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Host pathogen interaction and the evolution of Pandemic Flu

Host pathogen interaction and the evolution of Pandemic Flu. This talk is mostly the work of a talented post-doc Ben Greenbaum, who was a in my group from 2007-2008. Greenbaum et al, PLoS Pathogens, 2008 Jun 6;4(6):e1000079. Viruses are Obligate Parasites.

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Host pathogen interaction and the evolution of Pandemic Flu

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  1. Host pathogen interaction and the evolution of Pandemic Flu This talk is mostly the work of a talented post-doc Ben Greenbaum, who was a in my group from 2007-2008. Greenbaum et al, PLoS Pathogens, 2008 Jun 6;4(6):e1000079

  2. Viruses are Obligate Parasites • They depend on hosts to replicate: • They evolve much faster than other “organisms” • They have a diverse set of genomes and encounter different host machinery and topography, hitting different nooks • They live on the edge of an error catastrophe Photo: www.flutrackers.com

  3. Viral Replication is complex and highly adapted to host species • http://www.mcb.uct.ac.za//tutorial/dnagen.htm#dsDNA • ‘Influenza Report’, by Kamps, Hoffman and Preisner (Sakai) • Viruses infect everything, including bacteria, fungi, plants, archea • dsDNA Viruses: Pox, Herpes, Adeno, Papovaviridae • ssDNA Viruses: Circoviridae, Parvoviridae • dsRNA Viruses: Reoviridae etc. • ssRNA (+) sense: (Astro-, Calici-, Corona-, Flavi-, Picorna-, Togaviridae, genus Arterivirus etc. • ssRNA (-) sense: Arena-, Orthomyxo-(FLU), Paramyxoviridae • Diploid ssRNA (Retroid): Replicating via longer than genome length intermediaries: Lentivirus (HIV, SIV), Avian Leukemia Virus (ALV), Mouse Mammary Tumor Virus (MMTV) etc. • dsDNA Retroid Viruses: Hepadnaviridae • http://en.wikipedia.org/wiki/RNA_virus is a good resource to references.

  4. HOW DO WE DEAL WITH THEM? • Edward Jenner (1796) showed that cowpox (vaccinia) induced protection against human smallpox • Jenner called his procedure vaccination • It took two centuries for smallpox vaccination to become universal. • In 1979, smallpox was eradicated

  5. Since Jenner • 1880s: Pasteur made a vaccine against chicken cholera and a rabies vaccine that was a spectacular success on its first trial in a boy bitten by a rabid dog. • In 1890, von Behring and Kitasato discovered that antibodies in the serum of vaccinated individuals specifically bound to the relevant pathogen (adaptive immune response) • ElieMetchnikoff discovered that microorganisms could be engulfed and digested by phagocytic cells or macrophages (innate immune response)

  6. Innate and Adaptive immunity • Innate immunity involves cells which are already activated and become immediately available to combat pathogens without requiring prior exposure. • Adaptive immunity develops during the lifetime as an adaptation to specific infections. It often confers life long protection against the same pathogen. • The antibodies in an individual reflect the infections to which he/she has been exposed.

  7. Immune cells derive from precursors in the bone marrow.

  8. Vaccination is the best way to control infectious diseases. • Diphtheria, polio, and measles have been virtually eliminated in the US • SSPE (subacutesclerosingPanencephalitis) is a brain disease - a late consequence of measles infection. Where measles was prevented, SSPE disappeared within ~10 years. • However, these diseases have not been eradicated worldwide. • Immunization must be maintained in a very high percentage of the population to prevent their reappearance.

  9. FLU “Phenotypes”

  10. The Influenza Virus • ssRNA- virus, no DNA step • Encodes own RNA Polymerase: translates –ve sense to +ve sense • Evolves via drift and shift • Seasonal Bottleneck • Typical size: 13.5 kb • ~ one mutation per copy • 100-1000 copies per cell • Seasonal and persistent • 8 different segments, 11 proteins • Two proteins on the surface: • HA and NA classify strain. • Three proteins in polymerase complex: • PB2, PB1 and PA. Noda et al, Nature 2006

  11. Replication of the Influenza A and B Viruses • Infection: HA binds to sialic acids of cell surface receptors • Fusion with endosomal membrane, release of virion content • Transcription of viral RNA • Translation of viral proteins • Formation of viral genome particles, transport of membrane proteins to cell surface • Budding virion particles • Neuraminidase (NA) sheds sialic acids from cell surface and viral particle is released

  12. Evolution of Viral Hemagglutinin in H5N1 & escaping immune response • Homotrimer of HA1 and HA2 subunits • Most variation in HA1, in sialic acid receptor binding and antibody-binding sites Mutations between 2005 with 2004 isolates are yellow; escape mutants are blue, and those that overlap both analyses are green. From: Stevens et al., Science 2006.

