Tracking and predicting the spread of pathogens and resistance

Richard Neher
Biozentrum, University of Basel

slides at

Human seasonal influenza viruses

slide by Trevor Bedford

Sequences record the spread of pathogens

images by Trevor Bedford

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

joint work 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

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

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

joint project with Trevor Bedford & his lab

Enterovirus D68 -- with Robert Dyrdak, Emma Hodcroft & Jan Albert

  • Non-polio enterovirus
  • Almost everybody has antibodies against EV-D68
  • Large outbreak in 2014 with severe neurological symptoms in
    young children (acute flaccid myelitis)
  • Another outbreak in 2016
  • Outbreaks tend to start in late summer/fall
  • Several reports of EV-D68 outbreaks last fall
    (201 AFM cases in the US in 2018)

EV-D68 whole genome deep sequencing project across Europe

Infections with multiple variants

  • A set of iSNVs at very similar frequencies in full linkage
  • Suggest infection with two related variants
  • 3 out of 50 samples: Implies high prevalence
Dyrdak et al, biorxiv

Carbapenemase producing bacteria

  • Reserve antibiotics used to treat MDR bacteria
  • Introduced in the 1980ies
  • Resistance spread rapidly
  • Resistance is mediated by several distinct beta-lactamases
    → pressing public health problem
    → fascinating instance of genes sweeping the globe by horizontal transfer
  • Resistance is horizontally acquired
    → tracking the core genome doesn't do it
  • Need to track genes on there mobilizing genetic background

Tracking bacteria by sequencing

  • Illumina → millions of short reads (<500bp)
  • Too short to bridge repetitive elements
  • → assemblies are fragmented into 100s of "contigs"
  • Problem: all the important bits are flanked by repetitive/mobile elements

(really terrible example)


Long-read sequencing

Long-read sequencing of Carbapenemase producing bacteria

  • Contigs with drug resistance genes ~1-6 genes
    → no phylogenetic resolution
  • long-read assemblies give full length plasmids
  • tracking via synteny and structural diversity, not SNPs
    → we need to reconstruct spread from genome structure evolution
Noll et al, biorxiv, 2018

Synteny alignments of Carbapenemase containing loci

  • Structural changes can resolve evolutionary relationships
  • Different KPC alleles are found on the same background
  • Identical KPC alleles are found on different backgrounds
  • Similar plasmids are spread across MLSTs and species boundaries
Noll et al, biorxiv, 2018

Synteny alignments of Carbapenemase containing loci

Noll et al, biorxiv, 2018


  • Timely data sharing + automated analysis allows near real-time tracking of influenza
  • Such analyses provide important input for vaccine strain selection
  • Sequencing, analysis, and dissemination can be rapidly set-up for emerging pathogens
  • Bacterial pathogens come with a special set of challenges
  • Fascinating evolutionary process beyond mutations in homologous sequence

Acknowledgments -- nextstrain

  • Trevor Bedford
  • Colin Megill
  • Pavel Sagulenko
  • Sidney Bell
  • James Hadfield
  • Wei Ding
  • Emma Hodcroft
  • Sanda Dejanic
  • John Huddleston
  • Barney Potter

Influenza and Theory acknowledgments

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

Acknowledgments -- Enterovirus

  • Robert Dyrdak
  • Jan Albert
  • Lina Thebo
  • Emma Hodcroft
  • Bert Niesters (Groningen)
  • Randy Poelman (Groningen)
  • Elke Wollants (Leuven)
  • Adrian Egli (Basel)
  • Andrés Antón Pagarolas (Barcelona)

Acknowledgments -- CPE

  • Wei Ding
  • Nicholas Noll
  • Eric Ulrich
  • Adrian Egli (at USB)

With-in host diversity

  • Above 0.5%, iSNVs are biological
  • Most samples have few iSNVs, three had more than 20
Dyrdak et al, biorxiv