Real-time tracking of virus evolution

Trevor Bedford (@trvrb)
29 Mar 2019
Population Biology, Ecology, and Evolution Seminar
Emory University

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

Stuttering chains and animal-to-human spillover

    MERS spillover in the Arabian Peninsula

Epidemic growth and human-to-human transmission

    Ebola spread in West Africa

New methods for rapid phylogenetics and visualization

MERS-CoV

Middle East respiratory syndrome coronavirus (MERS-CoV)

• First identified in Saudi Arabia in 2012
• 2229 confirmed cases to date and 791 deaths
• Camels thought to be the intermediate host
• 30% of common colds due to endemic human coronaviruses

Ongoing incidence, but lack of epidemic growth

Cases localized to the Arabian Peninsula

Hypotheses for MERS transmission

MERS-CoV spillover at the camel-human interface

with Gytis Dudas, Luiz Carvalho and Andrew Rambaut

Genomic dataset

• 174 virus genomes from human infections
• 100 virus genomes from camel infections

MERS tree with host state

Phylodynamic reconstruction of host state

Humans are transient hosts

Asymmetric migration rates

• 56 (48–63) camel-to-human transmission events resulting in 174 sequenced human infections
• 3 (0-12) human-to-camel transmission events

Introduction events tend to occur between April and July

Dromedary camel calving occurs between Nov and Feb

Monte Carlo simulation

Phylogenetic clustering suggests $R_0$ below 1.0 and ~2000 human cases driven by ~600 introduction events

Critically, no evidence of increasing cluster sizes through time

Many other viruses that exhibit stuttering chains of human infection

• Nipah virus (fruit bats / pigs, Southeast Asia)
• Lassa virus (rodents, West Africa)
• Avian influenza (birds, mainland China)

Sylvatic introductions of yellow fever virus show similar dynamics

Ebola

Ebola epidemic of 2014-2016 was unprecedented in scope

Ebola epidemic in West Africa

Ebola epidemic within Sierra Leone

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

Sequenced genomes were representative of spatiotemporal diversity

Phylogenetic reconstruction of epidemic

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

Each introduction results in a minor outbreak

Regional outbreaks due to multiple introductions

Regional outbreaks due to multiple introductions

Ebola spread in West Africa followed a gravity model with moderate slowing by international borders, in which spread is driven by short-lived migratory clusters

The ability of single genes vs full genomes to resolve time and space in outbreak analysis

with Gytis Dudas

Accuracy vs precision

Approach accuracy and precision through a machine learning approach to model testing. Leave out 60/600 tips and predict time and location of these tips

Maximum likelihood divergence trees

BEAST time trees

Date reconstruction

Evolutionary rate reconstruction

Location reconstruction

Estimates are generally well calibrated

Actionable inferences

Genomic analyses were mostly done in a retrospective manner

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

Nextstrain

Project to conduct real-time molecular epidemiology and evolutionary analysis of emerging epidemics

with Richard Neher, James Hadfield, Emma Hodcroft, Tom Sibley,
John Huddleston, Colin Megill, Sidney Bell, Barney Potter,
Charlton Callender

Nextstrain architecture

All code open source at github.com/nextstrain

Two central aims: (1) rapid and flexible phylodynamic analysis and
(2) interactive visualization

Rapid build 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)

Nextstrain is two things

• a bioinformatics toolkit and visualization app, which can be used for a broad range of datasets
• a collection of real-time pathogen analyses kept up-to-date on the website nextstrain.org

nextstrain.org

Rapid on-the-ground sequencing in Makeni, Sierra Leone

Newly released features

• Bacteria build pipelines using VCF rather than FASTA
• "Community" builds to promote frictionless sharing of results

Genomic epidemiology of the ongoing DRC Ebola epidemic

Acknowledgements

Bedford Lab: Alli Black, John Huddleston, Barney Potter, James Hadfield,
Louise Moncla, Tom Sibley, Maya Lewinsohn, Katie Kistler

MERS: Gytis Dudas, Andrew Rambaut, Luiz Carvalho

Ebola: Gytis Dudas, Andrew Rambaut, Luiz Carvalho, Philippe Lemey, Marc Suchard, Andrew Tatem

Nextstrain: Richard Neher, James Hadfield, Emma Hodcroft, Tom Sibley, John Huddleston, Sidney Bell, Barney Potter, Colin Megill, Charlton Callender