Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution
- University of Washington, United States
- Centers for Disease Control and Prevention (CDC), United States
- The Francis Crick Institute, United Kingdom
- The Francis Crick Insitute, United Kingdom
- National Institute of Infectious Diseases, Japan
- National Instituite of Infectious Diseases, Japan
- Peter Doherty Institute for Infection and Immunity, United States
- Peter Doherty Institute for Infection and Immunity, Australia
- University of Basel, Switzerland
- Fred Hutchinson Cancer Research Center, United States
Abstract
Seasonal influenza virus A/H3N2 is a major cause of death globally. Vaccination remains the most effective preventative. Rapid mutation of hemagglutinin allows viruses to escape adaptive immunity. This antigenic drift necessitates regular vaccine updates. Effective vaccine strains need to represent H3N2 populations circulating one year after strain selection. Experts select strains based on experimental measurements of antigenic drift and predictions made by models from hemagglutinin sequences. We developed a novel influenza forecasting framework that integrates phenotypic measures of antigenic drift and functional constraint with previously published sequence-only fitness estimates. Forecasts informed by phenotypic measures of antigenic drift consistently outperformed previous sequence- only estimates, while sequence-only estimates of functional constraint surpassed more comprehensive experimentally-informed estimates. Importantly, the best models integrated estimates of both functional constraint and either antigenic drift phenotypes or recent population growth.
Data availability
Sequence data are available from GISAID using accession ids provided in Supplemental File S1.Source code, derived data from serological measurements, fitness metric annotations, and resulting fitness model performance data are available in the project's GitHub repository (https://github.com/blab/flu-forecasting).Raw serological measurements are restricted from public distribution by previous data sharing agreements.
Article and author information
Author details
Pierre Barrat-Charlaix
Funding
Cancer Research UK (FC001030)
- Lynne Whittaker
- Burcu Ermetal
- Rodney Stuart Daniels
- John W McCauley
National Institute of Allergy and Infectious Diseases (U19AI117891-01)
- Trevor Bedford
National Institute of Allergy and Infectious Diseases (R01AI127893-01)
- Pierre Barrat-Charlaix
- Richard A Neher
- Trevor Bedford
Medical Research Council (FC001030)
- Lynne Whittaker
- Burcu Ermetal
- Rodney Stuart Daniels
- John W McCauley
Wellcome (FC001030)
- Lynne Whittaker
- Burcu Ermetal
- Rodney Stuart Daniels
- John W McCauley
Ministry of Health, Labour and Welfare (10110400)
- Seiichiro Fujisaki
- Kazuya Nakamura
- Noriko Kishida
- Shinji Watanabe
- Hideki Hasegawa
Japan Agency for Medical Research and Development (JPfk0108118)
- Shinji Watanabe
Australian Government Department of Health
- Ian Barr
- Kanta Subbarao
National Institute of Allergy and Infectious Diseases (F31AI140714)
- John Huddleston
National Institute of General Medical Sciences (R35GM119774-01)
- Trevor Bedford
Pew Charitable Trusts
- Trevor Bedford
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
-
- 4,803
- views
-
- 556
- downloads
-
- 57
- 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)
Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution
eLife 9:e60067.
https://doi.org/10.7554/eLife.60067
Further reading
-
- Evolutionary Biology
- Epidemiology and Global Health
- Microbiology and Infectious Disease
- Genetics and Genomics
eLife is pleased to present a Special Issue to highlight recent advances in the growing and increasingly interdisciplinary field of evolutionary medicine.
-
- Cell Biology
- Evolutionary Biology
Maintenance of rod-shape in bacterial cells depends on the actin-like protein MreB. Deletion of mreB from Pseudomonas fluorescens SBW25 results in viable spherical cells of variable volume and reduced fitness. Using a combination of time-resolved microscopy and biochemical assay of peptidoglycan synthesis, we show that reduced fitness is a consequence of perturbed cell size homeostasis that arises primarily from differential growth of daughter cells. A 1000-generation selection experiment resulted in rapid restoration of fitness with derived cells retaining spherical shape. Mutations in the peptidoglycan synthesis protein Pbp1A were identified as the main route for evolutionary rescue with genetic reconstructions demonstrating causality. Compensatory pbp1A mutations that targeted transpeptidase activity enhanced homogeneity of cell wall synthesis on lateral surfaces and restored cell size homeostasis. Mechanistic explanations require enhanced understanding of why deletion of mreB causes heterogeneity in cell wall synthesis. We conclude by presenting two testable hypotheses, one of which posits that heterogeneity stems from non-functional cell wall synthesis machinery, while the second posits that the machinery is functional, albeit stalled. Overall, our data provide support for the second hypothesis and draw attention to the importance of balance between transpeptidase and glycosyltransferase functions of peptidoglycan building enzymes for cell shape determination.
