RNA virus evolution and the predictability of next year's flu


Richard Neher
Biozentrum, University of Basel


slides at neherlab.org/201803_ASTAR.html

Evolution of HIV


  • Chimp → human transmission around 1900 gave rise to HIV-1 group M
  • ~100 million infected people since
  • subtypes differ at 10-20% of their genome
  • HIV-1 evolves ~0.1% per year
image: Sharp and Hahn, CSH Persp. Med.

HIV infection

  • $10^8$ cells are infected every day
  • the virus repeatedly escapes immune recognition
  • integrates into T-cells as latent provirus
image: wikipedia

HIV acknowledgments

  • Fabio Zanini
  • Jan Albert
  • Johanna Brodin
  • Christa Lanz
  • Göran Bratt
  • Lina Thebo
  • Vadim Puller

HIV-1 evolution within one individual



silouhette: clipartfest.com, Zanini at al, 2015. Collaboration with Jan Albert and his group

HIV-1 sequencing before and after therapy

Zanini et al, eLife, 2015; Brodin et al, eLife, 2016. Collaboration with the group of Jan Albert


Population sequencing to track all mutations above 1%

Zanini et al, eLife, 2015; antibody data from Richman et al, 2003

Inference of fitness costs

  • mutation away from preferred state with rate $\mu$
  • selection against non-preferred state with strength $s$
  • variant frequency dynamics: $\frac{d x}{dt} = \mu -s x $
  • equilibrium frequency: $\bar{x} = \mu/s $
  • fitness cost: $s = \mu/\bar{x}$
  • Split the genome into categories from high to low conservation
  • Fit model of minor variation to each category
  • $\Rightarrow$ harmonic average fitness cost in category

Fitness landscape of HIV-1

Zanini et al, Virus Evolution, 2017

Selection on RNA structures and regulatory sites

Zanini et al, Virus Evolution, 2017

Does HIV evolve during therapy?

Brodin et al, eLife, 2016

No evidence of ongoing replication

Brodin et al, eLife, 2016

No evidence of ongoing replication

Brodin et al, eLife, 2016

Influenza A/H3N2 virus evolution

Joint work with....

  • Boris Shraiman
  • Colin Russell
  • Trevor Bedford


  • Influenza virus evolves to avoid human immunity
  • Vaccines need frequent updates

nextflu.org

joint work with Trevor Bedford & his lab

Fitness variation in rapidly adapting populations

RN, Annual Reviews, 2013; Desai & Fisher; Brunet & Derride; Kessler & Levine

strong selection

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

Bursts in a tree ↔ high fitness genotypes

Can we read fitness of a tree?

Predicting evolution

Given the branching pattern:

  • can we predict fitness?
  • pick the closest relative of the future?
RN, Russell, Shraiman, eLife, 2014

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

Validate on simulation data

  • simulate evolution
  • sample sequences
  • reconstruct trees
  • infer fitness
  • predict ancestor of future
  • compare to truth
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)
  • what other context might this apply?
 RN, Russell, Shraiman, eLife, 2014

nextstrain.org

joint work with Trevor Bedford & his lab

nextstrain.org

  • integrate data from many different sources
  • analyze those data in near real time
  • disseminate results in an intuitive yet informative way
  • provide actionable insights

nextstrain.org

  • Trevor Bedford
  • Colin Megill
  • Pavel Sagulenko
  • Sidney Bell
  • James Hadfield
  • Wei Ding