Influenza hemagglutinin protein stability correlates with fitness and seasonal evolutionary dynamics

Transcription

1 Influenza hemagglutinin protein stability correlates with fitness and seasonal evolutionary dynamics Eili Y. Klein, Ph.D. Assistant Professor, Department of Emergency Medicine & Fellow, Center for Disease Dynamics, Economics & Policy

2 Influenza Burden Leading causes of death, US children 18,000 hospitalizations Millions of excess outpatient visits 2 of 23

3 Influenza Burden Death toll (fraction of world population) 1E+0 1E-1 1E-2 1E-3 1E-4 1E-5 1E-6 1E-7 1E-8 World epidemics Smallpox Flu AIDS Flu Flu Ebola Flu SARS MERS Years Ago Worldwide annually (WHO) 3 million cases 250,000 to 500,000 deaths U.S. economic burden of $83.3 billion annually virus bacteria 3 of 23

4 Challenge to Successful Vaccine Viral Mutations Infection Vaccine Production Vaccination Dec-Feb Mar-Sep Oct-Nov Viral Selection Mutations Influenza Virus 4 of 23

5 Hypothesis Protein thermostability of HA protein affects fitness and evolutionary dynamics What are the primary fitness differences between co-existing virus strains that leads to persistence 1. New strain (red) dies out 2. New strain (red) persists 3. New strain (red) takes over 5 of 23

6 Stability of the Hemagglutinin Protein Successful viral replication requires the virus to assemble proteins, particularly the hemagglutinin protein 6 of 23

7 Effect of hemagglutinin protein stability on evolution More Stable Estimated Change in hemagglutinin Stability (ΔΔG) Less Stable v 9,797 H1N1pdm09 hemagglutinin sequences with full open reading frames, date information, and were isolated between 3/12/2009 and 4/9/2015 v Stability predicted by Eris Algorithm Global Initiative on Sharing All Influenza Data (GISAID) EpiFlu database (platform.gisaid.org) 7 of 23

8 Effect of hemagglutinin protein stability on evolution Estimated Change in hemagglutinin Stability (ΔΔG) Estimated Change in hemagglutinin Stability (ΔΔG)K-means clustering algorithm 8 of 23

9 Effect of hemagglutinin protein stability on evolution More Stable Estimated Change in hemagglutinin Stability (ΔΔG) Less Stable 9 of 23

10 Effect of hemagglutinin protein stability on evolution Phylogenetic Tree Tree determined using RAxML Blackbox for all non-duplicate nucleotide sequences collected after 10/1/2010 Estimated Change in hemagglutinin Stability (ΔΔG) 10 of 23

11 Effect of hemagglutinin protein stability on evolution Most Likely Ancestor Smallest pairwise distance measurement (i.e., highest relatedness) between two strains using the K80 model (Kimura 1980). In the case of ties, both ancestral strains were included of 23

12 Effect of hemagglutinin protein stability on evolution More Stable Most Likely Ancestor Estimated Change in hemagglutinin Stability (ΔΔG) Less Stable 12 of 23

13 Laboratory confirmation of computational estimates More Stable Estimated Change in hemagglutinin Stability (ΔΔG) P=0.015 Experimental test of stability Less Stable 13 of 23

14 Are more stable viruses more fit? More stable viruses produced more virus *** ** ** ** Less stable More stable 14 of 23

15 HA Protein Stability and Virus Fitness More stable viruses produced more virus and infected more cells. *** ** ** ** * * Less stable More stable Less stable More stable 15 of 23

16 Mutations and Stability 16 of 23

17 Mutations and Stability 17 of 23

18 Evolutionary Dynamics 18 of 23

19 Future work Computational forecasts of escape viruses based on stability predictions TTGCCGTAACGGATGTAAATTGCCATAACGGGCTAA TTGCCATAACGGAGGTAAATTGCCATAACGGGCTAA TTGCCATAACGGATGTAAGTTGCCATAACGGGCTAA TTGCCATAACGGATGTAAATTGCCATAAGGGGCTAA TTGCCATAACGGATATAAATTGCCATAACGGGCTAA TTGCCATCACGGATGTAAATTGCCATAACGGGCTAA TTGCCATAACGCATGTAAATTGCCATAACGGGCTAA TTGCCATTACGGATGTAAATTGCCATAACGGGCTAA TTGCCATAACGGATGTAAATTGCCAGAACGGGCTAA TTGCCATAACGGATGTAAATTGCCATAACGAGCTAA TTGCCATAACAGATGTAAATTGCCATAACGGGCTAA TTGCCATAACGGATGTTAATTGCCATAACGGGCTAA TTGCCATAACGGATGTAAATTGCCATAGCGGGCTAA TTGCCATAACGGATGTAAATTGCCATAACGGGCAAA TTGCCATAACGGATTTAAATTGCCATAACGGGCTAA Experimental antibody binding assays 19 of 23

20 Experimental Binding Assays Immune cells Antibody Viral mutant capsid gene BINDING substrate Harmless + FACS Viral mutant capsid protein mutant Escape mutant Escape mutant gene Harmless mutant Escape mutant gene SEQUENCE 20 of 23

21 Accelerated viral evolution in emulsion Drop volume: 0.5 nl Number of cells: 2 cells/drop Number of viruses: 1-10 pfu/drop Burst size: 100 pfu/infection Drop split: 10% Split rate: 500,000 drops/hour Reinjected drops passage Incubation Waste Cells 21 of 23

22 Hydrogel Display A library of proteins and their DNA code 1 DNA anchor (primer) encapsulate hydrogel hydrogel 1 mutant gene PCR in drop s hydrogel multiple gene copies BG BG BG Protein anchor (BG SNAP) Water-in-oil drop Water-in-oil drop 4 hydrogel hydrogel hydrogel Multiple protein copies Protein translation in drops hydrogel BG Antibody binding assay Wash and bind fluorescent Ab Water-in-oil drop Wash 22 of 23

23 Thanks Deena Blumenkrantz Andy Pekosz Andrew Feldman David Weitz Adrian Serohijos Eugene Shakhnovich Jeong-Mo Choi, João V. Rodrigues, Brendan D. Smith, Andrew P. Lane 23 of 23