1. 2 Host pathogen interaction and the evolution of Pandemic Flu This talk is mostly the work of a...

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Transcript of 1. 2 Host pathogen interaction and the evolution of Pandemic Flu This talk is mostly the work of a...

Page 1: 1. 2 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.

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Page 2: 1. 2 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.

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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

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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

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• 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.

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• 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

HOW DO WE DEAL WITH THEM?

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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)

• Elie Metchnikoff discovered that microorganisms could be engulfed and digested by phagocytic cells or macrophages (innate immune response)

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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.

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Immune cells derive from precursors in the bone marrow.

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Vaccination is the best way to control infectious diseases.• Diphtheria, polio, and

measles have been virtually eliminated in the US

• SSPE (subacute sclerosing Panencephalitis) 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.

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FLU “Phenotypes”

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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

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Replication of the Influenza A and B Viruses

1.1. Infection: HA binds to sialic Infection: HA binds to sialic acids of cell surface receptorsacids of cell surface receptors

2.2. Fusion with endosomal Fusion with endosomal membrane, release of virion membrane, release of virion contentcontent

3.3. Transcription of viral RNATranscription of viral RNA

4.4. Translation of viral proteinsTranslation of viral proteins

5.5. Formation of viral genome Formation of viral genome particles, transport of particles, transport of membrane proteins to cell membrane proteins to cell surfacesurface

6.6. Budding virion particlesBudding virion particles

7.7. Neuraminidase (NA) sheds Neuraminidase (NA) sheds sialic acids from cell surface sialic acids from cell surface and viral particle is releasedand viral particle is released

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Evolution of Viral Hemagglutinin in H5N1 & escaping immune response

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.

Homotrimer of HA1 and HA2 subunits

Most variation in HA1, in sialic acid receptor binding and antibody-binding sites

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FLU virus infects many hostsFLU virus infects many hosts

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Parsimony Tree showing viral evolution driven by positive selection (Fitch et al., PNAS 1997)

• ‘‘Cactus’-like phylogeny, 1 Cactus’-like phylogeny, 1 surviving lineagesurviving lineage

• Non-silent (replacement) Non-silent (replacement) mutations occur more often mutations occur more often in the (surviving) trunk in the (surviving) trunk branchesbranches

• Indicative of positive Indicative of positive Darwinian selectionDarwinian selection

• No significant region-specific No significant region-specific biases observedbiases observed

Most parsimonious gene tree for 254 influenza HA genes (subtype H3) from 1968-1997.

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Maximum Likelihood treeMaximum Likelihood treefor viral evolutionfor viral evolution

• Accumulating diversityAccumulating diversity Antigenic driftAntigenic drift

point mutationspoint mutations Antigenic shiftAntigenic shift - -

segment exchange between virusessegment exchange between viruses

• Variant fixationVariant fixation Immune-driven Immune-driven positive selectionpositive selection Genetic Genetic drift drift --

population bottlenecks, population bottlenecks,

founder effectsfounder effects

‘Cactus-like’ ML tree of HA1 nucleotide sequences from H3N2 influenza A viruses. (From Smith et al., Science 2004.

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Pandemic strains result from “Antigenic Shift”Pandemic strains result from “Antigenic Shift”

From: Belshe, N Engl J Med, 2005.

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

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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

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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 (CU), 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

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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? 29

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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)

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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

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Look for Patterns• Counts words to determine probabilities

• Statistic:

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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?

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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

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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)

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CpG Evolution of H1N1

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Evolution of # of CpGs

Evolution of the fraction of CG Arginine (CGN) codons (compared to CGN, AGA, AGG)

Evolution of η

Evolution of ρ

Evolution of CpG in H1N1 using various measures

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Evolution of CpG in Influenza B

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“Protected” CpGs “Exposed” CpGs

Evolution of CG is Context Dependent

(C/G)CG(C/G) (A/U)CG(A/U)

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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).

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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

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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

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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

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TLR7 and TLR8 respond to RNA viruses such as influenza viruses and HIV

• 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).

