Virus evolution:

a framework for

ancient & modern

problems

Sidney Bell (@sidneymbell)

Bedford Lab, University of Washington

car

cat

Reconstructing evolution is a lot like "telephone"

zebra

....

car

cat

Reconstructing evolution is a lot like "telephone"

zebra

Reconstructing evolution is a lot like "telephone"

Evolution can track viral migration and change

Where did this virus come from?

When did interesting traits change?

Epidemiology MS

2015 - 2016

"Where did HIV come from?"

Molecular Bio PhD

2014 - 2018

"How does dengue hide from immunity?"

Nextstrain

Ongoing

Real-time tracking of

viral evolution 

Where we're headed

Cross-species transmission can be devastating

HIV has entered human populations >15 times

x2

x2

x12

>40 primate species carry

a unique SIV

How often do SIVs switch host species?

?

?

?

Viral phylogenies show

history and migration

Color = host species

 

Cross-species transmission looks

like color changes

(Bell & Bedford, PLoS Pathog., 2017)

Integrating over uncertainty:

~1,000 sequences

~24,000 trees

(Bell & Bedford, PLoS Pathog., 2017)

Viral phylogenies show

history and migration

SIVs have been adapting to new hosts for millions of years

(Bell & Bedford, PLoS Pathog., 2017)

Virus evolution

is also a powerful framework for answering modern questions

Dengue is a mosquito-borne virus

that kills 15,000 children annually

There are 4 serotypes of dengue, each containing substantial genetic diversity

DENV1

DENV3

DENV4

DENV2

Early expansion 1850 - 1950

Rapid expansion since 1950

Local circulation since 1700s

Each serotype has recently expanded geographically

Serotype cocirculation

makes dengue a major public health concern

Lifelong protection

Temporary

cross-protection

Initial

response

Immunity is both friend and foe

Lifelong protection

After

1-3 yrs

Increased risk

Immunity is both friend and foe

Immunity

friend vs. foe

depends on

"antigenic distance"

"Antigenic distance" example:

Why you need a new flu shot every year

Measles

Lifelong protection

"Antigenically uniform"

Flu

"Antigenicallydiverse"

Temporary protection

(Continuing our example)

Genetic change underlies antigenic change

ACTG

ACTT

AGTT

Flu

Antigenic evolution

Genetic

evolution

(Now back to dengue)

DENV antigenic relationships

are poorly understood

Serotypes are genetically distinct

Clades are genetically distinct

Serotypes are antigenically distinct

Are clades antigenically distinct?

≠

?

≠

≠

Titers approximate pairwise

antigenic distance

Experimentally measure how well sera recognizes each virus

Sera produced by 1st infection

Test viruses

Titers approximate pairwise

antigenic distance

0
0 2
0

1

2

2-fold

change

4-fold

change

4-fold

change

Antigenic Distance

\propto

log2(Titer)

Distance

Dengue serotypes look antigenically diverse

NHP sera; 3 months post primary infection

= 2-fold change in titer

Katzelnick et al, Science 2015

How? Impact?

How do
dengue genotypes
map to
antigenic phenotypes?

Can we predict antigenic phenotypes from virus genotypes?

Phylogenies can describe both genetic and antigenic relationships

Quantify antigenic change along each branch, 

Neher et al, PNAS 2016

0 1 2
0 2
0
\approx \sum{d_b}

Titer

between

&

+         avidity +     potency

d_b
d_{1}
d_{2}
d_{3}

Does within-serotype genetic diversity change antigenic phenotypes?

