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Antigenic variation in malaria involves a highly structured switching pattern

Antigenic variation in malaria involves a highly structured switching pattern. Mario Recker Department of Zoology, University of Oxford. Mathematical approach to (understand) malaria.

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Antigenic variation in malaria involves a highly structured switching pattern

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  1. Antigenic variation in malaria involves a highly structured switching pattern Mario ReckerDepartment of Zoology, University of Oxford

  2. Mathematical approach to (understand) malaria “the mathematical method of treatment is really nothing but the application of careful reasoning to the problems at issue.”Ross R, 1911. The Prevention of Malaria . London: John Murray. Sir Ronald Ross 20. Aug. 1897 ??? ? ? Macdonald G, 1957. The Epidemiology and Control of Malaria from McKenzie & Samba, AJTMH 2004

  3. circumsporozoite protein (CSP) diversity merozoite surface proteins (MSP) variant surface antigens (VSA) Major multigene families: • rif > 150 copies per genome • stevor 30 copies per genome • Pfmc-2TM 13 copies per genome • var 60 copies per genome Scherf et al., Annu Rev Microbiol 2008 Most targets of protective immunity polymorphic surface proteins Development of immunity / effective vaccines hindered by extensive antigenic diversity: - mutation / recombination (genotypic change) - antigenic variation (no genotypic change) www.fda.gov/CbER/blood/malaria071206sk5.gif

  4. Sequence diversity of var genes is immense! adapted from Gardner, M. et al., 2002, Kyes, S. et al., 2002 cumulative diversity of DBLa seqnuences pairwise sharing among DBLa seqnuences from Barry et al, PLoS Pathog. 2007

  5. Antigenic variation in P.falciparum • PfEMP1(P. falciparumErythrocyte Membrane Protein 1) • embedded on surface of red cell • causes severe disease through adherence to host cell receptors • important immune target IE binding to endothelium IE binding to erythrocytes IE binding to dendritic cell EM by D. Ferguson, Oxford Univ.

  6. Infected blood cells sequester in tissue capillaries EM by D. Ferguson, Oxford Univ.

  7. (Molecular) Requirement for antigenic variation - every var gene recognised as part of a family - mechanism to limit expression to a single copy - activation coinciding with silencing of previously active gene - cellular memory to avoid ‘early’ repertoire exhaustion Result: succeeding waves of parasitaemia dominated by a single variant of PfEMP1 Scherf et al., Annu Rev Microbiol 2008 PfSir2: P.falciparum silent information regulator TPE: telomere position effect what orchestrates expression at population level?

  8. What orchestrates sequential dominance? - use mathematical models to create and test hypotheses - For example: • differences in growth rates or probabilities in switch rates(e.g. Kosinski, 1980) • differences in growth rates or probabilities in switch rates(e.g. Kosinski, 1980) • differences in growth rates or probabilities in switch rates(e.g. Kosinski, 1980) • differences in growth rates or probabilities in switch rates(e.g. Kosinski, 1980) • differential susceptibilities assigned to variants expressing two surface proteins (e.g. Agur et al., 1989) • differential susceptibilities assigned to variants expressing two surface proteins (e.g. Agur et al., 1989) • differential susceptibilities assigned to variants expressing two surface proteins (e.g. Agur et al., 1989) • differential susceptibilities assigned to variants expressing two surface proteins (e.g. Agur et al., 1989) • modifications of switch rates by ‘natural selection’(Frank, 1999) • modifications of switch rates by ‘natural selection’(Frank, 1999) • modifications of switch rates by ‘natural selection’(Frank, 1999) • immunological interaction, e.g. cross-immunity(e.g. Recker et al, 2004) • immunological interaction, e.g. cross-immunity(e.g. Recker et al, 2004)

  9. 60 50 55 50 40 30 20 10 0 60 58 18 50 40 30 20 10 0 Increases in levels of antibodies to VSA expressed by heterologous isolates are transient and limited. Agglutinating antibody titer Percentage of infected red cells positive time after infection

  10. Model assumption: each variant comprises a unique major epitope which elicits variant specific, long-lived immune response a number of minor epitopes which elicits transient, cross-reactive immune response

  11. The model dynamics of variant i: intrinsic growth rate clearance by specific response clearance by cross-reactive response dynamics of specific response zi: immune response proportional to antigen decay rate m’>>m dynamics of transient, cross-reactive response, wi: transient immune response proportional to antigen variants with shared epitopes

  12. Mathematical model without switching Recker et al, Nature 2004 Model suggested that parasite-host relationship has evolved to favour some short-lived immune responses that allow the parasite to persist and the host to survive

  13. var 1 Abundance var 2 var 3 time In vitro switching dynamics • Horrocks et al. (PNAS, 2004) showed • on and offrates for a given variant are dissimilar • on and offratesvary dramatically among different variants - rates appear to be intrinsic property of a particular gene - → could introduce a hierarchy of expression whereby stable variants are more prominently expressed, at least during the early phases of infection?

  14. To investigate the nature of var gene switching, generate transcription profiles for the entire repertoire in clonal parasite populations and measure the change in that profile over time stable dominance of initial variant 1st generation 2nd generation initial variant replaced

  15. change over generations determined by:

  16. - use mathematical model to determine most likely switching pathway - off rate switch bias on rate use iterative approach to find ‘best-fit’ switch matrix and off-rate vector

  17. Switch matrix: Switch sequence: 1→2 → 4 → 3 →

  18. Clone 3D7_AS2

  19. Clone It_B2B

  20. even for a stable clone…

  21. Clone B10 Clone B12 Data provided by Dzwikowski, Frank & Deitsch

  22. To test the validity of this prediction, examine the var transcript distribution in Clone 2 every few generations

  23. Evolutionary conflict: protection of repertoire vs. protection against immune attack repertoire protection: immune evasion:

  24. Evolutionary conflict: protection of repertoire vs. protection against immune attack Assume var gene repertoire as a network where - nodes = variants - edges = switch / transition probabilities Task: optimise network over two traits - pathlength (= repertoire protection) - robustness (= adaptability to selection pressure)

  25. Clone 3D7_AS2

  26. Clone It_B2B

  27. Investigate effects of hierarchical switching for in vivo dynamics

  28. naïve host highly structured switching results in (significantly?) increased length of infection.

  29. naïve host highly structured switching results in (significantly?) increased length of infection. semi-immune host sms and lattice-type pathways far more flexible in overcoming pressure from pre-existing immune responses to help set up chronic infections.

  30. Antigenic relationship between variants minor epitope 1 b c d e a u v x minor epitope 2 y z Switch sequence: (au) → (bu,av) → (cx) → (dx,cy) →…

  31. Summary • for pathogens with a limited antigenic pool, such as P. falciparum, tight control over variant expression is essential • tightly ordered gene activation requires every subsequent variant to be able to evade current immune responses and therefore may be compromised by previous infections • highly structured switching in P. falciparum has evolved as an evolutionary compromise between the protection of its limited antigenic repertoire and the flexibility to fully utilise this repertoire when needed

  32. Acknowledgements University of Oxford Department of Zoology • Sunetra Gupta • Caroline Buckee • Robert Noble • Sam Kinyanjui • Pete Bull • Kevin Marsh • Chris Newbold • Andrew Serazin • Sue Kyes • Zóe Christodoulou • Robert Pinches

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