RNA/DNA viruses

RNA/DNA viruses

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Analyze pDC cells in mouse

Public gene expression data from Iparraguire et al:

Stimulated Mice at1 and 4 hrs with Flu andCpG DNA agonists

High IFNA Producer

Express TLR7/9

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

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IFN-α production after pDCs stimulation

A successful host antiviral defense depends largely on rapidand robust IFN-α production

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Modified Influenza viruses with Low CpG/High CpGInduce differential production of IFN-α

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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

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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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Gene expression levels of highly expressed genes to control expression levels vs. CpG frequency

Gene expression levels of highly expressed genes to control expression levels vs. ApT frequency

Dinucleotide Frequency vs. Gene Expression for Flu stimulated pDC cells

Highly expressed genes have low CpG frequency provides the immune system with a marker to distinguish self/non-self

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CpG motifs in RNA sequences influence NK cell activation through pDCs.

• NK cells incubated with V1-1U-CpG/GpC, V1-2U-CpG/GpC, and V1-4U-CpG/GpC in the presence or absence of pDCs (10:1 ratio of NK cells to pDC)

• We observed that coculture of NK cells with IFN-α-producing pDCs (i.e., CpG RNA-stimulated pDCs) increased CD69 levels on the NK cell surface (Fig. 4A) and induced high levels of IFN-γ

• The activation was completely abrogated when all U’s were replaced with A’s and was dependent on the U’s around the CpG dinucleotide

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Possible Functional Consequences

• IFNA should imply NK

• One possible high cytokine downside

• NK should imply IFN

• 1U, 2U show differences at smaller scale

NK Cells

0

5

10

15

20

25

30

35

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45

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1U C

pG

1U G

pC

2U C

pG

2U G

pC

4U C

pG

4U G

pC

Sequence Type

%C

D 6

9

IFN Gamma MFl

0

200

400

600

800

1000

1200

4U C

pG

4U G

pC

Sequence Type

IFN

Gam

ma

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Segment to Segment Communications

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Influenza Segment

Sha

nnon

Ent

ropy

per

Seg

men

t

Entropy per Segment in 50-50 Experiments

• Shows how well equal sample concentration is maintained

•Low Entropy implies segment will be “difficult to talk to”

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-log10(p-value)

Mut

ual I

nfor

mat

ion

Bet

wee

n S

egm

ents

Mutual Information Between Segments

• Permutation Test for Significant Associations

• Generalizable to 3-point correlations, with care

• Measure of “Magnitude of Transfer”

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Significant Associations

Maximum Possible MI

Sig

nific

ant M

I Val

ues

• Greatest Magnitude was in Duck-Human Reassortant – Segs 4&7

•Used for Other Segmented Viruses, Reoviruses in this case

•Sufficient experiments could give “channel capacity” of cell-type

Page 59: 1. 2 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.

Implications

• Surveillance: One can test co-circulating strains for potentially dominant pairings

• Early emergence: One can test for dominance of emergent vs. seasonal strains for balance in vaccinations

• Fundamental: Linking of dominant strains to epitopes, host biology, cell-type, etc.

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Is this reflected in genes across species?

IL-6 has largest change of all genes, followed by IFNA and IL1 family

The lowest 10% CpG are random in chicken with 3x the frequency - swine genome coming…

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Stimulated Genes ssRNA Viruses CGAA 0.4306 CGAT 0.5402 TCGA 0.4498 CGAA 0.5422 CGAT 0.4671 TTCG 0.5478 GTCG 0.4695 ACGA 0.5479 CGTA 0.4699 TCGA 0.5488 GCGA 0.4813 GACG 0.5639 TACG 0.5111 TACG 0.5834 CGAC 0.5147 TCGT 0.5958 ACGA 0.5242 GTCG 0.6004 CCGA 0.544 ATCG 0.6066

