Enhanced ER proteostasis and temperature differentially impact the mutational tolerance of influenza hemagglutinin
- Massachusetts Institute of Technology, United States
- Fred Hutchinson Cancer Research Center, United States
- Tufts University, United States
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.
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ER proteostasis and temperature differentially impact the mutational tolerance of influenza hemagglutininPublicly available at the NCBI Gene Expression Omnibus (accession no: GSE115168).
Article and author information
Author details
Matthew D Shoulders
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.
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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Enhanced ER proteostasis and temperature differentially impact the mutational tolerance of influenza hemagglutinin
eLife 7:e38795.
https://doi.org/10.7554/eLife.38795
Further reading
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- Biochemistry and Chemical Biology
- Computational and Systems Biology
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.
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- Biochemistry and Chemical Biology
- Genetics and Genomics
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.
