eIF1A residues implicated in cancer stabilize translation preinitiation complexes and favor suboptimal initiation sites in yeast

  1. Pilar Martin-Marcos
  2. Fujun Zhou
  3. Charm Karunasiri
  4. Fan Zhang
  5. Jinsheng Dong
  6. Jagpreet Nanda
  7. Neelam Sen
  8. Mercedes Tamame
  9. Michael Zeschnigk
  10. Jon R Lorsch  Is a corresponding author
  11. Alan G Hinnebusch  Is a corresponding author
  1. National Institutes of Health, United States
  2. Universidad de Salamanca, Spain
  3. University Duisburg-Essen, Germany

Abstract

The translation pre-initiation complex (PIC) scans the mRNA for an AUG codon in favorable context, and AUG recognition stabilizes a closed PIC conformation. The unstructured N-terminal tail (NTT) of yeast eIF1A deploys five basic residues to contact tRNAi, mRNA, or 18S rRNA exclusively in the closed state. Interestingly, EIF1AX mutations altering the human eIF1A NTT are associated with uveal melanoma (UM). We found that substituting all five basic residues, and seven UM-associated substitutions, in yeast eIF1A suppresses initiation at near-cognate UUG codons and AUGs in poor context. Ribosome profiling of NTT substitution R13P reveals heightened discrimination against unfavorable AUG context genome-wide. Both R13P and K16D substitutions destabilize the closed complex at UUG codons in reconstituted PICs. Thus, electrostatic interactions involving the eIF1A NTT stabilize the closed conformation and promote utilization of suboptimal start codons. We predict UM-associated mutations alter human gene expression by increasing discrimination against poor initiation sites.

Data availability

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Pilar Martin-Marcos

    Laboratory on the Mechanism and Regulation of Protein Synthesis, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, United States
    Competing interests
    No competing interests declared.
  2. Fujun Zhou

    Laboratory on the Mechanism and Regulation of Protein Synthesis, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, United States
    Competing interests
    No competing interests declared.
  3. Charm Karunasiri

    Laboratory on the Mechanism and Regulation of Protein Synthesis, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, United States
    Competing interests
    No competing interests declared.
  4. Fan Zhang

    Laboratory of Gene Regulation and Development, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, United States
    Competing interests
    No competing interests declared.
  5. Jinsheng Dong

    Laboratory of Gene Regulation and Development, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, United States
    Competing interests
    No competing interests declared.
  6. Jagpreet Nanda

    Laboratory on the Mechanism and Regulation of Protein Synthesis, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, United States
    Competing interests
    No competing interests declared.
  7. Neelam Sen

    Laboratory of Gene Regulation and Development, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, United States
    Competing interests
    No competing interests declared.
  8. Mercedes Tamame

    Instituto de Biología Funcional y Genómica (IBFG-CSIC)), Universidad de Salamanca, Salamanca, Spain
    Competing interests
    No competing interests declared.
  9. Michael Zeschnigk

    Institute of Human Genetics and Eye Cancer Research Group, University Duisburg-Essen, Essen, Germany
    Competing interests
    No competing interests declared.
  10. Jon R Lorsch

    Laboratory on the Mechanism and Regulation of Protein Synthesis, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, United States
    For correspondence
    jon.lorsch@nih.gov
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4521-4999
  11. Alan G Hinnebusch

    Laboratory of Gene Regulation and Development, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, United States
    For correspondence
    ahinnebusch@nih.gov
    Competing interests
    Alan G Hinnebusch, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1627-8395

Funding

National Institutes of Health (Intramural Research Program)

  • Alan G Hinnebusch

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Metrics

  • 2,622
    views
  • 388
    downloads
  • 46
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

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)

  1. Pilar Martin-Marcos
  2. Fujun Zhou
  3. Charm Karunasiri
  4. Fan Zhang
  5. Jinsheng Dong
  6. Jagpreet Nanda
  7. Neelam Sen
  8. Mercedes Tamame
  9. Michael Zeschnigk
  10. Jon R Lorsch
  11. Alan G Hinnebusch
(2017)
eIF1A residues implicated in cancer stabilize translation preinitiation complexes and favor suboptimal initiation sites in yeast
eLife 6:e31250.
https://doi.org/10.7554/eLife.31250

Share this article

https://doi.org/10.7554/eLife.31250

Further reading

    1. Biochemistry and Chemical Biology
    2. Computational and Systems Biology
    A Sofia F Oliveira, Fiona L Kearns ... Adrian J Mulholland
    Short Report

    The spike protein is essential to the SARS-CoV-2 virus life cycle, facilitating virus entry and mediating viral-host membrane fusion. The spike contains a fatty acid (FA) binding site between every two neighbouring receptor-binding domains. This site is coupled to key regions in the protein, but the impact of glycans on these allosteric effects has not been investigated. Using dynamical nonequilibrium molecular dynamics (D-NEMD) simulations, we explore the allosteric effects of the FA site in the fully glycosylated spike of the SARS-CoV-2 ancestral variant. Our results identify the allosteric networks connecting the FA site to functionally important regions in the protein, including the receptor-binding motif, an antigenic supersite in the N-terminal domain, the fusion peptide region, and another allosteric site known to bind heme and biliverdin. The networks identified here highlight the complexity of the allosteric modulation in this protein and reveal a striking and unexpected link between different allosteric sites. Comparison of the FA site connections from D-NEMD in the glycosylated and non-glycosylated spike revealed that glycans do not qualitatively change the internal allosteric pathways but can facilitate the transmission of the structural changes within and between subunits.

    1. Biochemistry and Chemical Biology
    2. Genetics and Genomics
    Conor J Howard, Nathan S Abell ... Nathan B Lubock
    Research Article

    Deep Mutational Scanning (DMS) is an emerging method to systematically test the functional consequences of thousands of sequence changes to a protein target in a single experiment. Because of its utility in interpreting both human variant effects and protein structure-function relationships, it holds substantial promise to improve drug discovery and clinical development. However, applications in this domain require improved experimental and analytical methods. To address this need, we report novel DMS methods to precisely and quantitatively interrogate disease-relevant mechanisms, protein-ligand interactions, and assess predicted response to drug treatment. Using these methods, we performed a DMS of the melanocortin-4 receptor (MC4R), a G-protein-coupled receptor (GPCR) implicated in obesity and an active target of drug development efforts. We assessed the effects of >6600 single amino acid substitutions on MC4R’s function across 18 distinct experimental conditions, resulting in >20 million unique measurements. From this, we identified variants that have unique effects on MC4R-mediated Gαs- and Gαq-signaling pathways, which could be used to design drugs that selectively bias MC4R’s activity. We also identified pathogenic variants that are likely amenable to a corrector therapy. Finally, we functionally characterized structural relationships that distinguish the binding of peptide versus small molecule ligands, which could guide compound optimization. Collectively, these results demonstrate that DMS is a powerful method to empower drug discovery and development.