• Overlap at 2-, 4-, and 8-fold level of expression

• Strong overlap in underrepresented motifs• Self-consistent, significant method• Allows creation of testable oligomers, with

noise

Specificity Specificity Predictability Predictability

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Anti-viral drugs

Neuraminidase inhibitors Oseltamivir (Tamiflu), Zanamivir (Relenza) Oseltamivir (Tamiflu), Zanamivir (Relenza) Inhibit NA, prevents virus from spreadingInhibit NA, prevents virus from spreading Effective against Influenza A and BEffective against Influenza A and B Resistant viruses mostly not able to transmit wellResistant viruses mostly not able to transmit well

M2 inhibitors (adamantanes) Amantadine, RimantadineAmantadine, Rimantadine

Block viral ion channel, prevents virus from infecting cellsBlock viral ion channel, prevents virus from infecting cells Effective only against Influenza A, increasing resistance Effective only against Influenza A, increasing resistance

observedobserved

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Epidemiology

• Seasonal epidemicSeasonal epidemic Surge in infection after antigenic drift to novel Surge in infection after antigenic drift to novel

phenotypephenotype

• PandemicsPandemics 1918 Spanish flu (H1N1): Avian strain1918 Spanish flu (H1N1): Avian strain 1957 Asian flu (H2N1), 1968 Hong Kong flu (H3N2): 1957 Asian flu (H2N1), 1968 Hong Kong flu (H3N2):

Cross-species segment reassortmentCross-species segment reassortment Threat of H5N1-related pandemicThreat of H5N1-related pandemic Recent Pandemic Flu H1N1 (2009)Recent Pandemic Flu H1N1 (2009)

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• Genetic studies: Genetic studies: Phylogenetic trees, Phylogenetic trees, clustering, determining genetic indicators of clustering, determining genetic indicators of strain fitness...strain fitness...

• Linking genotype to (antigenic) Linking genotype to (antigenic) phenotypephenotype

• Studies of phylogeographyStudies of phylogeography: Regional : Regional spread and diffusion of viral strainsspread and diffusion of viral strains

• Epidemiological modeling usingEpidemiological modeling using simulationssimulations

Computational studies of influenza evolutionComputational studies of influenza evolution

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Genetic composition and structureGenetic composition and structure

• GenomeGenome RNA virusRNA virus 8 segments, 11 proteins8 segments, 11 proteins PB1

PB2PAHANPNAM

NS

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Innate Immune Hypothesis:• As 1918 H1N1 and avian H5N1 have more CpGs they create a higher

immune response, increasing damage and secondary infection• H5N1 have stronger immune response than recent H1N1 in vitro (Cheung et

al, Lancet. 2002, Chan MC et al, Respir Res. 2005)• DNA viruses are recognized by TLR9 as unmethylated CpG DNA, TLR9 is

deleted in birds.• Motifs in ssRNA viruses recognized by TLR7 are not known

from CDC

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Recent History

• Ray Owen (1940s) : genetically different twin calves with a common placenta were immunologically tolerant of one another's tissues.

• Peter Medawar (1953): If exposed to foreign tissues during embryonic development, mice become immunologically tolerant to these tissues.

• Burnet proposed that: potentially self-reactive lymphocytes are removed before they can mature (clonal deletion). He has since been proved right but the mechanisms of tolerance are still unclear.

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CG in FLU in other species

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Page 69: 1. 2 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.

1898: Loeffler & Frosch showed that infectious agent in foot-and-mouth disease in cattle was smaller than any bacterium. It was a VIRUS

Viruses exist in a grey area between living and non-living states. They can only replicate in host cells.

Outside host cells, a virus is metabolically inert and has a protein coat (capsid) enclosing DNA or RNA.

Replication: •Virus bind to a host cell and inserts its genetic material.•Infected cell is made to produce viral protein and genetic material •Viral particles are assembled and released to infect new cells. •This proceeds until the host dies or gets rid of the virus.

•Some viruses (chickenpox, herpes) remain dormant in host cells after infection and can reemerge many years later.

Page 70: 1. 2 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.

Context dependence of CpG motif frequency in H1N1 evolution

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