  13. FLU virus infects many hosts

  14. Parsimony Tree showing viral evolution driven by positive selection(Fitch et al., PNAS 1997) • ‘Cactus’-like phylogeny, 1 surviving lineage • Non-silent (replacement) mutations occur more often in the (surviving) trunk branches • Indicative of positive Darwinian selection • No significant region-specific biases observed Most parsimonious gene tree for 254 influenza HA genes (subtype H3) from 1968-1997.

  15. Maximum Likelihood treefor viral evolution • Accumulating diversity • Antigenic drift point mutations • Antigenic shift - segment exchange between viruses • Variant fixation • Immune-driven positive selection • Genetic drift - population bottlenecks, founder effects ‘Cactus-like’ ML tree of HA1 nucleotide sequences from H3N2 influenza A viruses. (From Smith et al., Science 2004.

  16. Pandemic strains result from “Antigenic Shift” From: Belshe, N Engl J Med, 2005.

  17. Clustering based on mutational bias suggests swine ancestry for 2009 H1N1 Flu

  18. 1918 flu killed 50-100 million people in 18 months In Brevig Mission, Alaska, it killed 72 out of 80 people in 5 days. The 1918 H1N1 viral sequence was obtained from RNA collected by Johan Hultin from grave of Inuit woman buried in the permafrost

  19. Vertebrate Genomes have low CpG • Text book explanation of low CpG in vertebrate DNA: • In Vertebrates, 70-80% of CpG dinucleotides are methylated to 5-methylcytosine. • Spontaneous deamination of cytosine forms uracil (CU), which is recognized and removed by DNA repair enzymes • Deamination of 5-methylcytosine forms thymine (5mC  T) which can result in a transition mutation (hard to correct). • Reduced CpG  reduces mutations to TG

  20. Facts and Hypotheses • CpG is under-represented in the DNA of many vertebrates. Many vertebrate ssRNA viruses also have low CpG content ARE THESE RELATED? AND IF SO, WHY ? • When a virus jumps between species, pressure to replicate, survive and adapt, may leave a footprint in dinucleotide frequencies. • Do these frequencies correlate with virulence?

  21. Analysis Methods and Results • Compare dinucleotide patterns in ssRNA viruses and hosts. • Identify dinucleotide patterns over/under represented in both viruses and host genes • Study the evolution of the H1N1 (1918) flu since it entered the human population • The 1918 H1N1 virus, has reduced its CG content over time. • Influenza B virus has low and constant CG. • Why? • The virus is evolving under selection pressure from the innate immune system, possibly due to motif specific recognition by Toll Like Receptors (TLRs)

  22. How do we identify dinucleotide frequency selection ? • Method should: • Avoid changing the codon bias of the sequences • Maintain amino acid sequence in proteins • Strategy: • Fix amino acid sequence and nucleotide frequency in viral coding regions • Generate sets of randomized sequences with these constraints • Use these to generate a null model for dinucleotide content • Compare the observed dinucleotide content with null model to compute a p-value

  23. Look for Patterns • Counts words to determine probabilities • Statistic:

  24. Influenza A Viral Patterns • p-values for unusual sequence patterns: • CpG and TpA under-represented (p<10-4) • CpA (p<10-3) and TpG overrepresented (p<10-4) • No other p-values less than 0.05 • Same result in every segment and strain • Viral mutations preferred: CpG, TpA  TpG, CpA • Influenza A is avoiding CpG, TpA motifs • Is this also true in other ssRNA virus?

