Signaling diversity enabled by Rap1-regulated plasma membrane ERK with distinct temporal dynamics

  1. Jeremiah Keyes
  2. Ambhighainath Ganesan
  3. Olivia Molinar-Inglis
  4. Archer Hamidzadeh
  5. Jinfan Zhang
  6. Megan Ling
  7. JoAnn Trejo
  8. Andre Levchenko
  9. Jin Zhang  Is a corresponding author
  1. University of California, San Diego, United States
  2. The Johns Hopkins University School of Medicine, United States
  3. Yale University, United States

Abstract

A variety of different signals induce specific responses through a common, Extracellular-signal regulated kinase (ERK)-dependent cascade. It has been suggested that signaling specificity can be achieved through precise temporal regulation of ERK activity. Given the wide distrubtion of ERK susbtrates across different subcellular compartments, it is important to understand how ERK activity is temporally regulated at specific subcellular locations. To address this question, we have expanded the toolbox of Förster Resonance Energy Transfer (FRET)-based ERK biosensors by creating a series of improved biosensors targeted to various subcellular regions via sequence specific motifs to measure spatiotemporal changes in ERK activity. Using these sensors, we showed that EGF induces sustained ERK activity near the plasma membrane in sharp contrast to the transient activity observed in the cytoplasm and nucleus. Furthermore, EGF-induced plasma membrane ERK activity involves Rap1, a noncanonical activator, and controls cell morphology and EGF-induced membrane protrusion dynamics. Our work strongly supports that spatial and temporal regulation of ERK activity is integrated to control signaling specificity from a single extracellular signal to multiple cellular processes.

Data availability

All data generated and analyzed in this study are included in manuscript and figures.

Article and author information

Author details

  1. Jeremiah Keyes

    Department of Pharmacology, University of California, San Diego, La Jolla, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4253-6834
  2. Ambhighainath Ganesan

    Department of Pharmacology and Molecular Sciences, The Johns Hopkins University School of Medicine, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Olivia Molinar-Inglis

    Department of Pharmacology, University of California, San Diego, La Jolla, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Archer Hamidzadeh

    Department of Biomedical Engineering, Yale University, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Jinfan Zhang

    Department of Pharmacology, University of California, San Diego, La Jolla, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Megan Ling

    Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. JoAnn Trejo

    Department of Pharmacology, University of California, San Diego, La Jolla, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Andre Levchenko

    Department of Biomedical Engineering, Yale University, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Jin Zhang

    Department of Pharmacology, Department of Bioengineering, Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, United States
    For correspondence
    jzhang32@ucsd.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7145-7823

Funding

National Cancer Institute (R35 CA197622)

  • Jin Zhang

National Institute of Diabetes and Digestive and Kidney Diseases (R01 DK073368)

  • Jin Zhang

National Institute of General Medical Sciences (K12GM068524)

  • JoAnn Trejo

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

Copyright

© 2020, Keyes 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

  • 4,602
    views
  • 617
    downloads
  • 44
    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. Jeremiah Keyes
  2. Ambhighainath Ganesan
  3. Olivia Molinar-Inglis
  4. Archer Hamidzadeh
  5. Jinfan Zhang
  6. Megan Ling
  7. JoAnn Trejo
  8. Andre Levchenko
  9. Jin Zhang
(2020)
Signaling diversity enabled by Rap1-regulated plasma membrane ERK with distinct temporal dynamics
eLife 9:e57410.
https://doi.org/10.7554/eLife.57410

Share this article

https://doi.org/10.7554/eLife.57410

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.