Real-time tracking of virus evolution
Trevor Bedford (@trvrb)
6 Apr 2018
Bioinformatics and Genomics Seminar
UNC Charlotte
We work at the interface of virology, evolution and epidemiology
Sequencing to reconstruct pathogen spread
Epidemic process
Sample some individuals
Sequence and determine phylogeny
Sequence and determine phylogeny
Localized Middle Eastern MERS-CoV phylogeny
Regional West African Ebola phylogeny
Global influenza phylogeny
Phylogenetic tracking has the capacity to revolutionize epidemiology
Outline
- Influenza circulation and antigenic drift
- Ebola spread in West Africa
- Zika spread in the Americas
- "Real-time" analyses
Influenza virion
Population turnover (in H3N2) is extremely rapid
Antigenic drift necessitates frequent H3N2 vaccine updates
Integrating influenza antigenic dynamics with molecular evolution
with Andrew Rambaut, Marc Suchard, Philippe Lemey and others
Global circulation patterns of seasonal influenza viruses vary with rates of antigenic drift
with Colin Russell, Philippe Lemey, Steven Riley and many others
Scientific publishing practices vs
a fast evolving virus
Vaccine strain selection timeline
nextflu
Project to provide a real-time view of the evolving influenza population
nextflu
Project to provide a real-time view of the evolving influenza population
All in collaboration with Richard Neher
nextflu
pipeline
- Download all recent HA sequences from GISAID
- Filter to remove outliers
- Subsample across time and space
- Align sequences
- Build tree
- Estimate clade frequencies
- Infer antigenic phenotypes
- Export for visualization
Phenotypic assay data used to directly infer titer drops on the phylogeny
Antigenic drift drives population turnover
Antigenic drift drives population turnover
Virus genomes reveal factors that spread and sustained the Ebola epidemic
with Gytis Dudas, Andrew Rambaut, Luiz Carvalho, Marc Suchard, Philippe Lemey,
and many others
Sequencing of 1610 Ebola virus genomes collected during the 2013-2016 West African epidemic
Phylogenetic reconstruction of evolution and spread
Tracking migration events
Factors influencing migration rates
Effect of borders on migration rates
Spatial structure at the country level
Substantial mixing at the regional level
Regional outbreaks due to multiple introductions
Each introduction results in a minor outbreak
Zika's arrival and spread in the Americas
Establishment and cryptic transmission of Zika virus in Brazil and the Americas
with Nuno Faria, Nick Loman, Oli Pybus, Luiz Alcantara, Ester Sabino, Josh Quick,
Alli Black,
Ingra Morales, Julien Thézé, Marcio Nunes, Jacqueline de Jesus,
Marta Giovanetti, Moritz Kraemer, Sarah Hill and many others
Road trip through northeast Brazil to collect samples and sequence
Case reports and diagnostics suggest initiation in northeast Brazil
Phylogeny infers an origin in northeast Brazil
Genomic epidemiology reveals multiple introductions of Zika virus into the United States
with Nathan Grubaugh, Kristian Andersen, Jason Ladner, Gustavo Palacios, Sharon Isern, Oli Pybus,
Moritz Kraemer, Gytis Dudas,
Amanda Tan, Karthik Gangavarapu, Michael Wiley, Stephen White,
Julien Thézé, Scott Michael, Leah Gillis, Pardis Sabeti, and many others
Outbreak of locally-acquired infections focused in Miami-Dade county
Phylogeny shows introductions from the Caribbean and a surprising degree of clustering
Flow of infected travelers greatest from Caribbean
Clustering suggests fewer, longer transmission chains and higher R0
Preliminary analysis of 31 genomes shows multiple introductions to USVI
Genomic analyses were mostly done in a retrospective manner
Dudas and Rambaut 2016
Key challenges to making genomic epidemiology actionable
- Timely analysis and sharing of results critical
- Dissemination must be scalable
- Integrate many data sources
- Results must be easily interpretable and queryable
Rethink database of virus and titer data
- Harmonizes data from different sources
- Integrates different types of data (serology, sequences, case details)
- Provides an interface for downstream analysis
Build scripts to align sequences, build trees and annotate
- Flexible build scripts to incorporate different viruses and analyses
- Constructs time-resolved phylogenies
- Annotates with geographic transitions and mutation events
Example augur pipeline for 1600 Ebola genomes
- Align with MAFFT (34 min)
- Build ML tree with RAxML (54 min)
- Temporally resolve tree and geographic ancestry with TreeTime (16 min)
- Total pipeline (1 hr 46 min)
Web visualization of resulting trees
- Interactive data exploration and filtering
- Framework through React / D3
- Connects phylogeny, geography and genotypes
Rapid on-the-ground sequencing by Ian Goodfellow, Matt Cotten and colleagues
Build out pipelines for different pathogens,
improve databasing and lower
bioinformatics bar
Acknowledgements
Bedford Lab:
Alli Black,
Sidney Bell,
Gytis Dudas,
John Huddleston,
Barney Potter,
James Hadfield,
Louise Moncla
Influenza: WHO Global Influenza Surveillance Network, GISAID, Richard Neher,
Barney Potter, John Huddleston, Dave Wentworth, Becky Garten, Jackie Katz, Marta Łuksza,
Michael Lässig, Richard Reeve
Ebola: Gytis Dudas, Andrew Rambaut, Luiz Carvalho, Philippe Lemey,
Marc Suchard, Andrew Tatem
Zika: Nick Loman, Nuno Faria, Oli Pybus, Josh Quick, Kristian Andersen,
Nathan Grubaugh, Jason Ladner, Gustavo Palacios, Sharon Isern, Gytis Dudas, Alli Black, Barney Potter,
Esther Ellis
Nextstrain: Richard Neher, James Hadfield, Colin Megill, Sidney Bell,
Charlton Callender, Barney Potter, John Huddleston, Emma Hodcroft