  25. CpG odds ratio for Human, insect, plant and bacterial (phage) ssRNA Viruses Phages have  no pressure to reduce CG Human Virus sequences have low CG content

  26. CpG in the genomes of humans and human viruses CpG odds ratio versus C+G content for human genes (blue) and human RNA viruses (red/black = -/+ strand)

  27. CpG Evolution of H1N1

  28. Evolution of CpG in H1N1 using various measures Evolution of # of CpGs Evolution of η Evolution of the fraction of CG Arginine (CGN) codons (compared to CGN, AGA, AGG) Evolution of ρ

  29. Evolution of CpG in Influenza B

  30. Evolution of CG is Context Dependent “Protected” CpGs “Exposed” CpGs (C/G)CG(C/G) (A/U)CG(A/U)

  31. Do birds have higher CpG than Humans • CpG in human genes is lower than in chicken genes. • Dominant effect is in cytokines (effectors of the immune response).

  32. Stimulatory Motifs • These motifs are underrepresented in • the RNA transcriptome of pDC cells • primate ssRNA viral genomes • CGAA, CGAT, TTCG, ACGA,TCGA, GACG, TACG, TCGT, GTCG, ATCG, CGTT, AACG, TCCG, CGCT,TCGC, GCGA, CGTA, CGGA, CGAC, ACCG, CGGT, CGAG, CCGA, CGCA, ACGG, ACGC, TCGG, CCGT, CTCG, CCGG, CGTC, GGCG, ACGT, CCGC, AGCG, GCCG

  33. Why does Flu Mimic Vertebrate Host CpG? • Viruses that avoid immune recognition survive better. • In DNA viruses, viral suppression is from recognition of unmethylated CpG DNA by Toll-like receptor TLR9 through two mechanisms: D-type recognition, which releases IFNγ, or K-type recognition, which stimulates monocytes and activates IL6 and NF-kB. • ssRNA may also be recognized by similar CpG motifs by proteins TLR3, TLR7, TLR8, RIG-I, etc, which recognize viral RNAs, although the specific sequence motif which induces transcription of cytokines is unknown. • Major Conclusions: • In primates, ssRNA viruses CpG in an A/T context • Are evolving over time to reduce their frequency • Are recognized by some component of the innate immune system • Specific proteins must exist in the host to mediate a high cytokine response to CpG sequences in an A+T rich domain • May be a method to sort potential pandemic viral strains by virulence

  34. Follow up Greenbaum BD, Rabadan R, Levine AJ. Patterns of Oligonucleotide Sequences in Viral and Host Cell RNA Identify Mediators of the Host Innate Immune System, PLoS ONE. 2009; 4(6): e5969. Jimenez-Baranda S, Greenbaum B, Manches O, Handler J, Rabadan R, Levine A, Bhardwaj N. Oligonucleotide Motifs That Disappear during the Evolution of Influenza Virus in Humans Increase Alpha Interferon Secretion by Plasmacytoid Dendritic Cells, J. of Virology, Apr. 2011, p. 3893–3904 Vol. 85, No. 8

  35. TLR7 and TLR8 respond to RNA viruses such as influenza viruses and HIV RNA/DNA viruses • TLR7 and TLR8 molecules localize in Endosomal compartments. On endosome-mediated internalization of virus, they bind to its ligands. • TLR7/8/9 and IRF7 are constitutively expressed only in plasmacytoid dendritic cells (pDCs), which when activated, produce IFN and can trigger an early innate immune response (NK T-Cells).

  36. Analyze pDC cells in mouse Public gene expression data from Iparraguire et al: Stimulated Mice at 1 and 4 hrs with Flu and CpG DNA agonists High IFNA Producer Express TLR7/9

  37. Mouse and Human CpG content is similarred = Type I interferon alpha genes

  38. A successful host antiviral defense depends largely on rapid and robust IFN-α production IFN-α production after pDCs stimulation

  39. Modified Influenza viruses with Low CpG/High CpG Induce differential production of IFN-α

  40. Ranking of Avian Strains by “non-self” motifs • A possible tool for rapid characterization of emerging strains • N = number of sequences available • Average over 36 most suppressed tetramer “non-self” motives in circulating Avian & Swine strains

  41. Acknowledgements: • Collaborators: • Benjamin Greenbaum (Rutgers/IAS) • Raul Rabadan (Columbia) • Arnold Levine (IAS, CINJ) • Gyan Bhanot (Rutgers, CINJ) • Nina Bhardwaj (NYU) • Olivier Manches (NYU) • Sonja Jimenez-Baranda (NYU) • Jesse Bloom (CalTech)

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