1. Biochemistry and Chemical Biology
  2. Evolutionary Biology
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Enhanced ER proteostasis and temperature differentially impact the mutational tolerance of influenza hemagglutinin

  1. Angela M Phillips
  2. Michael B Doud
  3. Luna O Gonzalez
  4. Vincent L Butty
  5. Yu-Shan Lin
  6. Jesse D Bloom
  7. Matthew D Shoulders  Is a corresponding author
  1. Massachusetts Institute of Technology, United States
  2. Fred Hutchinson Cancer Research Center, United States
  3. Tufts University, United States
Research Article
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Cite this article as: eLife 2018;7:e38795 doi: 10.7554/eLife.38795

Abstract

Herein, we systematically and quantitatively evaluate whether endoplasmic reticulum (ER) proteostasis factors impact the mutational tolerance of secretory pathway proteins. We focus on influenza hemagluttinin (HA), a viral membrane protein that folds in the host's ER via a complex pathway. By integrating chemical methods to modulate ER proteostasis with deep mutational scanning to assess mutational tolerance, we discover that upregulation of ER proteostasis factors broadly enhances HA mutational tolerance across diverse structural elements. Remarkably, this proteostasis network-enhanced mutational tolerance occurs at the same sites where mutational tolerance is most reduced by propagation at fever-like temperature. These findings have important implications for influenza evolution, because influenza immune escape is contingent on HA possessing sufficient mutational tolerance to evade antibodies while maintaining the capacity to fold and function. More broadly, this work provides the first experimental evidence that ER proteostasis mechanisms define the mutational tolerance and, therefore, the evolution of secretory pathway proteins.

Data availability

FASTQ files for DMS sequencing are available in the Sequence Read Archive under accession number SRP149672. The deep mutational scanning data analysis will be available upon publication at https://github.com/amphilli/HA_DMS_2018, and is also available in Dataset 1. All differential selection values from deep mutational scanning (pre- and post-filtering) are available in Figure 5-source data 1. The complete RNAseq data are available from GEO under accession number GSE115168.

The following data sets were generated

Article and author information

Author details

  1. Angela M Phillips

    Department of Chemistry, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9806-7574
  2. Michael B Doud

    Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8172-6342
  3. Luna O Gonzalez

    Department of Mathematics, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Vincent L Butty

    BioMicro Center, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Yu-Shan Lin

    Department of Chemistry, Tufts University, Medford, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6460-2877
  6. Jesse D Bloom

    Fred Hutchinson Cancer Research Center, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1267-3408
  7. Matthew D Shoulders

    Department of Chemistry, Massachusetts Institute of Technology, Cambridge, United States
    For correspondence
    mshoulde@mit.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6511-3431

Funding

National Science Foundation (CAREER Award 1652390)

  • Matthew D Shoulders

National Science Foundation (Graduate Research Fellowship)

  • Angela M Phillips

Richard and Susan Smith Family Foundation (Award for Excellence in Biomedical Research)

  • Matthew D Shoulders

Massachusetts Institute of Technology

  • Matthew D Shoulders

Tufts University

  • Yu-Shan Lin

National Cancer Institute (Koch Institute Support (core) Grant P30-CA14051)

  • Vincent L Butty
  • Matthew D Shoulders

National Institutes of Health (Al127893)

  • Jesse D Bloom

Howard Hughes Medical Institute (Faculty Scholars grant)

  • Jesse D Bloom

Simons Foundation (Faculty Scholars grant)

  • Jesse D Bloom

National Institute of Environmental Health Sciences (MIT Center for Environmental Health Sciences (core) Grant P30-ES002109)

  • Vincent L Butty
  • Matthew D Shoulders

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

Reviewing Editor

  1. Franz-Ulrich Hartl, Max Planck Institute for Biochemistry, Germany

Publication history

  1. Received: June 6, 2018
  2. Accepted: August 29, 2018
  3. Accepted Manuscript published: September 6, 2018 (version 1)
  4. Version of Record published: October 4, 2018 (version 2)

Copyright

© 2018, Phillips 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.

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