Interserotype hypothesis

Full tree hypothesis

Interpolate across the tree

to estimate antigenic relationships

\hat{T_{ij}} = \sum{d_b} + v_i + s_j
\sum_{i,j}(\hat{T_{ij}} - T{ij})^2 + \lambda \sum_{b}d_b + \gamma \sum_{i} v_i^2 + \delta \sum_{j} s_j^2

Learn these

Minimize

this

Predict titers

\hat{T_{ij}} = \sum{d_b} + v_i + s_j
\sum_{i,j}(\hat{T_{ij}} - T{ij})^2 + \lambda \sum_{b}d_b + \gamma \sum_{i} v_i^2 + \delta \sum_{j} s_j^2

dTiter on each branch

Virus

avidity

Serum

potency

Predict titers

\hat{T_{ij}} = \sum{d_b} + v_i + s_j
\sum_{i,j}(\hat{T_{ij}} - T{ij})^2 + \lambda \sum_{b}d_b + \gamma \sum_{i} v_i^2 + \delta \sum_{j} s_j^2

Squared Error

Minimize

this

L1 norm on branch effects

L2 norm on virus avidity & serum potency

Pearson R 0.79
Abs. Error 0.71
Sqr. Error 0.87
0.90
0.61
0.61

Between-serotype variation explains most of

dengue antigenic phenotypes

Within-serotype variation significantly contributes to dengue antigenic phenotypes

Test Error

Interserotype hypothesis

Full tree hypothesis

Each serotype of dengue contains multiple

distinct antigenic phenotypes

Log2 titer distance from root

DENV1

DENV3

DENV4

DENV2

>= 10 distinct phenotypes

Genetic distance is associated

with antigenic distance

Homotypic genotypes

Heterotypic genotypes

How does

antigenic diversity impact dengue population dynamics?

Serotypes cycle through populations

Genotypes

Does antigenic novelty contribute to dengue clade turnover?

Population susceptibility:

Previously circulating:

Population

immunity:

Clade growth:

Predict clade growth

from antigenic novelty

Lukzsa and Lassig, Nature, 2014

\propto e^{(f_i(t) + 5)}

Growth rate @

next 5 years

How antigenically distant*

is          from what has recently circulated?

* from

interserotype

or

full-tree

titer model

Does antigenic novelty contribute

to dengue fitness?

f_i(t) = 1 - P_i(t)

Relative frequency of j

Waning immunity

P_i(t) \propto \sum_{t-n}^{t} \gamma(n) \sum_{j} x_{j}(t) * C(D_{ij})

Antigenic distance between i and j

Lukzsa and Lassig, Nature, 2014

Does antigenic novelty contribute

to dengue fitness?

f_i(t) = 1 - P_i(t)

Relative frequency of j

Waning immunity

Probability of protection from i

given exposure to j

Lukzsa and Lassig, Nature, 2014

P_i(t) \propto \sum_{t-n}^{t} \gamma(n) \sum_{j} x_{j}(t) * C(D_{ij})

Antigenic novelty significantly

contributes to dengue viral fitness

Pearson R 0.88 0.87

Interserotype antigenic phenotypes

drive population dynamics

Interserotype model

Full tree model

Summary:

1: Dengue serotypes are moderately antigenic diverse

 

2: Serotype-level antigenic relationships

drive dengue

population dynamics

Future Work

We can predict which clades will be dominant.

Can this help predict

epidemic severity?

Turning theory into practice

via rapid dissemination

DENV2

Log2 titer distance from Sanofi vaccine

Turning theory into practice

via rapid dissemination

Ongoing Collaborations

Ted Gobillot, UW

High-throughput characterization of Zika & DENV antibodies

Frank Wen, UChicago

Vaccine-driven influenza evolution

Nextstrain

Real-time analysis of viral evolution

as a teaching tool for

Acknowledgements

Trevor Bedford, Leah Katzelnick, Sarah Hilton, Colin Megill

Gytis Dudas, James Hadfield, John Huddleston, Alli Black, Barney Potter, Louise Moncla

Richard Neher, David Shaw, Duncan Ralph

Erick Matsen, Jesse Bloom, Julie Overbaugh,

Adam Geballe, Daniela Witten

Slides: The Noun Project & RevealJS

Questions?

github.com/sidneymbell/talks

                 .org/dengue

                       @sidneymbell