 4N0T).
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Brown, A., Fernández, I., Gordiyenko, Y. et al. Ribosome-dependent activation of stringent control. Nature 534, 277–280 (2016). https://doi.org/10.1038/nature17675
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DOI: https://doi.org/10.1038/nature17675
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