HCV Evolution: Diversification and Convergence Yury Khudyakov Division of Viral Hepatitis Centers for Disease Control and Prevention, Atlanta, GA

Public Health Reduction of morbidity and mortality - Diagnostics - Treatment - Prevention Medicine Introduction

  A high rate of mutation defines rapid HCV evolution  HCV genome continuously changes  “Arms Race”  Pervasive coevolution  Opportunity for convergence Introduction

PHYLOGENETIC ANALYSIS Intra-Host HCV Variants Patient 1 Patient 2 Patient 3 Patient 4

Network of coordinated substitutions in the HCV polyprotein K-Core Decomposition of HCV Network

Bayesian Network of HCV Polyprotein Site Interactions and Therapy Outcome

Bayesian Network associating the HVR1 sites with IFN response and host demographic factors HVR1-BN

Intra-Host Evolution over Many Years

15.991aIDUFemaleUnknownD aUnknownMaleBlackC aIDUFemaleBlackB 8.841bTransfusionMaleWhiteA YearsGenotypeTransmissionGenderRacePatient ID Sentinel County HCV Follow-up Study

Divergence Time DBAC HCV Quasispecies Divergence During Long-Term Chronic Infection Patients

HVR1: patient A Time-pints (Yrs) yr yr HVR1: patient B Time-points (Yrs) yr HVR1: patient D Time-points (Yrs) yr yr HVR1: patient C Time-points (Yrs) yr yr yr HVR1 Phylogenetic Trees

DBAC dN/dS Time Changes in Selection Pressures Over Time dN/dS vs. Time HVR1 – R=-0.58, p= NS5A – R=-0.61, p= Titer vs. Time R=0.585, p= Titer vs. dN/dS R=-0.383, p=0.012 Patients

Genetic Linkage to Viral and Host Factors Genomic Structure QS diversity HCV QS SEQUENCE HOST Viral titer dN/dS HCV QS SEQUENCE Factors

I.Molecular Epidemiologic Data NHANESIII: 106 patients 1384 HVR1 quasispecies; Genotypes 1 – 6 HVR1: positions 1491 to 1577nt (polyprotein 488 to 516) 5’UTR: positions 127 to 340nt NS5B: positions 8290 to 8589nt (polyprotein 2651 to 2749) II.Quantitative Structure Relationships Probabilistic Graphical Models: Bayesian Networks (BN) III.Predictions Causal models: BN classifiers

Bayesian Network Model Associating Sequences of HCV HVR1 Quasispecies to Viral and Host Parameters

Bayesian Network Model Associating Sequences of HCV HVR1 Quasispecies to Viral and Host Parameters

Bayesian Network Model Associating Sequences of HCV HVR1 Quasispecies to Viral and Host Parameters

Bayesian Network Model Associating Sequences of 3 HCV Genome Regions to Viral and Host Parameters

Target classes10-fold-CV ‡ (%) Acc. randTest † (10-fold-CV ‡ ) TestSet** Genotype99.9% % dN/dS ^^ (3-bin) (2-bin) 94.4% 92.2% % 82.7% NQSaa-hvr188.0% % NQSnt-hvr187.7% % Viral Titer97.2% % ‡ Avg. accuracies † Random assignment of class labels ** 10 NHANES-3 patients; 5M and 5F; Genotypes 1a and 1b; 185nt/96aa HVR1 QS ^^ Based on dNdS 3 class or 2 class grouping Quantitative Validation of Models Predictions: Classification Modeling

Five physicochemical properties (Atchley et al, 2005): Polarity, α-helix, Size, aa frequency, Charge Multiple sequence alignment Euclidean distance between every pair of sequences Visualization of distance matrix Pathfinder network (r = ∞, q = n-1) Methods

PFNET

Inter-genotype convergence Genotype 1

Genotype 2 Inter-genotype convergence

24.3% of all links are between different genotypes. Genotype convergence

We immunized mice with 102 HVR1 peptides covering all high-density regions of the sequence space. We tested the reactivity of each sera against 262 peptides (in yellow), a total of reactions Cross-reactivity experiment

There were 5039 positive reactions (blue links), which correspond to 18.85% of all tested.

Three peptides (yellow) were found that collectively reacted with all 262 antigens.

Relationship between the reduction of selection pressure and cross-immunoreactivity among HCV intra-host variants PatientCorrelation between DN/DS and ACR p-value Patient B Patient C Patient D *ACR DN/DS Patient C

Public Health: Reduction of morbidity and mortality - Diagnostics - Treatment - Prevention Medicine: Conclusion Many viral phenotypic traits with significant medical and public health implications are convergent rather than ancestral

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