Tracking and predicting the evolution of human RNA viruses


Richard Neher
Biozentrum & SIB, University of Basel


slides at neherlab.org/202010_rockefeller.html

Human seasonal influenza viruses

slide by Trevor Bedford

Positive tests for influenza in the USA by week

Data by the US CDC

Sequences record the spread of pathogens

Mutations accumulate at a rate of $10^{-5}$ per site and day!
images by Trevor Bedford


  • Influenza viruses evolve to avoid human immunity
  • Vaccines need frequent updates

Influenza B viruses have split into two lineages

Le Yan, RN, Shraiman, bioRxiv, 2018

GISRS and GISAID -- Influenza virus surveillance

  • comprehensive coverage of the world
  • timely sharing of data through GISAID -- often within 2-3 weeks of sampling
  • hundreds of sequences per week (in peak months)
→ requires continuous analysis and easy dissemination
→ interpretable and intuitive visualization

nextflu.org

joint project with Trevor Bedford & his lab

Beyond tracking: can we predict?

Fitness variation in rapidly adapting populations

  • Speed of adaptation is logarithmic in population size
  • Environment (fitness landscape), not mutation supply, determines adaptation
  • Different models have universal emerging properties
RN, Annual Reviews, 2013; Desai & Fisher; Brunet & Derride; Kessler & Levine

Neutral/Kingman coalescent

strong selection

Bolthausen-Sznitman Coalescent

RN, Hallatschek, PNAS, 2013; see also Brunet and Derrida, PRE, 2007; Desai, Walczak, Fisher, Genetics, 2013

Burst in the tree ↔ high fitness

Can we infer fitness from a genomic snapshot?

Fitness inference from trees

$$P(\mathbf{x}|T) = \frac{1}{Z(T)} p_0(x_0) \prod_{i=0}^{n_{int}} g(x_{i_1}, t_{i_1}| x_i, t_i)g(x_{i_2}, t_{i_2}| x_i, t_i)$$
RN, Russell, Shraiman, eLife, 2014

Validation on simulated data

RN, Russell, Shraiman, eLife, 2014

Prediction of the dominating H3N2 influenza strain

  • no influenza specific input
  • how can the model be improved? (see model by Luksza & Laessig)
 RN, Russell, Shraiman, eLife, 2014

Limits of predictability

Barrat-Charlaix et al, 2020
BBC
by Trevor Bedford
by Trevor Bedford

Tracking diversity and spread of SARS-CoV-2 in Nextstrain

Available data on Jan 26

Early genomes differed by only a few mutations, suggesting very recent emergence
nextstrain.org/ncov/2020-01-26
→ the closest to "real-time" we have experienced so far...
Figure by James Hadfield/Emma Hodcroft
Mutations accumulate constantly, but most of them are irrelevant and rare.
The genome accumulates about two mutations a month...
Diversified into multiple global variants. Groups 20A/B/C have taken over.

A European clusters in summer 2020

nextstrain.org/ncov

What's next?

Seasonal incidence of influenza viruses

Data by the US CDC

2009 pandemic influenza -- US

by Trevor Bedford

Human corona viruses have pronounced seasonal prevalence (Sweden)

  • Most respiratory virus including established CoVs show seasonality
  • Little direct evidence; absolute effect of seasonality unknown
  • But expect control of the virus to be harder in winter
Neher et al

Potential transition to an endemic seasonal virus

Influenza and Theory acknowledgments

  • Boris Shraiman
  • Colin Russell
  • Trevor Bedford
  • Pierre Barrat
  • Oskar Hallatschek

  • All the NICs and WHO CCs that provide influenza sequence data
  • The WHO CCs in London and Atlanta for providing titer data

Acknowledgments

Trevor Bedford and his lab -- terrific collaboration since 2014

especially James Hadfield, Emma Hodcroft, Ivan Aksamentov, Moira Zuber, and Tom Sibley

Data we analyze are contributed by scientists from all over the world

Data are shared and curated by GISAID

Acknowledgments

  • Robert Dyrdak
  • Jan Albert
  • Valentin Druelle
  • Emma Hodcroft