Ribosome•RelA structures reveal the mechanism of stringent response activation
Abstract
Stringent response is a conserved bacterial stress response underlying virulence and antibiotic resistance. RelA/SpoT-homolog proteins synthesize transcriptional modulators (p)ppGpp, allowing bacteria to adapt to stresses. RelA is activated during amino-acid starvation, when cognate deacyl-tRNA binds to the ribosomal A (aminoacyl-tRNA) site. We report four cryo-EM structures of E. coli RelA bound to the 70S ribosome, in the absence and presence of deacyl-tRNA accommodating in the 30S A site. The boomerang-shaped RelA with a wingspan of more than 100 Å wraps around the A/R (30S A-site/RelA-bound) tRNA. The CCA end of the A/R tRNA pins the central TGS domain against the 30S subunit, presenting the (p)ppGpp-synthetase domain near the 30S spur. The ribosome and A/R tRNA are captured in three conformations, revealing hitherto elusive states of tRNA engagement with the ribosomal decoding center. Decoding-center rearrangements are coupled with the step-wise 30S-subunit 'closure', providing insights into the dynamics of high-fidelity tRNA decoding.
Data availability
-
Structure of RelA bound to ribosome in absence of A/R tRNA (Structure I)Publicly available at the RCSB Protein Data Bank (accession no: 5KPS).
-
Structure of RelA bound to ribosome in presence of A/R tRNA (Structure II)Publicly available at the RCSB Protein Data Bank (accession no: 5KPV).
-
Structure of RelA bound to ribosome in presence of A/R tRNA (Structure III)Publicly available at the RCSB Protein Data Bank (accession no: 5KPW).
-
Structure of RelA bound to ribosome in presence of A/R tRNA (Structure IV)Publicly available at the RCSB Protein Data Bank (accession no: 5KPX).
Article and author information
Author details
Funding
Howard Hughes Medical Institute
- Nikolaus Grigorieff
National Institutes of Health (RO1 GM106105)
- Andrei A Korostelev
National Institutes of Health (PO1 GM62580)
- Nikolaus Grigorieff
Helen Hay Whitney Foundation
- Anna B Loveland
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2016, Loveland et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 5,588
- views
-
- 929
- downloads
-
- 140
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Biochemistry and Chemical Biology
- Structural Biology and Molecular Biophysics
African trypanosomes are the causative agents of neglected tropical diseases affecting both humans and livestock. Disease control is highly challenging due to an increasing number of drug treatment failures. African trypanosomes are extracellular, blood-borne parasites that mainly rely on glycolysis for their energy metabolism within the mammalian host. Trypanosomal glycolytic enzymes are therefore of interest for the development of trypanocidal drugs. Here, we report the serendipitous discovery of a camelid single-domain antibody (sdAb aka Nanobody) that selectively inhibits the enzymatic activity of trypanosomatid (but not host) pyruvate kinases through an allosteric mechanism. By combining enzyme kinetics, biophysics, structural biology, and transgenic parasite survival assays, we provide a proof-of-principle that the sdAb-mediated enzyme inhibition negatively impacts parasite fitness and growth.
-
- Structural Biology and Molecular Biophysics
The relationship between protein dynamics and function is essential for understanding biological processes and developing effective therapeutics. Functional sites within proteins are critical for activities such as substrate binding, catalysis, and structural changes. Existing computational methods for the predictions of functional residues are trained on sequence, structural, and experimental data, but they do not explicitly model the influence of evolution on protein dynamics. This overlooked contribution is essential as it is known that evolution can fine-tune protein dynamics through compensatory mutations either to improve the proteins’ performance or diversify its function while maintaining the same structural scaffold. To model this critical contribution, we introduce DyNoPy, a computational method that combines residue coevolution analysis with molecular dynamics simulations, revealing hidden correlations between functional sites. DyNoPy constructs a graph model of residue–residue interactions, identifies communities of key residue groups, and annotates critical sites based on their roles. By leveraging the concept of coevolved dynamical couplings—residue pairs with critical dynamical interactions that have been preserved during evolution—DyNoPy offers a powerful method for predicting and analysing protein evolution and dynamics. We demonstrate the effectiveness of DyNoPy on SHV-1 and PDC-3, chromosomally encoded β-lactamases linked to antibiotic resistance, highlighting its potential to inform drug design and address pressing healthcare challenges.